Success Factors for the Acceptance of Smart Home Technology Concepts

  • Gabriela Salomon
  • Patrick Müller


Digitalization changes consumer markets rapidly. There is an increasing focus on technological innovations as well as concepts that improve daily routines and offer support for self-determined living. Various technology companies have recognized this need and developed different types of hard- and software products, so-called Smart Home (SH) technology. In Germany, the SH technology market is still in its infancy. To increase market success, there is a need to understand which factors influence the acceptance of those products. In this study, the acceptance of different SH concepts was examined, using the framework of the Unified Theory of Acceptance and Use of Technology (UTAUT). In a field experiment with 496 participants, acceptance models for two different SH concepts were assessed. The results of the empirical study suggest that the UTAUT is a valid framework for modelling the acceptance of SH technology. Overall success factors for the acceptance are Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions. While there was no difference in the overall structure of the UTAUT models for the different SH concepts, distinct strengths emerged. Theoretical as well as practical implications of these findings for the marketing of SH products are discussed.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Abicht, L., Brand, L., Freigang, S., Freikamp, H., & Hoffknecht, A. (2010). Internet der Dinge im Bereich Smart House. Retrieved from
  2. Birchley, G., Huxtable, R., Murtagh, M., Ter Meulen, R., Flach, P., & Gooberman-Hill, R. (2017). Smart Homes, private homes? An empirical study of technology researchers’ perceptions of ethical issues in developing smart-home health technologies. BMC medical ethics, 18(1), 23.Google Scholar
  3. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Taylor & Francis.Google Scholar
  4. Esposito Vinzi, V., Chin, W. W., Henseler, J., & Wang, H. (2010). Handbook of partial least squares: Concepts, methods and applications. Heidelberg: Springer.Google Scholar
  5. Ghalandari, K. (2012). The effect of performance expectancy, effort expectancy, social influence and facilitating conditions on acceptance of e-banking services in Iran: The moderating role of age and gender. Middle-East Journal of Scientific Research, 12(6), 801–807.Google Scholar
  6. Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks: Sage.Google Scholar
  7. Hair, J. F., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26(2), 106–121.Google Scholar
  8. Halaszovich, T. F. (2010). Neuprodukteinführungsstrategien schnelldrehender Konsumgüter: Eine empirische Wirkungsanalyse des Marketing Mix. Wiesbaden: Springer.Google Scholar
  9. Hulland, J. (1999). Use of Partial Least Squares (PLS) in Strategic Management Research: A Review of Four Recent Studies. Strategic Management Journal, 20, 195–204.Google Scholar
  10. Kazanli, S. (2016). Smart Home – Internet der Dinge im privaten Umfeld – Konzeption und Entwurf eines intuitiven Anzeige- & Bedienkonzeptes für eine Medienzentrale eines exemplarischen SH Services (Unpublished bachelor’s thesis). Hochschule der Medien, Stuttgart.Google Scholar
  11. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory (McGraw-Hill Series in Psychology) (Vol. 3). New York: McGraw-Hill.Google Scholar
  12. Schiller, K. (2018). Was ist ein Smart Home? Geräte und Systeme. Retrieved from
  13. Rogers, E. M. (1983). Diffusion of innovations, New York: Free Press.Google Scholar
  14. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 27, 425–478.Google Scholar
  15. Verbraucherzentrale Rheinland-Pfalz (2016). Vierten Verbraucherdialog „Smart Home“ – Chancen nutzen, Risiken minimieren. Retrieved from
  16. Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). The new organizing logic of digital innovation: an agenda for information systems research. Information Systems Research, 21, 724–735.Google Scholar

Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019

Authors and Affiliations

  • Gabriela Salomon
    • 1
  • Patrick Müller
    • 2
  1. 1.University of Applied SciencesStuttgartDeutschland
  2. 2.University of UtrechtUtrechtNederland

Personalised recommendations