IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-04065165.html
   My bibliography  Save this paper

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 calculus theories

Author

Listed:
  • Elodie Attié
  • Lars Meyer-Waarden

    (TSM - Toulouse School of Management Research - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - CNRS - Centre National de la Recherche Scientifique - TSM - Toulouse School of Management - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse)

Abstract

In today's digitalized world, technologies such as the Internet of Things (IoT) and smart connected objects (SCOs) are moving to the forefront and have given rise to fundamental changes in consumers' daily lives. During the context of COVID-19, the IoT and SCOs enabled people to better deal with the pandemic situation (e.g., control their health or use fitness indicators) (Gupta et al., 2021). The purpose of this study is to explain the acceptance and usage of SCOs and therefore extend the technology acceptance model (TAM; Davis, 1989) with other theories (i.e., uses and gratification, diffusion of innovation, privacy calculus), and thus new antecedents adapted to the SCO context. More specifically, in addition to the TAM's main variables (i.e., perceived usefulness, ease of use, intention to use, real use), we investigate the roles of concepts rarely investigated in innovation and new technology research, such as well-being, social image, privacy concerns, and innovativeness. We also study the differences in the adoption of SCOs between different user adoption stages, such as the early adopters, early majority, and late majority (Rogers, 1983). The data come from 702 respondents surveyed in a longitudinal study over three years of their acceptance and real usage. Structural equation modeling shows that the TAM variables remain relevant in the SCO context. The results show that utilitarian benefits are the main reasons leading to SCO technology acceptance, and well-being and social image lead to higher usage in the long term. However, privacy concerns are the main obstacles to the adoption of SCOs.

Suggested Citation

  • 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.
  • Handle: RePEc:hal:journl:hal-04065165
    DOI: 10.1016/j.techfore.2022.121485
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    References listed on IDEAS

