Search Results (114)

Influencer marketing has emerged as a dominant communication strategy in India’s rapidly expanding digital marketplace, reshaping how brands engage with consumers across social media platforms. Despite growing scholarly attention, existing research remains fragmented across themes such as celebrity endorsements, influencer credibility, consumer engagement, and technology-driven communication practices. This study synthesizes the evolving body of literature on influencer marketing in India using bibliometric mapping, thematic analysis, and Latent Dirichlet Allocation (LDA) topic modeling. The analysis reveals that the field’s intellectual structure is defined by four major research themes and latent topic patterns: celebrity endorsements, influencer credibility, consumer engagement, and technology-driven communication practices. A central outcome of the study is the development of a conceptual framework grounded in Stimulus–Organism–Response (S–O–R) theory that explicitly demonstrates how influencer attributes and digital communication stimuli trigger consumer cognition and behavioral outcomes. The study’s primary theoretical contribution is to integrate the previously disconnected research streams into a cohesive framework, providing a foundation for future theoretical development and scholarly inquiry. This systematic synthesis offers a structured understanding of the specific mechanisms driving influencer marketing in the Indian context. Full article

Artificial intelligence is increasingly used to produce and distribute sustainability-related brand communication, yet its effects on consumer brand perceptions remain insufficiently understood. This study examines AI-enabled green brand communication as a sustainability signalling mechanism and investigates its associations with purchase intention through brand identity, brand aspiration, and brand image, while also considering the moderating role of perceived green authenticity. Data were collected in the United Kingdom between March and May 2025 through an online questionnaire completed by 324 adult social media users familiar with sustainability-related brand communication, and the proposed relationships were examined through reliability, validity, structural path, and moderation analyses. The results show that AI-enabled green brand communication is positively associated with both brand identity and brand aspiration. Brand identity and, more strongly, brand aspiration are positively associated with brand image, while brand image is positively associated with purchase intention. Perceived green authenticity further strengthens the positive associations between AI-enabled green brand communication and both brand identity and brand aspiration. The findings suggest that AI-enabled sustainability communication can support favourable brand evaluations and purchase intentions, but its effectiveness depends on whether consumers perceive the message as authentic, credible, and aligned with the brand’s environmental positioning. Full article

Brands increasingly rely on digital peer communication to promote environmentally friendly products. Whether electronic word-of-mouth (EWOM) actually shifts green purchase intention (GPI), though, is far from settled. Some studies have found no reliable word-of-mouth effect; others have examined green trust and anticipated guilt separately, leaving the joint operation of these parallel mediators poorly specified. This is especially true in Bali, Indonesia, where environmental pressures, heavy social media use, and Tri Hita Karana values coexist. Working under the stimulus–organism–response (SOR) framework, this study tests a dual-mediation model that routes EWOM to GPI through anticipated guilt and green trust among eco-conscious social media users. Survey responses from 393 participants were analysed with partial least squares structural equation modelling (PLS-SEM). EWOM related positively to GPI, directly and through both mediators. Anticipated guilt and green trust each partially mediated the effect, so the mediation was partial rather than full. The EWOM-to-guilt path was the stronger of the two. The EWOM-to-trust path was weaker, yet both mediators connected to GPI at similar strength. This study contributes a dual-pathway SOR specification by incorporating anticipated guilt into digital peer communication within a tourism-heavy cultural setting. Interpreted with caution, the pattern indicates that credible EWOM aimed at greener, more responsible consumption may operate through two mechanisms simultaneously, validating trust and prompting moral anticipation among digitally exposed, eco-conscious consumers. However, this interpretation still needs experimental and longitudinal testing before these relationships can be treated as causal. Full article

