Section 5: Factors Affecting Multifactor Productivity in Trucking

Introduction

Technology and Advances in Technology

Technology is the recipe, the “know-how,” that is used by producers in different industries in order to produce a product or deliver a service. The technology utilized should be the best available technology, in order to produce a product or service at the greatest possible level (and quality), given the available inputs (resources). The production of a product or service at the maximum level (given resources) also implies that it is produced at the lowest possible cost (cost per unit).

The technology of production refers to the mixture, or factor proportions, of the inputs used in production, and the ways (or techniques) by which the inputs are combined—in order to maximize output. For services (as well as for products), the main inputs in production are: labor, capital, land, and intermediate inputs. In practice, there are various types of these main inputs. For example, the capital input includes various type of equipment and structures. The intermediate inputs include purchased materials, services, and energy inputs such as petroleum and electricity.

At a point in time, a firm, or an industry or economy, can maximize its output of a service (or product) by meeting two conditions: 1) full utilization of available resources (labor, capital, land, and intermediate inputs); and 2) by using the best technology that is available for the delivery of a service (or the production of a product). In the case of truck transportation, full utilization of resources means that trucks are full with freight at all times, on originating and return trips. It also means that trucks use roads that minimize any loss of time due to road congestion, construction, or accidents. Full utilization of trucks also implies the minimizing of the out-of-service time of trucks due to maintenance problems. With respect to the second requirement, the use of the best available technology includes the utilization of capital goods (e.g., equipment, machines) that incorporate in them the latest technological advances.This would lead to the highest possible level of output and, consequently, productivity. Capital goods can include equipment such as computers, and software.

When, and if, the level of maximum output is attained, it can only increase further with additional increases in resources (labor, capital, land, and intermediate inputs) and improvements in technology. Either of these two factors require the passage of time. Over time, labor can increase through population growth, which can lead to higher numbers of labor force in the economy. Moreover, man-made capital, such as machines and structures, requires time to be created. In addition, improvements to the technology used in production can entail improvements in the quality of the inputs or by the discovery of new ways of combining the inputs used in the production process. Improvements such as these are typically the result of research and development activity, which requires time as well as expenditures. That activity may take place outside the industry that may eventually be affected. For example, improvements in computers and software can take place in the computer industry; and, subsequently, these improved capital inputs can be used in truck transportation and lead to production increases.

The above effects can be illustrated with a production possibilities frontier, shown in Figure 2. The discussion will use an economy for illustrative purposes; one could substitute an industry or a firm, and the outcomes shown would still apply. Let us assume that an economy uses its resources and makes two outputs: bread and shirts (i.e., food and clothes). The potential levels of these two outputs are shown on the two axes of the diagram.

In that case, the production relationship can be stated as:

Output = depends on (Labor, Capital, Land, Intermediate Inputs), Technology. The meaning of this relationship is that the level of output depends on the amounts of the inputs used in production— i.e., labor, etc.—and the technology used. “Technology” is outside the parenthesis; it is not a physical input like labor and capital, and it can influence the productivity of the physical inputs. Its effects are generally incorporated in the MFP or residual.

The production possibilities frontier (Figure 2) represents the various combinations of the two outputs that would result in the maximum level of (total) output. Point B on the curve shows the maximum output, which is possible when the economy is using its resources fully and utilizing the best available technology. Point A, which is below B, indicates an output level lower than the maximum. That level would be attained if the economy’s resources were not fully utilized. That could be the result if there was unemployed labor or capital in the economy due to an economic recession. That point would also be reached if firms in the economy did not use the best available technology and thus did not maximize their output. That level would also be attained if there were monopolies in the economy that restricted output in maximizing their profits.

In order for the economy to move to a higher production possibilities frontier—i.e., at a higher level of output, indicated by point C—there would be need for time to pass. During this passage of time, it would be possible for resources of the economy to increase. This would include population growth and hence growth in labor. Over time, there could also be an increase in capital—buildings and equipment—and land. Technology could also improve over time through the discovery of new ways of producing raw materials, intermediate inputs or final products/services.

The above discussion can be applied to the trucking industry. In that case, the trucking industry could be thought of as making two types of output—e.g., the delivery of bread and shirts. The analysis would follow the same lines as for the economy. The main point is that for the trucking industry to deliver the greatest level of transportation services, there is need to: 1) employ fully the needed inputs, and 2) use the best available technology. Also, for the level of output of the trucking industry to increase, over time, there would be need to employ more resources and/or improved technology (including a more efficient industry structure).

