Group Title: structure and characteristics of the Florida exempt perishables trucking industry
Title: structure and characteristics of the Florida exempt perishables trucking industry
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Title: structure and characteristics of the Florida exempt perishables trucking industry
Series Title: structure and characteristics of the Florida exempt perishables trucking industry
Physical Description: Book
Creator: Beilock, Richard
Publisher: University of Florida Agricultural Experiment Station
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Volume ID: VID00001
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Full Text

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Food and Resource Economics Department
Agricultural Experiment Stations
hutituts of Food and Agricultural Sciences
Unvrfty of Florida, Gaknesvile 3261

Richard Beilocl

George Fletche

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The results are reported of a survey of over 600 truckers carrying
perishables from Florida during the 1982-1983 crop season. The findings
indicate that owner-operators haul the majority of the state's produce
and that most loads are arranged via brokers. The fleet and private car-
riers, like the owner-operators, were found to specialize in carrying
produce. The average respondent in each group reported that the majority
of time was devoted to hauling exempt goods.

Keywords: transportation, produce



INTRODUCTION ................. .................... ................. 1

THE SURVEY ...................... ..... ....... ... ............. ... 2

RESULTS .................................... ... ..... .... .......... 4

Carrier and Trip Characteristics ..... .................... 4

Carrier Types ................. ............... ... .... ..... 4
Commitment to Exempt Goods Transportation .................. 4
Firm Location .. .................................... .... 6
Destinations .................................... .... ... 7
Shuttling .o..oe.. ......... .................... O.... ...... 7
Load Configuration ...................... .... ....... .... 8
Pickups and Drops ................... ... ..... .... ........... 8
Load Arrangements ... ............................ ............ 8
Backhaul into Florida and Interstate Hauls ....o............ 10
Trucker Comments ............................................ 12

Rate Analysis .............................................. 15

Theoretical Model ............................ ............... 16
Empirical Estimation ............................... ......... 17
Results of Estimation Process ............................ 19

SUMMARY AND CONCLUSIONS ......................................... 24

FOOTNOTES ................... ..................................... 26

APPENDIX I .........C....... ........................... 27

Survey Instrument ........o.................................... 28

APPENDIX 2 eeoee ............... .... e.. ......... .................. 29

Value-of-Service Rationale .........C....o ...c........ ..... ... 30

REFERENCES oe... e...e... ..................... ................ 31


Table Page

1 Selected Carrier Characteristics ........................... 5

2 Selected Perishable Shipment Characteristics ............... 9

3 Backhaul Practices and Intrastate Trucking Activity ........ 11

4 Principal Driver Complaints ................................ 13

5 Expected Parameter Signs and Condition of Rationale ........ 20

6 Truck Rate Estimation Equations o........o............... 21

The Structure and Characteristics of the
Florida Exempt Perishables Trucking Industry


In Florida, as in most areas of the country, exempt perishable

commodities are transported primarily by motor carriers. In fact, over

90 percent of all produce, by weight, shipped from the state is via

truck (USDA, 1980-1982). Despite this dependence, very little is known

regarding the characteristics of the perishable trucking industry. Such

knowledge could be of value to industry participants in developing short

and long range marketing strategies and to policymakers in assessing the

impacts of alternative policies.

In this report the results are presented and analyzed of a study of

truckers carrying Florida produce and ornamentals interstate during the

1982-1983 crop year. The principal objectives of the study are the


1. to determine the relative importance of owner-operators, for-

hire fleets, and agricultural cooperatives in the exempt

perishables trucking system,

2. to determine the manner in which transportation arrangements

are made and whether these arrangements differ between carrier

groups, and

Richard Beilock is an assistant professor of Food and Resource Eco-
nomics, University of Florida. George Fletcher is a transportation
specialist with the Florida Department of Agriculture and Consumer

3. to identify and quantify the major determinants of truck rates.

In the next section a description of the survey procedures employed

to gather data for the study is presented. Next, the results are pre-

sented, beginning with a discussion of carrier and trip characteristics

(to answer objectives 1 and 2), and continuing with the analysis of the

truck rate determinants (objective 3). Finally, the survey results are

summarized and conclusions drawn.


The peninsular configuration of Florida greatly facilitates the

monitoring of interstate truck shipments of exempt commodities. All

shipments by truck from the central and southern part of the state must

pass through a 140 mile wide bottleneck. Possible exit points are

further restricted by extensive areas of marshes, floodplains, and

swamps (such as the Okeefenokee). Taking advantage of these features,

the Florida Department of Agriculture and Consumer Services maintains

checkpoints, known as roadguard stations, to monitor agricultural

products entering and leaving Florida east of the Suwannee River. These

stations provide ideal sites for sampling trucks.

