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Determinants of smart home adoption and differences across technology readiness segments

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  • Basarir-Ozel, Birgul
  • Nasir, V. Aslihan
  • Turker, Hande B.

Abstract

Smart home technologies (SHTs) encompass a wide range of products and services that fulfill users' needs and wants regarding the enhancement of the quality and comfort of their daily lives. Despite the pervasive impact of these technologies, SHT penetration is still growing at a relatively slow pace. A prominent reason of this might be inadequate understanding of the factors that motivate consumers to embrace SHTs. However, it is difficult to explain the adoption of SHTs with a replication of traditional adoption models due to differences in contextual factors. In addition, existing models solely use conventional adoption variables from the consumer perspective and exclude the business viewpoint. Hence, to fill this gap, initially, in-depth interviews with industry experts have been conducted and some predictive variables that were not mentioned in the literature have been identified. Consequently, these variables were used to enrich the existing diffusion of innovation (DOI) model and offer an extended SHT adoption framework. Based on this framework, value superiority, consumer protection, design & reputation, enjoyment, complexity, and compatibility have been extracted through exploratory factor analysis (EFA) as the dimensions of SHT adoption. However, the relative impact of these dimensions may be different for distinct consumer segments. To identify these differences and better design marketing and communication efforts, it is crucial to consider different characteristics of user segments and cohorts. For this purpose, users were classified into meaningful segments based on Technology Readiness Index (TRI) 2.0. Therefore, first, the TRI 2.0 variables were grouped into two categories as technology motivators and technology inhibitors after running another EFA. Based on these two dimensions, users were grouped under three segments after cluster analysis as Tech Savvies, Tech Yin-Yangers, and Tech Mediocres. Ultimately, the final objective of this research is to discover the differences among these segments in terms of their attitude toward and intention to adopt SHTs. Subsequently, independent regression analyses have been run to figure out the relative impact of the six dimensions of SHT adoption on attitude toward and intention to adopt SHTs for three different clusters. It is observed that there are significant differences among these segments that signal the vital importance of treating these consumer groups in distinct ways.

Suggested Citation

  • Basarir-Ozel, Birgul & Nasir, V. Aslihan & Turker, Hande B., 2023. "Determinants of smart home adoption and differences across technology readiness segments," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    • Handle: RePEc:eee:tefoso:v:197:y:2023:i:c:s0040162523006091
    DOI: 10.1016/j.techfore.2023.122924
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    1. Hsu, Chin-Lung & Lu, Hsi-Peng & Hsu, Huei-Hsia, 2007. "Adoption of the mobile Internet: An empirical study of multimedia message service (MMS)," Omega, Elsevier, vol. 35(6), pages 715-726, December.
    2. Schill, Marie & Godefroit-Winkel, Delphine & Diallo, Mbaye Fall & Barbarossa, Camilla, 2019. "Consumers’ intentions to purchase smart home objects: Do environmental issues matter?," Ecological Economics, Elsevier, vol. 161(C), pages 176-185.
    3. Wei Gu & Peng Bao & Wenyuan Hao & Jaewoong Kim, 2019. "Empirical Examination of Intention to Continue to Use Smart Home Services," Sustainability, MDPI, vol. 11(19), pages 1-12, September.
    4. Franceschinis, Cristiano & Thiene, Mara & Scarpa, Riccardo & Rose, John & Moretto, Michele & Cavalli, Raffaele, 2017. "Adoption of renewable heating systems: An empirical test of the diffusion of innovation theory," Energy, Elsevier, vol. 125(C), pages 313-326.
    5. Ramírez-Correa, Patricio & Grandón, Elizabeth E. & Rondán-Cataluña, F. Javier, 2020. "Users segmentation based on the Technological Readiness Adoption Index in emerging countries: The case of Chile," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    6. Birgul Basarir-Ozel & Hande Bahar Turker & Vesile Aslihan Nasir, 2022. "Identifying the Key Drivers and Barriers of Smart Home Adoption: A Thematic Analysis from the Business Perspective," Sustainability, MDPI, vol. 14(15), pages 1-19, July.
    7. Susan A. Brown & Viswanath Venkatesh & Hartmut Hoehle, 2015. "Technology adoption decisions in the household: A seven-model comparison," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(9), pages 1933-1949, September.
    8. Sovacool, Benjamin K. & Furszyfer Del Rio, Dylan D., 2020. "Smart home technologies in Europe: A critical review of concepts, benefits, risks and policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    9. Jamie Bennett & Osvaldas Rokas & Liming Chen, 2017. "Healthcare in the Smart Home: A Study of Past, Present and Future," Sustainability, MDPI, vol. 9(5), pages 1-23, May.
    10. Yogesh K. Dwivedi & Michael D. Williams & Viswanath Venkatesh, 2008. "Guest Editorial: A profile of adoption of Information & Communication Technologies (ICT) research in the household context," Information Systems Frontiers, Springer, vol. 10(4), pages 385-390, September.
    11. Alladi Venkatesh, 2008. "Digital home technologies and transformation of households," Information Systems Frontiers, Springer, vol. 10(4), pages 391-395, September.
    12. Hong, Areum & Nam, Changi & Kim, Seongcheol, 2020. "What will be the possible barriers to consumers’ adoption of smart home services?," Telecommunications Policy, Elsevier, vol. 44(2).
    13. Tony Woodall & Julie Rosborough & John Harvey, 2018. "Proposal, project, practice, pause: Developing a framework for evaluating smart domestic product engagement," AMS Review, Springer;Academy of Marketing Science, vol. 8(1), pages 58-74, June.
    14. Tsui-Yii Shih, 2013. "Determinates of Consumer Adoption Attitudes: An Empirical Study of Smart Home Services," International Journal of E-Adoption (IJEA), IGI Global, vol. 5(2), pages 40-56, April.
    15. Herbjørn Nysveen & Per Egil Pedersen, 2016. "Consumer adoption of RFID-enabled services. Applying an extended UTAUT model," Information Systems Frontiers, Springer, vol. 18(2), pages 293-314, April.
    16. van Oorschot, Johannes A.W.H. & Hofman, Erwin & Halman, Johannes I.M., 2018. "A bibliometric review of the innovation adoption literature," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 1-21.
    17. Marie Schill & Delphine Godefroit-Winkel & Mbaye Fall Diallo & Camilla Barbarossa, 2019. "Consumers’ intentions to purchase smart home objects: Do environmental issues matter?," Post-Print hal-02091348, HAL.
    18. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    19. Shin, Jungwoo & Park, Yuri & Lee, Daeho, 2018. "Who will be smart home users? An analysis of adoption and diffusion of smart homes," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 246-253.
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