Factors Affecting Changes in MFP of Truck Transportation

A number of factors can affect changes in multifactor productivity at the industry level. In the case of truck transportation, there were increases and decreases in MFP over the period of analysis, and these changes can be divided into three subperiods for assessment: 1) the subperiod of 1987-1995, during which truck MFP increased by an average annual rate of 2.0%; 2) the subperiod of 1995-2001, during which truck MFP declined at an average annual rate of –0.8%; and 3) the most recent subperiod of 2001-2003, during which truck MFP increased at an annual rate of 1.1%. Thus, the analysis has the challenging task of evaluating the factors that resulted in such a changing pattern of truck MFP.

The factors which have affected changes in truck MFP—in a positive or negative manner— include: 1) Improvements in the quality of capital: computers, software, trucks (information technologies); 2) The efficiency of utilizing intermediate inputs; this includes the fuel efficiency/inefficiency of trucks; 3) Average length of haul; 4) Containerization; and 5) Changes in the structure of the industry—particularly following truck deregulation at the interstate and intrastate levels. The text below examines the effect of these factors over the period of analysis.¹²

1) Improvements in the Quality of Capital

There were improvements, over time, in the quality of capital used in truck transportation. Capital includes buildings, equipment—such as trucks and computers—and software. In truck transportation, there were increases in the capital input over time; and newer capital is typically more efficient than older capital, as it incorporates in it improvements in technology (embodied technical progress).

Table 7 present data on two measurements of the capital input in truck transportation: capital and capital per worker. These factors are assessed for the entire period of analysis (1987-2003) and for the three subperiods—1987-1995, 1995-2001, and 2001-2003. According to these calculations, the capital input increased by 43.4% over the entire 1987-2003 period (column 2). This translates into an average annual growth rate of 2.3%. With respect to subperiods, over 1987-1995, capital used in truck transportation increased by 20.6% or an annual rate of 2.4%. Over the following 1995-2001 subperiod, capital increased by a higher annual rate of 3.7%. Then, during the most recent 2001-2003 subperiod, capital decreased by -2.2% per annum.

With regard to capital per worker, this ratio increased by 20.4% over the period of analysis (column 3), or at an average annual rate of 1.2%. With respect to subperiods, capital per worker increased by 1.7% during the 1987-1995 subperiod; this growth rate declined to 0.9% over the next 1995-2001 period. During the most recent 2001-2003 subperiod, capital per worker did not grow.

The increase in capital per worker during 1987- 1995 would have affected increases in truck MFP through the availability of technological advances incorporated in new capital goods. As new investment takes place in an industry, capital investment of more recent vintage incorporate newer and more efficient technology as compared to capital investment of an older vintage. These technological advances typically contribute positively to multifactor productivity.

During 1995-2001, there was an increase in capital per worker while truck MFP decreased during this period. The decrease can be attributed to the impact of other factors, which are discussed at a later point and are listed in Table 14. In the last subperiod, 2001-2003, capital per worker did not increase while truck MFP increased. In this case, MFP increases were affected by other factors besides technological advances incorporated in capital.

In order to assess more closely the possible sources of technological advances through changes in the capital stock, an assessment is carried out of more detailed types of capital assets. A channel through which technological advances can affect the productivity of truck transportation is through information technologies. This refers to the use of computers and computer software that results in improved delivery of freight. Later text in this section describes the various types of information technology used in trucking over the period of analysis. Consequently, in carrying out the assessment, data were obtained for these two variables in truck transportation, as well as data on capital stock in the form of trucks. These data are presented in Table 8; they are in the form of quantity indexes.

These data show the very rapid increases in the stock of both computers and software used in truck transportation, over the period of analysis. Over time, computers grew more than software. For computers and peripheral equipment, the index increased significantly from 100 in 1987 to 76023 in 2003. For software, the index also increased significantly from 100 in 1987 to 44,232 in 2003. In terms of growth rates, the stock of computers grew at an annual rate of 51.4% over the period of analysis. They increased at a higher annual rate of 82.5% during the first subperiod of 1987-1995. This rate declined to an impressive 30.5% per annum during the second subperiod of 1995-2001. During the most recent 2001-2003 subperiod, computers grew at a still slower rate of 11.8% per annum.

With regard to software, their stock increased steadily and significantly over time, up to 2000; it subsequently declined, but was still maintained at high levels. The pattern for software stock over time is similar to that of computers. During the first subperiod, of 1987-1995, the software stock increased at an annual rate of 93.6%. This was even higher than the rate of increase for computers. However, during the second subperiod, 1995- 2001, software grew at a substantially slower, although still impressive, rate of 15.3%. This rate declined further to –2.2% during 2001-2003.

