Influences of User Experience on Consumer Perception: A Study on “Autonomous Driving”

  • Sarah SelinkaEmail author
  • Marc Kuhn
Conference paper
Part of the Developments in Marketing Science: Proceedings of the Academy of Marketing Science book series (DMSPAMS)


Existing studies on autonomous driving examine automated driving functions based on theoretical consumer ideas or, in a few cases, referred to driving simulations. However, we find a lack in research on how consumers perceive and evaluate automated driving innovation technology in real driving conditions. Focusing on available “Level 2”-series functions, in this paper we concentrate on the effect of driving experience on perception and valuation of the automated driving functionalities. We developed and conducted a user experience study with a pre- and a post-questionnaire, a standardized test-track and 197 test drivers using either Mercedes-Benz E-Class or Tesla Model S. Results indicate that consumers expect much more than already provided by the technology. We found a high influence of driving experience on the consumer perception of automated driving functions.


Autonomous driving User experience Innovation Before–after comparison 


  1. Aeberhard, M., Rauch, S., Bahram, M., Tanzmeister, G., Thomas, J., Pilat, Y., Homm, F., Huber, W., & Kaempchen, N. (2015). Experience, results and lessons learned from automated driving on Germany’s highways. IEEE Intelligent Transportation Systems Magazine, 7(1), 42–57.CrossRefGoogle Scholar
  2. Bansal, P., & Kockelman, K. M. (2018). Are we ready to embrace connected and self-driving vehicles? A case study of Texans. Transportation, Springer, vol. 45(2), pages 641–675, March.Google Scholar
  3. Beiker, S. A. (2012). Legal aspects of autonomous driving. Santa Clara Law Review, 52, 1145.Google Scholar
  4. Bertrandias, L., Carricano, M., & Sadik-Rozsnyai, O. (2016). Delegating decisional power to objects: A consumer value model in the context of autonomous driving. Oslo, BI Norvegian Business School, 45th EMAC (European Marketing Academy) Conference.Google Scholar
  5. Chan, C.-Y. (2017). Advancements, prospects, and impacts of automated driving systems. International Journal of Transportation Science and Technology, 6(3), 208–216.CrossRefGoogle Scholar
  6. Czubenko, M., Kowalczuk, Z., & Ordys, A. (2015). Autonomous driver based on an intelligent system of decision-making. Cognitive Computation, 7, 569–581.CrossRefGoogle Scholar
  7. Grunwald, A. (2015). Gesellschaftliche Risikokonstellation für autonomes Fahren—Analyse, Einordnung und Bewertung. In M. Maurer, J. Gerdes, B. Lenz, & H. Winner (Eds.), Autonomes Fahren. Berlin: Springer Vieweg.Google Scholar
  8. Haboucha, C. J., Ishaq, R., & Shiftan, Y. (2017). User preferences regarding autonomous vehicles. Transportation Research Part C, 78, 37–49.CrossRefGoogle Scholar
  9. Haist, T. (2016). Autonomes Fahren: Eine kritische Beurteilung der technischen Realisierbarkeit.
  10. Hepperle, C., Orawsk, R., Nolte, B. D., Mörtl, M., & Lindemann, U. (2012). An integrated lifecycle model of product-service-systems. Proceedings of the 2nd CIRP IPS2 Conference 2010, 14–15 April, Linköping, Sweden, No. 077, pp. 159-166.Google Scholar
  11. Hofstede, G., & Hofstede, G. J. (2007). Lokales Denken, globales Handeln. Interkulturelle Zusammenarbeit und globales Management. In C. Boersch & R. Elschen (Eds.), Das Summa Summarum des Management. Die 25 wichtigsten Werke für Strategie, Führung und Veränderung. Wiesbaden: Gabler.Google Scholar
  12. König, M., & Neumayr, L. (2017). Users’ resistance towards radical innovations: The case of the self-driving car. Transportation Research Part F, 44, 42–52.CrossRefGoogle Scholar
  13. Kulviwat, S., Bruner, G., Kumar, A., Nasco, S., & Clark, T. (2007). Toward a unified theory of consumer acceptance technology. Psychology & Marketing, 24(12), 1059–1084.CrossRefGoogle Scholar
  14. Markides, C. (2006). Disruptive innovation: In need of better theory. Journal of Product Innovation Management, 23(1), 19–25.CrossRefGoogle Scholar
  15. Mayring, P. (2008). Qualitative Inhaltsanalyse. Grundlagen und Techniken. Weinheim: Beltz Verlag.Google Scholar
  16. Rödel, C., Stadler, S., Meschtscherjakov, A., & Tscheligi, M. (2014). Towards autonomous cars: The effect of autonomy levels on acceptance and user experience. Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (pp. 1–8).Google Scholar
  17. SAE International. (2017, August 11). Automated driving levels of driving automation are defined in new SAE international standard J3016.
  18. Schöttle, B., & Sivak, M. (2014). Public opinion about self-driving vehicles in China, India, Japan, the US, the UK, and Australia. Transportation Research Institute.Google Scholar
  19. 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.CrossRefGoogle Scholar

Copyright information

© Academy of Marketing Science 2019

Authors and Affiliations

  1. 1.Baden-Wuerttemberg Cooperative State UniversityStuttgartGermany

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