-------

-------
                  the pri/ate sector in
              solid n/aste management
            A Profile of its Resources  and Contribution
                    to Collection and  Disposal

                    Volume 1, Executive Summary
                    Volume 2, Analysis of Data
             This report (SW-51d.l) on work performed
under Federal solid waste management demonstration grant no. D01-U1-00247
          to the National Solid Waste Management Association,
           was prepared by APPLIED MANAGEMENT SCIENCES, INC.
           and is reproduced as received from the grantee
               U.S. ENVIRONMENTAL PROTECTION AGENCY
                             1973

-------
This report has been reviewed by the U.S. Environmental Protection
      Agency and approved for publication.  Approval does not
      signify that the contents necessarily reflect the views
   and policies of the U.S. Environmental Protection Agency, nor
    does mention of commercial products constitute endorsement
         or recommendation for use by the U.S. Government
                        2d Printing
                            1974
               (with new cover1 and title page)
        An environmental protection publication  (SW-51d.l)
               in  the solid waste management  series

-------
                              INTRODUCTION

      The private sector in the field of solid waste management has, until
this time,  never been quantitatively described in terms of its structure,
scope, and contribution to the resolution of the nation's collection problems.
This study provides that description on an authoritative basis.   It focuses
on the private sector contractor involved in the collection of solid wastes
from residential, commercial, and industrial  sources.
      The need to more fully understand the role of the private contractor
was,  in great measure, stimulated by the  current concern for the environ-
ment.  In response to this need, the Office of Solid Waste Management
Programs  (OSWMP) of the Environmental  Protection Agency (EPA)  in June
of 1969 provided a grant to the National Solid Wastes Management Association
(NSWMA) for the purpose of surveying private  solid wastes  contractors
throughout the nation to profile their organizations and activities, and to
statistically analyze and report the data to provide a basis for policy-
oriented decision making.
      This study, completed for NSWMA by the principals and staff  of
Applied Management Sciences, concerns the resources and  contribution of
the private sector.  Resources can,  in this context, be described as the
men and equipment involved in the private contractor sector.  Contribution
is,  in its simplest terms, the "share" of the residential,  commercial, and
industrial market served by private contractors.
                                   111

-------
      The description and analysis of "resources and contribution" are the
major issues addressed.  These are, in fact, made up of a series of sub-
issues.  Within the framework of "resources" consideration is in the num-
ber and types of trucks and men;  sub-issues extend to measurements of
utilization and  relative efficiency and how these characteristics are  affected
by size,  customer type, contractual relationships, etc.  "Contribution" is
essentially a description of what the private sector collects, how much
they collect, and from whom.  The study results relate the proportion of
the market served and the gross output of the private sector.  Contribution
also considers issues such as  type and quality of service.
      This study is based on the completion of 2014 personal interviews
•with private contractors throughout the nation.  Of those interviews,  1000
were drawn using a two-stage  cluster sample and are projectable within
reasonable limits  to national total.   Most of this report is based on those
1000 interviews.  The balance of  the interviews are supportive in nature
and will be used for future research.
      This report is presented in three volumes.  This,  the initial volume,
briefly summarizes the results.  Volume 2 is more extensive and provides
a description of the methods used in Chapter 2, and in Chapters 3-7, analyzes
the data in detail.  Volume 3 contains the base tables from which all analysis
has been drawn.
      This study,  for the first time, provides an authoritative description
of the private sector  contractor involved in the collection of solid wastes
from residential,  commercial, and industrial sources.   No comprehensive
national information previously existed depicting this industry in gross
terms or in specific characteristics. Fulfillment of the  description of the
private sector  of this industry is  the primary objective of this large-scale
undertaking. Review of all study data reveals a dynamic and changing in-
dustry which is larger, more vigorous, and making a significantly more
important contribution to the solid waste management collection and  disposal
system than previously assumed.
                                    IV

-------
THE PRIVATE SECTOR IN SOLID WASTE MANAGEMENT
 A Profile of its Resources and Contribution
          to Collection and Disposal
          Volume 1, Executive Summary

-------

-------
                            CONTENTS
                                                                 PAGE
CHAPTER                                                       	


  1         SUMMARY AND HIGHLIGHTS	   1.1

               Figure 1.1: Fleet. Composition of Average
                 Contractor >	   1.2

               Figure 1.2: Trends in Operation of Total Packer
                 and Non-Packer Trucks in the Private Sector    1. 3

               Table 1. 1: National Estimate  of Total Trucks      1.4

               Table 1.2: National Estimate  of Trends in
                 Operation of Packer and Non-Packer Trucks
                 in the Private Sector	   1.4

               Table 1.3: National Estimate  of Specialized
                 Equipment Serviced by the Private Sector. .  .   1. 5

               Table 104: Percent of Total Equipment Oper-
                 ated by Percent of Total Trucks  (38%) in
                 10-49 Truck Operations  ....„„	   1.6

               Figure 1.  3: Distribution of Mix of Tonnage
                 Collected Within Contractor Size Categories   .   1.7

               Table 1.5: Tonnage Shares by Customer Types.   1. 10

               Table 1.6: National Estimate-Per  Capita Genera-
                 tion of Residential, Commercial, and Industrial
                 Refuse	    1.10
               Figure 1.4; Distribution of Contractors Among
                 Customer Types	„  .    1. 11

               Table 1.7: Year of Company Origin in Present
                 Form	    1. 11

               Table 1.8: National Estimate of Customers Ser-
                 viced by the Private Sector Under Direct
                 Contract and Government Franchise „  .  .  .  .    1.12

               Table 1<,9: National Estimate of Customers Ser-
                 viced by the Private Sector Under Direct Con-
                 tract and Government Franchise by Size of
                 Contractor	    1.13
                                    Vtl

-------
                            CONTENTS


CHAPTER                                                       PAGE
             Table 1. 10: Size of Contractor Indicators by
               Type of Wastes Collected in Private Sector. . .     1. 14

              Table 1. 11: National Estimate - Share of Popu-
               lation Served by Private Sector	     1.15

             Figure 1. 5: Fleet Configuration by Collection
               Mix	     1.17

             Table 1.12: Percent Distribution of Tonnage by
               Number of Tons Per Day in the Private Sector.     1.18

             Table 1. 13: Percent Distribution of Tonnage by
               Contractor Size in the Private Sector	     1.18
                                  vm

-------
                         SUMMARY AND HIGHLIGHTS

      The private sector of solid waste management represents a significant
portion of the total field in terms of its resources and its contribution to the
collection process.  There are approximately 10,000 firms operating 62,000
vehicles and employing 102,000 persons.  In residential collection,  the
private sector serves approximately 109 million people in 35 million housing
units.  Over 90 percent of the commercial/industrial wastes are handled by
private contractors.  The private sector collects, through either direct
customer contracting or government franchising or contracting,  73  percent
of the nation's estimated total solid waste tonnage.
      This industry is characteristic of most other large industries in the
nation; a relatively small number of organizations hold a major portion of
the market.  Generally, 15  percent of the companies  (1500) collect about
75 percent of the tonnage, serve 62 percent of the customers, and operate
about one-half of the total vehicles in the industry.  These contractors oper-
ate highly mechanized collection equipment and have the highest utilization
or efficiency as  measured by the ratios  of tons per truck or tons per man
crew.  The 5700  operators of less  than 3 or fewer trucks affect waste col-
lection to a lesser degree, since they serve only  10 percent of the customers
and collect a similar proportion of the total tonnage.
      To a very large extent, private contractors operate packer trucks and
special collection vehicles.   Less than 15 percent of the vehicles presently
operated by full-time contractors are open non-packer-type trucks.
                                     1.1

-------
      This summary describes the resources and contribution of the private
sector in terms of the equipment, manpower, customers  served,  and tonnage
of wastes handled.

RESOURCES OF THE PRIVATE SECTOR
      The 62,000 vehicles operated by private contractors are distributed
among three basic types.   Figure 1. 1 illustrates the average fleet composi-
tion as being two-thirds packer vehicles,  one-fifth special collection
vehicles, and the balance open non  packers.  Trend data  in the survey shows
a rapid growth in fleet size between 1965 and 1970 in terms of the total
mimber of trucks, and also the number of packer type trucks.
                                 SpccUl Collection*
                                   Vehicle!
                •roll-off chauif, hoi it type vehicle §, tatellite vehicle*. etc,,
                  FIGURE i.i: FLEET COMPOSITION OF AVERAGE CONTRACTOR
      The distribution  01 all vehicles in tV\ •>. inc.Uotry rsfl etc the ;.rD\vt" .-£
packers and certain  special vehicles, and a decline in the number of open
non-packer trucks.
                                      1.2

-------
 O

 k.



H-
 o
\
\
\
\
\
1






















\



^
\
\
t\
£\
^v
-o
ca
i














^
\
\
\
\
\
\
\



\

«J
O-\
\
\

\
\
\
\















\
\
\
\
o.\
\





\
\
\
\
\
\
\
\












\
\
\


\
\
\
\
\
\
\
1






1



















\
\
\
\
\ 1
1
1
1
1 1




1
£
     (j




                                                                                     h


                                                                                     UJ


                                                                                     U


                                                                                     CL
                                                                                        D


                                                                                        <



                                                                                        UJ


                                                                                        U


                                                                                        CL
                                                                              (O
                                                                              CD
in
                 o
                 o
                 CD

                 o"
                 •st
                                      O
                                      o
                                      o
                                      o"
                                      ro
o  o

§  i

o  o
CM  r-
                                                                              CO
                                                                              05
                                                                                     h-
                                                                                     o

                                                                                     LL
                                                                                     oa:


                                                                                        g
                                                                                     i- ij-i
                                                                                     < ^

                                                                                     UJ [_
                                                                                     Q UJ
                                                                                     UJ
                                                                                     a:
                                                                                     Z)
                                                                                     o

                                                                                     LL
                           1.3

-------
                                   TABLE 1.1
                         NATIONAL ESTIMATE OF TOTAL TRUCKS
Type of Truck
Total Trucks
Packers
Rear Loaders
Front Loaders
Side Loaders
Non Packers
Open
Side Loaders
Special Collection Vehicles
Roll-off Chassis
Hoist Type Vehicles
Satellite Vehicles
Other Collection Vehicles
Number of
Trucks
61,648
41,602
26,230
7,670
7,702
7,327
7,244
83
12,736
6,496
2,206
2,315
1,719
Percent of
Total Trucks
100. 0%
67.5%
42. 5%
12.4%
12. 5%
1 1 . 9%
1 1 . 8%
0. 1%
20. 7%
10. 5%
3.6%
3.8%
2. 8%
Among the packer vehicles,  rear loaders account for two-thirds,  with front
loaders and  side loaders  sharing the balance.  Approximately one-half of the
special vehicles are roll-off chassis.
                                 TABLE 1.2
                 NATIONAL ESTIMATE OF TRENDS IN OPERATION OF PACKER
                   AND NON PACKER TRUCKS IN THE PRIVATE SECTOR

1965
1968
Percent Change
1965 to 1968
1970
Percent Change
1968 to 1970
Percent Change
1965 to 1970
Packers
Number Percent
22,739 72.1%
31.843 79.4%
+40.0%
41,602 85.0%
+30.6%
+83. 0%
Type of Truck
Total Packers and
Non Packers Non Packers
Number Percent Number Percent
8,784 27.9% 31,523 100%
8,308 20.7% 40,151 100%
-5.4% +27.4%
7,327 15.0% 48,929 100%
-11.7% +21.9%
-16.1% +55.2%
To complete the description of equipment,  one must consider the various
types of specialized equipment serviced by the private sector.
                                      1.4

-------
                                     TABLE 1.3
                         NATIONAL ESTIMATE OF SPECIALIZED EQUIPMENT
                             SERVICED BY THE PRIVATE SECTOR
Type of
Roll-off
Roll- off
!Rat,o
Equipment
Bodies
Chaf
of Bo
>sis
dies to Chassis)
Total
Number
109
6

,151
,494
16.8
Number
Who
2,
2,

of Contractors
Service
084
084

Percent of Contractors
Who Service
20
20

.8%
.8%

Mean Number
Per Contractors
52,
3

.4
.1




      Stationary Containers       1,783,876
      Specially Designed Stationary
      Containers *              20,812
      Stationary Compactors        20.479
6,156

 656
1,713
61.4%

 6.5%
17.1%
Z89. 8

 31.7
 12.0
      * Includes sludge containers, acid containers, rubber or plastic lined containers, etc.

While no trend data are available, the less formal evidence assembled by the
Applied  Management Sciences'  study team, and supported by NSWMA staff
and members, indicates that a  rapid growth has occurred in the number of
units of  specialized equipment (roll-off bodies,  stationary  containers,  sta-
tionary compactors, and special containers)  over the past  five to  ten years.
CONTRACTOR SIZE
      The 10,000 contractors operating in the nation are primarily 1-3 truck
organizations.  About  one-fourth of  the companies operate 4-9 trucks, and
15 percent have over 10 trucks.  The 1500 largest companies operate 6 out
of 10 trucks and collect from approximately 7 of 1 0 customers served  by the
private sector.  While there are large numbers of small.companies, they
operate  fewer trucks (16% of 62,000) and collect  proportionately  fewer
customers.
      Contractor  size is a  direct  result  of the tonnage collected  and
customers served in terms of both types and  quantities.  The type  of truck
operated is, to a large extent,  determined by  the type  of waste  collected.
For  example,  contractors collecting a large  percentage of commercial and
industrial wastes operate proportionately more front-end loaders  and  roll-
off units.
                                      1.5

-------
      Medium size companies  (10 to 19 trucks) operated the more
sophisticated equipment to  a level above our initial expectations (Table 1.4).
                                    TABLE l.H:
                     PERCENT OF TOTAL EQUIPMENT OPERATED BY PERCENT OF
                       TOTAL TRUCKS (381) IN 10-49 TRUCK OPERATIONS
% of Total Equipment
Operated by Type
Rear Loaders
Front Loaders
Side Loaders
Roll-off Chassis
Hoist type Vehicles
32%
45
55
48
56
                     Roll-off Boches                     38
                     Stationary Containers                 49
                     Specially designed Stationary Containers    78
                     Stationary Compactors                53
      Larger firms (50 trucks or more)  own  an average of 82 vehicles.   They
have a significantly different vehicle mix than mid-sized firms.  The large
firms have a  greater  proportion of rear loaders, which typically have 50
percent less capacity than the front or side loaders.  This limits the capacity
of the large operator  disproportionately when compared to the front-loader
oriented mid-sized operator.   The large operator has, of course,  adjusted
his fleet to his mix of customers.  His heavy orientation to residential
collection prescribes rear loaders as the most  efficient mechanism  for
collection.
      In terms of special collection equipment,  the  large contractor is
oriented toward a highly effective use of roll-off chassis and bodies.  While
owning  only 17 percent of the  roll-off chassis, these contractors service
41 percent of the roll-off bodies in the private sector. This is supported
by a small proportion of commercial and industrial customers,  with heavy
tonnage attributed  to  each customer.  This is also related to demolition and
construction waste collection  operators, where roll-off bodies are fre-
quently used for longer term on-site storage.
                                     1. 6

-------
in-
in
         H
         Eis&l
         vm
in
CM
                1

                                   V.*.'.1

                                                      s

                                                         -LO
                                                          r»
                                                                           X
                                                                           Ul
                                                                           I
                                                                           _i
                                                                           <
                                                                    S<     v>
                                                                   -O     3
                                                                    LO     Q
                                                          -in
                                                           CM
                                                                 <
                                                                 0
                                                                 oc
                                                                 Ul
                                                                 5

                                                                 o
                                                                 u
                                                                                        Q
                                                                                        LLJ
                                                                                        H
                                                                                        u
                                                                                        LU
                                                                              O LU
                                                                              °E
                                                                              LJJ o
                                                                              00
                                                                              < ai
                                                                              ZH
                                                                              z <
                                                                              o o
                                                                              "-UJ
                                                                              U_ M
                                                                              OJ71
                                                                                        CO
                                                                                        LU
                                                                                        Qi
                                                                                        z>
                                                                                        o
   o
   D
   DC


CC LU
          LO
                  6oc
                  CM h-
                              C/J
   Cfl
   ^
   o
   D
O) CC
CO K
                                           LO
                                              0
                                              D
   O
   D
CO CC
CM t-
o

CC
                                 1.7

-------
      Small contractors,  particularly in the 1-3 truck size, represent, for
the most part,  the individual family business.  The statistics reveal these
companies to be primarily proprietorships. The small contractor is some-
what more oriented toward the open truck and less oriented toward the
specialized collection vehicle.  By virtue  of his limited capacity, he is more
acutely residential and  small commercial.  Some 46 percent of the single
truck operators are  exclusively residential; nonetheless, 54 percent of the
single truck operators utilize packer trucks.
MANPOWER UTILIZATION
      One of the most interesting findings of this study relates to the crew
size used by private contractors in vehicle operations. The average crew
size for all vehicle types is 1. 59 men per truck, ranging from 1.19 men
per truck for front loaders to 1. 99 men per truck for rear loaders.   Crew
size averages exclude special collection vehicles which are generally de-
signed to  operate with a one-man crew. Among the total of 102, 000
employees, 73.7 percent or  75,000 are directly utilized on the route, leaving
the balance as overhead personnel.
      A key consideration in examining the number and proportion of collec-
tion employees per company is the contractor's mix of collection.  As the
contractor's tonnage  (and, therefore,  his  customers) tend  to become more
commercial and industrial, his net number of men per truck reduces.  This
condition  is, of course,  a function of the more mechanized equipment used
in servicing commercial  and industrial accounts.
      Since the largest  contractors (50 trucks or more), as measured by
fleet size, are most heavily involved in residential  collection, their fleets
tend to contain a high percentage of rear  loaders.  The larger crew size
required on rear loaders,- as compared with front loaders  and roll-off
vehicles,  results in  a slight  increase  in the average crew size per truck
as contractor  size increases.
      In total, approximately two-thirds of all private sector personnel are
in the  employ of the  larger organizations which constitute 15 percent of all
                                     1. 8

-------
companies.  Due to the types of wastes collected, employees of these
organizations tend to operate more mechanized and specialized types of
vehicles and, as a result, yield a higher tonnage per employee per truck
than personnel of other smaller contractors.
CONTRIBUTION OF THE PRIVATE SECTOR
      An assessment of the contribution of the private contractor must be
determined on the basis of the types of wastes collected, tonnages collected,
and the customer population served.  The customer population is described
by residential (single and two to four family housing units) customers,
commercial customers (including apartments of five or more  units), and
industrial  customers.  The quantity of waste collected is analyzed by both
the proportions  of the population served and the tonnage collected.  What
the private sector collects is rather broad.   Private contractors  collect
all forms of wastes on a  regular basis.  Their type of customer dictates
the type of waste they collect.
      In total, the private sector collects 73  percent of the solid waste
tonnage generated daily in the nation, while serving 51  percent of the
residential units and 91 and 94 percent of the  commercial and  industrial
customers, respectively. Merging apartment units into the residential
framework,  108 million people  residing in 35 million housing units are
collected weekly.  Almost half of the residential group  is served  by the
private sector under some form of government contract or franchise.
      Total collection tonnage handled by the private sector equals 685. 5
thousand tons daily.  Per capita waste is 8. 6 pounds exclusive of agriculture,
demolition, and construction wastes.  The per capita distribution is 3.9
pounds residential,  2.5 commercial, and 2.2 industrial waste  daily.  Less
than 10 percent of the  private sector customers are commercial and industrial
establishments,  yet, as expected,  they account for 65 percent of  the tonnage
collected.
                                     1.9

-------
                                    TABLE 1 5:
                          TONNAGE SHARES BY CUSTOMER TYPES
Typo of Customer
Residential
Commercial
Indu stnal
Percent of total
No. of Customers
90. 3%
8. 3
1. 3
Daily Share
of Tons
ZJ . 9%
33.7
31 . 3
                                    TABLE 1.6
                      NATIONAL ESTIMATE - PER CAPITA GENERATION OF
                     RESIDENTIAL. COMMERCIAL. AND INDUSTRIAL REFUSE
                                    Total*    Residential    Commercial    Industrial
Residential, Commercial, and Industrial
Tons Collected by Private Sector on
Average Day
Share of Residential, Commercial, and Industrial
Customers Collected Nationally
Residential, Commercial, and Industrial
Tons Collected Nationally on Average Day
Perceril of Total Tonnage
Nation.U 1970** Population
Refuse per Person Per Day


644.



511.

52.4%

878.
73
ZOJ.Z11,


581
.3%
OZ6
8.6


199, 132

50.2%

396,677
50. 2%

3.9


230,865 214,514

91.0% 94.0%

253,698 228,206
91.0% 94.0%

2.5 2.2
 * Total does not include demolition and construction refuse, or other refuse.
** From 1970 Census
THE PRIVATE SOLID WASTE CONTRACTOR
      While over half of the solid waste contractors collect all forms of
waste,  a significant portion are exclusively involved in the collection of
commercial and industrial wastes only.  Figure 1. 4  on the following page
illustrates  the total distribution of contractors  among customer types.
Merging the generalist and specialist contractors,  96 percent collect com-
mercial and industrial waste and 59 percent residential waste.
      In terms of business structure,  most firms in the industry are pro-
prietorships.  This structure is most prevalent among contractors operating
less  than 5 trucks and collecting  less than  50 tons per day.  Firms above
this level are more likely to be incorporated with at least 75 to 80 percent of
the larger  firms choosing this form of organization.
                                       1. 10

-------
                     100% Commercial
                     and Industrial
                                          Residential, Commc rcial
                                          and Industi ial
                          X
                100% Residential - 3.7%
                  FIGURE 1.4:
DISTRIBUTION OF CONTRACTORS AMONG
CUSTOMER TYPES
      As would be expected, the larger contractor is significantly older than
the 13. 9 year norm for business operations in the industry.  The largest
operators have typically operated in their present business form for almost
24 years.  Among those contractors whose operations are exclusively resi-
dential, almost 1 in 7 began their  present business operations during the
eighteen-month period from the beginning of 1970 to mid-1971.  This com-
pares to an industry norm of 1  in  20 new establishments during the same
time frame.
                                   TABLE 1.7
                       YEAR OF COMPANY ORIGIN IN PRESENT FORM
Year Started
1970-71
1965-69
1960-64
1950-59
1940-49
Before 1940
Don't know
Total
594
2,729
2.066
2,574
1,171
831
61
Percent
5.9%
27.2
20.6
25. 7
11.7
8. 3
0.6
Cumulative
Percent
5.9%
33. 1
53.7
79.4
91. 1
99.4
100.0
                                      1.11

-------
      Among the major events occurring concurrent with this survey was

the apparently strong development of acquisition and/or merger activity

by and with firms  in  and out of the field  of solid waste management.  During

the course of the study, the Applied Management Sciences' field group

identified many private contractor organizations that were considering

merger or acquisition.  It is  the contention of Applied Management Sciences

that this development was in its initial stages at the time of this survey

and is  probably not fully accounted for in the study.

                                      TABLE 1.8
                NATIONAL ESTIMATE OF CUSTOMERS SERVICED BY THE PRIVATE SECTOR
                     UNDER DIRECT CONTRACT AND GOVERNMENT FRANCHISE
Tyrx* of Collodion
Residential Customers
Contract Direct
Government Franchise
Total Residential Customers
Commercial Customers
Contract Direct
Government Franchise
Total Commercial Customers
Number of
Customers
12,432,149
12,284,509*
24,716,758
1,990,083
285,445
i 2,275,528
Pnrr.ont of
Customers
50.37.
49.7V.
100.07.
87.27.
12.87.
100.0%
Numhor of
Contractors
4,906
1,738
5,883"
9,055
741
9,651**
Numlior of Customers
Per Contractor
2,534
7,068
4,201
220
385
236
    * The original estimate of Government franchise customers was 11,717,509 or 47.4 percent of
      all residential customers. The 2.3 percent of residential customers unaccounted for was the result
      of some responding contractors counting a government franchise as one customer arid reporting
      serving one customer under government franchise.

    ** The number of contractors who contract directly and have government franchises add to more than the
      total because some contractors operate under both direct contracting and government franchise systems.
       The  government contracting or franchising mechanism ic a common
mode of residential operations and a less significant one in commercial
collection.   While relatively few contractors are operating under government
contracts or franchises,  they do tend to be very large.  The  clear  majority
of the residential customers of 20 or more truck operators are government

contract or  franchise based.
                                         1. 12

-------
                                   TABLE 1.9
              PERCENT OF CUSTOMERS SERVICED BY THE PRIVATE SECTOR UNDER
                  DIRECT CONTRACT AND GOVERNMENT FRANCHISE WITHIN
                               CONTRACTOR SIZES
Type of Collection

Residential Customers
Direct Contract
Government
Franchise
Total Residential
Contractors
Commercial Customers
Direct Contract
Government
Frar.chis e
Total Commercial
Customers

1
truck

60%
40
100%

86%
14
100%

2-3
trucKs

61%
39
100%

96%
4
100%

4-5
trucks

83%
17
100%

98%
2
100%
Size of
6-9
trucks

66%
34
100%

91%
9
100%
Cont act r
10-19
trucks

52%
48
100%

88%
12
100%

20-49
trucks

26%
74
100%

75%
25
100%

50 or more
trucks

46%
54
100%

86%
14
100%

Total

50%
50
100%

87%
13
100%
Franchising of commercial and industrial customers appears to occur more
frequently where residential franchising occurs.  In this context,  it is evident
that the larger residentially oriented contractors who acquire the  major
government contracts often serve the bulk of the commercial and industrial
franchised customers.
      Residential contractors with government franchises are heavily con-
centrated in SMSA's over one million.  Among the 1853 residential contrac-
tors located in these areas, approximately half operate in whole or part
under some form of government contract franchise.  Four  regions,  the
North Atlantic, Mid-Atlantic, Mid-west,  and West, have the highest number
of customers  served and the largest proportion of contractors operating
under franchise conditions.
                                   1. 13

-------
CHARACTERISTICS OF THE COLLECTION FUNCTION

      All forms of wastes are collected by private contractors with the
larger organizations handling various unique types such as abandoned
vehicles,  dead animals, etc.
                                TABLE 1.10
               SIZE OF CONTRACTOR INDICATORS BY TYPE OF WASTES COLLECTED
                              IN PRIVATE SECTOR
Number of Contractors
Type oi Waste Who Collect
Rubbish
Garbage
Yard Refuse
Bulky Wastes
Ashes
Construction and Demolition
Wastes
Special Wastes
Dead Animals
Street Refuse
Animal and Agriculture
Wastes
Sewage Treatment Residues
Abandoned Vehicles
9,950
7,889
7,807
7,623
6,405
5,156
3,113
1,733
1 , 727
1,587
394
375
Percent of Contractors Mean Number
Who Collert ol Trucks
99.2%
78.7
77.9
76.0
63.9
51.4
31.0
17.3
17.2
15.8
3.9
3.6
6. 16
7.12
6.78
6.87
7.40
7.94
9.93
10.49
11.44
13.59
14.09
15.08
Mean Number
of Tons
Daily
72.29
81.26
76.82
81.17
88.17
102.94
152.02
127.69
146.98
183.55
239.85
220.19
Tons Per
Truck
11.4
11.4
11.3
11.8
11.9
13.0
15.3
12.2
12.9
13.5
17.0
14.6
       The bulk of contractors handle combined collection of residential,
 commercial, and industrial wastes.
 RESIDENTIAL COLLECTION
       Collection from single family households or multi-family dwellings
 of up to 4 units have been traditionally considered residential.  Apartments
 of 5 or more units have been identified as commercial customers.  To allow
 a complete perspective on residential waste and its collection, we have
 merged the  data into a residential framework only.  Within these guidelines,
 private collection contractors  service  35 million housing units and 109
 million people.
                                     1.14

-------
                                            TABLE 1.11
                            NATIONAL ESTIMATE - SHARE OF POPULATION SERVED BY
                                          PRIVATE SECTOR

Number of Private Contractors Who Collect
Percent of All Private Contractors (10,027)
Number of Customers Collected By Private
Sector
Estimated Number of Customers Nationally
Percent of Tol al Customerii Collected By
Private Sector
Number of Units Collected By Private Sector
Number of oc r-upied Units Nationally *
Percent of Total occupied Units Collected
By Private S«-< tor
Single Family
Homes
5,883
59%
23.348,933
46,075,691
51%
23,348,933
46,075,691
51%
Duplexes.
4 Units
4,284
43%
1,367.825
3,115,747
44%
4,103,475
9,347,242
44%
Total
Residential
5,883
59%
24,716,758
49,191.438
50%
27,452,408
55,422,933
50%
Apts. 5 or
More Units
6,260
62%
644,688
678,612
95%
7.645,282
8.026,814
95%
Total **
Housing Units
..***
--
25,361,466
47,870.050
51%
35.097,690
63,449,747****
55%
  Population Collected by Private Sector
  (3.1 per occupied unit)                   72,381,692   12,720,773    85,102,465  23,700,374   108,802,839
  Population in Occupica Housing Units         142,834.642   28.976,450   171,811,092  24,883,128   197,399,913****
  Percent of PopulatiorvCollected By
  Private Sector                               51%        44%        50%        95%         55%

  * Includes mobile homes and trailers
  ** Total Housing Units include Residential Units (Single Family Homes and Duplexes to 4 Unit Apartments),
    and Apartmenta of'ive or more,
 ***  The Number of contractors serving Total Housing Units is unobtainable due to overlap between contractors
    collecting Residential Units and Apartments.
**** From 1970 Census of Housing.
         Large contractors  (15. 4 percent of the operators and 59. 6 percent of
  the trucks) collect 69 percent of the single-family houses served by the
  private sector and approximately 80 percent of all multi-family units  served
  by the  private sector.  The private sector is oriented heavily toward collec-
  tion in larger SMSA's in  providing service to 50 percent of the residential
  housing units in the nation.
         Based on the traditional residential  definitions (one to fourplex units),
  3. 9 pounds of solid waste per capita is  generated  daily.   The  141,000 tons
  per day handled by large contractors represents 71  percent of all  residential
  waste.  A  large proportion  of residential waste (39%) is further concentrated
  among about 160 operations of 50 trucks or  more.
                                           1. 15

-------
      About 6 out of 10 contractors handle significant quantities of residential
waste.  As their proportion of residential wastes increases, their proportion
of rear and side loader ownership increases.  Among those who are exclusively
residential, a significantly larger segment of their fleet is in non packers.
This indicates that exclusively residential contractors often tend to be  small.
      Based on trucks in operation, the gross tonnage per truck across the
industry equals 1 4. 2 tons daily or 9. 1 tons per  crew member.  This com-
pares with 9. 8 tons per truck and 4. 7 tons per  crew member for those
collecting residential wastes only.
COMMERCIAL AND INDUSTRIAL COLLECTION
      Commercial  and industrial tonnage accounts for 65 percent of the daily
wastes  collected by the private  sector.  Gross  weight exceeds  445,000 tons
per day. Almost all private solid waste contractors collect some commercial/
industrial waste.  Applied Management Sciences estimates private contractors
collect  91 percent of the commercial and 94 percent of the industrial customers
throughout the nation.   It should be noted that commercial •waste includes the
95 percent of the total apartment refuse which is collected by private con-
tractors.
      Collecting in the commercial/industrial market is significantly
different from that of the residential sector.  High tonnage is generated
from relatively few stops.  Service to  this market requires the use of the
more automated and sophisticated equipment such as front-end loaders,
roll-offs, hoist  type vehicles,  etc.  These types of vehicles usually involve
on-site containerization of the waste.
      Two  measures indicate the concentration of  commercial/industrial
waste collection.  In terms of tonnage,  15 percent of the  contractors collect-
ing 100 tons per day or more collect 77 percent of the commercial/industrial
waste.  Size of contractor by truck count indicates that 15 percent (10 trucks
or more) of the  operators  collect 66  percent  of the commercial/industrial
                                    1. 16

-------
IT)
ss



                       I

                              n
                              .
-------
                                        TABLE 1.12

                   PERCENT DISTRIBUTION OF TONNAGE BY NUMBER OF TONS PER DAY
                                   IN THE PRIVATE SECTOR
Type of Tonnage

Distribution of Total
Contractors
Distribution of Tonnage
Among Number of Tons
Total Tonnage
Residential
Commercial
Industrial
Distribul ion of Tonnape
Within Number of Tons
Total Tonnage
Residential
Commercial
Industrial
Other*
Number of Tons Collected Per Dav
1-6

26. 3%


1.3
1.8
1.5
0.5


100%
41.7
40.3
11.7
6.3
7-12

17. Z%


2.3
2.6
3.0
1.3


100%
33.6
45.2
17.5
3.7
13-24

18.6%


4.6
5.9
5.6
2.7


100%
38.5
41.5
18.1
1.9
25-49

12.3%


6.3
8.2
6.6
4.5


100%
39.2
36.1
22.0
2.7
50-99

11.0%


10.8
13.1
11.1
8.8


100%
36.4
35.2
25.0
3.4
100-249

9.


20
18
21
21



2%


.3
.8
.0
.4


100%
27
35
32
4
.8
.4
.3
.5
250-499

2.8%


13.8
13.5
13.9
14.6


100%
29.4
34.4
32.5
3.7
500-999

1.6%


15.2
16.9
17.2
12.6


100%
33.6
38.8
25.4
2.2
1000 or
more

1.1%


25.4
19.2
20.0
33.7


100%
22.7
27.0
40.9
9.4
Total

100%


100
100
100
100


100%
29.1
33.7
31.3
5.9
* Other Refuse includes demolition and construction refuse,and all other refuse.



  waste.   Due to the density of commercial/industrial waste,  truck nn;»it is not

  an accurate  descriptor of the  collection  contribution.  Obviously, some

  organizations  that are small in terms of truck count collect  large tonnage

  in  this  marketplace.

                                           TABLE 1.13

                         PERCENT DISTRIBUTION OF TONNAGE BY CONTRACTOR SIZE
                                      IN THE PRIVATE SECTOR
lype of 1'jnnage

Distribution of Total
Contractors
Distribution of Tonnage
Among Contractor Sizes
Total Tonnage
Kcs identia 1
Commercial
Industrial
Distribution of Tonnage
Within Contractor Size
Total
Residential
Commercial
Industrial
Other*
Size ol Contractor
1
truck

26.0%


2. 1
2.4
2.5
1.3


100%
34.2
40. 5
18.4
6.9
2-3
trucks

31.8%


8.0
8.0
9.5
6.9


100%
30.0
41. 0
26.6
2.4
4-5
trucks

14. 1%


7.0
6.2
7.9
6.3


100%
27.0
39.0
28.0
6.0
6-9
trucks

12.6%


14.8
12.0
16.2
16.9


100%
24.5
37.6
35.3
2.6
10-19
trucks

9. 8%


26.4
22. 7
25.6
32.2


100%
25.8
33.2
37.5
3.5
20-49
trucks

4.0%


25.2
19.8
25.2
30.4


100%
23.6
34.2
37.0
5.2
50 or more
trucks

1.6%


16.5
28. 8
13.0
6.1


100%
52.5
27.0
11.3
9.2
Total

100%


100
100
100
100


100%
29. 1
33.7
31. 3
5.9
  *Other Refuse includes demolition and construction refuse, and all other refuse.
                                            1. 18

-------
      Clearly, commercial/industrial collection is most properly identified
as the principal activity of the 10-49 truck contractor.  These contractors
collect 51 percent of the daily commercial load and 62 percent of the daily
industrial tonnage.  As indicated in the initial section of this analysis,
this particular segment of contractors is particularly oriented toward the
necessary equipment (front loaders, roll-offs,  containers, etc. ),  to
service the  commercial/industrial requirements.  It should be noted a
commercial emphasis is also evident at the level of the 5-9 truck  operator,
but is  greater at the  10-49 truck levels, while  the operator with 50 or more
trucks is primarily involved in residential wastes.
      Commercial/industrial collection reflects the latest mechanized
technology of  the solid waste field. By virtually every measure,  contractors
committed wholly to this activity are above the  norm in terms of mean number
of tons (17.  2)  per truck per day, as well as mean number of tons (14. 8) per
man per day.  The commercial  collection vehicle collects 175 percent of
the tonnage  of a residential truck with half the  crew.
      In  the final analysis, the private sector serves a majority of the
people and (with some regional exceptions) nearly all of the commercial and
industrial organizations in the United States.
                                    1.19

-------

-------
THE PRIVATE SECTOR IN SOLID WASTE MANAGEMENT
 A Profile of Its Resources and Contribution
          to Collection and Disposal
          Volume 2, Analysis of Data

-------

-------
                               CONTENTS


CHAPTER                                                        PAGE



    2         METHODOLOGICAL APPROACH .  ......     2.1

                SUMMARY	     2.1

                 Table 2. 1:  Comparison of  Truck Counts in
                   Sample and Over-Sample for Portland ...     2,4

                 Table 2.2:  Comparison of  Truck Counts in
                   Sample and Over-Sample for Chicago  .  „  .     2.5

                QUESTIONNAIRE DEVELOPMENT .  .  .  .  „  .     2.7

                SAMPLE DESIGN	„  .  .  .  .     2.14

                 Figure 2. 1:  Bureau of Census Regions  ...     2. 17

                 Figure 2.2:  Sample Size vs. Error  .  .  „  .  .     2.22

                 Figure 2. 3:  Sensitivity of Sample Size to Con-
                   tractor Population Size When Measuring
                   Means or Totals. „	„	     2.24
                 Figure 2.4:  Sensitivity of Sample Size to Con-
                   tractor Population Size When Measuring
                   Proportions	„  .  .     2.26
                 Figure 2. 5:  Distribution of Numbers of SMSA's
                   by Population and Region Within Continental
                   U. S	     2.29
                 Figure 2. 6:  Distribution of Sample SMSA's by
                   Region and Population	     2.30

                 Figure 2. 7:  Distribution of Contractors  in
                   SMSA's by Region and Population  .  .  .  ,  .     2.30

                 Figure 2. 8:  Distribution of Contractors  by
                   Region and Population	„  .  .     2. 31

                 Figure 2. 9:  Distribution of Contractor Sample
                   in SMSA's by Region and Population ....     2.31

                 Figure 2. 10:  Distribution of Sample Contrac-
                   tors by Region and Population  „	     20 32
                                    1.23

-------
                           CONTENTS (Cont.)


CHAPTER                                                        PAGE

                SAMPLE RELIABILITY	
                 Figure 2. 11;  Distribution of Sample Interviews
                   in Region I	     2.34

                 Figure 2. 12:  Distribution of Sample Interviews
                   in Region II	     2.35

                 Figure 2. 13:  Distribution of Sample Interviews
                   in Region III ...	     2.37

                 Figure 20 14:  Distribution of Sample Interviews
                   in Region IV	     2.38

                 Figure 2. 15:  Distribution of Sample Interviews
                   in Region V	     2.40

                 Figure 2. 16:  Distribution of Sample Interviews
                   in Region VI .  .   . „	, .  .  .     2.43

                 Figure 2. 17:  Distribution of Sample Interviews
                   in Region VII . .   «,	     2.44

                 Figure 2. 18:  Distribution of Sample Interviews
                   in Region VIII  .   . .  .  ,	     2.46

                 Figure 2. 19:  Distribution of Sample Interviews
                   in Region IX	„  .      2.47

                 Table 2. 3:  Over-Sample SMSA's .  .  .  .  .  .     2050
                 Figure 2.20:  Final  Estimated Distribution of
                   Contractors by Region and Population.  .  .     2.52
                 Figure 2.21:  Final Estimated  Distribution of
                   Establishments by Region and Population  .     2.53
                 Figure 2. 22:  Final  Estimated Distribution of
                   Establishments by Region and Population  .     2. 54

                 Figure 2. 23:  Final  Estimated Distribution of
                   Establishments by Region and Population  .     2. 54

                INTERVIEWING TECHNIQUE  ........     2. 67

                TABULATION PROCESSES  o .   . .  .  .  .  .  .     2.71

                DATA CONSIDERATIONS .	     2.77

    3         VOLUME OF WASTE  . o	     3.1
                CHAPTER SUMMARY	     3.2

                TOTAL VOLUME .  „	     3.3
                                    1.24

-------
                         CONTENTS (Cont.)


CHAPTER                                                       PAGE
                 Table 3. 1: National Estimate - Share of Daily
                   Tonnage Collected by the Private Sector by
                   Residential,  Commercial, and Industrial
                   Refuse  .  „  . .  „	     3.3
                 Table 3.2; National Estimate - Daily Tonnage
                   Per Customer Collected by the Private Sec-
                   tor by Residential, Commercial, and Indus-
                   trial Refuse	,	     3.4

                 Table 3.3; National Estimate - Per Capita
                   Generation of Residential, Commercial, and
                   Industrial Refuse	„	     3.4

               TONNAGE PER  CONTRACTOR BY DAILY TON-
               NAGE COLLECTED	o,...     3.6

                 Table 304: National Estimate of Tonnage by
                   Number of Tons Per Day in the Private
                   Sector	,.,....,....     3.7

                 Table 3.5: Percent Distribution of Tonnage by
                   Number of Tons Per Day in the Private Sec-
                   tors  	„	=	     3.7
                 Table 3. 6: Tons Per Truck and Employee by
                   Tons  Collected Per Day in the Private Sector    3.8

               DAILY TONNAGE BY CONTRACTOR SIZE  .  .     3.10
                 Table 3.7: National Estimate of Tonnage by Con-
                   tractor  Size  in the Private Sector .  . . „  .     3.10
                 Table 3.8: Percent Distribution of Tonnage by
                   Contractor Size  in the Private Sector ...     30 11

                 Table 3.9: Tons Per Truck and Employee by
                   Size of Contractor in the  Private Sector .  .     3.11
                 Figure 3.1: Distribution of Mix of  Tonnage
                   Collected Within Contractor Size Categories     3. 12

               DAILY TONNAGE BY MIX OF COLLECTION  .  .    30 13

                 Table 3. 10: Tons  Per Truck and Employee by
                   Mix of Collection in the Private Sector ....    3.13

                 Table 3. 11: National Estimate of Tonnage by
                   Mix of Collection in the Private Sector .  .   .    3.14
                                   1.25

-------
                        CONTENTS (CONT.)