To avoid the above problems, in this study it was decided to opt

for a much shorter survey instrument (see Appendix) to be administered

via a face-to-face interview while the trucker was stopped for the state

agricultural inspection. The time period from six P.M. to midnight was

chosen for the interview session because this time of day is usually

associated with high outbound traffic volumes. To ensure a

representative sampling, an interview was conducted for every truck

carrying produce or ornamentals. The cargo, origin, and destination

information were verified by examining the shipping documents (as they

were being examined by the state agricultural inspector). Moreover to

minimize recall problems, the survey was limited to asking the trucker

about ongoing or recent events, carrier characteristics, the current

haul, and the trip which brought the carrier to Florida.

The busiest roadguard station in the state, on 1-95 at Yulee,

Florida, was selected for the survey. Two day interview periods were

conducted during the crop year at approximately two month intervals. In

all, 685 interviews were completed on the following dates:

number of interviews

November 11 and 12, 1982 147

January 26 and 27, 1983 98

March 28 and 29, 1983 198

June 1 and 2, 1983 215

It should be noted that 35 of the interviews in November were conducted

at the westbound 1-75 roadguard station. Due to the lower traffic

levels on that artery and the increased costs related to conducting

interviews at two sites, all subsequent interviews were carried out on

I-95, In later testing, however, no differences were found between

these surveys and those conducted at the same time at I-95, except for

the destinations and the carriers' base or home state.


Carrier and Trip Characteristics

Carrier Types

The owner-operator emerges as the dominant carrier of Florida

perishables. In each survey month, between 49 and 56 percent of the

drivers identified themselves as owner-operators (Table 1). Roughly

one-quarter are for-hire fleet operations, and just under one-fifth are

private carriers. Only 6 trucks, or one percent of the sample were

identified as belonging to an agricultural cooperative or to other types

of firms.

Commitment to Exempt Goods Transport

Perishables carriers appear to be specialists. Over two-thirds of

their time, on average, was estimated to be devoted to carrying exempt

goods. The remaining time is divided between leasing their services to

regulated carriers, and hauling regulated goods under their own author-

ity (Table 1). The amount of time actually devoted to hauling exempt

commodities is underestimated. This is true because those truckers

reporting that they were always under permanent lease were listed as not

hauling exempt commodities despite the fact that they were carrying

perishables at the time of the interview. Therefore the actual average

percent of time devoted to carrying exempt commodities is probably

between 70 and 75 percent.

Of some surprise was fact that fleet carriers devote about the same

proportion of time to hauling exempt goods as do owner-operators and

Table 1. Selected carrier characteristics

Survey month
November January March June

number of carriers (percentages in parentheses)
Carrier status:
Owner-operator 81 (55) 54 (55) 111 (56) 105 (56)
For-hire fleet 37 (25) 26 (27) 52 (26) 57 (27)
Private fleet 29 (20) 17 (17) 32 (16) 52 (24)
Other 0 (0) 2 (2) 3 (2) 1 (0)

Hauling exempt commodities:
Owner-operators 62 64 70 b7
For-hire fleet 73 63 65 bU
Private fleets 71 68 82 95
All carriers 67 65 70 73

Trip leasing:
Owner-operators 15 14 14 18
For-hire fleets 9 12 13 16
Private fleets 15 7 8 5
All carriers 14 12 13 14

Permanent leasing:
Owner-operators 17 22 11 11
For-hire fleets 0 4 2 5
Private fleets 3 b 0
All carriers iU 15 6

Using own authority:
Owner-operators 6 0 5 4
For-hire fleets 19 21 20 1i
Private fleets 11 19 10 0
All carriers 9 8 11 o

Firm location:
Florida 59 (40) 32 (33) 64 (32) 55 (26)
GA, NC, SC 33 (22) 21 (21) 57 (29) 72 (33)
VA, WV, MD, DE 9 (6) 9 (9) 20 (10) 21 (10)
PA, NJ, NY 19 (13) 23 (23) 27 (14) 32 (15)
New England 3 (2) 4 (4) 10 (5) lu (5)
Lake States2 7 (5) 2 (2) 8 (4) 4 (2)
Canadi 6 (4) 4 (4) 7 (4) d (4)
Other 11 (8) 4 (4) 5 (2) 1U (5)

