IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v197y2023ics0040162523006091.html
   My bibliography  Save this article

Determinants of smart home adoption and differences across technology readiness segments

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162523006091
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2023.122924?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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).
    2. 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.
    3. Alladi Venkatesh, 2008. "Digital home technologies and transformation of households," Information Systems Frontiers, Springer, vol. 10(4), pages 391-395, September.
    4. 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).
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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).
    16. 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.
    17. 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.
    18. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Attié, Elodie & Meyer-Waarden, Lars, 2022. "The acceptance and usage of smart connected objects according to adoption stages: an enhanced technology acceptance model integrating the diffusion of innovation, uses and gratification and privacy ca," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    3. Große-Kreul, Felix, 2022. "What will drive household adoption of smart energy? Insights from a consumer acceptance study in Germany," Utilities Policy, Elsevier, vol. 75(C).
    4. Wenqing Zhang & Liangliang Liu, 2022. "How consumers’ adopting intentions towards eco-friendly smart home services are shaped? An extended technology acceptance model," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 68(2), pages 307-330, April.
    5. Sven Laumer & Andreas Eckhardt & Natascha Trunk, 2010. "Do as your parents say?—Analyzing IT adoption influencing factors for full and under age applicants," Information Systems Frontiers, Springer, vol. 12(2), pages 169-183, April.
    6. Elodie Attié & Lars Meyer-Waarden, 2022. "The acceptance and usage of smart connected objects according to adoption stages: an enhanced technology acceptance model integrating the diffusion of innovation, uses and gratification and privacy ca," Post-Print hal-04065165, HAL.
    7. Ferreira, Laura & Oliveira, Tiago & Neves, Catarina, 2023. "Consumer's intention to use and recommend smart home technologies: The role of environmental awareness," Energy, Elsevier, vol. 263(PC).
    8. Fleiß, Eva & Hatzl, Stefanie & Rauscher, Jürgen, 2024. "Smart energy technology: A survey of adoption by individuals and the enabling potential of the technologies," Technology in Society, Elsevier, vol. 76(C).
    9. Schniederjans, Dara G., 2017. "Adoption of 3D-printing technologies in manufacturing: A survey analysis," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 287-298.
    10. Lee, Jiyoon & Ryu, Min Ho & Lee, Daeho, 2019. "A study on the reciprocal relationship between user perception and retailer perception on platform-based mobile payment service," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 7-15.
    11. Odou, Philippe & Schill, Marie, 2020. "How anticipated emotions shape behavioral intentions to fight climate change," Journal of Business Research, Elsevier, vol. 121(C), pages 243-253.
    12. Gao, Tao (Tony) & Rohm, Andrew J. & Sultan, Fareena & Pagani, Margherita, 2013. "Consumers un-tethered: A three-market empirical study of consumers' mobile marketing acceptance," Journal of Business Research, Elsevier, vol. 66(12), pages 2536-2544.
    13. Muhammad Ishfaq Khan & Shahbaz Khalid & Umer Zaman & Ana Ercília José & Paulo Ferreira, 2021. "Green Paradox in Emerging Tourism Supply Chains: Achieving Green Consumption Behavior through Strategic Green Marketing Orientation, Brand Social Responsibility, and Green Image," IJERPH, MDPI, vol. 18(18), pages 1-24, September.
    14. Pal, Debajyoti & Zhang, Xiangmin & Siyal, Saeed, 2021. "Prohibitive factors to the acceptance of Internet of Things (IoT) technology in society: A smart-home context using a resistive modelling approach," Technology in Society, Elsevier, vol. 66(C).
    15. Ingrid Moons & Patrick De Pelsmacker, 2015. "An Extended Decomposed Theory of Planned Behaviour to Predict the Usage Intention of the Electric Car: A Multi-Group Comparison," Sustainability, MDPI, vol. 7(5), pages 1-34, May.
    16. Wan Nie & Antonieta Medina-Lara & Hywel Williams & Richard Smith, 2021. "Do Health, Environmental and Ethical Concerns Affect Purchasing Behavior? A Meta-Analysis and Narrative Review," Social Sciences, MDPI, vol. 10(11), pages 1-24, October.
    17. 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.
    18. W. Lasarov & S. Hoffmann & R. Mai & J. Schleich, 2024. "Carbon footprint tracking apps: The spillover effects of feedback and goal-activating appeals," Post-Print hal-04689730, HAL.
    19. Raphael Iten & Joël Wagner & Angela Zeier Röschmann, 2021. "On the Identification, Evaluation and Treatment of Risks in Smart Homes: A Systematic Literature Review," Risks, MDPI, vol. 9(6), pages 1-30, June.
    20. Li, Wenda & Yigitcanlar, Tan & Liu, Aaron & Erol, Isil, 2022. "Mapping two decades of smart home research: A systematic scientometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 179(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:197:y:2023:i:c:s0040162523006091. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.