Positionimz and Communications
`
`[41]
`
`[42]
`
`[43]
`
`Castle Rock Consultants. Heavy Vehicle Electronic License Plate (HELP) Program. Executive
`Summary, April 1989.
`
`Shosharma Zuboff. In the Age of the Smart Machine: The Future of Work and Power. Basic
`Books, New York 1988.
`
`Innovative Computing Corporation. Advertising Material for the Innovative Transuortation
`System.
`
`[44]
`
`Traffie werld, December 3, 1990.
`
`[45]
`
`Traffie Management, August 1988
`
`[46]
`
`Containerization International, September 1990.
`
`[47]
`
`Containerization International, December 1990.
`
`[48]
`
`Amulf Grubler. The Rise and Fall of Infrastructures: Dvnamics of Evolution and Technological
`gghanges in Transportation. Physica-Verlag, Heidelberg 1989.
`
`[49] William L. Garrison. Using Technology to Improve Transportation. Transnortation for the
`Eujme. Springer-Verlag, 1989.
`
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`APPENDIX
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`TOWARD-IVHS ORIENTED MONITORING OF THE TRUCKING INDUSTRY’S
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`ADOPTION AND USE OF POSITION AND COMMUNICATION SYSTEMS
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`The convergence of the trucking industry’s adoption of new technologies to improve services and
`
`productivity with IVHS efforts was discussed in the body of this report. The HELP project represents
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`partial convergence of interests, but possibilities for the convergence of interests may be much greater
`
`than the interests the HELP program is identifying. Patterns of technology adoption and use by trucking
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`firms are beginning to emerge, and steps to explore the possible convergence of trucking and IVHS
`
`interests appear timely.
`
`A first step might be the continued monitoring of the activities of trucking forms, and a review
`
`of the survey undertaken in the research reported here may assist in clarifying the problems to be solved
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`if the development of a monitoring system is undertaken.
`
`Detailed inventories are available of domestic ships, rail locomotives and cars, and aircrafi.
`
`Regulatory agencies maintain extensive data systems on firms and their activities, and agency data are
`
`published by industry associations and/or in trade journals. For instance, the Association of American
`
`Railways publishes ICC data on firms, and Aviation Week and Space Technology publishes data on
`
`airline equipment and firm profitability.
`
`Such extensive and accessible information is not as available on trucks and the trucking industry.
`
`The American Trucking Associations (ATA) publishes ICC data on the finance and operations
`
`characteristics of firms for many of the approximately 40,000 firms regulated by the ICC in its Motor
`
`Vehicle Carrier Annual Report. However, there are between 100,000 and 150,000 owner operators,
`
`about 45,000 private motor carriers, and other operators as well. All trucks used on highways pay
`
`registration and weight fees, and truck registrations by state are reported in the FHWA’s annual Highway
`
`Statistics. Truck inventory and use studies (cited earlier as Reference 4) provide census-type data on the
`
`population of trucks and their major use categories. For example, it reports that the 4.7 million trucks
`
`in California in 1987 undertook 62.5 billion VMT.
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`Although valuable, these and other sources of information are much less rich than sources of
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`information on other modes. Coverage is the main problem as not much data are available cutting across
`
`all activities. Investigations using samples may be used to obtain richer data, but there is the problem
`
`of drawing samples representative of appropriate populations. For instance, one can sample from ICC
`
`regulated firms’, but that might not be the pertinent population for the subject under investigation.
`
`A second problem is targeting appropriate units of observation, and the appropriate unit of
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`observation changes depending on the question. The development of the technology and its marketing
`
`is undertaken by original equipment firms and third party vendors. Decisions about the adoption and use
`
`of technologies are made by trucking firms. The behavior of trucks equipped with communications
`
`technologies may be important for some IVHS purposes. These statements illustrate that the appropriate
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`unit of observation varies, for example, technology suppliers need to be observed to monitor technology
`
`availability and trucks observed to monitor highway use attributes. This issue of the appropriate unit of
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`observation is complicated by the lack of data fully descriptive of populations of firms and vehicles. For
`
`different purposes, different units of observation are needed and data descriptive of populations are
`
`limited.
