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The influence of Consumers’ Purchase intention on Smart Wearable Device: A study of Consumers in East China

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  • Chen Wei

    (Asia Metropolitan University, Malaysia)

Abstract

In order to better analyze the influencing factors of consumers’ purchase intention of smart wearable devices, this paper uses the technology acceptance model as the theoretical basis, and selects the factors that may have a greater impact on the purchase intention of smart wearable devices as the investigation project. By constructing a theoretical analysis model of consumers’ purchase intention of smart wearable devices, interpret the relationship between the key variables of smart wearable devices and the influence of consumers’ purchase intention, verify the credibility of various assumptions, and propose the development path of China’s smart wearable industry based on the research and analysis results. Specifically, the research contents include the following: (1) According to relevant theories and literature analysis, screen out the influencing factors that affect the usefulness and ease of use of smart wearable devices, and under the framework of the technology acceptance model, analyze the explanatory relationship of the influencing factors that affect consumers to purchase smart wearable devices from two aspects: perceived ease of use and perceived usefulness. (2) With the help of investigation and statistical analysis, the correlation between independent variables and dependent variables that affect the purchase intention of smart wearable devices is discussed. (3) Starting from the personal characteristic attributes of consumers such as age, gender, educational background and income level, the differences between the personal characteristic attributes of consumers and the purchase intention of consumers of smart wearable devices are discussed. The path relationship between independent variables and dependent variables shows that the theoretical analysis model of the purchase intention of smart wearable device consumers constructed in this paper can better analyze the internal influence of the factors affecting the purchase intention of smart wearable device consumers, and help smart wearable device manufacturers and intermediate service providers better understand the key factors affecting the purchase intention of smart wearable device consumers, and guide their product development and marketing activities.

Suggested Citation

  • Chen Wei, 2021. "The influence of Consumers’ Purchase intention on Smart Wearable Device: A study of Consumers in East China," International Journal of Science and Business, IJSAB International, vol. 5(8), pages 46-72.
    • Handle: RePEc:aif:journl:v:5:y:2021:i:8:p:46-72
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    References listed on IDEAS

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    1. Massoud Moslehpour & Van Kien Pham & Wing-Keung Wong & İsmail Bilgiçli, 2018. "e-Purchase Intention of Taiwanese Consumers: Sustainable Mediation of Perceived Usefulness and Perceived Ease of Use," Sustainability, MDPI, vol. 10(1), pages 1-17, January.
    2. Teo, Thompson S. H. & Lim, Vivien K. G. & Lai, Raye Y. C., 1999. "Intrinsic and extrinsic motivation in Internet usage," Omega, Elsevier, vol. 27(1), pages 25-37, February.
    3. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    4. 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.
    5. Roehrich, Gilles, 2004. "Consumer innovativeness: Concepts and measurements," Journal of Business Research, Elsevier, vol. 57(6), pages 671-677, June.
    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. Lee Cronbach, 1951. "Coefficient alpha and the internal structure of tests," Psychometrika, Springer;The Psychometric Society, vol. 16(3), pages 297-334, September.
    8. Rogers, Everett M, 1976. "New Product Adoption and Diffusion," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 2(4), pages 290-301, March.
    9. Lam, Shun Yin & Chiang, Jeongwen & Parasuraman, A., 2008. "The effects of the dimensions of technology readiness on technology acceptance: An empirical analysis," Journal of Interactive Marketing, Elsevier, vol. 22(4), pages 19-39.
    10. 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.
    11. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    12. 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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