-------
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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
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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
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THE PRIVATE SECTOR IN SOLID WASTE MANAGEMENT
A Profile of its Resources and Contribution
to Collection and Disposal
Volume 1, Executive Summary
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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
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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
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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
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1.3
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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
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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
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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
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1.7
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
-------
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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
-------
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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 _ _
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_ -.7f -.--- :
51 : Vi
(/) n=r:z^=
^ y I7=mz:3
Ik. =Z~~Ii^
r* C
in ^S
rx m .
Ȥ=
ro ii
ro >, "
i± a
r cri vi
in flJ ^ r» v E
J£ ^ U O =
3 6 = ~2[1
!. O *^L-
1- ^ U
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tv -* r- * in
*< ^ *~ f-
O i- O c
h 1- H * o .
-«-
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1 1 1 1
o in o m
o r^ in (vi
(U
1^
i_ o ^r
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o .b 01
ui u
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l/l I
a- u >~
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(VI
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z
JT
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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
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