Actor-Network Theory as a Framework to Analyse Technology Acceptance Model’s External Variables: The Case of Autonomous Vehicles

  • Patrice SeuwouEmail author
  • Ebad Banissi
  • George Ubakanma
  • Mhd Saeed Sharif
  • Ann Healey
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 630)


The main factor for growth in a globalised and highly competitive world is to have an innovative and continuous improvement for the new technologies; however, it is difficult to guarantee the success of such factor without considering the human nature of the people. The Unified Theory of Acceptance and Use of Technology (UTAUT2) is a model that has been used for years to help us understand the drivers of acceptance of new information technologies by its users. This paper presents the Actor-Network Theory (ANT) as a framework to analyse external variables influencing technology acceptance. We have identified a new construct and moderating factor enabling the extension of the UTAUT2. The scenario used to conduct our investigation is the Autonomous Vehicle (AV) which is a disruptive technology and may prove to be the next big evolution in personal transportation. The study was conducted using an anonymous survey, over 410 responses so far, and numerous interviews with experts in the field of sociology, psychology and computer science in order to refine the proposed model. Our research findings reveal not only the usefulness of ANT in developing an understanding the human and non-human actants playing a role in consumer’s behavioural intention of using AV, but ANT also helps us to argue that culture is a direct determinant of behavioural intention and social class is a very important moderating aspect.


Technology acceptance model Unified theory of acceptance and use of technology Actor-Network theory Autonomous vehicles Security 


