Chapter One gives a brief overview of the changes that took place in the U.S. trucking Industry after the passage of the Deregulation acts in 1980. This chapter focuses on the four major changes witnessed by the industry namely Industry Bifurcation, Increase in the demand for trucking Industry, increase in the number of new entrants and decline in the unit revenues, costs and profits. This chapter forms the basis for the next chapter which relates these changes with the overall change in productivity in the trucking industry post deregulation. Chapter Two discusses the concept of Productivity in respect to the U.S. trucking industry. This chapter talks about the different methods of measuring productivity and forms the conclusion on the type of productivity measurement that will then be used for the remainder of this paper. Chapter Three talks about the growth in productivity in the trucking Industry with respect to Truckload, Less-than Truckload and Hybrid operators and compares the Multifactor Productivities of each of these operators Chapter Four discusses the various factors post deregulation that caused the variations in the growth rate of Multifactor Productivity along with statistical data to correlate the productivity trends in a more conclusive manner. Chapter Five concludes the report with a personal viewpoint on the contribution of Deregulation in improving the Productivity of the Trucking Industry.

1. CHANGES IN TRUCKING INDUSTRY AND ITS PRODUCTIVITY
POST DEREGULATION
Submitted by: Ashish Pal Singh Rekhi

2. 2
ACKNOWLEDGEMENTS:
I would like to thank all the people who guided and supported me while writing this research project.
Firstly, I would like to thank my Professor, Mr. Robert Hoffman, who provided constant guidance to me
for the entire duration that I wrote this paper.
Secondly, I would like to thank Captain Vijay Wadhawan, Marine Superintendent, at the Saudi Arabian
Chevron Inc., Al Zour, Kuwait, and Mr. Steve Silao, Operations Manager, Bin Nowiran Contracting and
Trading Co, Ahmadi, Kuwait, for agreeing to speak with me and share his experience about the various
sectors in the trucking Industry.
This paper would not have been possible without their constant support and guidance.

3. 3
OUTLINE OF PAPER:
Chapter One gives a brief overview of the changes that took place in the U.S. trucking Industry after the
passage of the Deregulation acts in 1980. This chapter focuses on the four major changes witnessed by
the industry namely Industry Bifurcation, Increase in the demand for trucking Industry, increase in the
number of new entrants and decline in the unit revenues, costs and profits. This chapter forms the basis
for the next chapter which relates these changes with the overall change in productivity in the trucking
industry post deregulation.
Chapter Two discusses the concept of Productivity in respect to the U.S. trucking industry. This chapter
talks about the different methods of measuring productivity and forms the conclusion on the type of
productivity measurement that will then be used for the remainder of this paper.
Chapter Three talks about the growth in productivity in the trucking Industry with respect to Truckload,
Less-than Truckload and Hybrid operators and compares the Multifactor Productivities of each of these
operators
Chapter Four discusses the various factors post deregulation that caused the variations in the growth
rate of Multifactor Productivity along with statistical data to correlate the productivity trends in a more
conclusive manner.
Chapter Five concludes the report with a personal viewpoint on the contribution of Deregulation in
improving the Productivity of the Trucking Industry.

4. 4
TABLE OF CONTENTS
ACKNOWLEDGEMENTS:............................................................................................................................. 2
OUTLINE OF PAPER:.................................................................................................................................... 3
TABLE OF FIGURES:..................................................................................................................................... 5
CHAPTER 1: CHANGES IN THE TRUCKING INDUSTRY POST DEREGULATION ........................................... 6
1.1. INDUSTRY BIFURCATION...........................................................................................................................6
1.2. INCREASE IN THE DEMAND FOR TRUCKING INDUSTRY................................................................................8
1.3. INCREASE IN NUMBER OF NEW ENTRANTS................................................................................................9
1.4. DECLINE IN UNIT REVENUES, COSTSAND PROFITS .....................................................................................9
CHAPTER 2: CONCEPT OF PRODUCTIVITY ............................................................................................... 11
2.1. DEFINITION OF PRODUCTIVITY................................................................................................................11
2.2. SELECTING OUTPUT AND INPUT VARIABLES.............................................................................................12
2.3. SINGLE FACTOR AND MULTI-FACTOR PRODUCTIVITY................................................................................12
CHAPTER 3: PRODUCTIVITY GROWTH IN TRUCKING INDUSTRY............................................................ 14
3.1. CUMULATIVE MULTI-FACTOR PRODUCTIVITY...........................................................................................14
3.2. YEARLY MULTI-FACTOR PRODUCTIVITY GROWTH.....................................................................................15
3.3. MULTI-PHASE PRODUCTIVITY..................................................................................................................16
CHAPTER 4: FACTORS CAUSING PRODUCTIVITY VARIATION IN TRUCKING INDUSTRY ........................ 17
4.1. UPGRADES IN THE QUALITY OF INFRASTRUCTURE....................................................................................17
4.2. IMPROVEMENT IN INFORMATION TECHNOLOGY.....................................................................................19
4.3. LENGTH OF HAUL ...................................................................................................................................20
4.4. CONTAINERIZATION...............................................................................................................................21
CHAPTER 5: CONCLUSION........................................................................................................................ 22
REFERENCES:............................................................................................................................................. 23

