This paper aims to study how combinations of dimensions in experiential messaging within brand-generated content (BGC) can drive social media engagement behaviors (SMEBs). It adopts a comprehensive approach to experiential messaging, exploring interactions among these dimensions to create effective combinations. The study analyzes a dataset of 1,037 Facebook posts from a tourism resort operator, applying fuzzy-set qualitative comparative analysis (fsQCA). The results reveal that no single experiential dimension is sufficient to drive SMEBs. Instead, three combinations emerge: (1) interpersonal sensitivity-combining sensory and relational messages; (2) passionate soul-integrating sensory, affective, and relational messages; and (3) mindful heart-blending cognitive, sensory, and affective messages. This study advances social media marketing research by demonstrating that experiential messaging should be analyzed holistically. By applying complexity theory and fsQCA, it enhances the understanding of how different dimensions interact to enhance SMEBs, offering actionable insights for both scholars and managers.
This bibliometric review synthesizes the literature in the burgeoning field of artificial intelligence (AI) in marketing. Analyzing 1,878 research publications from the Scopus database, we map the intellectual structure and evolution of this domain. Our analysis identifies the foundational works, leading authors, and key thematic clusters, showing how AI technologies are integrated into marketing strategies and their subsequent impact on performance. The review advances the field by offering a qualitative synthesis that distills core theoretical paradigms and empirical insights on AI applications in business marketing. Building on this analysis, we determine critical research gaps and propose future research directions, presenting a structured framework to guide subsequent inquiries in AI-driven marketing.
Research on Ducoffe's Web Advertising Model spans diverse contexts and rapidly changing digital channels, yet the literature remains fragmented and lacks a comprehensive, theory-driven synthesis. This review addresses these gaps by systematically consolidating two decades of research (1995-2024), integrating bibliometric mapping and thematic analysis within the Target-Antecedent-Consequence-Intervention (TACI) framework. We identify key antecedents (informativeness, entertainment, credibility, personalization), explore context-sensitive extensions, and critically evaluate methodological and empirical trends. Theoretical contributions include clarifying the model's conceptual boundaries, resolving inconsistencies across studies, and proposing directions for future empirical work. Practically, the review delivers actionable guidance demonstrating how ad value drivers vary by platform, audience, and format, and outlining evidence-based strategies for personalization, trust-building, campaign adaptation, and balancing engagement with irritation. These insights support both ongoing academic inquiry and managerial decision-making in digital advertising.
In the past two decades, search engine advertising (SEA) has evolved into a dominant form of digital marketing. Yet academic research in this domain remains fragmented across disciplines, highlighting the need for a comprehensive synthesis. Consequently, this study conducts a theory-context-method framework-based systematic literature review of 122 peer-reviewed articles published between 2021 and 2025, gathered from the Scopus database. The findings reveal a major theoretical deficit, with over 75% of studies lacking a formal framework. Contextually, SEA research clusters heavily within China and the US, leaving developing regions underrepresented and themes like privacy, ad design, and big data underexplored. Methodologically, while approaches range from econometric models to deep learning, quantitative designs heavily dominate (n = 87), leaving qualitative and mixed-methods research scarce. Additionally, this review proposes a future research agenda incorporating various theories (information foraging theory) and methods (goal programming) to advance scholarly and practical SEA understanding.
Brands' self-operated live streaming commerce is a novel marketing approach, yet the mechanisms underlying consumer brand engagement remain unclear. This study draws on Uses and Gratifications theory and employs partial least squares structural equation modeling (PLS-SEM) together with necessary condition analysis (NCA) to examine the antecedents and outcomes of consumer brand engagement within the context of the apparel industry. Using purposive sampling, data were collected from 332 Chinese apparel brands' self-operated live streaming commerce consumers. The results further demonstrate that perceived information usefulness, perceived enjoyment, economic benefits, and social support are significant and necessary motivations of consumer brand engagement. Moreover, consumer brand engagement serves as a significant and necessary condition for brand trust and brand loyalty, while it is not a necessary condition for self-brand congruity. This research assists marketers in optimizing brand self-operated live streaming commerce.
The digital transformation of grocery retail is reshaping consumer behavior and operational strategies through online platforms, immersive technologies, and virtual marketplaces. This study critically reviews academic literature on grocery shopping across digitalized channels to identify key themes, research trends, and knowledge gaps. 166 Web of Science-indexed publications were analyzed. In response to recent calls, the study adopts a multi-method approach combining (1) bibliometric analysis, and (2) qualitative thematic analysis. This study is among the first systematic literature review studies in digitalized grocery shopping areas to integrate the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) protocol with the antecedents-decisions-outcomes- theory-context-method (ADO-TCM) framework. Findings are structured using the ADO-TCM framework, around antecedents, decisions, outcomes, and associated theories, contexts, and methods. The review identifies 10 major themes and 29 subthemes across four domains: online, omnichannel, virtual/AR-based, and Metaverse-based grocery shopping. The study provides a comprehensive synthesis of the field and highlights the need for more interdisciplinary, theory-driven, and methodologically plural research, while proposing 10 future research directions.
