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Predicting intention to purchase on group buying website in Taiwan: Virtual community, critical mass and risk

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Abstract:

Purpose ‐ This study proposes integrating the perceived risk and social influence literatures on online group buying (OGB) intentions with the basic TAM variables (perceived usefulness and perceived ease of use). Design/methodology/approach ‐ Based on an empirical survey of 304 online adopters of OGB in Taiwan, the paper uses structural equation modeling to confirm the research model. Findings ‐ The results reveal that perceived critical mass had the largest total effect on intention to use group buying websites. The findings also indicate that perceived usefulness and a sense of virtual community (SOVC) have significant effect on OGB intention. In addition, both perceived ease of use and website quality influence perceived usefulness. As expected, perceived risk has negative effect on OGB intention. Research limitations/implications ‐ This study only considered buying intention with regard to foodstuffs, and it is unclear whether these analytical results can be generalized to other items. Further research could apply this model to examine group coupons (such as discount vouchers for restaurants). Practical implications ‐ To sustain a successful group buying website, attention must be paid to enhancing user's SOVC, enlarging the critical mass, and lowering the perceived risk. Practitioners can apply the findings of this study to focus on the determinants of success for their online shopping websites. Originality/value ‐ Theoretically, while drawing upon TRA studies, this paper provides a model that is capable of lending an understanding of the determinants of OGB intention. From a managerial perspective, the findings indicate that webmasters can improve or manage website members' buying intentions by increasing the sense of virtual community and critical mass.

Keywords: Internet; Online group buying; Perceived critical mass; Perceived risk; Purchasing intention; Social networks; Technology acceptance model

Document Type: Research Article

DOI: https://doi.org/10.1108/14684521211275984

Publication date: 2012-09-21

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