CHAPTER                                                        PAGE
                 Table 3. 12:  Percent Distribution of Tonnage
                   by Mix of Collection in the Private Sector       3.15

                DAILY TONNAGE BY REGION AND CITY SIZE     3.16

                 Table 3. 13:  National Estimate of Tonnage by
                   Region in the  Private Sector	,    3. 16

                 Table 3. 14:  Percent Distribution of Tonnage by
                   Region in Private Sector	    3.17

                 Table 3. 15:  National Estimate of Tonnage by
                   SMSA Size in  Private Sector	    3.17

                 Table 3. 16:  Percent Distribution of Tonnage by
                   SMSA Size in  Private Sector	    3.18

              CUSTOMERS  OF THE PRIVATE SECTOR  ....    4. 1

                CHAPTER SUMMARY	    4. 3

                ESTIMATES OF PRIVATE SECTOR MARKET . .    4,4

                 Table 4. 1:  National Estimate - Private Sec-
                   tor's  Share of Customers	    4.4

                 Figure 4. 1:  Distribution of Contractors Among
                   Customer Types .  „	    4.5

                 Table 4.2:  National Estimate - Share of Popu-
                   lation Served  by Private Sector  „	    4. 6

                CUSTOMERS BY  CONTRACTOR SIZE	    4.7
                 Table 4.3;  National Estimate of Customer
                   Types Serviced by the Private Sector by
                   Contractor Size .  „	    4. 7

                 Table 4.4:  Mean Number of Customer Types
                   Serviced by the Private Sector by Contractor
                   Size	 .  .  .   .  .  .  .    4.7
                 Table 4. 5:  Percent Distribution of Customer
                   Types Serviced by the Private Sector by
                   Contractor Size	    4. 8

                 Table 4. 6:  Proportion of Contractors and
                   Customer  Types Collected	     40 8

                CUSTOMERS AND TONNAGE SHARES .  . .  .     4.9
                 Table 4.7:  Tonnage Shares by Customer Types    4.9
                                   1.26

-------
                          CONTENTS (Cont. )


CHAPTER                                                       PAGE
                CUSTOMERS BY DAILY TONNAGE	    4. 10

                 Table 4.8: National Estimate of Customer Types
                   Serviced by the Private Sector by Tons Col-
                   lected 	,   .  ,  .  .  .    4. 10

                 Table 4.9: Mean Number of Customer Types
                   Serviced by the Private Sector by Tons Col-
                   lected 	,  .  .  .  „    4. 11

                 Table 4. 10: Percent Distribution of Customer
                   Types Serviced by the Private Sector by Tons
                   Collected	„	    4,11

                CUSTOMERS BY MIX OF COLLECTION  ...    4.13

                 Table 4. 11: National Estimate of Customer
                   Types Serviced by the Private Sector by
                   Mix of Collection	„  .  . .  .  °     4.13

                 Table 4. 12: Mean Number of Customer  Types
                   Serviced by the Private Sector by Mix of
                   Collection. . .  .  „	     4.14

                 Table 4. 13: Percent Distribution of Customer
                   Types Serviced by the Private Sector by Mix
                   of Collection. .  .  „	     4.14

                CUSTOMERS BY REGIONAL AND CITY SIZE
                CHARACTERISTICS	     4.16

                 Table 4. 14: National Estimate of Customer
                   Types Serviced by the Private Sector by
                   SMSA Size .  .  „	     4.16
                 Table 4. 15: Mean Number of Customer  Types
                   Serviced by the Private Sector by SMSA Size    4. 17

                 Table 4. 16: Percent Distribution of Customer
                   Types Serviced by the Private Sector by
                   SMSA Size	„  .  .     4. 17

                 Table 4. 17: National Estimate of Customer
                   Types Serviced by the Private Sector by
                   Region	„  .  .     4. 18

                 Table 4. 18: Mean Number of Customer  Types
                   Serviced by the Private Sector by Region  a     4. 19
                                    1.27

-------
                            CONTENTS (Cont.)
CHAPTER                                                        PAGE


                 Table 4. 19:  Percent Distribution of Customer
                   Types Serviced by the Private Sector by
                   Region	„.„..,.	   4. 19

                TYPE OF WASTE COLLECTED AND  FREQUENCY  4. 20

                 Table 4.20:  Size of Contractor Indicators by
                   Type of Wastes Collected in Private Sector .  .   4. 20

                 Table 4.21:  Percent of Collection Frequency  by
                   Customer Type ......  „	   4.21
                 Table 4. 22:  Mean Collection Frequency (Times
                   Per  Week) of Household Refuse From Single
                   Family Homes by Contractor Size Among The
                   Private Sector	   4. 21

                 Table 4.23:  Mean Collection Frequency (Times
                   Per  Week) of Household Refuse From Single
                   Family Homes by Daily Tonnage Among the
                   Private Sector  .„...„	„ .  .    4. 22

                 Table 4. 24:  Mean Collection Freqiiency (Times
                   Per  Week) of Household Refuse From Single
                   Family by Mix of Collection Among Private
                   Sector	„.„	    4.22
                 Table 4.25:  Mean Collection Frequency (Times
                   Per  Week) of Household Refuse From Single
                   Family Homes by Region Among Private
                   Sector	.	  .    4.23

                 Table 4.26:  Mean Collection Frequency (Times
                   Per  Week) of Household Refuse From Single
                   Family Homes by SMSA Size Among Private
                   Sector	    4.23

                CURB SERVICE	    4.24

                 Table 40 27:  National Estimate - Residential
                   Customers Receiving Curb Service From Pri-
                   vate Sector	    4. 24

                 Table 4.28:  Incidence  of Curb Service  for Resi-
                   dential Customers Serviced by the Private Sec-
                   tor by Contractor Size .  .  .  „	    4. 25
                                    1.28

-------
                         CONTENTS (Cont. )

CHAPTER                                                          PAGE
                 Table 4. 29:  Incidence of Curb Service for
                   Residential Customers Serviced by the Pri-
                   vate Sector by Contractor Mix of Collection      4. 25
                 Table 4. 30:  Incidence of Curb Service for
                   Residential Customers Serviced by the Pri-
                   vate Sector by SMSA Size	„ .  .   4. 26
                 Table 4. 31:  Incidence of Curb Service for Resi-
                   dential Customers Serviced by the Private
                   Sector by Region	   4. 26

              EQUIPMENT AND MANPOWER  . .  „	   5. 1
                CHAPTER SUMMARY .  =  .„....*.,..   5.3
                EQUIPMENT ESTIMATES AND UTILIZATION .  „   5.4
                 Table 5. 1:  National Estimate of Total  Trucks
                   Operated by the  Private Sector   .,.00..   5.4
                 Figure  5. 1:  Fleet Composition of Average Con-
                   tractor 	„  .  .  o  .  o   .  o	   5.5
                 Figure  5.2:  Distribution of Ttotal Trucks Among
                   Truck Types „.„..<,	   50 6
                 Table 5.2:  National Estimate of Truck Utilization
                   Per Day in Private Sector ...»	   5.7
                 Table 5.3;  Utilization of Trucks in Private Sector
                   by Size of Contractor.     .  .  „	
                 Table 5.4:  Utilization of Trucks in Private Sector
                   by Mix of Collection	
                 Table 5. 5;  Utilization of Trucks in Private Sector
                   by SMSA Size	„	   5.9
                MANPOWER ANALYSIS .  .  „	   5. 10
                 Table 5. 6:  National Estimate of Manpower Em-
                   ployed by Private Sector	  .   5. 10
                 Table 50 7:  Analysis of Manpower by Mix  of Col-
                   lection in Private Sector ...   .  ......   5. 11
                 Table 5.8:  Analysis of Manpower by Contractor
                   Size in Private Sector	„ .  .   5. 11
                                     1.29

-------
                          CONTENTS (Cont.)


CHAPTER                                                         PAGE
                 Table 5. 9: Analysis of Manpower in Private
                   Sector by SMSA Size ...........      5. 12

                TRUCK TYPES AND SIZE OF CONTRACTOR  .      5. 14

                 Table 5, 10:  Percent Distribution of Truck Types
                   by Contractor Size in Private Sector ....      5.14

                 Table 5. 11:  National Estimate of Truck Types by
                   Contractor Size in Private Sector	      5. 15

                 Table 5. 12:  Percent Distribution of Truck Types
                   Within Contractor Sizes in Private Sector  .      5. 16

                 Table 5. 13:  Percent of Pakcer Trucks in-Private
                   Sector by Contractor Size	„ .      5. 16

                TRUCK TYPE AND MIX OF COLLECTION  .  .  .     5. 18

                 Figure 5. 3:  Fleet Configuration by Collection Mix 5. 19

                 Table 5. 14:  Mean Number of Trucks Operated by
                   Private Sector by Mix of Collection	    5. 20

                 Table 5. 15:  National Estimate of Truck Types by
                   Mb£ of Collection in Private Sector . .  .  . .    5. 20

                 Table 5. 16:  Percent Distribution of Truck Types
                   by Mix of Collection in Private Sector ....     5. 21
                 Table 5. 17:  Percent Distribution of Truck Types
                   Within Collection Mix in Private Sector ...    5. 21

              TRUCK TYPE AND  DAILY TONNAGE  . . .  .  . .    5.22
                 Table 5. 18:  Mean Number of Truck Types by
                   Number  of Tons Collected Per Day in Private
                   Sector	,	    5.22

                 Figure 5.4:  Mean Number of Total Trucks,
                   Trucks Collecting Today, and Daily Tonnage by
                   Contractor Size	    5. 23

                 Table 50 19:  National Estimate of Truck Types
                   by Tons  Collected in Private Sector	    5. 24

                 Table 5. 20:  Percent Distribution of Truck Types
                   Within Tons Collected in Private  Sector ...    5* 25
                                    1.30

-------
                          CONTENTS (Cont.
CHAPTER                                                         PAGE

                 Table 5.21:  Percent Distribution of Truck Types
                   by Tons  Collected in Private Sector	5.26

                REGIONAL AND CITY SIZE CHARACTERISTICS .  .  5. 27

                 Table 5.22;  National Estimate of Total Trucks
                   Operated by Private Sector for Each Region . .  5.27

                 Table 5.23:  National Estimate of Truck Types by
                   SMSA Size in Private Sector	5.27

                 Table 5.24:  Mean Number of Truck Types by
                   Region in Private Sector	5, 28
                 Table 5. 25:  Mean Number of Truck Types by
                   SMSA Size	5. 28

                 Table 5.26:  Percent Distribution of Truck Types
                   Within Regions in Private  Sector	5. 29

                 Table 5.27:  Percent Distribution of Truck Types
                   Within SMSA Size in Private Sector	5.30

                 Table 50 28:  Percent Distribution of Truck Types
                   By Region in Private Sector	5. 30

                 Table 5.29:  Percent Distribution of Truck Types
                   by SMSA Size in Private Sector	5.31

                PACKER-NON PACKER USE TRENDS	5.32
                 Table 5. 30:  National Estimate of Trends in Opera-
                   tion of Packer and Non Packer Trucks in the
                   Private Sector	5. 32

                 Table 5.31:  National Estimate of Trends in Opera-
                   tion of Packer and Non Packer Trucks by Region 5. 33

                 Table 5. 32:  Mean Number of Packers and Non
                   Packers in 1970, 1968, and 1965 by Size of Con-
                   tractor  	5. 34

                 Table 5. 33:  Mean Number of Packers and Non
                   Packers in 1970, 1968, and 1965 by Tons Col-
                   lected Per Day	5, 34

                 Table 5. 34:  Mean Number of Packers and Non
                   Packers in 1970, 1968, and 1965 by Mix of
                   Collection	„  50 35
                                     1.31

-------
                          CONTENTS (Cont. )


CHAPTER                                                         PAGE


                 Table 5.35: Mean Number of Packers and
                   Non Packers in 1970,  1968, and 1965
                   by SMSA Size	      5. 36

               SPECIALIZED EQUIPMENT	      5.37

                 Table 5.36: National Estimate of Specialized
                   Equipment Serviced by the Private Sector  .      5. 37

                 Table 5.37: National Estimate of Specialized
                   Equipment by Contractor Size in Private  Sector   5. 38

                 Table 5. 38: Percent Distribution of Special Equip-
                   ment by Contractor Size in Private Sector .  .     5. 39

                 Table 5. 39: National Estimate of Special Equip-
                   ment by Mix of Collection in Private Sector  .     5. 30

                 Table 5.40: Percent Distribution of Special
                   Equipment by Mix of Collection in Private
                   Sector	     5.40

                 Table 5.41: National Estimate of Special Equip-
                   ment by SMSA Size  in  Private Sector  ....     5.40

                 Table 5.42: Percent Distribution of Special
                   Equipment by SMSA Size in Private Sector .  .     5.41

     6         DIRECT CUSTOMER CONTRACTING AND
              GOVERNMENT FRANCHISING	   6. 1
               CHAPTER SUMMARY	   6.2
               EXTENT  OF CONTRACTING AND FRANCHISING  .   6. 3
                 Table 6. 1:  National Estimate of Customers
                   Serviced by the Private Sector Under Direct
                   Contract and Government Franchise	   6.3

               CONTRACTING/FRANCHISING AND
               CONTRACTOR  SIZE	   6.4
                 Table 6. 2:  National Estimate of Private
                   Contractors Who  Contract Direct and Have
                   Government Franchises by Contractor Size  .  .   6.4

                 Table 6. 3:  Percent Distribution of Private
                   Contractors Who  Contract Direct and Have
                   Government Franchises  by Contractor Size  .  .   6. 5
                                  1.32

-------
                           CONTENTS (Cont. )


CHAPTER
                                                                  PACE
                 Table 6.4:  National Estimate of Customers
                   Serviced by the Private Sector Under Direct
                   Contract and Government Franchise by
                   Size of Contractor  	   6.6
                 Table 6. 5:  Percent Distribution of Customers
                   Serviced by the Private Sector Under Direct
                   Contract and Government Franchise by
                   Size of Contractor  	   6.6
                 Table 6. 6:  Percent of Customers  Serviced by
                   the Private Sector Under Direct Contract
                   and Government Franchise Within
                   Contractor Sizes	   6.7

              CONTRACTING/FRANCHISING AND DAILY
              TONNAGE	   6.8
                 Table 6. 7:  National Estimate of Private
                   Contractors Who  Contract Direct and Have
                   Government Franchises by Tonnage	   6.8

                 Table 6. 8:  Percent Distribution of Private
                   Contractors Who Contract Direct and Have
                   Government Franchises by Tonnage	   6.9

                 Table 6. 9:  National Estimate of Customers
                   Serviced by the Private Sector Under Direct
                   Contract and Government Franchise by
                   Tonnage	   6. 10
                 Table 6. 10: Percent Distribution of Customers
                   Serviced by the Private Sector Under Direct
                   Contract and Government Franchise by
                   Tonnage	   6. 10
                 Table 6. 11: Percent Distribution of Customers
                   Serviced by the Private Sector under Direct
                   Contract and Government Franchise by
                   Tonnage	   6. 11
              CONTRACTING/FRANCHISING AND MIX OF
              COLLECTION	   6.12
                 Table 6. 12: National Estimate of Private
                   Contractors Who  Contract Direct and Have
                   Government Franchises by Mix of Collection  .   6. 12
                 Table 6. 13: Percent Distribution of Private
                   Contractors Who  Contract Direct and Have
                   Government Franchises by Mix of Collection  .   6. 13
                                     1.33

-------
                         CONTENTS (Cont. )


CHAPTER                                                         PAGE

                 Table 6.14:  National Estimate of Customers
                   Serviced by the Private Sector Under Direct
                   Contract and Government Franchise by
                   Mix of Collection	   6. 14

                 Table 6. 15:  Percent Distribution of Customers
                   Serviced by the Private Sector Under Direct
                   Contract and Government Franchise by
                   Mix of Collection	   6. 14

                 Table 6.16:  Percent of Customers  Serviced
                   by the Private Sector Under Direct Contract
                   and Government Franchise Within Mix of
                   Collection Categories	   6. 15
              REGIONAL AND CITY SIZE CHARACTERISTICS .  .   6. 16
                 Table 6. 17:  National Estimate of Private
                   Contractors Who Contract Direct and Have
                   Government Franchises by SMSA Size	   6. 16

                 Table 6. 18:  Percent Distribution of Private
                   Contractors Who Contract Direct and Have
                   Government Franchises by SMSA Size	   6. 17

                 Table 6.19:  National Estimate of Customers
                   Serviced by the Private Sector Under Direct
                   Contract and Government Franchise by
                   SMSA Size	   6.18
                 Table 6. 20:  Percent Distribution of Customers
                   Serviced by the Private Sector Under Direct
                   Contract and Government Franchise by
                   SMSA Size  	   6.18

                 Table 6. 21:  Percent of Customers  Serviced by
                   the Private Sector Under Direct Contract and
                   Government Franchise Within SMSA Size ...   6.19
                 Table 6. 22:  National Estimate of Private
                   Contractors Who Contract Direct and Have
                   Government Franchises by Region	   6. 20

                 Table 6. 23:  Percent Distribution of Private
                   Contractors Who Contract Direct and Have
                   Government Franchises by Region	   6. 20
                                   1.34

-------
                        CONTENTS (Cont.)


CHAPTER                                                        PAGE


                 Table 6. 24:  National Estimate of Customers
                   Serviced by the Private Sector Under
                   Direct Contract and Government Franchise
                   by Region   	   6. 21

                 Table 6. 25:  Percent Distribution of Customers
                   Serviced by the Private Sector Under Direct
                   Contract and Government Franchise by Region   6. 22

                 Table 6. 26:  Percent Distributipn ,of Customers
                   Serviced by the Private Sector Under Direct
                   Contract and Government Franchise
                   Within Regions	   6. 22


    7         BUSINESS STRUCTURE	     7. 1

               CHAPTER SUMMARY	     7.2

               BUSINESS STRUCTURE BY SIZE OF OPERATION   7. 3
                 Table 7. 1:  Mean Number of Trucks,  Employees,
                   and Tons Per Day  by Type of Ownership ...    7. 3

                 Table 7.2;  National  Estimate of Companies Owned
                   as Proprietorships, Partnerships,  or  Corpora-
                   tions by Size of Contractor	     7. 4

                 Table 7. 3:  Percent of Companies Owned as Pro-
                   prietorships, Partnerships, or Corporations
                   by Contractor Size	„	      7.4

                 Table 7.4:  National Estimate  of Companies
                   Owned as Proprietorships, Partnerships, or
                   Corporations, by Daily Tonnage	„     7. 5
                 Table 7. 5: Percent of Companies Owned as Pro-
                   prietorships, Partnerships, or Corporations
                   by Daily Tonnage .    	     7. 5

               AGE OF OPERATION	    7.6

                 Table 7. 6:  Year of Company Origin in Present
                   Form	,.	    7. 6

                 Table 7. 7; Percent Distribution of Year Business
                   Started in its Present Form by Contractor Size   7. 6

                 Table 7.8: Percent Distribution of Year Business
                   Started in its Present Form by Daily Tonnage    7, 8

                 Table 7.9: Percent Distribution of Year Business
                   Started in its Present Form by Region .  .  ,     7. 8


                                     1,35

-------
                         CONTENTS  (Cont. )


CHAPTER                                                         PAGE


               OTHER SOLID WASTE RELATED BUSINESSES .     7. 8

                 Table 7. 10:  Number of Companies Per Estab-
                   lishment	    7.8

                 Table 7. 11:  Number of Establishments Which
                   are Subsidiaries of Another Firm or Operate
                   Subsidiaries	     7. 8

                 Table 7. 12:  Number of Establishments Engaged
                   in Related Businesses	7. 9

                 Table 7. 13:  Number and Percent of Establishments
                   Engaged in Related Businesses by Size of
                   Establishment	7.9
                                  1.36

-------
                      METHODOLOGICAL APPROACH

SUMMARY
      The study methodology for the  survey and analysis of the private
sector of the solid waste management industry had several essential ele-
ments.   The first component consisted of designing a questionnaire to
elicit information to support meaningful analyses in terms of the study
objectives.   The second element involved defining the universe of private
solid waste contractors and selecting a sample  to provide reliable national
estimates.  The third segment comprised  selecting and training inter-
viewers  who could expertly draw the maximum  amount of information
from the respondents.  The fourth element consisted of all the data
handling including interviewing, editing, coding, and tabulating.   Finally,
the last  step involved the analysis of the survey data and the collection of
secondary data such as housing statistics gathered by the Census  to support
the study objectives.  Each phase of the study design and performance
proceeded  subsequent to  review and approval by the Research Committee
of NSWMA and the Office of Solid Waste Management Programs of EPA.
      Once the list of contractors was developed, the base sample of 1000
contractors was selected.  The sample design for the study incorporated a
two-stage stratified cluster method.  A description of this design follows:
      •      Contractors were first stratified by regions of the  country:
            (First stage of  stratification)
      •      Within each region  of the  country, Standard Metropolitan Areas
            (SMSA's) were  stratified by size: (Second stage of stratification)

                                   2. 1

-------
      •     SMSA's within each size stratum and region were listed
            and clusters (SMSA's) were randomly selected: (Cluster phase).

      •     The number of contractors to be interviewed within each
            cluster was determined proportionately with respect to region,
            city size,  and number of contractors in each cluster.

      •     Contractors to be interviewed were  randomly selected from
            the list in each city.


The goal of the sample design of 1000 interviews was to achieve a 95 percent

confidence that the estimates derived from the sample data would not  vary

by more than plus or minus five percent from the true population values

(i.  e. , those which would have been obtained if a complete census of all con-

tractors had been conducted).

      The calculations of national estimates and variances of these estimates

for the two  stage stratified cluster design require city-by-city information,

which was not provided for all questions in the data tabulations.  Therefore,

calculations were derived on the basis of a solely regional stratification

(i. e. , assuming contractors were stratified by region and randomly selected

within region).  As seen in this chapter, these estimates are  conservative

since they do not take full advantage of the further stratification by city size.

Examples of various  estimates  and  accuracy intervals are presented below:

      Proportion of Contractors Collecting From Single Family Houses

      There is a 95 percent confidence that the true proportion  of con-
      tractors  serving single family houses is within plus or minus 4. 9 per-
      cent of 58. 2 percent;  i. e. , between 55. 3 percent and 61. 1 percent.

      Average Number of Single Family Houses Collected By  Those
      Contractors Serving Such Customers

      There is a 95 percent confidence that the average number of single
      family customers for contractors collecting single family houses is
      within plus or minus 5. 4 percent of 4222;  i. e. ,  between 3994 and
      4450.

      Proportion of Contractors Collecting Industrial Customers

      There is a 95 percent confidence that the true proportion  of contractors
      collecting from  industrial customers is within plus or minus 5 percent
      of 60. 6 percent; i. e. ,  between 57. 6 percent and 63. 6 percent.
                                    2.2

-------
       Average Number of Industrial Customers Collected By Those
       Contractors Serving Such Contractors
       There is a 95 percent confidence that the true average number of
       industrial customers for contractors collecting industrial customers
       is within plus or minus 17. 8 percent of 61. 5; i. e. ,  between 50. 6
       and 72. 4.
       Total Number of Tons
       There is a 95 percent confidence that the true total number of tons
       collected by the private sector is within plus or minus 16.2 percent
       of 685, 602; i. e. , between 574, 535 and 796, 669.
       Total Number of Trucks
       There is a 95 percent confidence that the true total number of trucks
       operated by the private sector is within plus or minus  11.4 percent
       of 61, 656; i. e. ,  between 54, 768 and 68, 544.
       Total Number of Employees
       There is a 95 percent confidence that the total number of employees
       in the private sector is within plus or minus 12. 8 percent of  102, 179;
       i.e., between 89, 100 and 115, 258.
      As  can be seen, at the 95 percent  confidence level, the range  of accuracy
for these  examples is from 4. 9 percent to 17. 8  percent.  The differences be-
tween the goal  and the achieved levels for certain questions resulted from
these factors.   First, in the estimates of averages and totals, the few very
large contractors have a disproportionate influence.  The effect of the large
contractors is  to skew some distributions such that they are non-normal.
The second factor involved in the larger  variances was the initial assumption
at the start of the survey that, for SMSA's of approximately  equal size, the
variation in contractor characteristics across SMSA's was minimal.  As
the field work progressed,  it was clear that the handling of solid waste
across SMSAps of the same size could vary from all private, to a mix of
private and public, to all public.  Finally,  the third  factor involves  the
statistical  phenomenon that as the respondent base for a. specific character-
istic decreases,  the associated relative error normally increases.  Thus,
for example, the estimate of the number  of firms having 50 or more trucks
                                  2.3

-------
 is between 57 and 184,  indicating a potential relative error of approximately
 50 percent.  However,  the estimate of  the proportion of firms having 10
 or more trucks is between 13 percent and 17 percent, indicating an absolute
 error of only 2 percent. As a result, statements about those firms with 10
 or more trucks - the top 15 percent of the sample - are associated with more
 reliable estimates.
       In addition to the  base  sample, an over-sample of 1000 was designed
 such that a census or a near census would be  conducted in forty of the sample
 cities.  The  purposes of the  over-sample were to assist in the definition and
 refinement of the universe, to check on the validity of the base sample de-
 sign,  and to  provide more  accurate  estimates  and variances of the estimates.
 In the assessment of the accuracy of the base sample, data for the key vari-
 able of trucks was compared on a city-by-city basis.  The result of this
 comparison showed an excellent  correspondence between the distributions
 of contractors by truck size and  between the average number of trucks per
 contractor.  For example, the following Tables 2. 1 and 2.2  show the data
 for Portland and Chicago.

                                Table 2.1
COMPARISON OF TRUCK COUNTS IN SAMPLE AND OVER-SAMPLE FOR PORTLAND
Number of Trucks
1
2-3
4-5
6-9
10-19
20-49
50 or more
Number of
Contractors in Over-Sample
52
28
11
6



Number of
Contractors .in Sample
7
7
4
1



 Average Trucks
 Per Contractor                     2.2                          2.5
                                    2.4

-------
                               Table 2.2

             COMPARISON OF TRUCK COUNTS IN SAMPLE AND
                      OVER-SAMPLE  FOR CHICAGO
Number of Trucks
1
2-3
4-5
6-9
10-19
20-49
50 or more
Average Trucks
Per Contractor
Number of
Contractors in Over -Sample
27
45
30
28
23
11
1

7. 0
Number of
Contractors in Sample
5
11
12
9
6
2
1

7.9
Such  close matches -were obtained in every over-sample city and thus sub-

stantiated the reliability of the base sample.

      The third purpose of the over-sample was to improve the accuracy of

the estimates derived from the sample data.   To illustrate this result,
calculations of the total number of trucks were performed for both the base

sample and for the over-sample.

      Base Sample Estimate of Trucks

      There is a 95 percent confidence that the total number of trucks
      operated by the private sector is between 54, 768 and 68, 544 and
      is estimated to be 61, 656.

      Over-Sample Estimate of Trucks

      There is 95 percent confidence that the total number of trucks
      operated by the private sector is between 59, 676 and 68, 464 and is
      estimated to be 64, 070.

Thus, as can be seen for the key variable  of truck count,  the over-sample

data provided an opportunity to selectively verify the base sample data with


                                   2. 5

-------
the highly refined near-census data.
      This chapter is  structured into the following subsections:
      •     Questionnaire Development
      •     Sample Design
      •     Sample Reliability
      •     Interviewing Technique
      •     Tabulation Processes
      •     Data Considerations
                                    2.6

-------
QUESTIONNAIRE DEVELOPMENT
      Once the major areas of information of business structure, collection
modes, equipment, manpower,  and salvage and disposal had been defined,
the questionnaire development evolved through an iterative procedure of
definition,  design,  review and pretest,  and redesign.  The definitional task
of this study phase involved the initial design of questions to obtain infor-
mation in all of the major areas of inquiry.  This consisted of the formula-
tion of secondary questions which supported  the primary issues.
      •     What is the business structure?
               Are solid waste contractors primarily proprietorships
               or are they going through incorporation?
            . .  Is solid waste management a highly transient industry
               or composed  of long-established firms?
            . .  What is the industry experience in merger and
               acquisition?
            . .  What other businesses  related to  solid waste collection
               are companies engaged in?
            . .  How does the private sector contract with his customer,
               directly or through a franchise or government contract
               arrangement?
      •     What are the characteristics  of the collection function?
            . .  What types of wastes does the industry collect?
            . .  How often are various residential wastes collected?
            . .  How many residential customers do  they service?
            . .  What is the practice concerning curb service?
            . .  How many commercial and industrial customers  do
               they have ?
            . .  How much wastes do they collect for each class of
               customer ?
      •     What  are the characteristics  of the equipment used for
            collection by the private sector?
               What are the  trends over the past five years in the
               number of open versus packer trucks?
                                   2. 7

-------
                How many of each type of open or packer trucks are
                there in the private sector?
                What are the truck capacities and crew sizes ?
                What is the extend of use  of innovations and special
                types of equipment?
                What are the maintenance practices ?
      •    What does the manpower  pool  in the private sector look like?
                How many people are drivers or  helpers?
           . .   What is the supervisorial and administrative man-
                power level?
                How many men are normally assigned as the truck
                crew?
                What is the usual workweek length?
      •    What is the role of the private collector in disposal and
           salvaging ?
                How many disposal sites does the private collector
                own or operate?
           . .   What is the capacity  of private sites?
                What are the burning and  covering  practices?
                How much of various types of wastes are salvaged?
With these information  classes defined,  a preliminary set of questions were
written to obtain data in all areas. To the extend possible,  the first draft
of the questionnaire was designed in  a manner consistent with the  format
used in the National Survey.
      After several drafts of the questionnaire had  been written to ensure
completeness and logic, a draft was  presented to the NSWMA Research
Committee on September 17,  1969, for their review.   The result  of this
review indicated that several areas in the document required further clari-
fication and amplification or needed precise definitions.  For example,
since one major area of interest was the types of solid waste materials
collected by contractors, exact classifications were needed for each waste
category.  These were  defined and formatted as a card to be presented to
the  respondent.
                                    2.8

-------
      GARBAGE
      RUBBISH
      YARD REFUSE
      ASHES

      BULKY WASTES
      STREET REFUSE
      DEAD ANIMALS
      ABANDONED VEHICLES
      CONSTRUCTION &
      DEMOLITION WASTES
      SPECIAL
      ANIMAL AND
      AGRICULTURAL
      WASTES
      SEWAGE TREATMENT
      RESIDUES
Wastes from the preparation,  cooking,
and serving of food
Market refuse,  waste from the hand-
ling,  storage,  and sale of produce and
meats
Paper,  cardboard, wood,  boxes, rags,
cloth,  bedding
Leather,  rubber, metals, tin cans,
metal foils, dirt
Stones, glass, bottles
Other mineral refuse

Grass,  leaves,  yard trimmings

Residue from fires used for cooking
and for heating  buildings,  cinders

Stoves, refrigerators,  other large
appliances
Furniture, large crates
Trees,  branches, palm fronds,
stumps, flotage
Street sweepings, dirt
Leaves

Cats, dogs, poultry, etc.
Horses, cows,  etc.

Automobiles,  trucks
Lumber,  roofing, rubble, plaster,  etc.
Pipe, wire, insulation, wood,  etc.

Hazardous wastes
Security wastes
Boiler house cinders,  paint  sludges,
chemical, plastic,  and metal scraps
and shavings, etc.
Food processing wastes
Manures, crop  residues


Coarse  screenings,  grit, septic tank
sludge,  de-watered  sludge
With these definitions,  consistent responses could be obtained from all

types of contractors.

      Further classification was also required in  defining the types of

customers from whom the private  sector collects. Since the collection of
                                    2. 9

-------
wastes from large apartment buildings is often a single bill rather than bills
to individual residents,  most collectors  consider apartment buildings with
five or more units to be commercial.  Customer definitions were  also
printed on a hand-out card to facilitate proper classification.
      RESIDENTIAL:        Single family, duplexes, and apartments
                            of four or less units
      COMMERCIAL:        Retail stores, office buildings,  banks,
                            service  stations, apartments of more
                            than four units,  hospitals,  schools
      INDUSTRIAL:         Manufacturing or processing plants
The third major area requiring clarification dealt with the types of trucks
and  specialized equipment used by the private collector.  While most con-
tractors would be clear on the differences between front, rear, and side
loader trucks, much confusion would exist between, say, stationary con-
tainers and stationary compactors.  Since word definitions would be difficult,
in addition to  being time-consuming,  a third card was designed depicting
various vehicle types and  specialized collection equipment.  Through the
use of these three cards, the major definitional areas were  placed on a
consistent basis, and ensured uniform and comprehensive responses on the
part of the respondents.
      Finally,  several other areas of the questionnaire required clarification
which could most appropriately be handled by the interviewers after they had
been properly instructed.  As one example,  a distinction was desired be-
tween the number of customers and the number of stops these customers
represented.  Particularly in commercial collection, there  exists a possi-
bility that while a contractor may collect from a number of chain stores,
he may only bill the owner of all the chains.  In this situation, these chain
stores represent one customer  but several stops.   Similarly,  for  large
industrial customers,  the contractor may have only one bill, but collect
from several plants.  Since  estimates relating to the number of stops were
desirable, both customer and stop information was requested.
                                   2.10

-------
      An additional  subject of interest,  and one which has gained more
importance since the initiation of this study, concerned the contracting
method through which the  private sector dealt with their customers.  Defi-
nitions of franchising and  direct contract were provided to assess the
degree to which contractors were operating under a franchise agreement
with governmental units, whereby the city and county allowed for extended
agreements covering specific geographical areas.
      The ]ast definitional area which required clarification was the expla-
nation of the number of days  in the week which the  contractor collected.
The intent in this question was to arrive at the number of days which the
contractor had trucks out  on  routes collecting.  Thus,  if a. contractor
worked a half day each on Saturday and Sunday, he would be defined as
working a six-day week.
      While the above issues  dealt primarily with the content and wording
in several  questions, the review process indicated a further problem area
which had to be addressed.  It was considered essential that the question-
naire be designed in such  a manner as to provide a method for verifying
                                                                      •
the responses of the contractors to certain key questions.  The approach
to this problem was the design of consistency checks at various points in
the questionnaire which  solicited identical information  in different ways.
For the critical issue of fleet sizes, three question techniques were
employed.   First, the contractor was asked his total compactor and non-
compactor fleet sizes and  later he -was asked to delineate the number of
each type of truck he had.   Still later,  the contractor was asked how many
trucks were out collecting, in maintenance, or being held in reserve.  Field
experience proved that this method  was extremely effective in gathering
accurate information on trucks.
      Furthermore,  since other variables, such as  employees and tonnages.
are highly correlated with the number of trucks,  additional consistency
checks were incorporated  within the document.  The following are illustrative
                                   2. 11

-------
      •     The ratio of the total employees out collecting and
            helping to the total number of trucks out on the routes
            was compared with the average normal crew sizes on
            the contractors' trucks.
      •     The total tonnage  collected by a  contractor was  compared
            with the capacity of his fleet.
In all, some 23 internal consistency checks  were designed for the question-
naire -which, in addition to the above variables,  dealt with responses on
collection frequencies,  types  and numbers of customers,  related business
activities,  and specialized equipment.
      The comments, revisions, and suggested improvements in both the
format and the content of the draft were incorporated into the overall design
of the questionnaire.  The revised document then served as the pretest
instrument which was initially tested among large and small contractors
in Los Angeles,  California; San Francisco,  California; Salem, Oregon; and
Chicago, Illinois.   The primary purposes of this initial pretest were to test
overall concepts and contents, to ensure that the questions were  understood
and relevant to the respondent, and to ascertain the data availability for
all types of respondents. As  a result of this effort, further  revisions were
made preparatory to a full-scale pretest effort.
      The final pretest  effort  was conducted in March of 1970 and was per-
formed in 13 Standard Metropolitan Statistical Areas  (SMSA's) in four
Bureau of the Census regions.  In all,  108 interviews were  completed in
Bridgeport,  Connecticut; Boston,  Massachusetts;  Providence, Rhode Island;
Rochester,  New York; Albany-Schenectady-Troy,  New York; Louisville,
Kentucky; Charleston, West Virginia; Charlotte,  North Carolina; Greensboro,
Winston-Salem,  North Carolina; Washington, D. C. ; Memphis, Tennessee;
and Miami, Florida.
      The results  of these interviews,  while indicating the final refinements
in the survey document, provided valuable insight into some of the problems
and procedural difficulties which would be encountered during the actual sur-
vey.  Methods for resolving these problems were  formulated during the pre-
test activity and became part  of our interviewers' training program and
                                   2. 12

-------
interviewing manual.  Examples of some of the lessons learned are as

follows:

      •    An introductory letter from NSWMA prior to contact by
           the interviewer was essential

      •    A  strong statement of the purposes  of the study and its
           importance to the private contractor was necessary.

      •    Assurances of complete anonymity were required.

      •    Appointments to meet with the respondents were
           essential and the interviewer had to express a will-
           ingness to go anywhere including breakfast diners,
           coffee shops, the landfills,  and the  respondents' homes.

These techniques assisted in ensuring an extremely high response rate.

      Thus, by the end of the first year's effort, a completely field-tested

and final survey document had been prepared and  an interviewers' manual

had been designed.
                                  2. 13

-------
SAMPLE DESIGN
      The objective of the sample design for this research was to provide
a systematic method for  surveying private solid waste contractors to obtain
an accurate profile of the solid waste industry.  As with any sampling plan,
the size of the sample had to be determined and the method of selecting the
sample had to be developed.  Both of these tasks required some knowledge
about the population being sampled in terms  of the overall size of the uni-
verse and of the important parameters to be measured. At the start of this
research, there was no firm estimate of the former and only reasonable
estimates of the latter.   Thus,  the major efforts in the design phase of the
sampling procedures "were to develop an estimate of the total number of
solid waste contractors in the  United States and to refine the assumptions
about the important parameters to direct the method of sample selection.
List Development
      As noted in the introduction, one of the difficulties associated with
this industry was the lack of a precise delineation and listing of the firms
engaged in solid waste  activities.  Since any sampling plan is highly dependent
on the size of the universe to be studied, the initial phase of the sampling
design period had to be concerned with the development of such a list.  In
the gathering of the master list of all private contractors throughout the
country,  three primary sources were used:
      •     the telephone yellow page directories  from all cities  in
            the country;
      •     license and permit lists  issued by municipalities,  counties,
            and states;
      •     membership  lists of National Associations as well as local
            associations.
Yellow page information  was acquired from three sources: the Library of
Congress,  direct collection of yellow pages from  major SMSA's, and a field
                                    2. 14

-------
staff with locations throughout the country.  Permit and license list infor-
mation was gathered by requesting such lists from every city and county
seat in the country.   Over 3, 000 requests were mailed  throughout the
country, and of those places which had such lists, 600 answered the request.
The third source of  contractor names and addresses came from the member-
ship file of NSWMA  and the membership files  of other local associations
throughout the  country.
      The  lists from these sources were punched onto computer cards and
run through a program that matched/merged the data.  In this way,  exact
duplicative names and addresses were deleted.  After computer editing  was
performed, a manual check of the list was conducted to remove duplications
which did not exactly match due to change in spellings or placement of
words.  In all,  11, 330 names of private solid  waste contractors were
gathered for the definition of the universe.
Sampling Procedure
      The  sampling  procedure was highly  dependent upon the objectives  of
the survey, the characteristics of the population being sampled, and the
resources  available. Consideration of these factors led to a two-stage
sampling plan for this survey.  The first stage consisted of selecting a
sample of SMSA's and cities not within SMSA's from the total population
of these units.   The  second stage consisted of selecting contractors within
SMSA's or cities. SMSA's have been  used as  the primary sampling units
where  such are defined because many times a  contractor located in an
SMSA serves not only the city in which he is located but other parts  of the
SMSA as well.
     Drawing a sample as described  here constituted cluster sampling
since contractors were not randomly selected  from the  total population of
contractors,  but rather clusters of contractors (SMSA's or  cities) were
                                   2. 15

-------
randomly selected and a random sample of contractors was then drawn
from the selected cluster.  The rationale for using cluster sampling was
that it provided administrative efficiency by reducing the number of separate
geographical locations which had to be visited.
      There was  good reason to believe that many of the parameters of
the solid waste contractor population being estimated from this survey
were directly proportional to city size.  Of course,  not all of the large con-
tractors are  located in  large cities, but most of them are.  Therefore,
efficiencies in sampling could be realized from stratification by population
in SMSA's.
      Stratification by geographical region -was also desirable to account
for differences that may exist in different areas of the nation.   One differ-
ence is  the types of industries served by solid waste contractors, which in-
fluences the type and mix of solid waste collected.   The  regions into which
the population was stratified were the nine regions defined by the Census
Bureau  which were used by BSWM in their survey.  These regions are shown
in Figure 1.
      Sample Size
      Since two-stage sampling was being employed, both the number of
SMSA's and cities to  be visited and the number of completed contractor
interviews had to be determined.  Both sample sizes depended upon the
respective population sizes, the distribution  of the population characteris-
tics within SMSA's or cities and among SMSA's or cities, and the types of
estimates being made by the survey.
      The size of the first-stage population was known.  At the  start of the
study, there  were 229 SMSA's in the continental United States and 1, 401
cities of greater  than 5, 000 population that were not in SMSA's.
      There were many characteristics being measured  by this survey, and
little was known  about most of them.  The variability in some of them, may
have been greater from SMSA-to-SMSA or city-to-city,  and the variability
                                     2. 16

-------
                                                                  o
                                                                  LU
                                                                  a:
                                                                  to
                                                                  13
                                                                  e/)
                                                                  z
                                                                  LU
                                                                  u
                                                                  LL
                                                                  O

                                                                  <
                                                                  111
                                                                  X.
                                                                  13
                                                                  OQ
                                                                  LU
                                                                  o:
                                                                  D
                                                                  O
                                                                  LL
2.  17

-------
 in others may have been greatest within SMSA's or cities.  Furthermore,
 the magnitudes  of the variations were not known. Because of the lack of
 knowledge about characteristic variability, optimum sizes  could not be
 determine for either the primary sample or the  secondary sample.  How-
 ever,  estimates could be made of the upper limits on both  sample sizes.
      Cluster sampling  is the least effective means of sampling when the
 characteristics being measured are the  same for all contractors  within any
given SMSA or city and are different only for contractors in different SMSA's
or cities.  This is  so  since the sample must be spread over a large number of
SMSA's or cities to obtain an acceptable sampling error, whereas the  objective
of cluster sampling is to take an in-depth sample from only a few SMSA's or
cities.  Thus, the number of SMSA's or  cities  that had to be visited to assure
an acceptable sampling error under this condition was the maximum number
of SMSA's  required for this  sampling plan.
      Cluster sampling is the most effective means of sampling when the
characteristics  being  measured have the same distribution within all SMSA's
or cities; that is, when there is no difference from SMSA-to-SMSA or  city-
to-city.  Stratified sampling, however,  is  the least effective  under this con-
dition since an in-depth  sample in at least  one  SMSA  or city is  required to
obtain an acceptable sampling error; whereas, the objective of  stratified
sampling is to spread the sample over all SMSA's or cities.  Thus, if the
number of contractors had been calculated to provide an acceptable sampling
error under the assumption  of stratification under the worst condition, the
value obtained would be  the maximum number of contractors  required for this
sampling plan.
      Three types of  sample estimates were to be made  from the  questionnaire
data, and each type dictated a different  computation of sample size.  All three
were considered in the determination of the contractor sample  size to be used
 in this survey.
                                  2, 18

-------
      •     Totals or means of population characteristics (e. g. , total
            amount of waste collected, average number of employees
            per contractor).
      •     Proportions of population with given characteristics (Q. g. , the
            percent of contractors -who collect from single family houses).
      •     Ratios not expressed directly in terms of the primary  popu-
            lation variable, number of private contractors (e.g., per-
            centage of trucks which are compactors, or average number
            of men per  truck.
The sample size dictated by each type was  calculated and the implications
of using a sample smaller than the maximum  of these three is  discussed in
the following paragraphs.
      Calculation of Number of SMSA's
      The maximum number of SMSA's required to ensure an acceptable
sampling error for those characteristics of a  contractor which have a small
variance within SMSA was derived.  In making the calculation,  proportions
were the only type of measure considered since only characteristics with
measures of this type are expected to have small variances within  cluster.
The number of SMSA's  was calculated under the following assumptions.
      •     at least one attribute of the population is characteristic of
            50  percent  of the sample,  and
      •     ninety percent confidence  in a relative sampling  variation of
            _+ 10 percent in a 50  percent measurement (+  5 percentage
            points) is adequate.
Under  these assumptions, the  sample size was calculated by the formula
                       V2N
           n =
                  M
                  \aj
               N la/  +
where
      •C 7- 	  Q
          -2_ =  the coefficient of variation of the characteristic being measured
           X
        = -0. =  °-5  =  i
           P    0.5
                                  2.19

-------
      N = the total number of SMSA's = 229
      D = the acceptable error in the parameter estimate = 0. 1.
      a = the point on the distribution of the parameter estimator that
          10 percent error = 1,65 (in units of standard deviation)
      X = estimate of the characteristic being measured.
      S = standard deviation of the estimate.
      Substituting into the equation,  we obtained
            n=
                229
      Calculation of Number of Contractors
      The maximum number of contractors  required to ensure an acceptable
sampling error for characteristics with a small variance between SMSA or
city were then calculated.  The sample size dictated by all three types of
measures were calculated and the implications of selecting other than the
maximum number were considered.
      Means or Totals
      In calculating the upper limit on the sample size for estimating means
or totals of population characteristics,  assumptions also must be made about
the standard deviations of the characteristics being measured and the sampling
error that is acceptable.   For this plan, the following assumptions have been
made:
      •     No population  characteristic has a standard deviation greater than
            80 percent of its mean (e. g., the amount of solid waste collected
            by a single  contractor).
      •     Ninety-five percent confidence —  that the estimate of population
            parameter (e. g., the total solid waste collected by all contractors)
            is within 5 percent of the true value of the population parameter is
            adequate.
—   This means that only 5 percent of the time will the estimate deviate from
    the parameter by more than 5 percent.
                                 2.20

-------
 Under these assumptions, the sample size is calculated by the formula
                   V2N
            n =
where
          g
      V = — =   the average coefficient of variation with SMSA of the
          X     characteristic being measured over all SMSA's = 0.8.
      N = the population size = 11,330
      D = the acceptable error in the parameter estimate = 0. 05
      a = the point on the distribution of the parameter estimator that
          represents 5 percent error = 2 (in units of standard deviation).
Substituting into the equation, we obtain

                   0.64 x  11, 330	
            n =
                                2
                11, 330 ( °'05  \   +0.64
                 7 7^1
                 f'       »  1000
Therefore,  under the conditions stated, an upper limit of sample size was
1,000 contractors.
      Plots of sample size versus the error at both 90 percent and 95 per-
cent confidence for several values of the coefficient of variation are shown
in Figure 2.  The dotted lines are 90 percent confidence curves and the solid
lines are 95 percent confidence curves.  Figure 2 shows that,  at S = 0. 8X
and 95 percent confidence,  increasing the sample  size to 2, 000 would only
reduce the error from 5 percent to 3. 5  percent (i. e. ,  we would be 95 per-
cent confident that the estimate would not deviate from the true value by more
than 3. 5, rather  than 5. 0 percent).  Also, the  figure shows the sample  sizes
required if the coefficient of variation of the characteristic being measured is

                                      2. 2i

-------
   9000
   8000
   7000
   6000
   5000
0)
N
_
a
E
   4000
   3000
    2000
    1000
                                      95 percent Confidence
                                      90 percent Confidence  —	
              12345678

                         Error of Estimation (percent of X)

        FIGURE 2.2:  SAMPLE SiZE VS . ERROR

                                  2.22

-------
100, 200, or 300 percent rather than 80 percent of the mean (i.e., S =  l.OX,
2. OX* or 3. OX  rather than 0.8X).  A coefficient of variation of 100 percent
would produce a sampling error of 6 percent at 95 percent confidence as
compared with 5 percent at a coefficient of variation of 80 percent.  Coefficients
of variations of 200 and 300 percent  would produce errors of well  over  10 per-
cent at 95 percent confidence.  Errors of this magnitude are unacceptable.
Increasing the sample  size to 2,000  and  requiring only 90 percent rather
than 95 percent confidence,  the relative  error can be maintained at just
about 10 percent with a standard deviation of 300  percent.
      The sensitivity of the sample size to changes in the size of the  popu-
lation of solid waste contractors was also investigated.  Figure 3  shows the
results of this investigation.  For population sizes between 10, 000 and
30,000,  a sample of 1,000 is sufficient to obtain parameter estimates within
5 percent.   The range  in population  size corresponds to a variation in
number of  contractors  per million population from 50 to  150.
      Population Proportions
      The sample size  required to estimate the proportions of the contractor
population  that have a specified characteristic was calculated  under the
following assumptions:
      •     At least one attribute of  the population is characteristic of
            50 percent  of the sample.
      •     Ninety-five percent confidence in a  relative sampling variation
            of jf5 percent in a 50 percent measurement (2.5 percentage
            points) is adequate.
The first assumption was  made because for a given sample size, the absolute
sampling error is maximum for a measured proportion of 50 percent.  If the
sample size is sufficient to provide 95 percent confidence that the error is
within  +2.  5 percentage points for a  measured proportion of 50 percent, the
sample will be sufficient to provide 95 percent confidence that the error is
less than +2. 5 percentage points for  a measured proportion either greater
                                      2. 23

