IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i8p7003-d1129528.html
   My bibliography  Save this article

Fuzzy Analytical Hierarchy Process for Strategic Decision Making in Electric Vehicle Adoption

Author

Listed:
  • Pasura Aungkulanon

    (Department of Materials Handling and Logistics Engineering, Faculty of Engineering, King Mongkut’s University of Technology North Bangkok, Bangkok 10800, Thailand)

  • Walailak Atthirawong

    (School of Science, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand)

  • Pongchanun Luangpaiboon

    (Thammasat University Research Unit in Industrial Statistics and Operational Research, Department of Industrial Engineering, Faculty of Engineering, Thammasat School of Engineering, Thammasat University, Pathumthani 12120, Thailand)

Abstract

In response to the requirement to address the global climate crisis in urban areas caused by the logistics sector, an increasing number of governments around the world have begun aggressive strategic actions to encourage manufacturers and consumers to adopt electric vehicle (EV) technology. One of the most beneficial aspects of driving an EV is that it reduces pollution while also reducing the use of fossil fuels, as well as improving public health by improving local air quality. Nevertheless, the level of EV adoption differs significantly across markets and geographies. EV adoption barriers slow the overall rate of electric mobility. This study ranks a list of obstacles and sub-hindrances to the adoption of electric vehicles in Thailand using the Fuzzy Analytical Hierarchy Process (FAHP), a Multi-Criteria Decision Making (MCDM) technique. The results showed that infrastructure policy barrier (A), which had the highest weight of 0.6058, was the biggest barrier to EV adoption, followed by technological barrier (B) with a weight of 0.2657, and then by market barrier with a weight of 0.1285. Insufficient charging infrastructure network (A3), lack of proper government support/incentives and collaboration (A1), insufficient electric power supply (A2), high capital cost (C3), and EV charging time (B3) were key sub-barriers to EV adoption in Thailand. Decision Making Systems (DMS) have additionally been created to assist executives in making decisions about the aforementioned barriers. The DMS is based on the concept of computer-aided decision making in that it allows for direct user interaction, analysis, and the ability to change circumstances and the decision-making process based on the executives’ own experience and abilities. Thus, the findings of this study aid in the formulation of market strategies for relevant stakeholders and shed light on potential policy responses.

