Trust development in live streaming commerce: interaction-based building mechanisms and trust transfer perspective

Purpose Live streaming commerce has emerged as an essential strategy for vendors to effectively promote their products due to its unique content presentation and real-time interaction. This study aims to investigate the influence of viewer-streamer interaction and viewer-viewer interaction on consumer trust and the subsequent impact of trust on consumers' purchase intention within the live streaming commerce context. Design/methodology/approach A survey questionnaire was conducted to collect data, and 403 experienced live streaming users in China were recruited. Covariance-based structural equation modeling (CB-SEM) was used for data analysis. Findings The results indicated that viewer-streamer interaction factors (i.e., personalization and responsiveness) and viewer-viewer interaction factors (i.e., co-viewer involvement and bullet-screen mutuality) significantly influence trust in streamers and co-viewers. Additionally, drawing on trust transfer theory, trust in streamers and co-viewers positively influences trust in products, while trust in co-viewers also positively influences both trust in streamers and products. Furthermore, all three forms of trust positively impact consumers' purchase intentions. Originality/value This study enriches the extant literature by investigating interaction-based trust-building mechanisms and uncovering the transfer relationships among three trust targets (streamers, co-viewers and products). Furthermore, this study provides some practical guidelines to the streamers and practitioners for promoting consumers’ trust and purchase intention in live streaming commerce.

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Publication Details

Journal
Industrial Management & Data Systems
Published
2024-08-26
DOI
https://doi.org/10.1108/imds-09-2023-0633
Citations
19
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
19.97
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article

Trust development in live streaming commerce: interaction-based building mechanisms and trust transfer perspective

Yaobin Lu, Yanhong Chen, Aihui Chen, Man Li
19 citations
Industrial Management & Data Systems
Technology Adoption and User Behaviour
19.97
article

Trust development in live streaming commerce: interaction-based building mechanisms and trust transfer perspective

Yaobin Lu, Yanhong Chen, Aihui Chen, Man Li
article en
19 citations

Abstract

Purpose Live streaming commerce has emerged as an essential strategy for vendors to effectively promote their products due to its unique content presentation and real-time interaction. This study aims to investigate the influence of viewer-streamer interaction and viewer-viewer interaction on consumer trust and the subsequent impact of trust on consumers' purchase intention within the live streaming commerce context. Design/methodology/approach A survey questionnaire was conducted to collect data, and 403 experienced live streaming users in China were recruited. Covariance-based structural equation modeling (CB-SEM) was used for data analysis. Findings The results indicated that viewer-streamer interaction factors (i.e., personalization and responsiveness) and viewer-viewer interaction factors (i.e., co-viewer involvement and bullet-screen mutuality) significantly influence trust in streamers and co-viewers. Additionally, drawing on trust transfer theory, trust in streamers and co-viewers positively influences trust in products, while trust in co-viewers also positively influences both trust in streamers and products. Furthermore, all three forms of trust positively impact consumers' purchase intentions. Originality/value This study enriches the extant literature by investigating interaction-based trust-building mechanisms and uncovering the transfer relationships among three trust targets (streamers, co-viewers and products). Furthermore, this study provides some practical guidelines to the streamers and practitioners for promoting consumers’ trust and purchase intention in live streaming commerce.

Industrial Management & Data SystemsVol. 124(12)
Tianjin University (CN), Guangdong University Of Finances and Economics (CN), Guangdong University of Finance (CN), Huazhong University of Science and Technology (CN)
Partnerships for the goals
Openalex Percentile: Top 1%
Technology Adoption and User Behaviour
19.97
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