2. Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
3. Axsen, J., & Kurani, K. S. (2012). Social influence, consumer behavior, and low-carbon energy transitions. Annual Review of Environment and Resources, 37, 311-340.
4. Axsen, J., & Kurani, K. S. (2013). Hybrid, plug-in hybrid, or electric—What do car buyers want?. Energy Policy, 61, 532-543.
5. Beck, L., & Ajzen, I. (1991). Predicting dishonest actions using the theory of planned behavior. Journal of research in personality, 25(3), 285-301.
6. Briggs, S. R., & Cheek, J. M., (1986). The role of factor analysis in the development and evaluation of
7. Castanier, C., Deroche, T., & Woodman, T. (2013). Theory of planned behaviour and road violations: The moderating influence of perceived behavioural control. Transportation research part F: traffic psychology and behaviour, 18, 148-158.
8. Chen, C.-F., & Chao, W.-H., (2011). Habitual or reasoned? Using the theory of planned behavior, technology acceptance model, and habit to examine switching intentions toward public transit. Transportation Research Part F: 14(2), 128–137.
9. Cristea, M., Paran, F., & Delhomme, P., (2013). Extending the theory of planned behavior: The role of behavioral options and additional factors in predicting speed behavior. Transportation Research Part F: 21, 122–132.
10. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982-1003.
11. Daziano, R. A., & Chiew, E. (2012). Electric vehicles rising from the dead: data needs for forecasting consumer response toward sustainable energy sources in personal transportation. Energy Policy, 51, 876-894.
12. Dickinger, A., & Kleijnen, M. (2008). Coupons going wireless: Determinants of consumer intentions to redeem mobile coupons. Journal of interactive marketing, 22(3), 23-39.
13. Eneizan, B. M., & Obaid, T. F. (2016). Prior research on green marketing and green marketing strategy: critical analysis. Singaporean Journal of Business, Economics and Management Studies, 51(3965), 1-19.
14. Eneizan, B. M., Abd Wahab, K., & Obaid, T. F. (2016). Effects of green marketing strategies on sales volume of green cars. Singaporean Journal of Business, Economics and Management Studies, 51(3814), 1-14.
15. Han, H., Hsu, L. T. J., & Sheu, C. (2010). Application of the theory of planned behavior to green hotel choice: Testing the effect of environmental friendly activities. Tourism management, 31(3), 325-334.
16. Hidrue, M. K., Parsons, G. R., Kempton, W., & Gardner, M. P. (2011). Willingness to pay for electric vehicles and their attributes. Resource and Energy Economics, 33(3), 686-705.
17. Horvath, C., Lewis, I., & Watson, B., (2012). Peer passenger identity and passenger pressure on young drivers’ speeding intentions. Transportation Research Part F: 15(1), 52–64.
18. Hsiao, C.-H., & Yang, C., (2010). Predicting the travel intention to take High Speed Rail among college students. Transportation Research Part F: 13(4), 277–287.
19. IEA, (2015). CO2 emissions from fuel combustion highlights 2015 ed. International Energy Agency, Paris, France.
20. IEA, (2017a). CEM 30@30 Campain. International Energy Agency, http://www.iea.org/topics/transport/subtopics/electricvehiclesinitiative
21. IEA, (2017b). Global EV Outlook 2017. International Energy Agency, Paris, France.
22. Jaber, J. O., Al-Ghandoor, A., & Sawalha, S. A. (2008). Energy analysis and exergy utilization in the transportation sector of Jordan. Energy policy, 36(8), 2995-3000.
23. Kim, Y., & Han, H. (2010). Intention to pay conventional-hotel prices at a green hotel–a modification of the theory of planned behavior. Journal of Sustainable Tourism, 18(8), 997-1014.
24. Lean, O. K., Zailani, S., Ramayah, T., & Fernando, Y., (2009). Factors influencing intention to use e-government services among citizens in Malaysia. Int. J. Info. Mgmt. 29(6), 458–475.