Geographical indication (GI) products are often understood through terroir, certification, and branding, yet less attention has been paid to the feedback dynamics through which their market value is amplified and destabilized. This paper applies systems thinking to the post-harvest value–trust subsystem of Xinhui Chenpi, a traditional Chinese aged citrus pericarp product with GI protection, to examine how value amplification and systemic vulnerability emerge through interacting feedback mechanisms. Drawing on 28 semi-structured interviews conducted between September 2023 and December 2024, supplemented by participant observation, policy and standard documents, field-based market observations, and contextual media materials, the study develops a preliminary causal loop diagram (CLD) with 15 endogenous feedback variables, 3 boundary value-input variables, 4 exogenous contextual inputs, and 21 causal links (18 endogenous and 3 value-input). The model identifies two reinforcing loops and two balancing loops through which price expectations, holding incentives, credible circulation supply, perceived scarcity, misrepresentation, and trust erosion interact. The trust-erosion loop shows how premium-driven misrepresentation increases claim uncertainty, weakens open-market consumer trust, reduces credible open-market liquidity, and further contracts credible circulation supply. Buyer exit and delayed supply response operate as limited balancing mechanisms because their effects are segment-dependent and constrained by aging and verification delays. The proposed CLD suggests that high-value mechanisms in aging-dependent GI products may also generate structural vulnerabilities, with implications for managing consumer trust, claim verification, and credible circulation in premium markets. Full article

Food festivals have become important instruments of regional tourism development, destination branding, agricultural promotion, and cultural policy. Yet the authenticity of food festivals is often evaluated through visitor perception or promotional discourse, leaving limited room for scalable assessment across large festival systems. This study develops a Location Quotient (LQ)-based framework for measuring agricultural embeddedness as a supply-side structural condition that can support objective material authenticity claims. Using a dataset of 277 South Korean regional food festivals, the study examines how featured food materials are connected to regional agricultural specialization and how this structural connection compares with budget scale, infrastructure, and material-duplication factors in explaining administrative visitor attendance and portfolio-level governance patterns. The results show that agricultural embeddedness is unevenly distributed across the national festival portfolio. Festival budget is the strongest predictor of log-transformed visitor attendance, whereas agricultural embeddedness is not significantly associated with visitor attendance after budget and infrastructure controls are included. Material-level duplication is useful as a portfolio diagnostic for identifying crowded food categories where place-product credibility may become strategically important. Scenario-based portfolio comparisons provide planning benchmarks suggesting that targeted restructuring and reallocation would be associated with higher average agricultural embeddedness under specified portfolio assumptions, although these scenarios should not be interpreted as causal forecasts. The study contributes to food tourism, event governance, and destination branding research by offering a reproducible way to assess the material grounding of food festival authenticity claims and by shifting policy discussion from festival proliferation toward portfolio quality. Full article

Virtual influencers are increasingly used in influencer marketing, yet it remains unclear whether trust generated by an artificial persona can be transferred to endorsed brands in the same way as trust generated by human influencers. This study examines artificial intelligence (AI)-mediated trust transfer among female consumers by comparing virtual and human influencers across four social media platforms. Drawing on source credibility, parasocial interaction, social presence, trust transfer, and brand attachment perspectives, we propose that influencer type is associated with brand outcomes through three observable social-cue pathways: perceived authenticity, parasocial interaction, and social presence. These cues are expected to be associated with influencer trust, which is then associated with brand trust, brand attachment, purchase intention, and recommendation intention. Using 78,432 female consumer comments from Xiaohongshu, Instagram, Weibo, and Douyin, matched across 12 virtual–human-influencer pairs, we construct text-derived linguistic indicators—proxies rather than validated psychometric constructs—through keyword dictionaries, sentiment classification, and standardized composite scoring. The results show that human influencers are associated with higher perceived authenticity, parasocial interaction, and social presence than virtual influencers. The strongest association in the model is the trust-transfer path from influencer trust to brand trust, and the indirect path is associated with a substantial share of the observed covariation between influencer type and brand attachment. Product type further qualifies these patterns: the human-influencer advantage is stronger for hedonic products than for utilitarian products. These findings suggest that virtual influencers should not be understood as universal substitutes for human influencers. Instead, their effectiveness depends on whether AI-mediated personas can generate the social and authenticity cues that the literature associates with trust transfer in a given product context. Full article

