Fostering the adoption of electric vehicles by providing complementary mobility services: a two-step approach using Best–Worst Scaling and Dual Response

AbstractThere is a substantial gap in research regarding the adoption of electric vehicles as a strategy to remedy the climate problem and reduce oil consumption by integrating complementary mobility services. To address this gap, we employ a two-step approach utilizing a hybrid stated preference method. Study 1 uses Best–Worst Scaling and identifies the top three complementary mobility services consumers would prefer with an electric vehicle. Study 2 applies Dual Response and analyzes the importance of these three services relative to other technological and economic factors of electric vehicles. Our results offer evidence that complementary mobility services may significantly foster electric vehicle adoption . Moreover, low purchase prices are less important than low recurring costs, such as electricity costs. Finally, a segmentation strategy may be fruitful because, e.g., men are more attracted by technological advantages than women and elderly consumers have a higher preference for services that offer convenience.

[1]  Ryuichi Kitamura,et al.  Demand for clean-fuel vehicles in California: A discrete-choice stated preference pilot project , 1993 .

[2]  Pavlos S. Kanaroglou,et al.  Household demand and willingness to pay for clean vehicles , 2007 .

[3]  Jordan J. Louviere,et al.  An introduction to the application of (case 1) best–worst scaling in marketing research , 2013 .

[4]  Marko P. Hekkert,et al.  Business strategies of incumbents in the market for electric vehicles: opportunities and incentives for sustainable innovation , 2015 .

[5]  Chee Wei Tan,et al.  A review of energy sources and energy management system in electric vehicles , 2013 .

[6]  Jerry A. Hausman,et al.  Assessing the potential demand for electric cars , 1981 .

[7]  Attentional Contrast during Sequential Judgments: A Source of the Number-of-Levels Effect , 2008 .

[8]  Christian Schlereth,et al.  DISE: Dynamic Intelligent Survey Engine , 2012 .

[9]  J. Thøgersen,et al.  Marketing of electric vehicles , 1999 .

[10]  Peter Palensky,et al.  Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads , 2011, IEEE Transactions on Industrial Informatics.

[11]  Deborah J. Street,et al.  The Construction of Optimal Stated Choice Experiments , 2007 .

[12]  D. Street,et al.  The Construction of Optimal Stated Choice Experiments: Theory and Methods by STREET, D. J. and BURGESS, L. , 2007 .

[13]  Willett Kempton,et al.  Vehicle-to-grid power fundamentals: Calculating capacity and net revenue , 2005 .

[14]  S. Mühlmeier,et al.  Who will buy electric cars? An empirical study in Germany , 2011 .

[15]  Reinhard Madlener,et al.  Consumer Preferences for Alternative Fuel Vehicles: A Discrete Choice Analysis , 2012 .

[16]  Aftabuzzaman,et al.  Achieving sustainable urban transport mobility in post peak oil era , 2011 .

[17]  D. McFadden Disaggregate Behavioral Travel Demand's RUM Side A 30-Year Retrospective , 2000 .

[18]  David A. Hensher,et al.  Travel behaviour research : the leading edge , 2001 .

[19]  Joffre Swait,et al.  Enriching Scanner Panel Models with Choice Experiments , 2003 .

[20]  Betriebsformen im Automobilhandel – Resultate einer empirischen Untersuchung , 2011 .

[21]  L. Thurstone A law of comparative judgment. , 1994 .

[22]  J. Lee,et al.  The Best–Worst Scaling Approach: An Alternative to Schwartz's Values Survey , 2008, Journal of personality assessment.

[23]  P. Green,et al.  Thirty Years of Conjoint Analysis: Reflections and Prospects , 2001 .

[24]  Vithala R. Rao,et al.  Applied Conjoint Analysis , 2014 .

[25]  Oliver Hinz,et al.  New product adoption in social networks: Why direction matters , 2014 .

[26]  Eric J. Johnson,et al.  A componential analysis of cognitive effort in choice , 1990 .

[27]  J. Louviere,et al.  Probabilistic models of set-dependent and attribute-level best-worst choice , 2008 .

[28]  G. Ewing,et al.  Car fuel-type choice under travel demand management and economic incentives , 1998 .

[29]  B. Skiera,et al.  Measuring Consumers' Preferences for Metered Pricing of Services , 2011 .

[30]  J. Louviere,et al.  Discrete Choice Experiments Are Not Conjoint Analysis , 2010 .

[31]  D McFadden DISAGGREGATE BEHAVIOURAL TRAVEL DEMAND'S RUM SIDE - A 30 YEAR RETROSPECTIVE. IN: TRAVEL BEHAVIOUR RESEARCH. THE LEADING EDGE , 2001 .

[32]  K. Train,et al.  Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles , 1999, Controlling Automobile Air Pollution.

[33]  Meryl P. Gardner,et al.  Willingness to pay for electric vehicles and their attributes , 2011 .

[34]  Christopher D. Wickens,et al.  Costs and Benefits of Head-Up Display Use: A Meta-Analytic Approach , 1998 .

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

[36]  R. Cooper,et al.  New Products: What Separates Winners from Losers? , 1987 .

[37]  J. Louviere,et al.  Determining the Appropriate Response to Evidence of Public Concern: The Case of Food Safety , 1992 .

[38]  K. Train Discrete Choice Methods with Simulation , 2003 .

[39]  William L. Moore,et al.  The no-choice option and dual response choice designs , 2006 .

[40]  Larry Lockshin,et al.  Testing the Robustness of Best Worst Scaling for Cross-National Segmentation with Different Numbers of Choice Sets , 2013 .

[41]  Mark Jaccard,et al.  The ‘neighbor effect’: Simulating dynamics in consumer preferences for new vehicle technologies , 2008 .

[42]  Christian Schlereth,et al.  Measurement of preferences with self-explicated approaches: A classification and merge of trade-off- and non-trade-off-based evaluation types , 2014, Eur. J. Oper. Res..

[43]  Jonn Axsen,et al.  Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles , 2009 .

[44]  A. Herrmann,et al.  Die Wirkung von Brand Communities auf die Markenloyalität — eine dynamische Analyse im Automobilmarkt , 2006 .

[45]  G. Ewing,et al.  Assessing Consumer Preferences for Clean-Fuel Vehicles: A Discrete Choice Experiment , 2000 .

[46]  P. Kotler,et al.  Principles of Marketing , 1983 .

[47]  John K. Dagsvik,et al.  Potential demand for alternative fuel vehicles , 2002 .

[48]  R. Dhar,et al.  The Effect of Forced Choice on Choice , 2003 .

[49]  Simon Shepherd,et al.  Factors affecting future demand for electric vehicles: A model based study , 2012 .