A very different picture is obtained for the stock of trucks. Light trucks (column 3) increased much slower over the period of analysis than computers or software; they increased by 17.8% over the entire 1987-2003 period. In fact, during the first subperiod (1987-1995), they experienced a decrease—from 100.0 to 91.5, or about -8.5%. In terms of growth rates, light trucks increased at an annual rate of 1.0% over 1987-2003. During the first subperiod (1987-1995), they actually declined by –1.1% per annum; during the next 1995-2003 subperiod, they increased at 5.5% per year, while during the most recent 2001-2003 subperiod, they decreased at –3.5% per year.

The capital stock of “Other trucks, buses, and truck trailers” experienced a decline over the entire 1987-2003 period (from 100.0 to 82.7). In terms of growth rates, during the entire period of analysis, the capital stock of “Other trucks, etc.” decreased at an annual rate of -1.2%. During the first subperiod (1987-1995), their stock increased by 0.4% per annum. However, this changed to an annual decline of –1.5% during the 1995-2001 subperiod; the decline continued at the higher rate of –6.3% during the most recent 2001-2003 subperiod.

In summary, these data indicate the rapid growth, over the period of analysis, of the two IT related capital assets—computers and software. By contrast, the capital stock of trucks either increased very little or declined over the same period. Consequently, changes in technology in computers and software would have been instrumental in affecting increases in truck MFP during 1987-1995. Increases in computers during the most recent 2001-2003 subperiod are also consistent with an increasing truck MFP during that subperiod. Since computers and software were increasing during 1995-2001 while MFP declined, it would appear that other factors contributed to the decreases in truck MFP during the 1995-2001 subperiod. Such factors are examined in other parts of this study.

2) Information Technologies: Hardware, Software, and Communications

Technological advances used in truck transportation include information technologies. These technologies include the use of computers and software as well as various channels of communication such as satellite communications and the internet. These technologies have affected all aspects of truck transportation services, including the operation of the truck, the selection of routes, truck maintenance, and the marketing of truck services. These technologies can be used by themselves or in combination with other IT technologies; the latter framework seems more typical.

The various information technologies that affected motor carrier operations include the following: a) On-board computers (OBC); b) Electronic data interchange (EDI); c) Automatic vehicle location (AVL); d). Satellite communications (SATCOM): e) Computer-aided dispatching (CAD), and Computer aided routing (CAR); f) Truck maintenance; and g) Transactions of truck services (marketing, operations). These technologies and their impact on trucking productivity are discussed below.

On-Board Computers (OBCs)

On-board computers are truck-based or handheld computers, used to obtain information on truck performance. These computers collect and process data received from sensors, and other devices, located on trucks. They keep records of readings and provide the fleet operator with performance information on the trucks and drivers. OBCs can be used as trip recorders and to monitor drivers’ hours of service and vehicle performance measures, such as speed and fuel consumption. OBCs are also used in conjunction with computer-aided routing and dispatching systems and with maintenance-scheduling software. On-board computers also become involved in the Automatic Vehicle Location system, described below.

On-board computers can contribute to increased productivity in the following ways:

Business Transactions. The computer on the truck registers delivery times of freight and customer signatures for proof-of-delivery. This has reduced paperwork and thus labor time to do such paperwork.

Driver Log. With OBC, drivers can input records of hours of service and fuel consumption. Such data make possible an assessment of fuel utilization, leading to truck speeds that minimize the use of fuel. Increased efficiency in the use of fuel, an intermediate input, would increase MFP. A reduction of total intermediate inputs, in relation to output, is not observed in trucking over the period of analysis—except for the last 2 to 3 years. It will be shown that the fuel efficiency in trucking decreased over the period of analysis.

Data Collection on Vehicle Performance. Onboard- computers provide information on various parts of truck performance. These include: engine idling, braking, and patterns of shifting and acceleration. The computer also provides data, from diagnostic systems, on ancillary equipment on the truck such as refrigeration units. Consequently, OBCs allow for remote diagnostics prior to a malfunction of the truck; this can be followed by preventive maintenance. Prompt preventive maintenance and repair improve the performance of trucks and reduce their out-of-service time. This results in higher levels of output and MFP.

Electronic Data Interchange (EDI)

Electronic Data Interchange (EDI) systems include computers and software that are used to send and receive electronic messages and data transmission between computers of two parties. The transmission can occur between trucking companies and shippers (or between any two trading partners). This technology enables the transmission of information, including electronic transactions, between companies in an easier, more accurate, and timely manner. EDI allows for efficient billing and receipt of freight-delivery acknowledgement.

