Quantifying Consumers' Willingness to Pay for Electric Vehicle Charging

Poor availability of a nationwide, publicly accessible charging infrastructure in Europe is seen as a major impediment for a stronger market penetration of electric vehicles (EVs). Making privately owned charging points for electric vehicles accessible to the public in a Peer-to-Peer (P2P) charging network may present a remedy to this problem. Developing such a P2P service, among others, requires knowledge on the customers' willingness to pay for EV charging. We survey customers of a utility company in a mid-sized European city to assess their willingness to pay for EV charging. Using choice-based conjoint analysis, we obtain customers' willingness to pay differentiated by charging point's characteristics and its location. The estimates are subsequently implemented in form of price recommendations into an actual web-based P2P platform that enables private individuals to provide and access EV charging services. This research contributes to the knowledge on the design of payment models in general and on the design of EV charging infrastructure services in particular. Poor availability of a nationwide, publicly accessible charging infrastructure in Europe is seen as a major impediment for a stronger market penetration of electric vehicles (EVs). Making privately owned charging points for electric vehicles accessible to the public in a Peer-to-Peer (P2P) charging network may present a remedy to this problem. Developing such a P2P service, among others, requires knowledge on the customers' willingness to pay for EV charging. We survey customers of a utility company in a mid-sized European city to assess their willingness to pay for EV charging. Using choice-based conjoint analysis, we obtain customers' willingness to pay differentiated by charging point's characteristics and its location. The estimates are subsequently implemented in form of price recommendations into an actual web-based P2P platform that enables private individuals to provide and access EV charging services. This research contributes to the knowledge on the design of payment models in general and on the design of EV charging infrastructure services in particular.

[1]  Paul E. Green,et al.  Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice , 1990 .

[2]  Chunyan Miao,et al.  Optimal Pricing for Efficient Electric Vehicle Charging Station Management , 2016, AAMAS.

[3]  V. Kumar,et al.  Attribute order and product familiarity effects in decision tasks using conjoint analysis , 1991 .

[4]  Thomas Bräunl,et al.  Electric vehicle battery charging behaviour: findings from a driver survey , 2013 .

[5]  Anil Namdeo,et al.  Spatial planning of public charging points using multi-dimensional analysis of early adopters of electric vehicles for a city region , 2014 .

[6]  Aleda V. Roth,et al.  New service development competence in retail banking: Construct development and measurement validation , 2007 .

[7]  Wolf Fichtner,et al.  Optimizing the allocation of fast charging infrastructure along the German autobahn , 2016 .

[8]  C. Perry,et al.  A customer‐oriented new service development process , 2002 .

[9]  Thomas H. Bradley,et al.  Design, demonstrations and sustainability impact assessments for plug-in hybrid electric vehicles , 2009 .

[10]  Mohan V. Tatikonda,et al.  New service development: areas for exploitation and exploration , 2002 .

[11]  Bryan K. Orme Sawtooth Software RESEARCH PAPER SERIES sing the Monetary Value of ttribute Levels with Conjoint Analysis : Warnings and Suggestions , 2001 .

[12]  Patrick Jochem,et al.  Willingness to Pay for E-Mobility Services : A Case Study from Germany , 2016 .

[13]  Johan Jansson,et al.  Advances in consumer electric vehicle adoption research: A review and research agenda , 2015 .

[14]  M. Hidrue,et al.  Is there a near-term market for vehicle-to-grid electric vehicles? , 2015 .

[15]  Eugene M. Johnson,et al.  A Proposed Model for New Service Development , 1989 .

[16]  Steven H. Cohen,et al.  Market segmentation with choice-based conjoint analysis , 1995 .

[17]  Robert Shorten,et al.  Alleviating a form of electric vehicle range anxiety through on-demand vehicle access , 2013, Int. J. Control.

[18]  M. Wedel,et al.  The No—Choice Alternative in Conjoint Choice Experiments , 2001 .

[19]  G. Venekamp,et al.  Dynamic pricing by scalable energy management systems — Field experiences and simulation results using PowerMatcher , 2012, 2012 IEEE Power and Energy Society General Meeting.

[20]  Mary Jo Bitner,et al.  Services Marketing: Integrating Customer Focus Across the Firm , 1996 .

[21]  Jordan J. Louviere,et al.  Design and Analysis of Simulated Consumer Choice or Allocation Experiments: An Approach Based on Aggregate Data , 1983 .

[22]  P. Green,et al.  Conjoint Analysis in Consumer Research: Issues and Outlook , 1978 .

[23]  Barbara Lenz,et al.  Mobilität in Deutschland 2008 , 2010 .

[24]  Kenneth Lebeau,et al.  Consumer attitudes towards battery electric vehicles: a large-scale survey , 2013 .

[25]  J. Spohrer,et al.  Marketing: a service science and arts perspective , 2014 .

[26]  I. Neumann,et al.  Experiencing Range in an Electric Vehicle: Understanding Psychological Barriers , 2012 .

[27]  Colin C.J. Cheng,et al.  Market‐creating service innovation: verification and its associations with new service development and customer involvement , 2012 .

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

[29]  S. Wooding,et al.  Bringing the electric vehicle to the mass market , 2012 .

[30]  Harley Krohmer,et al.  Measuring Consumers’ Willingness to Pay. Which Method Fits Best? , 2012 .

[31]  Anibal T. de Almeida,et al.  Impact of the electricity mix and use profile in the life-cycle assessment of electric vehicles , 2013 .

[32]  Elisabetta Cherchi,et al.  A long panel survey to elicit variation in preferences and attitudes in the choice of electric vehicles , 2014 .

[33]  Ralf Philipsen,et al.  Fast-charging station here, please! User criteria for electric vehicle fast-charging locations , 2016 .

[34]  Simon S. K. Lam,et al.  Is Customer Participation in Value Creation a Double-Edged Sword? Evidence from Professional Financial Services across Cultures , 2010 .

[35]  A. Menegaki Valuation for renewable energy: A comparative review , 2008 .

[36]  Zhong Fan,et al.  A Distributed Demand Response Algorithm and Its Application to PHEV Charging in Smart Grids , 2012, IEEE Transactions on Smart Grid.

[37]  R. B. Chase,et al.  A Critical Evaluation of the New Service Development Process: Integrating Service Innovation and Service Design , 2000 .

[38]  B. Nykvist,et al.  Rapidly falling costs of battery packs for electric vehicles , 2015 .

[39]  Oya Ekin Karasan,et al.  A Benders decomposition approach for the charging station location problem with plug-in hybrid electric vehicles , 2016 .