5. 5
TABLE OF FIGURES:
1.1. Trend of Top 50 Hybrid Carriers Post Deregulation 7
1.2. Bifurcation in the trucking industry from 1977 up to 1992 7
1.3. Ton-Miles by Mode of Transportation, post 1980 8
1.4. Percentage Ton-miles by Mode of Transportation, 1993 and 2007 8
1.5. Increase in Number of Truck Carriers Post Deregulation 9
1.6. Median Revenue per Ton-Mile, 1977 – 1991 10
1.7. Median Expense per Ton-Mile, 1977 – 1991 10
1.8. Median Income (Profit) per Ton-Mile, 1977 – 1991 10
2.1. Productivity Flow Chart 11
3.1. Multi-Factor Productivity in TL and LTL Sector 14
3.2. Yearly Multi-Factor Productivity in TL and LTL Sector 15
3.3. Ideal Situation for MFP calculation 16
3.4. Best Situation with available Data 16
4.1. Growth in Capital and Capital per worker, 1987 – 2003 18
4.2. Sub-Period Growth in Capital and Capital per worker, 1987 – 2003 18
4.3. Factors affecting MFP growth for different sub-periods 19
4.4. Average Length of Haul (1985 – 2001) 21
4.5. Number of containers used (1990 – 2004) 21

6. 6
CHAPTER 1: CHANGES IN THE TRUCKING
INDUSTRY POST DEREGULATION
This section includes a description of the various
changes that the trucking industry underwent
after the control on their activities was waived off
post the deregulation.
These include:
 Industry Bifurcation
 Increase in the demand for Trucking
Industry in comparison to other
Transportation modes
 Increase in the number of New entrants
 Decrease in costs and revenues
1.1. INDUSTRY BIFURCATION
Post Deregulation, a majority of the Trucking
Companies were hybrid in the sense that they
specialized in both Truckload (TL) and Less-Than-
Truckload (LTL) operations. However, post the
deregulation, the industry witnessed bifurcation in
context to companies specializing in either
Truckload (TL) or Less-Than-Truckload (LTL)
operations.
A Truckload (TL) operation generally refers to any
carrier carrying shipment weighing 10,000 pounds
or more whereas a Less-Than-Truckload (LTL)
operation refers to any carrier carrying shipment
weighing less than 10,000 pounds.
In a Truckload (TL), the driver picks up the load
from the shipper and delivers it directly to the
consignee without stopping to pick up additional
freights whereas, in comparison, LTL operations
are much more intensive wherein since the
shipment size is small, the driver stops at
economically feasible locations to pick-up and
deliver consignments in order to increase the
revenue per truck.
In terms of costs associated, TL operations are
much faster and cheaper (on a per unit basis) in
comparison to LTL. However, to make TL
operations a more financially feasible option, the
quantity of freight to be shipped from the source
to the destination must be large enough to justify
purchasing an entire truckload haul.
Due to the deregulation, the once popular hybrid
carriers in the trucking industry soon lost to