The use of computers for financial transactions reduces paperwork and related labor costs, and thus reduces costs of business transactions. This increase multifactor productivity.

Automatic Vehicle Location (AVL) and Satellite Communications (SATCOM)

Automatic vehicle location (AVL) refers to a broad category of ground-based or satellite technologies, with which it is possible to track the location of trucks. Dispatchers, drivers, shippers, and receivers can track a truck from pickup to delivery of freight; coordinate inter-modal shipments; and perform just-in-time deliveries. In addition to vehicle tracking, SATCOM technologies provide communication between the dispatchers and the truck drivers; this allows for real time coordination of fleet routing and dispatching activities. With an on-board computer, two-way text or voice communications can allow for routing and dispatching of trucks in current time/real time, as well as the (real-time) monitoring of vehicle operating parameters such as speed, etc. With this system, the motor carrier can also locate a truck in case of a breakdown. This results in less out of- service time, and thus higher levels of output (freight delivered) and MFP.

Computer-Aided Routing (CAR) and Dispatching (CAD)

These technologies involve computer hardware and specific software that are used for dispatching, routing, and decision support for route selection of trucks. Good route selection can contribute to minimizing the time and cost of moving freight. These systems are used to schedule drivers and trucks subject to parameters, such as allowable driving hours, size of load, and origin and destination. The basic systems allow for the planning and scheduling of truck activities prior to the dispatch of a truck. In addition, more sophisticated systems allow for routing and dispatch decisions based on real-time truck locations; estimate delivery times and distances; help improve cost estimates; and generate route maps.

The technologies of computer-aided dispatching (CAD) and computer-aided routing (CAR) lead to improved fleet routing and dispatching. This results in an increased utilization of trucks. This includes a reduction in the number, and extent, of empty trucks, particularly on back hauls. This increases trucking output and, consequently, raises truck productivity and MFP.

Computer-aided dispatching and routing provide for improved dispatcher productivity. This technology results in less time needed for truck carriers’ staff to complete routing procedures as compared to previous manual systems. These technologies also improve communication efficiency. With a computerized system, information to drivers can be relayed instantaneously. Consequently, information on a pick-up of freight can be transacted by the truck carrier and the information relayed quickly to an appropriate truck driver, who is close to the freight. This results in increased output (load) for that particular truck, and greater output for the trucking firm—and for the trucking industry.

Truck Maintenance

Technological advances have affected positively truck maintenance through the increased use of maintenance-tracking software (MTS). These software improve the maintenance of trucks by tracking and reordering parts for the repair department of a truck fleet. These software also carry out real-time diagnostics of trucks. As information becomes promptly available on the performance of trucks, maintenance tracking software is used to schedule preventive and emergency repairs, as needed, in the most cost-effective manner. Preventive maintenance reduces maintenance costs as potential problems are repaired before they become bigger and more expensive jobs. This also reduces the out-of-service time of trucks.

Marketing of Truck Services

There has been an increase in the use of computerized systems for the buying and selling of truck transportation services. These include hardware, software, the internet, and satellite communications. The result is higher delivered freight output for the quantity of labor and capital used; this increases production efficiency/MFP.

In summary, information technology contributed to productivity in truck transportation in a number of ways:

On the operations side, computers have been used for communications between the truck carrier and the truck drivers. These communications helped carriers increase vehicle utilization through increased monitoring and reducing unnecessary out-of-route miles by drivers. Information availability on road work or the closing of roads (as a result of accidents) enables the driver to avoid the affected roads and choose other routes. These computers have also been used to schedule trips by trucks, including which freight to deliver and which roads to take. Information technologies would also contribute to lower fuel costs through improved routing. Improved routing would entail the choice of the quickest (and lower cost) route between two points.

On the maintenance side, computers have been used to schedule regular maintenance checks for trucks. Computers have also been used to check for problems developing in trucks. This can prevent a breakdown of a truck on the road with the accompanying negative effects of the truck being out-of-service.

On the administrative side, the use of computers would include personnel transactions and records. Personnel information would relate to the keeping of records for full-time truck drivers and those on a contractual basis. Since the trucking industry has had substantial turnover of drivers, the keeping of correct and updated personnel records would be of particular importance. On the sales side, computers have been used to obtain receipts when the freight is delivered. This entailed electronic transactions and the electronic dissemination of such information. Administrative costs fell as new technologies were adopted that involved paperless transactions.

