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Augmented reality shopping application usage: The influence of attitude, value, and characteristics of innovation

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  • Jiang, Yi
  • Wang, Xueqin
  • Yuen, Kum Fai

Abstract

Consumers' intentions are crucial to the wide usage of augmented reality shopping applications (ARSAs). Combining innovation diffusion, perceived value, and attitude theories, this study proposes a theoretical model that identifies the antecedents of consumers' innovation to use ARSAs and specifies their interrelationships. A total of 379 consumers were surveyed using questionnaires, and the data were analyzed through confirmatory factor analysis and structural equation modeling. Results show that the effects of the perceived relative advantage, perceived compatibility, and perceived observability on consumers' intentions to use ARSAs are mediated by consumers' attitudes toward ARSAs. In addition, attitudes have an indirect impact on consumers' intentions to use ARSAs through perceived value. Theoretically, this study synthesizes behavioral theories anchored on innovation and marketing to explain consumer's use intention. Managerially, this study provides strategic recommendations for technology companies developing ARSAs and retailers wishing to adopt ARSAs.

Suggested Citation

  • Jiang, Yi & Wang, Xueqin & Yuen, Kum Fai, 2021. "Augmented reality shopping application usage: The influence of attitude, value, and characteristics of innovation," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    • Handle: RePEc:eee:joreco:v:63:y:2021:i:c:s0969698921002861
    DOI: 10.1016/j.jretconser.2021.102720
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    2. Fuyong Lu & Xian Huang & Xintao Wang, 2022. "Willingness to Pay for Mobile Health Live Streaming during the COVID-19 Pandemic: Integrating TPB with Compatibility," Sustainability, MDPI, vol. 14(23), pages 1-22, November.
    3. Lyu, Tu & Chen, Hao & Guo, Yulin, 2023. "Investigating innovation diffusion, social influence, and personal inner forces to understand people's participation in online e-waste recycling," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
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    5. Cheng-Chia Yang & Shang-Yu Yang & Yu-Chia Chang, 2023. "Predicting Older Adults’ Mobile Payment Adoption: An Extended TAM Model," IJERPH, MDPI, vol. 20(2), pages 1-17, January.

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