Suggested Citation

  • Pasura Aungkulanon & Walailak Atthirawong & Pongchanun Luangpaiboon, 2023. "Fuzzy Analytical Hierarchy Process for Strategic Decision Making in Electric Vehicle Adoption," Sustainability, MDPI, vol. 15(8), pages 1-20, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:7003-:d:1129528
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/8/7003/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/8/7003/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mikhailov, L., 2002. "Fuzzy analytical approach to partnership selection in formation of virtual enterprises," Omega, Elsevier, vol. 30(5), pages 393-401, October.
    2. Gupta, Himanshu, 2018. "Evaluating service quality of airline industry using hybrid best worst method and VIKOR," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 35-47.
    3. Robinson, A.P. & Blythe, P.T. & Bell, M.C. & Hübner, Y. & Hill, G.A., 2013. "Analysis of electric vehicle driver recharging demand profiles and subsequent impacts on the carbon content of electric vehicle trips," Energy Policy, Elsevier, vol. 61(C), pages 337-348.
    4. Badri, Masood A., 2001. "A combined AHP-GP model for quality control systems," International Journal of Production Economics, Elsevier, vol. 72(1), pages 27-40, June.
    5. Ardeshiri, Ali & Rashidi, Taha Hossein, 2020. "Willingness to pay for fast charging station for electric vehicles with limited market penetration making," Energy Policy, Elsevier, vol. 147(C).
    6. Beck, Patrick & Hofmann, Erik, 2012. "Multiple criteria decision making in supply chain management – Currently available methods and possibilities for future research," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 66(2), pages 180-213.
    7. Govindan, Kannan & Soleimani, Hamed & Kannan, Devika, 2015. "Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future," European Journal of Operational Research, Elsevier, vol. 240(3), pages 603-626.
    8. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    9. Zhang, Xian & Wang, Ke & Hao, Yu & Fan, Jing-Li & Wei, Yi-Ming, 2013. "The impact of government policy on preference for NEVs: The evidence from China," Energy Policy, Elsevier, vol. 61(C), pages 382-393.
    10. Sierzchula, William & Bakker, Sjoerd & Maat, Kees & van Wee, Bert, 2014. "The influence of financial incentives and other socio-economic factors on electric vehicle adoption," Energy Policy, Elsevier, vol. 68(C), pages 183-194.
    11. F. Hutton Barron & Bruce E. Barrett, 1996. "Decision Quality Using Ranked Attribute Weights," Management Science, INFORMS, vol. 42(11), pages 1515-1523, November.
    12. Weiss, Martin & Patel, Martin K. & Junginger, Martin & Perujo, Adolfo & Bonnel, Pierre & van Grootveld, Geert, 2012. "On the electrification of road transport - Learning rates and price forecasts for hybrid-electric and battery-electric vehicles," Energy Policy, Elsevier, vol. 48(C), pages 374-393.
    13. Krause, Rachel M. & Carley, Sanya R. & Lane, Bradley W. & Graham, John D., 2013. "Perception and reality: Public knowledge of plug-in electric vehicles in 21 U.S. cities," Energy Policy, Elsevier, vol. 63(C), pages 433-440.
    14. Chanwit Kongklaew & Khamphe Phoungthong & Chanwit Prabpayak & Md. Shahariar Chowdhury & Imran Khan & Nuttaya Yuangyai & Chumpol Yuangyai & Kuaanan Techato, 2021. "Barriers to Electric Vehicle Adoption in Thailand," Sustainability, MDPI, vol. 13(22), pages 1-13, November.
    15. Banker, Rajiv D. & Cooper, William W. & Seiford, Lawrence M. & Thrall, Robert M. & Zhu, Joe, 2004. "Returns to scale in different DEA models," European Journal of Operational Research, Elsevier, vol. 154(2), pages 345-362, April.
    16. Yipeng Liu & Jong Min Lee & Celia Lee, 2020. "The challenges and opportunities of a global health crisis: the management and business implications of COVID-19 from an Asian perspective," Asian Business & Management, Palgrave Macmillan, vol. 19(3), pages 277-297, July.
    17. Poder, Thomas G. & He, Jie, 2017. "Willingness to pay for a cleaner car: The case of car pollution in Quebec and France," Energy, Elsevier, vol. 130(C), pages 48-54.