Finally, it is noted that the data on computers and software would not include information technology equipment utilized on the trucks themselves. The latter would be part of the truck and they would have been included in the measurement of the capital stock for trucks.

3) Intermediate Inputs

An industry’s MFP can also be affected by its efficiency in utilizing intermediate inputs. In examining this point, the ratio was calculated of intermediate inputs to gross output of the trucking industry, and the results are shown in Table 9. These results indicate that in terms of current prices, intermediate inputs accounted for about 50% of gross output over the period of analysis (column 3). Moreover, over time, there was an increase in the ratio of intermediate inputs to gross output. Intermediate inputs were 47% of gross industry output in 1987; in subsequent years, the ratio increased and reached a high of 56% in 2000. However, from 2001 to 2003, the ratio declined (from 55% to 51%).

Since the ratio in current prices could be affected by increases in the relative price of intermediate inputs (including fuel), tabulations were also carried out in quantity terms. These tabulations are in terms of growth rates, and are shown in Table 9, particularly columns 7 and 8. They support the results of calculations in current price.

The growth rates in quantity terms indicate that over the period of analysis, the quantity of intermediate inputs increased faster than output of the trucking industry. This is also observed for the two subperiods of 1987-1995 and 1995- 2001. However, this trend was reversed in 2001, and over the most recent 2001-2003 period, both the quantity of output and intermediate inputs decreases. During that period, intermediate inputs decreased at a substantially faster rate annual rate (-7.3%) than output (-3.9%).

Thus, these numbers, in current dollars and in quantity terms, indicate that there was a decline in the efficiency with which intermediate inputs were utilized in trucking, over 1987-1995 and 1995-2001. However, there was an increase in the efficiency of utilizing intermediate inputs over the most recent period 2001-2003. The decrease in the efficiency of utilizing intermediate inputs, during 1995-2001, was a contributory factor to the declining truck MFP during that period. Also, the efficiency of utilizing intermediate inputs in truck transportation was increasing over the last three years of the period of analysis. This would have contributed to the increasing MFP during those years.

In attempting to explain the decrease in efficiency of utilizing intermediate inputs over most years of the period of analysis, one notes that a major intermediate input in truck transportation is fuel. Therefore, an examination is carried out of fuel efficiency in trucking.

One would expect that improvements in the capital input of truck transportation would include the use of newer trucks that incorporate in them the results of new technologies. These new technologies would include truck engines that are more fuel-efficient than older engines. Improvements in fuel efficiency are expected to result in reduced use of fuels and consequently of intermediate inputs. This would contribute to increased efficiency of the industry in using intermediate inputs, which would have contributed positively to truck MFP.

In evaluating such a possibility, data on fuel efficiency are presented in Table 10 and Table 11. Data in Table 10 are for heavy single-unit trucks; they indicate that there was a rather steady increase in the fuel efficiency of these trucks over the 1987- 2002 period. Their fuel efficiency increased over time from 6.4 miles per gallon (mpg) in 1987 to 7.5 in 2001; it declined slightly to 7.4 mpg in 2002. Calculations with growth rates (in the same table) show a similar development. Fuel efficiency of these trucks increased at an annual rate of 0.8% during 1987-1995; it increased rather substantially at 1.6% per annum during the 1995-2001 subperiod.

Table 11 presents data on the fuel efficiency of combination trucks. These trucks use one or more trailers. Consequently, they would carry greater and heavier freight than single unit trucks. The data presented indicate, for one, that these trucks had lower fuel efficiency than single unit trucks. In 1987, the combination trucks obtained 5.7 miles per gallon compared to 6.4 miles per gallon for the single unit trucks. Moreover, the fuel efficiency of the combination trucks decreased over the period of analysis, from 5.7 mpg in 1987 to 5.2 mpg in 2002. That implies a decline of –0.6% per year. Consequently in 2002, these trucks were even less fuel-efficient (at 5.2 mpg) than in 1987 (5.7 mpg); they were also considerably less fuel-efficient than the single-unit trucks which obtained 7.4 mpg in 2002.

With respect to subperiods, the fuel efficiency of combination trucks increased by 0.2% annually, during 1987-1995. However, during the subsequent subperiod of 1995-2001, their fuel efficiency declined significantly at an annual rate of -1.2%. This decline in fuel efficiency would have contributed to the decline in the efficiency of utilizing intermediate inputs during 1995-2001 (shown in Table 9); it would also have been a contributory factor in the declining truck MFP during 1995-2001.