Percent from Florida:
Owner-operator 51 37 41 32
Other carriers 26 22 20 19
All carriers 40 33 32 26

GA, NC, SC 17 (12) 21 (21) 39 (20) 61 (28)
VA, WV, MD, DE 18 (12) 6 (6) 31 (16) 32 (15)
PA, NJ, NY 43 (29) 49 (50) 75 (38) 62 (38)
New England2 18 (12) 11 (11) 26 (13) 14 (7)
Lake States 10 (7) 0 (0) 3 (1) 3 (1)
Canada 15 (10) 8 (8) 18 (9) 14 (7)
Other 26 (18) 3 (3) b (3) 9 (4)

Percentages in parentheses.
2Ohio, Indiana, Michigan, Wisconsin, Minnesota, Illinois, Missouri, and
3All states west of the Appalachians and excluding the Lake States.

private carriers. In the November, January, March, and June surveys,

the fleet drivers estimated that, on average, 73, 63, 65, and 60 percent

of their time, respectively, was devoted to hauling exempt commodi-

ties. Moreover, in no month did the average percent of time employed

carrying regulated goods under their own authority exceed 21 percent.

Therefore, the for-hire fleets hauling Florida perishables, then, tend

to treat exempt carriage as an integral part of their operations, rather

than as a sideline.

Reliance on leasing by owner-operators does not appear to be as

pervasive as is commonly supposed. Estimates for time devoted to per-

manent leasing was around 20 percent in November and January, and

lowered to 11 percent in March and June. This reduction is thought to

be due to the reduced necessity to secure regulated loads during the

peak produce movement months.

Firm Location

About one third of the truckers in each month reported that Florida

is their firm's home base (Table 1). Another 20 to 33 percent are from

Georgia or the Carolinas. The large majority of these are from North

Carolina, which was the second most important state in each survey

month. The third most important state of origin in each month was

either New Jersey or Pennsylvania.

Of some interest was the fact that owner-operators were about twice

as likely as other carriers to be based in Florida. The percentage of

Florida-based owner-operators and other carriers tended to lower as the

crop season progressed (40 percent of all carriers in November versus

33, 32, and 26 percent in January, March, and June, respectively). It

is thought that this may indicate that Florida-based carriers are better

able to capture loads than are carriers from other states. Early in the

growing season, when shipments are beginning to grow, Florida-based

carriers are able to handle a larger share than their capacity permits

when shipment volumes are at a fairly high level.


Across survey months the distribution of states of destination

differs somewhat. This is thought to be due to two reasons: first,

part of the November survey took place on 1-75, while all of the

January, March, and June surveys were on 1-95; and second, in January

truckers were beginning to 'run for home' prior to the independent

truckers strike. In all three survey months, as would be expected, the

Pennsylvania-New Jersey-New York area was the most important destina-



It was noted that many trucks displayed road use and fuel tax

stickers for a very limited number of states. This led to speculation

that some carriers were operating shuttle-like operations between

Florida and a limited set of destinations. This type of operation may

allow the carrier to become very familiar with terminal markets and

receivers and to avoid payment of fees to several states. One indica-

tion of shuttling would be to determine how many drivers reported that

their current destination was in Florida or in the same area as the

origin point for the load last carried into Florida. In November,

January, March, and June, 50, 42, 38, and 42 percent of the carriers,

respectively, fit this description. This suggests that, contrary to the

popular image of the wide ranging trucker, many carriers limit their

operation to one or a few corridors.

Load Configuration

Approximately one quarter of the loads shipped are mixed or multi-

ple commodity loads (see Table 2). Many of the vehicles had three or

more commodities. It should be noted that in no survey month was a

relationship noted between the propensity to carry mixed loads and

carrier status, years of trucking experience, or the method by which the

load was arranged which was significant at conventional levels of proba-


Pickups and Drops

Between 20 and 41 percent of the loads, depending on the survey

month, required multiple pickups, and between 34 and 49 percent had

multiple drops. As would be expected, there is a greater likelihood for

mixed than straight loads to have multiple pickups or drops (in every

month. In no survey month were owner operators significantly more or

less likely than fleet carriers to acquire multiple pickup or drop


Load Arrangements

The majority of Florida's perishable loads are arranged via brokers

(Table 2). As might be expected owner-operators tend to utilize brokers

Table 2. Selected perishable shipment characteristics

Survey month
November January March June

number of carriers (percentages in parentheses)

Principal commodity:

Load configuration:



43 (29) 26
104 (71) 73

116 (79) 62
31 (21) 37


Arrangement of outbound

Load arranged prior to
returning to Florida:









71 (36)
17 (9)
110 (56)

6 (3)
55 (25)
154 (72)

47 (24) 42 (20)
151 (76) 173 (80)

116 (59) 172 (U0)
82 (41) 43 (20)

119 (60)
79 (40)


119 (51)
105 (49)

(b )

100 (51) 131 (61)
98 (49) 84 (39)

Time necessary to
arrange load:
Less than 1 day
1-3 days
Over 3 days

Average time to arrange
load (days):

Citrus is considered to be one commodity.



