پذیرش اتومبیل خودران با استفاده از نظریه‌های یکپارچه پذیرش و استفاده از فناوری و اشاعه نوآوری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، دانشکده مهندسی عمران و محیط‌زیست، دانشگاه تربیت مدرس، تهران

2 عضو هیات علمی دانشگاه تربیت مدرس

چکیده

پیدایش اتومبیل خودران باعث انقلابی در سیستم حمل‌و‌نقل آینده می‌گردد. در کنار مزایای بالقوه این فناوری، چالش‌های جدید و ناشناخته‌ای در حوزه حمل‌و‌نقل به وجود می‌آید. از گام‌های نخست بررسی تأثیر این وسایل، شناخت عوامل نهان مؤثر بر پذیرش آن است. اکثر پژوهشگران به‌ منظور بررسی عوامل نهان تأثیرگذار بر پذیرش اتومبیل خودران از نظریه یکپارچه پذیرش و استفاده از فناوری استفاده کرده‌اند که تجمیعی از هشت نظریه پیشین استفاده از فناوری است، ولی از برخی متغیرهای مؤثر بر پذیرش غافل است. در این مقاله برای اولین بار از ترکیب نظریه یکپارچه پذیرش و استفاده از فناوری و نظریه اشاعه نوآوری استفاده می‌گردد و متغیرهای نهان امید به عملکرد، امید به تلاش و تأثیر اجتماعی (در نظریه یکپارچه پذیرش و استفاده از فناوری) و قابلیت مشاهده و آزمایش (در نظریه اشاعه نوآوری) بررسی می‌شوند. نتایج مدل پرداخت ‌شده برای 338 نمونه حاصل ‌شده از پرسشنامه طراحی و توزیع‌ شده به این منظور در سال 98 میان ساکنین شهر تهران، حاکی از آن است که متغیر امید به عملکرد بیشترین و متغیر قابلیت آزمایش کمترین تأثیر را در میزان پذیرش اتومبیل خودران دارد. نتایج این مطالعه می‌تواند مورد استفاده سیاست‌گذاران حمل‌و‌نقل برای شناخت عوامل مشوق و بازدارنده بر پذیرش اتومبیل خودران و رفع موانع و چالش‌های پیشروی افراد به ‌منظور پذیرش این فناوری و در نتیجه آن بهره‌گیری از مزایای بالقوه آن باشد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Acceptance of Autonomous Vehicles using a Combination of UTAUT and DOI

نویسندگان [English]

  • Iman Farzin 1
  • Amirreza Mamdoohi 2
1 Ph.D., Candidate, Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran
2 Associate professor, Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran.
چکیده [English]

The advent of autonomous vehicles (AVs) revolutionized the future transportation system. Along with the potential benefits of this technology, new and unknown challenges in the field of transportation are emerging. One of the first steps in examining the impact of these devices is to identify latent variables that affect their acceptance. Most researchers have used the unified theory of acceptance and use of technology (UTAUT) to examine the latent variables influencing the acceptance of AVs, which is a combination of the previous eight theories of acceptance models but ignores some variables affecting acceptance. In this paper, a combination of UTAUT and diffusion of innovations (DOI) theory, and the latent variables of performance expectancy (PE), effort expectancy (EE), social influence (SI) (in UTAUT), and observability (OB), and trialability (TR) (in DOI) were examined. The results of the calibrated proposed model (for 338 samples obtained from the design and distributed questionnaire for this purpose in 2019 among the residents of Tehran) indicated that the PE and OB had the highest and least impact on the acceptance of AVs, respectively. The results of this study can be used by policymakers to address the barriers and challenges facing individuals to adopt this technology and thus benefit from its potential benefits.

کلیدواژه‌ها [English]