Moreover, the number of miles traveled by the less fuel-efficient combination trucks have been greater than those traveled by the single-unit trucks, by rather substantial magnitudes (column 2 of Table 10 and Table 11). Consequently, the fuel efficiency of the truck transportation industry, in total, declined over the period of analysis—and particularly over the last several years of the period. A declining fuel efficiency is consistent with, and contributes to, the decrease in the industry’s efficiency in the utilization of intermediate inputs observed previously. This, in turn, is consistent with a declining MFP observed over the 1995- 2001 subperiod.

4) Average Length of Haul

Changes in the average length of haul (ALOH) can affect multifactor productivity in trucking. An increase in the average length of haul—affected by longer truck trips (distance from origin to destination)—can contribute to better fuel efficiency and an improved utilization of other intermediate inputs such as engine oil, etc. This would affect positively the efficiency of utilizing intermediate inputs which, in turn, affects MFP.

It has already been observed that truck transportation experienced a decline in the efficiency of utilizing intermediate inputs, with the exception of the more recent 2001-2003 period. An objective of analyzing the average length of haul will be to assess whether this factor contributed to the decline in fuel efficiency of the industry or whether it served as an offsetting factor to that decline.

Table 12 presents data on the average length of haul (ALOH) of trucks. These numbers indicate that the average length of haul increased over the 1985 to 2001 period. This increase took place steadily over time—so that while in 1985, the ALOH was 589 kilometers, by 1995, it had risen to 669 kilometers. By 2001, it had increased still further to 781 kilometers. In terms of rates of increase, the average length of haul increased faster during the more recent 1995-2001 period (2.6% per year) as compared to the 1985-95 period (1.3% per year).

The data indicate that increases in the average length of haul would have contributed positively to the overall efficiency/MFP of the trucking industry. With regard to subperiods, the increase in the ALOH over 1985-1995 would have contributed to the increase in truck MFP during that time. During the second subperiod, 1995-2001, the ALOH of trucks is shown to have increased while truck MFP declined. During this time, the ALOH acted to offset the negative impact of other factors on the declining truck MFP.

5) Containerization

Containerization refers to the movement of commodities in (large) containers rather than in smaller units. The use of containers in transportation includes rail-truck and truck-water transport, and has become more widespread over time. Within the continental United States, containers are used to transport cargo by truck from a point of origin to a particular destination. They are also used in the intermodal market, which includes the transportation of freight by truck to, and from, a train or a ship. Intermodal firms link different forms of transportation for ultimate delivery to the customer. Containers have become an integral component of intermodal transportation, which has been expanding over time.

Containers are part of the capital input of the truck transportation industry. They represent a technological improvement over previous ways of transporting freight (use of smaller boxes, etc.) and are thus an improvement in the quality of the capital input. The technological advances are incorporated into the capital input. Thus, the impact of the use of containers would be measured in the MFP of the industry.

The use of containers resulted in an increased use of automation in the loading and unloading of trucks. Because commodities are in containers, cargo is moved by crane or forklift; this procedure requires less manual labor than the handling of smaller packages. Consequently, the utilization of this mode of handling freight reduces the time required to transfer cargo; this increases productivity and reduces handling costs. The use of containers also tends to reduce the cost of damage or theft of freight. The benefits of using containers include: reduced employee injuries; reduced damage to the truck; and improvement in loading efficiencies. Thus, containerization contributes to increased productivity/MFP.

In order to examine the impact of this factor, data on containers were collected and tabulated. It is difficult to find a central source of such data with a comprehensive data base, for the years that cover the period of analysis. Consequently, the basic tabulation uses data on containers from the railroads, and these data are supplemented with data from other sources.

Data on containers are presented in Table 13, for the period 1990-2004. They refer to containers used in truck-rail intermodal transportation. These data indicate that the number of containers used increased by 7.8% per annum over the 1990-2003 period. Moreover, the first subperiod, 1990-1995, has the highest annual growth rate, at 10.0%. This subperiod is similar to the initial subperiod for truck MFP (1987-1995). The following subperiod, of 1995-2001, has a substantially lower growth rate for containers, at 6.1% per annum. The most recent subperiod, of 2001-2003, has a growth rate that is higher that the previous subperiod, at 7.6%.

The rates of increase in the number of containers used correspond well to the changes in truck MFP. Truck MFP was increasing during 1987-1995, while the number of containers used increased at the highest rate (over 1990-2003) during 1990- 1995. Truck MFP decreased during the following subperiod, 1995-2001, and the numbers of container used increased at the lowest rate during that subperiod. Finally, truck MFP was increasing again during 2001-2003, and the use of containers was also increasing during that subperiod.

