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An Internet of Things (IoT) Acceptance Model. Assessing Consumer’s Behavior toward IoT Products and Applications

Author

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  • Maria Tsourela

    (Department of Business Administration, International Hellenic University, 62100 Serres, Greece)

  • Dafni-Maria Nerantzaki

    (Department of Business Administration, International Hellenic University, 62100 Serres, Greece)

Abstract

A common managerial and theoretical concern is to know how individuals perceive Internet of Things (IoT) products and applications and how to accelerate adoption of them. The purpose of the current study is to answer, “What are the factors that define behavioral intention to adopt IoT products and applications among individuals?” An IoT adoption model was developed and tested, incorporating pull factors from two different information impact sources: technical and psychological. This study employs statistical structural equation modeling (SEM) in order to examine the conceptual IoT acceptance model. It is demonstrated that facilitated appropriation, perceived usefulness and perceived ease of use, as mediators, significantly influence consumers’ attitude and behavioral intention towards IoT products and applications. User character, cyber resilience, cognitive instrumentals, social influence and trust, all with different significance rates, exhibited an indirect effect, through the three mediators. The IoT acceptance model (IoTAM) upgrades current knowledge on consumers’ behavioral intention and equips practitioners with the knowledge needed to create successful integrated marketing tactics and communication strategies. It provides a solid base for examining multirooted models for the acceptance of newly formed technologies, as it bridges the discontinuity in migrating from information and communication technologies (ICTs) to IoT adoption studies, causing distortions to societies’ abilities to make informed decisions about IoT adoption and use.

Suggested Citation

  • Maria Tsourela & Dafni-Maria Nerantzaki, 2020. "An Internet of Things (IoT) Acceptance Model. Assessing Consumer’s Behavior toward IoT Products and Applications," Future Internet, MDPI, vol. 12(11), pages 1-23, November.
    • Handle: RePEc:gam:jftint:v:12:y:2020:i:11:p:191-:d:439311
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    as
    1. Rouibah, Kamel & Abbas, Hasan & Rouibah, Samia, 2011. "Factors affecting camera mobile phone adoption before e-shopping in the Arab world," Technology in Society, Elsevier, vol. 33(3), pages 271-283.
    2. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    3. 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.
    4. Joanna Goode, 2010. "Mind the Gap: The Digital Dimension of College Access," The Journal of Higher Education, Taylor & Francis Journals, vol. 81(5), pages 583-618, September.
    5. Ha, Sejin & Stoel, Leslie, 2009. "Consumer e-shopping acceptance: Antecedents in a technology acceptance model," Journal of Business Research, Elsevier, vol. 62(5), pages 565-571, May.
    6. Barbara H. Wixom & Peter A. Todd, 2005. "A Theoretical Integration of User Satisfaction and Technology Acceptance," Information Systems Research, INFORMS, vol. 16(1), pages 85-102, March.
    7. Porter, Constance Elise & Donthu, Naveen, 2006. "Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics," Journal of Business Research, Elsevier, vol. 59(9), pages 999-1007, September.
    8. repec:cup:judgdm:v:5:y:2010:i:5:p:411-419 is not listed on IDEAS
    9. Ostlund, Lyman E, 1974. "Perceived Innovation Attributes as Predictors of Innovativeness," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 1(2), pages 23-29, Se.
    10. Revels, Janeaya & Tojib, Dewi & Tsarenko, Yelena, 2010. "Understanding consumer intention to use mobile services," Australasian marketing journal, Elsevier, vol. 18(2), pages 74-80.
    11. Bernadette Szajna, 1996. "Empirical Evaluation of the Revised Technology Acceptance Model," Management Science, INFORMS, vol. 42(1), pages 85-92, January.
    12. Muslim Amin & Sajad Rezaei & Maryam Abolghasemi, 2014. "User satisfaction with mobile websites: the impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust," Nankai Business Review International, Emerald Group Publishing Limited, vol. 5(3), pages 258-274, July.
    13. 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.
    14. 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.
    15. Alalwan, Ali Abdallah & Baabdullah, Abdullah M. & Rana, Nripendra P. & Tamilmani, Kuttimani & Dwivedi, Yogesh K., 2018. "Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust," Technology in Society, Elsevier, vol. 55(C), pages 100-110.
    16. Heidenreich, Sven & Kraemer, Tobias & Handrich, Matthias, 2016. "Satisfied and unwilling: Exploring cognitive and situational resistance to innovations," Journal of Business Research, Elsevier, vol. 69(7), pages 2440-2447.
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    3. Sudesh Sheoran & Sanket Vij, 2023. "A Consumer-Centric Paradigm Shift in Business Environment with the Evolution of the Internet of Things: A Literature Review," Vision, , vol. 27(4), pages 431-442, August.
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    6. Renata Walczak & Krzysztof Koszewski & Robert Olszewski & Krzysztof Ejsmont & Anikó Kálmán, 2023. "Acceptance of IoT Edge-Computing-Based Sensors in Smart Cities for Universal Design Purposes," Energies, MDPI, vol. 16(3), pages 1-22, January.

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