Journal of Theoretical and Applied Electronic Commerce Research

32 pages, 1332 KB

Open AccessArticle

Strategic Disclosure of AI Curation: A Boundary Condition on Algorithm Aversion in Hedonic E-Commerce

by Tiannv Ma, Yuqi Du, Yong Wang and Liying Zhou

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 232; https://doi.org/10.3390/jtaer21070232 (registering DOI) - 18 Jul 2026

Abstract

Algorithm-aversion research predicts that consumers prefer human curators to algorithmic ones in subjective decision domains, including taste-based hedonic recommendation. Drawing on the algorithmic-symbiosis paradigm and on assortment-perception theory, this paper identifies a boundary condition on that prediction: disclosing that recommendations are AI-curated rather [...] Read more.

Algorithm-aversion research predicts that consumers prefer human curators to algorithmic ones in subjective decision domains, including taste-based hedonic recommendation. Drawing on the algorithmic-symbiosis paradigm and on assortment-perception theory, this paper identifies a boundary condition on that prediction: disclosing that recommendations are AI-curated rather than human-curated lifts purchase intention in hedonic e-commerce but not in utilitarian e-commerce. The mechanism is a search-side option-breadth inference—the consumer’s attribution about the size of the option pool the curator considered upstream—which is diagnostic in preference-formative consumption categories where consumers build, rather than match, a preference. Three online experiments deployed through a Chinese consumer panel test the framework. Study 1 (

N = 228

) finds the predicted Disclosure × Product-type interaction (

η_{p}^{2} = 0.025

) with the AI-versus-human lift confined to the hedonic cell (

d = 0.65

). Study 2 (

N = 257

) isolates the option-breadth pathway against trust and competence as competing mediators. Study 3 (

N = 519

) extends the design to a second hedonic category, decomposes option breadth into search-side and display-side subdimensions through an eight-item bi-factor scale, tests mentalizing alongside option breadth as a competing mediator, and brings the moderated-mediation test by consumer AI familiarity to conventional statistical power (index of moderated mediation

= + 0.065

, 95% CI

[+ 0.014, + 0.118]

). Implications for interactive-marketing practice and algorithmic-disclosure regulation are discussed. Full article

(This article belongs to the Topic Algorithmic Symbiosis in the New Era of Interactive Marketing)

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28 pages, 1558 KB

Open AccessArticle

Beyond Static Expertise: Unpacking Live-Streamer Professionalism as Contextual Competence in Interactive Commerce

by Mei Huang, Qiulin Sun, Xiao Yu, Fang Wan and Danping Liu

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 231; https://doi.org/10.3390/jtaer21070231 (registering DOI) - 17 Jul 2026

Abstract

Traditional celebrity endorser models conceptualize expertise as a static trait focused on the possession of product knowledge. However, the synchronous and highly interactive nature of live commerce challenges these static models in explaining consumer engagement. Grounded in Social Presence Theory and a contextual [...] Read more.

Traditional celebrity endorser models conceptualize expertise as a static trait focused on the possession of product knowledge. However, the synchronous and highly interactive nature of live commerce challenges these static models in explaining consumer engagement. Grounded in Social Presence Theory and a contextual competence perspective, the present study reconceptualizes live-streamer professionalism as a set of dynamic competencies enacted through real-time interaction. Using a sequential mixed-methods design, Study 1 employs a grounded theory analysis of qualitative data collected from consumers, streamers, and platform practitioners to identify core dimensions of streamer professionalism. Study 2 develops and validates a multidimensional measurement scale. Study 3 leverages a comprehensive engagement model to benchmark the proposed framework against competing, expertise-based explanations. The results reveal five distinct dimensions of streamer professionalism (Business Knowledge Reserve, Expressive Ability, Professional Quality, Interactive Ability, External Visible Traits) and a dual-pathway mechanism: Business Knowledge Reserve primarily enhances cognitive product involvement, whereas Interactive Ability strengthens context attachment by amplifying perceived social presence. The proposed model demonstrates greater explanatory power than traditional expertise frameworks, particularly in explaining affective attachment. Collectively, these findings shift the analytical focus from who the source is to how professionalism is performed within interactive service encounters, thereby advancing a performance-oriented view of professionalism in live commerce and informing platform governance and influencer management. Full article

