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Although user stickiness has been studied for several years in the field of live e-commerce, little attention has been paid to the effects of streamer attributes on user stickiness in this field. Rooted in the stimulus-organism-response (S-O-R) theory, this study investigated how streamer attributes influence user stickiness.

The authors obtained 496 valid samples from Chinese live e-commerce users and explored the formation of user stickiness using partial least squares-structural equation modeling (PLS-SEM). Artificial neural network (ANN) was used to capture linear and non-linear relationships and analyze the normalized importance ranking of significant variables, supplementing the PLS-SEM results.

The authors found that attractiveness and similarity positively impacted parasocial interaction (PSI). Expertise and trustworthiness positively impacted perceived information quality. Moreover, streamer-brand preference mediated the relationship between PSI and user stickiness, as well as the relationship between perceived information quality and user stickiness. Compared to PLS-SEM, the predictive ability of ANN was more robust. Further, the results of PLS-SEM and ANN both showed that attractiveness was the strongest predictor of user stickiness.

This study explained how streamer attributes affect user stickiness and provided a reference value for future research on user behavior in live e-commerce. The exploration of the linear and non-linear relationships between variables based on ANN supplements existing research. Moreover, the results of this study have implications for practitioners on how to improve user stickiness and contribute to the development of the livestreaming industry.

The purpose of this paper is to assess the influence mechanism of the word-of-mouth reputation of influencers.

This study explored word-of-mouth reputation from four characteristics of information source of influencers: credibility, professionalism, interactivity and attractiveness. The grounded theory was used to extract the characteristic indicators of influencers and used questionnaire surveys to obtain 218 valid samples. The fuzzy-set qualitative comparative analysis (fsQCA) was used for the configuration analysis.

The results revealed the following: (1) a causal asymmetric correlation exists between the driving mechanism of high word-of-mouth reputation and non-high word-of-mouth reputation; (2) influencers matching high word-of-mouth reputation comprises potential, developmental and almighty types, whereas live streaming influencer matching non-high word-of-mouth reputation comprises elementary and groping types; and (3) all factors must be combined to play a role, and neutral permutations of two solutions were found among the three overall solutions to attain high word-of-mouth reputation; (4) the combination of high user activity and high exposure is the core configuration that results in high word-of-mouth reputation.

This study provides recommendation for consumers, live streamers, brand and e-commerce platform on how to promote the sustainable and healthy development of influencer marketing.

This study focused on elucidating how the characteristics of information source affect the word-of-mouth reputation of influencers and have a reference value for the research on word-of-mouth reputation in the context of live commerce.