  1. 1.
    Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Q. 27(3), 425–478 (2003)Google Scholar
  2. 2.
    ERTRAC. Automated Driving Roadmap: Status 3rd Draft for public consultation (2015)Google Scholar
  3. 3.
    Wei, J., et al.: Towards a viable autonomous driving research platform. In: IV Intelligent Vehicles Symposium (2013)Google Scholar
  4. 4.
    Kuderer, M., Gulati, S., Burgard, W.: Learning driving styles for autonomous vehicles from demonstration. In: IEEE International Conference on Robotics & Automation (ICRA), Seattle (2015)Google Scholar
  5. 5.
    Cowan Schwartz, R.: More Work for Mother: The Ironies of Household Technology from the Open Hearth to the Microwave. Basic Books, New York (1983)Google Scholar
  6. 6.
    Norman, D.: The Design of Everyday Things. Doubleday, New York (1990)Google Scholar
  7. 7.
    Lyytinen, K., Rose, G.: Disruptive information system innovation: the case of internet computing. Inf. Syst. J. 13, 301–330 (2003)CrossRefGoogle Scholar
  8. 8.
    Lyytinen, K., Rose, G.: The disruptive nature of it innovations: the case of internet computing in systems development organizations. MIS Q. 27(4), 557–595 (2003b)Google Scholar
  9. 9.
    Christensen, C.: The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. Harvard Business School Press, Cambridge (1997)Google Scholar
  10. 10.
    Seba, T.: Clean Disruption of Energy and Transportation. Milton Keynes (2014)Google Scholar
  11. 11.
    Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage. Sci. 46(2), 186–204 (2000)CrossRefGoogle Scholar
  12. 12.
    Venkatesh, V., Thong, J.Y.L., Xu, X.: Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q. 36(1), 157–178 (2012)Google Scholar
  13. 13.
    Fishbein, M., Ajzen, I.: Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Addison-Wesley, Reading (1975)Google Scholar
  14. 14.
    Davis, F.D., Bagozzi, R., Warshaw, P.: User acceptance of computer technology: a comparison of two theoretical models. Manage. Sci. 35, 982–1003 (1989). doi: 10.1287/mnsc.35.8.982 CrossRefGoogle Scholar
  15. 15.
    Davis, F., Bagozzi, R., Warshaw, P.: Extrinsic and intrinsic motivation to use computers in the workplace. J. Appl. Soc. Psychol. 22(14), 1111–1132 (1992)CrossRefGoogle Scholar
  16. 16.
    Ajzen, I.: Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. J. Appl. Soc. Psychol. 32, 665–683 (2002)CrossRefGoogle Scholar
  17. 17.
    Taylor, S., Todd, P.: Assessing it usage: the role of prior experience. MIS Q. 19(4), 561–570 (1995a)Google Scholar
  18. 18.
    Taylor, S., Todd, P.: Understanding information technology usage: a test of competing models. Inf. Syst. Res. 6, 144–176 (1995b)Google Scholar
  19. 19.
    Thompson, R.L., Higgins, C.A., Howell, J.M.: Personal computing: toward a conceptual model of utilization. MIS Q. 15(1), 125–143 (1991)CrossRefGoogle Scholar
  20. 20.
    Moore, G.C., Benbasat, I.: Development of an instrument to measure the perceptions of adopting an information technology innovation. Inf. Syst. Res. 2(3), 192–222 (1991)CrossRefGoogle Scholar
  21. 21.
    Compeau, D.R., Higgins, C.A., Huff, S.: Social cognitive theory and individual reactions to computing technology: a longitudinal study. MIS Q. 23(2), 145–158 (1999)CrossRefGoogle Scholar
  22. 22.
    San Martin, H., Herrero, A.: Influence of the user’s psychological factors on the online purchase intention in rural tourism: integrating innovativeness to the UTAUT framework. Tourism Manage. 33(2), 341–350 (2012). doi: 10.1016/j.tourman.2011.04.003 CrossRefGoogle Scholar
  23. 23.
    Gruzd, A., Staves, K., Wilk, A.: Connected scholars: examining the role of social media in research practices of faculty using the UTAUT model. Comput. Hum. Behav. 28, 2340–2350 (2012)CrossRefGoogle Scholar
  24. 24.
    World Health Organization, World report on road traffic injury prevention, Geneva (2004). Accessed 26 June 2015
  25. 25.
    Garvin, A.D., Roberto, A.M.: Change through persuasion. Harvard Bus. Rev. 83, 104–112 (2005)Google Scholar
  26. 26.
    KPMG. Connected and Autonomous Vehicles - The Economic opportunity, s.l., SMMT Driving the motor industry (2015)Google Scholar
  27. 27.
    Stanley, M.: Autonomous Cars: Self-Driving the New Auto Industry Paradigm, s.l., Morgan Stanley Blue paper (2013)Google Scholar
  28. 28.
    Hoogendoorn, R., et al.: Towards safe and efficient driving through vehicle automation: the Dutch automated vehicle initiative (2013)Google Scholar
  29. 29.
    Jóhannesson, G.T.: Tourism translations, actor-network theory and tourism research. Tourist Stud. 5(2), 133–150 (2005)CrossRefGoogle Scholar
  30. 30.
    Rhodes, J.: Using actor-network theory to trace an ICT (telecenter) implementation trajectory in an African women’s micro-enterprise development organization. USC Annenberg School for Communication 5(3), pp. 1–20 (2009)Google Scholar
  31. 31.
    Alcadipani, R., Hassard, J.: Actor-network theory, organizations and critique: towards a politics of organizing. Organization 17(4), 419–435 (2010)CrossRefGoogle Scholar
  32. 32.