`
`Finally, the industry is quite heterogeneous. The ATAS’ Report, for example, identifies about
`
`40 types of carriers, from bulk tanks to local household goods carriers.
`
`In many cases, one would not
`
`expect different types of carriers to respond in the same way to a technological option.
`
`Too much should not be made of these aspects of data availability and related problems, for there
`
`are difficulties in any data gathering situation. The researchers were aware of the situation at the
`
`initiation of the research, and the survey undertaken was viewed both as an attempt to develop
`
`information and illuminate the problems of obtaining information.
`
`Turning to the survey activities in this research, the first survey step involved telephone
`
`interviews with equipment suppliers and trucking firms and visits to interview industry informants. These
`
`efforts were not very successful, especially telephoning.
`
`It was necessary to make many call backs,
`
`appropriate informants were difficult to reach, and there was a tendency for the information from
`
`informants to be non comparable from firm to firm. At best, a considerable effort was yielding
`
`interesting information that could not be treated in a systematic way. There was also the issue of the
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`extent that firms contacted were representative of the populations of interest. Interested in decisions about
`
`technology adoption and use, firms known to be interested in new technology were first contacted, and
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`this led to identification of similar firms. To obtain balanced information, some firms known not to be
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`active in technology adoption were contacted (a control group). But it was soon found that most non-
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`adopters had not considered adoption in a systematic way; a few had decisions on hold waiting to see the
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`experiences of others.
`
`Telephone interviewing is a well established information gathering method, and it may well be
`
`usefill if a monitoring system is developed. The experience of these researchers pretty much says
`
`something obvious: telephone sampling will require a good bit of preliminary design and, especially, a
`
`high level of understanding of the populations and the behavior being sampled. Also, it might require
`
`the establishment of a panel through personal contacts in order to assure useful responses to telephone
`
`calls.
`
`As the work was going along the researchers contacted the American Trucking Associations for
`
`information and suggestions. Dr. Russell Capelle, Jr., of the Research and Statistics Division of the
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`Associations provided data on the ICC regulated carriers, as well as providing information from his files
`
`on the technologies available to truckers. Mr. David Willis of the Associations’ Research Foundation
`
`provided information on research he had accomplished, and suggested that the Foundation join us and
`
`execute a mail survey of firms. However, after some joint work on the questions to be asked, the
`
`Foundation decided not to participate in the survey.
`
`(The questionnaire used is attached to this
`
`Appendix.)
`
`A commercial firm that maintains statistics on and a mailing list of trucking firms was contacted
`
`and asked to provide a sample of firms as described in the text of this report. The firm, Transportation
`
`Technical Services, Inc., of Fredericksburg, VA and New York, maintains the National Motor Carrier
`
`Data Base containing 30,055 records on firms that report to the ICC. The last update of the data base
`
`was November 15, 1990. Using the data base mailing list, 1,000 questionnaires were mailed. Usable
`
`returns of 253 questionnaires were received.
`
`Interestingly, about 5 percent of the mailing was returned
`
`by the post office as not deliverable. This may be a comment on the quality of the data base and/or the
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`economic problems and turn over of firms in the industry. Fourteen firms stated that they would like to
`
`have a copy of the results of the survey.
`
`Data were extracted from the returned questionnaires and preliminary analyses made. Because
`
`the survey was intended to provide quantitative information to support the results of the literature and
`
`interview work, final analyses were restricted to topics covered in the body of this report. The
`
`as
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`researchers view the survey as useful, but do not think of it as definitive in any way. One problem is
`
`uncertainty about the relevance of population sampled. Although it certainly included the large firms in
`
`the U.S., the Motor Carrier Data Base contains only about three-fourths of the firms that report to the
`
`ICC, and, as stated, not all firms report to the ICC. Statistical tests for significance were run on some
`
`of the data to assure the validity of impressions given by the data included in the text of the report.