-------
    990
    980
    970
    960
0)
N

i/5
a
E
«J
V)
    950
    9MO
    930
    920
                10,000       15,000     20,000       25,000



                      Number of Contractors in Population
30,000
        FIGURE 2.3: SENSITIVITY OF SAMPLE SIZE TO CONTRACTOR

                    POPULATION SIZE WHEN MEASURING MEANS OR

                    TOTALS

                                    2.24

-------
than or less than 50 percent.   For example, the error associated with a 20 per-
cent or 80 percent measurement is 2 percentage  points (p is between 18 per-
cent and 22 percent  or q is between 78 percent and 82 percent) and the error
associated 5  percent of 95 percent measurement  is within 1 percentage point
(p is between 4 percent and 6 percent or q is between 94 percent and 96 per-
cent).
      The determination of the sample size necessary to  estimate proportions
of population characteristics  is a special case of the determination of the
sample size for the  means or totals of population characteristics.  Thus,
the equation presented earlier was used to calculate the sample size for
this case.  The  difference is  that the coefficient of variation of the pro-
portion is calculated by the equation
            v -
            V
                P    0.5
where
      P = the proportion of the population with the attribute = 0. 5
      Q = 1 - P = the proportion of the population without the attribute = 0. 5
      A coefficient of variation of 1. 0 placed more stringent requirements on
the sample than does a relative variance of 0.8.  In estimating proportions,
a sample  of 1, 500 would have been required under the assumptions  made.  If
a sample  of 1,000 rather than 1, 500 was used to estimate proportions, a
measurement of 50 percent would estimate the true proportion with 6 percent
(3 percentage points) with 95 percent confidence.  A measurement of 20 per-
cent or 80 percent would  estimate the true proportion within 2. 5 percentage
points and a measurement of 5 percent or 95 percent would estimate the true
proportion within  1. 3 percentage points.
      The sensitivity of sample size to contractor population size has been
determined and is shown  in Figure 4.
      Ratios
      If the unit being sampled is a contractor and estimates are to be made
of the ratio of two characteristics of the contractor, the sampling with respect
                                   2. 25

-------
1520
1500
1480
1460
1440
1420
1400
1380
            10,000
15,000
20,000
25,000
30,000
     FIGURE 2.4: SENSITIVITY OF SAMPLE SIZE TO CONTRACTOR
                POPULATION SIZE WHEN MEASURING PROPORTIONS
                               2.26

-------
to the two characteristics is essentially cluster sampling rather than  simple
random sampling.   For example,  in estimating the ratio of the number of
compactor trucks to the total number of trucks, a random  sample of trucks
is not selected from the total population of trucks for collecting solid  waste,
but rather contractors are selected and the trucks owned by these contractors
are counted.  In general,  sampling  in this  way requires a larger sample than
simple  random sampling to make  estimates of the same precision.  Thus,
the primary question was  whether a larger sample was needed to obtain an
acceptable estimate of ratios than was needed to make an acceptable estimate
of population proportions.
To calculate the sample size required to estimate ratios, the correlation
coefficient of the numerator and denominator  of the  ratio must be known  as
well as the  coefficient of variation of the numerator and of the denominator.
The smaller the correlation, the larger the variation of the ratio from con-
tractor to contractor and thus the larger the sample  size required to obtain
an estimate of a given precision for the total population  of  contractors.
Since the crew size for a given  type of truck is highly correlated with  the
type of  truck,  the ratio of crew size per truck should be  accurately  estimated
with a  relatively small sample.
      The assumptions made in calculating the sample size for ratios  were
as follows:
      *     The  characteristic in  the  numerator and  the characteristic
            in  the denominator of  the  ratio were both assumed to have a
            standard deviation equal to 80 percent of their  means.
      •     No two characteristics comprising a ratio have a  correlation
            smaller than 0. 2.
      •     Ninety-five percent  confidence that the interval between +_5 per-
            cent of the measurement includes  the actual value of the ratio
            is adequate.
                                     2. 27

-------
Under the assumptions, the sample size is calculated by the formula
            n
                          V2  -   2 P V V
                                       v"
where the  ratio being estimated is R -- -~—
      V  - the coefficient of variation of the numerator = 0. 8
       !X
      V  - the coefficient; of variation of the demoninator = 0.8
       P - tlie correlation coefficient of X and Y = 0. 2
and the remainder of the symbols arc as  defined previously.  The equation
                                                             2      2
for means  and totals is a special case of this equation with V    + V     2PV  V
                                                            x      y       x y
              2.
replaced by V .  The former expression   is the coefficient of variation of
the proportion among contractors.  If this value is  greater than the coefficient
of variance of 0.64 for means and totals, then a larger sample size would
be required to estimate the ratio with the Carrie  precision that a mean or
total is estimated with.  This  is,  in fact, the case for

            V  "'  )  V  *  - Y.fiV V      1. lc>2
              x      y        x  y

and a sample si'/c  of

                    11,330 x l.J.52       	         13, 052	
            11 " "if, ^30 x'.000625 rr."T52     ~   7.081 + 1.152'

              w  I, i>\)()

      If a sample of 1, 000 rather  than 1, 600 is used, the worst ratio will have
a precision of only  6.6 percent, with 95-percent  confidence.  The sensitivity

-------
of the sample size to population size will be similar to those previously shown
for  other  sample sizes.
      In conclusion, it was determined that the sample could be conducted with
1,000 interviews to make inferences about all types of population parameters
with a maximum error of 6.6 percent at 95-percent confidence if the stated
assumptions hold.  Many inferences  can be made with only a 5-percent error
at 95-percent confidence.
Sample Apportionment
      The first part of the sample apportionment was among Standard Metro-
politan Statistical Areas (SMSA's) and cities not in SMSA's.  The second part
was among  contractors within cities.
      As the first step in apportioning the sample among the SMSA's, all
SMSA's were classified by region and by size  of SMSA within region.  The
stratified population of SMSA's from which the sample was drawn is shown
in Table 1.  The number of SMSA's  drawn from each stratum, while main-
taining a proportionate sample of  124 SMSA's  is shown in Table  2.
* ^_^Region
PopulaUorf 	
50,000-
99,999
100,000-
249,999
250,000-
499,999
500.000-
1,000,000
over
1 ,000,000
TOTAL
1
4

12

3

3

J
23
2
-

4

10

5

6
25
3
-

10

3

5

2
ZO
4
3

7

11

6

2
29
5
-

,:3

10

7

6
!6
6
3

7

3

1

3
17
7
7

14

9

3

3
36
8
2

3

-

1

1
9
Q
-

4

10

3

7
24
Total
19

86

59

34

31
229
    Figure 2.5: DISTRIBUTION OF NUMBERS OF SMSA's BY POPULATION AND REGION WITHIN CONTINENTAL U.S.
                                   2.29

-------
^__Region
P Q p n 1 A t ion"^-^^
50,000-
99.999
100,000-
249,999
Z50.000
499,999
500,000
1,000,000
over
1,000,000
TOTAL
1

2

5

2

2

1
12
2

-

2

6

3

3
14
3

-

6

1

3

1
11
4

2

4

6

3

1
16
5

-

13

5

4

3
25
6

1

5

1

1

1
9
7

4

7

4

2

2
19
8

1

2

-

1

1
5
9

-

2

5

2

4
13
Total

10

46

30

21

17
124
               Figure 2.6: DISTRIBUTION OF SAMPLE SMSA's BY REGION AND POPULATION
      In drawing the sample of contractors within the selected SMSA's,  the
contractor list was also classified by region and SMSA size within region.
Tables 3 and 4 depict the distribution of contractors which existed at the
beginning of the study.
Population- 	 _
50,000-
99,999
100,000-
249,999
250,000-
499,999
500,000-
1,000,000
over
1,000,000
TOTAL
1

47

190

224

178

93
732
2

-

39

397

217

1176
1829
3

-

52

15

129

370
566
4

5

26

66

99

80
276
S

-

460

428

434

764
2086
6

55

84

200

61

436
836
7

12

76

235

138

152
613
8

1

121

-

39

265
426
9

-

40

145

236

1746
2167
Total

120

1088

1710

1531

5082
9531
             Figure 2.7: DISTRIBUTION OF CONTRACTORS IN SMSA's BY REGION AND POPULATION
                                      2.30

-------
—-^.Region
P o p ul atioiT^— ^_
SMSA
N ON -SMS A
TOTAL
1
732
76
808
2
1829
335
2164
3
566
66
632
4
276
105
381
5
2086
406
2492
6
836
558
1394
7
613
41
654
8
426
97
523
9
2167
115
2282
Total
9531
1799
11330
              Figure 2.8:  DISTRIBUTION OF CONTRACTORS €Y REGION AND POPULATION
      Once the distribution of the universe to various region and city size
strata had been accomplished, the next step was to apportion the  1, 000 sample
interviews.  As with the  selection of the number of SMSA's,  numbers of
contractors to be interviewed within each cell were determined based on the
proportions of the total number.   Tables 5 and 6 show this allocation.
""-—^^R ei; ion
Pooulr.Uoif — ~^_
50,000-
99,999
100,000-
2-19,999
250,000-
499,999
500,000-
1,000,000
over
1,000,000
TOTAL

1

4

17

20

16

8
65

2

-

3

34

20

104
161

3

-

6

1

10

33
50

4

2

4

6

7

5
24

5

-

42

37

38

67
184

o

5

7

18

5

39
74

7

3

8

20

11

12
54

8

1

11

-

3

23
38

9

-

3

13

21

154
191

Total

11

98

149

135

448
841
           Figure 2.9: DISTRIBUTION OF CONTRACTOR SAMPLE IN SMSA's BY REGION AND POPULATION
                                       2.31