Virtual reality (VR) adoption in fashion e-commerce represents a disruptive innovation that redefines how brands craft immersive consumer experiences. This study aims to validate a research model about VR-based brand engagement in the fashion commerce context. It seeks to uncover the effect of VR attributes such as interactivity, vividness, product reality congruence, and modality richness on perceived realism, as well as subsequent outcomes of immersion and VR-based brand engagement. Data were collected from 306 respondents through Credamo's paid panel using purposive sampling to recruit consumers with relevant online fashion purchasing and VR brand experience. The Partial Least Squares Structural Equation Modeling (PLS-SEM) and combined importance-performance map analyses were employed. The study reveals that interactivity, vividness, product reality congruence, and modality richness positively influence perceived realism, which in turn strongly drives immersion and subsequently enhances VR-based brand engagement in fashion e-commerce. Combined importance-performance map analysis further identifies immersion as the primary strategic lever and perceived realism as a key bottleneck, while the antecedent features serve as well-performing hygiene factors requiring only maintenance. This study contributes to the literature on VR-related fashion research and offers practical insights for fashion e-commerce managers seeking to use virtual reality to enhance brand engagement.
This study explores how Generation Y consumers' purchase intentions on TikTok are influenced by interactive, visually rich content, using the elaboration likelihood model (ELM) and stimulus-organism-response (S-O-R) models. By incorporating trust as a mediator and need for touch (NFT) as a moderator, the study investigates how central and peripheral cues affect flow experience and purchase intention. Surveying 443 Gen-Y TikTok users in Mainland China, the data were analyzed using partial least squares-structural equation modeling. Results indicate that both central (content diagnosticity, vicarious expression) and peripheral cues (social and physical attractiveness) enhance flow, which in turn increases trust and purchase intention. Additionally, trust mediates the flow-intention relationship, and NFT moderates this process. The findings extend ELM and S-O-R models in the context of short-form video commerce, offering practical insights for marketers to optimize TikTok strategies by focusing on engagement, trust, and sensory appeal.
Problematic social media use has largely foregrounded emotional and mental health outcomes, whereas cognitive outcomes remain underexamined. Anchored in the Stressor-Strain-Outcome (SSO) framework, this study tests whether depressive symptoms and subjective fatigue mediate the association between problematic WeChat use and executive functioning. A cross-sectional survey of China WeChat users recruited via purposive sampling was analyzed using PLS-SEM. Results indicated that Problematic WeChat use was positively associated with depressive symptoms and subjective fatigue; in turn associated with poorer executive functioning. Indirect effects from problematic WeChat use on executive functioning via depressive symptoms and subjective fatigue were statistically significant. These findings extend the applications of the SSO framework and media scholarship to cognitive outcomes and underscore the importance of considering co-occurring emotional and physiological strains. Practically, the results suggest that youth-focused digital well-being efforts should be monitored alongside the prevention and supportive strategies for youth psychological well-being.
With the advent of social media, influencers are leveraging unprecedented opportunities to build personal brands and engage in entrepreneurial ventures beyond third-party endorsements. Through two experiments conducted in sport and lifestyle contexts, we examine how third-party endorsing and self-branding affect consumer perceptions of involvement, profit-seeking, and authenticity, ultimately shaping support intentions via a warranting perspective. Our findings suggest that social media influencers' self-branding functions as a dual-valence warranting cue: while it increases perceptions of profit-seeking and reduces authenticity, it simultaneously enhances authenticity through perceived involvement. This study contributes to warranting theory by proposing stake magnitude as a crucial dimension to consider when explaining and predicting how consumers evaluate information beyond the source's perceived control and self-interest. From a practical perspective, our findings indicate that self-branding can maintain authenticity despite its strong commercial intent. By strategically emphasizing their dedication, commitment, and accountability in their own-branded products, influencers can effectively leverage self-branding to seize entrepreneurial opportunities and diversify their revenue streams.
Influencers are important for social media marketing, impacting the behavioral intention of followers. Such impact is often augmented by the halo effect. With the growing popularity of travel influencers in China, whether the halo effect can be observed in destination marketing is not well understood. To better understand the halo effect in the context of travel influencers, this study proposes a model to investigate how different characteristics of influencers affect the perceived uniqueness of the featured destination and the perceived influencer-destination congruence, which further affects the destination visit intention. The findings contributed to the literature on the mechanism driving followers' behavioral intention as a response to influencer marketing and provided insights to both influencers and marketers.