`
`Statistical tests indicate that the cellular and pager systems are being adopted at a greater rate than voice
`
`radio and ordinary telephones, and there is not much difference between the latter.
`
`Perhaps a good way to describe our view of the survey is to say that it was a reconnaissance of
`
`some industry activity, with findings reported that complimented information from other sources. The
`
`approach used in our work is similar to the approach used by some researchers who work on trucking
`
`topics and thus it has general acceptance. For example, Paul R. Murphy, J. E. Smith and J. M. Daley’s
`
`“Ethical Behavior of U. S. General Freight Carriers: An Empirical Assessment” (in The Logistics and
`
`Transportation Review, 27, March 1991) drew its sample from the same date base we used, and then
`
`analyzed the sample results using discriminant functions and t-tests. The difference is only that our
`
`discussion of findings did not extend to reports of tests of significance.
`
`This Appendix will close with comments that might be usefill if filrther investigations are
`
`undertaken.
`
`The first question is what to look for, what is the goal of the work? To paint the situation, topics
`
`mentioned in the text of the report will be mentioned again in a terse fashion.
`
`1. Suppliers are offering" 1,001 technological delights” to the trucking industry. Some
`
`of these are on the drawing board or just entering market niches.
`
`2. Firms are selecting fiom these, as well as new versions of older technologies, in
`
`order to improve productivity and services.
`
`3. Not much attention is being paid to these developments by IVHS programs.
`
`4.
`
`Still, there is the possibility of considerable mutual interest between trucking and
`
`IVHS goals.
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`5. What the truckers do may or may not support these mutual interests. IVHS work
`
`may or may not support mutual interests.
`
`6. So the goal is to understand position and communication technology trends in trucking
`
`from the point of view of IVHS interests.
`
`What makes matters difftcult is this: It is very difftcult to monitor and interpret changes by only
`
`a few firms in a large pool of firms. There is the option of waiting until a trend(s) is well established,
`
`at which time monitoring would be easy. But it may be costly to wait because predominant technologies
`
`may emerge that do not take advantage of the possible mutual interests of IVHS programs and the
`
`trucking industry.
`
`If the decision is made not to wait, here are some options for attempting to monitor the current
`
`and emerging situation:
`
`Surveys of the type undertaken in the current study could be repeated. Because at this time there
`
`are small numbers of new technology adopters, large samples should be taken. Also, because different
`
`types of carriers may have different technology adoption and use patterns, samples should be subdivided
`
`by type of carrier. The disadvantages are the large samples required and the difficulty of sampling fiom
`
`carriers not reporting to the ICC.
`
`Instead of attempting to sample firms, it might be possible to piggy-back questions onto on-going
`
`surveys of drivers. A study published recently illustrates the use of information obtained by contacting
`
`drivers at rest stops and state points of entry (Federal Railroad and Maritime Administrations, Double
`
`Stack Container Systems:
`
`Implications for U.S. Railroads and Ports. 1990). Questions might be
`
`added to efforts to evaluate the HELP program. However, it may be difficult to infer what firms are
`
`doing from driver-obtained information. Also, it may be difficult to judge how well the population
`
`sampled is representative of the industry.
`
`Consideration of the processes of technological change suggests other options. A good bit is
`
`known about the characteristics of innovators and innovative firms and about the diffilsion of new
`
`technologies. Using this information as well as information available from the industry on the activities
`
`of firms, a panel of selected firms might be monitored. Disadvantages are requirements for intensive
`
`interviewing and difficulties in generalizing to the population of all firms.
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`There are some approaches that combine the last suggestion with more traditional and formal
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`survey methods. Panels are often used for monitoring purposes, as well as to anticipate decisions when
`
`new products are offered. Again, there is the disadvantage of resource intensiveness and uncertainties
`
`about what the population of all firms would do.
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