(This article belongs to the Special Issue Interactive Marketing in Digital Commerce: Consumer Behavior, Engagement and Decision-Making)

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19 pages, 802 KB

Open AccessArticle

A Parsimonious Two-Segment Structure in Smartphone E-Commerce: Evidence from Romanian University Students

by Ovidiu-Aurel Ghiuță

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 230; https://doi.org/10.3390/jtaer21070230 - 17 Jul 2026

Abstract

Online shopping is expanding rapidly in emerging European markets, yet many consumers still combine digital channels with offline verification. This study asks whether the resulting heterogeneity among young consumers is genuinely complex or reducible to a simpler structure. Drawing on technology-acceptance and perceived-risk [...] Read more.

Online shopping is expanding rapidly in emerging European markets, yet many consumers still combine digital channels with offline verification. This study asks whether the resulting heterogeneity among young consumers is genuinely complex or reducible to a simpler structure. Drawing on technology-acceptance and perceived-risk perspectives, it analyses survey data from 457 Romanian university students, of whom 269 were routed to eight attitudinal items on online smartphone purchasing. The questionnaire was distributed to students at two Romanian universities through institutional email and faculty social media accounts, yielding a non-probability convenience sample; no probability-based selection procedure was applied. After examining the dimensionality and reliability of the items through exploratory factor analysis, K-means clustering was used to segment respondents, and the solution was checked against hierarchical clustering. Two segments emerged: cautious, lower-online-orientation consumers, who report lower perceived convenience, speed, price advantage, and overall use of online purchasing, and online-oriented adopters, who view digital channels as efficient and convenient. Rather than many fine-grained segments, the data point to a dominant behavioural axis, namely overall orientation towards online purchasing. The findings provide evidence consistent with a parsimonious two-segment account of consumer heterogeneity in a rapidly developing digital market, and they suggest differentiated omnichannel strategies: confidence-building and risk-reduction measures for cautious consumers and experience optimisation for digital adopters. Full article

(This article belongs to the Section Digital Marketing and the Evolving Consumer Experience)

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30 pages, 2160 KB

Open AccessArticle

Algorithmic Transparency and Immersive Retail: Investigating the Joint Effects of Explainable AI and Augmented Reality on Consumer Trust and Purchase Decisions

by Reema Nofal

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 229; https://doi.org/10.3390/jtaer21070229 - 16 Jul 2026

Abstract

The convergence of artificial intelligence (AI) and augmented reality (AR) is reshaping digital retail, yet how algorithmic transparency, explainable AI, and AR-based immersion jointly shape consumer responses remains theoretically underdeveloped. Drawing on the Stimulus–Organism–Response (S–O–R) model, this study examines the influence of cognitive [...] Read more.

The convergence of artificial intelligence (AI) and augmented reality (AR) is reshaping digital retail, yet how algorithmic transparency, explainable AI, and AR-based immersion jointly shape consumer responses remains theoretically underdeveloped. Drawing on the Stimulus–Organism–Response (S–O–R) model, this study examines the influence of cognitive stimuli (algorithmic transparency and explainable AI) and experiential cues (AR immersion) on trust, perceived usefulness, immersion, purchase decisions, and continued usage intention. Using survey data from 420 online shoppers in the West Bank, Palestine, and analyzed via structural equation modeling, the findings indicate that cognitive evaluations—particularly perceived usefulness and trust—exert stronger effects on purchase decisions than immersion. Specifically, algorithmic transparency enhances trust, while explainable AI strengthens perceived usefulness; AR immersion contributes to engagement, but its behavioral effects remain comparatively weaker. The results suggest that experiential engagement serves as a complementary enhancer, operating most effectively when supported by transparent and useful AI systems. The study extends AI–AR commerce literature by proposing a multi-stage S–O–R framework and demonstrating the conditional role of immersion in emerging digital markets. Full article