161 (81)
20 (10)
17 (9)



190 (88)
24 (12)
1 (0)

to a somewhat greater degree than do fleet carriers, and much more often

than do private carriers. About half of the carriers reported that

their outbound perishables load from Florida was arranged prior to the

time they entered the state. Such arrangements generally take the form

of unwritten contracts between the carrier and the broker or shipper or

receiver to tender one or two loads per week.

Over two-thirds of the carriers reported that they were successful

in securing loads within 24 hours. Less than 15 percent in any month

indicated taking more than 3 days to find a load. This is particularly

impressive considering that, due to heavy rains, trucks were generally

in surplus in January and, to a lesser extent, in March. It should be

cautioned, however, that the only truckers interviewed were those with

perishable loads. Those failing to secure loads were not interviewed.

While no count was taken, it was noted that large numbers of empty

refrigerated vehicles passed the roadguard station in January. As would

be expected, considering the increase in shipments during the spring,

the average time to arrange loads declined rapidly after January (1.79

days in January versus .99 and .46 days in March and June, respec-


Backhaul into Florida and Interstate Hauls

Overall, between 74 and 78 percent of the truckers, depending upon

the survey month, reported having loads when they last entered Florida

(Table 3). In all four survey months, private carriers were most likely

to enter Florida empty, and in three of the four months fleet carriers

were most likely to enter the state with a load. For both fleet

Table 3. Backhaul practices and intrastate trucking activity

Survey month
November January March June

number of carriers (percentages in parentheses)
Percent with an inbound load
Owner-operator 81 76 73 54
Fleet carrier 78 85 96 70
Private carrier 69 47 59 29
All carriers 78 74 77 50

Inbound load arranged byl
Use of authority 28 (14) 13 (18) 41 (27) 25 (23)
Trip lease 31 (27) 19 (26) 45 (29) 35 (32)
Broker 31 (27) 17 (23) 32 (21) 14 (13)
Shipper 11 (10) 6 (8) 11 (7) 13 (12)
Receiver 0 (0) 2 (3) 3 (2) 5 (5)
Other 14 (12) 16 (22) 21 (14) 16 (15)
No load 32 26 45 107

Percent with ICC authority
Owner-operator 16 23 18 15
Fleet carrier 49 58 56 61
Private carrier 24 25 22 0

Made any intrastate hauls
while in Florida?
Yes 3 (2) 0 (0) 4 (2) 3 (1)
No 144 (98) 99 (0) 194 (98) 212(99)

'Percent of those with inbound load in parentheses.

carriers and owner-operators, the full backhaul rate is quite high,

indicating good utilization of the vehicles over the southbound leg of

the journey. For private carriers southbound utilization rates are

fairly low--averaging about 50 percent. This, however, is typical of

private carriage. Given recent relaxations in regulations governing the

use of private fleet vehicles, these utilization rates are expected to

improve somewhat over time.

The three most frequently employed methods of securing loads

reported were:

1) use of own authority

2) trip leasing, and

3) via brokers.

Owner-operators were much more apt to arrange inbound carriage via

brokers and trip leasing and less apt to use their own ICC authority

than were fleet carriers. This is not surprising when it is noted that

fleet carriers were three times as likely as were owner-operators to

possess an ICC authority.

Intrastate hauls within Florida were negligible. Out of 658 inter-

views, only 10 truckers reported making an intrastate haul prior to

securing the perishables load.

Trucker Comments

Truckers were asked what are the one or two principal problems in

exempt trucking (Table 4). Unfortunately, due to human error, comments

were not solicited in the June survey. The most frequently noted

problem was low rates. The truckers correctly noted that while most

Table 4. Principal driver complaints

Survey month1
November January March


Rates too low

Fuel costs too high

Brokers hold down rates
and/or take too much

Taxes too high





Lumping charges too high 36

Weight and length
regulations prohibitive 8

Regulations confusing and
nonuniform from state to
state 10

Poor road and safety condition 2

1No comments were collected in the June

f carriers










2As drivers sometimes offered none or more
percentages may not total to 100.

