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Identifying factors influencing the slow market diffusion of electric vehicles in Korea

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Abstract

Electric vehicles (EVs) are considered as a driving force behind the automotive industry’s transformation based on eco-friendliness and high energy efficiency. Unlike expectations, the diffusion of EVs is proceeding at a slow pace in Korea. This study therefore aims to identify the factors influencing the slow market diffusion of EVs from a socio-technical perspective, by comparing the perceptions of the experts and the individuals. We constructed 15 factors in the five dimensions including costs, automobile characteristics, charging conditions, policy instruments, and perceptions for the analytic hierarchy process analysis. Surveys were performed with 58 EV experts and 87 individuals with driver’s licenses in Korea. The results identified and prioritized charging concerns as the highest barrier in both groups, and burden of costs as another critical barrier in the individual group. All factors in charging concerns, burden of initial costs, insufficient performance, and insufficient financial incentives were identified as major influential factors in both groups. While, lack of non-financial supports (for experts), and burden of battery costs and lack of social empathy (for individuals) were ranked as other upper factors. Statistical analysis of the analysis of variance results revealed that the burden of costs was more of a hurdle to the individuals than to the experts. These results suggest implications for policy-making and practice in promoting a widespread EV market.

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References

  • Adepetu, A., Keshav, S.: The relative importance of price and driving range on electric vehicle adoption: Los Angeles case study. Transportation 44(2), 353–373 (2017)

    Google Scholar 

  • Bakker, S., Trip, J.J.: Policy options to support the adoption of electric vehicles in the urban environment. Transp. Res. Part D: Transp. Environ. 25, 18–23 (2013)

    Google Scholar 

  • Beck, M.J., Rose, J.M., Greaves, S.P.: I can’t believe your attitude: a joint estimation of best worst attitudes and electric vehicle choice. Transportation 44(4), 753–772 (2017)

    Google Scholar 

  • Bjerkan, K.Y., Nørbech, T.E., Nordtømme, M.E.: Incentives for promoting battery electric vehicle (BEV) adoption in Norway. Transp. Res. Part D: Transp. Environ. 43, 169–180 (2016)

    Google Scholar 

  • Brudermann, T., Mitterhuber, C., Posch, A.: Agricultural biogas plants-a systematic analysis of strengths, weaknesses, opportunities and threats. Energy Policy 76, 107–111 (2015)

    Google Scholar 

  • Brunelli, M.: Introduction to the Analytic Hierarchy Process. Springer, Berlin (2014)

    Google Scholar 

  • Carley, S., Krause, R.M., Lane, B.W., Graham, J.D.: Intent to purchase a plug-in electric vehicle: a survey of early impressions in large US cites. Transp. Res. Part D: Transp. Environ. 18, 39–45 (2013)

    Google Scholar 

  • Central Intelligence Agency.: The World Fact Book. https://www.cia.gov/library/publications/the-world-factbook/rankorder/2119rank.html (2016). Accessed 1 May 2017

  • Chan, C.C., Wong, Y.S.: Electric vehicles charge forward. IEEE Power Energy Mag. 2(6), 24–33 (2004)

    Google Scholar 

  • Chen, M.K., Wang, S.C.: The critical factors of success for information service industry in developing international market: using analytic hierarchy process (AHP) approach. Exp. Syst. Appl. 37(1), 694–704 (2010)

    Google Scholar 

  • Downey, M.: Selection and adoption of low and zero carbon technologies in social housing: a socio-technical network approach. Doctoral dissertation, University of Reading. (2014)

  • Egbue, O., Long, S.: Barriers to widespread adoption of electric vehicles: an analysis of consumer attitudes and perceptions. Energy Policy 48, 717–729 (2012)

    Google Scholar 

  • Farid, S., Ahmad, R., Niaz, I.A., Arif, M., Shamshirband, S., Khattak, M.D.: Identification and prioritization of critical issues for the promotion of e-learning in Pakistan. Comput. Hum. Behav. 51, 161–171 (2015)

    Google Scholar 

  • Forman, E., Peniwati, K.: Aggregating individual judgments and priorities with the analytic hierarchy process. Eur. J. Oper. Res. 108(1), 165–169 (1998)

    Google Scholar 

  • Franke, T., Neumann, I., Bühler, F., Cocron, P., Krems, J.F.: Experiencing range in an electric vehicle: understanding psychological barriers. Appl. Psychol. 61(3), 368–391 (2012)

    Google Scholar 

  • Haddadian, G., Khodayar, M., Shahidehpour, M.: Accelerating the global adoption of electric vehicles: barriers and drivers. Electr. J. 28(10), 53–68 (2015)