    18. Biresselioglu, Mehmet Efe & Demirbag Kaplan, Melike & Yilmaz, Barbara Katharina, 2018. "Electric mobility in Europe: A comprehensive review of motivators and barriers in decision making processes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 109(C), pages 1-13.
    19. Chang, Da-Yong, 1996. "Applications of the extent analysis method on fuzzy AHP," European Journal of Operational Research, Elsevier, vol. 95(3), pages 649-655, December.
    20. Zubaryeva, Alyona & Thiel, Christian & Barbone, Enrico & Mercier, Arnaud, 2012. "Assessing factors for the identification of potential lead markets for electrified vehicles in Europe: expert opinion elicitation," Technological Forecasting and Social Change, Elsevier, vol. 79(9), pages 1622-1637.
    21. Madhusudhan Adhikari & Laxman Prasad Ghimire & Yeonbae Kim & Prakash Aryal & Sundar Bahadur Khadka, 2020. "Identification and Analysis of Barriers against Electric Vehicle Use," Sustainability, MDPI, vol. 12(12), pages 1-20, June.
    22. Azadfar, Elham & Sreeram, Victor & Harries, David, 2015. "The investigation of the major factors influencing plug-in electric vehicle driving patterns and charging behaviour," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 1065-1076.
    23. Haddad, Malik & Sanders, David, 2018. "Selection of discrete multiple criteria decision making methods in the presence of risk and uncertainty," Operations Research Perspectives, Elsevier, vol. 5(C), pages 357-370.
    24. Paweł Cabała, 2010. "Using the analytic hierarchy process in evaluating decision alternatives," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 20(1), pages 5-23.
    25. Michael K. Lim & Ho-Yin Mak & Ying Rong, 2015. "Toward Mass Adoption of Electric Vehicles: Impact of the Range and Resale Anxieties," Manufacturing & Service Operations Management, INFORMS, vol. 17(1), pages 101-119, February.
    26. Miao, Zhuang & Baležentis, Tomas & Shao, Shuai & Chang, Dongfeng, 2019. "Energy use, industrial soot and vehicle exhaust pollution—China's regional air pollution recognition, performance decomposition and governance," Energy Economics, Elsevier, vol. 83(C), pages 501-514.
    27. She, Zhen-Yu & Qing Sun, & Ma, Jia-Jun & Xie, Bai-Chen, 2017. "What are the barriers to widespread adoption of battery electric vehicles? A survey of public perception in Tianjin, China," Transport Policy, Elsevier, vol. 56(C), pages 29-40.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jung-Fa Tsai & Sheng-Che Wu & Pajaree Kathinthong & Thu-Hien Tran & Ming-Hua Lin, 2024. "Electric Vehicle Adoption Barriers in Thailand," Sustainability, MDPI, vol. 16(4), pages 1-15, February.
    2. Zhang, Hong & Irfan, Muhammad & Ai, Fengyi & Al-Aiban, Khalid M. & Abbas, Shujaat, 2024. "Analyzing barriers to the adoption and development of electric vehicles: A roadmap towards sustainable transportation system," Renewable Energy, Elsevier, vol. 233(C).
    3. Levent Özlü & Dilay Çelebi, 2024. "Electrifying Freight: Modeling the Decision-Making Process for Battery Electric Truck Procurement," Sustainability, MDPI, vol. 16(9), pages 1-23, April.
    4. Pasura Aungkulanon & Walailak Atthirawong & Woranat Sangmanee & Pongchanun Luangpaiboon, 2023. "Fuzzy Techniques and Adjusted Mixture Design-Based Scenario Analysis in the CLMV (Cambodia, Lao PDR, Myanmar and Vietnam) Subregion for Multi-Criteria Decision Making in the Apparel Industry," Mathematics, MDPI, vol. 11(23), pages 1-32, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Patyal, Vishal Singh & Kumar, Ravi & Kushwah, Shiksha, 2021. "Modeling barriers to the adoption of electric vehicles: An Indian perspective," Energy, Elsevier, vol. 237(C).
    2. Zhang, Hong & Irfan, Muhammad & Ai, Fengyi & Al-Aiban, Khalid M. & Abbas, Shujaat, 2024. "Analyzing barriers to the adoption and development of electric vehicles: A roadmap towards sustainable transportation system," Renewable Energy, Elsevier, vol. 233(C).
