Purpose: The purpose of this paper is to assess the influence mechanism of the word-of-mouth reputation of influencers.Design/methodology/approach: 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.Findings: 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.Practical implications: 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.Originality/value: 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.

Purpose: 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.Design/methodology/approach: 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.Findings: 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.Originality/value: 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.

Purpose: Compensatory consumption focuses on the psychological value of products. Special agricultural products have symbolic and social functions that effectively meet psychological needs and stimulate compensatory consumption behavior. The social commerce context not only enriches consumer experience but also influences consumer purchase decisions. This study constructs a model based on the elaboration likelihood model (ELM) and the stimulus-organism-response (SOR) theory to explore the mechanism of compensatory consumption behavior of special agricultural products in a social commerce context.Design/methodology/approach: This study uses a two-stage method of partial least squares structural equation model (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) to analyze 523 valid samples collected through random sampling. PLS-SEM was used to examine the relationships and effects between the variables; fsQCA was used to conduct a cohort analysis between the variables to further reveal the complexity and diversity of compensatory consumption behaviors.Findings: PLS-SEM indicates that product attributes and social affordances influence consumers’ triggering of compensatory consumption behavior for control and belongingness needs. fsQCA shows that there are three different modes, and the satisfaction of belongingness or control needs is a necessary condition for triggering compensatory consumption behavior.Originality/value: There is limited research on compensatory consumption behavior specifically focused on special agricultural products. This study explores the influencing factors and mechanisms of compensatory consumption behavior related to special agricultural products. The occurrence of compensatory consumption behavior is not only influenced by product attributes but also by the social commerce environment. In marketing strategies, it is important to not only consider product characteristics but also pay attention to consumers’ social and psychological needs.

Purpose: Contextual cues have become a hot research topic in the field of mobile consumer behavior, owing to the continuous rise of digital marketing. However, the complex online shopping scene makes it challenging to directly identify the association between the characteristics of contextual cues and consumer behavior. Presently, few studies have only systematically extracted and refined the types and characteristics of contextual cues. The purpose of this study is to explore the types and mechanisms of contextual cues in online shopping scenarios.Design/methodology/approach: This study uses the word2vec algorithm, grounded theory and co-occurrence cluster method, along with online shopping word-of-mouth (WOM) text and consumer behavior theory, in order to explore different types of contextual cues and its efficiency from 5,619 comment corpus.Findings: This study puts forward the following conclusions. (1) From the perspective of online shopping, contextual cues comprise aesthetic perception cues, value perception cues, trust-dependent cues, time perception cues, memory attention cues, spatial perception cues, attribute cues and relationship cues. (2) Based on the online shopping scenarios, contextual cues and their interaction effects exert an effect on consumer satisfaction, recommendation, purchase and return behavior.Originality/value: The study conclusions are helpful to further reveal the deep association between contextual cues and consumer behavior in the process of online shopping, thus providing practical and theoretical enlightenment for enterprises to not only effectively reshape the scene but also promote the consumers' active purchase behavior.