    as
    1. John R. Hauser & Patricia Simmie, 1981. "Profit Maximizing Perceptual Positions: An Integrated Theory for the Selection of Product Features and Price," Management Science, INFORMS, vol. 27(1), pages 33-56, January.
    2. Eric von Hippel, 1986. "Lead Users: A Source of Novel Product Concepts," Management Science, INFORMS, vol. 32(7), pages 791-805, July.
    3. Peter Schmuck & Tim Kasser & Richard Ryan, 2000. "Intrinsic and Extrinsic Goals: Their Structure and Relationship to Well-Being in German and U.S. College Students," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 50(2), pages 225-241, May.
    4. Jong-Chul Oh & Sung-Joon Yoon, 2014. "Predicting the use of online information services based on a modified UTAUT model," Behaviour and Information Technology, Taylor & Francis Journals, vol. 33(7), pages 716-729, July.
    5. Markus Blut & Cheng Wang, 2020. "Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage," Journal of the Academy of Marketing Science, Springer, vol. 48(4), pages 649-669, July.
    6. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    7. Ritu Agarwal & Jayesh Prasad, 1998. "A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology," Information Systems Research, INFORMS, vol. 9(2), pages 204-215, June.
    8. Ritu Agarwal & Michelle Dugas & Guodong (Gordon) Gao & P. K. Kannan, 2020. "Emerging technologies and analytics for a new era of value-centered marketing in healthcare," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 9-23, January.
    9. Muk, Alexander & Chung, Christina, 2015. "Applying the technology acceptance model in a two-country study of SMS advertising," Journal of Business Research, Elsevier, vol. 68(1), pages 1-6.
    10. Nawel Ayadi & Corina Paraschiv & Eric Vernette, 2017. "Increasing consumer well-being: risk as potential driver of happiness," Applied Economics, Taylor & Francis Journals, vol. 49(43), pages 4321-4335, September.
    11. Kieran Mathieson, 1991. "Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior," Information Systems Research, INFORMS, vol. 2(3), pages 173-191, September.
    12. Thomas P. Novak & Donna L. Hoffman, 2019. "Relationship journeys in the internet of things: a new framework for understanding interactions between consumers and smart objects," Journal of the Academy of Marketing Science, Springer, vol. 47(2), pages 216-237, March.
    13. Rauschnabel, Philipp A. & He, Jun & Ro, Young K., 2018. "Antecedents to the adoption of augmented reality smart glasses: A closer look at privacy risks," Journal of Business Research, Elsevier, vol. 92(C), pages 374-384.
    14. Thomas P. Novak & Donna L. Hoffman & Yiu-Fai Yung, 2000. "Measuring the Customer Experience in Online Environments: A Structural Modeling Approach," Marketing Science, INFORMS, vol. 19(1), pages 22-42, May.
    15. Marikyan, Davit & Papagiannidis, Savvas & Alamanos, Eleftherios, 2019. "A systematic review of the smart home literature: A user perspective," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 139-154.
    16. Midgley, David F & Dowling, Grahame R, 1978. "Innovativeness: The Concept and Its Measurement," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 4(4), pages 229-242, March.
    17. 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).
    18. Sheppard, Blair H & Hartwick, Jon & Warshaw, Paul R, 1988. "The Theory of Reasoned Action: A Meta-analysis of Past Research with Recommendations for Modifications and Future Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 15(3), pages 325-343, December.
    19. Jun, Seung-Pyo & Yeom, Jaeho & Son, Jong-Ku, 2014. "A study of the method using search traffic to analyze new technology adoption," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 82-95.
    20. 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.
    21. Donna L Hoffman & Thomas P Novak & Eileen FischerEditor & Robert KozinetsAssociate Editor, 2018. "Consumer and Object Experience in the Internet of Things: An Assemblage Theory Approach," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(6), pages 1178-1204.
    22. Sirgy, M. Joseph, 1985. "Using self-congruity and ideal congruity to predict purchase motivation," Journal of Business Research, Elsevier, vol. 13(3), pages 195-206, June.
    23. Carola Stryja & Gerhard Satzger, 2019. "Digital nudging to overcome cognitive resistance in innovation adoption decisions," The Service Industries Journal, Taylor & Francis Journals, vol. 39(15-16), pages 1123-1139, December.
    24. Tsou, Hung-Tai & Hsu, Sheila Hsuan-Yu, 2015. "Performance effects of technology–organization–environment openness, service co-production, and digital-resource readiness: The case of the IT industry," International Journal of Information Management, Elsevier, vol. 35(1), pages 1-14.
    25. Dorothy Leonard-Barton & Isabelle Deschamps, 1988. "Managerial Influence in the Implementation of New Technology," Management Science, INFORMS, vol. 34(10), pages 1252-1265, October.
    26. Sung S. Kim & Naresh K. Malhotra, 2005. "A Longitudinal Model of Continued IS Use: An Integrative View of Four Mechanisms Underlying Postadoption Phenomena," Management Science, INFORMS, vol. 51(5), pages 741-755, May.
    27. Tomás Escobar-Rodríguez & Mercedes Romero-Alonso, 2014. "The acceptance of information technology innovations in hospitals: differences between early and late adopters," Behaviour and Information Technology, Taylor & Francis Journals, vol. 33(11), pages 1231-1243, November.
    28. Morwitz, Vicki G & Johnson, Eric J & Schmittlein, David C, 1993. "Does Measuring Intent Change Behavior?," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(1), pages 46-61, June.
    29. Jahanmir, Sara F. & Cavadas, Joana, 2018. "Factors affecting late adoption of digital innovations," Journal of Business Research, Elsevier, vol. 88(C), pages 337-343.
    30. Inès Chouk & Zied Mani, 2017. "Drivers of consumers’ resistance to smart products," Post-Print hal-02980400, HAL.
    31. Cassie Mogilner & Jennifer Aaker & Sepandar D. Kamvar, 2012. "How Happiness Affects Choice," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 39(2), pages 429-443.
    32. Mary C. Gilly & Mary Wolfinbarger Celsi & Hope Jensen Schau, 2012. "It Don't Come Easy: Overcoming Obstacles to Technology Use Within a Resistant Consumer Group," Journal of Consumer Affairs, Wiley Blackwell, vol. 46(1), pages 62-89, March.