(percentages in parentheses)2

22 (22)

2 (2)




4 (4)



47 (24)

6 (3)




16 (8)



than one comment, the


costs have continued to rise, truck rates have not increased since

1980. The frequency of complaints regarding rates increased from

November to March perhaps reflecting disappointment with the failure of

rates to increase as the growing season progressed (13, 22, and 24

percent of the truckers cited low rates as a major problem in November,

January, and March, respectively).

A second area of concern was with regard to lumping or forced

unloading fees. Many truckers feel that the receiver should bear the

costs of unloading. This, they argue, would quickly eliminate the

practice of lumping. The percent of carriers citing lumping as an

important problem dropped from 24 in November to 10 in March. It is

felt that this reflected increased concern with the problems of unsea-

sonably low rates and regulatory changes (primarily those in the Surface

Transportation Assistance Act of 1982), rather than any easing of the

lumping situation.

Three closely related complaints were:

1) regulations are confusing and nonuniform from state to state,

2) weight and length regulations are prohibitive, and

3) road and fuel taxes are too high.

Several truckers expressed the sentiment that the system is either

unnecessarily confusing or 'out to get them' or both. They strongly

resent being faced with a new set of rules and taxes everytime a state

line is crossed. Several expressed skepticism when asked if they felt

that the Surface Transportation Assistance Act of 1982 would help to

rationalize the system.

The two other problem areas (high fuel costs, and road safety) were

cited by three percent or less of the truckers in each month. Given the

near-zero change in fuel costs over and immediately before this period,

the apparent lack of concern with fuel costs is not surprising. How-

ever, it should be stressed that carrier complaints regarding low rates

were usually qualified by stating that the rates were low relative to

costs--including fuel. The low response rate regarding safety is

thought to be due to the overshadowing concerns for financial survival.


Respondents were questioned regarding the rates received for the

current (northbound) produce haul. In this section the determinants of

rate levels will be assessed. Of interest will be answering such ques-

tions as:

Are carriers adequately compensated for multiple pickups and


Do brokers increase or decrease rates?,

Does carrier experience or status affect rates received for similar

loads?, and

Does the commodity matter?

In this section, only data from the March and June surveys will be

employed because in the November survey data were not collected regard-

ing the number of drops. The January data is excluded because of

unusual circumstances during the time of the survey. Heavy rains had

slowed or interrupted harvesting operations in the southern part of the

state. Moreover, truckers were beginning to 'run for home' due to the

impending independent truck strike (which began in January 31, 1983).

In the next subsection the theoretical model underlying the analysis is

briefly discussed. Readers may skip this and the next section without

loss of continuity.

Theoretical Model

In unregulated markets, the price of transportation services is

determined by the interaction of demand and supply. On the demand side,

the amount any shipper/receiver is willing to pay for transportation

services (PD) is determined by the spread or margin (M) between the

destination and origin values of the commodity (QD) to be shipped and

the inventory costs (INV) of holding or otherwise using the commodi-

ties. If different qualities of transportation services are available,

S/R will be willing to purchase quality i up to the point where the

marginal cost for that quality (MCi) equates with its marginal return

(MRi) (Johnson). MRi will depend upbn commodity and market characteris-

tics (X). For example, the more perishable and valuable the commodity,

the greater the value of rapid transport to minimize product deteriora-

tion and interest charges on the commodity in transit. The general

form, then, of the demand equation is:

(1) PD = D(QD, INV, M, X, QUAL).

On the supply side the price (PS) necessary to bring forth the

services depends upon the opportunity costs of alternative uses (PA) and

the direct or variable input costs (INP). INP will depend upon such

factors as the quantity to be hauled (Q), distance (D), and the quality

of service (QUAL):

(2) PS = S(PA, QS, INP, D, QUAL).

The system is closed by equating the demand and supply prices and quan-


(3) QS = QD = Q, and
(4) PS = P P.

Empirical Estimation

The competitive structure of the industry suggests that rates are

likely to correspond closely to costs. Therefore, for the empirical

analysis PT is specified as being primarily a function of the variables

related to costs. This reduced form approach may be justified on the

grounds that the net overall impact on PT of the variables in the model

are of primary interest here. Moreover, a reduced form approach is

common in transportation literature (e.g., Beilock and Shonkwiler,

Binkley and Harrar, Ferguson and Glorfeld, and Perkins).