-------
~~~---^Re«ion
? o p ^.1 at loTr- — _^
SMS A
NON-SMSA
TOTAL
1
65
6
71
2
161
30
191
3
50
5
55
4
24
9
33
5
184
36
"°
6
74
50
124
7
54
4
53
8
38
9
•17
9
191
10
201
Total
841
159
1000
             figure 2.10: DISTRIBUTION OF SAMPLE CONTRACTORS BY REGION AND POPULATION
      The final  sampling procedures involved the actual selection of SMSA's
within each cell.  For example, in Region!., the Northeast,  Boston,
Massachusetts is the only SMSA with a population greater than one million,
and thus all eight interviews were conducted in this city.  In Region 9, West,
on the other hand, four  out of the  seven SMSA's of greater than one million
population were  randomly selected.  The 154 interviews to be conducted in
this  cell were then divided proportionate to the number of contractors in the
four SMSA's.   Tables 7 through 15 show the SMSA's and non-SMSA's in which
interviewing was conducted, and the number of interviews in each site.  Con-
tractors within each city were randomly selected from the total list of con-
tractors which had been developed.
                                     2. 32

-------
  SAMPLE RELIABILITY
        As can be seen from the preceding section on the sample design, there
  •were two major factors which determined the reliability and accuracy of the
  sample estimates.  The first of these was the relationship of the sample size
  (1000) to the estimate of the total universe (11,330).  The second factor was
  the value of the coefficients of variation and the assumptions made about this
  value (equaled . 8) in the initial design.  Neither of these factors were known
  precisely at the start of the survey. Besides gathering the  questionnaire
  data, two other main objectives  of the survey were to gain insight into these
  two factors.
        To accomplish these  objectives, an innovative approach was taken.
  In each cell of the region/city size matrix,  one SMSA was randomly selected
  and a census or near census was performed.  Thus,  in 40 SMSA's, an average
  of 76 percent of the  contractors  were interviewed,  and in many cases, all
  contractors were interviewed.  Table 16 shows the SMSA's where  over-
  sampling was  performed and the percent of completion.  In  all,  1, 333 inter-
  views were conducted in the over-sample  SMSA's.
      The fmrposes of the over-sampling  were three-fold.  First, each inter-
viewer was instructed before entering each city to contact every name  on his
list to attempt to complete an interview.  At a minimum,  the interviewer was to
determine if the contractor was still  in the  solid waste business.  In addition,
in each over-sample SMSA,  the interviewer was to make  an exhaustive attempt
to determin-e the undercoverage of the existing list.  The  interviewer examined
license lists, the yellow  pages,  and any local association list.  Also, and of
importance,  he  showed his list to  contractors he interviewed  to determine if
they knew of any businesses which were not on the list.  As a result  of these
efforts,  an addition of 1 3 percent  of contractors was achieved.
      The second purpose of  the over-sample technique was to refine the
estimates of the totals and standard deviations of key variables.  Since the
derivation of the overall  totals and variances were to be constructed from the
complicated two-stage cluster design, increasing the number of interviews in
over a third  of the SMSA's would improve these estimates.  Thus,  in summary,
the over-sampling technique served to refine the information required to assess
the sampling reliability.
                                   2. 33

-------
                 Figure 2.11



DISTRIBUTION OF SAMPLE INTERVIEWS IN REGION
City
Size
1,000,000
500,000
to
1,000,000
250,000
to
500,000
100,000
to
250,000
50,000
to
100,000
NSMSA

TOTAL
No. of
3MSA
1
3
3
12
4
16


SMSA's
in
Samolc
1
2
2
5
2
2


Interviews
To Be Done
8
16
20
17
4
6



71
Cities
Boston, Mass.
Providence- Pa wtucket-
Warwick, R.I. -Mass.
Springfield -Chicopee-
Holyoke, Mass. -Conn.
Bridgeport, Conn.
Worcester, Mass.
Brockton, Mass.
Lawrence- Ha verhill,
Mass. -N. H
Lowell, Mass.
New Britain, Conn..
Waterbury, Conn.
Fitchburg-Leominster,
Mass.
Meriden, Conn.
Middletown, Conn.
Wallingford, Conn.



No.
of Con-
tractors
62
50
13
27
51
16
22
2
6
17
7
9
15
5



Completed
No. of
Interviews
8
10
6
4
16
4
6
1
2
4
2
2
5
1


71
                      2.34

-------
                 Figure 2.12



DISTRIBUTION OF SAMPLE INTERVIEWS IN REGION II
City
Size
1,000,000
500,000
to
1,000,000
250,000
to
500,000
100,000
to
250,000
50,000
to
100,000
NSMSA
Mo. ol
5MSA
6
5
10
4
--
30
SMSA's
in
Sample
3
3
6
2
--
12
Interviews
To Be Done
104
20
34
3
--

30
Cities
Philadelphia, Pa.
Pittsburgh, Pa.
Buffalo, N.'Y.
Albany -Schenectady-
Troy, N.Y.
Rochester, N. Y.
Jersey City, N. J.
Harrisburg, Pa.
Johnstown, Pa .
Trenton, N. J.
York, Pa.
Binghamton, Pa. -N. Y.
Lancaster, Pa.
Altoona, Pa.
Vineland-Milleville-
Bridgeton, N, J.
--
Middletown, N. Y.
Poughkeepsie, N. Y.
No.
of Con-
tractors
184
137
17
27
40
16
18
3
5
IS
6
9
2
5
--
13
6
Completed
No. of
Interviews
66
35
3
7
7
6
9
2
3
8
5
7
1
2
--
4
3
                      2.35

-------
Figure 2.12 (Cont'd)



     REGION  II
City
Size
NSMSA

TOTAL
No. of
5MSA



SMSA's
in
Sample



Interviews
To F>c Done






191
Cities
Secaucus, N. J.
Danville, Pa.
Huntington, Pa.
Lakewood, N. Y.
Middlesex, N. J.
Fairview, N. J.
Monticello, N. Y.
Cranbury, N. J.
East Rutherford, N. J.
Newburg, N. Y.







No. '
of Con-
tra ctoi-K
9
6
5
9
7
4
5
5
3
2







Completed
No. of
Interviews
3
5
3
1
4
2
1
1
1
2
1






191
         2.36

-------
                  Figure 2.13




DISTRIBUTION OF SAMPLE INTERVIEWS IN REGION III
City
Size
1,000,000
500,000
to
1,000,000
250,000
to
500,000
100,000
to
250,000
50,000
to
100,000
NSMSA

TOTAL
Nro. o
SMS A
2
5
3
10
--
40


SMSA's
in
Snmolc
1
3
1
6
--
2


Interviews
To r,e Done
33
10
1
6
--

5


55
Cities
Baltimore, Md.
Louisville, Ky. -Ind.
Greensboro- Winston-
Salem-High Point, N.C
Richmond, Va.
Charlotte, N. C.
Charleston, W. Va.
Wilmington, N. C.
Lexington, Ky.
Durham, N. C.
Roanoke, Va.
Fayetteville, N. C.
--
Fredericksburg, Va.
Goldsboro, N. C.

•

No.
of Con-
tractors
92
28
7
19
6
5
6
4
6
2
5
--
4
5



Completed
No. of
Interviews
33
5
2
3
1
3

1
1

1
--
2
3


55
                       2.37

-------
                  Figure 2.14




DISTRIBUTION OF SAMPLE INTERVIEWS IN REGION IV
City
Size
1,000,000
500,000
to
1,000,000
250,000
to
500,000
100,000
to
Z50.000
50,OOC
to
100, OOC

Mo. of
5MSA
2
6
11
7
3

SMSA's
in
Sample
1
3
6
3
2

Interviews
To Be Done
5
7
6
4

2


Cities
Miami, Fla.
Memphis, Tenn.
Jacksonville, Fla.
Tampa-St. Petersburg,
Fla.
Greenville, S. C
Columbia, S. C.
Augusta, Ga.
Orlando, Fla.
West Palm Beach, Fla
Chattanooga, Tenn.
Savannah, Ga.
Macon, Ga.
Huntsville, Ala.
Knoxville, Tenn.
Tallahassee, Fla.
Albany, Ga.
•

No.
of Con-
tractors
21
7
14
12
3
6
6
13
8
10
4
1
S
13
1
3

Completed
No. of
Interviews
5
1
2
4
1
1
1
1
1
1
2

1
1
1
1

                        2.38

-------
Figure 2.14 (Cont'd)




     REGION IV
City
Size
NSMSA

TOTAL
\To. of
JMSA
14


SMSA's
in
Sample
2


Interviews
To Be Done
9





24
Cities
Ft. Pierce, Fla.
Daytona Beach, Fla.















No.
of Con-
tractors
9
7















Completed
No. of
Interviews
2
7














24
        2.39

-------
                  Figure 2.15




DISTRIBUTION OF SAMPLE INTERVIEWS IN REGION V
City
Sixc
1,000,000
500,000
to
1,000,000
250,000
to
500,000
100,000
to
250,000
\To. of
3MSA
6
7
10
23
SMSA's
in
Sample
3
4
5
13
Interviews
To Be Done
67
38
37



42


Cities
Indianapolis, Ind.
Chicago, 111.
Detroit, Mich.
Akron, Ohio
Toledo, Ohio
Gary, Ind.
Grand Rapids, Mich.
Canton, Ohio
Lansing, Mich.
Peoria, 111,
Rockford, 111.
Flint, Mich.
Muncie, Ind.
Racine, Wise.
Kalamazoo, Mich.
Muskegan-Muskegan
Heights, .Mich.
Springfield, Ohio
No.
of Con-
tractors
70
225
196
122
15
22
201
144
61
23
13
36
6
17
IT
15
22
Completed
No. of
Interviews
6
46
15
15
3
3
17
13
7
3
10
4
2
--
4
3
5
                       2.40

-------
Figure 2.15 (Cont'd)




     REGION V
City
Size

50,000
to
100,000
NSMSA
\To. of
3MSA

--
30
SMSA's
in
Sample

--
14
Interviews
To Be Done

--
36




Cities
Hamilton -Middleton,
Ohio
Ann Arbor, Mich.
Decatur, 111.
Saginaw, Mich.
Champaign-Urbana, 111
Anderson, Ind.
Mansfield, Ohio
Springfield, 111.
--
Chilocothe, Ohio
Owosso, Mich.
Beloit, Wise.
Charleston, 111.
Galesburg, 111.
Michigan City, Ind.
Elkhart, Ind.
•
Goshen, Ind.
No.
of Con-
tractors
28
17
21
12
40
13
17
10

40
4
10
10
9
3
1
2
Completed
No. of
Interviews
4
4
3
2
6
3
4
2
--
6
4
4
4
3
3
1
2
        2.41

-------
Figure 2.15 (Cont'd)



     REGION V
City
Size


TOTAL
Mo. of
3MSA



SMSA's
in
Samnlc



Interviews
To Be Done



220
Cities
Warsaw, Ind.
Logansport, Ind.
Bunker Hill, Ind.
Kokomo, Ind.
Russia ville, Ind.
New Castle, Ind.











No.
of Con-
tractors
1
2
1
3
1
1











Completed
No. of
Interviews
1
2
1
3
1
1










220
          2.42

-------
             FIGURE 2.16

DISTRIBUTION OF SAMPLE INTERVIEWS IN
              REGION VI
City
Six.c
1,000,000
500,00
to
1,000,00
250, On
to
500.00

i nn nn
to
250 00


50,000
to
100,000

-

NSMSA



TOTAL
NTo. o
SMSA
3
1
3


7


3



25




SMSA's
in
.Sam pi o
1
1
1


4


1



7




Interviews
To Tic Done
39
5
18


7


5



50



124
Cities
Kansas City, Mo.
Omaha, Neb.
Duluth, Minn.
Topeka, Kans.
Cedar Rapids, Iowa
Fargo -Moor head,
N. Dak.
Sioux City, Iowa
Lincoln, Neb.
Sioux Falls, S. Dak.
Manhattan, Kan.
Iowa City, Iowa
Burlington, Iowa
Norfolk, Neb.
Fremont, Neb.
Grand Island, Neb.
Mason City, Iowa

No.
of Con-
tractor:'
59
29
29
6
22
14
35
4
16
31
4
18
8
10
12
32

Completed
No. 01
Intervicsvr;
39
S
18
1
2
1
3

5
8
4
5
8
9
7
9
124
                  2.43

-------
                   Figure 2.17




DISTRIBUTION OF SAMPLE INTERVIEWS IN REGION VII
City
Six.e
1,000,000
500.000
to
1,000,000
Z50,000
to
500,000
100,000
to
250,000
50,000
to
100,000
No. of
SMS A
3
3
9
14
7
SMSA's
in
Sample
2
2
4
7
3
Interviews
To Be Done
12
11
20

8

3

Cities
Dallas, Texas
Houston, Texas
Fort Worth, Texas
Oklahoma City, Okla.
Beaumont -Port
Arthur, Texas
Shreveport, La.
Tulsa, Okla.
Corpus Christi, Tex.
Lake Charles, La.
Lawton, Okla.
Ft. Smith, Ark.
Amarillo, Texas
Galveston, Texas
Lafayette, La.
Texarkana, Tex.
Tyler, Texas
•
Sherman -Denis on,
Texas
No.
of Con-
tractors
21
49
124
10
18
5
96
4
3
1
3
8
6
5
1
1
3
Completed
No. of
Interviews
8
4
10
1
1
1
15
3
1
1
1
1
1
2
1
1
1
                        2.44

-------
Figure 2.17 (Cont'd)



    REGION VII
City
Pi:-o

NSMSA

TOTAL
No. of
^\',^\

12


SMSA's
in
SnnmV

3


Interviews
To )V Don i.

4




58
Cities
San Angclo, Texas
Victoria, Texas
Muskogcc, Okla.
Wagoner, Okla.













No.
of Con-
tractor-
1
23
1
1













C o rv. p 1 o r c d
N o . o t
rv.U".'N'ov. ?
1
T
1
1












58

-------
                   FIGURE 2.18




DISTRIBUTION OF SAMPLE INTERVIEWS IN REGION VIII
City
Size
1,000,000
500,000
to
1,000,000
250,000
to
500,000
100,000
to
250,000
50,000
to
100,000
NSMSA

TOTAL
\To. of
SMS A
1
1
--
5
2
15


SMSA's
in
Sample
1
1
--
2
1
2


Interviews
To Be Done
23
3
--
11
1
9

47
Cities
Denver, Colo.
Salt Lake City, Utah
--
Colorado Springs,
Colo.
Ogden, Utah
Billings, Mont.
Ft. Collins, Colo.
Greeley, Colo.









No.
of Con-
tractors
114
27
--
21
8
1
13
4









Completed
No. of
fnt er views
23
3
--
7
4
1
7
2








47
                        2.46

-------
                  Figure 2.19




DISTRIBUTION OF SAMPLE INTERVIEWS IN REGION IX
City
Si^e

i AHA nnn
1 ,UUU,UUU

500,000
to
1,000,000


250,000
to
500,000

100,000
irt
250,000
50,000
to
100,000

NSMSA

NTo, of
-MSA

1


3



10




--

60

SMSA's
in
Snrnolc

4


2



5




--

7

_ _ . _
| Interviews
To Re Done

i 54


21



13




--

10

Cities
San Diego, Calif.
Los Angeles, Calif,,
Seattle, Wash.
San Francisco, Calif.
Phoenix, Ariz.
Portland, Oregon
Salinas -Monterey,
Calif.
Oxna rd - Ventura ,
Calif.
Bakersfield, Calif.
Tacoma, Wash.
Tucson, Arizona
Salem, Oregon
Reno, Nevada
--
Bremerton -Point
Orchard, Oreg.
Baker, Oregon
•
Pendlcton, Oregon
No,
of Con-
tractot-s
35
450
37
152
40
150
11
22
18
8
6
18
6
--
10
1
1
Completed
No. of
Interviews
7
11E
11
24
Z
19
3
5
3
1
1
2
1
--
3
1
1
                       2.47

-------
Figure 2.19 (Cont'd)



     REGION IX
City
Size
















TOTAL
Mo. of
SM.^A

















SMSA's
in
Sarnnlc

















Interviews
To He Done
















201
Cities
Burns, Oregon
Coos Bay, Oregon
North Bend, Oregon
Springfield, Oregon













No.
of Con-
tractors
1
2
1
1













Completed
No. of
Inter vi cwr.
1
2
1
1












201
         2.48

-------
       The third purpose of the over-sample was to provide a verification
procedure through which the estimates made from the sample data could be
checked.  Since the  sample interviews were to be randomly selected from
the list of all private contractors in each city,  a comparison  of the distribu-
tions of the sample data versus the over-sample data could be performed to
assess any sampling bias.  Such procedures were performed and supported
the randomness of the sample.
Definition of the Universe of Private Contractors
       At the start of this research, as mentioned,  the total  universe of pri-
vate solid waste contractors was  estimated to be approximately 11, 330.
Through  the interviewing process, changes in both the total number of con-
tractors  and the way the contractors were  distributed among  regions and  city
sizes occurred.  These  changes -were due to several factors and followed a
natural progression.  As the first step, the interviewer attempted to reach
the contractors on his list to set up an appointment.  If no number was listed
for a particular contractor in the white or  yellow pages, or by the operator,
and if no other contractor  knew of his existence, that contractor was listed
as not in business.   Second, if a contractor was reached but was not a solid
waste collector, he  was also listed as not in business.  Finally,  a contractor
in the field of solid waste was further screened according to the accepted
definition that he devoted at least 75 percent of his time in the field.   These
types of deletions comprised the major changes in the list.  In addition,
small changes were due to duplications on  the list where in one place the
name of the company was given,  and in another, the name of  the owner
appeared,  or where both a street address and a post office box number
appeared.
                                   2.49

-------
     TABLE 2.3



OVER-SAMPLE SMSA'S
SMS A
Los Angeles, Ca,
Chicago, III.
Portland, Ore.
Denver, Colo.
Tulsa, Okla.
Baltimore, Md.
Boston, Mass.
Kansas City, Mo.
Champaign-Urbana, III.
Duluth, Minn.
Omaha, Neb.
Salt Lake City, Utah
Bridgeport, Conn.
Colorado Springs, Colo.
Miami, Fla.
Dallas, Texas
Buffalo, N. Y.
Sioux Falls, S. D.
Jersey City, N.J.
Toledo, Ohio
Springfield -Chi.
Holy. -Mass. -Conn.
Rockville, III.
Salinas - Monteray, Ca.
Oklahoma City, Okla.
Lancaster, Pa.
Greensboro-Winston Salem, N.C.
Fitchburg, Leominster, Mass.
Contractors
450
225
150
114
96
92
62
59
40
29
29
27
27
21
21
21
17
16
16
15
13
13
11
10
9
7
7
Interviews
350
165
100
90
66
70
42
44
30
26
24
24
23
16
16
15
15
15
10
14
10
10
11
10
7
7
6
% Completed
78
73
66
79
70
76
68
75
75
90
83
89
85
76
76
71
88
94
62
93
77
77
100
100
78
100
86
        2.50

-------
                          TABLE 2.3  (Cont'd.)
                         OVER-SAMPLE SMSA'S
    SMSA
Memphis,  Tenn.
Reno,  Nevada
New Britain, Conn.
Charlotte,  N.C.
Augusta, Ga.
Topeka,  Kans.
Savannah,  Ga.
Lexington, Ky.
Lake Charles,  La.
Altonna,  Pa.
Billings, Mont.
Tallahassee, Fla.
Tyler, Texas
Contractor^   Interviews
     7
     6
     6
     6
     6
     6
     4
     4
     3
     2
     1
     1
     1
6
5
5
4
4
5
4
3
3
2
1
1
1
% Completed
     86
     83
     80
     67
     67
     83
    100
     75
    100
    100
    100
    100
    100
                                   2.51

-------
       The number of deletions were calculated by region and by city size
and the proportions were used tp project the total dimunition of the entire
universe.  Of the original list, it was estimated that 2,457 or 21. 6 percent
were no longer in business, leaving 8, 873  contractors.  However,  due to
the efforts in the over sampling phase of the study,  a 13 percent  addition to
the reduced list  was achieved, leaving a total of  10, 027 contractors.  Tables
17 and 18 show the estimated  distribution.
~"~ 	 ^_l\oKion
Po p ul LuTTT; — — __
50,000-
99,999
100,000-
2-19,999
250,000-
499,999
500,000-
1 ,000,000
over
1 ,000,000
TOTAL
1
31
171
129
86
62
479
2
-
39
351
105
1281
1776
3
-
56
15
125
405
601
4
10
46
70
79
45
250
5
-
362
374
430
848
2014
6
94
115
22S
29
554
1020
7
13
38
217
121
92
481
S
1
144
-
27
126
298
9
-
46
114
309
1043
1512
Total
149
1017
1498
1311
4456
8431
          Figure 2.20: FINAL ESTIMATED DISTRIBUTION OF CONTRACTORS BY REGION AND POPULATION
                                      2. 52

-------
---^Region
P o o ul n tioIT~--~^_
SYSA
NON-SMSA
TOTAL
1
47')
50
529
2
1776
248
2024
3
601
43
644
4
250
123
373
5
2014
387
!401
6
1020
583
1603
7
4H1
26
507
8
298
93
391
9
1512
43
1555
Total
8431
1596
10027
             Figure 2.21: FINAL ESTIMATED DISTRIBUTION OF CONTRACTORS BY REGION AND CITY
      As the final step in the interviewing process, those contractors in
business  were classified in terms of establishments.  For this  study, if
several companies were located at the same address and if the records
for all companies were combined, these companies were considered to be
one establishment.  On the other hand, if  companies  at the same address
were run separately and separate financial books were maintained, each
company was defined as an establishment.  To project to the total  universe
of contractors (i. e. , companies), individual questionnaires were filled out
for each company.  Tables 19 and 20 show the distribution of establishments
by region and city size.
      Thus,  the output of the first objective of the over-sample phase of
the study was a refinement of the estimate of total contractors to be 10, 027.
This is the number  to be used in  recalculating the reliability estimates.
                                    2.53

-------
" •—^J? e"lon
Po pal a ticm-^-^_
50,000-
99,999
100,000-
249,999
250,000-
499,999
500,000-
1,000,000
over
1,000,000
TOTAL
1
27
150
113
76
54
420
2
-
34
308
92
1124
1158
3
-
4<
13
110
355
527
4
9
41
61
69
39
219
5
-
318
328
377
744
1767
6
82
101
200
26
486
895
7
12
33
190
106
81
422
8
1
126
-
24
110
261
9
-
40
100
271
915
1326
Total
130
892
1313
1151
3909
7395
Figure 2.22: FINAL ESTIMATED DISTRIBUTION OF ESTABLISHMENTS BY REGION AND POPULATION
' 1~~___Region
P o p ul a. tioiT~~~ ^_^
SMSA
NON-SMSA
TOTAL
1
420
44
464
2
1558
217
1775
3
527
38
565
4
219
108
327
5
1767
339
2106
6
895
511
1406
7
422
23
445
8
261
82
343
9
1326
38
1364
Total
7395
1400
8795
   Figure 2.23:  FINAL ESTIMATED DISTRIBUTION OF ESTABLISHMENTS BY REGION AND POPULATION
                                        2. 54

-------
      Derivation of Variance Formulas
      The second factor in the estimate of the levels of confidence and
 accuracy of the sample values involved the assumptions about the coefficient
 of variations  (S/X).  In this formula,"X" is the value of the variable being
 measured,  and can be a mean, a total, or a proportion, and "S" is  the
 standard deviation of the estimate.  The coefficient of variation V = S/X,
 is a measure of the dispersion of the sample data.
      To calculate the variance of the sample estimates (equals the square
 of the standard deviation),  two methods were employed.  The first method
 utilized a variance formula based solely on regional stratification.  That is,
 this formula assumes that contractors  were stratified solely by region,
 and then selected randomly within region; and does not take into account
 stratification by  city size or  cluster sampling within city size strata.
 This  derivation is given below:
      FORMULA 1:   VARIANCE  BASED ON REGIONAL STRATIFICATION
 Let
                          J.-L
      i =  1,	,  9  be the i   region
      n.  = number of sample  contractors in the  i   region
      j =  1,	, n.  be the j    contractor in the i   region
      x_ = value  of a parameter for the j   respondent in the i  region
      N.  = number of contractors in the i   region
      N = total number of contractors in the Nation
Then, the following  formulas hold for various estimates:
                           9        N-     ^
      x = national total = >      	—  \ "*
                                  n.
                                   i
      x - national mean -
                          N
                                   2.55

-------
         2
      V   = variance of the national total
       x
                     N.    / N.-n. \     n.
                    n.   In./  n.-l
                     '
         2
      V—   = variance of the national mean
       x
      The second method of calculation of the variance formula was derived
based on the overall two-stage stratified cluster sample design.  This
formulation takes into account all the sampling steps which are summarized
as follows:
      •     Stratification by region
      •     Stratification by city size within region
      •     Random selection of clusters within city size stratum within
            region.
      •     Allocation of contractors to  selected clusters proportionate
            to number of contractors in  clusters.
      •     Random selection of contractors within clusters.
Based upon this methodology, the following formula resulted:

          FORMULA 2:  VARIANCE BASED ON CLUSTER DESIGN
Let
      i = 1,  --- 9 be the i   region
      j = 1>  --- 6 be the j   city size stratum
      M.. =  number of cities in the j   city size  stratum in region i»
      m.. =  number of cities in sample from the j   city size
        J
            stratum in region i.
                                   2.56

-------
      N  ,  = number of contractors in the k   city in the i   city
       ijk                                        y
             size stratum in region i.

      n..,  = number of contractors sampled in the k   city in the
       IJ     th
             j   city size  stratum in region i.


            M..
             ij
      N   = £     N..,  =  total number of contractors in the i
        i    ^-1                                    th
                         city size stratum in the i   region.
      	      N..
      N..    =  -r-p	   = average number of contractors per city in
                 ii      ,,   .th  .,    .    ,    ,    .   ,,   .th
                  J      the j    city size  stratum in the i   region.

               N..,
      W.., =   -
                N..


                                                th
      x. .,  =  total number of trucks  for the  S.   sampled contractor
       1J      -   ,u  ith   -,  •   4-v,   -th  ..    .     .   ,    .   .,   .th
              in the k   city in  the j   city size stratum in the i   region.
Then,
                             n..
                   r   i      f    x    i
      f    _ 1N      	i	 >       iikjf    = total number of trucks
       ijk    ijk  L n..,    * - 1     J   J               ,
                      ^                      for the k   city in the
                                             j   city size stratum in
                                              .th
                                             i   region.
                          m..
ij     iJ   L^	  ^      X4lk
           m^   v - i      XJK
                                   --i
                                      -1
      x.. = M..       1      r               = total number of trucks for
                    ij   k = 1      J         the j   city size stratum in
                                             .,   .th
                                             the i   region.
                                      2. 57

-------
      x.  = X -  x.. =; total number of trucks for the i   region
     9
  = £   x.
                  ~ total number of trucks for the nation.
To calculate the variance formula, a multi-step process is required and is

as follows:
            =  T    ff      ~ variance of total number of trucks in country.
         x    ~  ,    x.                                                 y
               1— I      1
               —"A      J.
        22                                            t
      o     -  D   /T   ..  = variance of total number  of trucks in i
         x.   j = i     xij
                            region.
a
              N    °     - variance of total number of trucks in the j
                 ij   ~
                       ij    city size stratum in region i.
X. .
IJ
m. .
i r ( w
Mijmij k=l "-
2 ~\
) cr2
x.
      = variance of the average number of trucks per contractor

        in the j   city size stratum in region i.
       2       M.. - m..

       'c    =   (M..) (m..)
                                    m..
                        -1	  r    (W...   x...
                        i..-l  tin      ijk    ijk
                         -I T    IV*~ 1
:..,   - x.. )
  -     ij
                                   Z.58

-------
       -
where  x
           m. .
             1J
                  r  1J
              . .  =   IT
              ij   Lk=1
                 (W. .,  x. ... )
                           '
                               /
                               / m. .
                              /    ij
            _

and where   x..,

              J

                    £

                    - 1
                                 = average number of trucks per

                                       ,    ,   .  , th     .   .th
                                   contractor in k   city in j

                                     ...    ,   ,     .  .th
                                   city size stratum  in i   region.
M.. - m..
                           mij

                             J
                                                        V  ]
M.. m..
  ij   ij
                        m.

              K7-Dl£i
                            
-------
                            n..
                                                n..
                                                    n..
               = variance of the number of trucks per contractor
                 in the k   city in the j   city size stratum
                 in the i   region.
                  Within cluster  (city) variance!

Combining all of these terms  and making the appropriate substitutions, the
following results.
                        M..
                         ij
                        m..
..2 [ M.. - m..  I
1.1  \   IJ 	!]_/
   \   M..    /
                                                    k=l   x ijk
             »T       n..,
             N..,       nk
               i.l k
              «
                 m. .

mii 2
L^IL. r V
m. . n , n..,
ij k=l ijk
I N.., -n...
\ nk nk
* N.. '
                                                                           x
                                                                              ijkl -
      Calculation of Selected Statistics
      Based on these formulas, calculations of the coefficients of variation
can be performed for selected information in the questionnaire.  Since the
questionnaire data for  each question was cross-tabulated by the variable for
regions, Formula 1 can be used for all estimates.  Since the data was not
tabulated for each city, Formula 2 cannot be used, in general.  However,
                                    2.60

-------
since the data were also cross -tabulated by the tonnage and truck variables,
estimates of the variances for these two parameters can be made on a city-
by-city basis.  Thus, the information that follows contains estimates  for
a number of variables based on the regional formula and for tons and  trucks
based on the cluster formula.
REGIONAL FORMULA 1
    Q. 2:  Proportion of Firms Operating More Than One Company at
          its Location
          Yes = 14. 3%
          No  = 85.7%

           ap = . 010435
          V = . 010435
Thus, there is a 95 percent confidence that the proportion of firms operating
more than one company at its location is between 12. 2 percent and 16. 4
percent.
    Q. 2: Average Number of Firms  Operated at the Location

         x  = 1.22
        
-------
Thus, there is a 95 percent confidence that the proportion of contractors
collecting from single family houses is between 55. 3 percent and 61. 1
percent.

    Q. 8:  Average Number of Single Family Houses Collected by Those
          Who Collect Single Houses

          X  = 4222

         *X  = 113. 67
          V  - H3.67  =  >Q27
                4222
Thus, there is a 95 percent confidence that the average number of  single
family houses collected by those who collect single family houses is
between 3995 and 4449.

    Q. 14: Proportion of Contractors Collecting from Commercial
          Customers
          Yes  =  96.67%
          No   =  3.33%
           p   =  .0056
           V   =  .0056  = .005793
                 .9667
Thus, there is a 95 percent confidence that the proportion of contractors
collecting from single family houses is between 95. 55 and 97. 79.

    Q. 14: Total Number of Commercial Customers
          X  =  2,353,183
          X  =  329,731
          V  =  329,731  -  .14
              2,353, 183
                                  2. bZ

-------
Thus, there is a 95 percent confidence that the total number of commercial
customers served by the private sector is  between 1,693,721 and 3,012,645.
Q. 14: Proportion of Contractors  Collecting From Industrial
       Customers
       Yes = 60. 6%
       No  =39.4%

        'p  ='015

       V   = i£ii  = .025
              .606
Thus, there is a 95 percent confidence that the proportion of firms col-
lecting from industrial customers  is between 57.6 percent and 63.6 percent.
Q. 14: Average Number of Industrial Customers Collected  by
       Those Who Collect Industrial Customers
       x  =61.5
       
-------
     Q. 20: Total Number of Trucks
           x  =  61,656
          
-------
Thus,  there is a 95 percent confidence that the total number of tons collected
by the private sector is between 608, 866 and 741, 170.

       x  = total trucks = 62,588
       
-------
100 that it would be less than 2. 5 times the standard deviation.  In other
words, there is a 95 percent confidence that the true population value lies
between the sample estimate plus  or minus twice  the standard deviation.
       Thus, for the three estimates of total trucks, at the  95 percent level,
the following result:

       STRATIFIED SAMPLE
       TOTAL TRUCKS » 61,656^6888
       i.e.  between 54,768 and 68,544
 For this estimate, there is a 95 percent confidence that the true value is
 within 11.2 percent of the  sample.
       CLUSTER SAMPLE
       TOTAL TRUCKS = 62, 588 +_ 5643
       i. e.  between 56, 945 and 68, 231
 For this estimate, there is a 95 percent confidence that the true value is
 within 9o 0 percent of the sample.
       OVER SAMPLE
       TOTAL TRUCKS = 64, 070 +_ 4394
       i.e.  between 59,676 and 68,464
 For this estimate, there is a 95 percent confidence that the true value is
 within 6. 9 percent of the sample value.
       These results are excellent and follow the progression to be expected
 from using a gross approximation of the variance and then a more refined
 estimate using the actual design characteristics. Finally, the use of the
 over-sample data provides extremely close estimates due to the com-
 prehensive coverage of the universe.
                                    2.66

-------
INTERVIEWING TECHNIQUE
      The conduct of the pretest interviews revealed that the interviewing
requirements for this survey were significantly different from the norm.
First, it was clear that a. businessman-to-businessman approach was
necessary to establish the proper rapport with the private contractor.
Second, since the vast majority of the respondents were vitally interested
in their businesses and the solid waste industry, the interview was facilitated
by having an interviewer knowledgeable in  the field,,  Third, since the in-
formation requested •was technical in  nature, interviewers who understood
concepts such as maintenance,  crew sizes, and routing, for example, were
needed.  Fourth, due to the complexity of the information required and to
the numerous internal consistency checks,  a high level interviewer was
required.  Finally,  since contractors were dispersed within an SMSA as
well as within a region, there was a need for interviewers who were willing
to travel and work at nearly any hour  of the day and on weekends.
      These  criteria dictated the selection of a highly unique interviewing
staff for  this survey.  In addition,  since  the contemplated interviewer training
program was designed to be extremely comprehensive and cover a period of
one week, the necessity for limiting the number of training sessions was
paramounto   This latter condition implied the existence of an interviewing
staff willing to travel over  extensive areas of the country and for extended
periods.   In addition,  it precluded the creation and training of interviewing
staffs throughout the country.  Thus,  the preliminary set of interviewer
selection criteria were as follows:
      •    Willingness to travel for two week to two month periods.
      •    Familiarity with trucking  and maintenance concepts.
      •    Some knowledge of and familiarity with interviewing
           technique So
      •    Ability to establish  rapport with the respondents.
To meet these characteristics,  a staff of retired military men was hired.
Each of these men had had recruitment interviewing courses, some knowledge
                                   2. 67

-------
of machinery concepts, and were  old enough to portray a business-like
approach.  Finally,  all were used to extensive traveling and were enthused
about the opportunity to travel and to get involved in a new industry.
      During August and September  of 1970, recruitment of interviewers
took place and four men were selected from a total of fifteen applicants.
Once the men were chosen, a one week training course was conducted by the
project staff with participation on the part of the BSWM.  The objective of
this  training period was to thoroughly familiarize the interviewing  staff with
not only the questionnaire, but also  with the field of solid waste management.
The  following is the outline of training sessions:
                  INTERVIEWER TRAINING OUTLINE
                          September 21, 1970
      Morning:
        1.   Introduction to study,  its purpose  and goals
        2.   Introduction of supervisory personnel
        3.   General discussion of questionnaire
        40   Introduction to equipment
      Afternoon:
        1.   Run through on entire questionnaire by instructor
        2.   Interviewer practicuum
        3.   Introduction to sampling procedures
      Evening Assignment: Read interviewer's manual
                           September 22, 1970
      Morning:
        1.   Quiz on the questionnaire, using incorrectly filled out  documents
        2.   Question and Answer  session on interviewer's manual  and
            questionnaire
      Afternoon:
        1.   Review of land disposal site investigation report
        2.   BSWM film  on landfill standards,  and presentation by BSWM
        3.   Question and Answer  session on land disposal site investigation
      Evening Assignment: Review equipment types and land disposal site
                           investigation report
                                   2.68

-------
                          September 23,  1970
      Morning:
       1.  Quiz on land disposal site investigation form and equipment types
       2.  Discussion of sampling problems
       3.  Second practicuum
       4.  Appointment and call-back procedures
      Afternoon:
       1.  Edit and coding procedures--emphasis on daily edit on-site
       2.  Procedure for reporting data to office
       3.  Trip to landfill
                      September 24 and 25, 1970
       1.  Actual practice interviewing under staff supervision.
The training  received  by the interviewers was highly effective as evidenced
by the extremely low refusal rate within the respondent group,  the often
reported after hours discussions between contractors and the interviewers,
and the high praise from the private solid waste  industry in terms of their
impression of the interviewers.
      Actual field interviewing began in the last week of September,  1970
and ended in May,  1971.   Interviewing was  conducted on a region-by-region
basis so  that field  and  quality control were  given schedules to be  met.  A
capsule summary of the procedures is as follows:
      •     Just prior  to the completion of one region,  the sample in the
           next region was selected.  A letter from NSWMA was sent to
           each potential respondent outlining the reasons for  and purposes
           of the study and requesting cooperation.
      •     Interviewer schedules were designed in such a manner as to
           minimize travel costs and to equalize the time on the road for
           each man.
      •     Completed interviews were mailed daily to the office  and imme-
           diately checked for completeness and internal consistency.
                                  2.69

-------
While in the field, each interviewer was responsible for conducting inter-
views, setting up the next day's appointments, and for  checking each day's
work.  The first checking procedure was designed to ensure that no major
errors were in the documents, and if there were, to be able to contact the
interviewer before he left the city of region.  In this manner,  interviewers
were able to recontact respondents while the information was still fresh
in their minds.
      Although the highest level of confidence and trust had been placed in
this type of interviewer, extensive verification procedures were carried out
to ensure the validity of the questionnaires.  A randomly selected  sample
of ten percent of all  respondents were contacted by telephone to ascertain
not only if the interview had been  conducted, but also to check the  responses
to several key questions in the document.  In addition,  every respondent
was mailed a post-card on which he was asked to indicate whether he had
been interviewed.  As a result of these procedures, it  was concluded that all
interviewing had been  completed as  reported.
                                   2.70

-------
TABULATION PROCESSES
      From the initial acquistion of data in the completed questionnaires,
several steps had to be undertaken to prepare meaningful tabular outputs
upon which analyses could be performed.  The questionnaires had to be
edited and coded, the data had  to be keypunched, and then tabulation plans
had to be  derived.  Each of these phases leading to  computer tabulations
involved manual procedures so extreme quality control techniques were
required.
      One determinant of an accurate survey is the  completeness and care
with which the editing and coding procedures are handled.  The major pur-
poses of editing and coding are to:
      •    Make entries clear, consistently uniform, and comprehensive.
      •    Reduce "no answers" or incomplete replies with the help of
           other information found elsewhere in the document.
      •    Identify areas  where additional information is required of the
           respondent.
      •    Provide instructions to prepare the document for computer
           editing.
To accomplish these objectives, an editing and coding manual was designed
which contained instructions which outlined the type and format of informa-
tion to be  contained in the  responses to each question.  The manual specified
each step to be followed by the  editors in examining each question,  and in
relating responses of groups of questions.
      One major function of the editing  which was performed  on each docu-
ment was  to check for complete answers and answers to every applicable
question.  An additional function was to ensure internal consistency in the
answers to several questions.  For example, if a contractor  served single
family houses, he should have  responded to the question on curb service.
Or, if he had indicated that he  was  also involved in disposal activities, then
he should  have answered the section on disposal.  A further function of the
                                  2.71

-------
editorial staff was to perform range checks on the data to flag suspicious
data.   For example, a respondent reporting a crew size  of over four men,
per truck would be held out,  or a respondent who indicated he collected more
than twenty tons per day with only one truck would be closely examined.
Thus,  the editing procedures were another method for checking for inadvert-
ent misrepresentation of data.
      The editing process was  performed by  staff members who were
thoroughly trained in terms of  the questionnaire document and the editing and
coding manual.  As questionnaires were received in the office, each  docu-
ment was immediately edited.  In those  cases of errors or missing data which
were not major enough to require the field interviewer to recontact the re-
spondent, a telephone  contact by the editor was performed.
      From the initial acquisition of the survey data as edited and verified
questionnaires,  the keypunch and computer editing and verification procedures
began.  Keypunch specifications  were written for the survey questionnaire
and corresponded to the coding instruction manual.   In accordance to standards
of the data processing industry,  the specifications included  alpha and numeric
codes, left or right columnar justifications,  and card location characteristics.
A thirty percent keypunch verification was initially performed, and than a
100 percent verification was performed  on a  sample of the data.
      The next operation was card cleaning and machine  editing.   As part
of this process, every column  was checked to ensure that only valid codes
appeared.  Furthermore, logic checks were  performed to ensure that the
respondent answered only those questions which were relevant to his com-
pany.  The final steps in the machine editing process were the performance
of consistency checks  and range  checks.  Primarily these checks were
those which were too complicated or time consuming to perform in the man-
ual edit.  An example  of these  include checking the sum of all of the various
types of trucks against the total given in another question.   Finally, the
card deck was passed through the computer  and all the punches were counted
by column to obtain a binary count.  This check was the last proof that
only valid codes existed in the  card deck.

                                  2. 72

-------
       Once these cleaning processes had been completed, the card-to-tape
operation was performed whereby the data were constructed  according to the
tabulation specifications.  These specifications included a detailed design of
each table in the report, how it was to be derived and presented.  The deriva-
tion procedure required the specification of the card column  and punches which
were to be combined to serve as the basic data.  The total tabulation process
and table  format consisted of two types of tabular outputs from which analysis
began.  The first of these were straight tabulations which were  frequency
counts and percentages for the total sample.  The  second -were cross-tabula-
tions which showed how the responses varied as a  function of several basic
demographic or descriptive variables.
       The design of the cross-tabulation variables consisted of two  steps:
determining which variables to use and determining how the  selected variables
should be presented.  In the first case,  several potential variables were con-
sidered and the following were selected:
       •     Region of the country
       •     SMSA size
       •     Size of contractor in terms of tons collected
       •     Size of contractor in terms of number of trucks
       •     Size of contractor in terms of total employees
       •     Contractors' mix of collection
The first  two variables are demographic in nature and were  designed to
assess variations in contractor characteristics due to regional and city size
differences.  The next set of three variables provide a means of assessing
differences  in operations resulting from several proxy variables for  size.
Finally, the last cross-tabulation variable was considered desirable to assess
the effects of different types of customer mixes on the methods  of operation.
                                   2. 73

-------
      When designing the categories to be used in the cross-tabulation vari-
ables, it is necessary that a sufficient number of respondents appear in each
break to allow for statistical comparisons.  To accomplish this task, pre-
liminary straight tabulations of the last four variables were performed to
assist in this design.  These tabulations were examined in the light of pro-
viding significant and meaningful breaks.  As  such, the following classifica-
tions  resulted:
           TOTAL
           ..  All (1000 respondents  =
           REGION OF THE COUNTRY
           ..  Northeast           71
           .  „  North Atlantic      191
           .  .  Mid-Atlantic         55
               South Atlantic        33
           ..  Mid-West          220
           .  .  North Central       124
               South Central        58
               Mountain            47
           ..  West               201
           CITY SIZE
           .  .  Over 1, 000, 000     445
           .  .  500,000-1,000,000  131
           ..  250,000-499,999    149
           ..  100,000-249,999    101
           ..  50,000-99,999       15
           ..  Non-SMSA          159
100 percent of the sample)
respondents
respondents
respondents
respondents
respondents
respondents
respondents
respondents
respondents

respondents
respondents
respondents
respondents
respondents
respondents
 7. 1 percent
19. 1 percent
 5.5 percent
 3. 3 percent
22.0 percent
12.4 percent
 5.8 percent
 4.7 percent
20. 1 percent

44.5 percent
13. 1 percent
14.9 percent
10. 1 percent
 . 15 percent
15.9 percent
                                  2.74

-------
     NUMBER OF TONS COLLECTED IN AN AVERAGE DAY
          1-6 tons            255 respondents     =  25.5 percent
          7-12 tons
          13-24 tons
          25-49 tons
          50-99 tons
          100-249 tons
          250-499 tons
          500-999 tons
          1000 or more tons
168 respondents
183 respondents
123 respondents
110 respondents
 92 respondents
 28 respondents
 16 respondents
 11 respondents
16.8 percent
18.3 percent
12.3 percent
11.0 percent
 9.2 percent
 2.8 percent
 1.6 percent
 1. 1 percent
(Note:  14 respondents or 1.4 percent would not answer this question)
•    NUMBER OF TRUCKS
          1 truck
          2-3 trucks
          4-5 trucks
          6-9 trucks
          10-19 trucks
          20-49 trucks
          50 or more trucks
258 respondents
317 respondents
142 respondents
127 respondents
 99 respondents
 41 respondents
 1 6 respondents
     NUMBER OF EMPLOYEES
          1 employee
          2-3 employees
          4-5 employees
          6-9 employees
          10-19 employees
          20-49 employees
          50 or more
          employees
191 respondents
275 respondents
128 respondents
146 respondents
109 respondents
 83 respondents

 38 respondents
25.8 percent
31.7 percent
14.2 percent
12.7 percent
 9.9 percent
 4. 1 percent
 1.6 percent

19.1 percent
27.5 percent
12.8 percent
14.6 percent
10. 9 percent
 8.3 percent

 8.3 percent
(Note:  30 respondents or 3. 0 percent did not answer this question)
                             2. 75

-------
           MIX OF COLLECTION
                100% Residential     37 respondents
                80-99% Residential  183 respondents
                60-79% Residential  140 respondents
                40-59% Residential  108 respondents
                20-39% Residential   66 respondents
                1-19% Residential    52 respondents
                100% Commercial
                or Industrial        414 respondents
=   3.7 percent
=  18.3 percent
=  14.0 percent
=  10. 8 percent
=   6. 6 percent
=   5.2 percent

=  41. 4 percent
Every question in the survey document was cross-tabulated by these vari-
ables and this provided significant insight into some of the causes for varia.
tions in methods of operation.
                                  2. 76

-------
 DATA CONSIDERATIONS
      The following chapters contain a detailed analysis of the survey re-
 sponses in terms of the total sample and of various  sub-populations.  The
 purposes of this  analysis are to provide a profile of the private sector and
 to describe the contribution of the private sector in  collecting the nation's
 solid waste.   To accomplish the latter objective, information about the pri-
 vate sector had to be compared with overall national statistics.  Thus, for
 example,  to estimate the proportion of the nation's single family residences
 served  by the private sector, an estimate of the total number of single
 family housing units was  needed.   Such estimates were obtained through  the
 gathering of secondary data from the following sources:  Statistical Abstract
of the United States,  1970,  Bureau of the Census; General Housing Character.
istics - United States Summary, 1970, Bureau of the Census; 1968 HUD
Statistical Yearbook, U. S.  Department of Housing and Urban Development;
Country Business Patterns, 19&9>  U.S. Department of Commerce: United
States Summary - U.S.  Census of  Population:  1970,  Bureau of the Census;
Housing Authorized by Building Permits and Public Contracts,  1970 Annual,
U.S. Department of Housing and Urban Development.
      These sources were then used to assess the private sector's contribu-
tion in the collection of various categories of customers.  For example,  in
estimating the proportion of the nation's population served by the private
sector,  several steps were involved.  First, since the Census data on hous-
ing characteristics are reported in terms of housing units, and the data for
this study are given in terms of customers or housing structures,  conver-
sion factors between units and structures had to be established.  For  single
family homes, this factor is one since the number of units equals the  number
of structures.  For 2-4 unit apartment buildings,  the number of structures
was multiplied by three to arrive at a unit estimate.  Finally,  it was deter-
mined that the average number of units in buildings of 5 or more units is
approxi-mately 12.  Through the use of these conversion factors, the per-
centages of total customers and of total housing units collected by the
                                  2.77

-------
private sector were computed.  Furthermore, to determine the number and
proportion of persons collected by the private sector,  the number of housing
units was multiplied by 3. 1, which is the national average of population per