Drawing on signaling theory and a relational perspective, this study examines how perceived influencer credibility is associated with e-loyalty intentions in influencer-mediated social commerce. Rather than claiming that each individual path is theoretically unexpected, this study positions its contribution in specifying a conditional signal-to-relationship process. Specifically, perceived influencer credibility is conceptualized as a credibility-based digital promotional signal, brand trust and customer engagement are examined as sequential relational mechanisms, and perceived brand authenticity is positioned as an identity-consistency boundary condition in the customer engagement–e-loyalty intention relationship. Using survey data from 372 consumers with influencer-mediated social commerce experience, the data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that perceived influencer credibility is positively associated with brand trust, brand trust is positively associated with customer engagement, and customer engagement is positively associated with e-loyalty intentions. The bootstrapped serial indirect association through brand trust and customer engagement is significant, indicating a trust–engagement pathway linking influencer-mediated promotional credibility to e-loyalty intentions. Perceived brand authenticity also positively moderates the customer engagement–e-loyalty intention relationship. Descriptive conditional indirect estimates further suggest that the indirect association through brand trust and customer engagement is stronger at higher levels of perceived brand authenticity; however, this conditional indirect pattern is interpreted conservatively because bootstrapped confidence intervals for the low and high conditional estimates were not directly available. These findings extend influencer marketing research by shifting attention from isolated credibility effects to a theory-driven process explaining how influencer credibility is associated with e-loyalty intentions through trust, engagement, and authenticity-based boundary conditions. Full article

Business influence increasingly unfolds in platform environments where visibility is ranked, repeated, measured, and monetized. At the same time, many platform interactions have shifted from reciprocal sociality toward creator-centered attention, mediated familiarity, and one-sided attachment. This perspective article develops the concept of parasocial business to explain how business actors convert platform visibility into credibility, trust, advocacy, and commercial value. Drawing on an integrative reading of research on parasociality, platformization, influencer labor, organizational reputation, marketing communication, and creator economies, this paper identifies three linked mechanisms: algorithmic visibility, persona design, and parasocial conversion. The conceptual analysis shows that parasocial business is not simply influencer marketing, personal branding, brand community, or consumer–brand relationship management. Its distinctive feature is the platformed conversion of repeated, persona-based familiarity into business-relevant authority and value. This paper develops the related concept of platformed authority and illustrates it through LinkedIn thought leadership, podcast-based business influence, and B2B expert visibility. This paper contributes to business administration and management research by showing how leadership communication, reputation governance, expert visibility, and organizational influence are increasingly shaped by platform infrastructures and public-facing personae. Full article

This study investigates asymmetric consumer responses to recycled thermoplastics, with a focus on the roles of eco-consciousness, sustainability knowledge, perceived concerns, trust, and value congruence. Using survey data from Hungarian consumers, the study applies linear and binary logistic regression analyses to examine how these factors influence brand perception, willingness to pay, and communication preferences. The results show that economic concerns act as a dominant barrier, significantly reducing both brand evaluations and willingness to pay, while functional concerns play a more limited role. Trust in sustainability communication and positive brand perception emerge as strong predictors of willingness to pay, with brand perception showing a stronger effect. Eco-consciousness consistently influences consumer responses, whereas sustainability knowledge demonstrates more selective and context-dependent effects. In addition, consumers show a clear preference for credible, evidence-based communication, while informal and promotional signals are less effective. Overall, the findings highlight the importance of reducing perceived risk, strengthening brand perception, and aligning sustainability communication with consumer expectations to support the adoption of recycled thermoplastics in the automotive industry. Full article

