Trucking Industry Response in a Changing World of Tolling and Rising Fuel Prices

Direct user fees based options are gaining further momentum all across the United States and particularly in the state of Texas. The success of such ventures or projects requires a clear assessment of demand for toll roads among the potential user groups. However, there is too little information about the trucking industry as far as its attitude towards toll roads is concerned. This lack of attention to response patterns can lead to optimism bias in truck toll forecasts. Through literature reviews, Texas specific focus groups, and surveys this study aims to establish the range in demand variation and route preferences for tolled roads across various segments of the trucking community. Fuel prices are found to influence route choices and consequently toll road revenue forecasts. In addition to fuel costs, the other trade-offs that emanate from this study include cargo characteristics, haul characteristics, etc. Therefore a better understanding of the demand structure of the trucking firms requires all the relevant trade-offs be taken into consideration.

[1]  R. Bain,et al.  Traffic forecasting risk: study update 2004 , 2004 .

[2]  N. V. Zyl,et al.  In Search of the Value of Time: From South Africa to India , 2006 .

[3]  D. Lee Demand Elasticities for Highway Travel , 2000 .

[4]  W G Adkins,et al.  VALUES OF TIME SAVINGS OF COMMERCIAL VEHICLES , 1967 .

[5]  Clifford Winston,et al.  U.S. Industry Adjustment to Economic Deregulation , 1998 .

[6]  David M Levinson,et al.  Operating Costs for Trucks , 2005 .

[7]  Leah Newman Macroergonomic Methods: Interviews and Focus Groups , 2002 .

[8]  Gary Barnes,et al.  Per Mile Costs of Operating Automobiles and Trucks , 2004 .

[9]  Terry Williams,et al.  Practical Use of Distributions in Network Analysis , 1992 .

[10]  Gerard de Jong,et al.  Value of Freight Travel-Time Savings , 2007 .

[11]  A. Reggiani,et al.  Meta-Analysis and the Value of Travel Time Savings: A Transatlantic Perspective in Passenger Transport , 2007 .

[12]  D. Hensher How do respondents process stated choice experiments? Attribute consideration under varying information load , 2006 .

[13]  P. Goodwin A REVIEW OF NEW DEMAND ELASTICITIES WITH SPECIAL REFERENCE TO SHORT AND LONG RUN EFFECTS OF PRICE CHANGES , 1992 .

[14]  H. Williams,et al.  Behavioural theories of dispersion and the mis-specification of travel demand models☆ , 1982 .

[15]  David A. Hensher,et al.  USING VALUES OF TRAVEL TIME SAVINGS FOR TOLL ROADS: AVOIDING SOME COMMON ERRORS , 2004 .

[16]  Phil. Goodwin,et al.  Empirical evidence on induced traffic , 1996 .

[17]  B. Silverman,et al.  Why Aren't All Truck Drivers Owner-Operators? Asset Ownership and the Employment Relation in Interstate For-Hire Trucking , 2003 .

[18]  Peter Bonsall EXPERIMENTS TO DETERMINE DRIVERS' RESPONSE TO ROAD USER CHARGES , 1998 .

[19]  Atreya Chakraborty,et al.  Product Differentiation and the Use of Information Technology : New Evidence from the Trucking Industry , 1999 .

[20]  J. Maule,et al.  Responses to complex pricing signals: Theory, evidence and implications for road pricing , 2007 .

[21]  Amelia C. Regan,et al.  Impacts of highway congestion on freight operations: perceptions of trucking industry managers , 1999 .

[22]  Michael D Meyer,et al.  Feasibility of Truck-Only Toll Lane Network in Atlanta, Georgia , 2006 .

[23]  Sergio J Ostria Evaluation of U.S. Commercial Motor Carrier Industry Challenges and Opportunities , 2003 .

[24]  R Bain,et al.  Traffic forecasting risk study update 2005: through ramp-up and beyond , 2005 .

[25]  K. Eisenhardt Building theories from case study research , 1989, STUDI ORGANIZZATIVI.

[26]  K. Kawamura,et al.  Commercial Vehicle Value of Time and Perceived Benefit of Congestion Pricing , 1999 .

[27]  I. Dey Qualitative Data Analysis: A User Friendly Guide for Social Scientists , 1993 .

[28]  José Holguín-Veras,et al.  Economic and Financial Feasibility of Truck Toll Lanes , 2003 .

[29]  Alain L. Kornhauser,et al.  Analysis of Route Choice Decisions by Long-Haul Truck Drivers , 2005 .