housing unit.
      There are,  in addition,  two issues which merit some discussion in
this  methodology section.  First, part of the  questionnaire deals with the
disposal and recovery activities of the private sector of solid waste manage-
ment.  The intent of this survey was to interview solid waste  collectors and
to assess, of those who collect wastes, what  their disposal and recovery
activities involve.  On  the other hand, the survey design specifically ex-
cluded those in private industry who handle solely the  disposal function or
are only involved  in salvage and recovery.  There are a substantial number
of private firms engaged in these fields, and  their scope is not determined
by this study.  Thus, the data base on disposal and  recovery in the following
material is limited to those activities performed by collection contractors,
and does not reflect the total private contribution.
      The second  issue again is  related to the basic survey design and the
definition of the universe to be sampled.  The data  obtained on the private
sector's collection function, in terms of the amounts of wastes and the
types of wastes, are also limited to those firms  primarily engaged in the
solid waste industry.  Thus,  specifically,  excluded from the study are those
firms which,  as adjuncts to their primary businesses, haul their own waste
products such as construction material, agricultural wastes,  etc. and those
companies or individuals who collect solid wastes on a "part-time" basis.
The  survey data,  while reliably estimating the total residential,  commercial,
and industrial wastes collected by the full-time solid waste management
industry, do not accurately reflect these other types of waste categories^
Therefore,  although the total wastes collected by the full-time private
sector are estimated, as well as their shares of all residential,  commercial,
and industrial wastes,  the total waste generated in  the nation  cannot be ac-
curately estimated through the data in this  study.
                                   2. 78

-------
                          VOLUME OF WASTE

      The primary variables describing the private solid waste contractor
are the quantity of waste which he collects and the types of customers from
whom he collects.  The subject of this chapter is, therefore, a description
of the total wastes collected daily by the private sector.  Tonnage collected
is displayed by the major control variables appearing throughout this study
(size of contractor,  daily tonnage,  mix of collection,  SMSA size and region).
Per  capita waste disposal,  along with tonnages generated by residential,
commercial, and industrial sources  are also examined.
      This chapter is structured into the following subsections:
      •    Chapter Summary
      •    Total Volume
      •    Tonnage Per Contractor  by Daily Tonnage  Collected
      •    Daily Tonnage by Contractor Size
      •    Daily Tonnage by Mix of  Collection
      •    Daily Tonnage by Region and City  Size
                                   3. 1

-------
                            CHAPTER SUMMARY

      The private sector collects over 685,000 tons per day of all types of wastes.
Two-thirds of the refuse is commercial or industrial, 29 percent is residential and
the balance is "miscellaneous" refuse such as demolition wastes.  Based upon these
tonnages, the per capita daily waste collected is 8. 6 pounds of which 3. 9 pounds is
residential.
      Commercial refuse is collected by the majority of contractors, and comprises
the largest share of total tonnage.  Industrial  refuse, however,  accounts for the
most tons per customer.
      The relationship of trucks and manpower to daily tonnage indicates an
increased effectiveness  in the tons per truck and the tons per employee as daily
tonnage increases.  This is a result of the concentration of commercial and
industrial wastes among those collecting large tonnages.  There is also a heavy
concentration of total tonnage among the 1400  to 1500 contractors who collect over
100 tons per day. This  concentration of the total tonnage collected per day  among
15 percent of the contractors is  also consistent with  the concentration of truck
ownership.
      In terms of collection mix, contractors who collect a greater  proportion of
commercial and industrial tonnage collect the most tonnage per truck and man.
The high ratios among these contractors seem due, in part, to the high usage of
more automated and sophisticated collection equipment required in the collection
of industrial and commercial wastes.
      The contractors located in SMSA's of over one million account for over half
of the tonnage collected. Most of the tonnage  is concentrated  in the Midwest, West,
and North Atlantic,  with residential tonnage more concentrated  in the West, and
industrial tonnage in the Midwest.
                                    3.2

-------
TOTAL VOLUME
       The total volume of refuse collected by the private sector is 685,466
tons per day (Table 3. 1).  Of this total, 199, 132 tons or 21. 9 percent is
residential refuse; 230, 865 tons or 33. 7 percent is commercial refuse;
214,514 tons or  31.3 percent is industrial refuse; and the remaining 40,955
tons consist of miscellaneous refuse  such as construction and demolition
wastes.
                  NATIONAL ESTIMATE SHARE OF DAILY TONNAGE COLLECTED BY THE PRIVATE
                     SECTOR BY RESIDENTIAL, COMMERCIAL, AND INDUSTRIAL REFUSE

Number of Tons Collected By
Private Sector On Average Day
Share of Total Tons
Number of Private Contractors
Who Collect
Share of Total Contractors
Total Tons*
685,466
100%
10,027
100%
Residential
199, 13Z
21.9%
5,883
58.7%
Commercial
230,865
33.7%
9,651
96.3%
Industrial
214,514
31.3%
5,806
57.9%
             * Total ton* includes demolition and construction refuse, and all other reiu«*.
      In drawing conclusions from this data,  the  estimate of tonnage from
miscellaneous refuse such as construction and demolition wastes should be
considered a conservative projection.  Those few organizations who dis-
pose of their own wastes were not included in the  sample.
      Per capita collection by the private  sector  varies by the type  of cus-
tomer (Table 3. 2).   Industrial customers  generate the  largest number of
pounds  per day (1, 196),  dropping to 226 pounds per day for commercial
customers  (excluding apartments of five or more units),  and 16 pounds  per
day for residential  customers (single-family home, duplexes, and two to
four-unit apartments).  The  average pounds per day for all customers is 50.
                                     3. 3

-------
                                         TABLE 3.2
                 NATIONAL ESTIMATE - DAILY TONNAGE PER CUSTOMER COLLECTED BY THE
                 PRIVATE SECTOR BY RESIDENTIAL. COMMERCIAL, AND INDUSTRIAL REFUSE
                           Total Toi\s   Residential             Comme rcial              Industrial
                                                Apartmcnts-5 or     Commercial-
                                                 More Units     Excluding Apartments

NumberofTonsonAverageDay     635,466    199,132     45,872            134,993        214,514
Number of Customers          27, 357, OZ3  24,716,758    644,688          1,630,840        358,727
Tons Per Customer                 0.025      0.008      0.071              0.113          0.598
Founds Per Customer                 50         16        142                226          1, 196
Number of Stops               27,587,115  24,716,758              2,438,894               431,463
Tons Per Stop                     0.025      0.008                 0.095                 0.497
Pounds Per Stop                      50         16                   190                   994
        The amount of residential, commercial, and industrial refuse generated
 per  day  in the United States can be  estimated based on the national estimate
 of total tonnage collected by the private sector (Table 3. 3).   Given the  national
 total of residential,  commercial,  and industrial tons per day (and excluding
 miscellaneous  waste),  a daily per capita generation  of each type of  refuse can
                                         TABLE 3.3
                           NATIONAL ESTIMATE - PER CAPITA GENERATION OF
                          RESIDENTIAL, COMMERCIAL, AND INDUSTRIAL REFUSE

Residential, Commercial, and Industrial
Tons Collected by Private Sector on
Average Day
Share of Residential, Commercial, and Industrial
Customers Collected Nationally
Residential, Commercial, and Industrial
Tons Collected Nationally on Average Day
Percent of Total Tonnage
National 1970** Population
Refuse per Person Per Day
Total*
644,511
52.4%
878,581
73. 3%
203,211,026
8.6
Residential
199, 132
50. 2%
396,677
50.2%

3.9
Commercial
230,865
91.0%
253,698
91.0%

2.5
Industrial
214,514
94. 0%
228, 206
94.0%

Z.2
    *  Total does not include demolition and construction refuse, or other refuse.
   **  From  1970 Census
                                            3.4

-------
be calculated by dividing the total  United States population into the number
of tons.  This yields a per capita figure of 3. 9 pounds of residential refuse,
2.5 pounds of commercial refuse,  and 2.2 pounds of industrial refuse, or
8.6 pounds of residential, commercial, and industrial waste per person
per day.
      The private sector collects 52.4 percent of the total customers and
73. 3 percent of the total tonnage.  The  disproportionate share is due to the
high proportions of commercial and industrial collection and the  high volumes
experienced  there.
                                   3.5

-------
TONNAGE PER CONTRACTOR BY DAILY TONNAGE COLLECTED
      The average contractor collects 68 tons per day.  This results in
ratios of 14 tons  per truck and 9 tons per man.  These ratios vary widely
on the basis of the total daily tonnage the company collects.  For  example,
those companies  with daily  collection ranging from  1-6 tons in fact average
3. 5 tons per company, 2. 9  tons per truck,  and only 2. 3 tons per man.
These relatively  low rates are due to the large residential component (41.7%)
in the tonnage collected by this portion of the population (Table 3.5) and to an
equipment mix which is more oriented  toward the open truck (Table 5.20).
      Gross tonnage collected is,  of course,  a  primary variable in des-
cribing the contractor.  Neither number of customers nor number of trucks
enable the analyst to illustrate the full  scope  of a company's contribution.
Customer count is not adequate because a  residential customer cannot be
equated with a commercial  or industrial customer.  As we have indicated,
a typical residential customer  generates 16 pounds per day while an indus-
trial customer  generates  an average of 1196 pounds per day.  Thus,  in terms
of tonnage, the average industrial customer is  the equivalent of  75 residen-
tial customers.   Therefore, a  simple customer count does not fully describe
a contractor's position in the industry.   Truck  counts also misrepresent the
actual description of a contractor due to differences in equipment  capacities
and material handling techniques.  So,  tonnage collected is the most gener-
ally accurate variable.
      Those contractors who are largest in terms of customer and truck
count,  also collect the largest  daily tonnage.  Specifically, 14. 7 percent of
the contractors collect 100  or more tons per  day.  The profile of these
contractors reveals a lower percentage of both residential and commercial
tonnage than that found among smaller  contractors;  however, the larger con-
tractors handle a significantly  greater  proportion of industrial waste.  The
percentage of industrial waste  collected is  the most significant factor in
these contractors' overall share of market which includes 74. 7 percent of
all wastes collected by the private sector.  Evidence suggests these contractors
                                   3.6

-------
                                                   TABLE 3.1

                           NATIONAL ESTIMATE OF TONNAGE BY NUMBER OF TONS PER DAY
                                             IN THE PRIVATE SECTOR
Type of Tonnage
1-6
Total Contractors 2,636
Number of Tons Collected Per Day
7-12 13-24 25-49
1,726 1,
Total Tonnage* 8,911 15,766 31,
Residential 3,584
Commercial 3,463
Industrial 1,073
5,177 11,
6,926 12,
2,789 5,
*Total Tonnage includes demolition and
865 1,238
531 43,184
749 16,329
928 15,237
792 9,653
50-99 100-249
1,099 918
74,030 139,150
26,086 37,437
25,626 48,482
18,877 45,906
250-499
277
94,594
26.883
32,090
31,319
1000 or
500-999 more Total
161 HO 10,027
104,191 174,108 685,466
33,653 38,233 199,132
39,709 46,173 230,865
27,029 72,291 214,514
construction refuse, and all other refuse.
TABLE 3.5
PERCENT DISTRIBUTION OF TONNAGE BY NUMBER OF TONS PER DAY
IN THE PRIVATE SECTOR
Type of Tonnage
1-6
Distribution of Total
Contractors 26.3%
Distribution of Tonnage
Amont; Number of Tons
Total Tonnage 1 .3
Residential 1.8
Commercial 1.5
Industrial 0.5
Distribution of Tonnage
Within Number of Tons
Total Tonnage 100%
Residential 41.7
Commercial 40.3
Industrial 11.7
Other* 6.3
7-12
17.2%
2.3
2.6
3.0
1.3
100%
33.6
45.2
17.5
3.7
Number of Tons Collected Per Day
13-24 25-49 50-99 100-249 250-499
18.6% 12.3%
4.6 6.3
5.9 8.2
5.6 6.6
2.7 4.5
100% 100%
38.5 39.2
41.5 36.1
18.1 22.0
1.9 2.7
11.0% 9.2%
10.8 20.3
13.1 18.8
11.1 21.0
8.8 21.4
100% 100%
36.4 27.8
35.2 35.4
25.0 32.3
3.4 4.5
2.8%
13.8
13.5
13.9
14.6
100%
29.4
34.4
32.5
3.7
1000 or
500-999 more Total
1.6% 1.1% 100%
15.2 25.4 100
16.9 19.2 100
17.2 20.0 100
12.6 33.7 100
100% 100% 100%
33.6 22.7 29.1
38.8 27.0 33.7
25.4 40.9 31.3
2.2 9.4 5.9
* Other Refuse includes demolition and construction refute, and all other refuse.
                                                     3.7

-------
                                    TABLE 3.6
                    TONS PER TRUCK AND EMPLOYEE BY TONS COLLECTED PER DAY
                                IN THE PRIVATE SECTOR



Total Contractors 2
Mean Number of Tons Per
Day
Mean Number Trucks
Collecting Per Day
Mean Number Employees
Collecting Per Day
Number of Tons Per Truck
Number of Tons Per Man
*Mean Crew Size Per Truck
Mean Capacity in Cubic
Yards of Compactor and
Non Packer Trucks


1-6
,636

3.5

1 .2

1.5
2.9
2.3
1.4


15.1


7-12 13-24
1,726 1,865

9.7 17.8

1.5 2.6

2.2 4.0
6.5 6.8
4.4 4.5
1.5 1.6


21.1 19.5
Nun

25-49
1,238

36.1

3.7

5.8
9.V
6.2
1.6


20.7
iber of Tons Collected Per Day

50-99
1,099

09.7

7.0

9.3
10.0
7.5
1.5


21.9

100-249
918

156.6

11.0

17.6
14.2
8.9
1.6


22.8

250-499
277

349.7

19.7

31.3
17.7
11.2
1.5


22.9
; r o n «-, r
500-999 n>or<- Tv.,jl
161 : 1 0 10,127

672.6 1635.6 (,8.1

32.9 48.9 4.8

59.3 105.7 7.5
20.4 33.4 14.3
11.3 15.5 9.1
1.9 1.6 1.6


25.3 23.9 21.48
*  Mean Crew Size reported for all types of trucks .

specialize in the larger tonnage producing customers in each category.
These contractors collect 75 percent of the total tonnage,  with 51 percent
of the total trucks  (Table 5. 21) and serve 62 percent of the total cus-
tomers (Table 4. 10).  Operationally, these contractors are capable of this
daily volume because of stationary compaction,  roll-off,  and hoist type
vehicles.  Packer  trucks comprise a large percent of their total fleet  (over
two-thirds) and they operate 78.5 percent of the total roll-off vehicles and
67. 7  percent of the hoist type vehicles.
      In addition, large contractors are more apt  to service customers
under a government  franchise than are small contractors  (Table 6. 8), and
the efficiency of a  consolidated route adds to the potential number of tons
per truck which can  be collected on an average day.
      The  distribution of tonnage by the number of tons collected per day
(Table  3.5) illustrates the  concentration of total tonnage among the  1,466
contractors collecting over 100 tons per day.  Of  the total daily tonnage,
these contractors collect 512,043 of 685,466 tons, or three-fourths  of the
total  tonnage.   The contractors collecting over  100 tons per day collect an
                                   3.8

-------
even larger share of the industrial tonnage (82%),  and contractors  collective;
1000 tons or more per day collect 33.7 percent of the industrial tonnage alone.
      In general, the  larger  the contractor, the larger the proportion of
industrial waste collected.  Industrial refuse makes up the largest percent
of total tons for contractors  collecting over 1000  tons per day (40. QCrV), and
the  lowest percent (11. 1%) for contractors collecting 1-6 tons per day.
                                  3. 9

-------
DAILY TONNAGE BY CONTRACTOR SIZE
      The distribution of tonnage by contractor size (Table 3.8) indicates
that approximately two-thirds of the  residential,  commercial,  and indus-
trial  refuse is concentrated among the contractors with 10 or more trucks
who account for 15 percent of the total contractors. Residential refuse is
concentrated most heavily among the 157 contractors operating 50 or more
trucks who  collect 29 percent or57, 350 tons of the total 199, 132 residential
tonnage collected daily.  Industrial refuse is concentrated among contrac-
tors with 10-49 trucks.  These contractors collect 63 percent of the total
industrial tonnage, or 134,286 tons  per day.
      Generally, as contractor size increases, the share  of residential and
commercial tonnage  decreases,  while the share of industrial tonnage increases,
Contractors with 50 or more trucks are an exception,  collecting a different
configuration  of refuse than any other contractor size.   For all other con-
tractor sizes,  commercial and industrial tonnage account for the largest
share of total tonnage, but for contractors with 50 or more trucks, residen-
tial refuse comprises over half of their total tonnage (Figure 3. 1).

                                    TABLE 3.7
                      NATIONAL ESTIMATE OF TONNAGE BY CONTRACTOR SIZE
                                IN THE PRIVATE SECTOR
Type of Tonnage Size of Contractor
1 2-3 4-5 6-9 10-19 20-49 50 or more
truck trucks trucks trucks trucks trucks trucks
Total Corlroctors 2,603 3,193 1,421 1,261 982 405 157
Total Tor.r.ase" 14.395 54,837 47,983 101,449 180,963 172,737 113,102
Kf.MacnUal 4,779 15,931 12,346 23,896 45,203 39,428 57,350
Comnerci.il 5.7^2 21,932 18,238 37,400 59,101 58,178 30,012
Znd.otrial 2,789 14,801 13,514 36,253 69,074 65,212 13,085
Total
10,02?
685,466
199, 132
230, 8o5
214,514
    otal Tonnage includes demolition and construction refuse, and all other refuse.
                                    3. 10

-------
                                                         TABLE 3.8

                                   PERCENT DISTRIBUTION OF TONNAGE BY CONTRACTOR SIZE
                                                  IN THE PRIVATE SECTOR
Type of Tonr.a^e


Diitr.i)'-.t'n-, of Total
Co:,tr,ictor<;
O ,*r "-' :,'>n ol Torna^r:
-'•rruii" C,(,r',r-' ctor Sizes
Total Tonnage
R L 3 Klential
Corfu;. crc lal
Inci^ st r lal
J^ . ,1.1.1/i.t on of Tonnage
V. :n'". C'jftractor Si'-e.
Total
Re-jidernal
Comr.ie rt 'a.1
- 'I'll, st r ..^ i
Other
Size of Contractor
1 2-3
truck trucks

26.0% 31.8%


Z.I 8.0
2.4 8.0
2.5 9.5
1.3 6.9


100% 100%
34.2 30.0
40.5 41.0
18.4 26.6
6.9 2.4
^Other Refuse includes deinolition and construction


4-5
trucks

14. !%


7. 0
6.;:
7.9
6. 3


100%
27.0
39.0
28. 0
6. 0
6-9
trucks

12.6%


14.8
12.0
16.2
Ito. 9


100%
24.5
37.6
35. 3
2.6
10-19
trucks

9. 8%


26.4
22.7
25.6
32.2


100%
25. 8
33.2
37. 5
3. 5
20-49 50 or more
trucks trucks Total

4.0% 1.6% 100%


25.2 16.5 100
19.8 28.8 100
25.2 13.0 100
30.4 fc. 1 100


100% 100% 100%
23.6 52.5 29.1
34.2 27.0 33.7
37.0 11.3 31.3
5.2 9.2 5.9
refuse, and all other refuse.
TABLE 3.9
TONS PER TRUCK AND EMPLOYEE BY SIZE

IN THE
PRIVATE SECTCR



OF CONTRACTOR



Size of Contractor


Total Contractors
Mean Number of Tons Per
Day
Mean Number Trucks
Collecting Per Day
Mean Number Employees
Collecting Pel Day
Number of Tons Per Truck
Number of Tons Per Man
'Mean Crew Size Per Truck
Mean Capacity in Cubic
Yards of Comnactor and
Non Pa^kei Trucks
! 2-3
truck trucks
2,608 3,193

6.1 17.9

0.9 1.6

1.3 2.4
6.7 U.O
4.7 7. 5
l.S 1.6


17.3 19.2
4-5
trucks
1,421

34.7

3.0

l. 5
11.7
7. 7
1. 5


20. 1
6-9
trucks
1,261

82.4

5.2

8.0
16. 0
10.3
1. 5


21.3
10-19
trucks
982

191. 1

10.3

16.3
18. 3
11.7
1.6


22.9
20-49 50 r - r^o-e
trucks truc'^ To'--:
405 15" 1'j, ';27

4J5.0 779.2 CH.4

22.5 69.5 4.8

35.9 12-:. 6 7.5
19.4 11.2 14. 3
12. ; 6. 3 9. 1
1.5 1.8 1.6


23.7 23.2 21. 5
* Mean Crt-w Si>:c reported for all types of trucks
                                                         3. 11

-------
o
LO-
       S
       N
       L-" ~
       tr^.-)
              vs*y
              f?;:V3
                       -
              &lj
LO
in-
CM
                                  fe.#.
                                  S$

                                  H
                                  ::::*
                                         S
                                         1

                                                     -LO
                                              -O
                                               LO
                                              -LO
                                               CM
                                                              to
                                                              LU
TH
                                        Q
                                        LU
                                        H
                                        U
                                        LU
                                        _J
                                        _J
                                        O
                                        u
                                        LU
                                        O
                                        <


                                        Ig
                                        H O
                                        U.tf
                                        OH
                                        x<
                                        |o
                                        "^ LU
                                        LL. M
                                        OLT;


                                        is
                                        HH
                                        ^^
                                        OQ <


                                        ^
                                        £o
                                        Q U
                                                            ro

                                                            LU
                                                            £

                                                            D
                                                            O
  CO
  ^:
  o
  D
  DC
  H

cc LU

°s
°i
LO 5
                       00
              en
                "
              6cc
              CM H
  CO
  ^
  CJ
  D
9 cc
CD H
                                  in
CO
^
o
D
CO
^
o
D
CC
H   r-
             CC
             H
                                 3.12

-------
DAILY TONNAGE BY MIX OF COLLECTION
      Those contractors whose collection mix is 20 to 39 percent residential
tonnage are, on the average, the largest contractors,  as measured by mean
number of trucks,  employees,  and tons collected.  In terms of efficiency,
however,  the contractors with a heavy commercial mix collect more tons
per truck and more tons per employee than those with a  heavy residential
mix.  This results from a high level of containerization  and mechanization.
The ratio of tons per employee is highest among contractors who collect
100 percent commercial and industrial refuse (14.8 tons per employee).
      The high ratio of tons per employee among contractors collecting 100
percent commercial and industrial is due to the  types of trucks  they use.
These contractors on the average use  more front loader packers,  and
special collection vehicles  such as roll-off chassis, and these pieces  of
equipment usually require a smaller crew size per truck.   As shown in
Table 3. 10, mean crew size is smallest among contractors collecting 100
percent commercial and industrial, yet their packer and non-packer trucks
have the largest capacity.
                                    TAULE 3.10
                     TONS PER TRUCK AND EA1PLOYEE BY MIX OF COLLECTION
                               IN THE PRIVATE SECTOR


Total Contractors
Mean Number of Tons Per Day
Mean Number of Trucks
Collecting Per Day
Mean Number of Employees
Collecting Per Day
Mean Number of Tons
Per Track
Mean Number of Tons
Per Employee
Mean Crew Size Per Truck**
Mean Capacity in Cubic Yards
of Compactors and Non Packers

100%
375
29.3

2.7

5.6

10.9

5.2
2.1

18. 8

80-

99%
1, 835
44.

4.

9.

9-

4.
2.

20.
4

9

7

1

6
0

3
% IU-s.dc.iu
al Collection
60-79% 40-59%
1, t(jZ L, GBl
67.8 88.

5.* 6.

11.4 10.

11.5 13.

5.9 8.
1.9 1.

20.8 22.
9

4

6

9

4
6

7
20-39%
DO i
168.9

8.6

14.7

19.6

11.5
1.7

22.3
1-19%
55
45.

3.

4.

13.

10.
1.

21.
•*
8

3

3

9

7
3

6
100%
**, 14^
72.

4.

4.

18.

15.
1.

23.
Total
> iu,OE7
4

0

7

1

4
2

4
68

4

7

14

9
1

21
.4

.8

.5

.3

. 1
.6

.4
  ^Commercial and Industrial
 *#Mean crew size reported for all types of trucks.
                                    3. 13

-------
      Contractors  collecting 80 to 99 percent residential refuse have the
lowest ratio of tons per truck and per man, even though they have more
trucks and employees than contractors collecting 100 percent residential.
This indicates that when a contractor collects over 80 percent of his ton-
nage from one category, the diversion of a small portion of the collection
effort to another type of refuse leads to a less efficient utilization of equip-
ment than a full commitment to either  residential, or commercial and
industrial collection.
                                    TABLE 3.11
                     NATIONAL ESTIMATE OF TONNAGE BY MIX OF COLLECTION
                                IN THE PRIVATE SECTOR
Type of Tonnaqe

Total Contractors
Total Tonnage**
Residential
Commercial
Industrial
100%
375
9,597
9,359
--
--
80-99%
1,
78,
60,
6,
2,
835
143
536
695
789
% Ros
60-79%
1,402
91,852
57,947
22, 394
ii, 006
idcntia! Collection
40-59%
1,031
91, 852
41, 220
24,703
13,729
20-

106
28
39
35
39%
661
,247
,277
,709
, 180
1-19%
522
22,620
1,991
12,005
7,508
100%*
4,
285,
--
125,
149,
143
154

129
087
Total
10, 027
685,466
199, 132
230, 865
214,514
 *Commercial and Industrial
v*Total Tonnage includes demolition and construction refuse, and all other refuse.

      The  percent distributic-i of tonnage by  mix of collection categories
(Table 3. 12) illustrates that the  4, 143 contractors who collect 100 percent
commercial and industrial waste pick up over half of the total commercial
refuse (125, 129 tons) and more than two-thirds of  the industrial refuse
(149, 087).  The heaviest concentration of residential refuse is among the
contractors  whose mix of collection  is 40-99 percent residential.  These
contractors  collect only 38. 2 percent of the  total tonnage, but 80. 2 percent
of the residential refuse.  Contractors with  this mix of collection play a
major role in residential franchising (Table  6. 13), and as a result,  serve
approximately 18.7 million (68.5%) of the single family houses  served
by the private  sector.
                                    3. 14

-------
                                                 TABLE 3.12

                           PERCENT DISTRIBUTION OF TONNAGE BY MIX OF COLLECTION
                                           IN THE PRIVATE SECTOR
Type of Tonnage
1 00%
Distribution of Total Contractors 3. 7%
Distribution of Tonnage
Among Mix of Coi'cction
Total Tonnage 1.4
Residential 4. 7
Commercial
Industrial
Distribution of Tonnnpe
Witain Mix of Collection
Total 100%
Residential 99. 6
Commercial
Industrial
Other** 0.4
"i Residential
80-99%
18.
11.
30.
2.
1.
3%
4
4
9
3
100%
80.
8.
3.
7.
1
7
6
6
60-79%
14.
13.
29.
9.
2.
0%
4
1
7
8
100%
65.
24.
6.
3.
2
8
5
5
Collection
40-59%
10.
13.
20.
10.
6.
8%
4
7
7
4
100%
46.
27.
14.
11.
4
4
7
5
20-39%
6.6%
15.5
14.2
17.2
16.4
100%
27.5
38. 1
32.6
1.8
1-19%
5.2%
3.3
1.0
5.2
3.5
100%
9.4
54.5
33. 1
3.0
100%*
41.
41.

54.
69.
3%
6
0
2
5
100%

44.
51.
4.
0
6
4
0
Total
100%
100
100
100
100
100%
29. 1
33.7
31. 3
5.9
 s;'Commerc;al and Industrial
**Other Refuse includes demolition and construction refuse, and all other refuse.
                                                 3. 15

-------
DAILY TONNAGE BY REGION AND CITY SIZE
       Table 3. 14 shows that contractors  located in the Midwest collect
28.5 percent,  (195, 358 tons), of the total  national tonnage, followed by the
West (23. 7%) and the North Atlantic (19.  9%).   These shares  of tonnage
tend to reflect the high population densities and heavy industrialization
(especially in the Midwest)  found in these regions.
       In the category of residential tonnage, the West is  predominant,
where 75, 272 tons  out  of the 199, 132 total residential tons (37. 8%) are
collected  by the private sector.  This is directly related to the relatively
high proportion of franchising in the Western region.

       Total tonnage is heavily concentracted among contractors located in
SMSA's of over one million.  These contractors comprise 44. 5 percent of
the  private sector and  collect 64 percent of the total tonnage (438, 698 tons).
Contractors  in SMSA's of 500,000 - 1,000,000 collect a large share of
industrial tons (22.0%) compared to their share  of  total tons (16.0%).
Residential refuse  comprises a significantly higher percent of total tonnage
(37%)  for  contractors located in non-SMSA's, than  for the contractors in
SMSA's.
                                       TABLE 3.13
                    NATIONAL ESTIMATE OF TONNAGE BY REGION IN THE PRIVATE SECTOR
      .' Tonnage                                 Region
                North-  North     Mid-  South   Mid-   North  South
                east   Atlantic Atlantic  Atlantic  West  Central  Central  Mountain  West    Total

  Tola. Contractors    529    2,014    6-4-i    373   2,-iOl   1.603   5C7      3'11    1,555   10. JIT
  Total Tonnage*    43, 3ft7   136,073  25, 5t>2  29,2-0  195.353  32,820 51.20^    9.053   Ic52,i7»  <5S?,4<<6
  Residrnt.al       4,613    29,095  13,289  9, o62  43. Ml  13,533  8,374    2.097    75. '29  I". 132
  Commercial      15,621    52,793   8,206  12,033  52,731  10,037 28, o7o    3,927    4i..S41  230.S65
  Industrial       21.1-13    46,571   3,431  7,34'  39,217   8, 06n 10, ii!>2    2,-112    24,946  214,514

   Total Tor.na0-e inc.udes demolition and construction rcluse, and all other refuse.
                                       3. 16

-------
                                                    TA3LE 3.14

                           PERCENT DISTRIBUTION OF TONSACE BY REGION IN PRIVATE SECTOR
Type of Tor.r.aLe
                    North-  North      Mid-    South
                    east    Atlantic  Atlantic  Atlantic
    Region
 Mid-   North    South
West   Central  Central  Mountain
                                                                                           V, <_-st
"Other Refuse includes demolit.on and construction refuse, and all other refuse.
                                                 TABLE 3.15

                       NATIONAL ESTIMATE OF TONNAGE BY SMSA SIZE IN PRIVATE srCTOR
                                                                                                     Total
Distribution of
*joU: Contractors
D: "5t nbuti<,n of Tonnage
.•^-7-01 f, i'.r yions
Total Tonnage
i'f.sKlenti.il
Commc re lal
LM st ribuUori of Tonnayc
'.. .tn.n ."' ijiut.s
lot.-! Tonnam.
.''.cs.O.j.tia!
Co.-rirnc re lal
In-1 ,tr.al
Other-

5. 3%


6.4
2. 3
6.8


100%
10. 5
35.6
4S.2
5.7

20. 2%


19.9
14.6
22.9


100%
21.4
33. 8
34.2
5.6

6


3
6
3


1
52
32
13,
Z

.4%


.7
. 7
.6


00%
.0
. 1
.4
.5

3.7%


4. 3
4. 9
5.2


100%
33. 1
41.2
25. 1
0.6

23.9%


28. 5
21.7
22.8


100%
22. 1
27.0
45.7
5.2

16.0%


4.8
6.8
4. 3


100%
41. 2
30.&
24.6
3.6

5.


7.
4.
12.


1C
16.
56.
21.
6.

1%


5
2
4


iO%
4
0
3
3

3. 9%


1. 3
I. 1
1. 7


100%
23. 2
43.4
32.2
1. 1

15. 5%


23. 7
37. 8
20. 3


100%
46. 4
2S. 8
15.4
9.4

1007»


100
100
100


100%
29. 1
33. 7
3). 3
5.9
Type of Tonnage
SMSA Size
Over

Total Contractors
Total Tonnage*
Residential
Commercial
Industrial
1, 000
4,
438,
135,
145,
125,
, 000
456
698
Oil
907
920
500,000-
1, 000, 000
1. 311
111, 731
21, 307
39, 016
47,408
250,
499,
1,
53,
15,
19,
17,
000-
999
498
466
333
162
161
100,
249,
1,
35,
11.
12,
10,
000-
990
017
644
351
467
511
50, 000-
999,999
149
6,855
2, 190
1, 847
2, 789
Non-
SMSA
1, 3"fi
39. 072
13, 939
12.. 236
1C. 72u

Total
10.027
685,466
199, 132
230, 865
214, 5,14
   *Total Tonnage includes demolition and construction refuse, and all other refuse.
                                                   3.17

-------
                                                TA;JLE s.ie
                      PERCENT DISTRIBUTION OF TONNAGE BY SMSA SIZE IN PRIVATE SECTOR
T/rie of Tonnage:


Distribution of Total
Contractors
Distribution of Total Tonr.age
Among S.MSA Sizes
Total 7onnage
Pes .cleiitial
Comme rcial
Ir.dustrial
Distribution of Tonnape
V. .th.n SMSA Size
TuUl
Rr&irJcntial
CvmriiC re la!
Industrial
Other '

Over
1, 000, 000

44. 5%


64.0
67. 8
63.2
58.7


100%
31. 8
33.8
28.2
6.2

500, 000-
1, 000, 000

13. 1%


16.3
10.7
16.9
22. 1


100%
19. 8
35.6
41.8
2.8
SMSA Si:
250, 000-
499,999

14. 9%


7.8
7.7
8.3
8.0


100%
29.7
36.5
31.6
2.2
''. C
100, 000-
249,999

10. 1%


5.2
5.7
5.4
4.9


100%
33.3
36.0
29.0
1.7

50, 000-
99, 999

1.5%


1. 0
1. 1
0.8
1.3


100%
31. 1
27.2
39.9
1.8

Non-
S.VSA

15.9%


5. 7
7.0
5. 3
5.0


100%
37.0
31.8
27. 1
4. 1


Total

100%


100
100
100
100


100%
29. 1
33. 7
31.3
5.9
"Other Refuse includes demolition and construction refuse, and all other refuse.
                                                   3. 18

-------
                    CUSTOMERS OF THE PRIVATE SECTOR
      The contribution of the private sector  is discussed in this chapter
in terms of the estimate of the number of customers served,  the percentage
these customers  represent of the total population, the types of wastes
collected, and the frequency with which waste is  collected.  Using the
survey data base, forecasts are  made of the total number of customers,
stops, housing units, and people served.
      To maintain consistency with other  sections of this report,  these
data are presented in terms of the five major  analysis variables:
      •     contractor size
      •     daily tonnage
      •     mix of collection
      •     SMS A size
      •     Region
Frequency of collection and incidence of curb  service are presented and
analyzed by the above mentioned variables, and the types of wastes
collected by the private sector are analyzed by contractor size and daily
tonnage.
      This chapter is structured into the following subsections:
                                    4. 1

-------
•     Chapter Summary




•     Estimates of Private Sector Market




•     Customers by Contractor Size




•     Customers and Tonnage Shares




•     Customers by Daily Tonnage




•     Customers by Mix of Collection




•     Customers by Regional and City Size Characteristics




0     Type of Waste Collected  and Frequency




•     Curb Service
                               4.2

-------
                             CHAPTER SUMMARY

      The private sector collects approximately half of the residential
customers in the United States, and over 90 percent of the commercial and
industrial customers.  While residential customers account for 90 percent of
the customers serviced by all  contractors, their wastes comprise only 21  per-
cent of the total tonnage collected.  Furthermore, except for the largest contractors,
the proportion of residential customers to total customers increases as contractor
size increases.
      As with truck ownership, large contractors collect a disproportionately
large share  of customers in  relation to their percentage of total contractors:
15 percent of the contractors service 69 percent of the total customers collected
by the private sector.  Contractors located in SMSA's of over one million also
collect a large share (over half) of total customers.
      Apartments of 5  or more units are predominantly collected twice a week
or more, while single family houses are usually collected once a week.
      The types of wastes collected by private contractors vary by contractor
size. As contractor  size increases, the types of wastes collected become more
comprehensive.  This coincides with the use of more sophisticated and special-
ized equipment by the  large contractors.
      Slightly over half of the residential customers serviced by the  private
sector receive curb service.  Curb service tends to be associated with large
contractors  located in SMSA's  of over one million.
                                   4.3

-------
ESTIMATES OF PRIVATE SECTOR MARKET
      Private contractors serve  over 108 million people each week in the
collection of all types of residential wastes throughout the nation.  This
represents more than 49 million housing units or over 55 percent of the
total.  Commercial and industrial waste collection are predominantly a
function of private contractor collection.  Over 90 percent  of all commercial
and industrial establishments are serviced by private contractors.
      Customers  are divided into residential  (including single family and
2 to 4 unit apartments),  commercial (apartments of 5 or more units,  stores,
offices,  etc. ), and industrial categories.  Thus,  commercial tonnage, in
terms of the types of wastes, may be somewhat distorted due to the inclusion
of apartment waste in the total estimate.
                                    TABLE 4.1
                    NATIONAL ESTIMATE - PRIVATE SECTOR'S SHARE OF CUSTOMERS

Number of Private
Who Collect
Residential

Contractors
5,883
Commercial*
Single Family
Homes
5,883
Duplexes -
4 Unit s
4, Z84

9, 65)
Apts. 5 or
More Units
6,260
Industrial

5,806
Percent of AH Private Contractors
(10,027)
59%
59%
43%
96%
62%
58%
Number of Customers Collected
by Private Sector
24,716,758
23,348,933
1,367,825
2,275, 528
644,688
358, 727
N imbcr of Stons Collected by-
Private Sec:or
Estimated Number
Nationally

of Customers
49, 191,438


46,075,691


3,115,747
2,438,894

2, 500, 580


678,612
431,463

458,206
Percent of Total Customers
Collected by Private Sector 50%
51%
44%
91%
95%
94%
    ^Commercial Customers Include Apartments of Five or More Units.
 Table 4. 1 specifically identifies the number and percent of apartment units
 served.  The residential and apartment market shares of 50 percent and
 95 percent,  respectively, indicate that the balance of the universe is served
 either  by a municipal operation (e.g.,  Los Angeles, Miami,  etc.),  by the
 organization generating the waste,  or by no collection operation at all.
                                       4.4

-------
      A  large portion of the contractors collect only commercial and industrial

wastes,  and a small proportion handle only residential customers.   Of course,

the majority  of contractors serve all types of customers.
                   100% Commercial
                   and Industrial
                                             Residential, Commercial,
                                             and Industrial
              100% Residential - 3. 7%
                 FIGURE 4.1:  DISTRIBUTION OF CONTRACTORS AMONG
                            CUSTOMER TYPES
                                       4.5

-------
                                              TABLE 4.2
                              NATIONAL ESTIMATE - SHARP OF POPULATION SERVED BY
                                            PRIVATE SECTOR
                                        Win Fumlly Uuulexos.      Total     Apts. 5or       Total**
                                        Home*     4 Units     Ho.Mnnll.1   More Unit*    il<»i*li
-------
  CUSTOMERS BY CONTRACTOR SIZE

         The private contractor collects an average of 2, 700 customers (Table
  4.4).  However, a more revealing portrayal of the industry indicates that the
  small proportion of  large contractors (15.4%) collect the bulk of the
  customers (68.8%)  (Table 4.5).  The largest contractors in terms of truck
  count serve an average of 38, 000 customers, or about 14 times the norm.
  Furthermore, it is important to  note that the customer proportion (68. 8%)
  served by those contractors operating 10 or more trucks is significantly
  greater than the truck proportion (5SU 5%) that they operate.  This  indicates
  a high level of efficiency in  serving customers among large contractors, and
  again is due to the use of specialized high compaction equipment.

                                      TABLiE 1.3
                    NATIONAL ESTIMATE OF CUSTOMER TYPES SERVICED BY THE PRIVATE
                                SECTOR BY CONTRACTOR SIZE
T", oe ol Customer

Total Contractors
Total Customera
Sir.rle Family Homes
D ip) cxce - 4 Units
Apartments - 5 Units or more
Commercial*
Industrial
Size of Contractor
1
truck
2,608
755, 4*01
630,421
36,931
i 16,762
79, OS1
8,968
2-3
trucks
3, 193
2,368,715
2,031,357
62,920
52,220
238,565
35,873
4-5
trucks
1,
2, 002,
1.751,
47,
43,
174,
29,
421
673
170
874
194
572
057
6-9
trucks
1,
3,445,
2,988,
142,
43,
268,
46,
261
927
663
254
194
017
993
10-19
trucks

7,242,
6,350,
357,
68,
446,
88,
982
717
910
002
982
558
247
20-49
trucks
405,
5,571,63-
4,786,531
362,474
99,282
334, 385
88,247
50 or more
trucks
157
5,986,477
4,833,229
358,370
321,699
733,894
60,984
Total
10, 027
27,351,013
23,348,933
1,367,825
644,688
Z, 275, 528
358,727
* The figures for Commercial Customers include Apartments of live or more Units.

                                     TABLE 4.4
                       MEAN NUMBER OF CUSTOMER TYPES SERVICES BY THE PRIVATE
                               SECTOR BY CONTRACTOR SIZE
Type of Customer

Total Contractors
Total Customers
Single Family Homes
Duplexes - 4 Units
SUe of Contractor
1
truck
2. 60S
290
Z4Z
14
Apartments - 5 Unit* or more 6
Commercial*
Industrial
30
3
2-3
trucks
1.193
742
636
20
16
73
11
4-5
trucks
1,421
1,409
1,232
34
30
123
20
6-9
trucks
1,261
2,733
2,370
113
34
213
37
10-19
trucks
982
7,37)
6,467
364
70
455
90
20-49
trucks
405
13.7S7
11,819
895
24 5
826
218
50 or more
trucks
157
38,130
30,785
2,283
2,049
4,674
J88
Total
10,027
2,728
2,329
136
64
zzr
36
      *Th« figures for Commercial Customers include Apartments of live or mere units.

                                        4. 7

-------
                                             TABLE 14.5
                          PERCENT DISTRIBUTION OF CUSTOMER TYPES SERVICED BY THE
                                  PRIVATE SECTOR BY CONTRACTOR SIZE
TvTJ<: ^f CL.stor-.cr

Distribution of Total
Cor.t ractors
Size of Contractor
1 2-3 4-5 6-9
r s
26.0% 31.8% 14. !<<', 12.o%
10-19 20-49 50 or more
trucks tracks trucks Total.

9. 8% 4. 0% 1. 6% 100%
2. 8
2.7
2.7
2.6
3.5
2.5
8, 7
8.7
4.6
8.1
10.5
10.0
7.3
7.5
3.5
6.7
7.7
8.1
12. 6
12.8
10.4
6.7
11.8
13.1
26.5
27.2
26. 1
10.7
19.6
24.6
20.4
20. 5
26.5
15.4
14.7
24.6
21.8
20.7
26.2
49.9
32.3
17.0
100
100
100
100
100
100
       .S'larr oj Total Customers  2.8
       Single Family Homes
       Duplexes - 4 Units
       Apartments - 5 or more
                  Units
       Commercial
       Inda&lrial

       Total Customers'-       100%    100%    100%     100%      100%    100%    100%      100%
       Single Famil/ Homes    83.5     85.8     87.4     86.7       87.7     85.5     80.7      85.4
       Duplexes - 4 Units       4.9      Z.7      2.4     4.1       4.9      6.8      6.0       5.0
       Apartments - 5 or more   I .2      2.3      2.2     1.3       1.0      1.8      5.4       2.4
       Commercial   "' §      10.5     10.1      8.7     7.8       6.2      6.1     12.3       3.3
       Inr.ustn.,:              1.2      1.5      1.5     1.4       1.2      1.6      1.0       1.3

       •  .\umbers total to more than 100 percent since Apartments  of five or more Units are also included in the
         category commercial customers.


       The  disproportionately large share  of the private collectors' customer

market  served by the large  contractors is relatively consistent across all

customer categories.   For  example,  the  shares of duplexes and apartments

are 78.8 percent and 76.0 percent,  respectively  (Table  4.6).
                                   TABLE 1.6
              PROPORTION OF CONTRACTORS. AND CUSTOMER TYPES COLLECTED
"ft Cumulative
Cor tractors To
l.C
4. 0
9.8
12.6
14. 1
31.8
26. 0
1.
5.
15.
28.
42.
73.
99.
6
6
4
0
1
9
9
%
Kes identia 1
Custome rs
21.
20.
27.
12.
7.
8.
2.
0
8
1
7
3
5
7
Cumulative
%
21.
41.
68.
81.
88.
97.
100.
0
8
9
6
9
4
1
%
Commercial
Customers
32.
14.
19.
11.
7.
10.
3.
3
7
6
8
7
5
5
Cumulative
%
32.
47.
66.
78.
36.
96.
100.
3
0
6
4
1
.6
, 1
%
Apartments Cumulative
5 or more Units %
49.
15.
10.
6.
6.
8.
2.
9
4
7
7
7
1
6
49.
65.
76.
82.
89.
97.
9
3
0
7
4
5
100. 1
"A
Industrial
Customers
17.
24.
24.
13.
8.
10.
2.
0
6
6
1
1
0
S
Cumulative
w
17.
41.
66.
79.
87.
97.
99,
0
6
2
3
4
,4
. 9
                                              4.8

-------
CUSTOMERS AND TONNAGE SHARES
      Single family, residential customers represent about 85 percent of the
total customers collected by contractors of all sizes.  Residential customers
(single family and 2 to 4  unit apartments) represent 90 percent of those served
and 21. 9 percent of the total tonnage.  The bulk (33. 7%) of the tonnage comes
from commercial customers,  while industrial customers account for 31. 3
percent of the total  tonnage  (Table 4.7), Clearly,  the  use of higher  capacity
and more sophisticated equipment and the existence of more wastes  of higher
density associated •with commercial and industrial collection explain the
inverse relationships  between  the proportions of customers and wastes.
                                   TABLE 4. 7
                TONNAGE SHARES BY CUSTOMER TYPES
Type of Customer
Residential
Commercial
Industrial
Share of Customers Share of Tons
90.3% 21.9%
8.3 33.7
1. 3 31. 3
While single family homes comprise over 80 percent of the total customers
for all contractor size groupings, this share is  lowest for contractors with
50 or more trucks.  Contractors of this size service a higher  percent of
commercial customers (12.3%) and apartments  (5.4%) than any other group
(Table 4. 5). On the other hand, commercial customers comprise a
disproportionately large share of the total customers serviced by contractors
with 1-3 trucks.   This results from the fact that 43.8 percent of the
contractors with 1-3 trucks collect commercial and industrial customers
exclusively.
                                     4.9

-------
 CUSTOMERS BY DAILY TONNAGE
      While  single family homes account for approximately 85 percent of the
average contractor's total customers, contractors collecting either 1-6 tons,
or over 1,000 tons do not follow the norm.   Among contractors collecting 1-6
tons per day, single family homes comprise a significantly lower percent of
their customers (41.4%), and duplexes (16.2%) and commercial customers
(38.8%) account for  significantly larger shares of the customers (Table 4. 10).
Commercial customers, as a whole,  and the subcategory of apartments  in
particular, comprise larger shares of total customers for contractors
collecting a  small number of tons (12 or less)  and for those collecting  500 or
more tons.
                                   TABLE «.e
                  NATIONAL ESTIMATE OF CUSTOMER TYPES SERVICES BY THE PRIVATE
                              SECTOR BY TONS COLLECTED
Type of Customer

Total Cor*t racLo r s
TuLal Customers
S.ngle Family Homes
D . jlrxes - 4 Units
Aoartm'-nts 5 or more
- ,'Jnits
Commercial
I-.ci jst rial
Number of Ton? Collected Per Day
1-
2.
H",
TO,
-7,
9,
65,
6,
fc
636
175
047
357
026
673
O'lk
7-
1,
968,
817,
27,
21 ,
106,
11,
12
726
062
213
357
919
632
8oO
13-24
1 ,
2, 581,
2,218,
123,
-.3,
215,
25,
Si-5
993
149
104
839
270
470
25.4")
1
2,806
2,521
77
42
183
22
,238
, 308
,685
,966
,549
, 698
,959
50-99
1
3, 816
3,455
84
52
224
50
,099
,289
,642
,805
,864
, 903
,939
100-249

6, 741,
5,790,
426,
72,
436,
87,
918
707
535
7ol
205
523
888
250

3, 794,
3,362,
209,
42,
178,
44,
-499
277
637
246
277
549
991
123
500-999 1000

3,887,
3,263,
212,
194,
375,
30,
161
672
851
013
051
957
851

Z,i'04,
I,8o7,
177,
Ib5,
4-35,
73,
or more Total
110
802
915
817
685
8=0
180
10, 027
27,351,013
23, 348.933
1, 367,825
644, 683
2,275, 52S
358,727
The figures for Commercial Customers include Apartments of five or more Units
                                       4. 10

-------
                                       TABU; 1.9

                 MEAN NUMBER OF CUSTOMER TY.'ES SERVICED BY THE PRIVATE
                               SECTOR BY TONS COLLECTED
Type of Customer
1-6
Total Contractors 2,636
Total Customers 64
Single Family Homes 27
Duplexes - 4 Units 10
Apartments 5 or more
Units 3
Commercial * 25
Industrial 2
Number of Tons Collected Per Day
7-12 13-24 25-49 50-99 100-249 250-499 500-999
1,726 1,865 1,238 1,090 918 277 161
561 1,384 2,267 3,473 7,344 13,699 24,147
473 1,189 2,037 3,144 6,308 12,138 20,303
16 66 63 77 465 756 1,317
13 24 34 48 79 154 1,205
62 115 "148 205 476 646 2,335
10 14 19 46 96 159 192
1000 Total
or more
110 10,027
23,680 2,728
16,981 2,329
1,617 136
1,506 64
4,417 227
665 36
* The figures for Commercial Customers include Apartments of five or more Unite
TABLE 4.10
PERCENT DISTRIBUTION OF CUSTOMER TYPES SERVICED BY THE PRIVATE
SECTOR BY TONS COLLECTED
Type of Customer

Distribution of Total
Contractors
Share of Total Customers
Single Family Homes
Duplexes - 4 Units
Apartments - 5 or more
_ , Units
Comr.iercial
Industrial
Total Customers *
Single Family Homes
Duplexes - 4 Units
Apartments - 5 or more
, Ur.its
Commercial
Industrial
Number of Tons Collected Per Dav
100- 250- 500-
1-6 7-12 13-24 25-49 50-99 249 499 999
26.3% 17.2% 18.6% 12.3% 11.0% 9.2% 2.8% 1.6%
0.6 3.5 9.4 10.3 14.0 24.6 13.9 14.2
0.3 3.5 9.5 10.8 14.8 24.8 14.4 14.0
2.0 2.0 9.0 5.7 6.2 31.2 15.3 15.5
1.4 3.4 6.8 6.6 8.2 11.2 6.6 30.1
2.9 4.7 9.5 8.1 9.9 19.2 7.9 16.5
1.7 4.7 7.1 6.4 14.2 24.5 12.3 8.6
100% 100% 100% 100% 100% 100% 100% 100%
41.4 84.4 85.9 89.9 90.5 85.9 88.6 84.1
16.2 2.8 4,8 2.8 2.2 6.3 5.5 5.5
5.3 2.3 1.7 1.5 1.4 1.1 1.1 5.0
38.8 11.0 8.3 6.5 5.9 6,5 4,7 9.7
3.6 1.7 1.0 0.8 1.3 1.3 1.2 0.8
1,000
or more Tatal
1.1% 100%
9.5 100
8.0 100
13.0 100
25.7 100
21.4 100
20.4 100
100% 100%
71.7 85.4
6.8 5.0
6.4 2.4
18.7 8.3
2.8 1.3
Numbers tulal to more than 100 percent since Apartments of five or more Units are also

included in the category Commercial Customers.
                                             4. li

-------
      Single family households represent 71. 7 percent of the customers of
organizations collecting 1000 tons or more per day.  This category of
