An Empirical Study of Alternative Fuel Vehicle Choice by Commercial Fleets: Lessons in Transportation Choices, and Public Agencies' Organization

The concern about air pollution has led government agencies to design and implement mandates to replace some commercial fleets’ gasoline vehicles with Alternative Fuel Vehicles (AFVs). In Part One of this dissertation, I investigate the diffusion of AFV’s in the commercial sector. Commercial fleets are frequently the first target of government regulation because policy agencies can target a large number of vehicles while regulating fewer establishments relative to the household sector. Using stated preference survey data from over 2000 commercial and local government fleets in California, I estimate multinomial logit and nested logit models of fuel choice that predict the probability of choosing each type of AFV. Given certain assumptions about vehicle technology, these models predict that starting in year 2010, almost 17% of new vehicle purchases by the commercial and local government fleets will be electric, about 20% will be compressed natural gas, and almost 21% will be methanol vehicles. I find that fuel choice probabilities differ depending on the market structure. Public agencies seem to be more AFV friendly than private firms. Important factors in fleet vehicle choice are the degree of familiarity of the firm’s staff with the AFV operation, the size of the establishment, government regulations, and the availability of the refueling infrastructure. In Part Two, I review hypotheses about the determinants of local government agencies’ efficiency and use the stated preference survey data to test these hypotheses. Public choice models predict systematic differences among government agencies regarding their cost considerations and sensitivity to environmental issues. The empirical evidence identifies two factors that affect government agencies’ performance. The first factor is jurisdiction: an agency that has a more rigid boundary, such as a city or a county, seems to operate more efficiently than an agency that has more flexible geographic boundaries, as is the case with the special districts. The second factor is direct citizen voting: an agency director who is subject to re-election seems to coordinate a more efficient agency operation than one that is appointed to the job as a career position.

[1]  Timothy H. Hannan,et al.  The Determinants of Technology Adoption: The Case of the Banking Firm , 1984 .

[2]  Camilla Kazimi,et al.  Evaluating the Environmental Impact of Alternative-Fuel Vehicles , 1997 .

[3]  Joseph Farrell,et al.  Choosing How to Compete: Strategies and Tactics in Standardization , 1994 .

[4]  Kenneth A. Small,et al.  EFFICIENT ESTIMATION OF NESTED LOGIT MODELS , 1985 .

[5]  Neil Gandal,et al.  NETWORK EFFECTS, SOFTWARE PROVISION, AND STANDARDIZATION* , 1992 .

[6]  D. McFadden Conditional logit analysis of qualitative choice behavior , 1972 .

[7]  Philip H. Dybvig,et al.  Adoption externalities as public goods , 1983 .

[8]  D. McFadden,et al.  Specification tests for the multinomial logit model , 1984 .

[9]  N. Economides,et al.  COMPETITION AND INTEGRATION AMONG COMPLEMENTS, AND NETWORK MARKET STRUCTURE* , 1992 .

[10]  Ronald N. Johnson,et al.  The Federal civil service system and the problem of bureaucracy , 1994 .

[11]  Thomas F. Golob,et al.  A PERSONAL VEHICLE TRANSACTIONS CHOICE MODEL FOR USE IN FORECASTING DEMAND FOR FUTURE ALTERNATIVE-FUEL VEHICLES , 1994 .

[12]  C. Shapiro,et al.  Technology Adoption in the Presence of Network Externalities , 1986, Journal of Political Economy.

[13]  Charles Wolf,et al.  Markets or governments: Choosing between imperfect alternatives , 1988 .

[14]  R. C. Hill,et al.  The economics of choice in the allocation of Federal grants: An empirical test , 1981 .

[15]  D Shonka Analysis of the NAFA fleet data base: passenger cars only , 1980 .

[16]  Paul Stoneman,et al.  Rank, Stock, Order And Epidemic Effects In The Diffusion Of New Process Technologies : An Empirical Model , 1990 .

[17]  P S Hu,et al.  Fleet vehicles in the Unites States: composition, operating characteristics, and fueling practices , 1992 .

[18]  Manuel Trajtenberg,et al.  The Welfare Analysis of Product Innovations, with an Application to Computed Tomography Scanners , 1989, Journal of Political Economy.

[19]  C. Shapiro,et al.  Systems Competition and Network Effects , 1994 .

[20]  K. Train Qualitative Choice Analysis: Theory, Econometrics, and an Application to Automobile Demand , 1985 .

[21]  Charles M. Tiebout A Pure Theory of Local Expenditures , 1956, Journal of Political Economy.

[22]  Gordon Tullock,et al.  The Politics of Bureaucracy. , 1966 .

[23]  Jennifer F. Reinganum Market Structure and the Diffusion of New Technology , 1981 .

[24]  W. Niskanen Bureaucracy and representative government , 1971 .

[25]  Joseph Farrell,et al.  Standardization, Compatibility, and Innovation , 1985 .

[26]  Ronald S. Warren Bureaucratic performance and budgetary reward , 1975 .

[27]  Jennifer F. Reinganum Technology Adoption Under Imperfect Information , 1983 .

[28]  D. Hill Derived Demand Estimation with Survey Experiments: Commercial Electric Vehicles , 1987 .

[29]  William A. Niskanen,et al.  Bureaucracy and Public Economics , 1994 .

[30]  K. Train A Structured Logit Model of Auto Ownership and Mode Choice , 1980 .

[31]  N. Kiefer Economic Duration Data and Hazard Functions , 1988 .

[32]  Wesley M. Cohen,et al.  Empirical studies of innovation and market structure , 1989 .

[33]  C F Blazek,et al.  Economic analysis of low-pressure natural-gas-vehicle storage technology. Task 3 topical report, March 1989-April 1990 , 1990 .

[34]  Michael H. Riordan,et al.  Regulation and Preemptive Technology Adoption , 1992 .

[35]  Mark R Berg,et al.  THE POTENTIAL MARKET FOR ELECTRIC VEHICLES: RESULTS FROM A NATIONAL SURVEY OF COMMERCIAL FLEET OPERATORS , 1985 .

[36]  Joseph Farrell,et al.  Installed base and compatibility : innovation, product preannouncements and predation , 1986 .

[37]  D. Hensher Stated preference analysis of travel choices: the state of practice , 1994 .

[38]  Hurvey Leibenstein Allocative efficiency vs. X-Efficiency , 1966 .

[39]  Paul Stoneman,et al.  A flexible model of technological diffusion incorporating economic factors with an application to the spread of colour television ownership in the UK , 1992 .

[40]  Thomas J. Lareau THE ECONOMICS OF ALTERNATIVE FUEL USE: SUBSTITUTING METHANOL FOR GASOLINE , 1990 .

[41]  M. J. Moran,et al.  Bureaucratic Discretion or Congressional Control? Regulatory Policymaking by the Federal Trade Commission , 1983, Journal of Political Economy.

[42]  Dennis C. Mueller,et al.  Public Choice II: A Revised Edition of Public Choice , 1989 .

[43]  Jennifer F. Reinganum On the diffusion of new technology: A game theoretic approach , 1981 .

[44]  Nancy Burns,et al.  The Formation of American Local Governments: Private Values in Public Institutions , 1994 .

[45]  Kenneth A. Small,et al.  On the Costs of Air Pollution from Motor Vehicles , 2018, Controlling Automobile Air Pollution.