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Food and Resource Economics Department
Agricultural Experiment Stations
hutituts of Food and Agricultural Sciences
Unvrfty of Florida, Gaknesvile 3261
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
TABLE OF CONTENTS
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
LIST OF TABLES
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
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
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
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
November January March June
number of carriers (percentages in parentheses)
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
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
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
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.
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.
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
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
November January March June
number of carriers (percentages in parentheses)
43 (29) 26
104 (71) 73
116 (79) 62
31 (21) 37
Arrangement of outbound
Load arranged prior to
returning to Florida:
47 (24) 42 (20)
151 (76) 173 (80)
116 (59) 172 (U0)
82 (41) 43 (20)
100 (51) 131 (61)
98 (49) 84 (39)
Time necessary to
Less than 1 day
Over 3 days
Average time to arrange
Citrus is considered to be one commodity.
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
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
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.
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
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
Poor road and safety condition 2
1No comments were collected in the June
2As drivers sometimes offered none or more
percentages may not total to 100.
(percentages in parentheses)2
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
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-
Are carriers adequately compensated for multiple pickups and
Do brokers increase or decrease rates?,
Does carrier experience or status affect rates received for similar
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.
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.
T T T
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:
P = P (D, PKUP, DROPS, DAYLOSS, OWNOP, SHUTTLE, BROKER, OEXPER).
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
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
Ad E d Condition or rationale
Positive association of costs (fuel, etc.)
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
Table 6. Truck rate estimation equations
Independent Model IA Model 2A Model 3A Model4A
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
7. About 75 percent of the inbound vehicles have full loads, and
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
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?
MAJOR COMMODITY AMOUNT NTUMER OF PICKUPS NUMBER OF DROPS DESTINA'
(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:
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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