Despite rapid growth in the AI endorser market, the psychological mechanisms governing their effectiveness remain theoretically fragmented. This study proposes the AHICC (AI–Human Interface in Consumer Cognition) model—integrating the Stereotype Content Model, Uncanny Valley hypothesis, anthropomorphism theory, Source Credibility Model, and Parasocial Interaction theory—to explain consumer responses to AI endorsers. A fully crossed 3 (endorser type: AI vs. hybrid vs. human) × 3 (anthropomorphism level: low vs. moderate vs. high) × 2 (technological transparency: low vs. high) between-subjects factorial experiment (n = 252) was conducted. Twenty-one sub-hypotheses were tested using MANOVA, polynomial regression, SEM, and bootstrap mediation analysis. All 21 sub-hypotheses were supported. AI endorsers outperformed human counterparts on brand attitude and purchase intention. Polynomial regression confirmed an inverted U-shaped Uncanny Valley effect with an optimal anthropomorphism level of 4.7 (7-point scale). High technological transparency attenuated the Uncanny Valley effect by approximately 60%. Dual-pathway mediation through cognitive and affective routes was confirmed, and TRI and product complexity emerged as significant boundary conditions. The AHICC model offers the first comprehensive framework for the AI endorser context, providing theoretically grounded guidance on anthropomorphism calibration, transparency strategy, and product-category-specific endorser selection. Full article

This study examines whether retail social media sentiment and community attention explain daily net capital flows into U.S. spot Bitcoin exchange-traded funds (ETFs), and whether issuer brand visibility conditions that relationship. We construct a balanced panel of $N=10$ ETFs over $T=514$ trading days (January 2024 to January 2026) and combine it with 162,819 cleaned Reddit posts to derive three AI-driven discourse variables: engagement-weighted sentiment, community attention, and a novel issuer-specific BrandScore. Entity fixed-effects regressions show that neither aggregate sentiment nor BrandScore level alone significantly predicts fund-level flows; however, the Sentiment $\times$ BrandScore interaction is significant ($\widehat{\beta }=2.930$, $p=0.038$), indicating that sentiment becomes economically meaningful only when attached to a visible issuer. This interaction survives two-way (entity + date) fixed effects ($p=0.012$) and winsorization ($p=0.004$). Panel quantile regressions reveal distributional heterogeneity in the brand-sentiment channel. Rolling 90-day window estimation confirms the mechanism is episodic, with the interaction achieving significance in 62.8% of subsample windows. These results provide suggestive evidence for a brand-filtered sentiment transmission mechanism in digital asset markets. Full article

Conversational AI agents are now a routine touchpoint in e-commerce customer service, and AI empathy has emerged as the headline humanization strategy for repairing relational damage during service failures. A growing evidence base reports that empathic AI often backfires, because consumers cannot reconcile felt warmth with their lay model of what an artificial agent is. This research asks under what conditions AI empathy can be made credible to consumers. We propose that mechanistic interpretability, operationalized in the present studies as a consumer-facing visualization of an AI agent’s internal emotion-vector activations designed in the style of mechanistic-interpretability research, operates as a costly authenticity signal that rehabilitates empathic AI by enabling an attributional shift along the experience dimension of mind perception. Signaling Theory carries the antecedent stage of the causal chain, where mechanistic interpretability serves as a verifiable cue of computational authenticity. Mind Perception Theory carries the downstream stage, where the authenticated empathy is converted into consumer-brand intimacy. Two between-subjects experiments preceded by a feasibility pilot tested the account on Mainland Chinese consumers recruited via the Credamo online panel. Study 1 used a single-factor design contrasting high versus low AI empathy. Study 2 used a two (AI empathy) by two (mechanistic interpretability) full factorial. Study 1 showed a pattern consistent with high (versus low) AI empathy lowering brand intimacy through reduced perceived authenticity. Study 2 replicated the AI-empathy backfire when interpretability was absent, reversed the sign of the AI-empathy slope on the perceived-authenticity mediator when interpretability was present, and neutralized the negative conditional indirect effect on brand intimacy through perceived authenticity. The findings introduce mechanistic interpretability to consumer-marketing scholarship as a manipulable signaling channel, document a structural reversal in the mediator-stage slope coupled with neutralization of the indirect effect on the relational outcome, and prescribe pairing empathic AI phrasing with mechanistic-transparency design rather than deploying empathy without an accompanying transparency cue. Full article