    Google Scholar 

  • Hagman, J., Ritzén, S., Stier, J.J., Susilo, Y.: Total cost of ownership and its potential implications for battery electric vehicle diffusion. Res. Transp. Bus. Manag. 18, 11–17 (2016)

    Google Scholar 

  • Hidrue, M.K., Parsons, G.R., Kempton, W., Gardner, M.P.: Willingness to pay for electric vehicles and their attributes. Resour. Energy Econ. 33(3), 686–705 (2011)

    Google Scholar 

  • Horbach, J., Rammer, C., Rennings, K.: Determinants of eco-innovations by type of environmental impact: the role of regulatory push/pull, technology push and market pull. Ecol. Econ. 78, 112–122 (2012)

    Google Scholar 

  • International Energy Agency.: Global EV Outlook 2016: beyond one million electric cars. https://www.iea.org/publications/freepublications/publication/Global_EV_Outlook_2016.pdf (2016). Accessed 2 Feb 2017

  • International Energy Agency.: Global EV Outlook 2017: beyond one million electric cars. https://www.iea.org/publications/freepublications/publication/GlobalEVOutlook2017.pdf (2017). Accessed 15 Dec 2017

  • International Energy Agency.: Key Trends in CO2 Emissions. http://www.iea.org/statistics/topics/CO2emissions/ (2015). Accessed 1 Mar 2017

  • Javid, R.J., Nejat, A.: A comprehensive model of regional electric vehicle adoption and penetration. Transp. Policy 54, 30–42 (2017)

    Google Scholar 

  • Jensen, A.F., Cherchi, E., Mabit, S.L.: On the stability of preferences and attitudes before and after experiencing an electric vehicle. Transp. Res. Part D: Transp. Environ. 25, 24–32 (2013)

    Google Scholar 

  • Khaligh, A., Li, Z.: Battery, ultracapacitor, fuel cell, and hybrid energy storage systems for electric, hybrid electric, fuel cell, and plug-in hybrid electric vehicles: state of the art. IEEE Trans. Veh. Technol. 59(6), 2806–2814 (2010)

    Google Scholar 

  • Korea Energy Economics Institute.: The Influence of Dissemination of Electric Vehicles on Korea’s Energy Supply and Demand. (2012). (in Korean)

  • Korea Environment Institute.: The Effects of Green Vehicle Incentives on Greenhouse Gas Reduction. (2015). (in Korean)

  • Korea Evaluation Institute of Industrial Technology.: The Trends of Market, Technology and Policy of Electric Vehicle. (2016). (in Korean)

  • Korea Ministry of Environment.: The Project for Dissemination of Electric Vehicles in 2017. (2017). (in Korean)

  • Korea Ministry of Environment.: The Standards of Vehicle Greenhouse Gas Emission and Fuel Economy in 2016–2020. (2014). (in Korean)

  • Korea Ministry of Trade, Industry and Energy.: The Research on Building the Ecosystem for Fostering New Industry of Electric Vehicles. (2015). (in Korean)

  • Korea National Statistical Office.: National Statistics Index. http://www.index.go.kr/potal/main/EachDtlPageDetail.do?idx_cd=1257 (2016). Accessed 12 Nov 2016 (in Korean)

  • Li, W., Long, R., Chen, H., Geng, J.: A review of factors influencing consumer intentions to adopt battery electric vehicles. Renew. Sustain. Energy Rev. 78, 318–328 (2017)

    Google Scholar 

  • Lieven, T.: Policy measures to promote electric mobility–a global perspective. Transp. Res. Part A: Policy Pract. 82, 78–93 (2015)

    Google Scholar 

  • LMC Automotive.: Automotive Production and Sales Forecast. http://www.lmc-auto.com/services/global-light-vehicle-sales-forecast/content-deliverables (2016). Accessed 1 May 2017

  • Matthews, L., Lynes, J., Riemer, M., Del Matto, T., Cloet, N.: Do we have a car for you? Encouraging the uptake of electric vehicles at point of sale. Energy Policy 100, 79–88 (2017)

    Google Scholar 

  • Mohamed, M., Higgins, C., Ferguson, M., Kanaroglou, P.: Identifying and characterizing potential electric vehicle adopters in Canada: a two-stage modelling approach. Transp. Policy 52, 100–112 (2016)

    Google Scholar 

  • Nikou, S., Mezei, J.: Evaluation of mobile services and substantial adoption factors with analytic hierarchy process (AHP). Telecommun. Policy 37(10), 915–929 (2013)

    Google Scholar 

  • Noppers, E.H., Keizer, K., Bolderdijk, J.W., Steg, L.: The adoption of sustainable innovations: driven by symbolic and environmental motives. Glob. Environ. Change 25, 52–62 (2014)

