Cogent Business & Management (Dec 2022)

Antecedents and consequences of consumers’ attitudes toward live streaming shopping: an application of the stimulus–organism–response paradigm

  • Chaang-Iuan Ho,
  • Yaoyu Liu,
  • Ming-Chih Chen

DOI
https://doi.org/10.1080/23311975.2022.2145673
Journal volume & issue
Vol. 9, no. 1

Abstract

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The purpose of this paper is to present an integrated model for live streaming shopping (LSS) to examine the antecedents and consequences of consumers’ attitudes. Based on the stimulus–organism–response (S-O-R) paradigm, this study investigates marketing stimuli effects within a live streaming commerce context on viewers’ cognitive and affective states by drawing from their unified knowledge of technology acceptance model (TAM), utilitarian gratification theory (UGT) and the theory of reasoned action (TRA) underpinnings and their subsequent responses. Data collected from 402 live streaming shoppers of several reputable retailers in Mainland China were used to empirically test the proposed framework via structural equation modelling. The theoretical framework found support for most hypothesized relationships. The research results confirm that the 7Ps marketing mix strategies as the stimuli factors positively influence the consumers’ cognitive and emotional states represented by perceived usefulness, perceived value, information gratification, entertainment gratification, and social interaction. These factors have been found to be the direct predictors of consumers’ attitudes toward LSS. Furthermore, consumers’ response in terms of their attitudes influences their intention to watch the show and subsequently affect their purchase intention. This paper bridges a gap in LSS studies, contributing to develop a more comprehensive framework and provide a better understanding of the factors that influence the the formation of consumers’ attitudes, and the influence of the formed attitudes on the intention to engage in LSS before actually making a purchase decision. The findings enable managers to determine how resources should be allocated to improve platform’s competence.

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