7. 7
specialized TL and LTL carriers with a majority of
them either loosing revenues, or re-strategizing
their operations to specialize in strictly TL or LTL
operations.
Figure 1.1 shows the trend of the Top 50 Hybrid
carriers post deregulation.
Figure 1.2 shows the trend of companies
performing TL, LTL and Hybrid operations prior to
and post Deregulation. In Figure 1.2, a significant
shift in carrier operations post deregulation (1980
onwards) can be observed. In comparison, post
deregulation, the number of carriers providing
both TL and LTL i.e. Hybrid operations reduced
significantly to negligible in number. Also, the
Figure 1.1: Trend of Top 50 Hybrid carriers post Deregulation Source: Form M data, author’s calculation
Figure 1.2: Bifurcation in the Trucking Industry from 1977 up to 1992 Source: Form M data, author’s calculation

8. 8
share of the Top 100 firms earning between 20% -
80% of their revenues from TL operations reduced
significantly from 82% to 10%.
1.2. INCREASE IN THE DEMAND FOR
TRUCKING INDUSTRY
Post deregulation, the transportation industry
experienced a major shift of dominance to the
Trucking Industry amongst various modes of
freight transportation. With the help of various
graphs based on the data from the Bureau of
Transportation Statistics (BTS), the author aims to
establish a comparison of the Trucking industry
with other modes of freight transportation.
As seen in figure 1.3, up until 1980, Rail, Pipeline
and Water Transportation had almost equal ton-
miles output, with the trucking industry trailing
behind by nearly 400 billion ton-miles. However,
post the deregulation, this trend witnessed
prominent alterations as just within the 25 years
to follow, the ton-miles of the trucking industry
increased by nearly 120%, whereas, apart from the
rail industry, all other modes i.e. Pipeline, Water
and Air transportation experienced huge
reductions in ton-miles, with water freight
transportation experiencing the most significant
drop.
Figure 1.4 illustrates the contribution of the
Trucking Industry in the overall freight
transportation industry.
As seen from the figure, the trucking industry
experienced rapid growth in terms of ton-miles
between 1993 up to 2007.
By 2007, specific truck transportation accounted
to nearly 41% of the total freight transportation.
Further, different intermodal transportation also
uses trucking in some phase which adds another
Figure 1.3: Ton-Miles by Mode of Transportation, post
1980
Source: Bureau of Transportation Statistics, Special Report (2007)
Figure 1.4: Percentage Ton-Miles by Mode of
Transportation, 1993 and 2007
Source: Bureau of Transportation Statistics, Special Report (2007)

9. 9
9% to the ton-miles of trucks, thereby bringing the
total up to 50%.
The trucking industry dominated the
transportation industry not only in terms of
percentage of ton-miles, but also in terms of the
value of goods transported. Trucks were, and
continue to be used as a major source of
transporting high-value products, with the
trucking industry transporting nearly 73% of the
total value of goods in 2007. This value has
decreased, though not significantly, in comparison
to 76% in 1993. This decrease can be attributed
mainly due to faster supply of higher quality
products via Air transportation.
1.3. INCREASE IN NUMBER OF NEW
ENTRANTS
With the ICC lifting barriers to entry for new
entrants in the late 1970s, there was a steep
increase in the number of ICC regulated motor
carriers.
Figure 1.5 depicts the rapid increase in new
entrants in the trucking industry post the policies
initiated by the ICC in late 1970s. These new
entrants where mainly smaller carriers which were
significantly inclined towards TL operations rather
than LTL operations. So, the graph above shows
the rapid increase in the truck load carriers and a
non-commensurate decline in the less-than-truck
carriers.
1.4. DECLINE IN UNIT REVENUES,
COSTS AND PROFITS
Post deregulation, the trucking industry witnessed
major changes in terms of revenues, profits and
expenses for the TL, LTL and Hybrid carriers.
Due to lift in the various restrictions, a lot of new
entrants came into the market. As the number of
suppliers increased, the main segregator between
companies became pricing. This causedcompanies
to lower their prices in order to attract customers.
Eventually, the price drop was evident in almost
every trucking company. Though this increased the
clientele for these companies, their revenues
declined and thus, so did their profits. The
companies were now facing the dilemma of either
Figure 1.5: Increase in Number of Truck Carriers Post
Deregulation
Source: American Trucking Association (ATA) annual Trends Report

