نقش خطر درک شده در توسعه نظریه یکپارچه پذیرش و استفاده از فناوری در پذیرش اتومبیل خودران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش آموخته دکتری، دانشکده مهندسی عمران و محیط زیست، دانشگاه تربیت مدرس، تهران، ایران

2 دانشیار، دانشکده مهندسی عمران و محیط زیست، دانشگاه تربیت مدرس، تهران، ایران

چکیده

اتومبیل‌های خودران با استفاده از فناوری‌های سنجش و ارتباطات خود، حرکت ایمن و کارآمد بدون دخالت انسانی را فراهم می‌کنند. این فناوری نقطه عطفی در حمل‌ونقل خواهد بود. ارزیابی پذیرش اتومبیل‌های خودران نقش مهمی در کاربست موفق و کارای آن ایفا می-کند. مرتفع نمودن موانع اقتصادی و فنی بدون از میان برداشتن مانع انسانی پذیرش بی‌ثمر خواهد بود. اکثر محققان پیش‌تر به منظور شناسایی عوامل نهان مؤثر بر پذیرش اتومبیل خودران از نظریه یکپارچه پذیرش و استفاده از فناوری استفاده نموده‌اند. در این پژوهش علاوه بر متغیرهای معمول این نظریه (شامل امید به عملکرد، امید به تلاش و تأثیر اجتماعی)، از متغیر نهان خطر درک شده نیز به منظور شناخت هرچه بیشتر عوامل نهان تأثیرگذار بر پذیرش اتومبیل خودران استفاده می‌گردد. به منظور پرداخت مدل معادلات ساختاری پیشنهادی در این پژوهش، 641 پرسشنامه به روش رجحان بیان‌شده تدوین و در سال 1398 میان ساکنین شهر تهران توزیع گردیده است. نتایج حاکی از تأثیرگذاری، به ترتیب، متغیرهای امید به عملکرد، خطر درک شده، امید به تلاش و تأثیر اجتماعی بر پذیرش اتومبیل‌های خودران است. نتایج این مطالعه می‌تواند به منظور ارزیابی و تخمین پاسخ افراد به اتومبیل‌های خودران قبل از شروع توسعه و اتخاذ سیاست‌های مناسب جهت بالا بردن نرخ نفوذ این وسایل مورد استفاده تصمیم گیران و سیاست‌گذاران قرار گیرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Role of Perceived Risk in Development of Unified Theory of Acceptance and Use of Technology in Acceptance of Autonomous Vehicles

نویسندگان [English]

  • Iman Farzin 1
  • Amir Reza Mamdoohi 2
1 Ph.D., Graduate, Faculty of Civil & Environmental Engineering, Tarbiat Modares University, Tehran, Iran.
2 Associate Professor, Faculty of Civil & Environmental Engineering, Tarbiat Modares University, Tehran, Iran.
چکیده [English]

Autonomous Vehicles (AVs) provide safe and efficient mobility without human intervention by using self-propelled and communication technologies. This technology will be a turning point in transportation. Evaluating the acceptance of AVs plays an important role in its successful and efficient use. Removing economic and technical barriers without removing the human barrier will be not efficient. Most researchers have used Unified Theory of Acceptance and Use of Technology (UTAUT) in order to identify the latent variable affecting the acceptance of AVs. In this study, in addition to the variables considered in this theory (including performance expectancy (PE), effort expectancy (EE), and social influence (SI)), the perceived risk (PR) variable is used to identify more latent variables affecting the acceptance of AVs. In order to calibrate the structural equation model proposed in this study, 641 stated preference questionnaires were distributed among the residents of Tehran. The results indicate that the variables of PE, PR, EE, and SI influence on the acceptance of AVs, respectively. The results of this study can be used by decision-makers and policymakers to evaluate and estimate the response to AVs before the start of development and adopt appropriate policies to increase the penetration rate of these vehicles.
.

کلیدواژه‌ها [English]

  • Acceptance of Autonomous Vehicles
  • Unified Theory of Acceptance and Use of Technology
  • Perceived Risk
-فرزین، ا، عباسی، م و ممدوحی، ا.، (1398)، "شناسایی عوامل جمعیت­شناختی مؤثر در تمایل به خرید و استفاده در شرایط رانندگی کسل­کننده و استفاده اشتراکی از اتومبیل خودران، مطالعات مدیریت ترافیک، شماره 55، زمستان،
 ص. 61- 90.
-فرزین، ا، ممدوحی، ا و نوری، ف.، (1400)، "ناهمگونی میان افراد در پذیرش اتومبیل خودران با استفاده از نظریه یکپارچه پذیرش و کاربرد فناوری"، نشریه مهندسی عمران شریف، (آماده انتشار).
-Acheampong, R. A., & Cugurullo, F., (2019), “Capturing the behavioural determinants behind the adoption of autonomous vehicles: Conceptual frameworks and measurement models to predict public transport, sharing and ownership trends of self-driving cars”, Transportation research part F: traffic psychology and behaviour, Vol. 62,
pp. 349-375.
-Anderson, J. M., Nidhi, K., Stanley, K. D., Sorensen, P., Samaras, C., & Oluwatola, O. A., (2014), “Autonomous vehicle technology: A guide for policymakers: Rand Corporation”.
-Buckley, L., Kaye, S.-A., & Pradhan, A. K., (2018), “Psychosocial factors associated with intended use of automated vehicles: A simulated driving study”, Accident Analysis & Prevention, Vol. 115, pp. 202-208.
-Cheein, F. A. A., De La Cruz, C., Bastos, T. F., & Carelli, R., (2009), ”­Slam-based cross-a-door solution approach for a robotic wheelchair”, International Journal of Advanced Robotic Systems, Vol. 6(3),
pp. 20- 32.
-Choi, J. K., & Ji, Y. G., (2015), “Investigating the importance of trust on adopting an autonomous vehicle”, International Journal of Human-Computer Interaction, Vol. 31(10), pp. 692-702.
-Engelberg, J. K., Hill, L. L., Rybar, J., & Styer, T., (2015), “Distracted driving behaviors related to cell phone use among middle-aged adults”, Journal of Transport & Health,Vol. 2(3), pp. 434-440.
-Ghaffari Targhi, M., (2017), “Factors Influencing the Use of Autonomous and Shared Autonomous Vehicles in Alberta”, Graduate Studies.
-Gkartzonikas, C., & Gkritza, K., (2019), “What have we learned? A review of stated preference and choice studies on autonomous vehicles”, Transportation Research Part C: Emerging Technologies, Vol. 98, pp. 323-337.
-Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R., (2006), “Multivariate data analysis”, Uppersaddle River: NJ: Pearson Prentice Hall.
-Hancock, G. R., Stapleton, L. M., & Mueller, R. O., (2018), “The reviewer’s guide to quantitative methods in the social sciences”, Routledge.
-Harst, L., Lantzsch, H., & Scheibe, M., (2019), “Theories predicting end-user acceptance of telemedicine use: systematic review”, Journal of medical Internet research, Vol. 21(5), pp. 131-152.
-Ingeveld, M., (2017), “Usage intention of automated vehicles amongst elderly in the Netherlands”.
 