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25 pages, 708 KB

Open AccessArticle

Consumer Trust and Privacy Concerns in AI-Driven E-Commerce: Evidence from a Hybrid SEM–ANN Study

by Israt Jahan Shithii, Afrosa Al-Jahan and Md Abdul Hannan Mia

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 228; https://doi.org/10.3390/jtaer21070228 - 16 Jul 2026

Abstract

Framing the study within the Unified Theory of Acceptance and Use of Technology (UTAUT) and the extended online privacy concern model, this study investigates the effects of effort expectancy, social influence, privacy concerns, and perceived risk on e-commerce consumer behavior, while positioning trust [...] Read more.

Framing the study within the Unified Theory of Acceptance and Use of Technology (UTAUT) and the extended online privacy concern model, this study investigates the effects of effort expectancy, social influence, privacy concerns, and perceived risk on e-commerce consumer behavior, while positioning trust in AI as a key mediating factor. The data were collected from 250 active e-commerce users in Bangladesh, and the analysis was done with a hybrid approach that integrates partial least squares structural equation modeling (PLS-SEM) with artificial neural network (ANN) analysis. The SEM results indicate that effort expectancy and social influence have significant positive effects on consumer behavior. Social influence also shows a significant positive effect on trust in AI. Trust in AI exhibits a significant positive effect on consumer behavior. However, perceived risk does not show a significant effect on either trust in AI or consumer behavior. Privacy concerns demonstrate a significant positive relationship with both trust in AI and consumer behavior, contrary to the hypothesized negative relationships. The mediation analysis shows that trust in AI significantly mediates the relationship between social influence and consumer behavior, while no significant mediation effects are observed for privacy concerns or perceived risk. The ANN results further confirm the dominance of social influence as the most important predictor of both trust in AI and consumer behavior, followed by effort expectancy and trust in AI, while perceived risk shows minimal predictive relevance. Overall, the findings suggest that consumer adoption of AI-enabled e-commerce is primarily driven by benefit-oriented factors rather than risk-based considerations in the present context. The study contributes to the literature by extending UTAUT and privacy calculus theory to AI-mediated commerce and by demonstrating the value of combining SEM and ANN to capture both explanatory relationships and predictive importance. From a managerial perspective, the results highlight the importance of strengthening social influence mechanisms, improving system usability, and building trust in AI systems to enhance consumer engagement in AI-driven e-commerce environments. Full article

(This article belongs to the Special Issue Emerging Technologies and Innovations in Electronic Commerce)

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50 pages, 2724 KB

Open AccessArticle

Algorithmic Nudging and Financial Over-Indebtedness: A Longitudinal Panel Analysis of AI-Integrated BNPL in MENA E-Commerce

by Osama Wagdi, Walid Abouzeid, Heba Farid and Sharihan M. Aly

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 227; https://doi.org/10.3390/jtaer21070227 - 15 Jul 2026

Abstract

Artificial intelligence-integrated ‘buy now, pay later’ (BNPL) platforms are diffusing rapidly across the Middle East and North Africa (MENA), raising concerns about consumer financial vulnerability. Drawing on choice architecture, payment decoupling, and financial literacy literatures, this study examines how three platform-level features—algorithmic nudging, [...] Read more.