    Google Scholar 

  • Park, J.H., Kim, Y.B., Kim, M.K.: Investigating factors influencing the market success or failure of IT services in Korea. Int. J. Inf. Manag. 37(1), 1418–1427 (2017)

    Google Scholar 

  • Quezada, G., Walton, A., Sharma, A.: Risks and tensions in water industry innovation: understanding adoption of decentralized water systems from a socio-technical transitions perspective. J. Clean. Prod. 113, 263–273 (2016)

    Google Scholar 

  • Rezvani, Z., Jansson, J., Bodin, J.: Advances in consumer electric vehicle adoption research: a review and research agenda. Transp. Res. Part D: Transp. Environ. 34, 122–136 (2015)

    Google Scholar 

  • Ryu, J., Leschine, T.M., Nam, J., Chang, W.K., Dyson, K.: A resilience-based approach for comparing expert preferences across two large-scale coastal management programs. J. Environ. Manag. 92(1), 92–101 (2011)

    Google Scholar 

  • Saaty, T.L.: Decision making-the analytic hierarchy and network processes (AHP/ANP). J. Syst. Sci. Syst. Eng. 13(1), 1–35 (2004)

    Google Scholar 

  • Saaty, T.L.: The Analytic Hierarchy Process: Planning, Priority Setting. Resource Allocation. RWS Publications, Pittsburgh (1990)

    Google Scholar 

  • Saaty, T.L., Kearns, K.: Analytical Planning: The Organization of Systems. Pergamon Press, Oxford (1985)

    Google Scholar 

  • Sawyer, S., Allen, J.P., Lee, H.: Broadband and mobile opportunities: a socio-technical perspective. J. Inf. Technol. 18(2), 121–136 (2003)

    Google Scholar 

  • Schuitema, G., Anable, J., Skippon, S., Kinnear, N.: The role of instrumental, hedonic and symbolic attributes in the intention to adopt electric vehicles. Transp. Res. Part A: Policy Pract. 48, 39–49 (2013)

    Google Scholar 

  • She, Z.Y., Sun, Q., Ma, J.J., Xie, B.C.: What are the barriers to widespread adoption of battery electric vehicles? A survey of public perception in Tianjin, China. Transp. Policy 56, 29–40 (2017)

    Google Scholar 

  • Shin, D.: A socio-technical framework for Internet-of-Things design: a human-centered design for the internet of things. Telemat. Inform. 31(4), 519–531 (2014)

    Google Scholar 

  • Shin, D.H., Jung, J.: Socio-technical analysis of Korea’s broadband convergence network: big plans, big projects, big prospects? Telecommun. Policy 36(7), 579–593 (2012)

    Google Scholar 

  • Sierzchula, W., Bakker, S., Maat, K., van Wee, B.: The influence of financial incentives and other socio-economic factors on electric vehicle adoption. Energy Policy 68, 183–194 (2014)

    Google Scholar 

  • Silvia, C., Krause, R.M.: Assessing the impact of policy interventions on the adoption of plug-in electric vehicles: an agent-based model. Energy Policy 96, 105–118 (2016)

    Google Scholar 

  • Steinhilber, S., Wells, P., Thankappan, S.: Socio-technical inertia: understanding the barriers to electric vehicles. Energy Policy 60, 531–539 (2013)

    Google Scholar 

  • Tai, Y.Y., Lin, J.Y., Chen, M.S., Lin, M.C.: A grey decision and prediction model for investment in the core competitiveness of product development. Technol. Forecast. Soc. Chang. 78(7), 1254–1267 (2011)

    Google Scholar 

  • United Nations Environment Program.: Climate Commitments of Subnational Actors and Business. http://www.cop21paris.org/about/cop21 (2015). Accessed 12 Nov 2016

  • United States Environmental Protection Agency. All-Electric Vehicles. http://www.fueleconomy.gov/feg/evtech.shtml#end-notes (2016). Accessed 1 July 2017

  • Vaidya, O.S., Kumar, S.: Analytic hierarchy process: an overview of applications. Eur. J. Oper. Res. 169(1), 1–29 (2006)

    Google Scholar 

  • Wang, N., Pan, H., Zheng, W.: Assessment of the incentives on electric vehicle promotion in China. Transp. Res. Part A: Policy Pract. 101, 177–189 (2017)

    Google Scholar 

  • Wedley, W.C.: Consistency prediction for incomplete AHP matrices. Math. Comput. Model. 17(4–5), 151–161 (1993)

    Google Scholar 

  • Yu, E., Hong, A., Hwang, J.: A socio-technical analysis of factors affecting the adoption of smart TV in Korea. Comput. Hum. Behav. 61, 89–102 (2016)

    Google Scholar 

  • Yun, S., Lee, J.: Advancing societal readiness toward renewable energy system adoption with a socio-technical perspective. Technol. Forecast. Soc. Chang. 95, 170–181 (2015)