10. 10
continuing to price high for their services and get
fewer customers, or to reduce their prices to
increase customer intake. What remained
common in both these alternatives was a
significant decline in revenues and profits.
Figures 1.6, 1.7 and 1.8 show the trend in
revenues, Expense and Income based around the
median for each.
First, talking about Median Revenue per Ton-mile,
LTL and TL carriers showed an almost constant
decline in revenues with a few exceptions arising
in 1980,19876 and 1992 wherein the revenues of
these years increased in comparison to that of the
previous years.
Secondly, the Median Expense also saw a decline
for TL and LTL carriers with the hybrid carriers
having minor variations in the years from 1985
through 1992.
Thirdly, the median Profit saw a decline in all three
sectors i.e. TL, LTL and Hybrid carriers. The year
post deregulation (1981) saw a sudden increase in
profits for all these carriers. However, this positive
trend could not be sustained for long, likely
because new entrants came into the trucking
industry around this time.
Figure 1.6,1.7,1.8: Median Revenue, Expense and Income
per Ton-Mile Post Deregulation
Source: American Trucking Association (ATA) annual Trends Report

11. 11
2.1. DEFINITION OF PRODUCTIVITY
Productivity is defined as the measure of output
generated for a given input(s). Theoretically
speaking, productivity can be increased by either
increasing your outputs for given set of inputs, or
outputs. Though this definition makes
productivity seem fairly straightforward,
productivity is a subjective term and thus,
calculating the productivity of a firm, an industry,
a good, or a service, requires an extensive analysis
of the respective organization's available data.
For the scope of this paper, the term
“productivity” refers to physical productivity i.e.
the relation between the physical inputs in the
trucking industry with the physical outputs in this
industry. Examples of physical units include ton-
miles and employees. However, these are not the
physical inputs that are considered thoroughly.
This is because these units may be ambiguous or
too large in number in some cases, which makes
using inputs such as investments, revenues, etc.
more practical.
As mentioned above, taking into account only the
physical measures of inputs and outputs, the role
of productivity in an organization is depicted in
figure 2.1.
For any firm seeking to achieve maximum
profitability, this can be done in three ways: by
obtaining low input prices (costs), by maximizing
productivity, or by obtaining high output prices.
So, if this hypothesis is considered in case of any
Supply chain network, the output of a supplier may
be the input of another firm, and thus, the input
price of the firm would depend on the output price
of the supplier. Contrary to using pricing as input
CHAPTER 2: CONCEPT OF PRODUCTIVITY

12. 12
and output units, using physical productivity
measures causes comparatively less enduring
harm to both, the supplier and the firm.
This justifies the importance given to productivity
growth amongst firms as well as policy makers.
2.2. SELECTING OUTPUT AND INPUT
VARIABLES
In context to freight transportation in the trucking
industry, the fundamental output is the movement
of goods from source to destination. In calculating
the productivity of a trucking operation, it is
essential to figure out what and how many inputs
are required to transport a given volume of goods
from the point of origin to the final destination.
Then, in calculating the productivity, the first step
would be to select a particular output that should
be measurable. The most commonly used unit for
this physical output is ton-miles (TM).
Ton-Miles or TM is then calculated using the
formula:
 TM is ton-miles
 MILE is miles per movement
 TON is the tonnage per movement
 The summation is over all movements m
As an example, suppose that a particular trucking
company is shipping 100 tons over a distance of
500 miles. This company is thus generating
500,000 ton-miles.
However, Ton-miles is not an accurate indicator of
the value of shipment as it doesn’t take into
account whether the transit is a longer light haul
operation or a shorted heavy haul operation.
Next, is the selection of a suitable unit(s) for the
input, which should also be measurable. The most
fundamental inputs in trucking operations are
labor, capital, and/ or fuel. However, while
considering only the physical productivity, the
capital input can be attributed to the equipment
used for freight transportation, i.e. trucks. There
are other physical inputs involved in a trucking
operation such as roads, land, topography, etc.
However, these cannot be measured easily
thereby considering them as physical inputs a
tedious task, which is therefore, neglected.
2.3. SINGLE FACTOR AND MULTI-
FACTOR PRODUCTIVITY
Apart from the basic calculations involving total
output produced versus the total input provided to
generate that given output, another method to
determine the contribution of particular input (or
inputs) to the overall output of an entity, ratios

