The market potential for plug-in hybrid and battery electric vehicles in Flanders: A choice-based conjoint analysis

Transportation Research Part D: Transport and Environment

Volumn 17, Issue 8, 2012, Pages 592-597

  Lebeau, Kenneth ^a   Van Mierlo, Joeri ^a   Lebeau, Philippe ^a   Mairesse, Olivier ^a   Macharis, Cathy ^a  

^a VRIJE UNIVERSITEIT BRUSSEL   (Belgium)

Author keywords

Battery electric vehicles; Electric vehicles; Plug in hybrid electric vehicles

Indexed keywords

BATTERY ELECTRIC VEHICLES; COMMERCE; COMPETITION; ELECTRIC BATTERIES; ELECTRIC VEHICLES; HYBRID VEHICLES; SECONDARY BATTERIES; VEHICLES;

CHOICE-BASED CONJOINT; FLANDERS; LARGE SCALE SURVEYS; MARKET POTENTIAL; MARKET SHARE; PLUG IN HYBRID ELECTRIC VEHICLES; PLUG-IN HYBRIDS; PURCHASE COST;

PLUG-IN HYBRID VEHICLES;

COST; ELECTRIC VEHICLE; MARKET CONDITIONS; SURVEY METHOD;

BELGIUM; FLANDERS;

EID: 84865769611     PISSN: 13619209     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trd.2012.07.004     Document Type: Article

References (17)

1. Achtnicht, M., Bühler, G., Hermeling, C., 2008. Impact of Service Station Networks on Purchase Decisions of Alternative-fuel Vehicles. Discussion Paper No. 08-088. Center for European Economic Research.
2. Brownstone D., Bunch D., Train K. Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles. Transportation Research Part B 2000, 34:315-338.
3. Bunch D., Bradley M., Golob T., Kitamura R., Occhiuzzo G. Demand for clean-fuel vehicles in California: a discrete-choice stated preference pilot project. Transportation Research Part A 1993, 27:237-253.
4. Chakraborty G., Ball D., Gaeth G., Jun S. The ability of ratings and choice conjoint to predict market shares: a Monte Carlo simulation. Journal of Business Research 2002, 55:237-249.
5. Ewing G., Sarigöllü E. Car fuel-type choice under travel demand management and economic incentives. Transportation Research Part D 1998, 3:429-444.
6. FEBIAC, 2011. Inschrijvingen van nieuwe wagens per brandstofsoort. (accessed on 06/07.12). http://www.febiac.be/public/statistics.aspx?FID=23andlang=NL.
7. Gelman A., Carlin J., Stern H., Rubin D. Bayesian Data Analysis 2009, Chapman and Hall, London. second ed.
8. Green P., Krieger A., Wind Y. Thirty years of conjoint analysis: reflections and prospects. Interfaces 2001, 31:56-73.
9. Hair J., Black W., Babin B., Anderson R. Multivariate Data Analysis: A Global Perspective 2010, Pearson, New Jersey.
10. Hidrue M., Parsons G., Kempton W., Gardner M. Willingness to pay for electric vehicles and their attributes. Resource and Energy Economics 2011, 33:686-705.
11. Horne M., Jaccard M., Tiedemann K. Improving behavioral realism in hybrid energy-economy models using discrete choice studies of personal transportation decisions. Energy Economics 2005, 27:59-77.
12. Johnson R. The CBC System for Choice-based Conjoint Analysis. Sawtooth Software 1994, Sawtooth Software, Inc., Sequim.
13. Johnson R., Orme B. Sawtooth Software How Many Questions Should You Ask in Choice-Based Conjoint Studies? 2002, Sawtooth Software, Inc., Sequim.
14. Lancaster K.J. A new approach to consumer theory. Journal of Political Economy 1966, 74:132-157.
15. Orme B. Getting Started With Conjoint Analysis: Strategies for Product Design and Pricing Research 2009, Research Publishers, Madison.
16. Potoglou D., Kanaroglou P. An Internet-based stated choices household survey for alternative fuelled vehicles. Canadian Journal of Transportation 2007, 1:36-55.
17. Wellman G., Vidican C. Pilot study of a hierarchical Bayes method for utility estimation in a choice-based conjoint analysis of prescription benefit plans including medication therapy management services. Research in Social and Administrative Pharmacy 2008, 4:218-230.