This study aims to predict the factors influencing the continuance intention of food delivery apps through an integrated expectation-confirmation model and task-technology fit. The study collected data from 353 users of food delivery apps and analyzed it using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results of the study show that task-technology fit significantly influences the confirmation of expectations and perceived usefulness of food delivery apps, which in turn positively influence satisfaction and continuance intention to use food delivery apps. The mediating effects of satisfaction on the relationships between confirmation of expectations and continuance intention, as well as between perceived usefulness and continuance intention, were also significant. The study's findings confirmed the moderating effect of personal innovativeness on the relationship between task-technology fit and confirmation of expectations. Furthermore, a multigroup analysis shows no significant differences between age and gender groups. This study contributed to the expectation-confirmation model by integrating task-technology fit and personal innovativeness as crucial constructs that significantly influence the food delivery apps' post-adoption. The findings of the current study provide useful guidance for restaurant chain managers in designing innovative apps that offer a seamless customer experience and encourage customers to place orders through food delivery apps.
The study examines the factors influencing consumers' intentions to use autonomous outdoor food delivery robots (OFDR) and forward company generated social media content by integrating the Technology Acceptance Model (TAM) with innovativeness of motivated consumers. Based on 403 valid responses from Malaysia, all hypotheses were supported except those related to functional and hedonic innovativeness, which showed no moderating effects between perceived usefulness and attitude. Social innovativeness did not moderate the relationship between perceived ease of use and attitude. Theoretically, the study extends understanding of digital consumer behavior in the the service domain by introducing an integrated model that enhances TAM with dimensions of consumer innovativeness, namely functional, hedonic, cognitive, and social. Practically, it provides insights for policmakers and businesses in promoting OFDR adoption through strategies that foster positive attitude, perceived usefulness, and ease of use, reducing labor costs and carbon emissions, as well as facilitating last-mile delivery in a developing nation.
This review systematically examines the factors influencing viewers' continuous watching intention in live streaming. Following the PRISMA protocol and utilizing a customized literature matrix, the study synthesizes research across multiple domains by analyzing contextual backgrounds, methodological approaches, theoretical foundations, and key findings. Building on prior reviews that have often addressed selected perspectives in isolation, this review proposes a structured and comprehensive Emotional-Cognitive-Social (ECS) conceptual framework that identifies conceptual overlaps among existing theoretical models and uncovers underexplored areas in the literature. The ECS framework is critically compared with traditional theories, highlighting its integrative potential. Moreover, the review explores the cross-cultural applicability of the ECS framework, revealing how emotional, cognitive, and social drivers may differ in relevance and impact across diverse cultural contexts. Findings indicate that despite growing academic and industry attention, research on continuous watching intention of live streaming remains theoretically fragmented and methodologically inconsistent, particularly as live streaming formats diversify and evolve. By providing a critical appraisal of the current knowledge landscape, this review proposes a forward-looking research agenda and offers actionable implications for platform designers, marketing professionals, and content creators aiming to enhance user engagement and continuous watching intention.
Social media platforms have become a global platform for self-expression; yet what users choose to disclose, their message valence, and privacy protection can vary widely across cultures. Managing and protecting individual personal privacy has become more important in response to the increased risk of data breaches. A theoretical framework based on Protection Motivation Theory was developed to look at the impact of perceived risks and perceived benefits on self-disclosure, privacy protection, and message valence after Facebook's privacy breaches. The model was tested using data from two countries (USA and Taiwan) and the results show that Facebook users seek to balance risks and benefits in terms of what they disclose, message valence, and their privacy protection. In addition, users intend to control their privacy settings, and cultural variation was also observed between the two countries. Implications from this study such as consumer protection, privacy laws, private and public policies, and regulations are discussed.
Impulse buying is a common behavior in live shopping, and business managers often worry about missing promotional opportunities related to it. This study aims to explore the relationships between CII (consumer-influencer interaction), CCI (consumer-consumer interaction), and consumer herd behavior within the context of live commerce, as well as the relationship between herd behavior and impulse buying, with perceived behavioral control included as a moderating variable. Data were collected through a questionnaire survey and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). This study categorizes herd behavior into two distinct concepts: informational herd behavior and normative herd behavior. The findings indicate that both consumer-influencer interaction (CII) and consumer-consumer interaction (CCI) positively influence informational and normative herd behaviors, which, in turn, have a positive impact on impulsive buying. However, perceived behavioral control does not significantly moderate the relationship between herd behavior and impulsive buying.
Fake news and deepfake (FN & DF) technology have emerged as critical areas of inquiry within internet commerce and digital communication research. Deepfake technology significantly influences the creation and rapid dissemination of fake news. The study takes a pioneering step in addressing inconsistencies within the existing literature by providing a clear and more comprehensive synthesis of how deepfakes contribute to spreading fake news. Following PRISMA guidelines, the study analyzes 34 articles using a thematic categorization framework. The review makes three primary contributions. First, it highlights current research patterns and emerging trends in this domain. Second, it identifies five themes associated with the FN & DF literature: Identity-Driven Dissemination, Cognitive Bias and Emotional Realism, Trust Erosion and Epistemic Uncertainty, Platform Incentives and Corrective Strategies, and Governance, Ethics, and Detection. Third, based on these themes, it proposes a conceptual framework reflecting antecedents, drivers, moderators, mediators, and outcomes. The study outlines future research directions and offers practical implications.