13. 13
known as singlefactorproductivity and multifactor
productivity are used.
Single factor productivity calculations are used in
places where the overall output needs to be
compared to the individual contribution of a single
input. A common example of usage of Single
Factor Productivity in the trucking industry is
calculating ton-miles per employee. For this, the
trucking company’s analysts simply formulate the
total ton-miles covered by their trucks over a
period of time and divide it by the total number of
employees working in the firm. This employee
count selection can be based on direct and/or
indirect impact that the individual members of the
firm have on the ton-miles. For example, some
firms calculate the employee productivity in ton-
miles by accounting for each and every employee
who is a part of the firm, including truck drivers,
supply chain managers, office workers, clericaland
non-clerical staff, etc. Others calculate it on the
basis of the trucking drivers involved in freight
transportation. So, for example, if a firm takes all
employees into account, it will have a single factor
productivity likely lesser than that of a firm taking
only truck drivers as employees into account.
However, this is subjective and though
theoretically it seems plausible, a lot of variations
occur in actual practice. Though Single Factor
productivity gives us an insight of a particular
input’s contribution in the total productivity of an
entity, it has some flaws in itself as a concept. This
is because the trucking industry is not a
streamlined industry, and so, instead of a single
input, a combination of input is required to
produce required output. This makes the use of
Single factor productivity for comparative analysis
fairly inadequate.
Multifactor productivity on the other hand
improves upon this flaw. In Multifactor
Productivity, a variety of inputs are combined
together to calculate the overall impact that this
combination of inputs has on the overall output of
the firm.
In Multifactor Productivity, a firm can club inputs
such as number of drivers, fuel cost for freight
transport, number of hours required to complete
a shipment, driver wage, etc. which are
interdependent on each other and get a clearly
idea of the productivity of the firm at the
operations and shipping implementation stages.
Similarly, different inputs can be combined to
compare productivity at different sectors of
functioning within the firm.

14. 14
As discussed in the previous chapter, since single
factor productivity (SFP) is an inaccurate measure
to compare the productivity between firms or
within a firm itself, for the scope of more
conclusive and reliable comparison, in this
chapter, the growth in trucking industry post
deregulation will be compared on the basis of
Multi-Factor Productivity (MFP).
As Discussed earlier, all measures of productivity
in this report are attributed to only physical
productivity, and not value, price or revenue
changes.
Since the trucking industry witnessed abifurcation
into 2 major categories i.e. Truckload (TL) and
Less-than-Truckload Operations, the individual
growths of both these sectors will be compared in
context to cumulative and yearly multi-factor
productivity growth.
3.1. CUMULATIVE MULTI-FACTOR
PRODUCTIVITY
The first parameter to be considered is the
Cumulative Multi-Factor Productivity (MFP)
performance for TL and LTL sectors. Post
deregulation, the truckload sector had better
performance than the Less-than truckload sector.
In practice, the TL sector experienced a growth of
23% between the years 1979 and 1992, which is
significantly greater than the 13% growth
experienced by the LTL sector.
This brings the average annual growth to 1.6% for
the TLsector, and nearly 1% for the LTL sector. The
difference in growth of the TL and LTL sectors can
be attributed to the fact that the LTL sector was
relatively more
unionized and thus, resistant to the changes that
accompanied the deregulation. Also, since the
number of LTL companies increased post the
CHAPTER 3: PRODUCTIVITY GROWTH IN TRUCKING
INDUSTRY
Figure 3.1. Multi-Factor Productivity in TL and LTL
Sector
Source: Bureau of Transportation Statistics, Special Report
(2007)