firms collect the largest number and percentage (21.4%) of the total
commercial customers served by the private sector and are second in the
industrial category on the same criteria.  Thus, commercial and industrial
wastes provide the  base for high daily tonnage.
                                     4. 12

-------
     CUSTOMERS BY MIX OF COLLECTION
           The data on customer types by mix of collection reveal some inter-
     esting trends.  Exclusively commercial-industrial contractors  serve only
     3.0 percent of the  available customers  (Table 4. 13) yet operate 33.8 per-
     cent of the trucks (Table 5. 16) and collect 41. 6 percent of the total tonnage
     (Table 3. 12).  Obviously, the percent of customers served within this
     context means little.  Most reflective of the exclusively commercial-
     industrial operators'  contribution is  the fact that these companies  serve
     over one-fourth, or 632,000,  of the commercial customers and one-half
     or 182,000, of the industrial customers.  In total, commercial and indus-
     trial customers provide two-thirds of the daily waste handled by private
     sector.

                                     TABLE 4.11
                   NATIONAL ESTIMATE OF CUSTOMER TYPES SERVICED BY THE PRIVATE
                               SECTOR BY MIX OF COLLECTION
TV-DO of Customer
100%
Total Contractors 375
Total C'lstorners 1,233,294
Single Family Homes 1,214,144
Duplexes - 4 Units 19,150
Apartments - 5 or mor^
Urns
Ir.'i . itriil
% Residential Collection
80-99%
1,
7,709,
6,981,
425,
76,
292,
10,
835
609
332
394
718
840
044
60-79%
1,
6,880,
5,930,
285,
203,
631,
32,
402
401
629
875
721
612
285
40-59%
1,
6,511,
5,837,
285,
154,
349,
39,
081
836
233
875
080
627
101
20-39%

3,946,
3,245,
341,
76,
280,
78,
661
073
502
956
718
413
202
1-19%

254,
140,
8,
16,
88,
17,
522
029
094
207
762
150
578
100%* Total
4,143 10,027
814,044 27,351,013
23,348,933
1,367,825
116,044 64-1,688
632.387 2,275,528
181,157 358,727
•f Commercial and Industrial
*=* The figures for Commercial Customers include Apartments of five or more Units .
                                       4.13

-------
                                                  TAI'.LE H. 12

                          MEAN NUMBER OF CUSTOMER TYPES SERVICED BY THE PRIVATE
                                        SECTOR BY M.X OF COLLECTION
T"

To
Tt,
Sir
Du
A,,
I
Co
pc of Customer
100%
tal Contractors 375
tal Customers 3, 289
i^U Family Homes 3,238
olexes - 4 Units 51
irtrrr-rts - T or more
r. 1 1 s
fiimc re ialj--'^
Industrial
*
*.*:

Commercial and Industrial
% Residential Collection
80-99%
1, 835
4,201
3,805
232
42
160
5

Tue figures for Commercial Customers include


60-79% 40-59%
1,402 1,081
4, 908 6, 024
4,230 5,400
204 264
145 143
451 323
23 36

Apartments of five or more Units.
TABLE 1.13
PERCENT DISTRIBUTION OF CUSTOMER TYPES SERVICED BY
SECTOR BY MIX OF COLLECTION








Tvje of Customers

Distribution of Total
Cant rat-to rs
Share of Total Customers
Simie Family Homes
Dup.rxcs - 4 Units
units
Indust rial
Total Customcrs*-'-
Sin^le Famil> Homes
Duplexes - 4 o'nits
Apartments - 5 or more
L ri i : s
Commercial
Industrial
20-39% 1-19% 100%*
661 522 4, 143
5,970 487 196
4,910 268
517 16 	
116 32 28
424 169 153
118 34 44



THE PRIVATE
Total
10, 027
2,728
2,329
136
64
227
3




% Residential Collection
100% 80-99%
3.7% 18.3%
4.5 28 2
5.2 29.9
1.4 31.1
11.9
12.9
2.8
100% 100%
98 4 90.6
l.o 5. 5
1.0
3.8
0.1
60-70% 40-59% 20-39%
14.0% 10. 8% 6.6%
25.2 23.8 14.4
25.4 25.0 13.9
20.9 20.9 25.0
31.6 23.9 11.9
27.8 15.4 12.3
9.0 10.9 21.8
100% 100% 100%
86.2 89.6 82.2
4. 2 4. 4 8. 7
3. 0 2.4 1.9
9. 2 5.4 7. 1
0.5 0.6 2. 0
1-19% 100%* Total
5.2% 41.3% 100%
0.9 3.0 100
0.6 -- 100
0.6 -- 100
2.6 18.0 100
3.9 27.8 100
4.9 50.5 100
100% 100% 100%
55.1 -- 85.3
3.2 -- 5.0
6.6 14.3 2.4
34,7 77.7 8.3
6.9 22,3 1.3








 •••  Commercial and Industrial

**  Number^ total to more than 100 percent since Apartments of five or more Units are also included in the
   category Commercial Customers.
                                                   4.  14

-------
      Those contractors whose tonnage is half residential and those whose
tonnage is 20-39 percent residential each serve about 6000 customers.
This coincides with their larger number of trucks which average 8. 18
and 10.48 per contractor,  respectively (Table 4.3).  The  20-39 percent
group is distinct from the others by virtue of its heavy involvement
in industrial collection.  This group is second only to the  purely commer-
cial contractor and collects 21.8 percent of all industrial  customers.
Exclusively residential contractors collect,  on the average, about 1000-
1100 residential customers per truck  (Table 4.5).
                                  4. 15

-------
CUSTOMERS BY REGIONAL AND CITY SIZE CHARACTERISTICS
      The proportion of all customers collected is highest for SMSA's
of over one million (58%), and decreases as SMSA size decreases
(Table 4. 16).  This indicates  a concentration of service by the private
sector in large SMSA's.  Smaller cities, particularly in the South,  often
have municipal collection.  Contractors in SMSA's of over one million
collect 527, 999 apartments out of the 644, 688 (82%), and 254, 337 of the
358, 727 industrial customers (71%).
      Single family homes comprise the largest share of customers
(91%) for contractors in non-SMSA's, and over 80 percent of the total
customers for all size  SMSA's.  Commercial customers  make up the
second highest share of customers for all SMSA's except those cities
of 100, 000 to  249, 999 where duplex apartments are  a higher  share of
total customers served than commercial customers.  The portion that
commercial and industrial customers comprise becomes a larger share
of total customers as SMSA size increases.
                                TABLE H.1H
               NATIONAL ESTIMATE OF CUSTOMER TYPES SERVICED BY THE PRIVATE
                             SECTOR BY SMSA SIZE
; p' of f. .st'iTM r
over
1 , 000 , ')GO

Fotrti C.Mornirs 15,«4«,4o7
'-,:-,.:* :-,i.i,iK ilon ns H, \rli, 147
;-;;'• x. -.!!,,<., .; z, 15;
/..,.- • •'- - 5 or .-. orr 327,999
Co r,-. . rc'.il " ' 1. -i',9, 8^8
Ir'l .blrial 254,337
Ti e .'i^jroa for Cr r.^n'orci.ii Custoin^rs
SMSA Size
500 ,000-
1 ,000,000
1,
3, 775,
3,245,
181 ,
52,
291,
56,
include >
311
501
502
921
220
758
320
\partments
250,
499,
1,
2,610,
2,334,
98,
30,
158,
19,
i of five
000-
099
498
535
893
483
945
146
013
or more
100,
249,
1,
2, 523,
2,241,
160,
18,
109,
12,
Units.
000-
999
017
331
498
036
696
242
555

50,000-
99,999
149
284, 188
233,489
6,839
1,289
39,914
3,946

Non
SMSA
1, 596
2,286,415
2,078,J55
68,391
13,538
127,414
12,555

Total
10,
27, 351,
23,348,
1,367,
044,
2, 275,
358,


027
013
933
825
688
528
727

                                  4. 16

-------
                                            TABLE 1.15

                      MEAN NUMBER OF CUSTOMER TYPES SERVICED BY THE PRIVATE
                                        SECTOR BY SMSA SIZE
Type of Customer
over
1,000,000
Total Contractors 4,456
Total Customers 3,555
Single Family Homes 2,959
Duplexes - 4 Units 191
Apartments - 5 or
more Units 118
Commercial * 348
Industrial 57

500, 000-
1, 000, 000
1,311
2,880
2,476
139

40
223
43

250.000
499,999
1,498
1,743
1, 559
66

21
106
13
* The figures for Commercial Customers include Apartments of five or

PERCENT

Type of Customer


Distribution ot Total
Contractors
Share of Total Customers
Single Family Homes
Duplexes - 4 Units
Apartments - 5 or more
Commercia' Umts
Industrial
Total Customers*
Single Family Homes
Duplexes - 4 Units
Apartments - 5 or more
Units
Commercial
Industrial

DISTRIBUTION


over
1,000,000
44. 5%
58.9
56.5
62.3
81.9
68.1
70.9
100%
83.2
5.4
3.3
9.8
1.6
TABLE 4.16
SMSA Sire
100,000-
249,999
1,017
2,481
2,204
157

18
107
12
more Units.


50,000- Xim
99, 999 SMSA
149 1,5%
1,907 1,432
1,667 1,301
46 43

9 8
268 80
26 8




Total
10, 027
2, 72o
2, 32?
! j'j

(A
227
36


OF CUSTOMER TYPES SERVICED BY THE PRIVATE
SECTOR BY SMSA

500,000- 250,
1,000,000 499,
13.1% 14.9
13.8 9.6
13.9 10.0
13.3 7.2
8.1 4.8
12.8 7.0
15.7 5.3
100% 100%
86.0 89.4
4.8 3.8
1.4 1.2
7.7 6.1
1.5 0.7
SIZE
SMSA Size
000- 100,000-
999 249.999
% 10.1%
9.2
9.6
11.7
2.9
4.8
3.5
i 100%
88.8
6. 3
0.7
4.3
0.5


50,000- Non
99,999 SMSA Total
1.5% 15.9% 100%
1.0 8.4 100
1.0 8.9 100
0.5 5.0 100
0.2 2.1 100
1.8 5.6 100
1.1 3.5 100
100% 100% 100%
82.2 90.8 85.3
2.4 3.0 5.0
0.5 0.6 2.4
14.0 5.6 8.3
1.4 0.6 1.3

















* Numbers total to more than 100 percent since Apartments ol five or more Units are also included in the
  category Commercial Customers.
                                               4. 17

-------
               The distribution of customer types  by region (Table 4. 19)  indicates
        that the 1, 555 contractors in the West collect the largest share of the
        total customers serviced by the private sector.  Western region con-
        tractors account for  27 percent of the  single family homes, 42 percent
        of the duplexes,  56 percent of all apartment buildings,  arid 42 percent
        of the commercial customers in the  U.S.  served by private contractors.
        This may be explained by the practice of franchising of both  residential
        and commercial collection by local governments in the Western region.
                The Midwest and North Atlantic contractors account for
        the second and third  highest share  of customers, respectively.
               Single family homes represent 93. 2 percent of the total customers
        collected by the private sector in the Mid-Atlantic and 72.2 percent of
        the customers in the Northeast.  Duplexes,  on the other hand, comprise
        21.6 percent of the customers  in the Northeast,  which is almost three
        times the proportion in any other region.  The Mountain,  South Central,
        and  West contractors'  collection mixes include the highest proportions of
        commercial customers, with the West also  servicing the highest pro-
        portion of apartments.  Industrial customers  comprise a higher share
        of total customers in the Northeast  (1.8%) and Midwest (1.7%) than in
        any  other regions. It must,  of course, be noted that industrial tonnage
        is a much higher proportion of the total tonnage than is the total propor-
        tion of industrial customers to the total number  of customers.
                                            TABLE t.17
                         NATIONAL. ESTIMATE OF CUSTOVER TYPES SERVICED BY THE PRIVATE
                                          SECTOR BY REGION
                          North       Mid-     South       Mid-     North    South
                Northeast   Atlantic    Atlantic    Atlantic     West    Central  Central   Mountain   West    Total

Total Cc.'.tractort,        529      2,024       644      373     2,401    1,603      507      391     1,555    10.027

,-otil C .storr-.-T.,     1,422,169   4,555,760   1,778,464  1,726,018  6,165,367  1,820,021 1,281,752  583,230  8,040,140 27,351,013
Sin.li- Family Homes  1,027,353   4,109,412   1,657,774  1,564,."79  5,463.650  1,587,727 1,074,051  490,328  6,397,608 23,348,933
D.-.plu. us - 4 ijr.us     307,761    136,783     41,035    42,-,03    127,208    93,012    35,563    6,839    575,854  1,367.825
Apartments -•> or more   9,02r,     68,932     19,341    14,828     98,637    37.392    16,117   16,117    363,604   644,0(18
Cc,rm,<.re.i.il  "nlts     ul,944    239,255     75,709   103,093    471,554   130,673   159,941   79,606    954,038  2,275,528
Ir.ri^btrial            25,111     70,310      3,946    16,143    102,955    8,609    12,197    6,457    112,640   358,727

J  The fiei.res lor Commercial Customers include Apartments of five or more Units
                                              4. 18

-------
                                                      TABLE t.18

                               MEAN NUMBER OF CUSTOMER TYPES SERVICED BY THE PRIVATE
                                                   SECTOR BY REGION
Type oi Customer

Total Cu.Ttractorb
Total Customers
Single Family Homes
Duplexes - 4 ijnus
Northeast
529
I, 688
1,942
532
Apartments - 5 or more
Units 17
Commercial
Inrlust r la 1
117
47
North
Atlantic
2,024
2,251
2,030
68
34
118
35
Mid-
Atlantic
644
2, 762
2, 574
64
30
118
6
South
Atlant.c
373
4,627
4, 194
114
40
276
43
Region
Mid-
West
2,401
2, 568
2,276
53
41
196
43
North
Central
1,603
1, 135
990
58
23
82
5
South
Central
507
2, 528
2, 118
70
32
315
24
Mountain
391
1,492
1,254
17
41
204
17
West
1, 555
5, 171
4, 114
370
234
614
72
Total
10,027
2,728
2,329
136
64
227
36
Jf The f.gures for Commercial Customers include Apartment;, of five or more Units
                                                      TABLE 1.19

                               PERCENT DISTRIBUTION OF CUSTOMER TYPES SERVICED BY THE
                                               PRIVATE SECTOR BY REGION
Typf- of Customer

Northeast
Distribution of Total
Contractors
Share of Total Customers
Sir.glc Famil/ Homes
Duplexes - 4 Units
K Units
Comme rcial
Industrial
Total Customers''1
Sir.gle Family Homes
Duplexes - 4 Units
Apartments - 5 or more
Units
Commercial
Industrial
5.3%
5.2
4.4
22.5
1 .4
2.7
7.0
100%
72.2
21.6
0.6
4.4
1.8
North
Atlantic
20
16
17
10
10
10
19
.2%
.7
.6
.0
.7
.5
.6
100%
90,
3.
1.
5.
1.
,2
,0
,5
3
5
Mid-
Atlantic
6.4%
6.5
7.1
3.0
3.0
3.2
1.1
100%
93.2
2.3
1.1
4.3
0.2
Region
South Mid-
Atlantic West
3.7%
6.3
6.7
3.1
2.3
4.5
4.5
100%
90.6
2.5
0.9
6.0
0.9
23.9%
22.5
23.4
9.3
15.3
20.7
28.7
100%
88.6
2. 1
1.6
7.7
1.7
North
Central
16.0%
6.7
6.8
6.8
5.8
5.7
2.4
100%
87.2
5.1
2.1
7.2
0.5
South
Central Mountain West
5.1%
4.7
4.6
2.6
2.5
7.1
3.4
100%
83.8
2.8
1.3
12.5
1.0
3.9%
a.i
2.1
.5
2.5
3.5
1.8
100%
84. 1
1.2
2.8
13.7
1.1
15.5%
29.4
27.4
42.1
56.4
42.1
31 .4
100%
79.6
7.2
4.5
11.9
1.4
Total
100%
100
100
100
100
100
100
100%
85.3
5.0
2.4
8.3
1.3
      X'-irr.bcrb total to more than 100 percent since Apartments of Five or more Units are also included in the category
      Commercial Customers .
                                                           4. 19

-------
TYPE OF WASTE COLLECTED AND FREQUENCY

      Virtually all contractors  report collecting rubbish.  In most instances
rubbish is combined with garbage and called "combined collection"*  Table
4.20 indicates  the types of wastes collected, the mean number of trucks,
and the mean tons collected daily.


                           TABLE 4.20
           SIZE OF CONTRACTOR INDICATORS BY TYPE OF WASTES COLLECTED
                         IN PRIVATE SECTOR
Number of Contractors
Type of Waite Who Collect
Rubbisn
Garbage
Yard Refuse
Bulky "A'aates
Ashes
Construction and Demolition
Wibt.-s
Special Wastes
Dead Animals
Street Refuse
Animal and Agriculture
V.'astrs
S< wayu Treatment Residues
Abandoned Vehicles
9
7
7
7
6

5
3
1
1

1


,950
,889
,807
,623
,405

,156
,113
,733
,7Z7

,587
394
375
Percent of Contractors Mean Number
Who Collect ot Trucka
99
78
77
76
63

51
31
17
17

15
3
3
.2%
.7
.9
.0
.9

.4
.0
.3
.Z

.8
.9
.6
6
7
6
6
7

7
9
10
11

13
14
15
. 16
.12
.78
.87
.40

.94
.93
.49
.44

.59
.09
.08
Mean Number
of Tons
Daily
72
81
76
81
88

102
152
127
146

183
239
220
.29
.26
.82
.17
.17

.94
.02
.69
.98

.55
.85
.19
Tons Per
Truck
11.
11.
11.
11.
11.

13.
15.
12.
12.

13.
17.
14.
4
4
3
8
9

0
3
2
9

5
0
6
        While the present data cannot fully explain all conditions, .the rela.
tionship of mean-tonnage-to-mean-trucks is of interest.   The  differ-
ences in tons per truck may be a function of the type of waste handled
and/or the type of equipment used.  Approximately 35 percent of the
residential customers  require twice a week collection and nearly 60
percent receive once a week collection.
                                 4.20

-------
                                     TABLE 4.21

                     PERCENT OF COLLECTION FREQUENCY BY CUSTOMER TYPE
Froqc
Loss
Once
c:\f-v of Collection
Than Once a Week
A Week
Twice a Week
Over
Tv/iCe a Week
Single Family
Homes
4.5%
58.8
34.7
1.-!
Duplexas-
4 Units
3.8%
50.3
42.5
3.3
Apartments-
5 or more Units
0.5%
22.3
40.4
37.1




       One of the major variables which affects the frequency of  collection

is region of the country (Table 4. 25).   This indicates that collection fre-

quency requirements are subject to local regulations and competitive

practices.  Size of contractor,  mix of collection, and daily tonnage are
of lesser importance as determinants of collection frequency.
                                 TABLE 1.22

          MEAN COLLECTION FREQUENCY (TIMES PER WEEK) OF HOUSEHOLD REFUSE FROM
            SINGLE FAMILY HOMES BY CONTRACTOR SIZE AMONG THE PRIVATE SECTOR
   of Household Refuse
                                          Size of Contractor
                       1
                      truck
2-3
trucks
 4-5
tracks
6-9
trucks
10-19
trucks
20-49  50 or more
trucks    trucks   Total
Combined Collection
Garurtjif
Rubbish
Yard Refuse-
Ashes
1.34
1.33
1.24
1.29
1.25
1.35
1.38
1.32
1.32
1 .30
1.36
1 .25
1.26
1.34
1.31
1.50
1.55
1 .46
1 .44
1.49
1.38
1.39
1.33
1.36
1.39
1.35
1.35
1.36
1.28
1.22
1.27
1.22
1.25
1.17
1.17
1.39
1,39
1.33
1.35
1.33
                                      4.21

-------
                                         TABLE U.23

            MEAN COLLECTION FREQUENCY (TIMES PER WEEK) OF HOUSEHOLD REFUSE FROM
                SINGLE FAMILY HOMES BY DAILY TONNAGE AMONG THE PRIVATE SECTOR
Tvpes o! Household Refuse N'umber of Tons Collected Per Dav
100-
1-6 7-12 13-24 25-49 50-99 249
Combined Collection 1.2-1 1.34 1.53 1.36 1.47 1.30
Garbage 1.21 1.37 1.47 1.36 1.53 1.32
Rubbish 1.1B 1.31 1.38 1.38 1.48 1.24
Yard Refuse 1.22 1.34 1.44 1.36 1.40 1.2t>
Ashes 1.20 1.30 1.46 1.33 1.45 1.21
TABLE t.24
250- 500- 1,000
500 999 or more
1.38 1.44 1.40 1.39
1.31 1.33 1.25 1.39
1 .40 1.14 1.33 1.33
1.40 1.11 1.33 1.35
1.25 1.11 1.33 1.33








MEAN COLLECTION FREQUENCY (TIMtS PER WEEK) OF HOUSEHOLD REFUSE FROM
SINGLE FAMILY HOMES BY MIX OF COLLECTION AMONG PRIVATE SECTOR
Tvoes of Household Refuse % Residential
100% 80-99% 60-797. 40-59%
Combined Collection 1.38 1.40 1.43 1.29
Garbage 1-55 1.45 1.35 1.25
Rubbioh 1.36 1.42 1.32 l.H
Yard Refuse 1.30 1.40 1.36 1.20
Ashes 1.33 1.38 1.35 1.20
Collection
20-39% 1-19% 100%v
1.33 1.27
1.34 1.27
1.37 1.14
1.36 1.22
1.Z8 1.18
Total
1.39
1.39
1.33
1.35
1.33
* Commercial and Industrial
                                            4.22

-------
                            TABLE U.25

MEAN COLLECTION FREQUENCY (TIMES PER WEEK) OF HOUSEHOLD REFUSE FROM
        SINGLE FAMILY HOMES BY REGION AMONG PRIVATE SECTOR
Types of Household Refuse

Combined Collection
Garbage
Rubbish
Yard Refuse
Ashes

Northeast
1 .33
1.00
1.10
1.24
1.15

North
Atlantic
1.37
1.42
1.34
1.34
1.33

Mid-
Atlantic
1.97
1.87
1.89
1.87
1.91

Houfh
Atlantic
1.94
2.13
1.25
1.58
1.62
Ronion
Mid-
West
1 .28
1.33
1.25
1.23
1.21

North
Central
1.32
1.20
1 .19
1.31
1.27

South
Central
1.80
1.33
1.62
1.57
1 .60


Mountain West
1 .00
1 .00
1.00
1.00
1 .00
1 .21
1 .18
1.20
1.22
i .24

Tola!
1.3V
1.39
1.33
1 .35
1 .33
                             TABLE 1.26

        MEAN COLLCETION FREQUENCY (TIMES PER WEEK) OF HOUSEHOLD
   REFUSE FROM SINGLE FAMILY HOMES BY SMSA SIZE AMONG PRIVATE SECTOR
Types of Household Refuse
Combined Collection
Garbage
Rubbish
Yard Refuse
Ashes
over
1,000,000
1.44
1.43
1.42
1.42
1.43
500,000-
1,000,000
1
1
1
1
1
.21
.26
.13
.12
.12
SMSA
250,000-
499.999
1.24
1.24
1.22
1.21
1.19
Size
100,000-
249,999
1.40
1.41
1.32
1 .41
1.42
50,000-
99,999
1.75
1 .33
1.00
1 .71
1 .57
Non
SMSA
1.41
1.39
1.33
1.38
1.3Z
Total
1.39
1.39
1.33
1.35
1.33
                               4.23

-------
CURB SERVICE
       One of the obvious measures of efficiency of service  in residential
collection is the number of residences served per day per truck.  This
measure is  markedly affected by the contractor's practice  of collecting
at the curbside rather than at some more distant location,  such as the
back or side door.  There are  significant implications in cost and man-
power related to the point of collection.  Slightly more than half of the
contractors collect at curbside  (Table 4. 27).  Fifty-five percent of the
residential customers have curbside collection.  The very  large and
small operators tend to provide more back door collection.  Generally
this provides a competitive differentiation to small  operators and is
often a franchise requirement for the large.
                                  TABLE 4.27
                 NATIONAL ESTIMATE - RESIDENTIAL CUSTOMERS RECEIVING CURB
                            SERVICE FROM PRIVATE SECTOR
        Number of Private Contractors Who Collect Residential Refuse          5,883
        Number of Private Contractors Who Give Curb Service to Residential
        Customers                                              3,046
        Percent of Private Contractors Who Give Curb Service to Residential
        Customers                                              51.8%
        Number of Residential Customers Receiving Curb Service          13,570,405
        lotal Number of Residential Customers Collected By Private Sector   24,716,758
        Percent of Residential Customers Collected By Private Sector
        Who Receive Curb Service                                   54.9%
      Based on our experience during the field effort,  curb service is
rapidly gaining acceptance nationwide.  This is particularly true in the
larger cities where cost effects are  substantial.  It is  clear that smaller
cities have a lower level of curb service.  However, no regional pattern
exists.
                                   4.24

-------
                                                     TABLH <4.23

                        INCIDENCE OF CURB SERVICE FOR RESIDENTIAL CUSTOMERS SERVICED BY THE
                                         PRIVATE SECTOR Bv CONTRACTOR SIZE
1 2-3
truck trucks
Contractors Who Service
Residential Customers 1,347 1,865
Contractors Who Give Curb
Service to Residential
Customers 405 920
Percent of Contractors Who
Give Curb Service 30, 1% 49. 3%
Si^e of Contractor
4-5 6-9 10-19
trucks trucks trucks
894 671 682
536 445 475
60.0% 66.3% 69.670
20-49 50 cr more
trccks trucks Total
288 135 5,833
183 82 3,046
63.5% 60.7% 51.8%
 Residential Customers                                '
 Served By Private
 Sector                  667,352  Z,076,208   1,804,323  3,139,028  6,698,241  5,141,086  5,ISO,519   24,716,758

 Residential Customers
 Who Receive Curb
 Service                 284,979  1,017,780     868,506  1.886,286  4,328,959 ' 2,836,215  2,334,110   IJ.,570,405

 Percent of Residential
 Customers  Who Receive
 Curb Service                42.7%      49.0%      48.1%      60.1%      64.6%     55.2%     45.0%        54.9%
                                                    TABLE 4.29
                               INCIDENCE OF CURB SERVICE FOR RESIDENTIAL CUSTOMERS
                         SERVICED BY THE PRIVATE SECTOR BY CONTRACTOR MIX OF COLLECTION
"'a Residential Collection
100% 80-99%
Contractors Who Service
Residential Customers 371 1,835
Contractors Who Give
Curb Service to
Residential Customers 161 932
Percent of Contractors
Who Give Curb Service 43.4% 50.8%
60-79%
1,406
810
57, 6%
40-59%
1,082
567
52.4%
20-39%
665
396
59. 5%
1-19%
524
183
34. 9%
100%* Total
5,883
3,046
5 1 . 87,
Residential Customers
Serviced By the Private
Sector                 1,235,838  7,390,311   6,203,906   6,129,756  3,608,647  148,301         __       24,716,758

Residential Customers
Who Receive Curb
Service                  773,513  3,759,002   3,148,334   3,216,186  2,605 ,,51ft   67,852        ..        13,570,405

Percent Residential
Customers Who Receive
Curb Service                62.6%      50.9%       50.7%       52.5%     72.2%    45.8%       --           54.9%
'--Commercial and Industrial
                                                        4.25

-------
                                                         TABLE 1.30

                                    INCIDENCE OF CURB SERVICE FOR RESIDENTIAL CUSTOMERS
                                        SERVICED BY THE PRIVATE SECTOR BY SMSA SIZE


Contractors V/ho Service
Residential Customer?

1 ,000,000
o r more
i, 353

500,000-
1.000,000
877

250, OOJ-
499,99'^
1, 135
SMSA Si ?e
100,000-
249,999
629

50,000-
99,999
106

Non
S.MSA
1,283

Total
5, 883
     Contractois Who Give
     Curb Service To
     Residential Customer*        1,224           335             536            262          40            649            3,046

     Percent of Contractors
     •iVIio Give Curb Service        66.1%         38.2%           47.27o          41.7%        37.7%          50.4%           51.8%

     Residential Customers
     Serviced By the Private
     Sector                  14,063,835     3,435,629       2,422,242      2,397,526      247,168     2,150,358       14,716,758

     Residential Customers
     Who Keceive Curb
     Service                  7,789,412     1,750,582       1,533,456      1,384,181       94,993     1,017,780       13,570,405

     Percent Residential
     Cus'Oi—.ors Who Receive
     Curb Service                 55.4%         51.0%           63.3%          57.7%        38.4%          47.3%           54.9%
                                                            TABLE 8.31

                                  INCIDENCE OF CURB SERVICE FOR RESIDENTIAL CUSTOMERS SERVICED
                                                 BY THE PRIVATE SECTOR BY REGION
                                       North       Mid-       Sc ith      Midr      North     South
                         Northeast    Atlantic    Atlantic     Atlantic      West     Central     Central    Moontair,    West    Total

Contractors Who Service
Residential Customers           312         830         559        288      1,547      1,130       2!2       218        788   5,833

Contractors Who Give Curb
Service to Residential
Customers                     171         583         340        181        796        362        '16       1'JO        418   3,04t

Percent of Contractors
WXo Give Curb Service        54.8%       70.2%       60.8%      62.8%      51.5%      32.0%    45.!%    45.9%      53.0%   51.8%

Residential Customers
Served By Private
Sector                   1,330,660   4,245,131   1,699,226  1,605,0(8  5,581,628  1,680,020 1,119,175  490,040  6,965,861  24,716,758

Residential Customers
V-o Receive Curb
Service                    920,3£1   2,676,553     792,263    76^,699  3,131,338   169,073    871.797  138,378  4,006,983  13,570,405

Percent of Residential
Customers Who Receive
Curb Service                 69.2%       63.0%       46.6%      47.6%      57.9%      10.1%    77.'!%    28.2%      57.5%   54.9%
                                                                 4,26

-------
                           EQUIPMENT AND MANPOWER

      This chapter describes the types of equipment owned and/or serviced
by the private sector and the manpower employed for daily operations.
Equipment is discussed in terms of packers and non-packers (mainly open
trucks),  special collection vehicles, and specialized collection equipment.
In addition to the total number of each type of truck, information on the
size of body, and the direct manpower  utilized with each vehicle  type appears.
The manpower analysis  concerns both  direct and overhead employees.  Data
on the daily utilization of equipment and manpower is analyzed by contractor
size,  daily tonnage collected, mix of collection, SMSA and non-SMSA  units,
and region.
      Tabular output for each variable  includes:
      •    A  national estimate of each type of equipment and of employees.
      •    The percent  distribution across and within categories for each
           variable.
As a further analysis of  truck ownership, trends relating to open vs. packer
trucks are presented for  1965,  1968, and 1970 by the major variables.
Special collection equipment such as roll-off bodies and various forms of
containers are examined  as a segment  of the  equipment structure of the
private contractor market.
      This chapter is structured into the following subsections:
           •       Chapter Summary
           •       Equipment Estimates and  Utilization

                                     5. 1

-------
•     Manpower Analysis




•     Truck Types and Size of Contractor




•     Truck Types and Mix of Collection




•     Truck Types and Daily Tonnage




•     Regional and City Size Characteristics




•     Packer -  Non-Packer Use Trends




•     Specialized Equipment
                               5.2

-------
                          CHAPTER SUMMARY
      The ownership of total trucks is heavily concentrated among the con-
tractors who operate 10 or more trucks.  These contractors comprise 15 percent
of the total contractors  and own 60 percent of the total trucks.  Examining the
ownership of specific types of trucks, one finds that packer trucks and special
collection vehicles are  also more heavily concentrated among the large contractors,
while non-packers are  more prevalent among small contractors.  Large contractors
tend to operate large capacity trucks, and collect more refuse per crew member
than small contractors.
      By region and SMSA size, contractors located in the West, South Atlantic,
and South Central, and in SMSA's of over one half million are, on the average,
the largest contractors. Contractors located in cities of over 500,000 accounted
for 58 percent of the private sector.
      The data on trends in ownership of packer and non-packer trucks, since
1965, indicate a substantial increase in the growth rate and number of packer
trucks,  and  a  slight decrease in non-packers.  While all sizes of contractors have
experienced an increase in packers, the decrease in non-packers is  much more
pronounced  among large contractors.  There is,  however, an increase in non-
packers among the smallest contractors.
      The specialized equipment serviced by some contractors includes roll-off
bodies,  stationary containers,  stationary compactors, and special containters.
Stationary containers and roll-off bodies are the most numerous of the types of
special equipment.  The contractors who service the specialized equipment tend
to be larger  contractors with a heavy commercial and industrial collection mix.
                                  5.3

-------
EQUIPMENT ESTIMATES AND UTILIZATION
     The private sector operates 61,600 vehicles, and of these slightly over
two-thirds are packer trucks, 12 percent are non-packers, and the balance
(21%) are special collection vehicles (Figure 5. 1).  In terms of number of
trucks,  a large  majority of the trucks are packers, which are further
subdivided into rear,  front, and side loaders.   The rear loader is the basic
truck used in the industry, constituting 43 percent of  all vehicles and 63
percent  of all packer type bodies (Figure  5. 2).
                                        TABLE 5.1
                                NATIONAL ESTIMATE OF TOTAL TRUCKS
                                 OPERATED BY THE PRIVATE SECTOR
                      Number of   Percent of    Percent of    Mean Capacity   Mean Crew   Cubic Yards
                       Trucks   Total Trucks   each Type    in Cubic Yards    Size      Per Crew
    Type of Truck                            of Truck                           Member
Tola! Trucks
Pac/":rs
Rear Loaders
Front Loaders
Sid
-------
                         Special Collection*
                             Vehicle!
•roll-off chauif,  hoi it type vehiclei, i4teUlte vehicle*, etc.


       Figure 5.1: FLEET COMPOSITION OF AVERAQE CONTRACTOR
                                 5,5

-------
        61,648
                26.230
8,000_
7,000-
6,000-
5,000-
4,000-
3,000-
2,000-
1,000-

                        7,670   7,702
                                       7,244
                                       * ) r£ tA 3 &••.
                                      $m
                                         ?f
                                       *%$&:
                                       mm
                                         «-''.>.'
                                                      6,496
                                                83
                                                                      4,034
                                                              2,206
                Rear    Front   Side-   Open   Side-  Roll-off Hoist-  Other
               Loader  Loader  Loader         Loader Chassis type    Collection
                                                             Vehicle Vehicles
        Total
        Trucks
                      Packers
Non Packers    Special Collection Vehicles
      FIGURE 5.2:  DISTRIBUTION OF TOTAL TRUCKS AMONG TRUCK TYPES
                                        5.6

-------
    Cubic yard capacity among packer trucks shows little difference between
rear and side loader vehicles.   Front loaders, however, are approximately
50 percent larger than other packers.  This factor,  combined with a
reduced crew size requirement in front loader trucks,  creates a  highly
efficient collection vehicle in terms of equipment and manpower usage
(Table 5. 1).
    The national estimates of daily truck utilization indicate that, on any
given day, 77. 5 percent  of a contractor's total trucks will be on the job
collecting, 19. 0 percent will be held in reserve, and 3. 6 percent will be out
for maintenance.   Our investigation reveals that a significant proportion of
the reserve fleet are most probably open trucks and are, in fact,  used on call
only.   Trucks of this nature are often used for the collection of special or
bulky items and,  as such, do not necessarily service daily routes.  Given
this is valid we can conclude that the 77. 5 percent is a conservative
reflection of daily truck  utilization.
                                   TABLE 5.2
                      NATIONAL ESTIMATE OF TRUCK UTILIZATION PER DAY
                                IN PRIVATE SECTOR

Total Trucks
Trucks Collecting Today
Trucks Held in Reserve
Trucks Out for Maintenance
Number of Trucks
61,648
47 ,121
11,691
2,231
Percent of Truck;
100%
77.5%
19.0%
3.6%
          Note: Numbers do not always add to total due to rounding error in forecasting
              national figures .

The  difference in truck utilization is relatively small across most variables.
Points of interest include the observation of a high daily utilization by one
truck operators (91%) and lower  utilization by operators of 2-5 trucks
(Table 5. 3). This utilization level should be moderated by the consideration
of a  general industry practice to maintain at least one extra vehicle in order
to always be able to serve the customer.  It bears  repeating that the  reserve
truck represents  a significant proportion of the total available fleet and
reduces  the reported utilization.  Also, the common practice in modernizing
                                     5.7

-------
equipment is to replace a non-packer with a packer, and retain the
non-packer as a reserve vehicle.
     Utilization of trucks reaches a peak among contractors who collect
20-39 percent of their total tonnage from residential customers  (Table  5.4).
This  condition is  a result of this group's size in terms of tonnage and
trucks  as measured by the average number of trucks per contractor
(10.48) (Table 5.4).
                                    TABLE 5.3
                 UTILIZATION OF TRUCKS IN PRIVATE SECTOR BY SIZE OF CONTRACTOR
Size of Contractor
1
truck
Total Contractors 2, 608
Mean Number of Total
Trucks 1.00
Mean Number of Trucks
Collecting Today 0.91
Percent of Total Trucks
Collecting on Average
Day 91.0%
2-3 4-5
trucks trucks
3,193 1,421

2.40 4.42

1.63 2.97


67.9% 67..:%
6-9 10-19
trucks trucks
1,261 982

7.17 13.31

5.15 10.47


71.8% 78.7%
20-49
trucks
405

27.59

22.49


81.5%
50 or more
trucks
157

82.75

69.50


84.0%

Total
10,02?

6.15

4.76


77.5%
                                    TABLE 5.4
                 UTILIZATION OF TRUCKS IN PRIVATE SECTOR BY MIX OF COLLECTION
% Residential Collection
100% 80-99% 60-79%
Total Contractors 375 1,835 1,402
Mean Number of Total Trucks 3.62 6.59 7.58
Mean Number of Trucks
Collecting Today 2.68 4.85 i>.89
Percent of Total Trucks
Collecting on Average Day 74.0% 73.6% 77.7%
40-59% 20-39% 1-19% 100%* Total
1,081 661 522 4,143 10,027
8.18 10.48 4.35 5.14 6.15
6.44 8.58 3.27 4.00 4.76
78.7% 81.9% 75.2% 77.8% 77.5%
   * Commercial and Industrial
                                    5.8

-------
                                             TABLE 5.5

                        UTILIZATION OF TRUCKS IN PRIVATE SECTOR BY SMSA SIZE
                                                        SMSA Size

                               over       500,000-   250,000-   100,000-   50,000-   Non
                              1,000,000   1,000,000   499,999    249,999    99,999   SMSA    Total


Total Contractors               4,456        1,311     1,498      1,017        149    1,596    10,027

Mean Number of Total Trucks     8.30         6.51      4.25       5.01       5.27     3.57      6.15

Mean Number of Trucks Collecting
Today                           6.60         5.10      3.23       3.56       4.00     2.47      4.76

Percent of Total Trucks Collecting
On an Average Day              79.5%       78.3%    76.0%     71.1%      75.9%    69.2%     77.5%
                                             5.9

-------
MANPOWER ANALYSIS

    Nationally,  the private sector employs  102,000 persons.  This
represents 10.2 employees per contractor.  However,  two-thirds of all
private sector employees work for only 15 percent of the contractors.
Collection employees (those out driving and helping on any given day)
account for about three-fourths of the total work force.
                                TABLE 5.6
                     NATIONAL ESTIMATE OF MANPOWER EMPLOYED
                             BY PRIVATE SECTOR

Total Employees
Employees Collecting Today
Mean Crew Size for all Collection Vehicles
Mean Number Days Worked Per Week
Total Number
102,388
75,460
1.59
5.78
Percent
100%
73.7


A key consideration in examining the number of collection employees is the
contractor's mix of collection.  As  the contractor's tonnage (and therefore
 his customers) tend to become more commercial and industrial, his net
 number of men per truck reduces (Table 5.7).  This condition is,  of
 course, a function of the equipment required in servicing commercial and
 industrial accounts.  As previously noted,  front loaders are used almost
 exclusively in collecting commercial and industrial customers, and have
 the smallest average crew size.  Furthermore, commercial and industrial
 collection often necessitates the  use of other specialized collection equip-
 ment such as roll-off chassis.
     In servicing  commercial and industrial customers  the use of truck
 types  which require small crew  sizes combined with the use of on  site
 containers results in a situation  where a small work force is capable of
 collecting a large amount of waste.
     Conversely,  residential collection generally requires more men per
 truck (Table 5.7). Those operations that are totally residential require on
 the average 2 men crews.  The type of equipment used  in residen-
 tial collection also affects the average crew size.   Both rear and side
 loader trucks predominate in residential collection, requiring more men
 for collection .
                                    5. 10

-------
                                       TABLE 5.7
                          ANALYSIS OF MANPOWER BY MIX OF COLLECTION
                                    IN PRIVATE SECTOR
% Residential Collection
100% 80-99% 60-79%
Total Contractors 375 1,835 1,402
Mean Number of Employees 7.29 11.88 14.68
Mean Number of Men Collecting
Today 5.59 9.69 11.41
Percent of Total Employees
Collecting on Average Day lb.1% 81.6% 77.7%
Mean Number of Total
Trucks Collecting Today 2-68 4.85 5.89
Mean Number of Men
Collecting Per Truck 2.09 z-°° 1.94
40-59% 20-39% 1-19% 100%* Total
1,081 661 522 4,143 10,027
14.89 19.78 6.53 7.07 10.21
10.59 14.71 4.31 4.65 7.53
71.1% 74.4% 66.0% 65.8% 73.8%
6.44 8.58 3.27 4.00 4.76
1.64 1.71 1.32 1.16 1.59
    * Commercial and Industrial

      Since the  largest contractors as measured by fleet size are the
most heavily involved in residential collection,  their fleet configuration
tends to contain a high percentage of rear loaders.   The larger crew
size required on rear loaders results  in a slight increase in the average
crew size per truck as contractor size increases.
                                       TABLE 5.8
                          ANALYSIS OF MANPOWER BY CONTRACTOR SIZE
                                    IN PRIVATE SECTOR

                                             Size of Contractor
                           1     2-3     4-5     6-9     10-19   20-49  50 or more
                         truck   trucks   trucks  trucks   trucks  trucks  trucks  Total
Total Contractors 2,608 3,193
Mean Number of Total
Employees 1.58 3.35
Mean Number of Men
Collecting Today 1.31 2.44
Percent of Total Employees
Collecting On Average Day 82. 9 72. 8
Mean Number of Total
Trucks Collecting Today .91 1.63
Mean Number of Men
Collecting Per Truck 1.44 1.50
1,421 1,261 982 405

6.06 11.44 23,73 50.49

4.49 8.00 16.29 35.93

74.1% 69.9 68.7% 71.2%

2.97 5.15 10.47 22.49

1.51 1.55 1.56 1.59
157 10,027

151.75 10.21

124.56 7.53

82.1% 73.7%

69.50 4.76

1.79 1.59
                                     5.11

-------
      The proportion  of daily collection employees to all employees
is highest in predominantly residential companies.  Those companies
are most often found among very large and very small contractors
(Table 5. 8).  This high ratio of collection employees to total employees
should, however, be expected.   Generally, a residentially based com-
pany will employ more drivers and helpers to collect the same tonnage
as  a   commercial  company.   Given a larger number of collection em-
ployees,  the percent they comprise of total employees  will be higher.
      Both the size of  a contractor and his residential/commercial mix
have effects on the  crew  size per truck and tht ratio of collection em-
ployees to total employees.  Commercial contractors,  who are generally
in the mid-size range,  have smaller crew sizes, because of the type of
equipment they operate.  The smallest and larg st contractors tend
to have a higher proportion of employees invol\ i in daily collection
(Table 5.8).
                                    TABLE 5.9
                    ANALYSIS OF MANPOWER IN PRIVATE SECTOR BY SMSA SIZE
                                       SVSA Siy.e
                         over     500,000-   250,000-  100,000-   50,000-   Non
                       1,000,000  1,000,000  499,999   249,999   99,999  SMSA   Total
Total Contractors
Mean Number of
Employees
Mean Number of
Collecting Today
Total
Employees
4,
14
10
456
.25
.68
1, 311
12.21
8.08
1,498
7. 61
5.31
1, 017
7. 11
5.36
149
8. 00
5.67
1,
5
3
596
.42
. 87
10,027
10.21
7.53
     Percent of Total Employees
     Collecting on an Average
Day
Mean Number of Total
Trucks Collecting Today
Mean Number of Men
Collecting per Truck
74.9

6.60

1.62
66.2

5. 10

1.58
69.8

3.23

1.64
75.4

3.56

1.51
70.9%

4. 00

1.42
71.4%

2.47

1.57
73.7%

4.76

1.59
                                    5. 12

-------
      In terms of city size, the proportion of employees involved in daily
collection is lowest in SMSA's of 5000,000 - 1, 000,000.  This is  consis-
tent with the finding that contractors in this group tend to have a heavy
commercial and industrial collection mix (Table 3. 15).
      In summary, packers comprise two-thirds of the total trucks oper-
ated by the  private sector,  and rear loader compactors make up the
single largest category of all trucks.  Non-packers account for 12 per-
cent of total trucks, and special collection vehicles 21  percent, with half
of the  special collection vehicles being roll-off chassis.  Packers repre-
sent over 85 percent  of all collection trucks exclusive of  special collec-
tion vehicles.
      The daily utilization of trucks  indicates  that slightly over three-
fourths of a contractor's total fleet is collecting on an average day,
and that approximately 2 out of ten trucks are held in reserve for special
pick-ups,  and less than 5% are "down" for maintenance.  Daily truck
utilization varies by contractor size with an increasing daily utilization
of trucks as contractor size increases.
                                   5. 13

-------
TRUCK TYPES AND SIZE OF CONTRACTOR
      The ownership  pattern  of the private solid waste fleet of 61, 000
vehicles shows that 15 percent of the contractors (those operating 10 or
more trucks) own 59 percent of the rear loaders and front loaders,  66
percent of the side loaders among packers, and similar proportions of
specialized collection vehicles. Conversely,  contractors with 3 trucks
or less operate 16 percent of the trucks while constituting 58 percent
of all collection companies.  This relationship holds true for all types
of trucks except non-packers.  In the case of open non-packer trucks,
small contractors with 1-3 trucks account for 41 percent of that type
of truck operated  by the private sector, and this percent tends to de-
crease as contractor  size increases (Table 5. 10).

                                    TABLE 5.10
                     PERCENT DISTRIBUTION OF TRUCK TYPES BY CONTRACTOR
                               SIZE IN PRIVATE SECTOR
Type of Truck


Distribution of Total
Contractors
Share of Total Trucks
Packers
Rear Loader
Front Loader
Side Loader
Non Packers
Open
Side Loader
Special Collection Vehicles
Roll-off Chassis
Hoist Type Vehicle
Other Collection
Vehicles *
Size of Contractor
1
truck
26. 0%
4.2

3.5
3.7
2.9

15.3
32.5

0.8
-.
„..

2-:
3
trucks
31.
12.

13.
10.
9.

26.
-

6.
5.
1.

8%
0

0
3
0

1
-

6
0
7

4-5
trucks
14. 1%
9.9

11.4
7.8
7.5

14.6
--

7.3
14.4
2. 1

6-9
trucks
12.
14.

12.
18.
13.

15.
32.

18.
18.
6.

6%
4

8
7
8

4
5

4
1
6

10-19
trucks
9.
20.

20.
26.
26.

11.
34.

20.
27.
14.

8%
8

2
8
3

5
9

9
9
9

20-49
trucks
4
17

13
18
29

7


28
29
18

. 0%
.8

.2
.6
.?

. 1
--

.9
.3
.2

50 or more
trucks
1
20

25
14
10

10


17
5
56

.6%
.9

.9
. 1
.6

.0
--

. 1
.3
.4

Total
100%
100

100
100
100

100
100

100
100
100

    * Other Collection Vehicles include satellite vehicles, container trains, etc.
                                    5.14

-------
       Contractors with 50 or more trucks own the most rear loaders
 (6, 803),  contractors with 10-19 trucks own the most front loaders  (2, 052),
 and contractors with 20-49 trucks own the most side loaders (2, 304)
 (Table 5. 11).  Special collection vehicles are most often owned by  oper-
 ators  of 10-49 trucks.

                                   TABLE 5.11
                    NATIONAL ESTIMATE OF TRUCK TYPES BY CONTRACTOR SIZE
                                 IN PRIVATE SECTOR
Type of Truck

Total Contractors
Total Trucks
Packers
Rear Loader
Front Loader
Side Loader
Non Packers
Open
Side Loader
Special Collection
Vehicles
Roll-off Chassis
Hoist Type Vehicle
Other Collection
Vehicles *
Size of Contractor
1
truck
2,608
2,608

907
282
227

1.111
27


55
_.
__

2-3
trucks
3, 193
7,398

3,410
792
695

1,893
--


429
111
67

4-5
trucks
1,421
6. 103

2,990
598
574

1,056
--


476
317
85

6-9
trucks
1.261
8,877

3,356
1,438
1,065

1, 119
27


1, 198
399
266

10-19
trucks
982
12,823

5,296
2,052
2,026

833
29


1,359
616
603

20-49
trucks
405
10,973

3,467
1,426
2.304

516
--


1,876
647
735

50 or more
trucks
157
12,884

6,803
1,081
810

715
--


1, 102
115
2,274

'Total
10,027
61,648

26,230
7,670
7,702

7,244
83


6,496
2,206
4,034

* Other Collection Vehicles include satellite vehicles- container trains, etc.
       Perhaps the most interesting approach to analysis of truck types in
 relation to total fleet size is through a study of the mix  of trucks within
 contractor size categories.   These data should be viewed in terms of
 truck types to total trucks,  and packer trucks to total packers.
       Packer trucks comprise  over half of the total trucks owned by  all
 sizes of contractors and almost three-fourths of the trucks owned by con-
 tractors with  10-19 trucks(Table 5. 12).  There is some variation among
 the different sizes of contractors in the distribution of the three types of
                                    5. 15

-------
packer trucks - rear loaders,  front loaders, and side loaders.  Rear

loaders make up the largest share of packers for all company sizes, but

this varies from 78.2 percent  of all packers owned by contractors with

50 trucks or  more,  to 48. 2 percent among contractors who own 20-49

trucks  (Table 5. 13). Side loaders comprise 32 percent of the total trucks



                                  TABLE 5.12

                  PERCENT DISTRIBUTION OF TRUCK TYPES WITHIN CONTRACTOR
                              SIZES IN PRIVATE SECTOR
Type of Truck

Distribution of Total
Contractors
Share of Total Trucks
Packers
Rear Loader
Front Loader
Side Loader
Non Packers
Open
Side Loader
Special Collection Vehicles
Roll-off Chassis
Hoist Type Vehicle
Other Collection
Vehicles *
Size of Contractor
1
truck

100%
100
54.3
34.8
10.8
8.7
43.6
42.6
1.0
2. 1
2. 1
--
..

2-3
trucks

100%
100
66.2
46. 1
10.7
9.4
25.6
25.6
--
8.2
5.8
1.5
0.9

4-5
trucks

100%
100
68.2
49.0
9.8
9.4
17.3
17.3
--
14.4
7.8
5.2
1.4

6-9
trucks

100%
100
66.0
37.8
16.2
12.0
12.9
12.6
0.3
21.0
13.5
4.5
3.0

10-19
trucks

100%
100
73. 1
41.3
16. 0
15.8
6.7
6.5
0.2
20. 1
10.6
4.8
4. 7

ZO-49
trucks

100%
100
65.6
31.6
13.0
21.0
4.7
4.7
--
29.7
17. 1
5.9
6.7

50 or more
trucks

100%
100
67.5
52.8
8.4
6.3
5.5
5.5

27. 1
8.6
0.9
17.6

Total

100%
100
67.5
42.5
12.4
12.5
11.9
11.8
0.1
20.7
10.5
3.6
6.6

  * Other Collection Vehicles include satellite vehicles, container trains, etc.
                                   TABLE 5.13


                      PERCENT OF PACKER TRUCKS IN PKIVATF SECTOR
                               BY CONTRACTOR SIZE
Type of Truck


Total Packers
Rear Loader
Front Loader
Side Loader
Size of Contractor
1
truck
100%
64. 1
19.9
16.0
2-3
trucks
100%
69.6
16.2
14.2
4-5
trucks
100%
71.8
14.4
13.8
6-9
trucks
100%
57.3
24.5
18.2
10-19
trucks
100%
56.5
21.9
21.6
20-49
trucks
100%
48.2
19,8
32.0
50 or more
trucks
100%
78.2
12.4
9.3

Total
100%
63.0
18. 4
18. 5
                                     5.16

-------
for companies with 20-49 trucks, which is a higher proportion of side-
loaders than for any other contractor size.  The share of front loaders
operated is highest for contractors with 6-9 trucks (24.5%) and 10-19
trucks (21.9%).
      There is a decided decrease in the share of non-packer trucks as
the size of contractor increases.  While non-packers account for 43 per-
cent of the trucks  operated by the smallest contractors, they drop to
less than 10 percent of those operated by  companies with 10 or more
trucks.
      The type of truck operated by a contractor is,  to a large degree, a.
function of the type of waste collected.  The high incidence  of rear loaders
among the  largest contractors is characteristic of their residential cus-
tomer tonnage.  Some 52. 5 percent of the tonnage  collected by a typical