Within each time period (March and June) the effects of the overall

level of market activity (truck capacity considerations) would be cap-

tured in the intercept.1 Moreover variable input costs did not change

appreciably between March and June (for example, the national average

retail diesel prices were 1.15 and 1.19 dollars per gallon in March and

June, respectively (Household Goods Carriers Bureau)). Finally, as

virtually all of the vehicles had full 42-45 foot trailers, the quanti-

ties carried were essentially the same.

Assuming that fuel efficiences, speeds, and labor costs are similar

across trucks, distance (D) is a reasonable proxy for running or line-

haul costs. As equipment types and handling procedures are similar from

load-to-load, the major observable variations in service per trip are

the number of pickups (PKUP) and drops (DROPS). Another service quality

is the promptness of carriage, that is the availability of vehicles as

needed. This relates to or can be proxied by the queue length of vehi-

cles ready to offer service. Queue length or the amount of excess

capacity offered is not observable. However, following DeVany and

Saving (1977), in a competitive market S/R will pay for longer or

shorter truck queues, or, equivalently, for more or less excess capacity

depending upon the urgency of their shipment. Therefore, the time-

sensitivity of the commodities may be substituted for queue length (for

a fuller discussion, see Appendix 2). In this analysis, time-sensi-

tivity will be captured by the average per day loss in cargo value

calculated as the per hundredweight farm level price divided by days of

storage life (DAYLOSS).2

Finally, in order to test the hypotheses that some carriers are at

a disadvantage in the market, the impact of three dummy and one contin-

uous variable will be examined:

OWNOP = 1 if carrier is an owner-operator, 0 otherwise

SHUTTLE = 1 if carrier is based in Florida or in one of the destin-

ation states for the haul, 0 otherwise,

BROKER = 1 if load arranged by a broker, 0 otherwise,

OEXPER = number of years of driving experience if an owner-

operator, 0 otherwise.

SHUTTLE is included on the premise that a carrier based at either end of

the haul would be likely to possess more market information than other

carriers. BROKER is included to determine if rates received are depen-

dent upon whether the load is arranged only by a broker.

The general form of the relationship to be estimated is:


Since many transportation rates rise at a slower rate with increased

distance,3 the inverse of distance (INVD) will be used in the estimation

process. Restricted and unrestricted models are estimated, and Chow

tests are employed to determine if differences exist in intercept and

slope parameters between months. The expected signs for the parameters

associated with each variable are presented in Table 5.

Results of Estimation Process

In Table 6 the results of the estimation process are presented.

the Goldfeld-Quandt test for heteroskedasticity (across INVD and

DAYLOSS) was carried out for each model, but none was indicated (John-

ston, p. 218-219). All equations were highly significant and, in all

cases the coefficients of determination ranged from .54 for the fully

restricted equation (model 4) to .62 for the fully unrestricted equation

(model 1).

The loss in explanatory power between the fully unrestricted equa-

tion (model 1) and the fully restricted equation (model 2) indicated

Table 5. Expected parameter signs and condition or rationale

Associated Expected
Ad E d Condition or rationale
variable signs

Positive association of costs (fuel, etc.)
and D

If carriers compensated for this service

If carriers compensated for this service

If time-sensitive commodities pay for
expedited service (excess capacity)

If owner-operator disadvantaged relative to
other carriers due to lack of information

If familiarity with origin or destination
markets results in an advantage in market

If brokers improve (lower) rates received

If a market advantage can be gained from
additional experience










Table 6. Truck rate estimation equations

Independent Model IA Model 2A Model 3A Model4A



















Number of



























AThe following


are the results

of Chow tests between appropriate models:
F-Ratio Significantly different
at 5 percent level

-JD denotes interaction term between the variable and a dummy which
equals I of the observation is from June, and zero if from March.
ISignificantly different from zero at the 10 percent level.

