Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abicht, L., Brand, L., Freigang, S., Freikamp, H., & Hoffknecht, A. (2010). Internet der Dinge im Bereich Smart House. Retrieved from http://www.frequenz.net/uploads/tx_freqprojerg/Abschlussbericht_Id__im_Smart_House_final.pdf.
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.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Taylor & Francis.
Esposito Vinzi, V., Chin, W. W., Henseler, J., & Wang, H. (2010). Handbook of partial least squares: Concepts, methods and applications. Heidelberg: Springer.
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.
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.
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.
Halaszovich, T. F. (2010). Neuprodukteinführungsstrategien schnelldrehender Konsumgüter: Eine empirische Wirkungsanalyse des Marketing Mix. Wiesbaden: Springer.
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.
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.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory (McGraw-Hill Series in Psychology) (Vol. 3). New York: McGraw-Hill.
Schiller, K. (2018). Was ist ein Smart Home? Geräte und Systeme. Retrieved from http://www.homeandsmart.de/was-ist-ein-smart-home.
Rogers, E. M. (1983). Diffusion of innovations, New York: Free Press.
Splendid Research (2017). Smart Home Monitor Deutschland 2017. Retrieved from https://de.statista.com/statistik/daten/studie/757023/umfrage/interesse-an-smart-home-anwendungen-nach-geschlecht-in-deutschland/.
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.
Verbraucherzentrale Rheinland-Pfalz (2016). Vierten Verbraucherdialog „Smart Home“ – Chancen nutzen, Risiken minimieren. Retrieved from https://mjv.rlp.de/fileadmin/mjv/Themen/Verbraucherschutz/Ergebnispapier_mit_Empfehlungen_zum_Verbraucher__und_Datenschutz_bei_Smart_Home_Angeboten_fuer_Anbieter_sowie_Verbraucherinnen_und_Verbraucher_.pdf.
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.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature
About this chapter
Cite this chapter
Salomon, G., Müller, P. (2019). Success Factors for the Acceptance of Smart Home Technology Concepts. In: Lochmahr, A., Müller, P., Planing, P., Popović, T. (eds) Digitalen Wandel gestalten. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-24651-8_6.3
Download citation
DOI: https://doi.org/10.1007/978-3-658-24651-8_6.3
Publisher Name: Springer Gabler, Wiesbaden
Print ISBN: 978-3-658-24650-1
Online ISBN: 978-3-658-24651-8
eBook Packages: Business and Economics (German Language)