    Google Scholar 

  • Zhang, X., Wang, K., Hao, Y., Fan, J.L., Wei, Y.M.: The impact of government policy on preference for NEVs: the evidence from China. Energy Policy 61, 382–393 (2013)

    Google Scholar 

  • Zhang, Y., Qian, Z.S., Sprei, F., Li, B.: The impact of car specifications, prices and incentives for battery electric vehicles in Norway: choices of heterogeneous consumers. Transp. Res. Part C: Emerg. Technol. 69, 386–401 (2016)

    Google Scholar 

  • Zhang, Y., Yu, Y., Zou, B.: Analyzing public awareness and acceptance of alternative fuel vehicles in China: the case of EV. Energy Policy 39(11), 7015–7024 (2011)

    Google Scholar 

  • Zubaryeva, A., Thiel, C., Barbone, E., Mercier, A.: Assessing factors for the identification of potential lead markets for electrified vehicles in Europe: expert opinion elicitation. Technol. Forecast. Soc. Change 79(9), 1622–1637 (2012)

    Google Scholar 

Download references

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Correspondence to Jong-Hyun Park.

Appendix: Questionnaire items and scales

Appendix: Questionnaire items and scales

Compare relatively important influence as the barriers (dimensions) to market diffusion of EVs in Korea.

Burden of costs

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Insufficient vehicle competences

Burden of costs

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Charging concerns

Burden of costs

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Insufficient policies

Burden of costs

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Lack of perceptions

Insufficient vehicle competences

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Charging concerns

Insufficient vehicle competences

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Insufficient policies

Insufficient vehicle competences

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Lack of perceptions

Charging concerns

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Insufficient policies

Charging concerns

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Lack of perceptions

Insufficient policies

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Lack of perceptions

Compare relatively important influence as the barriers (factors) to market diffusion of EVs in Korea.

In terms of burden of costs

Burden of initial costs

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Burden of operation costs

Burden of initial costs

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Burden of battery costs

Burden of operation costs

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Burden of battery costs

In terms of insufficient vehicle competences

Insufficient performance

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Concern about safety

Insufficient performance

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Lack of models

Concern about safety

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Lack of models

In terms of charging concerns

Lack of charging infrastructures

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Long charging time

Lack of charging infrastructures

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Limited driving range

Long charging time

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Limited driving range

In terms of insufficient policies

Insufficient financial incentives

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Lack of non-financial supports

Insufficient financial incentives

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Inefficient industrial policies

Lack of non-financial supports

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Inefficient industrial policies

In terms of lack of perceptions

Lack of individual awareness

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Lack of social empathy

Lack of individual awareness

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Low willingness of automakers

Lack of social empathy

⑨-⑧-⑦-⑥-⑤-④-③-②-①-②-③-④-⑥-⑦-⑧-⑨

Low willingness of automakers

In the above questionnaire, the scale from ① to ⑨ means the following.

Equally important

Equally to moderately important

Moderately important

Moderately to strongly important

Strongly important

Strongly to very strongly important

Very strongly important

Very strongly to extremely important

Extremely important

Explanation on factors in questionnaire

Dimension/factor

Explanation

Burden of costs

Burden of initial costs

Burden of ownership costs including vehicle price and purchasing taxes

Burden of operation costs

Burden of operation costs including electricity costs

Burden of battery costs

Burden of battery changing and maintaining costs

Insufficient vehicle competences

Insufficient performance

Concerns about poor vehicle performance including top speed or vehicle output

Concern about safety

Concerns about poor safety, including vehicle fire or breakdown

Lack of models

Lack of selectable vehicle types or models

Charging concerns

Lack of charging infrastructures

Lack of availability of charging points or stations

Long charging time

Long time required to recharging including quick or normal charging

Limited driving range

A lack of driving range per one-charging

Insufficient policies

Insufficient financial incentives

Insufficient government support through financial incentives including subsidies, tax exemptions

Lack of non-financial supports

Lack of government’s non-financial supports including bus lane access and exemption from road tolling

Inefficient industrial policies

Inefficient government’s policies of industrial promotion including standardization, fuel economy policies, and regulatory

Lack of perceptions

Lack of individual awareness

Lack of individual awareness on the benefits and risks of EVs

Lack of social empathy

Lack of social empathy on eco-friendly and economic benefits

Low willingness of automakers

Low willingness of automakers on investment, sales promotion, and advertising on EVs

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Kim, MK., Park, JH., Kim, K. et al. Identifying factors influencing the slow market diffusion of electric vehicles in Korea. Transportation 47, 663–688 (2020). https://doi.org/10.1007/s11116-018-9908-1

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