2Significantly different from zero at the 5 percent level.
3Significantly different from zero at the 1 percent level.


some differences between the March and June samples (the null hypothesis

of no difference between models 1 and 4 can be rejected at the 5 percent

level). This is thought to be due primarily to differences between the

market conditions in March and June. In March, Florida interstate

produce and ornamentals shipments were approximately 3,000 truckloads

per week, a rate which had been maintained since early January. Truck

supplies were adequate, with some surpluses. By contrast, in early June

movements were at their annual peak of 7,000 to 8,000 truckloads weekly,

and, though no serious shortages developed, truck supplies were tight.4

As would be expected, in all equations PT is strongly and posi-

tively related to D, as indicated by the highly significant parameter

estimate for INVD. Also as expected, the parameter estimates suggest

that rates taper or increase more slowly with increased distance.5 In

model 1, the parameter associated with INVD-JD (the interaction term

between INVD and a dummy variable equal to 1 if June and 0 if March) was

not significant even at the 10 percent level, indicating considerable

stability in the rate-distance relationship across months. Considering

the greater urgency in early June to return for another load before

shipment volumes collapse, the somewhat higher per distance penalty or

fee indicated by the estimated parameter for INVD-JD (-2060500) is

reasonable and, in a one-tailed test, the parameter would be significant

at the 10 percent level.

The positive sign and high level of significance for the estimated

parameter associated with DAYLOSS (significantly different from zero, in

all models, at the one percent level) lends strong support to DeVany and

Saving's contention that value-of-service pricing schemes evolve in

unregulated markets. The positive sign for the parameter associated

with June slope shifter (DAYLOSS-JD) is reasonable, when it is consid-

ered that with the tighter truck supply situation in June, higher

premiums would be necessary to secure expedited service. Moreover,

given the much higher temperature in June than in March, holding costs

would be higher. While this parameter estimate was not significantly

different from zero at the 10 percent level, it was significant at that

level employing a one-tailed test. Depending upon the model, it is

estimated that in March for every 1,000 dollars more of average daily

loss (DAYLOSS), PT was between 87 and 112 dollars higher, and, in June,

between 112 and 153 dollars higher.

The evidence regarding reimbursement for pickups and drops is

somewhat mixed. From model 1, the estimates indicate that in March

carriers received no reimbursement for pickups (the parameter estimate

of -2.214 was highly insignificant), but 129.40 dollars per drop (signi-

ficant at the one percent level) ceteris paribus. In June the reverse

was the case, with 76.67 dollars received per pickup (78.88 2.21 =

76.67, parameter significant at the one percent level), but no reim-

bursement for drops (129.4 114.2 = 15.20, insignificantly different

from zero at conventional levels). One possible explanation for these

results is that in March the focus is on the costs inherent in making

deliveries under difficult or uncertain weather conditions, while in

June the major concern is the time and cost involved in making pickups

during peak production. Nevertheless, it must be concluded that the

question of remuneration for pickup and drop services is still unan-

swered. It should be noted, however, that there was no evidence to

support the hypothesis that fleet operators secured single or few pickup

and drop loads more frequently than owner-operators.

Overall, the indicators of carrier status and market familiarity

(OWNOP, SHUTTLE, BROKER, and OEXPER) proved to be of little explanatory

value. With the single exception of SHUTTLE for March carriers, no

factor appeared to appreciably affect PT. The absence of the effect of

SHUTTLE in June is reasonable because the advantages to be gained from

knowing where and how to look for loads are likely to be less when loads

are abundant. The omission of all of the carrier sophistication indica-

tors (model 3) or all but SHUTTLE (model 2) does not greatly alter the

remaining parameters or compromise the explanatory power of the equation

(Table 6, footnote 1).

Summary and Conclusions

In this report the results of a study of the Florida perishables

trucking industry have been presented. The study may be divided into

two parts--a description of the overall structure and characteristics of

the system, and an analysis of the determinants of freight rates. The

principal results of the former are:

1. Owner-operators carry approximately 55 percent of Florida's

perishable products shipped by truck.

2. All classes of carrier (owner-operator, fleet carrier, and

private carrier) which haul Florida perishables tend to speci-

alize in exempt commodity carriage.

3. About 25 percent of the shipments are mixed loads.

4. About 55 percent of perishable loads are arranged through

brokers, and roughly half of the loads are not arranged until

after the truck arrives in Florida.

5. Roughly 30 percent of the loads require multiple pickups and

around 40 percent require multiple drops.

6. Many carriers appear to restrict their operations to one or a

few corridors.

7. About 75 percent of the inbound vehicles have full loads, and

low rates.

8. Low rates, forced unloading charges, and confusing, often

redundant regulations are the three major concerns of truckers


The rate analysis focused on two major questions:

1. Does the rate structure resemble a value-of-service price

system? and

2. Are carriers reimbursed for additional services,.in particular,

multiple pickups and drops?

The findings indicate that the answer to the first question is 'yes.'