Artificial intelligence-integrated ‘buy now, pay later’ (BNPL) platforms are diffusing rapidly across the Middle East and North Africa (MENA), raising concerns about consumer financial vulnerability. Drawing on choice architecture, payment decoupling, and financial literacy literatures, this study examines how three platform-level features—algorithmic nudging, AI personalization intensity, and perceived ease of credit—are associated with impulsive buying tendency and downstream financial outcomes, and whether BNPL-specific financial literacy attenuates these associations. A multi-method design combined cross-sectional partial least squares structural equation modeling (N = 1247 active BNPL users in seven MENA countries) with a six-month longitudinal follow-up (N = 847, 68% retention). Algorithmic nudging was positively associated with impulsive buying tendency, which in turn was associated with elevated financial stress and longitudinal debt accumulation. The ‘loyalty trap’—a paradoxical state in which financially stressed consumers maintain high platform loyalty—is provisionally documented via piecewise longitudinal trajectories. We emphasize that this pattern is consistent with but not causally established by the present design, and we outline specific experimental and quasi-experimental research designs needed for causal identification. BNPL-specific financial literacy moderated the associations between algorithmic nudging, impulsive buying, and adverse financial outcomes, with the highest-literacy quartile exhibiting substantially attenuated debt trajectories. We discuss boundary conditions, alternative explanations, and the limits of causal inference in non-experimental panel data. Findings inform evolving BNPL regulatory frameworks in MENA, with particular relevance to nudge-transparency disclosures, contractual cooling-off periods, and credit-bureau reporting standards. Full article

(This article belongs to the Section FinTech, Blockchain, and Digital Finance)

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27 pages, 655 KB

Open AccessArticle

Persuasion Cues and Consumer Engagement in Food Influencer Short-Form Videos: An ELM–COBRA Perspective

by Rulan Liu, Syuhaily Osman, Mohamad Fazli Sabri and Nur Aqilah Amalina Jaafar

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 226; https://doi.org/10.3390/jtaer21070226 - 14 Jul 2026

Abstract

Beginning with the notion that short-form video sites represent key digital commerce destinations for food influencers in general, there is very little research explaining how specific persuasion cues lead to varying degrees of consumer engagement. Based upon the Elaboration Likelihood Model (ELM), Social [...] Read more.

Beginning with the notion that short-form video sites represent key digital commerce destinations for food influencers in general, there is very little research explaining how specific persuasion cues lead to varying degrees of consumer engagement. Based upon the Elaboration Likelihood Model (ELM), Social Proof theory and the COBRA framework, this study aims to understand whether argument quality as a central-route cue and perceived emotional appeal as a peripheral-route cue affect consumption, contribution, creation engagement behaviors. Additionally, the study will determine if perceived post popularity, a platform-generated social proof signal, affects these relationships. A survey was conducted of 386 users of short food influencer videos. PLS-SEM analysis was performed on the survey data. Results indicated that both argument quality and perceived emotional appeal positively influence all three engagement levels. Perceived emotional appeal exerts a stronger effect, particularly on higher-engagement behaviors. The moderating effects of perceived post popularity were limited and applied solely to contribution, where it weakened the positive relationship between argument quality and contribution but strengthened the positive relationship between perceived emotional appeal and contribution. This study builds upon existing knowledge of how consumers respond to food influencer content by exploring differences between types of engagement and integrating platform-generated signals within an ELM-based theoretical model. Full article

(This article belongs to the Special Issue Interactive Marketing in Digital Commerce: Consumer Behavior, Engagement and Decision-Making)

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27 pages, 2432 KB

Open AccessArticle

How Perceived Fit Shapes Value Co-Creation and Co-Destruction in Intelligent Customer Service: Psychological Mechanisms and Moderation by Digital Self-Efficacy

by Lei Wang, Jiayi Ren, Shiyi Sun and Yitao Chen

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 225; https://doi.org/10.3390/jtaer21070225 - 11 Jul 2026

Abstract

Intelligent customer service is increasingly used to reduce service costs and improve efficiency, yet users often experience divergent outcomes, ranging from value co-creation to value co-destruction. Using task–technology fit theory as the primary theoretical lens, this study examines how the alignment between users’ [...] Read more.