15. 15
deregulation, the oversupply of LTL companies
negatively impacts the productivity performance
of the LTL sector on account of excess capacity.
In totality, the trucking industry experienced
positive growth, in both the TL and LTL sectors.
However, this growth cannot be solely attributed
as a productivity revolution post deregulation. A
more plausible conclusion to this would be that
since the deregulation lifted various bans and
restrictions on the industry, a majority of the
trucking industries saw this lift as an opportunity
to expand their business and operate under a
more self-controlled environment. Also, since the
deregulation encouraged a lot of new players into
the market, the number of trucking companies
increased causing higher dependence of Supply
Chain Activities on the industry, thereby pushing
companies to increase productivity in order to stay
in business.
3.2. YEARLY MULTI-FACTOR
PRODUCTIVITY GROWTH
In this segment, the author will be discussing the
yearly growth pattern of Multi-Factor Productivity
in the Trucking Industry. Figure 3.2 shows the
yearly growth in the TL and LTL sectors post
deregulation along with statistics from 1978 and
1979 for comparison in trends pre and post
deregulation. A major variation in the growth
patterns between TL and LTL sectors occurred in
1980 and 1981, i.e. the first two years wherein the
deregulation norms were implemented.
The TL sector experienced significant positive
growth in these years whereas the LTL sector
witnessed
major setbacks causing a deeply negative
productivity trend. However, after the first 2 years
post deregulation, both the TL and LTL sectors
experienced growth in Multi-Factor productivity
with exceptions being in the years 1982, 1985 and
1989. However, since this data is not completely
accurate, a cumulative analysis of Multi-Factor
Productivity bears a more reliable result than a
yearly productivity analysis. Also, the decrease in
productivity in these years can be attributed to
recessions that took place in that time, which
inevitably caused companies to reduce their work
Figure 3.2. Yearly Multi-Factor Productivity in TL
and LTL Sector
Source: Bureau of Transportation Statistics, Special Report
(2007)

16. 16
force in order to balance finances with the
decrease in production, and thus, demand for the
trucking industry. An interesting thing to note here
is that though the TL and LTL sectors experienced
negative growths in the years 1982, 1985 and
1989, the years following them showed significant
growth in productivity. This means that though
recessionhit the trucking business adversely,post-
recession the companies emerged leaner and
more competitive.
3.3. MULTI-PHASE PRODUCTIVITY
Multi-Phase productivity is a concept that is
applicable in the trucking industry. In this concept,
single or multiple inputs give outputs that are
dependent on each other i.e. on output is
generated from another output, hence the term
Multi-Phase. There is often confusion between
Multiple Outputs and Multi-phase outputs,
wherein the former is a process which generates
multiple outputs independent of each other, and
the latter is aprocess wherein multiple outputs are
produced in dependence with each with other. It
is often argued that the trucking industry is amulti-
phase industry wherein multiple inputs and
outputs collaborate in a somewhat linear
formation in such a way that each succeeding
phase is an extension of the previous phase.
However, what prevents widespread usage of this
measurement is the fact that data regarding the
usage of given inputs is highly subjective and
tracking and collecting this data is extremely
tedious. Given below are flowcharts which
respectively represent the Ideal situation for
analyzing the multiphase productivity, and the
best situation that can be created and analyzed
with the available data from Form M.
The insufficiency in available data makes using
Multi-phase productivity for comparing truck
companies unappealing.
Figure 3.3. Ideal situation for Multi-Phase Productivity
Calculation
Source: Form M Data
Figure 3.4. Best situation with available data
Source: Form M Data

17. 17
In this previous chapters, the author has discussed
the changes that the trucking industry witnessed
post deregulation, the concept of productivity in
context to the trucking industry, and the growth in
productivity in TL and LTL sectors of the trucking
industry post deregulation. Though, in generalized
terms, the deregulation brought with it changes in
the growth patterns of productivity, in this
chapter, the various factors that caused this
change in the productivity trend will be discussed.
On account of truck transportation, there were
increments and abatements in MFP over the time
of examination, and these progressions can be
partitioned into three sub periods for appraisal: 1)
the sub period of 1987-1995, in which truck MFP
expanded by a normal yearly rate of 2.0%; 2) the
sub period of 1995-2001, in which truck MFP
declined at a normal yearly rate of 0.8%; and 3) the
latestsub period of 2001-2003, in which truck MFP
expanded at a yearly rate of 1.1%.
Further, the factors that influenced changes in the
trucking industry, both in a positive as well as
negative manner include upgrades in the quality of
infrastructure, improvement in Information
Technology, changes in Haul lengths,
containerization.
4.1. UPGRADES IN THE QUALITY OF
INFRASTRUCTURE
The period following the deregulation witnessed a
significant increase in the quality of infrastructure
in the trucking industry. This infrastructure
included buildings, equipment(s), trucks,
information systems, etc. Post deregulation, i.e.
once the various restrictions on trucking trade
were lifted, trucking companies began investing in
improvement and/or replacement of existing
infrastructure with more sophisticated and
efficient counterparts in an attempt to increase
overall productivity. In discussing this further, the
upgrades in infrastructure will be analyzed in
terms of the total capital input and the capital per
worker in order to better understand the influence
of these upgrades on the productivity of trucking
firms.
CHAPTER 4: FACTORS CAUSING PRODUCTIVITY
VARIATION IN TRUCKING INDUSTRY