Additional data on containers are presented in two appendix tables. These data are consistent with, and reinforce, the findings based on data in Table 13. First, Appendix J presents data on containers used in waterborne trade of the U.S. That is another segment of the container market and relates to truck-ship (or ship-truck) transportation. Although these data cover fewer years than the rail data, they show similar trends. They indicate that the increase of shipping containers during the most recent subperiod, of 2001-2003, was greater than during the previous subperiod of 1998-2001. One notes that truck MFP increased during 2001- 2003, while it decreased during 1995-2001.

Finally, another set of data are presented in Appendix K. These data refer to containers used in trucks that crossed the border of the United States for Canada or Mexico. These data indicate a rather steady increase in the use of containers over the 1996-2002 period (with a decline in 2003). They also show a pattern similar to that which has been observed. During the most recent 2001-2003 subperiod, the use of containers increased substantially more (at 16.4% annually) than during the previous 1996-2001 subperiod (0.6%). And truck MFP also decreased during 1995-2001, while it increased during 2001-2003.

The data on containers indicate that the use of containers was a factor that affected efficiency in truck delivery and truck MFP. The data indicate high growth of containers use during the 1990- 1995 subperiod (or parts of that period) and during 2001-2003. By contrast, low increases of containers use are observed during the 1995-2001 subperiod. Changes in truck MFP corresponds quite well to changes in containers use: During the 1990 (1987) to 1995 period, and the 2001-2003 period, truck MFP increased; while during 1995- 2001, truck MFP declined.

6) Changes in Industry Structure— Deregulation

The structure of an industry can change over time as a result of deregulation, mergers/acquisitions, and bankruptcies. Such changes can affect efficiency (productivity) in an industry. With respect to mergers, the acquisition of one firm by another implies that the more efficient firm acquires a less efficient firm. In that case, the more efficient firm has typically grown faster (sales), has gained significant amounts of revenues and profits, and is able to secure financial resources. All of these characteristics enable it to acquire another, less efficient firm. Two types of mergers are relevant to the analysis: horizontal and vertical. A horizontal merger combines two firms in the same industry into one firm. Consequently, in the new post-merger firm, there is expected to be merging of certain functions of the two pre-merger firms; these would include finance, payroll, and advertising. These developments result in the same output being produced but with fewer inputs such as labor, equipment, building space, and materials/ services. This results in a reduction in inputs, and thus costs, and an increase in multifactor productivity. Vertical mergers involve mergers of transportation firms that provide complementary services. The provision of complementary services within the same trucking company can increase efficiency.

The structure of the trucking industry changed considerably over the period of analysis—following deregulation at the interstate level in 1980, and at the intrastate level in 1995. The latter completed deregulation in the trucking industry and made it comprehensive. The Motor Carrier Act of 1980 did not affect restrictions on intrastate commerce; and as time passed, the cost of shipping across state borders widened significantly from the cost of shipping within state borders. In 1994, 41 states still maintained some type of economic regulation over intrastate trucking, and intrastate rates were, on the average, 40 percent higher than rates for interstate freight delivery of the same distance.¹³ In 1995 the Interstate Commerce Commission Termination Act was passed and it lifted economic regulation from intrastate trucking.

Deregulation—interstate and intrastate—of the trucking industry resulted in significant changes. There was a notable amount of entry in, as well as exit from, trucking. The entry side included the appearance of new truckload (TL) firms, the expansion of less-than-truckload (LTL) firms into new markets, and the emergence of third parties such as brokers. Truckload carriers were no longer restricted to predetermined routes and commodities; some of them merged and consolidated with others to provide national coverage.

The change in truck transportation from interstate deregulation, and which apparently continued after the intrastate deregulation in 1995, resulted in a decrease in the relative importance of less-than-truckload trucking and a corresponding increase in the relative importance of truckload trucking. Data on shipments, in Appendix L, show that in 1989 and early 1990s, the LTL segment of the trucking industry accounted for 39% of total shipments (LTL and TL). In 1998 and subsequent years up to 2003, the relative importance of the LTL segment decreased to 29% of total industry shipments.

While few carriers specializing solely in LTL trucking were formed since 1980, there was significant geographic expansion by existing LTL firms into each other’s territories, and entry by other carriers, including carriers from other modes (e.g. rail). These new entrants included newly formed subsidiaries of existing LTL firms, and the expanded operations of truckload, small package, package express, and air cargo carriers.¹⁴

A comparison of the status of the 100 largest motor carriers (of property) between 1979 and 1991 shows that¹⁵ : 1) Forty-nine carriers were operating, 37 of which were still among the 100 largest; and 2) Fifty carriers had ceased operations since 1979. At least 35 of these carriers were identified as having filed for bankruptcy.

