Browse > Article
http://dx.doi.org/10.14400/JDC.2018.16.5.115

Extending of TAM through Perceived Trust and its Application to Autonomous Driving  

Lee, Kangmun (Dept. of Business Administration, Kyungnam University)
Roh, Taewoo (Dept. of International Trade and Commerce, Soonchunhyang University)
Publication Information
Journal of Digital Convergence / v.16, no.5, 2018 , pp. 115-122 More about this Journal
Abstract
The purpose of this study is to investigate the effect of technology acceptance model (TAM) on behavioral intention in order to grasp the degree of technology acceptance on autonomous driving among the various factors that consumers perceive as unmanned vehicle system becomes commercialized. In addition to the mediating effect of perceived usefulness proposed by the existing TAM, this study proposed the perceived trust (PT) and hypothesized its mediating effect on behavioral intention to use the self-driving. Path anlaysis is adopted to investigate our hypothesis using the structural equation model. The sample used for the analysis was 149 valid data among 160 responses. The effects of total effect, direct effect, and indirect effect were confirmed by hypothesis test on mediating effect. Non-parametric bootstrapping analysis was also performed to confirm the robustness. All the hypotheses were significant and we found a partial indirect effect, which implies that mediation effect of PT on behavioral intention.
Keywords
Autonomous Driving; Technology Acceptance Model; Perceived Trust; Mediation Effect; Structural Equation Model;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
연도 인용수 순위
1 Kramer, R. M. (1999). Trust and Distrust in Organizations: Emerging Perspectives, Enduring Questions. Annual Review of Psychology, 50(1), 569-598.   DOI
2 Waytz, A., Heafner, J. & Epley, N. (2014). The Mind in the Machine: Anthropomorphism Increases Trust in an Autonomous Vehicle. Journal of Experimental Social Psychology, 52, 113-117.   DOI
3 Alotaibi, M. B. (2016). Exploring Users' Attitudes and Intentions toward the Adoption of Cloud Computing in Saudi Arabia: An Empirical Investigation. Journal of Computer Science, 10(11), 2315-2329.   DOI
4 Hu, L. T. & Bentler, P. M. (1999). Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.   DOI
5 Lee, K. & Roh, T. W. (2017). The Effect of Public Service Motivation on Job Satisfaction and Perceived Job Performance: Focusing on the Mediation Effect of Person-Organization Fit. Journal of Digital Convergence, 15(9), 155-165.   DOI
6 Tak, J. G. & Roh, T. W. (2017). Effects of Supervisor's Authentic Leadership on Ocb and Job Performance for Employees. Journal of Digital Convergence, 15(1), 171-179.   DOI
7 Tak, J. G. & Roh, T. W. (2017). The Effectiveness of Authentic Leadership on Public and Private Organizations. Journal of Digital Convergence, 15(10), 161-171.   DOI
8 Yandron, D. & Tynan, D. (2016. 6. 30). Tesla Driver Dies in First Fatal Crash While Using Autopilot Mode. The Guardian. https://www.theguardian.com/technology/2016/jun/30/tesla-autopilot-death-self-driving-car-elon-musk
9 Morris, D. Z. (2016. 10. 15). Mercedes-Benz's Self-Driving Cars Would Choose Passenger Lives over Bystanders. Forbes. http://fortune.com/2016/10/15/mercedes-self-driving-car-ethics/
10 Verberne, F. M., Ham, J. & Midden, C. J. (2012). Trust in Smart Systems: Sharing Driving Goals and Giving Information to Increase Trustworthiness and Acceptability of Smart Systems in Cars. Human Factors, 54(5), 799-810.   DOI
11 Bertoncello, M., &Wee, D. (2015. 6). TenWays Autonomous Driving Could Redefine the Automotive World. Mckinsey. Http://www.mckinsey.com/industries/automotive-and-assembly/our-insights/ten-ways-autonomous-driving-could-redefine-the-automotive-world.
12 Ramsey, M. (2017. 1. 26). On the Road to Driverless Cars. Forbes. https://www.forbes.com/sites/gartnergroup/2017/01/26/on-the-road-to-driverless-cars/#c2988a317ede
13 SAE. (2014). Automated Driving. Warrendale, Pennsylvania: SAE International.
14 David, A. (2016. 8. 26). Everyone Wants a Level 5 Self-Driving Car-Here's What That Means. Wired. https://www.wired.com/2016/08/self-driving-car-levels-sae-nhtsa/
15 Lutin, J. M., Kornhauser, A. L. & Lerner-Lam, E. (2013). The Revolutionary Development of Self- Driving Vehicles and Implications for the Transportation Engineering Profession. ITE Journal, 83(7), 28.
16 Neubauer, C., Matthews, G., Langheim, L. & Saxby, D. (2012). Fatigue and Voluntary Utilization of Automation in Simulated Driving. Human Factors, 54(5), 734-746.   DOI
17 CDC. (2016. 6. 16). Impaired Driving: Get the Facts. Centers for Disease Control and Prevention. https://www.cdc.gov/motorvehiclesafety/impaired_driving/impaired-drv_factsheet.html
18 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.   DOI
19 Diels, C., & Bos, J. E. (2015). Self-Driving Car Sickness. Applied Ergonomics, 53, 374-382.
20 Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340.   DOI
21 Chauh, S. H. W., Rauschnabel, P. A., Kery, N., Ramayah, T. & Lade, S. (2016). Wearable Technologies: The Role of Usefulness and Visibility in Smartwatch Adoption. Computers in Human Behavior, 65, 276-284.   DOI
22 Koo, W., Cho, E. & Kim, Y. K. (2014). Actual and Ideal Self-Congruity Affecting Consumer's Emotional and Behavioral Responses toward an Online Store. Computers in Human Behavior, 36, 147-153.   DOI
23 Wu, J. H., & Wang, S. C. (2005). What Drives Mobile Commerce?: An Empirical Evaluation of the Revised Technology Acceptance Model. Information &Management, 42(5), 719-729.   DOI
24 Jeong, J. Y. & Roh, T. W. (2017). The Intention of Using Wearable Devices : Based on Modified Technology Acceptance Model. Journal of Digital Convergence, 15(4), 205-212.   DOI
25 Lee, Y. S. (2017). The Effects of Consumer Characteristics on the Acceptance of Mobile Commerce. Journal of Digital Convergence, 15(5), 173-187.   DOI
26 Legris, P., Ingham, J. & Collerette, P. (2003). Why Do People Use Information Technology? A Critical Review of the Technology Acceptance Model. Information & Management, 40(3), 191-204.   DOI
27 Jang, H. J. & Noh, G. Y. (2017). Extended Technology Acceptance Model of Vr Head-Mounted Display in Early Stage of Diffusion. Journal of Digital Convergence, 15(5), 353-361.   DOI
28 Elbanhawi, M., Simic, M. & Jazar, R. (2015). In the Passenger Seat: Investigating Ride Comfort Measures in Autonomous Cars. IEEE Intelligent Transportation Systems Magazine, 7(3), 4-17.   DOI
29 Kim, S. & Park, H. S. (2017). Impacts of Individual and Technical Characteristics on Perceived Risk and User Resistance of Mobile Payment Services. Journal of Digital Convergence, 15(12), 239-253.   DOI