    3. Cruz-Jesus, Frederico & Figueira-Alves, Hugo & Tam, Carlos & Pinto, Diego Costa & Oliveira, Tiago & Venkatesh, Viswanath, 2023. "Pragmatic and idealistic reasons: What drives electric vehicle drivers' satisfaction and continuance intention?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    4. Elena Higueras-Castillo & Sebastian Molinillo & J. Andres Coca-Stefaniak & Francisco Liébana-Cabanillas, 2020. "Potential Early Adopters of Hybrid and Electric Vehicles in Spain—Towards a Customer Profile," Sustainability, MDPI, vol. 12(11), pages 1-18, May.
    5. Chun Yang & Jui-Che Tu & Qianling Jiang, 2020. "The Influential Factors of Consumers’ Sustainable Consumption: A Case on Electric Vehicles in China," Sustainability, MDPI, vol. 12(8), pages 1-16, April.
    6. Jingnan Zhang & Shichun Xu & Zhengxia He & Chengze Li & Xiaona Meng, 2022. "Factors Influencing Adoption Intention for Electric Vehicles under a Subsidy Deduction: From Different City-Level Perspectives," Sustainability, MDPI, vol. 14(10), pages 1-24, May.
    7. Moon-Koo Kim & Jong-Hyun Park & Kyungsoo Kim & Byoungkyu Park, 2020. "Identifying factors influencing the slow market diffusion of electric vehicles in Korea," Transportation, Springer, vol. 47(2), pages 663-688, April.
    8. She, Zhen-Yu & Qing Sun, & Ma, Jia-Jun & Xie, Bai-Chen, 2017. "What are the barriers to widespread adoption of battery electric vehicles? A survey of public perception in Tianjin, China," Transport Policy, Elsevier, vol. 56(C), pages 29-40.
    9. Kim, Moon-Koo & Oh, Jeesun & Park, Jong-Hyun & Joo, Changlim, 2018. "Perceived value and adoption intention for electric vehicles in Korea: Moderating effects of environmental traits and government supports," Energy, Elsevier, vol. 159(C), pages 799-809.
    10. Shuping Wu & Zan Yang, 2020. "Availability of Public Electric Vehicle Charging Pile and Development of Electric Vehicle: Evidence from China," Sustainability, MDPI, vol. 12(16), pages 1-14, August.
    11. Liangui Peng & Ying Li & Hui Yu, 2021. "Effects of Dual Credit Policy and Consumer Preferences on Production Decisions in Automobile Supply Chain," Sustainability, MDPI, vol. 13(11), pages 1-19, May.
    12. Makena Coffman & Paul Bernstein & Sherilyn Wee, 2017. "Electric vehicles revisited: a review of factors that affect adoption," Transport Reviews, Taylor & Francis Journals, vol. 37(1), pages 79-93, January.
    13. Goel, Pooja & Kumar, Aalok & Parayitam, Satyanarayana & Luthra, Sunil, 2023. "Understanding transport users' preferences for adopting electric vehicle based mobility for sustainable city: A moderated moderated-mediation model," Journal of Transport Geography, Elsevier, vol. 106(C).
    14. Dwivedi, Pankaj Prasad & Sharma, Dilip Kumar, 2023. "Evaluation and ranking of battery electric vehicles by Shannon’s entropy and TOPSIS methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 212(C), pages 457-474.
    15. Zhao, Xingrong & Ma, Ye & Shao, Shuai & Ma, Tieju, 2022. "What determines consumers' acceptance of electric vehicles: A survey in Shanghai, China," Energy Economics, Elsevier, vol. 108(C).
    16. Nilsson, Måns & Nykvist, Björn, 2016. "Governing the electric vehicle transition – Near term interventions to support a green energy economy," Applied Energy, Elsevier, vol. 179(C), pages 1360-1371.
    17. Philip, Thara & Whitehead, Jake & Prato, Carlo G., 2023. "Adoption of electric vehicles in a laggard, car-dependent nation: Investigating the potential influence of V2G and broader energy benefits on adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 167(C).
    18. Madhusudhan Adhikari & Laxman Prasad Ghimire & Yeonbae Kim & Prakash Aryal & Sundar Bahadur Khadka, 2020. "Identification and Analysis of Barriers against Electric Vehicle Use," Sustainability, MDPI, vol. 12(12), pages 1-20, June.
    19. Sovacool, Benjamin K. & Abrahamse, Wokje & Zhang, Long & Ren, Jingzheng, 2019. "Pleasure or profit? Surveying the purchasing intentions of potential electric vehicle adopters in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 69-81.
    20. Martins, H. & Henriques, C.O. & Figueira, J.R. & Silva, C.S. & Costa, A.S., 2023. "Assessing policy interventions to stimulate the transition of electric vehicle technology in the European Union," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:7003-:d:1129528. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.