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Wearable Technology Adoption Among Romanian Students: A Structural Model Based on TAM

Author

Listed:
  • Mihai Felea

    (Bucharest University of Economic Studies, Romania)

  • Mihaela Bucur

    (Bucharest University of Economic Studies, Romania)

  • Cristian Negru?iu

    (Bucharest University of Economic Studies, Romania)

  • Maria Ni?u

    (Bucharest University of Economic Studies, Romania)

  • Drago? Andrei Stoica

    (Bucharest University of Economic Studies, Romania)

Abstract

The Internet of Things (IoT) has gained particular attention, both from academia and from companies and industries, as a result of its characteristics and the opportunities that this technology generates for end-users and for the business environment. Thus, the creation of this network that connects the objects around us allowed optimization and improvement of activities in various fields. The adaptation and deployment of IoT in wearable smart devices has created an important market, due to the popularity, the functionality and the use of these devices in various professional and everyday activities. The purpose of this paper was to examine the adoption of wearable technology in the broader context of the development of innovations and technologies in the field of IoT. A new theoretical model based on Technology Acceptance Model (TAM) was developed and tested to identifying the relations between factors influencing the attitude towards use and the intention to use of wearable devices. A survey carried out on Romanian students provided the necessary data to test the model. The results of Structural Equation Modelling (SEM), based on the Partial Least Squares (PLS) method, led to the acceptance of eight out of the nine issued hypotheses, indicating that the three exogenous variables (perceived usefulness, perceived enjoyment and visual attractiveness of wearable devices) have a significant positive influence (with one exception) on endogenous variables (intention to use and attitude towards the use of wearable devices).

Suggested Citation

  • Mihai Felea & Mihaela Bucur & Cristian Negru?iu & Maria Ni?u & Drago? Andrei Stoica, 2021. "Wearable Technology Adoption Among Romanian Students: A Structural Model Based on TAM," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(57), pages 376-376.
    • Handle: RePEc:aes:amfeco:v:23:y:2021:i:57:p:376
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    References listed on IDEAS

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    1. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    2. Dragos TOHANEAN & Sorin-George TOMA & Ionel DUMITRU, 2018. "Organizational Performance and Digitalization in Industry 4.0," Journal of Emerging Trends in Marketing and Management, The Bucharest University of Economic Studies, vol. 1(1), pages 282-288, November.
    3. Nascimento, Bruno & Oliveira, Tiago & Tam, Carlos, 2018. "Wearable technology: What explains continuance intention in smartwatches?," Journal of Retailing and Consumer Services, Elsevier, vol. 43(C), pages 157-169.
    4. Lee, Yong-Ki & Park, Jong-Hyun & Chung, Namho & Blakeney, Alisha, 2012. "A unified perspective on the factors influencing usage intention toward mobile financial services," Journal of Business Research, Elsevier, vol. 65(11), pages 1590-1599.
    5. 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.
    6. 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.
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    Cited by:

    1. Andreea Simona Saseanu & Rodica-Manuela Gogonea & Simona Ioana Ghita, 2024. "The Social Impact of Using Artificial Intelligence in Education," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(65), pages 1-89, February.

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    More about this item

    Keywords

    Wearable Devices; Internet of Things (IoT); Technology Adoption; Technology Acceptance Model (TAM); Structural Equation Modelling (SEM); Partial Least Squares (PLS);
    All these keywords.

    JEL classification:

    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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