18. 18
Table 4.1. presents data in terms of Capital and
Capital per worker for the time period 1987 up to
2003. According to this data provided by the
Bureau of Transportation Statistics, the capital
input amid the period of analysis (1987-2003)
increased by 43.4%. This percentage when
attributed to each year of analysis sums down to
an annual capital growth rate of roughly 2.3%. In
terms of Capital per worker, this growth
percentage is calculated to be roughly around
20.6% for the same period, and so, the annual
capital per worker growth rate for this time period
comes down to 1.2%. To get clarity on the time
periods that involved the maximum capital
contribution, we divide the period from 1987 to
2003 into three sub-periods i.e. 1987-1995, 1995-
2001 and 2001-2003. Further, calculating the
capital input and capital per worker for each of
these sub-periods we get the following statistics:
As seen from the table, growth in Capital was
+2.4% from 1987-1995, +3.7% from 1995-2001,
and -2.2% from 2001-2003. This illustrates that a
majority of improvements in infrastructure took
place in the period 1995-2001.
Table 4.1.: Growth in Capital and Capital Per worker, 1987 – 2003. Source: Bureau of Transportation Statistics
Table 4.2. Sub-period Growth in Capital and Capital Per
worker, 1987 – 2003. Source: Bureau of Transportation
Statistics

19. 19
However, this growth in capital did not translate
to an equivalent growth in MFP during the same
time period. In fact, Multi-Factor Productivity saw
a decline in this period. This anomaly was
observed in the sub-period of 2001-2003 as well
wherein though the growth in capital was
significantly negative, and the growth in capital
per worker was also stalled, the MFP during this
period showed an increase. To understand the
cause of these anomalies, one needs to consider
external factors that may have had an impact on
the MFP during these sub-periods. Table 4.3
underlines these external factors and their
individual significance on the respective time
periods.
4.2. IMPROVEMENT IN INFORMATION
TECHNOLOGY
A major contributor in the improvement in
trucking productivity is technology. Post
deregulation, the trucking industry witnessed
major technological advances which included use
of on-board computers, software, satellite
communications and the internet.
On-board Computers are of two types: Truck-
based or Handheld. The main feature of these
computers is that they provide real-time
information about trucking operations and
performance via sensors fitted in appropriate
locations within the truck. These computers can be
used for a variety of purposes including analyzing
Table 4.3. Factors affecting MFP growth in different sub-periods. Source: Bureau of Transportation Statistics

20. 20
truck performance, obtaining driver hours of
service, truck speed and location, fuel
consumption patterns, etc. All these help a
trucking company’s management to better
understand the operating of their trucks and thus,
implement changes or rectifications to make the
operations more efficient and productive.
Apart from improving productivity through a
detailed tracking and monitoring system, these
On-Board Computers also aid in increasing
productivity by:
 Improving Business Transactions: with
continuous tracking and proof of delivery
features, the interests of the trucking
company are safeguarded in cases wherein
the customer may falsely claim of
maleficent activities directed towards the
company.
 Computer-Aided Routing (CAR) and
Dispatching (CAD): These technologies
enable the company to optimize truck
routes for quicker dispatch from
warehouse and faster delivery. These
systems are helpful in strategizing driving
hours, size and quantity of shipment, haul
routes, and in some cases, even deciding
up on implementing TL or LTL operations.
All this eventually helps the company
minimize the time and cost of moving
freight.
 Truck Maintenance: With the
advancement in technology, improved
hardware and software were available that
could accurately monitor the truck
performance thereby enabling the trucking
companies to perform servicing and
maintenance jobs on-time. This greatly
reduced the probability of in-field
breakdowns and also increased the life of
the trucks, which eventually improved the
performance of the trucks and the
productivity of the company.
4.3. LENGTH OF HAUL
With improvements in technology and strategic
planning, the functioning of trucks improved
significantly on account of proper and timely
maintenance. The trucks could now perform
better in terms of distance travelled as well as fuel
savings. This allowed trucking companies to
increase the length of hauls so as to transport
more freight. Increase in the number of shipments
and the distance between the origin and
destination, the companies could now transport
more freight at a quicker and more cost-efficient