Structural changes in the trucking industry included trucking companies diversifying out of the traditional LTL market. For example, Roadway Services, Inc. was an LTL firm, and it created a subsidiary (Roberts Transportation Services) that performed almost no standard LTL business. The subsidiary was in the business of handling rush shipments, of rather high value. Much of its revenues came from shipments that were smaller than 10,000 lbs. (i.e., technically LTL), but these shipments were not routed through traditional LTL sort terminals. Rather, most of these shipments were picked up within 90 minutes of a customer request and were dispatched directly to their destination. ¹⁶⁶

During the period of analysis, the LTL segment experienced significant decreases in the number of firms, accompanied by an increase in the size of the average firm. In 1975, this segment consisted of about 528 firms (generating $10.6 billion in revenues). By 1989, the segment had shrunk to 159 firms which had $13.4 billion in revenues; and by the end of 1993, there were only 108 firms, generating $16.7 billion in revenues.¹⁷ These data indicate that over the period 1976-1993, there was a substantial change in the structure of the LTL segment of the industry and, thus, in the entire trucking industry.

After interstate deregulation, the LTL firms experienced mergers and bankruptcies. At the same time, a number of LTL carriers, particularly, smaller ones, were able to succeed. From the largest 50 LTL carriers in 1979, twelve companies survived as of 1994 (controlled by 10 corporate parents). Of the top 50 firms, a number of firms merged with others that later closed, while a number of firms shut down operations. Moreover, more closures occurred to firms that were relatively smaller in the group of the top 50 firms. Conversely, more of the relatively larger firms in the top 50 firms were able to survive in the post-regulatory environment (of interstate deregulation).¹⁸

With respect to bankruptcies, a number of bankruptcies took place in the truck transportation sub-sector. Since efficient companies are expected to survive and grow over time, and inefficient companies are less likely to survive, bankruptcies in truck transportation would tend to result in increased efficiency (productivity) in the industry. It would appear that bankruptcies related, for one, to increased competition from new industry entrants, typically with lower costs, that followed deregulation in 1980 and 1995.

It takes several years for the impacts of deregulation to show in the industry structure and performance. The positive impacts of deregulation would include the expansion of efficient firms in the industry, the entry of new firms that would need to be competitive—i.e., efficient—and the exit of inefficient firms from the industry. It appears that the efficiency of the industry was affected positively by the comprehensive deregulation completed in 1995. It would have taken several years for industry adjustments to take place—through mergers/acquisitions, etc.—that would result in increased efficiency in the trucking industry. It would seem that the impact on higher efficiency began to be shown during 2001-2003, during which period truck MFP was increasing again.

There were adjustments in the industry after the interstate and intrastate deregulation of trucking. These two periods of deregulation were probably a shock to the industry, with existing firms attempting to expand while new firms were attempting to enter the industry. One outcome of the new entrants in the industry was more competition, which eventually resulted in a number of (less efficient) firms leaving the industry. In such circumstances, there is typically need for a period of time to pass, in order for adjustments to take place, before the industry reaches some equilibrium between supply of truck services and demand for truck services (the former being affected by the number and type of firms in the industry). It would seem that industry adjustments had taken place to a sufficient degree by 2001, and production efficiency in the industry subsequently began to increase—as shown by an increase in trucking MFP.

In conclusion, it appears that changes in the structure of the (for-hire) trucking industry, as a result of mergers/acquisitions and bankruptcies, over 1987-2003, resulted, in general, in increases of industry efficiency. This would have affected truck MFP increases, during 1987-1995—after interstate deregulation—and truck MFP increases during 2001-2003, after intrastate deregulation.

¹² Improvements in the labor force could also affect multifactor productivity in the industry. These improvements include the effects of additional training and education of labor. Lack of appropriate data prevent the direct quantification of this factor. Consequently, its impact would be included in the multifactor productivity.

¹³ Federal Highway Administration. “Regulation: From Economic Deregulation to Safety Reregulation,” p. 5.

¹⁴ Interstate Commerce Commission, 1992, p. 38.

¹⁵ Ibid., p. 52.

¹⁶ Ibid., pp. 89-91.

¹⁷ Feitler, Corsi, and Grimm, 1998, p. 5.

¹⁸ Rakowski, 1994.