This study investigates how parasocial interactions with travel influencers shape consumer–brand identification and purchase intention within hospitality-related virtual communities. Grounded in social influence theory and the literature on parasocial interaction, the study examines the mediating roles of perceived information quality and a sense of belonging in influencer-led digital environments. Data were collected from 940 consumers and analyzed using confirmatory factor analysis and structural equation modeling. The findings demonstrate that parasocial interaction significantly enhances perceived information quality and consumers’ sense of belonging to influencer-led virtual communities, thereby strengthening consumer–brand identification and purchase intention. The results further suggest that influencer-led social environments function not only as promotional channels but also as psychologically meaningful communities that shape consumer perceptions and behavioral outcomes. By integrating parasocial interaction, virtual community belonging, and consumer–brand identification within a hospitality context, this study contributes to the growing literature on influencer marketing and digital consumer behavior. Full article

This study examines the effects of digital sustainability orientation on consumers’ responses, with a focus on the roles of digital green innovation and consumer environmental consciousness in shaping green brand advocacy in social media marketing. Drawing on the Resource-Based View, Dynamic Capability perspective, and Signaling theory, the study proposes that sustainability-oriented digital strategies are more effective when translated into visible, credible forms of digital green innovation. Using the quantitative research design, data were collected from a sample of 300 Saudi Arabian consumers who interact with eco-friendly brands and sustainability-related content on digital platforms such as Facebook, WhatsApp, Instagram, and TikTok. The study used purposive and convenience sampling to ensure that participants were aware of sustainability communication online. Data analysis was performed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) to test the measurement and structural models and evaluate the hypotheses. The results show that the direct positive effect of digital sustainability orientation on digital green innovation is high, but there is no direct effect on green brand advocacy. However, digital green innovation fully mediates this relationship, making the importance of tangible innovation even greater in turning sustainability intentions into consumer support. Moreover, consumer environmental consciousness plays a significant moderating role in the relationship between digital sustainability orientation and green brand advocacy, suggesting that the more environmentally conscious consumers are, the more responsive they are to sustainability-driven digital strategies. The study contributes to the available literature on digital sustainability and green marketing by showing that being sustainability-oriented is not enough to encourage consumer advocacy without having credible innovation. Practically speaking, the findings show that organizations must pay attention to innovation-based sustainability initiatives and develop genuine digital communication strategies to attract environmentally conscious consumers. Ultimately, the research serves as a great reminder of the importance of integrating digital innovation, sustainability practices, and consumer engagement as key drivers of strong green brand advocacy. Full article

Interactive digital commerce environments increasingly rely on influencers as algorithmically amplified intermediaries between brands and consumers. However, the process through which influencer attributes translate into brand trust remains theoretically underdeveloped. Drawing on Social Influence Theory and Source Credibility Theory, this study develops a process-based model in which consumer engagement operates as a psychological mechanism linking influencer characteristics, namely credibility, brand alignment, interactivity, and authenticity, to brand trust. Using survey data from 400 active social media users in Lebanon and partial least squares structural equation modeling (PLS-SEM), the findings reveal that all four influencer attributes significantly enhance consumer engagement, which in turn strongly predicts brand trust. Influencer–brand alignment emerges as the strongest driver of engagement, suggesting that value congruence functions as a heuristic cue in interactive digital commerce contexts. By conceptualizing engagement as a trust-internalization mechanism within platform-mediated environments, this study advances electronic commerce theory and provides context-sensitive insight into digital trust formation in emerging markets. Full article