Modeling Consumers’ Usage Intention of Augmented Reality in Online Buying Context: Empirical Setting with Measurement Development

Citation

Shah Alam, Syed and Masukujjaman, Mohammad and Sayeed, Md. Shohel and Omar, Nor Asiah and Ayob, Abu Hanifah and Wan Hussain, Wan Mohd Hirwani (2022) Modeling Consumers’ Usage Intention of Augmented Reality in Online Buying Context: Empirical Setting with Measurement Development. Journal of Global Marketing. pp. 1-24. ISSN 0891-1762

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Abstract

The main objective of this study is to identify the factors that affect consumers’ intention to use AR for their online buying context. This study integrated three theories with additional constructs of perceived enjoyment and personal innovativeness. Data was collected through a personal-administered questionnaire from 265 respondents. In this study, PLS based Structural Equation Modeling was used to analyze the data. The study results show that all the estimated relationships were found significant and positive except the relationship between social identity and attitude, social identity and perceived usefulness, and personal innovativeness and perceived ease of use. Attitude significantly and positively mediates the association between two constructs of the Technology Acceptance Model (TAM) and behavioral intention. The findings of this study also reveal that self-efficacy significantly moderates the association between attitude and behavioral intention. This study validated a new model developed for examining the intention to use augmented reality in the online buying context. Here, a model is developed by integrating the Technology Acceptance Model (TAM), Social Identity Theory, and Self-identity Theory with additional constructs of perceived enjoyment and personal innovativeness. This study will contribute to the knowledge extension of using augmented reality in the online buying context.

Item Type: Article
Uncontrolled Keywords: Augmented reality, online buying, empirical study
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 02 Aug 2022 00:24
Last Modified: 02 Aug 2022 00:24
URII: http://shdl.mmu.edu.my/id/eprint/10273

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