21. 21
pace. Table 4.4 illustrates the average length of
haul (ALOH) of trucks.
As seen from the table, from 1985 onwards, the
average length of haul increased constantly till
2001 with minor setbacks in the years 1993 and
1994.
In terms of statistics, the sub-period of 1995-2001
witnessed the maximum rate of increase in
average length of haul i.e. around 2.6% annually
compared to the annual rate of 1.6% in the sub-
period of 1985-1995.
4.4. CONTAINERIZATION
Containerization refers to using large containers
for freight transportation rather than smaller
units. Containers are considered as a part of the
capital input in the truck freight transportation
industry. This is because containers are an
improvement to the earlier used small boxes for
storing commodities. With the introduction of
containers, the use of small individual boxes faded
away quicker as these containers required lesser
manual handling and could be lifted through
cranes or forklifts. This gave rise to an increased
use of automation to dispatch and store these
containers, and made the loading and unloading
process significantly less timing consuming. The
introduction of automated processes influenced
the MFP of the trucking industry positively as it
significantly reduced the labor requirement and
also,the time required to handle the commodities.
Table4.5 shows the number of containers used per
year in the period from 1990-2004. As seen from
the table, the number of containers used
increased constantly without any anomaly in trend
witnessed in this period.
The use of containers further helped utilize the
available resources more efficiently i.e. the truck
space could now be used
to transport greater
amount of freight than
what was possible whilst
using small boxes. Thus, in
totality, containerization
helped improve the
productivity significantly.
Table 4.5. Number of
containers used (1990-
2004)
Source: AAR “Railroad
Facts.” 2005 Edition
Table 4.4.
Average
Length of Haul
(1985-2001)
Source: AAR
“Railroad
Facts.” 2005
Edition

22. 22
This trucking Industry dominates the freight transportation industry today with almost 50% of the total
freight transported via trucks, either directly, or indirectly. This dominance was brought about post the
passage of Deregulation Acts which greatly reduced the earlier held restrictions on trucking operations.
Post 1980, the trucking industry has come a long way in almost every aspect of its operations.
First, the Deregulation brought with it bifurcation in the Industry and Emergence of New Entrants that
deeply affected the financial condition of the industry. Though at first it seemed disastrous for existing
companies, once the companies adapted to this change by altering their strategy of operations, the
overall amount of shipments via trucks grew exponentially. So, even though the deregulation may have
been bad news for some companies which had to eventually shut down, in totality, it proved to be a
boom for the trucking industry in general.
Secondly, the deregulation brought with it the urgent need for companies to make improvements in
their operating process in order to survive. With the rapid influx of new entrants, pricing and efficiency
became the core competencies that got a company orders. For this, the trucking companies introduced
a variety of strategic changes to ultimately increase productivity. These steps taken by the companies
greatly aided the company in not just increasing their clientele, but also save capital by reforming to
more efficient and productive operating processes.
Lastly, as stated in this paper, the productivity of all sectors of business improved post deregulation.
Some critics argue that deregulation isn’t the source of this change, and that with advancements in
technology and operations, these changes were bound to happen. I personally feel that even though this
may be correct to some extent, but the deregulation acts definitely acted as a catalyst to fast-track the
rate of productivity growth in the trucking industry.
CHAPTER 5: CONCLUSION

23. 23
REFERENCES:
 Productivity and Competition in the U.S. trucking Industry since Deregulation, Veiko Paul
Parming, University of Toronto, 2011
 Economic Deregulation of the Trucking Industry, Economic Policy Institute, Belzer, M
 Factors affecting Multifactor Productivity in Freight Transportation, Bureau of Transportation
Statistics
 A decade of Growth in Domestic Freight, Bureau of Transportation Statistics (2007),
 The Measurement of Supply and Demand in Freight Transportation, Bayliss, B. (1988)
 American Trucking Association, American Trucking Trends