50 truck or more operator is residential.   The rear  loader  was designed
primarily to fulfill this collection requirement,  although containerization
has also  increased the utilization in commercial collection.  Where com-
mercial and industrial tonnage is highest the incidence of front loaders
and roll-off chassis is highest (Table 7.8).  Gross tonnage capabil-
ities are affected by equipment types, i.e. , front loaders have a capacity
of 50 percent greater than rear or side loaders.
      Thus in addition to contractor size,  the mix  of equipment is a cri-
tical determinant of a contractor's real contribution to the collection process,
                                   5. 17

-------
TRUCK TYPE AND MIX OF COLLECTION
      The data support the concept that the types of trucks a contractor
operates are related to his mix of collection.  However, an interesting
anomaly occurs in the description of the exclusively commercial contractor.
The 4, 143 contractors who collect only commercial and industrial wastes
operate 34 percent of the trucks in the industry (Table 5. 16). This represents
a disproportionately low share of trucks.  The natural implication suggests
that these contractors are small.   However, total  commercial collection,
in fact, implies a high level of sophisticated equipment. Contractors  who
collect only commercial wastes collect the highest gross tonnage per employee
per day and a mean number of tons per day per truck (18. 1) about twice  that
of the exclusively residential  contractor (10. 9) (Table 3.9).
      It should be noted that "commercial" collection in this study is defined
as including apartments  of five or more units.  Therefore, those contractors
who are reported as exclusively commercial also  serve apartment residences.
The significant difference is their ability to use containers, front loading
equipment,  and special collection equipment in maximizing tonnage collected.
      Companies specializing exclusively in residential or commercial
collection operate the  lowest mean number of trucks.  Total residential
operations are, however, dominated by rear loaders  and non-packers.
Commercial operators are significantly more  involved with front loaders and
special collection equipment.
      Contractors whose mix  of collection includes 20-39 percent residential
tonnage operate the most trucks and packers per contractor.  This group also
has the highest total tonnage (19. 6) per truck per day, which suggests a  highly
efficient use of the packer truck.
      As might be expected,  the mean number of trucks owned by a contractor,
across the entire universe, is directly related to the  average number of tons
he collects.  While significant variances  in terms  of tons per truck occur by
equipment type,  one can conclude that on  an industry basis, the more tons
a contractor collects a day the more trucks he needs  to service his business.
                                     5. 18

-------
  z
  o
-O
So
0<
CC CC
LU I-
25*


5|
o ±

g Q
f*\ ^—
   K

   LU


&) 35

t^ CC
                           z
                           LU
<*>%
CM CC
          I-
          z

         o ^


        S CO
   I-


   LU
^ Q

S W

6"J
to cc
                                                                              X

                                                                              s

                                                                              z
                                                                              o

                                                                              h
                                                                              u
                                                                              LU

                                                                              _l
                                                                              O
                                                                              u


                                                                              00

                                                                              Z
                                                                              O

                                                                              h-

                                                                              OL

                                                                              O
                                                                              LL
                                                                              Z
                                                                              o
                                                                              CJ


                                                                              LU
                                                                              LU
                                                                              -I
                                                                              U.
LU



O

iL
                                      5.19

-------
                                                     TABLE 5.14

                               MEAN NUMBER OF TRUCKS OPERATED BY PRIVATE SECTOR
                                                BY MIX OF COLLECTION
Type of Truck

Total Contractors
Total Trucks
Packers
Non Packers
Special Collection
* Commercial and



Type of Truck

Total Contractors
Total Trucks
Pa c '< r r s
IU-n r Loader
Front Loader
Side Lo;iclcr
Nor. IJ;.-cX e rs
Op.-n
Sif'c Loader
Mix oi Collection
100% 80-997o 60-79% 40-59%
375 1,835 1,402 1,081
3.62 6.59 7.58 8.18
2.84 5.22 6.36 6.56
0.73 0.57 0.71 0.80
Vehicles 0.05 0.81 0.51 0.82
Industrial
TABLE 5.15
NATIONAL ESTIMATE OF TRUCK TYPES BY MIX OF
IN PRIVATE SECTOR
% Residential
100% 80-99% 60-79% 40-59%
375 1,835 1,402 1,081
1,311 11,854 10,204 3,549

630 6,767 4,853 4,459
54 521 890 1,174
339 1,972 2,757 1,163

268 1,043 978 840
15 23

20-397. 1-19%
06 1 522
10.^8 4.53
8.18 2.90
0.64 0 .54
1.68 0.90


COLLECTION

Collection
20-39% 1-19%
661 522
6,728 2,181

3,594 918
675 414
924 100

420 283
--

100'" rot.u
4, 143 10, ','27
5. 1 * 1 . 1 5
2.43 4.15
0.83 0.73
1.88 1.27





100%* Total
4, 143 10,027
20, 810 61, b48

4,984 26,230
3,942 7,670
447 7,702

3,404 7,244
45 83
5>p
-------
                                               TABLE 5.16

                              PERCENT DISTRIBUTION OF TRUCK TYPES BY MIX
                                    OF COLLECTION IN PRIVATE SECTOR
Type of Truck
100%
                                 80-99%    60-7951
                                                         % Residential Collection

                                                      40-59%    ZO-39%     1-19%    100%*    Total
Distribution of Total
  Contractors            3.7%    18.3%      14.0%     10.8%      6.6%       5 .Z%   41.3%

Share of Total Trucks     2.1      19.2       16.6       13.9      10.9        3.5     33.8

Packers

   Rear Loader           2.4      25.8       18.5       17.0      13.7        3.5     19.0
   Front Loader          0.7       6.8       11.6       15.3       8.8        5.4     51.4
   Side  Loader            4.4      25.6       35.8       15.1      12.0        1.3      5.8

N'on Packers

   Open                  3.7      14.4       13.5       11.6       5.8        3.9     47.0
   Side  Loader             --        --       18.2       28.1        --         --     53.8

Special  Collection Vehicles

   Roll-off Chassis        0.3      10.6        7.1        7.6      11.5        3.6     59.3
   Hoist Type Vehicle      --       2.6        5.2        6.5       7.1        1.5     77.2
   Other Collection
     Vehicles •'•*           --      20.0        3.3        6.3       5.2        4.9     60.3***
                                                                                               100%
                                                                                               100
                                                                                               100
                                                                                               100
                                                                                               100
                                                                                               100
                                                                                               100
                                                                                               100
                                                                                               100

                                                                                               100
   Commercial and Industrial
                                                                       ....g 100% commercial and industrial
                                                                       .ch affects the national projection.
                                               TABLE 5.17

                        PERCENT DISTRIBUTION OF TRUCK TYPES WITHIN COLLECTION
                                         MIX IN PRIVATE SECTOR
 T*'pe qf Truck
                           100%
                                    80-99%
                                                % Residential Collection

                                              60-79%     40-59%    20-39%
                                                                              1-19%
                                                               100%*
                                                                                                 Total
Distribution of Total
Contractors
Share of Total Trucks
Pii-r era
Rf:ar Loader
Front Loader
Side Loader
Non Packers
Open
Side Loader
Special Collection Vehicles
Roll-off Chassis
Hoist Type Vehicle
Other Collection
Vehicles = = *
100%
100
78.1
4H.1
4.1
25.9
20..4
20.4
--
1.5
1.5
..


100%
100
78.1
57.1
4.4
16.6
8.8
8.8
--
13.1
5.8
0.5

6.8
100%
100
8.)
47
8
27
9

-------
TRUCK TYPE AND DAILY TONNAGE
      The private sector collects 685, 500 tons of all types of wastes
daily using 61, 600 trucks.  Across all vehicles this equals  11.1 tons
per truck per day, or typically,  5.5  tons per trip to the disposal site
assuming an average of two trips per day.   The statistics developed
for this study do not allow a direct relationship between any given type
of truck and the tonnage which it collects.  However,  general infer-
ences may be drawn by the tonnage collected over the gross number of
trucks and overall proportions of specific types operated.
      In the context of tonnage collected, it appears as though contractors
who collect 1000 tons  or more daily  require a heavy commitment to
special collection vehicles, and  on the average operate 62.5 trucks
in total (Table 5. 18).  Among those contractors collecting 1000 tons
or more, 68 percent of their total tonnage  is commercial or industrial
(Table 3.6).
                                  TABLE 5.18
                      MEAN NUMBER OF TRUCK TYPES BY NUMBER OF TONS
                         COLLECTED PER DAY IN PRIVATE SECTOR
Typt ol Truck

Total Contractors
Mean Trucks
Packers
Non Packers
Special Collection
Vehicles
Number ot Tons Collected Per Day
1-6 7-12
2,636 1,726
1-6 2.1
0.7 1.5
0.8 0.5
0.0 0.1
13-24
1,865
3.6
2.6
0.6
0.3
35-49 50-99
1,238 1,099
5.2 8:9
3.8 5.9
°-6 0.8
0.7 2.3
100-249
918
13.6
9.6
0.6
3.3
250-499
277
24.7
16.7
1.1
6.7
500-999
161
37.3
30.1
1.9
5.3
1000
or more
110 10
62.5
40.3
1.5
20.7
Total
.02?
6.2
4.2
0.7
1.3
       Analysis from another point of view shows that operators of 50
 trucks or more average  83 trucks with 70 on the road daily,  and collect
 only 779 tons  per day (Figure 5.4).   It should be noted, however, that
 52.5 percent of the large contractors' waste is residential and therefore
 is less dense per  cubic  yard (Table 3.8).  At the same time the contrac-
 tor with 50 trucks or more operates a lower proportion of special collec-
 tion vehicles than his 1000 tons or more a day counterpart.

                                 5. 22

-------

R ^ • ' • \\.'. 	 .'• 	 -...;..: ;...-' •"- =' • ' T 	 - V':' 	 • 	 " 	 J— — —* -

•M
* W :\ \ : ! . :
10 C ' \\ : * - -
5 o - ±A\ - . ' : - .

^ u ^E^: r.—^
fsj J 	 _ 	 	 _
•M
_ -.7f -.---•• :•
51 : Vi
(/) n=r:z^=
^ y I7=mz:3
Ik. =Z~~Ii^

r* C ••
in ^S

rx m .
»§••= 	
ro ii
ro >, •"
i± a
r™ cri vi
in flJ ^ r» v E
J£ ^ U • O =
3 6 = ~2[1
!. O *^L-
1- ^ U
— O in
tv -* r- *— in
*•< ^ *~ f-
O i- O • c
h 1- H * o .
-«-
=^^-_-_— • »j L;

1 1 1 1
o in o m
o r^ in (vi

(U
1^
i_ o ^r
03 m
o .b 01
ui u
z
•z.
0
l/l I—
a- u >~
1 3 -J
(VI 
"> Q
215 o
o 2
•- -i O
z
JT
U
LU
_J
_l
^ 8
U3 3 ^/
i u
a:
l—
in U
* E i-
o
•-UJ
O. Nl
°M
* a: „
f> ^£ QJ Q-
(vi ^ CD p
ZH
< z
oi o
u ^
E "*
*• oi
- ce.
"D
O
O.

5.23

-------
      Packer trucks account for the majority of trucks owned by all con-
tractors, except for those who collect 1-6 tons, and for these contractors,
packers account foremost half (44.8%) of their total  trucks.  Among
contractors who collect 500-999 tons  daily, 79.6 percent of their fleet
are packer trucks.  They represent the highest proportion of packers oper-
ated by any particular contractor segment.  Part of this high percentage
of packers  includes front loaders  which make up 24.2  percent of the
trucks owned by 500-999 ton contractors,  and constitute more than twice
the percentage of front loaders operated nationally (12. 4%)(Table 5.20).
                                   TABLE 5.19
                          NATIONAL ESTIMATE OF TRUCK TYPES
                         BY TONS COLLECTED IN PRIVATE SECTOR
 T/pe of Truck                      Namber of Tons Collected Per Day
                  1-6   7-12   13-24  25-49  50-99  100-249 250-499  500-999  1000  Total
                                                                or more
Total Contractors
Total Trucks
Pack t-rs
Rear Loader
Front Loader
Side Loader
Non- Pa<_ kcrs
Open
Side Loader
Sure lal Collection
V t h i c 1 c- s
Roll-olf Chassis
Hoist Type Vehicle
Other Collection
Vehicles*
2,636
4, 065

1,259
184
377

2,137
30


26
--

52
1, 726
3,515

1,548
598
308

855
19


84
88

15
1, 865
6., 407

3,279
606
739

1,166
--


201
57

359
1,238
6,263

2,990
606
963

761
--


409
296

238
1, 099
9,914

3,803
1 ,074
1,363

898
13


682
276

1,805
918
12,198

4,538
2,002
1,902

594
21


1,884
596

661
277
6, 785

2,707
706
1,140

340
--


896
459

537
161
5, 731

2,597
1,388
578

319
--


702
1Z6

21
110
6,768

3.489
50fc
331

167
--


1,618
313

344
10,027
61

26
7
7

7



6
Z

4
,648

,230
,670
,702

,244
83


,496
,206

,034
    Other Collection Vehicles include satellite vehicles, container trains, etc.
                                   5.24

-------
                                     TABLE 5.20
                        PERCENT DISTRIBUTION OF TRUCK TYPES WITHIN TONS
                               COLLECTED IN PRIVATE SECTOR
   Type of Truck
                     1-6
                          7-12
                               13-24   25-49
Number Tons Collected Per Day
 50-99  100-249   250-499   500- (99   I'JOO
                          01 IP ir-
                                                                           Total
Distribution of Total
Contractors
Share of Total Trucks
Packers
Rear Loader
Front Loader
Side Loader
Non Packers
Open
Side Loader
Special Collection Vehicle
Roll-off Chassis
Hoist Type Vehicle
Other Collection
Vehicles *

100%
100
44,8
31 .0
4.5
9.3
53.3
52.6
0.7
s 1.9
0.6
--

1.3

100%
100
69.8
44.0
17.. 0
8.8
24.8
Z4.3
0.5
5.3
2.4
2.5

0.4

100%
100
72.2
51.. 2
9.5
11. 5
18.2
18.2
--
9.6
3.1
0.9

5.6

100%
100
72.8
47.7
9.7
15. 4
12.2
12.2
--
15.0
6.5
4.7

3.8

100%
100
62.9
38.4
10,8
13.7
9.2
9.1
0.1
27.9
6.9
2.8

18.2

lon%
100
69 .2
37.2
16.4
15.6
5.1
4.9
0-2
25.7
15.4
4.9

5.4

100%
100
67.1
39 -9
10.4
16.8
5.0
5.0
--
27.9
13.2
6.8

7.9

100%
IOC
79.6
•45.3
24.2
1 0.1
5.6
5.6
--
14.8
12.2
2.2

0.3

100%
100
6J
5: .'>
7 . 5
4. 9
2.5
2.5
--
33.6
23.9
4.6

5.1

100
100
67.
-i L. .
12.
12.
11 .
11 .
^
20.
10
Z.

6.

%

S
5
1
-j
9
8
1
7
5
6

6
     Other Collection Vehicles include satellite vehicles, container trains, etc.
      Contractors collecting 1000 tons or more  own 2,275 special col-
lection vehicles, and of these 1, 618 are roll-off chasses.  This consti-
tutes one-fourth of the total roll-off chassis operated by the  private
sector.  Roll-off chassis  comprise 24. 9 percent of the total  trucks oper-
ated by contractors collecting  1000 tons or more which is more than
twice the percent they  comprise in the fleet composition of the contrac-
tors taken in total (10. 5%).
      Contractors collecting 100 tons or more operated a disproportionate
share of trucks. Among total  contractors, those who collect 100 or more
tons per day make  up 14. 7 percent of all contractors, but operate 51.1
percent of the total trucks,  and collect 74. 7 percent of the total tonnage.
                                   5.25

-------
                                   TABLE 5 21
                       PERCENT DISTRIBUTION OF TRUCK TYPES BY TONS
                             COLLECTED IN PRIVATE SECTOR
Type of Truck

Distribution of Total
Contractors
Share of Total Trucks
Packers
Rear Loader
Front Loader
Side Loader
Non Packers
Open
Side Loader
Number
1-6
26. 3%
6.5

4.8
2.4
4.9

29.5
35.6
7-12
17.
5.

5.
7.
4.

11.
23.
2%
7

9
8
0

8
4
13-24
18.
10.

12.
7.
9.

16.
-
6%
4

5
9
k

1
•
25-49
12.
10.

11.
7.
12.

10.
-
3%
2

4
9
5

5
-
of Tons Collected Per Day
50-99 100-249 250-499 500-999 1
11.
16.

14.
14.
17,

12.
15.
0%
I

5
0
7

4
3
9.
19.

17.
26.
24.

8.
25.
2%
8

3
1
7

2
7
2
11

10
9
14

4

.8%
.0

.3
.2
.8

.7
--
1.6%
9. 3

9.9
18.1
7.5

4.4
-•
000 Total
• j:iurt
i.i',;
11.0

13.3
6.6
',.3

2.3
--
KJO
100

100
100
100

100
100
Special Collection Vehicles
Roll-off Chassis
Hoist Type Vehicle
Other Collection
Vehicles*
0.4
--

1.3
1.
4.

0.
3
0

4
3.
2.

8.
1
6

9
6.
13.

5.
3
4

9
10.
12.

44.
5
5

7
29.
27.

16.
0
0

4
13
20

13
.8
.8

.3
10.8
5.7

0.5
24.9
14.2

8.5
100
100

100
    Other Collection Vehicle) include satellite vehicles, cortainer train*, etc.
      Tonnage is the determinant of the fleet size and configuration of
the fleet in the private sector.  Certainly more trucks are required to
collect more tonnage.  Truck type is usually dictated by the type of
customers being served and the type of equipment appropriate to these
customers.  Within the limits  of this guideline, truck type is a signi-
ficant variable in allowing the  contractor  to maximize his load and,
therefore, operating efficiency.
                                    5.26

-------
REGIONAL AND CITY SIZE CHARACTERISTICS


      Truck types tend to vary according to the region of the country and


city size.   The variance is due to the type of service provided by the pri -

vate sector (residential, commercial, etc.), contractual conditions, and,


of course,  the types of waste collected.


                                     TAELE 5.22

                        NATIONAL ESTIMATE OF TOTAL TRUCKS OPERATED BY
                             PRIVATE SECTOR FOR EACH REGION
Type of Track
North
Northeast Atlantic
Total Contractors 529 2,024
Total Trucks 2,413 12,568
Pa crcr s
Rear Loader 932 6,086
Front Loader 387 742
Side Loader 119 997
N'on Packers
Open 543 1,784
Side Loader
SnociJil Coiioction Vehicles
Roll-off Chassis 268 1,454
Hoist Type Vehicle 104 965
Other Collection
Vehicles-* 60 540
Mid-
Atlantic
644
2,763
1,123
211
691
270
23
70
211
164
Region
South Mid- North
Atlantic West Central
373 2
3,413 14
1,412 6
327 I
497 1
407 1
23
193 2
91
463
* Other Collection Vehicles include satellite Vehicles, container
,401 1,603
,421 6,645
,892 3,144
,134 155
,035 310
,773 993
22
,333 284
524 91
708 1,668
trains, etc.
South
Central
507
3,592
604
708
1,162
358
410
166
184

Mountain
391
1,349
874
75
42
275
83

West
1,555
14,505
5,163
3,931
2,850
843
15
1,401
54
248

Total
10,027
61 ,648
26,230
7,670
7,702
7,244
83
6,496
2,206
4,034

TABLE 5.23
NATIONAL
Tvoe of Truck
over
1 ,000,000
Total Contractors 4,456
Total Trucks 35, 942
Packers
Rear Loader 15,895
Front Loader 4 .962
Side Loader 3.574
Non Packers
Open 3,339
Side Loader
Special Collection
Vc h:'.i<;s
Roil-off Chassis 4,554
Hoist Type Vehicle 966
Other Collection
Vehicles* 2,652
ESTIMATE OF TRUCK TYPES BY SMSA SIZE
IN PRIVATE SECTOR
500,000-
1,000,000
1, 311
8, 226

2,675
928
1,949
1,021
656
432
565
SMSA Size
250,000- 100,000-
499,999 249,999
1,498
6,137

2,623
867
855
891
17
448
263
173
1.017
5,028

1,993
514
655
717
24
351
324
450
50,000-
99,999
149
775

262
115
146
80
23
58
42
49
Non
SMSA
1,596
5,571

2,780
291
531
1,195
19
429
181
145
Total
10,027
61,648

26,230
7,670
7,702
7,244
83
6.496
2,206
4,034






     * Other Collection Vehicles include satellite vehicles, container trains, etc.
                                      5.27

-------
      The private contractor  population is concentrated in large, high
density, urban areas.  As a result,  two-thirds of the private sector
vehicles are operated in three regions   t-hr North  AH?TitM ,  Mu5<,vf <;f.
and We-s*', which account for on** half thr national p/~>p\i1.^*'ioTv  f or.- ^?
rerJrly, 71 percent of all trucks are  IT r-> \-ir-r-. of over c>oo,nC"'   r v  .,
while ^1 percent of the U.S. population  is locat*3-^ TL n^r  SV*-^ ' ;    i*-!v
16 percent of the private contractors, ^-nr> 9 perr«nt r>£ fh^ t^ir''<•- =•' *
IT non-SMSA's.  The private  r ontr m r j'o^hf-» of *?iirks,
more dependent on open trucks.
                                    TABLE 5 1H
                          MEAN NUMBER OF TRUCK TYPfS PY RFi"ION
                                 IN PRIVATE SECTOR
Type of Truck
Northeast

Total Contractors 529
Moan Trucks 4.56
Packers 2.72
Non Packers 1 .03
Special Collection
Vehicles 0.81


Type of Truck

Total Contractors
Mean Trucks
Packers
Non Packers
Special Collection
Vehicles
Region
North Mid- South Mid- North S-vit?-

2,024 644 373 2,401 1,603 507 --'»!
6.20 4.29 9.15 6.01 4.15 7.09 3.45
3.86 3.15 6.00 3.78 2.25 4.88 2.53
0.88 0.45 1.15 0.75 0.62 0.71 0.70
1.46 0.69 2.00 1.48 1.28 1.50 0,22
TABLE 5.25
MEAN NUMBER OF TRUCK TYPES BY SMSA SIZE
SMSA Size
over 500,000- 250,000- 100,000- 50,000- Non
1,000,000 1,000,000 499,999 249,999 99,999 SMSA
4,456 1,311 1,498 1,017 149 1.596
8.3 6.51 4.25 5.01 5.27 3.57
5.75 4.49 3.05 3.25 3.67 2.33
0.75 0.78 0.60 0.73 0.67 0.76
1.8 1.24 0.60 1.03 0.93 0.48



i - '

-------
      In the western states a high level of franchising has resulted in the
development of larger companies.  Many cities, or smaller communities
within SMSA's, are franchised in whole or part in this region and large
truck fleets are required to serve them.  Traditionally,  the South Atlantic
states have operated collection under municipal systems.  As  a result,  it
appears that relatively few companies have developed.  Those companies
that have been established have tended to grow through commercial and
industrial collection to relatively substantial size.
      Operation of specific truck types varies by  region.  Packers comprise
the largest share of trucks in all regions (67.5%), and are highest in the
West (82.3%).  Rear loaders make up the largest share of all trucks  (42.5%)
that operate in every region except the South Central where  side loaders
account for 32 percent of the total trucks,  front loaders  20  percent, and
rear loaders  17 percent.  The 3, 931 front  loaders operated  in the West
also account for half of the national total and 27 percent  of the total fleet
in that region.
                                   TABLE 5.26
                     PERCENT DISTRIBUTION OF TRUCK TYPES WITHIN REGIONS
                                 IN PRIVATE SECTOR
Type of Truck

Northeast
Distribution of Total
Contractors
Share of Total Trucks
Packers
Hear Loader
iTrcjnt Loader
Side Loader
Xon Pat-kcrs
Open
Sldu Loader
Spfcial Collfc'.ion
Vehiti'-s
Roll-off Chassis
Hoist Type Vehicle
Other Collection
Vehicles*

100%
100
59.6
38.6
16.1
4.9
22.5
22.5
--

17.9
11.1
4.3

2. 5
North
Atlantic


100%
100
62.
48.
S.
7.
14.
14.
-

23.
11.
7.

4.

2
4
9
9
2
2
-

6
6
7

3
Mid
Atlantic

100%
100
73.2
40.6
7.6
25.0
10.8
10.0
0.8

16.0
2.5
7.6

5. 9
South
Atlantic

100%
100
65.6
41.4
9.6
14.6
12.6
11.9
0.7

21.9
5.6
2.7

13.6
Region
Mid-
West

100%
100
62.9
47.8
7.9
7.2
12.5
12.3
0.2

24.7
16.2
3.6

4.9
North
Central

100%
100
54.3
47.3
2.3
4.7
14.9
14.9
--

30.8
4.3
1.4

25.1**
South
Central

100%
100
68.9
16.8
19.7
32.4
10.0
10.0
--

21.1
11.4
4.6

5.1
Mountain

100%
100
73.5
64.8 .
5.6
3.1
20.4
20.4
--

6.2
6.2
-.


West

100%
100
82.3
35.6
27.1
19.6
5.9
5.8
0.1

11.8
9.7
0.4

1.7
Total

100%
100
67.5
42.5
12.4
12.5
11.9
11.8
0.1

20.7
10.5
3.6

6.6
     Other Collection \fehicles include satellite vehicles, container trains, etc.
     The high percentage of other collection vehicles in the North Central is due to the effect of one contractor
     operating over 100 satellite vehicles
                                   5.29

-------
                                            TABLE 5.27

                            PERCENT DISTRIBUTION OF TRUCK TYPES WITHIN SMSA
                                       SIZE IN PRIVATE SECTION
Type of Truck

Distribution of Total
Contractors
Share of Total Trucks
Packers
Rear Loader
Front Loader
Side Loader
Non Packers
Open
Side Loader
Special Collection
Vehicles
Roll-off Chassis
Hoist Tvpe Vehicle
Other Collection
Vehicles *
SMSA Size
over
1,000,000

100%
100
69.3
43.3
15.5
10.5
9.0
9.0
--

21 .7
12.8
2.5

6.4
500,000-
1 ,000,000

100%
100
68. Q
31.5
12.6
24.8
12.0
12.0
--

19.0
8.0
4.9

6.1
250,000-
499,999

100%
100
70.7
42.7
14.1
1 1.9
14.8
14.5
0.3

14 .4
7.3
4.3

2.8
100,
249,

100
100
64.
39.
11 .
13.
14 .
14.
0.

20.
7.
6.

7 .
000-
999

/o
50,000-
99, T; 9

100

'!,
100
9
3
7
9
5
1
4

5
1
1

3
69.
32.
16.
20.
12.
10.
2.

17.
7.
5.

5.
6
8
5
3
6
1
5

B
6
1

1
Non
SMSA

iOO
100
65 .
49.
5.
10.
21 .
21 .
0.

13.
7
3.

2.

7(,

4
4
9

4
1
3

2
o
1

2
Total

1 C '}
100
67.
42.
12.
12.
1 1 .
11 .
0.

20.
10.
3 .

6.

•;»

5
5
4
5
0
H
1

I
^
1,

6
         * Other Collection Vehicles include satellite vehicles, container trains, etc.
       Specialized collection vehicles,  necessary in commercial and  indus-

trial collection,  are  primarily in the largest cities and in the North  Atlantic,

Mid-West,  and Western states.   About 65-70 percent  of the roll-off  chassis

and hoist type vehicles  are operated in these areas (Tables  5.28 and 5.29).


                                           TABLE 5.23

                            PERCENT DISTRIBUTION CF TRUCK TYPES BY REGION
                                        IN PRIVATE SECTOR
T ype of True k

Di
Sh


Northeast
str.iv.tior. of Total
Contractors 5.3%
are of Total Trucks 3.9
Rear Loader 3 . 5
F r o -. t L o a d e r 5.1
S.dc Loacer 1 . 5
North
Atlantic
20.
20.
23 ,
9 .
12.
2%
4
2
7
9
Region
Mid- So ith Mid-
Atlantic Atlantic West
6 4% 3.7% 23.
4.5 5.5 23.
4.3 b.4 26 .
?.."• 43 14.
9 .'J 6.5 13 .
9%
4
3
8
4
North
Central
16.
10.
12.
4.
0%
8
0
0
0
South
Central Mountain
5.
5.
2.
9.
15.
1% 3.9%
8 2.2
3 3.3
2 1 .0
1 .5
West
15.5%
23.5
19.7
51 .2
37.0
Total
100%
100
100
100
100
Non Packers


lr
\ ,




Open 7.5
Sid(-' Loader —
ocial Ccj.lt cnon
r .cl, i
Roll-oif Chasis 4. 1
IIi;i
-------
                                           TABLE 5.29

                            PERCENT DISTRIBUTION OF TRUCK TYPES BY
                                   SMSA SIZE IN PRIVATE SECTOR
Type of Truck

Distribution of Total
Contractors
Distribution of Total
Trucks
Packers
Rear Loader
Front Loader
Side Loader
Non Packers
Open
Side Loader
SVISA Si7.e
over
1,000,000

44.

58.

60.
64.
46.

46.
--

5%

3

6
7
4

1

500,000-
1,000,000

13.

13.

10.
12.
25.

14.
--

1%

3

2
1
3

1

250
499

14

9.

10,
11 ,
11 ,

\,>.
21,
,000-
,999

.9%

.9

,0
.3
,1

.3
.1
100,000-
249,999

10

8.

7
6
8

9
28

. 1%

Z

.6
.7
.5

.9
.7
50,
99

1

1

1
1
1

1
27
000-
,999

.5%

.2

.0
.5
.9

.1
.7
Non
SMS A

15.9%

9.0

10.6
3.8
6.9

16.5
22.6
Tola!

100%

100

100
100
100

100
100
Special Collection Vehicles
Roll-olf Chassis
Hoist Type Vehicle
Other Collection
Vehicles *
70.
43.

65.
1
8

7
10.
19.

14.
1
6

0
6
11

J
.9
.9

.3
5
14

11 .
.4
.7

2
0
1

1.
.9
.9

2
6.6
8.2

3.6
100
100

100
* Other Collection Vehicles include satellite vehicles(  container trains, etc.
                                        5.31

-------
PACKER-NON PACKER USE TRENDS
      Nationally, packers increased by 83 percent from 1965 to 1970 to a
level of 41, 600.  During the same period, non-packers decreased from
8800 to 7300,  or 16 percent.  These parallel equipment patterns demon-
strate vast changes in use of technology and capacity among private con-
tractors during the late 1960's.
      The trend data available from this survey indicates that those com-
panies operating during the period grew by 55 percent in the total  number
of packer and non-packer trucks operated.
                              TABLE 5.30
                 NATIONAL ESTIMATE OF TRENDS IN OPERATION OF PACKER
                   AND NON PACKER TRUCKS IN THE PRIVATE SECTOR

1965
1968
Percent Change
1965 to 1968
1970
Percent Change
1968 to 1970
Percent Change
1965 to 1970
Number Percent
22,739 72.1%
31,843 79.4%
+40.0%
41,602 85.0%
+30.6%
+ 83.0%
Type of Truck
Non Packers
Number Percent
8,784 27.9%
8,308 20.7%
-5.4%
7,327 15.0%
-11.7%
-16. 1%
Total Parkers and
Non Packers
Number
31,523
40,151
+ Z7.
48,929
+21.
+ 55.
Percent
100%
100%
4%
100%
9%
2%
NOTE:  This does not imply the entire industry grew at this rate.  Some
companies have gone out of business and they are not considered here.
However, in terms of the absolute number of trucks,  growth in truck
count has been impressive.
                                 5.32

-------
       Growth in packers has been fairly constant proportionately  by region

throughout the country,  ranging from a low of a 40 percent increase in the

North Central region to  a.  62 percent increase in the Mountain region.
                                        TABLE 5.31
                        NATIONAL ESTIMATE OF TRENDS IN OPERATION OF PACKER
                               AND NON PACKER TRUCKS BY REGION
  Type ol Track                                      Regior^

                           North    Mid-    South    Mid-   North   South
                 Northeast  Atlantic   Atlantic  Atlantic   West  Central  Central Mountain   '.V«»t


  Packers
       1970
       1968
       1965

  Non- Packers
       1970
       1968
       1965

  Total Packers and
  Non Packers
       1970
       1968
       1965

  Special Collection
  Vehicles


  Total Trucks
       1970
1,438
1.Z07
  804


  543
  580
  469
7.8Z5
6,534
4.5Z5


1,784
2,157
2,096
1,981   9,609
1,787   8,691
1,273   6,619
  430   2,959

2,413   12,568
Z.025
1,244
  843


  293
  281
  247
        Z.318
        1.5Z5
        1,090
          445


        2,763
Z,Z36
1,549
1,039

  430
  476
  373
Z.666
Z.025
1,412
9,061
6,954
4,746
1,795
1 ,916
1,844
              10,856
               8,870
               6,590
         747    3,565

       3,413   14,421
3,609  2,474
2,840  1,802
2,159  1,285
  993
1,024
  908
348
253
201
       991
       690
       374
275
275
       4,602   2,832    1,266
       3,864   2,055     965
       3,067   1,486     59d
               2,043    760     83


               6,645   3,592   1,349
      11,944  -ll.lijt
      9,024  31,843
      6,96fa  22,739
                    12,802  4B,?29
                    10,370  4'J, 1 51
                     9,389  31,523
                            1,703   12.736


                            14,4C5   6l,t48
  The three  principal  regions having the preponderance of packer trucks

  operate essentially the same proportion of total packers today   as they did

  five years ago.

        The  decrease  in non-packers is deceptive.   In fact,  the number  of

  non-packers has remained relatively constant in most regions of the coun-

  try, and even increased  in some.   Virtually all of the decline in non-

  packers  since 1965 can be attributed to the decrease of non-packers in

  the West.
                                        5.33

-------
                                           TABLE 5.32

                           MEAN NUMBER OF PACKERS AND NON PACKERS IN
                             1970, 1968. AND 1965 BY SIZE OF CONTRACTOR
Tvpe o! Truck

Packers
1170
1968
19t 5
Non XVckirs
1970
1968
1965
Total Packers and
Non 1',-ickers
L'I'/Q
19^8
1965
Sncci.-xl Collection
VchjrU's
1 970
Total Trucks
1970
Size of Contractor
1
truck

0
0
0

0
0
0


0
0
0


0

1

.56
,48
.39

.42
.41
.41


.98
.88
.80


.02

.00
2-3
trucks

1
1
0

0
0
0


2
1
1


0

2

.61
.31
.86

.60
.64
.59


.21
.95
.44


.19

.40
4-5
trucks

3
2
1

0
0
0


3
2
2


0

4

.07
.14
.38

,75
.84
.79


.82
.98
.17


.60

.42
6-9
trucks

4
3
2

0
0
0


5
4
3


1

7

.83
.77
.70

.90
.99
.87


.73
.76
.57


.44

.17
10-19
trucks

9
7
5

0
0
0


10
8
6


2

13

.93
.97
.71

.87
.93
.93


.80
.90
.64


.51

.31
20-49
trucks

in
14
10

1
1
1


19
15
11


8

27

.17
.07
.41

.22
.54
.56


.39
.61
.98


.20

.59
50 or more
trucks Total

57
40
30

4
8
15


62
48
46


20

82

.69
.06
.56

.75
.00
.44


.44
.06
.00


.32

.75

4. .15
3.18
2.27

0.73
0.83
0.88


4.88
4.00
3,15


1.27

6.15
                                             TA3LE 5.33

                        mEAN NUiviSER OF PACKEKS AND NON PACKERS IN 1970, 1968,
                            AND 1965 BY NUMBER OF TONS COLLECTED PER DAY
Type of Truck
                    1-6
                  Number of Tone Collected Per Day

7-12   13-24   25-49  50-99   100-249   250-599   500-999
                                                                                           Total
P.K !•< rt,



Non



1970
1968
I'll 5
Packer*
1970
1968
1965
0
0
0

0
0
0
.73
.57
.37

.80
.79
.73
1
1
0

0
0
0
.53
.19
.84

.48
.54
.54
2
2
1

0
0
0
.62
.07
.34

.60
.69
.56
3
2
2

0
0
0
.85
.84
.05

.58
.70
.57
5
4
3

0
0
0
• 90
.35
.19

.78
.83
.79
9
7
5

0
0
1
.63
.84
.63

.63
.76
.01
16
14
11

1
1
1
.36
.54
.32

.14
.68
.82
30
25
20

1
3
4
.06
.75
.88

.88
.06
.00
40
19
11

1
3
13
.27
.64
.09

.45
.45
.45
4.15
3.18
2.27

0.73
0.83
0.88
Total Packers and
Xon



sr,
Vnr.i

Par kor h
1970
l')68
19>.5
lal Collection
c]r-s
1970

1
1
1


0

.53
.36
.09


.03

2
1
1


0

.01
.72
.38


.11

3
2
1


0

.22
.75
.91


.33

4
3
2


0

.42
.54
.62


.74

6
5
3


2

.68
.17
.98


.26

10
8
6


3

.26
.60
.64


.31

18
16
13


6

.00
.21
.14


.71

31
28
24


5

,94
.81
.88


.32

41
23
24


20

.73
.09
.55


.73

4.88
4.00
3.15


1.27
Total Trucks

1970
1
.57
2
.11
3
.56
5
.16
8
.94
13
.57
24
.71
37
.25
b2
.45
6.15
                                               5.  34

-------
                                  TABLE 5.3U
                      MEAN NUMBER OF PACKERS AND NON PACKERS IN
                        1970, 1968, AND 1965 BY MIX OF COLLECTION
Type of Truck

Packers
1970
19 (-8
19t5
Open Non Packer*
1970
1968
1965
Total i'ackcrs and
.•".or. I/v-i"'rs
1970
] ') •'. K
1 ri f. 5
Special Collection
1970
Total Trucks
% Residential Collection
100%

2
2
2

0
0
0


3
3
2
Vehicles
0


.84
.43
.03

.73
.70
.49


.57
.14
.51

.05

80-99%

5
3
2

0
0
0


5
4
3

0


.22
.57
.89

.57
.73
.8:


.79
.30
.69

.81

60-79%

6
4
3

0
0
1


7
5
4

0


.36
.94
.21

.71
.99
.74


.07
.94
.95

.51

40-59%

6
5
3

0
0
0


7
6
4

0


.56
.21
.79

.80
.82
.81


.36
.0-4
.59

.82

20-39%

8
6
4

0
0
0


8
6
5

1


.18
.30
.59

.64
.65
.70


.82
.95
.29

.68

1-19%

2
2
1

0
0
0


3
2
2

0


.90
.40
.42

.54
.58
.63


.44
.98
.06

.90

100%*

2
1
1

0
0
0


3
2
2

1


.43
.91
.34

.83
.91
.83


.26
.81
.16

.88

Total

4
3
2

0
0
0


4
4
3

1


.15
.18
.27

.73
.83
.88


.88
.00
.15

.27

     1970
                   3.62   6.59
                                7.58
                                       8.18
                                              10.48
                                                     4.53
                                                           5.14
                                                                  6.15
  * Commercial and Industrial
Ranking those contractors who increased their packer truck fleets at a
rate above the national norm (83%) on selected characteristics,  we include
operation of:
                  50 or more trucks
                  4-5 trucks                      122
                  2-3 trucks                       87
%
89
                  1-9 percent residential
                      tonnage                    104
                  60-79 percent residential
                      tonnage                     98
                  1000 tons or more per day      263
                  13-24 tons per day              95
                  25-49 tons per day              88
                  50-99 tons per day              88
                                  5.35

-------
Clearly, the mechanization process in packer trucks reaches it highest
level among contractors collecting 1000 or more tons per day and who
collect 68 percent of their refuse from commercial and industrial sources
(Table 3. 6).  This is probably correlated with growth in front end loaders
and containerization.  At the same time large fleets were adding packers,
they were dropping non-packers.  The information contained in  Table 5.33
shows that the loss among non-packers  is over whelming, among companies
collecting 100 tons or  more per day.  The decrease  in the average number
of non-packers is greatest among the largest companies.
      Supporting the decrease of non-packers  among  large companies is
the parallel decrease in non-packers among contractors located in the
larger cities.
                                 TAI3LE 5.35
                    MEAN NUMBER OF PACKERS AND NON PACKERS IN 1970,
                            1968, AND 1965 BY SMSA SIZE
Type of Truck

1
over
,000,000
500,000-
1,000,000
SMSA Size
250,000-
499,999
100,000-
249,999
50
99
,000-
,999
Non
SMSA
Total
Packers
N'on

Non
1970
19( B
1965
Packers
1970
19^3
1V.5
i PrjciM-i s and
Packers
1970
196B
Special Collection Vehicles
Tola

1970
1 Trucks
1970
5
4
3
0
0
1
6
5
0
1
8
.75
.51
.40
.75
.92
.19
.50
.43
.59
.80
.30
4
3
2
0
0
0
5
4
3
1
6
.49
.47
.71
.78
.92
.84
.27
.39
.55
.24
.51
3
2
1
0
0
0
3
2
2
0
4
.05
.19
.44
.60
.70
.67
.65
.89
.11
.60
.25
3
2
1
0
0
0
3
3
2
1
5
.25
.48
.41
.73
.67
.60
.98
.15
.01
.03
.01
3
2
1
0
0
0
4
3
2
0
5
.67
.80
.80
.67
.87
.73
.34
.67
.53
.93
.27
2
1
0
0
0
0
3
2
1
0
3
.33
.60
.91
.76
.78
.69
.09
.38
.60
.48
.57
4.15
3.18
2.27
0.73
0.83
0.88
4.88
4.00
3.15
1.27
6.15
                                  5.36

-------
SPECIALIZED EQUIPMENT
      Beyond the typical vehicle operations,  various kinds of containers
play a major  role in the  contractor's operations.  Basically, the container
allows an increased volume of on-site  storage prior to collection,  and
a limitation on the frequency of required collection.  Containerization is
more prevalent among large contractors in service to commercial cus-
tomers.  However, as will be explained later in this chapter,  some con-
tainerization  is used in exclusively residential conditions.
      This study quantified private contractor services relating to four
types of specialized equipment--roll-off bodies, stationary containers,
specially designed stationary  containers,  and stationary  compactors.
Often these four types  of equipment are used in combination with each
other and  therefore, do not represent completely distinct installations.
Furthermore, some  contractors may not own the  specialized equipment
which they account for, since the customer may be  the owner.   In this
case, the contractor still services the  equipment.
      The private sector operates or services about 1.8  million stationary
containers or 290 per contractor among those that service that type of
equipment.  It should be noted that 67.5 percent of all contractors  operate
packers which closely correlates to the 61 percent  servicing stationary
containers.
                                   TABLE 5.36
                       NATIONAL ESTIMATE OF SPECIALIZED EQUIPMENT
                           SERVICED BY THE PRIVATE SECTOR
Type of Equipment
Roll-off Bodies
Roll-off Chassis
(Ratio of Bodies to Chassis)
S'af.or.ary Containers
Specially Designed Stationary
Containers *
Stationary Compactors
Total Number of Contractor
Number Who Service
109,151 2,084
*>,494 2,084
16.8
1,783,876 6,156
20,812 656
20.479 1,713
s Percent of Contractors Mean Number
Who Service Per Contractors
20.8% 52.4
20.8% 3.1

61.4% 289.8
6.5% 31.7
17.1% 12.0
    * Includes sludge containers, acid containers, rubber or plastic lined containers, etc.
                                 5,37

-------
      Stationary containers have a wide range of uses  due to their range
in size (from 1/2  yard up).  They are used in large proportion by those
contractors who are exclusively commercial and  industrial.  However,
it is important to  note the  incidence of specialized containers  in residen-
tial collection.  An example of containerization in residential collection
is the system currently in use in Bade County,  Florida, where  each
household has a small container on wheels which is  serviced at curbside.
      Roll-off bodies are used by contractors of all sizes (in terms  of
truck count).  The one-truck contractors depicted in the following table
operate single roll-off chassis each of which on the  average supports almost
13 roll-off bodies.  The national total of 109, 000 bodies represents  16. 8
bodies  per chassis.  The wide variance in that  relationship is best ex-
plained by the 39:1  ratio experienced by the largest  contractors compared
to the national norm.  Large contractors  service 41 percent of all roll-
off bodies.  This  apparent high level of efficiency is probably due to the
large contractor's  ability  to drop roll-off bodies  for long periods of time
between pickups to  service construction sites,   or  to use for other indus-
trial and commercial  tasks.
                                   TABLE 5.37
                 NATIONAL ESTIMATE OF SPECIAL EQUIPMENT BY CONTRACTOR SIZE
                                IN PRIVATE SECTOR
Tvpe of Equipment

Total Contractors
Roll-off Bodies
Roll-off Chassis
1 2-3
truck trucks
2,608 3,193
655 3,929
52 429
Size
4-5
trucks
1, 421
5,348
481
of Contractor
6-9
trucks
1, 261
13,207
1,195
10-19
trucks
982
17,682
1,351
20-49
trucks
405
23,457
1,838
50 or more
trucks
157
44,861
1,150
Total
10,02
109,15.
6,49'
   (Ratio of Bodies to Chassis)   12.6     9.2     11.1     11.1     13.1     12.8    39.0     16.8

  StaUonary Containers      42,813  164,117   165,900   217,633   488,782   394,237  310,394  1,783.876
Special Designed Stationary
  Containers*
Stationary Compactors
Mean Number of Stationary
  Compactors
395    1,082   2,060
942      840   4,628
                                                    5,432    10,718   1,103   20,812
                                                    4,853    5,181   4,034   20,479
                               4.8
                                       4.5
                                             10.1
                                                     9.6
                                                            20.4
                                                                   41.3
                                                                           2.0
  * Includes sludge containers, acid containers, rubber or plastic lined containers, etc.
                                     5.38

-------
                                        TABLE 5.38


                     PERCENT DISTRIBUTION OF SPECIAL EQUIPMENT BY CONTRACTOR
                                    SIZE IN PRIVATE SECTOR
Type of Eauipment
1
truck
Total Contractors 26.0%
Roll-off p.odies 0.6
Roll-off Chassis 0.8
Stationary Containers 2.4
Specially Designed Stationary
Containers *
Stationary Compactors
Size of
2-3
trucks
31.8%
3.6
6.6
9.2
1.9
4.6
4-5
trucks
14. 1%
4.9
7.4
9.3
5.2
4. 1
6-9
trucks
12.
12.
18.
12.
9.
22.
6%
1
4
2
9
6
Contractor
10-19 20-49
trucks trucks
9. 8% 4. 0%
16.2 21.5
20.8 28.3
27.4 22.1
26.1 51.5
23.7 25.3
50 or more
trucks Total
1.6%
41. 1
17.7
17.4
5. 3
19.7
100%
100
100
100
100
100
     * Includes .sludge containers, acid containers, rubber or plastic lined containers, etc.





       The ratio of roll-off bodies to chassis is lowest among commercial


collectors.   This coincides with the commercial operator being smaller


(5. 0 trucks on the average) than companies  collecting a combination of


wastes.




                                         TABLE 5.39

                     NATIONAL ESTIMATE OF SPECIAL EQUIPMENT BY MIX OF COLLECTION
                                      IN PRIVATE SECTOR
Type of Equipment
100%
Total Contractors 375
Roll-off Bodies 218
Roll-off Chassis 20
(Ratio of Bodies to Chassis) 10.9
Stationary Containers 1.784
Specially Designed Stationary
Containers #*
Stationary Compactors
Mean Number of Stationary
Compactors
% Residential Collection
80-99%
1, 835
31, 326
689
45.5
130,223
125
1,270
0.7
60-79%
1,402
12,225
461
26.5
276,501
10,260
694
0.5
40-59%
1,081
12,225
494
24.7
280,069
1, 165
1,454
1.3
20-39%'
661
11,024
747
14.8
255,094
812
3,113
4.7
1-19%
522
2,292
234
9.8
92, 762
749
704
1.3
100%*
4, 143
39, 731
3, 852
10.3
747, 444
7,680
13,250
3.2
Total
10, 027
109, 151
6,496
16.H
1,783, 376
20, 812
20,479
2.0
   * Commercial and Industrial
  ** Includes sludge containers, acid containers, rubber or plactic lined containers, etc.
                                           5.39

-------
       Stationary compactors  are concentrated among the large contractors

(20-39% residential) and contractors who collect 100 percent commercial

and industrial refuse.  This type of equipment is generally mated  with

roll-off bodies.   It is estimated that the private sector owns or  services
over 20,000  stationary compactors.
                                      TABLE 5.tO

                         PERCENT DISTRIBUTION OF SPECIAL EQUIPMENT
                           BY MIX OF COLLECTION IN PRIVATE SECTOR
TyDe of Equipment
100%
Total Contractors 3.7%
Roll-off Bodies 0.2
Roll-oft Chassis 0.3
Stationary Containers 0,1
Specially Deaigned Stationary
Containers **
Stationary Compactors
% Residential Collection
80-99% 60-79% 40-59% 20-39%
18.3% 14.0% 10.8% 6.6%
28.7 11.2 11.2 10.1
10.6 7.1 7.6 11.5
7.3 15.5 15.7 14.3
0.6 49.3 5.6 3.9
6.2 3.4 7.1 15.2
1-19% 100%* Total
5.2% 41.3% 100%
2.1 36.4 100
3.6 59.3 100
5.2 41.9 100
3.6 36.9 100
3.4 64.7 100
    '"' Commercial and Industrial
   ** Includes sludge containers, acid containers, rubber or plastic lined containers, etc.
                                   TABLE 5.U1

                   NATIONAL ESTIMATE OF SPECIAL EQUIPMENT BY SMSA SIZE
                                IN PRIVATE SECTOR
Type ot Equipment
1
Total Contractors
Roll-off Bodies
Roll-off Chassis
(Ratio of Bodies to Chassis)
over
,000,000
4,456
86,120
4,554
18.9
Stationary Containers 1,189,845
Specially Designed Stationary
Containers *
Stationary Compactors
Mean Number of Stationary
Compactors
6,244
13.086
15.4
500,000-
1,000,000
1,311
10.042
656
•15.3
258,662
12,466
2,703
10.3
SMSA Size
250,000- 100,000-
499,999 249,999
1,498
6,767
448
15.1
114,168
187
2,294
10.7
1,017
2,401
351
6.8
67,787
749
901
5.5
50,000-
99,999
149
546
58
9.4
17.839
645
102
2.0
Non
SMSA
1, 596
3,165
429
7.4
133,791
520
1,393
8.4
Total
10,027
109.151

-------
       Virtually all of the specialized collection  equipment is  located in

cities of over 250, 000.
                                            TABLE 5.12

                        PERCENT DISTRIBUTION OF SPECIAL EQUIPMENT BY SMSA SIZE
                                        IN PRIVATE SECTOR
       Type of Equipment                                 SMSA Size

                                over     500,000-    250,000-   100,000-   50,000-   Non
                              1,000,000  1,000,000   499,999    249,999    99,999   SMSA   Total
Total Contractors
Roll-off Bodies
Roll-off Chassis
Stationary Containers
Specially Designed Stationary
Containers "
Stationary Compactors
44
78.
70,
66
30
63
.5%
.9
.1
.7
.0
.9
13
9
10
14
59
13
. 1%
.2
.1
.5
.9
.2
14
6
6
6
0
11
.9%
.2
.9
.4
.9
.2
10
2
5
3
3
4
.1%
.2
.4
.8
.6
.4
1
0
0
1
3
0
.5%
.5
.9
.0
.1
.5
15
2
6
7
2
6
.9%
.9
.6
.5
.5
.8
100%
100
100
100
100
100
       '•'Includes sludge containers, acid containers, rubber or plastic lined containers, etc.
                                             5.41

-------

-------
 DIRECT CUSTOMER CONTRACTING AND GOVERNMENT FRANCHISING

      This chapter describes the extent of direct customer contracting
and government franchising* among private contractors.  These two
methods of service are discussed for both residential and commercial
customers.   Data on direct customer contracting and franchising are
analyzed by contractor size, daily tonnage, mix of collection, SMSA
and non-SMSA units, and region.
      Tabular output for each variable includes:
      •    National estimates  of the number  of contractors engaged
           in direct customer  contracting and government franchising
           and the number of customers  served under each system.
      •    The percent distribution of contractors across categories
           for each variable.
      •    The percent distribution of customers across and within
           categories for each variable.
      This chapter is structured  into the following subsections:
      •    Chapter Summary
      •    Extent of Direct Customer Contracting and Franchising
      •    Contracting/Franchising and Contractor Size
      •    Contracting/Franchising and Daily Tonnage
      •    Contracting/Franchising and Mix  of Collection
      •    Regional and City Size Characteristics
* Government franchising in this context refers to franchises or contracts
awarded private contractors by municipalities,  county governments, etc.
                                6.1

-------
                          CHAPTER SUMMARY
    The data illustrating the extent of direct cust mer contracting and govern-
ment franchising show that approximately half of  ie residential customers are
serviced under direct customer contract, while the great majority of commercial
customers are serviced by direct contract.
    The incidence of government franchising is I in ted to approximately one-
third of the residential contractors, and less than 10 percent of the commercial
contractors.  Contractors with government franchises are, on the average,
larger  (as measured by  number of trucks operated and daily tonnage), collect
both residential and commercial customers, are located in SMSA's of over one
million, and are located  in the North Atlantic, Mid-Atlantic, South Central, and
West regions.
                                   6.2

-------
 EXTENT OF CONTRACTING AND FRANCHISING
        Nearly half of the residential customers collected by the private
 sector are served under direct contract arrangements.  While residential
 customers are divided equally between direct contracting and  franchising
 mechanisms, only 30 percent of the 5, 883 contractors who collect from
 residential customers have government franchises.  This  indicates that