    33. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    34. Davis, Brennan & Pechmann, Cornelia, 2013. "Introduction to the Special Issue on transformative consumer research: Developing theory to mobilize efforts that improve consumer and societal well-being," Journal of Business Research, Elsevier, vol. 66(8), pages 1168-1170.
    35. Laukkanen, Tommi, 2016. "Consumer adoption versus rejection decisions in seemingly similar service innovations: The case of the Internet and mobile banking," Journal of Business Research, Elsevier, vol. 69(7), pages 2432-2439.
    36. Kim, Jiyeon & Forsythe, Sandra, 2008. "Adoption of Virtual Try-on technology for online apparel shopping," Journal of Interactive Marketing, Elsevier, vol. 22(2), pages 45-59.
    37. Huh, Young Eun & Kim, Sang-Hoon, 2008. "Do early adopters upgrade early? Role of post-adoption behavior in the purchase of next-generation products," Journal of Business Research, Elsevier, vol. 61(1), pages 40-46, January.
    38. Wilson, Charlie & Hargreaves, Tom & Hauxwell-Baldwin, Richard, 2017. "Benefits and risks of smart home technologies," Energy Policy, Elsevier, vol. 103(C), pages 72-83.
    39. Donald L. Amoroso & Scott Hunsinger, 2009. "Measuring the Acceptance of Internet Technology by Consumers," International Journal of E-Adoption (IJEA), IGI Global, vol. 1(3), pages 48-81, July.
    40. Jang, Hyeong Yu & Noh, Mi Jin, 2011. "Customer acceptance of IPTV service quality," International Journal of Information Management, Elsevier, vol. 31(6), pages 582-592.
    41. Nawel Ayadi & Corina Paraschiv & Eric Vernette, 2017. "Increasing consumer well-being: risk as potential driver of happiness," Post-Print halshs-01698318, HAL.
    42. Hsiao, Chun Hua & Yang, Chyan, 2011. "The intellectual development of the technology acceptance model: A co-citation analysis," International Journal of Information Management, Elsevier, vol. 31(2), pages 128-136.
    43. Dekimpe, Marnik G., 2020. "Retailing and retailing research in the age of big data analytics," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 3-14.
    44. 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. 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).
    2. Lars Meyer-Waarden & Julien Cloarec, 2022. "“Baby, you can drive my car”: Psychological antecedents that drive consumers’ adoption of AI-powered autonomous vehicles," Post-Print hal-03385891, HAL.
    3. Meyer-Waarden, Lars & Cloarec, Julien, 2022. "“Baby, you can drive my car”: Psychological antecedents that drive consumers’ adoption of AI-powered autonomous vehicles," Technovation, Elsevier, vol. 109(C).
    4. Huang, Dan & Jin, Xin & Coghlan, Alexandra, 2021. "Advances in consumer innovation resistance research: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    5. Gansser, Oliver Alexander & Reich, Christina Stefanie, 2021. "A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application," Technology in Society, Elsevier, vol. 65(C).
    6. 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.
    7. Seok Chan Jeong & Beom-Jin Choi, 2022. "Moderating Effects of Consumers’ Personal Innovativeness on the Adoption and Purchase Intention of Wearable Devices," SAGE Open, , vol. 12(4), pages 21582440221, November.
    8. 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).
    9. Paolo Franco, 2023. "Older consumers and technology: A critical systematic literature review," AMS Review, Springer;Academy of Marketing Science, vol. 13(1), pages 92-121, June.
    10. Nripendra P. Rana & Yogesh K. Dwivedi & Banita Lal & Michael D. Williams & Marc Clement, 2017. "Citizens’ adoption of an electronic government system: towards a unified view," Information Systems Frontiers, Springer, vol. 19(3), pages 549-568, June.
    11. Avornyo, Philip & Fang, Jiaming & Antwi, Collins Opoku & Aboagye, Michael Osei & Boadi, Evans Asante, 2019. "Are customers still with us? The influence of optimum stimulation level and IT-specific traits on mobile banking discontinuous usage intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 47(C), pages 348-360.
    12. Christopher R. Plouffe & John S. Hulland & Mark Vandenbosch, 2001. "Research Report: Richness Versus Parsimony in Modeling Technology Adoption Decisions—Understanding Merchant Adoption of a Smart Card-Based Payment System," Information Systems Research, INFORMS, vol. 12(2), pages 208-222, June.
    13. Yu-Sheng Kao & Kazumitsu Nawata & Chi-Yo Huang, 2019. "An Exploration and Confirmation of the Factors Influencing Adoption of IoT-Based Wearable Fitness Trackers," IJERPH, MDPI, vol. 16(18), pages 1-31, September.
    14. Kulviwat, Songpol & Bruner II, Gordon C. & Al-Shuridah, Obaid, 2009. "The role of social influence on adoption of high tech innovations: The moderating effect of public/private consumption," Journal of Business Research, Elsevier, vol. 62(7), pages 706-712, July.
    15. Agarwal, Reeti & Rastogi, Sanjay & Mehrotra, Ankit, 2009. "Customers’ perspectives regarding e-banking in an emerging economy," Journal of Retailing and Consumer Services, Elsevier, vol. 16(5), pages 340-351.
    16. Ingrid Gottschalk & Stefan Kirn, 2013. "Cloud Computing As a Tool for Enhancing Ecological Goals?," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(5), pages 299-313, October.
    17. Nan Zhang & Xunhua Guo & Guoqing Chen, 2011. "Why adoption and use behavior of IT/IS cannot last?—two studies in China," Information Systems Frontiers, Springer, vol. 13(3), pages 381-395, July.
    18. Nripendra P. Rana & Yogesh K. Dwivedi & Banita Lal & Michael D. Williams & Marc Clement, 0. "Citizens’ adoption of an electronic government system: towards a unified view," Information Systems Frontiers, Springer, vol. 0, pages 1-20.
    19. Markus Blut & Cheng Wang, 2020. "Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage," Journal of the Academy of Marketing Science, Springer, vol. 48(4), pages 649-669, July.
    20. Małecka, Agnieszka & Mitręga, Maciej & Mróz-Gorgoń, Barbara & Pfajfar, Gregor, 2022. "Adoption of collaborative consumption as sustainable social innovation: Sociability and novelty seeking perspective," Journal of Business Research, Elsevier, vol. 144(C), pages 163-179.

    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:hal:journl:hal-04065165. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.