25. Ministry of Energy and Mineral Resources (MEMR)(2010). Annual report 1985-2009, Amman, Jordan; 1986-2010.
26. Ministry of Public Works and Housing (MPWH)(2010). Annual report 2009. Amman, Jordan.
27. Moan, I. S., (2013). Whether or not to ride with an intoxicated driver: Predicting intentions using an extended version of the theory of planned behaviour. Transportation Research Part F: 201369193–205.
28. Moons, I., & De Pelsmacker, P. (2015). An extended decomposed theory of planned behaviour to predict the usage intention of the electric car: A multi-group comparison. Sustainability, 7(5), 6212-6245.
29. Okamura, K., Fujita, G., Kihira, M., Kosuge, R., & Mitsui, T., (2012). Predicting motivational determinants of seatbelt non-use in the front seat: A field study. Transportation Research Part F: 15(5), 502–513.
30. Palinski, M. (2017). A Comparison of Electric Vehicles and Conventional Automobiles: Costs and Quality Perspective.
31. Pallant, J., (2011). SPSS Survival Manual (4th Edition). Crows Nest, NSW: Allen & Unwin.
32. personality scales. J. Personality. 54, 106–148.
33. Rezvani, Z., Jansson, J., Bodin, J., (2015). Advances in consumer electric vehicle adoption research: A review and research agenda. Transportation Research Part D: Transport and Environment 34, 122-136.
34. Sang, Y. N., & Bekhet, H. A. (2015). Modelling electric vehicle usage intentions: an empirical study in Malaysia. Journal of Cleaner Production, 92, 75-83.
35. Schuitema, G., Anable, J., Skippon, S., & Kinnear, N. (2013). The role of instrumental, hedonic and symbolic attributes in the intention to adopt electric vehicles. Transportation Research Part A: Policy and Practice, 48, 39-49.
36. Scutt, D. (2016). was a record-breaking year for global car sales, and it was almost entirely driven by China. Business Insider, http://www.businessinsider.com/2016-was-a-recordbreaking-year-for-global-car-sales-and-it-was-almost-entirely-driven-by-china-2017-1.
37. Statistical yearbook (2009). Amman, Jordan: Department of Statistics (DoS).
38. Statistical yearbook 1970-2008(2009). Amman, Jordan: Department of Statistics (DoS); 1971-2009.
39. Wang, S., Fan, J., Zhao, D., Yang, S., & Fu, Y. (2016). Predicting consumers’ intention to adopt hybrid electric vehicles: using an extended version of the theory of planned behavior model. Transportation, 43(1), 123-143.
40. Zhang, X., Bai, X., (2017). Incentive policies from 2006 to 2016 and new energy vehicle adoption in 2010–2020 in China. Renewable and Sustainable Energy Reviews 70, 24-43.
- Abstract viewed - 52 times
- PDF downloaded - 10 times
This work is licensed under a Creative Commons Attribution 4.0 International License.
Assistant Professor, Head of Marketing Department, Jadara University, Irbid, Jordan
How to Cite
The adoption of electrics vehicles in Jordan based on theory of planned behavior
Vol 2 No 2 (2019): AJEBM
Submitted: May 5, 2019
Published: Jun 14, 2019
Using the electric vehicles (EVs) is indispensable for the reduction in fossil fuels consumption which are the main cause of carbon emission. However, research investigating the intention to adopt electric vehicle from developing countries perspective is limited. To fill this gap, this study used TPB model to study the effect of Attitude towards adoption EV, Subjective norm, and Perceived behavioral control on Intention to adopt electric vehicle. The conceptual framework of the study hypothesized several relationships and for that the data was collected through a questionnaire from a sample of 250 individual in Jordan. Results show that Attitude towards adoption EV, Subjective norm, and Perceived behavioral control have a positive influence on EV adoption intention. The findings lead towards the important implications that will help understanding consumer behavior towards adoption of EVs