  • Autonomous vehicles
  • unified theory of acceptance and use of technology
  • Diffusion of innovations theory
  • structural equation modeling
[1] S.C. Blum, J.M. Schwartz, C. Oliver, Autonomous transportation techniques, in, Google Patents, 2019.
[2] S. Edwards, L. Wundersitz, Distracted driving: Prevalence and motivations, Accident Analysis and Prevention, 54 (2019) 99-107.
[3] D.J. Fagnant, K. Kockelman, Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations, Transportation Research Part A: Policy and Practice, 77 (2015) 167-181.
[4] J.M. Anderson, K. Nidhi, K.D. Stanley, P. Sorensen, C. Samaras, O.A. Oluwatola, Autonomous vehicle technology: A guide for policymakers, Rand Corporation, 2014.
[5] R. Schulz, S.R. Beach, J.T. Matthews, K. Courtney, A. Devito Dabbs, L. Person Mecca, S.S. Sankey, Willingness to pay for quality of life technologies to enhance independent functioning among baby boomers and the elderly adults, The Gerontologist, 54(3) (2014) 363-374.
[6] S. Labi, T.U. Saeed, M. Volovski, S.D. Alqadhi, An exploratory discussion of the Impacts of Driverless Vehicle Operations on the Man-Made Environment, in:  1st International Conference on Mechanical and Transportation Engineering. Kuala Lumpur, Malaysia, 2015.
[7] W. Payre, J. Cestac, P. Delhomme, Intention to use a fully automated car: Attitudes and a priori acceptability, Transportation research part F: traffic psychology and behavior, 27 (2014) 252-263.
[8] D. Milakis, B. Van Arem, B. Van Wee, Policy and society related implications of automated driving: A review of literature and directions for future research, Journal of Intelligent Transportation Systems, 21(4) (2017) 324-348.
[9] S. Puylaert, Social desirability and mobility impacts of early forms of automated vehicles (2016).
[10] Z. Wadud, D. MacKenzie, P. Leiby, Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles, Transportation Research Part A: Policy and Practice, 86 (2016) 1-18.
[11] A. Dillon, M.G. Morris, User acceptance of new information technology: theories and models, in, Medford, NJ: Information Today, 1996.
[12] A.M. Momani, M. Jamous, The evolution of technology acceptance theories, International Journal of Contemporary Computer Research (IJCCR), 1(1) (2017) 51-58.
[13] H. Taherdoost, Development of an adoption model to assess user acceptance of e-service technology: E-Service Technology Acceptance Model, Behaviour & Information Technology, 37(2) (2018) 173-197.
[14] V. Venkatesh, M.G. Morris, G.B. Davis, F.D. Davis, User acceptance of information technology: Toward a unified view, MIS quarterly, (2003) 425-478.
[15] M.S. Hornor, Diffusion of innovation theory, URL: http://www. ciadvertising. Org/studies/student/98_fall/theory/hornor/paperl (accessed May 26, 2007) (1998).
[16] R. Madigan, T. Louw, M. Wilbrink, A. Schieben, N. Merat, What influences the decision to use automated public transport? Using UTAUT to understand public acceptance of automated road transport systems, Transportation research part F: traffic psychology and behaviour, 50 (2017) 55-64.
[17] M.M. Rahman, M.F. Lesch, W.J. Horrey, L. Strawderman, Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems, Accident Analysis & Prevention, 108 (2017) 361-373.
[18] T. Leicht, A. Chtourou, K.B. Youssef, Consumer innovativeness and intentioned autonomous car adoption, The Journal of High Technology Management Research, 29(1) (2018) 1-11.
[19] M. Ingeveld, Usage intention of automated vehicles amongst elderly in the Netherlands (2017).
[20] S. Kapser, M. Abdelrahman, Acceptance of autonomous delivery vehicles for last-mile delivery in Germany–Extending UTAUT2 with risk perceptions, Transportation Research Part C: Emerging Technologies, 111 (2020) 210-225.
[21] S.-A. Kaye, I. Lewis, S. Forward, P. Delhomme, A priori acceptance of highly automated cars in Australia, France, and Sweden: A theoretically-informed investigation guided by the TPB and UTAUT, Accident Analysis & Prevention, 137 (2020) 105441.
[22] G.R. Hancock, R.O. Mueller, L.M. Stapleton, The reviewer’s guide to quantitative methods in the social sciences, Routledge, 2010.
[23] G.F. Khan, M. Sarstedt, W.-L. Shiau, J.F. Hair, C.M. Ringle, M.P. Fritze, Methodological research on partial least squares structural equation modeling (PLS-SEM), Internet Research (2019).
[24] F. Hair Jr. Joseph, C. Black William, J. Babin Barry, E. Anderson Rolph, Multivariate data analysis 7th Ed., in, Upper Saddle River, NJ: Prentice Hall, 2009.
[25] B. Williams, A. Onsman, T. Brown, Exploratory factor analysis: A five-step guide for novices, Australasian journal of paramedicine, 8(3) (2010).
[26] P. Jing, G. Xu, Y. Chen, Y. Shi, F. Zhan, The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review, Sustainability, 12(5) (2020) 1719.
[27] Z. Xu, K. Zhang, H. Min, Z. Wang, X. Zhao, P. Liu, What drives people to accept automated vehicles? Findings from a field experiment, Transportation research part C: emerging technologies, 95 (2018) 320-334.
[28] A.J.T. Solbraa Bay, Innovation adoption in robotics: consumer intentions to use autonomous vehicles, 2016.
[29] T. Zhang, D. Tao, X. Qu, X. Zhang, R. Lin, W. Zhang, The roles of initial trust and perceived risk in public’s acceptance of automated vehicles, Transportation research part C: emerging technologies, 98 (2019) 207-220.
[30] K.F. Yuen, Y.D. Wong, F. Ma, X. Wang, The determinants of public acceptance of autonomous vehicles: An innovation diffusion perspective, Journal of Cleaner Production, (2020) 121904.
[31] W.M. Al-Rahmi, N. Yahaya, A.A. Aldraiweesh, M.M. Alamri, N.A. Aljarboa, U. Alturki, A.A. Aljeraiwi, Integrating technology acceptance model with innovation diffusion theory: An empirical investigation on students’ intention to use E-learning systems, IEEE Access, 7 (2019) 26797-26809.
[32] A. Tamjidyamcholo, R. Gholipour, M. Afshar Kazemi, Examining the Perceived Consequences and Usage of MOOCs on Learning Effectiveness, Iranian Journal of Management Studies, 13(3) (2020) 495-525.
[33] H. Strömberg, O. Rexfelt, I.M. Karlsson, J. Sochor, Trying on change–Trial ability as a change moderator for sustainable travel behavior, Travel Behavior and Society, 4 (2016) 60-68.
[34] K.F. Yuen, X. Wang, L.T.W. Ng, Y.D. Wong, An investigation of customers’ intention to use self-collection services for last-mile delivery, Transport Policy, 66 (2018) 1-8.