Intelligent customer service is increasingly used to reduce service costs and improve efficiency, yet users often experience divergent outcomes, ranging from value co-creation to value co-destruction. Using task–technology fit theory as the primary theoretical lens, this study examines how the alignment between users’ service task requirements and intelligent customer service capabilities is associated with divergent value outcomes. Within this framework, cognitive load and perceived control are theorized as two localized psychological mechanisms, human–AI trust as a conversion mechanism, and digital self-efficacy as a boundary condition. Using two scenario-based experiments, we develop and test the proposed model. Study 1 shows that participants in the high-fit condition reported higher value co-creation and lower value co-destruction than those in the low-fit condition. The results further reveal an asymmetric mechanism: cognitive load did not directly explain value co-creation but was more strongly associated with value co-destruction, whereas perceived control showed a broader association with both value outcomes. Study 2 extends Study 1 by examining digital self-efficacy as a boundary condition and shows that the conditional indirect association patterns vary across levels of digital self-efficacy. These findings contribute to extending task–technology fit theory to post-use value formation and provide cautious implications for intelligent customer service design and management. Full article

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20 pages, 3464 KB

Open AccessArticle

Brand- or User-Generated? The Impact of Product Tutorial Sources on Purchase Intention in Social Commerce

by Wenhao Bai, Zhong Yao, Wuhuan Xu and Yazhou Luo

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 224; https://doi.org/10.3390/jtaer21070224 - 11 Jul 2026

Abstract

Product usage tutorials are central to social commerce, yet little is known about whether the same tutorial information persuades consumers differently when it is generated by brands or by peer users. Drawing on the Persuasion Knowledge Model and cue consistency theory, this study [...] Read more.

Product usage tutorials are central to social commerce, yet little is known about whether the same tutorial information persuades consumers differently when it is generated by brands or by peer users. Drawing on the Persuasion Knowledge Model and cue consistency theory, this study examines how brand-generated tutorials (BGTs) and user-generated tutorials (UGTs) influence purchase intention, and how trust, brand image, and cross-source content similarity shape these effects. Two between-subjects experiments were conducted in the context of cosmetics tutorials on Rednote. Study 1 used a 3 (tutorial source: BGT, UGT, none) × 2 (brand image: high, low) design; Study 2 compared high BGT–UGT similarity, low similarity, and UGT-only conditions. Results show that both BGTs and UGTs increase purchase intention relative to no tutorial, with UGTs producing a stronger effect. Trust mediates the effect of UGTs but not BGTs, while brand image does not moderate source effects. In co-presence conditions, high BGT–UGT similarity strengthens purchase intention, whereas low similarity weakens it. These findings identify source-level commercial intent as a boundary condition for trust formation and show that cross-source cue consistency determines whether brand tutorials validate or undermine peer-generated guidance. Full article

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22 pages, 16607 KB

Open AccessArticle

Enhancing Personalized E-Commerce Recommendations Under the User–Agent–Platform Paradigm: An LLM-Driven Method

by Junbiao Xu, Zhicai Zhang and Chong Zhang

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 223; https://doi.org/10.3390/jtaer21070223 - 10 Jul 2026

Abstract

Recommendation systems are widely used in e-commerce, social media, and content distribution, yet LLM-based recommendation workflows still face recurring challenges in data completeness, sample balance, and output stability. In addition, the conventional “user-platform” structure leaves limited room for user-side mediation of exposure and [...] Read more.

Recommendation systems are widely used in e-commerce, social media, and content distribution, yet LLM-based recommendation workflows still face recurring challenges in data completeness, sample balance, and output stability. In addition, the conventional “user-platform” structure leaves limited room for user-side mediation of exposure and preference expression. This paper presents ABP, a workflow-level extension of

i^{2}

Agent in the User–Agent–Platform setting. ABP contains three modules: Adaptive Description Enrichment (ADE), Batch-balanced Sampling Strategy (BSS), and Prompt-driven Workflow Optimization (PWO). ADE repairs missing or rigid item text with richer natural-language descriptions, BSS builds balanced comparative inputs for user profiling, and PWO strengthens multi-stage reasoning with structured output constraints. Experiments on four real-world datasets show that ABP achieves strong ranking results under the reported protocol. Across the 16 reported dataset–metric pairs, the five-run mean results of ABP show an average relative improvement of 24.62% over

i^{2}

Agent, with especially large gains on Amazon Book and Amazon Movietv. Under a fixed five-run protocol, ABP shows limited run-to-run dispersion on Amazon Book, Amazon Movietv, and Yelp, while Goodreads exhibits comparatively larger but still bounded variation. Overall, these results suggest that carefully designed workflow improvements can improve LLM-based recommendation quality in the reported setting while maintaining the agent’s role as a user-side mediation layer in the User–Agent–Platform setting. Full article