    Arnaboldi, M., Spiller, N.: Actor-network theory and stakeholder collaboration: the case of cultural districts. Tourism Manage. 32(3), 641–654 (2011)CrossRefGoogle Scholar
  33. 33.
    Cohen, E., Cohen, S.A.: Current sociological theories and issues in tourism. Annals of Tourism Research (2012).
  34. 34.
    Latour, B.: Reassembling the Social: An Introduction to Actornetwork-Theory. Clarendon Lectures in Management Studies. Oxford University Press, New York (2005)Google Scholar
  35. 35.
    Latour, B.: The Powers of association. In: Law, J. (ed) Power, action and belief: A new Sociology of Knowledge? Sociological Review Monograph, vol. 32, pp. 264–280. Routledge & Kegan Paul, London (1986)Google Scholar
  36. 36.
    Latour, B.: The prince for machines as well as for machinations. In: Elliott, B. (ed) Technology and Social Process. Edinburgh University Press, Edinburgh, pp. 20–43 (1988b)Google Scholar
  37. 37.
    Latour, B.: Technology is society made durable. In: Law, J. (ed.) A Sociology of Monsters. Essays on Power, Technology and Domination, pp. 103–131. Routledge, London (1991)Google Scholar
  38. 38.
    Latour, B.: We Have Never Been Modern. Harvester Wheatsheaf, Hemel Hempstead (1993)Google Scholar
  39. 39.
    Latour, B.: On actor-network theory—a few clarifications. Soziale Welt-Zeitschrift fur Sozialwissenschaftliche forschung und praxis 47(4), 369 (1996)Google Scholar
  40. 40.
    Latour, B., Woolgar, S.: Laboratory Life, The Social Construction of Scientific Facts, New Edition edn. Princeton University Press, Princeton (1986)Google Scholar
  41. 41.
    Garrety, K.: Actor Network Theory. In: Hasan, H. (ed.) Being Practical with Theory: A Window into Business Research. University of Wollongong, Wollongong (2014)Google Scholar
  42. 42.
    Callon, M.: Some elements of a sociology of translation: domestication of the scallops and the fishermen of St Brieuc bay’. In: Law, J. (ed) Power, Action & Belief: A New Sociology of Knowledge? Routledge & Kegan Paul, London, pp. 196–229 (1986b)Google Scholar
  43. 43.
    Dolwick, J.S.: The social and beyond: introducing actor-network theory. J. Marit. Archaeol. 4(1), 21–49 (2009)CrossRefGoogle Scholar
  44. 44.
  45. 45.
    Tatnall, A., Burgess, S.: Using actor-network theory to research the implementation of a B-B portal for regional SMEs in Melbourne, Australia. In: 15th Bled Electronic Commerce Conference, Slovenia, 17-19 June (2002)Google Scholar
  46. 46.
    Tatnall, A., Gilding, A.: Actor-network theory and information systems research. In: Proceedings of the 10th Australasian Conference on Information Systems (ACIS), Wellington, Victoria University of Wellington (1999)Google Scholar
  47. 47.
    Van Der Duim, R., Henkens, R.: Wetlands, poverty reduction and sustainable tourism development, opportunities and constraints, Wageningen, the Netherlands, Wetlands International (2007)Google Scholar
  48. 48.
    Paget, E., Dimanche, F., Mounet, J.P.: A tourism innovation case: an actor-network approach. Ann. Tourism Res. 37(3), 828–847 (2010)CrossRefGoogle Scholar
  49. 49.
  50. 50.
    Rodger, K.J.: Wildlife tourism and the natural sciences: bringing them together. Ph.D. Thesis, School of Environmental Science, Division of Science and Engineering, Murdoch University, Perth, Western Australia (2007)Google Scholar
  51. 51.
    McLean, C., Hassard, J.: Symmetrical absence/symmetrical absurdity: critical notes on the production of actor-network accounts. J. Manage. Stud. 41(3), 493–519 (2004). doi: 10.1111/j.1467-6486.2004.00442.x. Publication link:a2df43f6-178d-4c31-88e5-f61c0ebd2d14 Google Scholar
  52. 52.
    Burgess, J., Clark, J., Harrison, C.M.: Knowledge in action: an actor network analysis of a wetland agri-environment scheme. Ecol. Econ. 35(1), 119–132 (2000)CrossRefGoogle Scholar
  53. 53.
    Dodds, W.B., Monroe, K.B., Grewal, D.: Effect of price, brand and store information on buyers’ product evaluations. J. Market. Res. 28(3), 307–319 (1991)CrossRefGoogle Scholar
  54. 54.
    Limayem, M., Hirt, S.G., Cheung, C.M.K.: How habit limits the predictive power of intention: the case of information systems continuance. MIS Q. 31(4), 705–737 (2007)Google Scholar
  55. 55.
    Yi, M.Y., Jackson, J.D., Park, J.S., Probst, J.C.: Understanding information technology acceptance by individual professionals: toward an integrative view. Inf. Manage. 43, 350–363 (2006)CrossRefGoogle Scholar
  56. 56.
    Connor, M.: Automobile sensors may usher in self-driving cars. Ed. Margery Connor. N.p., 26 May 2011. Accessed 09 Sep 2016
  57. 57.
    Olarte, O.: Human error accounts for 90% of road accidents. driver risk management solutions (2011). Accessed 09 Sep 2016

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Patrice Seuwou
    • 1
    • 2
    Email author
  • Ebad Banissi
    • 1
  • George Ubakanma
    • 1
  • Mhd Saeed Sharif
    • 3
  • Ann Healey
    • 2
  1. 1.Division of Computing and Informatics, School of EngineeringLondon South Bank UniversityLondonUK
  2. 2.Department of Digital Innovation and Creative EnterpriseGSM LondonLondonUK
  3. 3.Department of Electronic and Computer EngineeringBrunel University LondonUxbridgeUK

Personalised recommendations