while  fewer contractors have franchises than contract direct,  those con-
tractors that do have franchises tend to be  larger and collect  from more
customers."  Those contractors who service residential customers under
government franchises collect,  on the average,  7,068 customers,  while
the contractors who have direct contracts with  residential customers
collect an average of 2, 534 customers (Table 6. 1).
        Commercial customers serviced under  government franchises
comprise  a relatively minor segment (12.8%) of the total commercial
customers.
                                     TA;3LE 6.1
                 NATIONAL ESTIMATE OF CUSTOMERS SERVICED BY THE PRIVATE SECTOR
                      UNDER DIRECT CONTRACT AND GOVERNMENT FRANCHISE
T\ TV of Collection
Rn«,K!"nt!al Customers
Cor.truct Direct
Govern! ri(jnt Franchise
Total Residential Customers
Onmrnorc'ip.l Customers
Contract Dirvct
Govf . r.rnrr.t I'ranchise
'iota! Commercial Customers
Number of
Customers
12,432,140
12,284,509'
24,716,758
1,990,083
285,445
2,275,528
Perce.it of.
Customers
50.3%
49.77.
100. 0%
87.27.
12.87.
100. 07.
Number of
Contractors
4,906
1,738
5,883"
9,055
741
9,651**
Number of Customers
Per Contractor
2,534
7,068
4,201
220
385
236
   *  The original estimate of Government franchise customers was 11,717,509 or 47.4 percent of
     all reMdrvitial customers. Tho 2.3 percent of residential customers unaccounted for was the result
     of sorr.c responding contractors counting a government franchise as one customer and reporting
     serving one cu.stomer under government franchise.
   •* The number of contractors who contract directly and have government franchises add to more than the
     total because some contractors operate under both direct contracting and government franchise systems.
                                      6.3

-------
 CONTRACTING/FRANCHISING AND CONTRACTOR SIZE
         Large  contractors account for a disproportionate share  of the con-
 tractors servicing residential customers under government franchise.   Of
 the  135 residential contractors operating 50 trucks or more,  74 percent
 have government franchises, while among  the  1,347 residential one-truck
 contractors  only 14 percent  have government franchises  (Table 6.2).
                                     TABLE 6.2
                   NATIONAL ESTIMATE OF PRIVATE CONTRACTORS WHO CONTRACT
                   DIRECT AND HAVE GOVERNMENT FRANCHISES BY CONTRACTOR SIZE
Type of Collection

truck


trucks


trucks
Size of C

trucks
Contractor

trucks


truck s '!"•.< !- i "1 
-------
        A similar but less dramatic situation occurs with commercial
franchises.   Small contractors represent 56 percent of those contractors
with commercial franchises,  while large contractors account for 33
percent (Table 6.3).
                                   TABLE 6.3
                 PERCENT DISTRIBUTION OF PRIVATE CONTRACTORS WHO CONTRACT
                 DIRECT AND HAVE GOVERNMENT FRANCHISES BY CONTRACTOR SIZE
 Type of Collection                       Size of Contractor

                 1       2-3      4-5      6-9      10-19     ZO-49    50 or more
               truck    trucks    trucks    tracks    trucks    trucks     trucks    Total
 Distribution of Total
 Contractors        26.0%    31.8%     14.1%     12.6%      9.8%    4.0%      1.6%     100T,
 Residential Contractors
Direct Contract
Government
Franchise
Total Residential
Contractors
24

10,

22.
.8

.9

.9
33

23.

31 ,
.2

.0

.7
16,

10.

15,
.2

,9

.2
11

14

11
.3

.9

.4
10.1

21.3

11.6
2

13

4
.5

.2

.9
1

5,

2,
.9

.7

.3
100

100

100
Commercial Contractors
Direct Contract
Government
Franchis e
Total Commercial
Contractors
24.

12.

24.
.8

,3

,7
33.

29.

32.
.2

.6

.4
14.

13.

14.
,9

6

,5
13,

11 ,

12,
.0

.1

.9
9.5

14.8

10.0
3

12

3
.1

.3

.8
1 .

6.

1 .
.6

,2

,7
100

100

100
        The number of customers serviced under franchises is also related
to contractor  size.  Over half of the total group of residential and commer-
cial customers collected by private contractors under government fran-
chises  are serviced by contractors with 20 or more trucks.  This exceeds
the  overall share  (42%) of  residential and commercial customers serviced
by that group,  illustrating the point that larger contractors are franchise-
oriented (Table 6.5).
                                    6.5

-------
                                               TABLE 6.«

                        NATIONAL ESTIMATE OF CUSTOMERS SERVICED BY THE PRIVATE
                      SECTOR UNDER DIRECT CONTRACT AND GOVERNMENT FRANCHISE BY
                                          SIZE OF CONTRACTOR
Tyr/f; of Crjlh'ctum

Total Contractors
Total Customers*'
Size of Contractor
1
truck
2,608
755,40]
2-3
trucks
3, 193
2,368,715
4-5
truck*
1,
2,002,
421
673
6-9
trucks
1,261
3,445, 927
10-19
trucks
982
7.242, 717
20-49
trucks
405
5,571,637
50 or more
trucks

5,986,
157
477
Total
10,
27.351,
027
013
Rp^i'l f nrial C istomers
Direct Contract
G'jvprnmc-nt
Fr;iriC.l.ibc
Total Residential
C ibtomcrs
400,411
266,941
667, 352
1,277,509
816, 768
2,094,277
1,493,
305,
1,799,
207
837
044
2,065,372
1, 064, 512
' 3, 130,917
3,481, 701
3,219,798
6,707,912
1, 338,741
3, 810,264
5, 149,005
2, 386,
2.803,
5, 191,
942
463
599
12,432,
12,284,
24,716,
149
609
758
CoKj/n"rclal Customers
Direct Contract
Government
Franchise
To'.al Commercial
CubtfjCm rs
67,663
11,418
79,081
228,360
9,705
238,565
171,
3.
174,
147
425
572
243, 895
23,977
268,017
394,036
52,522
446,558
250,750
83,635
334,385
632,
101,
733,
846
048
894
1,990,
285,
2,275,
083
445
528
Total Customers include industrial customers.
                                                TABLE 6.5

                       PERCENT DISTRIBUTION OF CUSTOMERS SERVICED BY THE PRIVATE
                        SECTOR UNDER DIRECT CONTRACT AND GOVERNMENT FRANCHISE
                                          BY SIZE OF CONTRACTOR
 Type of Collection
                                                    Size of Contractor
1
truck
2-3
trucks
4-5
trucks
6-9
trucks
10-19
trucks
20-49
trucks
50 or more
trucks
Total
 Distribution of Total
 Contractors            26.0%   31.8%     14.1%      12.6%       9.8%      4.0%     1.6%

 Share of Total
 Customers*             2.7     8.6      7.3       12.6      26.5       20.4     21.9

 Residential Customers

    Direct Contract       3.2    10.3      12.0       16.6      28.0       10.8     19.2

    Government
    Franchise            2.2     6.7      2.5        8.7      26.2       31.0     22.8

    Total Residential
    Customers           2.7     8.5      7.3       12.7      27.1       20.8     21.0

 Commercial  Customers
    Direct Contract      3.4     11.5      8.6       12.3      19.8       12.6     31.8

    Government
    Franchise           4.0      3.4      1.2        8.4      18.4       29-3     35.4

    Total Commercial
    Customers          3.5     10.5      7.7       11.»      19.6       14.7     32.3
100%


100


100


100


100


100


100


100
 *  Total Customers include industrial customers.
                                                 6.6

-------
       An analysis of customers  serviced under direct customer contract
or government franchise as  a function of the size of contractors shows
that customers serviced under government franchises make up the largest
share of total customers among contractors  operating 20 or more trucks.
Contractors operating 20-49 trucks collect 74 percent of their residential
customers and 25 percent of their commercial customers under government
franchises.  Contractors operating 50 trucks or more service 54 percent
of their residential customers and 14 percent of their commercial cus-
tomers under a franchise (Table  6.6).  Of all contractor size categories,
only those contractors with  20-49 trucks collect more than half (71 percent)
of their total  customers under a  franchise mechanism.   These contractors
are heavily concentrated in  those regions and city size strata which have
a high degree of franchising (Tables 6.20 and 6.23).
                                  TABLE 6.6
                 PERCENT OF CUSTOMERS SERVICED BY THE PRIVATE SECTOR UNDER
                    DIRECT CONTRACT AND GOVERNMENT FRANCHISE WITHIN
                               CONTRACTOR SIZES
Typo of Collection

Resir.cr.tial Customers
Direct Contract
Government
Franchise
Total Residential
Contractors
C'^mri.crr ia] CustG-T-c-rs
Direct Cor.lract
Govc rn.i'.er.t
Franchise
Total Commercial
Customers
1
truck
60%
40
100%
86%
14
100%
2-3
trucks
61%
39
100%
96%
4
100%
4-5
trucks
83%
17
100%
98%
2
100%
Size of
6-9
trucks
66%
34
100%
91%
9
100%
Contractor
10-19
trucks
52%
48
100%
83%
12
100%
20-49
trucks
26%
74
100%
75%
25
100%
50 or more
trucks
46%
54
100%
86%
14
100%
Total
50%
50
100%
87%
13
100%
                                   6.7

-------
CONTRACTING/FRANCHISING AND DAILY TONNAGE
      The relationship of daily tonnage to the type of contracting mechanism
follows the same pattern as that of contractor size.   Contractors collecting
a large number of tons per day are the most involved in franchise collection
arrangements for both residential and commercial customers.
        The number of contractors with franchises for residential customers
is larger than the number  contracting directly for those contractors collecting
250 tons per  day or more.   There are no tonnage categories in which contrac-
tors with government franchises for  commercial customers outnumber those
who contract directly.  However, the percent of contractors with government
franchises is greater among contractors  collecting 50 tons  or  more per day
than the percent they comprise of total commercial contractors (Table 6. 8).
                                     TABLE 6.7
                    NATIONAL ESTIMATE OF PRIVATE CONTRACTORS WHO CONTRACT
                      DIRECT AND HAVE GOVERNMENT FRANCHISES BY TONNAGE
Type of Collection


Total Contractors
Number of Tons Collected Per Day

1-6
2,636

7-12
1,726

13-24
1,865

25-49
1,238

50-99
1, 099

100-249
918
1000 or
250-499 500-999 more
277 161 110

Total
10,020
Residential Contractors
Uirect Contract
Government
Franchise
Total Residential
Cont ractors
1,452
99
1,524
824
149
930
981
389
1,177
687
229
782
461
280
624
324
320
48S
74
139
176
74
90
118
29
40
65
4,906
1 ,738
5, 8«3
Commercial Contractors
Direct Contract
Government
Franchise
Total Commercial
Customers*
2,381
27
2,463**
1,585
110
1,671
1,666
183
1,806
1 ,150
73
1,207
1,005
119
1,072
815
128
90S
217
46
270**
154
46
164
81
9
97**
9,055
741
9,651
  *The number of contractors who contract directly and have government franchises add to more than the total because
   some contractors operate under both direct contracting and government franchising systems.
 **The number of contractors who contract directly and have government franchises do r.ot add to the total or more
   than the total due to "No answers1'.
                                      6.8

-------
                                    TABLE 6.8
                  PERCENT DISTRIBUTION OF PRIVATE CONTRACTORS WHO CONTRACT
                     DIRECT ANO HAVE GOVERNMENT FRANCHISES BY TONNAGE
 Type of Collection                        Number of Tons Collected Per Day
                                                                  1000 or
                  1-6  7-12   13-24   25-49  50-99  100-249  250-499  500-999  more:

 Distribution of Total
 Contractors        26.3%  17.2%  18.6%   12.3%  11.0%   9.2%     2.8%    1.6%   1.1%

 Residential Contractors
Direct Contract
Government

Total Residential
Customers
29.6

5.7

25.9
16

8

15
.8

.6

.8
20

22

20
.0

.4

.0
14.0

13.2

13.3
9

16

10
.4

.1

.6
6.

18.

8.
6

4

3
1.5

8.0

3.0
1

5

2
.5

.2

.0
0

2

1
.6

.3

.1
100

10')

100
Commercial Contractors
Direct Contract
Government
Franchise
Total Commercial
Customers
26.3

3.6

25.5
17

14

17
.5

.8

.3
18

24

18
.4

.7

.7
12.7

9.9

12.5
11

16

11
.1

.1

.1
9.

17.

9.
0

3

4
2.4

6.2

2.8
1

6

1
.7

.2

.7
0.

1

1
.9

.2

.0
100

100

100
        The share of residential customers serviced under a franchise is
highest among contractors collecting over 100 tons per day.  These con-
tractors  comprise only 15 percent of the total contractors,  but collect
three-fourths of the total residential customers serviced under  a govern-
ment franchise.  Similarly, for commercial customers,  contractors  col-
lecting more than 100 tons per day collected 87  percent of the commercial
customers serviced under government franchises (Table  6. 10).
                                     6.9

-------
                                                      TABLE -j.9

                               NATIONAL ESTIMATE OF CUSTOMERS SERVICED BY THE PRIVATE
                        SECTOR UNOER DIRECT CONTRACT ANO C JVERriMENT FRANCHISE 3Y TONNAGE
Type of Collection                                   Number of Tons Collected Per Day
                                                                                                              I 1003 or
                      1-6      7-12         13-24       25-49       50-99     100-249     250-49$     500-999     mor-e     Total


Total Contractors     2,636    1,726        1,865        1,238        1,099       918        277         161        HO     10,027

Total Customers*   169,175  968.062    2,581,993    2,806,308    3,810,289 6,741,707  3,794,637   3.887,672  2,604,84227,351,013

Residential Gusto' ^ers
   Dvrect Contract   79,871  667,210    1,437,529    1,871,749    2,230,482 3,127,300    795,762   1.232,226  1,002,409 12,432,149
   Government
   Franchise         17,532  177,360      903,724      727,902    1,309,965  3,089,996  2,775,761   2,248,638  1,043,323 12,284,609
   Total Residential
   Customers        97,404  844,570    2,341,253    2,599,651    3,540,447 6,217,296  3,571,52.3   3,480,864  I, 045, 732 24,716,758

Commercial Customers

   Direct Contract   65,673  101,494      200,998      173,137      218,905    334,334    137,316     276,622    479,610  1,990,083
   Government
   Franchise           --      5,138       14,272       10,561        5,994    102,189     41,675      99,335      6,280    285,445
   Total Commercial
   Customers*       65,673  106,632      215,270      183,698      224,903   436,523    178,991     '375,957    485,890  2,275,528


*  Total Customers include industrial customers.
                                                         TABLE 6.10

                               PERCENT DISTRIBUTION OF CUSTOMERS SERVICED BY THE PRIVATE
                          SECTOR UNDER DIRECT CONTRACT AND GOVERNMENT FRANCHISE BY TONNAGE
Type of Collection
1-6
Distribution of Total
Contractors 26. 3%
Share of Total
Customers* 0.6
Residential Customers
Direct Contract 0.6
Government
Franchise 0. 1
Total Residential
Contractors 0. 4
Commercial Customers
Direct Contract 3.3
Government
Franchise
Total Commercial
Customers 2. 9
7-12 13-24
17.2% 18;

3.5 9.

5.4 11.

1.4 7.

3.4 9.

5.1 10.

1.8 5.

4.7 9.
6%

4

6

4

5

1

0

5
Nu
mber of Tons Collected
25-49
12.

10,

15.

5.

10.

8.

3.

8.
3%

3

1

9

5

7

7

1
50-99
1 1

13

17

10

14

11

2

9
. 0%

.9

.9

. 7

.3

.0

.1

.9
100-249
9. 2%

24.6

25. 1

25.2

25.2

16.8

35.8

19.2
Per Day
250-499
2.8%

13.9

6.4

22.6

14.4

6J?

14.6

7.9
1000 or
500-99') more
1.

14.

9.

18.

14.

13,

34.

16.
6% 1.1%

2 9.5

9 8.1

3 8.5

1 8.3

.9 24.1

.8 2.2

5 21.4
Total
100%

100

100

100

100

100

100

100
      * Total Customers include industrial customers.
                                                             6.10

-------
        Both residential and commercial contractors collecting 100 tons
or more  collect a high percent of the customers serviced under govern-
ment franchises (compared to their share of total customers) except for
commercial contractors collecting 1000 tons or more.  These contractors
collect 21 percent of the total commercial customers but only 2  percent
of the commercial customers serviced under government franchise
(Table 6. 11).  This corresponds with the findings in Table 6. 11  which
show that among commercial contractors collecting 1000 tons  or more,
customers serviced under  government franchise comprise only  1 percent
of their total customers.
        For residential contractors, those collecting 250-499 customers
per day service a significantly higher percent of their total customers
under a government franchise arrangement than did other contractors.
Among commercial contractors, those  collecting 100-999 tons per day
have the highest percent of customers serviced under government fran-
chise (over 20%). Of all contractor size groups, only those  contractors
who collect between 250-999 tons per day service more  than  half of their
total customers under franchise arrangements (Table 6.9).
                                 TABLE 6.11
                PERCENT DISTRIBUTION OF CUSTOMERS SERVICED BY THE PRIVATE
             SECTOR UNUtK UlKECT CONTRACT ANU GOVERNMENT FRANCHISE BY TONNAGE
Type of Collection

1-6
Residential Customers
Direct Contract 82%
Government
Franchise 18
Total Residential
Customers 100%
Commercial Customers
Direct Contract 100%
Government
Franchise
Number of Tons Collected Per D?.y

7-12

79%

21

100%

95%

5

13-2T4 25-49

61% 72%

39 28

100% 100%,

93% 94%

7 6

50-99

63%

37

100%

97%

3

100-249

50%

50

1007o

77%

23

250-499

22%

78

100%

77%

23
1000 or
500-999 more Total

35% 49% 50%

65 51 50

100% 100% 100;;

74% 99% 87%

Zt 1 13
 Total Commercial
 Customers     100%   100%    100%   1007o    100%     100%   100%    100%    100%   100%
                                 6.11

-------
CONTRACTING/FRANCHISING AND MIX OF COLLECTION
        The number  of residential contractors collecting under government
franchises is lowest among the 522 contractors collecting 1-19 percent resi-
dential refuse.   Among these  contractors 90,  or 17 percent, are involved
in government franchising agreements,  while among the other residential
contractors,  approximately 30 percent have government franchises (Table 6. 12).
Contractors  with collection mixes  of 60-99 percent residential comprise the
largest share of total residential contractors  (55. 1%) and the  largest share
of residential contractors with government franchises (59. 7%).  For all
other collection mix categories, the share of  contractors with government
franchises was  the same or less than the contractor's share of total
contractors  (Table 6. 13).
                                     TABLE 6. 12
                    NATIONAL ESTIMATE OF PRIVATE CONTRACTORS WHO CONTRACT
                  DIRECT AND HAVE GOVERNMENT FRANCHISES BY MIX OF COLLECTION
Type of Collection

Total Contractors
Residential Contractors
Direct Contract
Government Franchise
Total Residential
Contractors-"'-*
Commercial Contractors
Direct Contract
Government Franchise
Total Commercial
Contractors'-*
100% 80-99%
375 1,835
299 1,437
109 619
375 1,835
1,702
256
1,835
60-79%
1,402
1,217
419
1, 402
1,304
192
1,402
% Residcntl-'l Collection
40-50% 20-39%
1,081 661
917 579
320 179
1, OMl bfal
1,023 652
91 ti4
1,081 661
1-19% 100"',- Totil
522 4, 143 10, (J27
412 -- J, ',"-'«>
90 - - 1 , 7 -. »
522 >* '' -- b, o« J
516 3,866 9,055
27 !10 741
522 4, 143**' 9, b51
 * Commercial and Industrial
** The number of contractors who contract directly and ha\ e government franchises add to rrore than the total because
  some contractors operate under both direct contracting and government f; cine his c system^.
#* The number of contractors who contract direct and have government franchises do not a<"k' to tho total or more tha-i
  the total due to "No answers".
                                     6. 12

-------
       Among commercial contractors, the highest incidence of government
franchise also occurs with those collecting 60-99 percent residential refuse.
Of the 3, 237 contractors in this category of collection mix, 448 or 14 percent
have  government franchises.  The percent of commercial contractors with
government franchises decreases as the collection mix  becomes more heav-
ily commercial and industrial.  Only 110 of the 4, 143 (3%) contractors who
collect 100 percent commercial and industrial  refuse service commercial
customers  under a government franchise.
        The concentration of commercial franchises among contractors who
are heavily residential (60-99%) indicates that  these contractors service
commercial customers under a franchise because the franchise covers
combined residential and commercial collection.  Thus, contractors with
a heavy residential mix may tend to acquire some commercial customers
because of the franchise.
                                   TABLE 6 13
                  PERCENT DISTRIBUTION OF PRIVATE CONTRACTORS WHO CONTRACT
                  DIRECT AND HAVE GOVERNMENT FRANCHISES BY MIX OF COLLECTION
 Type of Collection                             % Residential Collection,
                     100%   80-99%   60-79%    40-50%   20-39%   1-19%   100";

 Distribution of Total
 Contractors             3.7%    18.3%   14.0%     10.8%     6.6%   5.2%   41.3%
 Residential Contractors
Direct Contract
Government
Franchis e
Total Residential
Contractors
Commeicial Contractors
Direct Contract
Government
Franchise
Total Commercial
Contractors
6.1 30.3
6.3 35.6
6.3 31.2
18.8
34.6
19.0
24.
24.
23.
14.
25.
It.
8
1
9
j
9
5
18.7
18.4
18.4
11.3
12.3
11.2
11.
10.
11 .
7.
8,
6.
.8
.3
.3
.2
.6
.9
8.
5,
8.
5,
3.
5.
,4
.2
.9
,7 '-2.7
.7 14.8
,4 43.0
100
100
100
100
100
100
 * Commercial and Industrial
                                    6.13

-------
                                             TABLF 6.1«

                       NATIONAL ESTIMATE OF CUSTOMERS SERVICED BY THE PRIVATE
                      SECTOR UNDER DIRECT CONTRACT AND GOVERNMENT FRANCHISE
                                        BY MIX OF COLLECTION
Type of Collection
100%
Total Contractors 375
Total Customers** 1,233, Z94 7
Residential Customers
Direct Contract 419, 3ZO 4
Government
Franchise 813,974 3
Total Residential
Customers 1,233,294 7
Commercial Customers
Direct Contract
Government
Franchise
Total Commercial
Customers
% Residential Collection
80-99%
1,835
, 708,609
,295,901
, 110, 8Z5
,406,725
218,909
73,931
292,840
60-79%
1,402
6, 880,401
3,294,747
2,921,757
6, 216, 504
585,084
46,528
631,612
40-59%
1.081
6,511,336 3,
2,694,168 1,
3,423,940 1,
6,123,108 3,
222,889
126,738
349,627
20-39%
661
946,073
639,468
947,990
587,458
Z56.721
23,692
280,413
1-19%
522
254,029
74, 151
74, 150
148, 301
83,583
4,567
88, 150
100%* Total
4,143 10,
814,044 27,351,
U,432,
12,284,
21,716,
622,896 1,990,
9,991 285,
632,887 .J.Z75,
027
013
149
609
758
083
445
5Z8
* Commercial and Industrial
** Total Customers include industrial customers.
TABLE 6. IS
PERCENT DISTRIBUTION OF CUSTOMERS SERVICED BY THE PRIVATE
SECTOR UNDER DIRECT CONTRACT AND GOVERNMENT FRANCHISE
BY MIX OF COLLECTION
Type of Collection
100%
Distribution of Total
Contractors 3.7%
Share of Total
Customers** 4.5
Residential Customers
Direct Contract 3.4
Government Franchise 6.6
Total Residential
Customers 5.0
Commercial Customers
Direct Contract
Government Franchise --
Total Commercial
Customers
°,i Residential Collection
80-99%
18.3%
28.2
34.6
25.3
30.0
11.0
25.9
12.9
60-79%
14.0%
25. Z
26.5
23.8
25. Z
29.4
16.3
27.8
40-59%
10.8%
23.8
21.7
27.9
24.8
11.2
44.4
15.4
20-39%
6.6%
14.4
13.2
15.9
14.5
12.9
8.3
12.3
1-19%
5.2%
0.9
0-6
0.5
0.6
4.2
1.6
3.9
100%* TDtal
41.3% 100%
3.0 100
100
100
100
31.3 100
3.5 100
27.8 100








 * Commercial and Industrial
** Tot.il Customers include industrial customers.
                                                  6.14

-------
                                             TABLE S.16

                     PERCENT OF CUSTOMERS SERVICED BY THE PRIVATE SECTOR UNDER
                       DIRECT CONTRACT AND GOVERNMENT FRANCHISE WITHIN MIX OF
                                       COLLECTION CATEGORIES
Type of Collection
100%
Residential Customers
Direct Contract 34%
G< vernment
Franchise 66
Total Residential
Customers 100%
Commercial Customers
Direct Contract
Government
Franchise
Total Commercial
Customers
80-99%
58%
42
100%

75%
25
100%
60-79%
53%
47
100%

93%
7
100%
40-59%
44%
56
100%

64%
36
100%
/o Residential Collection
20-39% 1-19% 100%*
45.7% 50%
54. 3% 50
100% 100%

92% 95% 98%
852
100% 100% 100%
Total
50%
50
100%

87%
13
100%
* Commercial and Industrial
                                              6. 15

-------
 REGIONAL AND CITY SIZE CHARACTERISTICS
         Residential contractors with government franchises are heavily
 concentrated in SMSA's of over one million.  Among the 1, 853 residen-
 tial contractors located in SMSA's  of over one million,  approximately
 half operate under government franchises.  This is a significantly higher
 percent of contractors involved in government franchising  than found in
 any other SMSA size  (Table 6. 17).  The concentration of franchising
 among residential contractors in  SMSA's of over  one million is  consistent
with the finding that these contractors tend to be large  (see Table  4.22),
 and are more likely to have a franchise.
        The proportion of commercial contractors with franchises  was
fairly equal for all SMSA sizes.
                                     TABLE 6.17
                    NATIONAL ESTIMATE OF PRIVATE CONTRACTORS WHO CONTRACT
                     DIRECT AND HAVE GOVERNMENT FRANCHISES BY SMSA SIZE
Type of Collection

Total Contractors
Residential Contractors
Direct Contract
Government Franchise
Total Residential
Contractors*
Commercial Contractors
Direct Contract
Government Franchise
Total Commercial
Contractors'''
over
1,000,000
4,456
1,246
909
1, 853
4,020
329
4, 304
500,000-
1,000,000
1, 311
795
200
877
1,222
128
1,274
SMSA Sue
250,000-
499,999
1,498
1,001
259
1, 135
1,295
91
1, 380
100,000-
249,999
1, 017
589
99
629
924
55
975
50,000-
99 ,999
149
93
10
106*-:-
145
19
154
Non
SM.SA Tola!
1, 596 10. 027
1,187 4,?0'j
Z59 1,736
1,288 5,883
1,458 9,055
119 741
1,563 9,651
 * The number of contractors who contract directly and have government franchises add to more: than the total becuase
   some contractors operate under both direct contracting and government franchise systems.
 ** The number of contractors who contract directly and have government franchises do not add to the total or more
   than the total due to "No answers".
                                    6.16

-------
                                    TABLE 6.18
                  PERCENT DISTRIBUTION OF PRIVATE CONTRACTORS WHO CONTRACT
                     DIRECT AND HAVE GOVERNMENT FRANCHISES BY SMSA SIZE
Type of Collection
over
1,000,000
SMSA Sizo
500,000-
1,000,000
250,000-
499,999
100,000-
249,999
50,000-
99,999
Non
SMSA

Total
 Distribution of Total
 Contractors             44.5%
 Residential Contractors
   Direct Contract        25.4
   Government Franchise    52.3
   Total Residential
   Contractors           31.5
 Commercial Contractors
13.1%

16.2
11.5

14.9
14.9%
,!0.4
14.9

19.3
         10.1%
12.0
 5.7

10.7
                           1.5%
1.9
0.6
1.8
                                  1 5 . 9 ,1
24.2
14.9

21.9
100
100
                                          100
Direct Contract 44.4
Government Franchise 44.4
Total Commercial
Contractors 44.6
13.5
17.3

13.2
14.3 10.2 1.6
12.3 7.4 2.5

14.3 10.1 1.6
16.1
16.0

16.2
100
100

100
        Fifty-seven percent of the total residential customers are located in
the largest SMSA's, while  64 percent of those who are serviced under govern-
ment franchise are located in these SMSA's.  SMSA's of 50, 000 to 99, 999,
however, contain only 2 percent of the total commercial customers,  but 10
percent of the commercial customers serviced under a franchise (Table 6.20).
This  disproportionately large share of commercial customers collected
under franchises in the  smallest SMSA's tends  to indicate that,  in the muni-
cipalities of this size, franchises include both residential and commercial
collection.
        This conclusion  is  supported by examining the percent of total cus-
tomers  serviced under direct contract or government franchise within SMSA
sizes.   Here we find that 68 percent of the residential customers and 70
percent of the commercial customers in SMSA's of 50, 000-99, 999 are ser-
viced under franchises.  This is a higher share than exists in any other SMSA
size  (Table  6.21).  While a relatively small percent of contractors in these
cities have franchises,  those that do  serve both the residential and commer-
cial customers  in an entire city.
                                    6. 17

-------
                                                 TABLE 6.19


                          NATIONAL ESTIMATE OF CUSTOMERS SERVICES BY THE PRIVATE
                        SECTOR UNDER DIRECT CONTRACT AND GOVERNMENT FRANCHISE BY
                                                 SMSA SIZE
Tvpe of Collection
over
1,000,000
Total Contractors 4, 456
Total Customers* 15,848,467
Residential Customers
Direct Contract 6. 179,493
Government
Franchise 7,864,809
Total Residential
Customers 14,044,302
Commercial Customers
Direct Contract 1,357,724
Government
Franchise 192.104
Total Commercial
Customers 1,549,828
SMSA_SJ7c
500,000- 250,000- 100,000- 50,000- N'on-
1,000,000 499,999 249,999 99,999 S.VSA Tot
-------
                                  TABLE 6.21
                 PERCENT OF CUSTOMERS SERVICED BY THE PRIVATE SECTOR UNDER
                 DIRECT CONTRACT AND GOVERNMENT FRANCHISE WITHIN SMSA SIZES
Type of Collection

Residential Customers
Direct Contract
Government Franchise
Total Residential
Customers
Commercial Customers
Direct Contract
Government Franchise
Total Commercial
Customers
SMSA Si7.e
over 500,000-
1,000,000 1,000,000
44%
56
100%
88%
1Z
100%
61%
39
100%
94%
6
100%
250,000-
499,999
52%
ttt
100%
88%
1?.
100%
100,000-
249,999
65%
35
100%
84%
16
100%
50,000-
99,999
32%
68
100%
30%
70
100%
Non-
S\:SA
6 1 %
39
100%
91%
9
100%
Total
507.
50
100%
87%
13
100%
        The North Atlantic, Mid-Atlantic, South Central, and West have the
highest percent of residential contractors with government franchises.  The
Mid-Atlantic has the most with 375 contractors out of 559, or 67 percent,
collecting under a government franchise.  The West has the second highest
percent of residential contractors involved  in government franchising with
348 out of a total of 788 contractors (44%),  followed by the North Atlantic
(38%), and South Central (37%)  (Table 6.22).  The  same regions also have a
larger share of contractors with  government franchises than would be ex-
pected on the basis of their share of total contractors (Table 6. 23).
       The Mid-Atlantic has  the  highest percent of contractors serving
commercial customers under government franchises--157 out of 579 total
contractors (27%)--and account for 21% of the total contractors with govern-
ment franchises.  While  only 17 percent of  the contractors in the West serve
commercial customers under franchises, these contractors represent 35
percent of all contractors with commercial franchises (Table 6.23).
                                   6. 19

-------
                                                    TABLE 6.22

                             NATIONAL ESTIMATE OF PRIVATE CONTRACTORS WHO CONTRACT
                                DIRECT AND HAVE GOVERNMENT FRANCHISES BY REGION
Tvpe of Collection
North Mid-
Northeast Atlantic Atlantic
Total Contractors 529 2,024 644
Residential Contractors
Direct Contract 270 648 235
Cove rnment
Franchise 68 318 375
Total Resident
Contractors* 312 830 559
Commercial Contractors
Direct Contract 453 1,874 570
Government
Franchise 64 31 163
Total Commercial
Contractors* 483 1,978** 579
Region
South Mid- North South
Atlantic West Central Central Mountain '.\ • tl 7V..il
373 2,401 1,603 507 391 1.5» 1'l.r,/?
285 1,482 1,060 167 2')6 5V; •'•,'!'>'.
57 349 129 78 17 348 1.7J8
288 1,547 1,130 212 218 78H S,h",i
353 2,182 1,512 462 380 1,259 9,055
34 76 25 70 8 270 7-U
367 2,268** 1,563** 502 396** 1,525*-" 9,651
 * The nv\mber of contractors who contract directly and have government franchisor add to mor^ th.ir tho tot-il
   because sonic contractors operate under both direct contracting and government franchise systems.
**  The number of contractors who contract directly and have government franchises do not add to the total or
   more than the total due to "No answers".
                                                    TABLE 6.23

                           PERCENT DISTRIBUTION OF PRIVATE CONTRACTORS WHO CONTRACT
                                DIRECT AND HAVE GOVERNMENT FRANCHISES BY REGION
Type of Collection
Northeast
Distribution of Total
Contractors
Residential Contiactors
Direct Contract
Government Franchise
Total Residential
Gont racto rs
Commercial Contractors
Direct Contract
Government Franchise
Total Commercial
Contractors
5
5
3
5
5
8
5
.3%
.5
.9
.3
.0
.7
.0
North
Atlantic
20
13
18
14
20
4
20
.2%
.2
.3
.1
.7
.2
.5
Mid-
Atlantic
6
4
21
9
6
22
6
.4%
.8
.6
.5
.3
.2
.0
Region
South Mid-
Atlantic West
3.77.
5.8
3.3
4.9
3.9
4.6
3.B
23,
30,
20
26,
24
10
23
.9%
.2
.1
.3
.1
.2
.5
North
Central
16
21
7
i9
16
3
16
.0%
.6
.4
.2
.7
.4
.2
South
Central
5.1%
3.4
4.5
3.6
5.1
9.4
5.2
Mountain West Total
3.9% 15.57« 100T-.
4.2 11.4 100
1.0 20.0 100
3.7 13.4 100
4.2 13.9 100
1.1 36.4 100
4.1 16.8 100
                                                       6.20

-------
            The same four regions--North Atlantic, Mid-Atlantic, South Central,
    and West--plus  the Northeast,  contain a larger share of residential customers
    serviced by government franchise than their share of total residential cus-
    tomers  (Table 6.25).  Within these five regions,  the residential customers
    serviced by government franchise account for over half of the total customers,
    and in the South Central they  comprise 84 percent of the total residential
    customers (Table 6. 26).
            The share of commercial customers serviced by government franchise
    are predominantly in the  West (210, 944 of the total 285, 440 or 74 percent)
    with the second  largest share being in the South Central  (15%) (Table 6. 25).
    Commercial customers serviced by government franchise also comprise a
    higher percent of the total customers  within these regions than in other
    regions  -  27 percent in the South Central and 22 percent in the West (Table 6. 26).
                                          TABLE 6.24
                        NATIONAL ESTIMATE OF CUSTOMERS SERVICED BY THE PRIVATE
                        SECTOR UNDER DIRECT CONTRACT AND GOVERNMENT FRANCHISE
                                          BY REGION
 \ pe of Collection                                         Region
Northeast
North
Atlantic
Mid-
Atlantic
South
Atlantic
Mid-
West
North
Central
South
Central
Mourtam W--,t
T..1..1
  Direct Contract     400,534 1,146,473    526,631  1,060,476 4,081,326  1.378,206   177.538  472,309  3,207,792 12,432,]4r»
  Government
  Franchise         934,580 3,099,722  1,172,178   546,306 1,509,532    302,533   932,076   24,B5»  3, 765, >,!>'' \ 2. 284, f,D';
  Total Residential
  Customers      1,335,114 4,246,195  1,698,809  1,606,782 5,590,858  1,680,739 1,109,614  497,167  ',,973,402 24,716,758
Commercial Customers
  Direct Contract     56,806   236,401    69,429    89,677   468,700    130,102   116,268   79,606    743,094  ],990,0d3
  FrTnchlT'        5'13S    2,B5t     6,280    13,416    2,854       571    43,673    --      210,944   2B5.445
  Total Commercial
  Customers        61,944   239.255    75,709   103,093   471.554    130,673   159, °4!   79,606    954,038  2,275,528


* Total Customers include industrial customers.
                                           6.21

-------
                                                TABLE 6. 25

                         PERCENT DISTRIBUTION OF CUSTOMERS SERVICED BY THE PRIVATE
                          SECTOR UNDER DIRECT CONTRACT AND GOVERNMENT FRANCHISE
                                                BY REGION
Type of Collection

Northeast
Distribution of Total
Contractors
Share of Total
Customers*
Residential Customers
Direct Contract
Government
Franchise
Total Residential
Custonyrs
Commercial Customers
Direct Contract
Government

Total Commercial
Customers

5.

5.

3.

7.

5.

2.

1.

2.

3%

2

2

6

4

9

8

7
North
Atlantic

20.

16.

9.

25.

17

11.

1.

10.

2%

7

2

2

2

8

0

5
Mid-
Atlantic

6.

6.

4.

9.

6.

3.

2.

3.

4%

5

2

5

9

5

2

3
Region
South Mid-
Atlantic West

3.

6.

8.

4.

6.

4.

4.

4.

7%

3

5

4

5

5

7

5

23.

22.

32.

12.

22.

23.

1.

20.

9%

5

8

3

6

6

0

7
North
Central

16

6

11

2

6

6

0

5

.0%

.6

. 1

.5

.8

e

.2

.8
South
Central Mountain W"st

5.

4.

1.

7.

4.

5.

15.

7.

1% 3.9%

7 2.1

4 3.8

6 0.2

5 2.0

a 4.0

3

0 3.5

15.5%

29.4

25.8

30.7

28.2

37.3

73.9

41.9
Total

100%

100

100

100

100

100

100

100
* Total Customers include industrial customers.
                                                 TABLE 6.26

                           PERCENT DISTRIBUTION OF CUSTOMERS SERVICED BY THE PRIVATE
                           SECTOR UNDER DIRECT CONTRACT AND GOVERNMENT FRANCHISE
                                               WITHIN REGIONS
Type of Collection

North
Northeast Atlantic
Residential Customers
Direct Contract 30%
Government Franchise 70
Total Residential
Customers 100%
Commercial Customers
Direct Contract 92%
Government Franchise 8
Total Commercial
Customers 100%
27%
73
100%
99%
1
100%
Mid-
Atlantic
31%
69
100%
92'%
8
100%
Region
South Mid-
Atlantic West
66%
34
100%
87%
13
100f?0
73%
27
100%
99%
1
100%
North
Central
82%
18
100%
100%
0
100%
South
Central
16%
84
100%
73%
27
100%
Mountain
95%
5
100%
100%
100%
West
46%
54
100%
78%
22
100%
Total
50%
50
100%
87%
13
100%
                                                  6.22

-------
                         BUSINESS STRUCTURE

      This  chapter describes the business  structure of the private sector
D£ solid waste management.   The management organization of the industry
is discussed in terms of the  relationship between business form (proprietor-
ship,  partnership,  or corporation) and descriptors of contractor size.  The
ige of the organization  and the extent of involvement in other solid waste
related businesses are  also analyzed by contractor size.
      This  chapter is structured into the following subsections:
      •     Chapter Summary
      •     Business Structure by Size of Operation
      •     Age of Operation
      •     Other Solid Waste Related Businesses
                                  7. 1

-------
                          CHAPTER SUMMARY
      Approximately one-half of the companies in the solid waste industry are
operated as proprietorships,  one-third as corporations, and ten percent as
partnerships.  Small contractors operate predominantly as proprietorships, and
large contractors operate as corporations.
      Nearly one-half of the companies in the private sector have been in their
present organizational form since 1960, indicating an apparent ease of entry into
the field.  Data from previous chapters indicate that entry into the solid waste
industry is most often through the development of an initial set of commercial
customers rather than residential customers. This conclusion is supported by
the fact that 44 percent of the contractors with 1-3 trucks serve commercial and
industrial customers exclusively.
                                   7.2

-------
BUSINESS STRUCTURE BY SIZE OF OPERATION
      The type of ownership under which the private sector operates is
related to the number of trucks, the number of employees,  and daily tonnage.
The following table indicates that companies organized as partnerships and
corporations have higher mean numbers of trucks,  employees, and tons per
day than companies operated as proprietorships.

                              TABLE 7. 1
      MEAN NUMBER OF TRUCKS, EMPLOYEES, AND TONS PER
                     DAY BY TYPE OF OWNERSHIP
Type of Number of
Ownership Contractors
Total
Proprietorship
Partnership
Corporation
10, 027
5,631
1,045
3,351
Mean #
Trucks
6.2
2.8
8.3
11.3
Mean #
Employees
10.2
3.7
14. 1
21. 1
Mean #
Tons/Day
68.4
20o 1
83.7
150.7
      The relationship of contractor size to type of ownership shows that
smaller companies operate as proprietorships, and larger companies
operate as corporations,,  Specifically,  79. 6 percent of the companies
operated as proprietorships are 1-3 truck  contractors (Table 7.3).  Pro-
prietorships decrease in percent of companies from 84 percent among one-
truck contractors to 7 percent among contractors with 50 or  more trucks.
                                  7. 3

-------
                        TABLE 7.2

 NATIONAL ESTIMATE OF COMPANIES OWNED AS PROPRIETORSHIPS.
   PARTNERSHIPS, OR CORPORATIONS BY SIZE OF CONTRACTOR
^ypc of Ownership

Totel Contractors
Proprietorbhip
Pa rtnc rship
Corporation
Size of Contractor
1
truck
2,608
2, 185
195
228
2-3
trucks
3, 193
2,297
293
603
4-5
trucks
1, 421
732
166
523
6-9
trucks
1,261
315
186
760
10-19
trucks
982
73
108
801
20 49 50 or more
tru :ks trucks
4)5 157
:Z 11
-8 29
3 5 117
Total
10, 027
5, o31
1, 045
3, 351
                         TABLE 7.3

PERCENT OF COMPANIES OWNED AS PROPRIETORSHIPS, PARTNERSHIPS,
            OR CORPORATIONS BY CONTRACTOR SIZE
Tyoc of Ownership


Share of Total
Cor.trac tors
Proprietorship
pa rtr.e Y ship
Corporation
Total Contractors
Proprietorship
pa rtnc r^hip
Corooration
Size of Contractor
1
truck

26.0%
38.8
18.7
6.8
100%
83.8
7. 5
8.7
2-3
trucks

31.8%
40.8
28. 0
18.0
100%
71.9
9.2
IS. 9
4-5
trucks

14. 1%
13.0
15.9
15.6
100%
51.5
11. 7
36.8
6-9
trucks

12.6%
5.6
17.8
22. 7
100%
>5.0
14. 8
60. 3
10-19
trucks

9.8%
1. 3
10. 3
23.9
100%
7.4
11. 0
81.6
20-49
trucks

4. 0%
0.4
6.5
9.4
100%
5.4
16. 8
77.8
50 or more
trucks

1.6%
0.2
2.8
3.5
100%
7.0
18.5
74.5

Total

100%
100
100
100
100%
56.2
10.4
33.4
                          7. 4

-------
      Solid waste contractors who are proprietorships collect an average of
20 tons per day, while companies organized as corporations collect an
average of 151 tons per day (Table  7. 1).  This point is further illustrated in
Table  7. 5, where 65 percent of the proprietorships collect less  than twelve
tons per day, while only 10 percent of the  corporations collect twelve tons
or less.  Conversely,  only 10 percent of those contractors who collect 1000
or more tons per day are proprietorships.
                                  TABLE 7.4
                  NATIONAL ESTIMATE OF COMPANIES OWNED AS PROPRIETORSHIPS,
                     PARTNERSHIPS, OR CORPORATIONS BY DAILY TONNAGE
Type of Ownership

Total Contractors
Proprietorship
Partnership
Corporation

Number of Tons Collected Per Day
1-6 7-12
2,636 1,726
2,383 1,273
117 245
137 208

13-34 25-49
1,865 1,238
1,143 467
186 195
536 576
TABLE 7.5
50-99 100-249 250-499 500-999
1,099 918 277 16.1
248 96 -- 11
117 108 39 29
734 714 238 121

1000
o r mo re - ota I
110 10.027
1 J 5 , <• 1 1
9 1,145
90 1.351

PERCENT OF COMPANIES OWNED AS PROPRIETORSHIPS,
PARTNERSHIPS, OR CORPORATIONS BY DAILY TONNAGE
Type of Ownership

Share of Total
Contractors
Proprietorship
Partnership
Corporation
Total Contractors
Proprietorship
Partnership
Corporation
1-6 7-12
26.3% 17.2%
42.3 22.6
11.2 23.4
4.1 6.2
100% 100%
90.4 73.8
4.4 14.2
5.2 12.1
Number
13-24 25-49
18.6% 12.3%
20.3 8.3
17.8 18.7
16.0 17.2
100% 1 )0%
61.3 37.7
10.0 15.3
28.7 4C.5
of Tons Collected Per Day
50-99 100-249 250-499 500-999 o
11.0% 9.2% 2.8% 1,6';;
4.4 1.7 -- 0.2
11.2 )0.3 3.7 2.8
21.9 21.3 7.1 3.6
100% 100% 100% 100%
22.6 10.5 -- 6.8
10.6 11.8 14.1 18.0
66.8 77.8 85.9 75.2
1000
r more Total
1.1% 100"1.,
0.2 10')
0.9 100
2.7 100
100% ItW'
10.0 56.2
8.2 10.4
81.8 33.4
                                   7.5

-------
AGE OF OPERATION
      The mean number of years all contractors have opt rated their busi-
ness in its present form is 13. 9 years, with one-third of the businesses
started since 1965,  and over half started since  I960,   The following table
shows the number and percent of contractors who startec their  company
in its present form for each time period.
                              TABLE 7.6
                    YEAR OF COMPANY ORIGIN IN PRESENT FORM
Year Started
1970-71
1965-69
1960-64
1950-59
1940-49
Before 1940
Don't know
Total
594
2,729
2,066
2,574
1, 171
831
61
Percent
5.
27.
20.
25.
11.
8.
0.
9%
2
6
7
7
3
6
Cumulative
Percent
5.9%
33. 1
53.7
79. 4
91. 1
99.4
100.0
      As would be expected, the contractors operating the most trucks, and
those collecting the most tonnage have been in business i:i their present
form the longest (Tables  7. 7 and 7. 8).
                                 TABLE 7.7
                     PERCENT DISTRIBUTION OF YEAR BUSINESS STARTED
                       IN ITS PRESENT FORM BY CONTRACTOR SIZE
Year Started

1970-71
1905-69
19tO-64
1950-59
1940-49
Before 1940
Mean Years in
Present Form
Size of Contractor
1
truck
9
21
19
27
11
9
14
.3%
.6
.0
.5
.6
.8
.6
2-3
trucks
4
31
17
25
12
18
13
.1%
.6
.7
.9
.6
.0
.7
4-5
trucks
5
33
21 .
18,
12
8
13
.6%
.0
,8
.3
.7
.4
.6
6-9
trucks
7
23
22
26
11
8
14
.1%
.6
.8
.0
.0
.0
.5
JO-19
trucks
3
25
31
26
5
6
12
.0%
.2
.3
.2
.1
.0
.8
20-49
trucks
4
7
24
39
12
9
16
.9%
.2
.4
.0
.2
.7
.6
50 o * more
tri-cks Total

12
12
31
12
31
23
0%
.6
.5
.3
.5
.3
.9
5
27
20
25
11
8
13
.9%
.2
.6
.7
.7
.3
.9
                                    7.6

-------
                                     TABLE 7.8
                      PERCENT DISTRIBUTION OF YEAR BUSINESS STARTED IN ITS
                             PRESENT FORM BY DAILY TONNAGE
Year Started
Number of Tons Collected Per Day
100-

1970-71
1965-69
1960-64
1950-59
1940-49
Before 1940
Mean Years in
Present Form
1-
5,
23
18,
31 ,
12
8

14,
6
,5%
.9
.4
.4
.2
.3

.5
7-
7.
22.
17.
26.
13.
12.

15.
• 12
2%
7
9
2
7
0

5
13-24
6.
30,
19,
18,
14.
8,

14.
0%
.8
.1
,2
,8
.2

,3
25-49
5.7%
38.2
19.5
21.9
8.1
6.5

11.5
50-99
7.3%
30.1
18.2
27.2
9.1
7.3

12.6
249
3.
21 .
34,
22.
9.
b,

14.
3%
.8
,8
.9
,8
.6

7
250-
499
0 %
10.7
32.1
32.2
10.7
10.8

17.0
500-
999
0
12.
37.
31 .
6.
12.

15.
1,000
or more
%
5
5
3
3
6

3
9.
0
1H.
18.
18.
36.

26.
, IT"

.2
,2
,2
.4

,4
5 . 9 %
27.2
20.6
25 7
11.6
8.2

13.9
      Contractors in the West have been in their present form significantly
longer (180 3  years) than contractors in other regions.  The greater length
of time contractors in the West have been in business  is due to the fact
that these contractors are,  on the average,  larger  contractors (Table  7.9).
                                    TABLE 7.9
                     PERCENT DISTRIBUTION OF YEAR BUSINESS STARTED IN ITS
                               PRESENT FORM BY REGION
Year Started

1970-71
1965-69
1960-64
1950-59
1940-49
Before 1940
Mean Years in
Present Form
Northeast
4.
26.
28.
17.
12.
9.
14.
2%
7
2
0
7
8
7
North
Atlantic
5
23
20
25
14
10
15
.7%
.1
.9
.6
.1
.4
.3
Mid-
Atlantic
9.
41.
10
21
12,
3,
11.
.1%
.8
.9
.8
.7
,6
,1
Rej
South
Atlantic
Q
33
24
21
o
3
10
.1%
.4
.2
.2
.1
.0
2
;ion
Mid-
West
2.
32.
20
24.
10.
8
13.
.7%
.7
.0
.5
.5
.7
,7
North
C ent ral
8.
29.
21 .
25.
11.
1.
11.
1%
8
0
8
3
6
6
South
Central
8.
32.
25.
24.
6.
1 .
9.
6%
7
9
1
9
7
5
Mountain
2.
21 .
21.
36.
12.
6.
13.
1%
3
3
2
8
4
7
West Total
7
14
19
30
1 1
15
18,
.5% s.rr.
.0 27.2
.4 2C.6
.8 25.7
.9 Jl .7
.5 o.3
.3 13.9
                                     7.7

-------
OTHER SOLID WASTE RELATED BUSINESSES

      If several companies are  located at the same address and if the records
for all companies are combined, these companies  are considered to be one
establishment.  On the other hand,  if companies at the same address are
run separately and  separate financial books are maintained, each company
is defined as an establishment.  A total of 8, 795 establishments own the 10, 027
private contracting companies involved in  collection,  with each establishment
operating a mean number of  1. 14 collection and/or disposal organizations.
                                 TABLE 7.10
                     NUMBER OF COMPANIES PER ESTABLISHMENT
                                                   Mean Number Per
                                        Total         Establishment

          Total Establishments              8.795
          Number of Collection and/or
          Disposal Companies at "this"
location
Number of Locations Operate
From
Total Number of Collection and/or
Disposal Companies
9,704

9,803

10,027
1.11

1. 12

1. 14
      As the following table indicates, 2. 9 percent of the total establishments
are subsidiaries of a parent firm and 3.  1 percent of the establishments
operate subsidiaries.

                                  TABLE 7.11
                NUMBER OF ESTABLISHMENTS WHICH ARE SUBSIDIARIES OF
                       ANOTHER FIRM OR OPERATE SUBSIDIARIES


Total
Establishments that are
Subsidiaries
Establishments Which Operate
Subsidiaries
Number of
Establishments
8,795

293

314
Percent of Total
Establishments
100%

2.9%

3.1%
                                     7.8

-------
      Over three-fourths of the total establishments are engaged in no
other business except collection,  but of those which are involved in other
businesses,  salvage operations and disposal sites were the most common.

                                   TABL&7.12
                  NUMBER OF ESTABLISHMENTS ENCAGED IN RELATED BUSINESSES
Type of Business
Total
None /No Other Business
Salvage Opeiations
Disposal Sites
Equipment Distribution
Land Development or
Reclamation Company
Other Business
Number of
Establishments
8,795
6,883
1.003
599
37V
282
221
Percent of Total
Establishments
100%
78. 3
11.4
6. 8
4. 3
3.2
2.5
      The operation of related businesses is much more prevalent among
establishments operating large collection companies.  As Table 7. 13 indi-
cates, 89 percent of the one-truck companies have no other related businesses,
while only 15 percent of companies with 50 or more  trucks have no other
related businesses.  The percent of establishments engaged in other business
 ncreases as company size increases.
                                     TABLE 7.13
                       NUMBER AND PERCENT OF ESTABLISHMENTS ENCAGED IN
                         RELATED BUSINESSES BY SIZE OF ESTABLISHMENT
Type of Business


Total Establishments
None/No Other Business
Salvage Operations
Disposal Sites
Equipment Distribution
I^and Development or Reclamation
Other Businesses
Total Establ.shments
None/No Other business
Salvage Operations
Disposal Sites
Equipment Distribution
Land Development or Reclamation
Other Business
Size of Contractor
1
truck
2,287
2, 037
230
9
--
Company 9
25
100%
89. 1
10. 1
0.4
--
Company 0. 4
1. 1
2-3
trucks
2,797
2,402
264
55
63
35
34
10(,%
85.9
9.->
2.0
2. 3
1. 3
1. 2
4-5
trucks
1,240
964
136
91
45
18
34
100%
77.7
11.0
7. 3
3.6
1.5
2.7
6-9
trucks
1, 108
771
153
145
72
35
34
100%
69.6
13.8
13. 1
6.5
3.2
3. 1
10-19
trucks
862
496
93
164
117
62
51
100%
57.5
10. 8
19.0
13.6
7.2
5.9
20-49
trucks
352
200
42
81
45
45
34
100%
56. 8
11.9
23.0
12. 8
12.8
9.7
50 or more
trucks
141
21
85
55
36
79
8
100%
14.9
60. 3
39.0
25.5
56.0
5. 7
Total

8, 795
6,883
1, 003
599
377
282
221
1 00%
78. 3
11.4
6.8
4. 3
3.2
2.5
                                   7.9
  ua815R
                                               OUS GOVERNMENT PRINTING OFFICE 1974 S46-31S/234 1-3

-------

-------