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Graphical abstract

24 pages, 6833 KB

Open AccessArticle

Toward Industry 5.0: An IoT-Enabled Digital Twin for Joint Sustainability and Resilience Optimization in Automated Warehouses

by George To Sum Ho, Valerie Tang, Carmen Kar Hang Lee, Manviel Man Fei Tam and Elle Wing Ho Chow

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 222; https://doi.org/10.3390/jtaer21070222 - 10 Jul 2026

Abstract

As e-commerce expands, automated e-fulfilment centers are important for fast and dependable delivery of orders placed online. Robotic equipment performs most of the operational work in these centers, supported by Internet of Things (IoT) that provide real-time operational data. Although these innovations show [...] Read more.

As e-commerce expands, automated e-fulfilment centers are important for fast and dependable delivery of orders placed online. Robotic equipment performs most of the operational work in these centers, supported by Internet of Things (IoT) that provide real-time operational data. Although these innovations show the principles of Industry 4.0, the transition to Industry 5.0 creates an economic trade-off between resilience and sustainability for the increasing demand for both. The main challenge is to reduce energy use without compromising the ability to manage demand fluctuations. Existing research has typically focused on sustainability or resilience by improving individual processes in isolation, which limits trade-off of resources usage and performance, as well as the interconnected nature of logistic operations. To respond to this challenge, the study proposes a Digital Twin for Joint Sustainability and Resilience Optimization (DT-JSRO) model to help in decision making coupled sustainability-resilience optimization. The DT-JSRO model lets managers run scenarios for performance evaluation in sustainability and resilience while guiding users on the best resource allocation strategies. A simulation experiment proved the feasibility and effectiveness of the proposed approach. The model simulates different operational scenarios to produce the best resource allocation strategies that can assist practitioners based on practical priorities, including solely sustainability, resilience or jointly optimizing the two when needed. Full article

(This article belongs to the Special Issue Pioneering Predictive Analytics: AI-IoT Synergies for Adaptive and Sustainable Distribution Models in E-Commerce Supply Chains)

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27 pages, 4883 KB

Open AccessArticle

From Visible Halos to Invisible Influence: A Mixed-Methods Analysis of KOC Strategies and Evolutionary Trajectories in Social Commerce

by Kai Lin Hsu and Wei-Hsi Hung

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 221; https://doi.org/10.3390/jtaer21070221 - 10 Jul 2026

Abstract

This study examines how key opinion consumers (KOCs) influence consumer behavior in social commerce, particularly under growing distrust toward traditional key opinion leaders (KOLs) and the resulting limitations in their influence. While prior research has primarily focused on trust-building, this study investigates how [...] Read more.

This study examines how key opinion consumers (KOCs) influence consumer behavior in social commerce, particularly under growing distrust toward traditional key opinion leaders (KOLs) and the resulting limitations in their influence. While prior research has primarily focused on trust-building, this study investigates how KOCs create perceived value through a distinct influence mechanism that distinguishes between the roles of trust and distrust. Using an explanatory sequential mixed-methods approach, this research integrates results from a quantitative study with findings from a qualitative study to arrive at robust meta-inferences. Following the PLS-SEM analysis (N = 582), qualitative interviews were conducted to corroborate these inferences and provide complementary insights into the psychological mechanisms underlying trust and distrust, identifying boundary conditions—such as the ineffectiveness of physical attractiveness—that redefine influence models in social commerce. The results indicate that a KOC’s expertise and recommendation cues significantly enhance perceived value, which serves as a key mediator influencing purchase behavior. This study conceptualizes the “invisible influence” effect as a distinct persuasion mechanism. KOCs construct utilitarian value through authentic, experience-based sharing. By identifying the mediating role of perceived value and mapping the evolutionary trajectories of influencer roles, this research extends social commerce strategy. Full article

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21 pages, 4337 KB

Open AccessSystematic Review

The Impact of Social Media Marketing on Brand Loyalty in Nepal: Insights from Bibliometric and Survey Analysis

by Ramesh Shahi, Tej Bahadur Shahi, Bishnu Bahadur Khatri and Arjun Neupane

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 220; https://doi.org/10.3390/jtaer21070220 - 9 Jul 2026

Abstract

With the rapid growth of social media use in Nepal and their engagement with customers, understanding how these platforms support customer loyalty becomes essential for retail businesses. This study investigates the role of social media marketing in shaping brand loyalty among retail customers [...] Read more.