 
-Jaccard, J., Wan, C. K., & Jaccard, J., (1996), “LISREL approaches to interaction effects in multiple regression: sage”.
-Jing, P., Xu, G., Chen, Y., Shi, Y., & Zhan, F., (2020), “The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review”, Sustainability, Vol. 12(5), pp. 120-142.
-Kline, R. B., (2011), “Convergence of structural equation modeling and multilevel modeling”.
-Kulviwat, S., Bruner II, G. C., & Al-Shuridah, O., (2009), “The role of social influence on adoption of high tech innovations: The moderating effect of public/private consumption”, Journal of business research, Vol. 62(7), pp. 706-712.
-Laroche, M., Yang, Z., McDougall, G. H., & Bergeron, J., (2005), “Internet versus bricks-and-mortar retailers: An investigation into intangibility and its consequences”, Journal of retailing,
Vol. 81(4), pp. 251-267.
-Leicht, T., Chtourou, A., & Youssef, K. B., (2018), “Consumer innovativeness and intentioned autonomous car adoption”, The Journal of High Technology Management Research, Vol. 29(1), pp. 1-11.
-Liu, H., Yang, R., Wang, L., & Liu, P. (2019), “Evaluating initial public acceptance of highly and fully autonomous vehicles”, International Journal of Human–Computer Interaction, Vol. 35(11),
pp. 919-931.
-Madigan, R., Louw, T., Wilbrink, M., Schieben, A., & Merat, N., (2017), “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, Vol. 50, pp. 55-64.
-Morando, M. M., Tian, Q., Truong, L. T., & Vu, H. L., (2018), “Studying the safety impact of autonomous vehicles using simulation-based surrogate safety measures”, Journal of Advanced Transportation.
-Panagiotopoulos, I., & Dimitrakopoulos, G., (2018), “An empirical investigation on consumers’ intentions towards autonomous driving”, Transportation Research Part C: Emerging Technologies, Vol. 95,
pp. 773-784.
 
-Ram, S., & Sheth, J. N., (1989), “Consumer resistance to innovations: the marketing problem and its solutions”, Journal of Consumer Marketing.
-Schierz, P. G., Schilke, O., & Wirtz, B. W., (2010), “Understanding consumer acceptance of mobile payment services: An empirical analysis”, Electronic commerce research and applications, Vol. 9(3),
pp. 209-216.
-Schoettle, B., & Sivak, M., (2014), “A survey of public opinion about autonomous and self-driving vehicles in the US, the UK, and Australia”.
-Solbraa Bay, A. J. T., (2016), “Innovation adoption in robotics: consumer intentions to use autonomous vehicles”.
-Taherdoost, H., (2018), “A review of technology acceptance and adoption models and theories”, Procedia manufacturing, Vol. 22, pp. 960-967.
-Taherdoost, H., (2019), “Importance of Technology Acceptance Assessment for Successful Implementation and Development of New Technologies”, Global Journal of Engineering Sciences.
-Thierer, A., (2013), “Technopanics, threat inflation, and the danger of an information technology precautionary principle”, Minn. JL Sci. & Tech., 14, 309.
-Thierer, A., & Hagemann, R., (2015), “Removing roadblocks to intelligent vehicles and driverless cars”, Wake Forest JL & Pol'y, Vol. 5, pp. 339-360.
-Veiga, J. F., Floyd, S., & Dechant, K., (2001), “Towards modelling the effects of national culture on IT implementation and acceptance”, Journal of Information technology, Vol. 16(3), pp. 145-158.
-Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D., (2003), “User acceptance of information technology: Toward a unified view”, MIS quarterly.
-Wang, J., & Wang, X., (2019), “Structural equation modeling: Applications using Mplus: John Wiley & Sons”
-Zhang, T., Tao, D., Qu, X., Zhang, X., Lin, R., & Zhang, W., (2019), “The roles of initial trust and perceived risk in public’s acceptance of automated vehicles”, Transportation Research Part C: Emerging Technologies, Vol. 98, pp. 207-220.
-Zmud, J., Sener, I. N., & Wagner, J., (2016), “Consumer acceptance and travel behavior: impacts of automated vehicles”.