Rates were found to be strongly and positively affected by the average

daily loss (due to perishability) of the commodity being hauled. Con-

sidering the competitive structure and unregulated status of the indus-

try, this suggests, as was hypothesized by DeVany and Saving, that

shipper/receivers pay and carriers charge for the excess capacity asso-

ciated with expedited service.

The answer to the second question is clouded. In the March sample

carriers appeared to be reimbursed for drops but not for pickups, while

the reverse was true for the June sample. While these differences may

be partially explained by differences between the months in congestion

at the loading areas in Florida and in weather conditions in the North,

the complete absence of compensation for March pickups and June drops is

puzzling. There was no evidence, however, that owner-operators were

more or less likely than fleet carriers to secure loads requiring multi-

ple pickups or drops. Therefore, while the question of compensation

remains unclear, it does not appear that one class of carrier desires or

is better able to avoid supplying additional pickup and drop services.


1. It would be expected that if vehicles were generally in short

supply in one month, then the base or intercept would differ as the

reservation price of carriers to take any given load would be


2. Farm level prices were obtained from the Florida Crop and Livestock

Reporting Service. Perishability estimates for Florida commodities

were obtained from Pavlovic et al. (1980).

3. Several researchers have noted a tapering effect in rates with

distance (e.g. Bressler and King (1978), and Wilson (1980).

4. Throughout March the truck supply situation was characterized as

'slight surplus' or 'adequate' in the USDA Fruit and Vegetable

Truck Rate Report while in June the classification changed to

'shortage' or 'slight shortage.' As further evidence of the change

in conditions, in the March survey truckers reported an average

delay of .99 days to secure a haul, versus .46 days, on average, in


5. In an alternative model specification (not shown) D and D squared

(DSQ) were employed instead of INVD. In all the parameter asso-

ciated with D was positive and that for DSQ was negative, and both

significant at the 5 percent level. The rate-distance peak was

well beyond the range of the data (rates peaked at about 3,000

miles distance). This specification was not employed as it

decreased degrees of freedom without changing the other parameters

or improving the fit of the equations over that achieved with INVD.


1. How long have you been a driver?

2. Which best describes your operation? (a) owner-operator (b) fleet operation
(c) private operation (d) agricultural cooperative (e) other

3. Do you have ICC authority? YES NO
If yes, to haul what comodities?

4. Out of what state do you operate?
(Base plate state.)

5. About what proportion of time do you haul Exempt Commodities? Z
Trip Lease? %
Permanent Lease? %

6. What is/are your load(s) today, how much of each, where did you make your pick-
ups and what are your destinations?

(List 2) or Z full seace

7. How did you get this load? (a) broker (b) direct contact with shipper
(c) direct contact with receiver (d) other

8. How long did it take to get it?
(From the time you started looking.)

9. Did you have this load arranged by the time you entered Florida? YES NO

10. What are you getting for the load you are now carrying? S

11. What did you bring into Florida?

12. From what state?
How did you get that load?

REGULATED: used own authority EXEMPT: broker
trip lease in Florida
ocher ,, shipper

13. What did you get on the load you brought into Florida? $
(See question fll.)

14. Did you make any intrastate hauls in Florida prior to getting this load?

YES NO If yes, what?

15. Is there ,.: area of exempt trucking that concerns you coday? (a) safety
(b) Lumping (c) non uniformity of trucking regulations from state to state
(d) rates (e) other



Let QT = quantity of the commodity transported,

QD = quantity of the commodity demanded,

PD = delivered price of the commodity,

PT = price of transport,

a = PT/PQ, and

%7 = percentage change.

The elasticity of demand for the commodity (ED) is equal to:

(1) ED =

Assuming constant inventories:

(2) QD = QT

Assuming that changes in freight rates are immediately passed through to

the final consumer,

(3) PD T= PT

Substituting (2) and (3) into (1) we get:

(4)ED =

Multiplying (4) through by a we get:

(5) aED = g =ET

where ET is the elasticity of demand for transportation. The larger is

PQ, given PT, the smaller is u, and, ceteris paribus the smaller is ET

(in absolute terms). For a durable good, PQ is a good proxy for the

rate of loss from delay. This is because the per unit costs of tied up


capital are obviously related to PQ. For a perishable, or a durable

with expected changes in PQ, the pQ ET relationship is somewhat

clouded. In such cases a truer index of shipping urgency, or loss from

delay would encompass both the capital costs of the delay and the

expected per unit time change in PQ. In the current study, shipping

urgency was proxied by the average per day loss in value due to spoil-

age. It should be noted that this assumes that expected and current per

unit commodity prices are equal.


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