With the rapid growth of social media use in Nepal and their engagement with customers, understanding how these platforms support customer loyalty becomes essential for retail businesses. This study investigates the role of social media marketing in shaping brand loyalty among retail customers in Nepal through an integrated research design that combines systematic bibliometric and survey data analysis. The bibliometric findings suggest a clear progression in the literature, moving from a foundational emphasis on relationship marketing and loyalty theory toward a more integrated framework that incorporates social media engagement and, ultimately, measurable business outcomes. The quantitative results based on survey data conducted with 100 Nepalese consumers active on Facebook, Instagram, and TikTok show that effective social media strategies and the ability to address implementation difficulties significantly enhance brand loyalty. In contrast, the direct influence of customer trust is limited. The findings highlight the importance of tailored and interactive content, supported by appropriate digital practices, particularly in regions with developing infrastructure. This study offers practical recommendations to improve digital engagement, encourage retailers to collaborate with local influencers, respond to customer feedback, maintain transparency in messaging, and enhance digital capabilities to implement effective social media strategies. It also underscores the value of producing culturally relevant content that aligns with local interests and behaviours. Full article

(This article belongs to the Special Issue Interactive Marketing in Digital Commerce: Consumer Behavior, Engagement and Decision-Making)

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23 pages, 2657 KB

Open AccessArticle

Consumer Reactions to Virtual Influencer Transgressions: How Anime-Looking and AI-Driven Influencers Are Less Vulnerable

by Wei Song, Siyuan Wei, Zinuo Li, Shengliang Deng and Yuqi Du

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 219; https://doi.org/10.3390/jtaer21070219 - 9 Jul 2026

Abstract

Virtual influencers in diverse appearances emerged and gained popularity on virtual platforms. However, how the appearances of virtual influencers affect consumers’ attitudes and reactions remained largely unexplored. Through three experimental studies, this paper examines the psychological mechanism and boundary conditions for consumer reactions [...] Read more.

Virtual influencers in diverse appearances emerged and gained popularity on virtual platforms. However, how the appearances of virtual influencers affect consumers’ attitudes and reactions remained largely unexplored. Through three experimental studies, this paper examines the psychological mechanism and boundary conditions for consumer reactions to virtual influencer transgressions. The results show that consumers are less forgiving and more negative in their reactions to transgressions conducted by human-like virtual influencers compared to anime-like ones, regardless of the type of transgression or the gender of the virtual influencer (Studies 1 and 2). Additionally, the driving mechanism of the virtual influencers has a moderating effect. When consumers are informed that the virtual influencer transgression is driven by a real person rather than AI, the impact of appearance on the reactions to transgressions is aggravated (Study 3). The result shows that appearance and driving mechanism both influence consumer perceptions of the virtual influencers’ agency, thereby determining the degree of reaction to transgressions. Full article

(This article belongs to the Topic Algorithmic Symbiosis in the New Era of Interactive Marketing)

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34 pages, 4966 KB

Open AccessArticle

Immersive Fashion Commerce and Persuasive Interface Design in DressGO on Roblox

by Matilde Martínez Moriel and Guillermo García-Badell Delibes

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 218; https://doi.org/10.3390/jtaer21070218 - 9 Jul 2026

Abstract

This article examines how DressGO, a fashion game developed by DRESSX on Roblox, organizes immersive fashion commerce for youth-oriented audiences through persuasive and gamified interface design. Rather than treating purchase as a discrete transactional event, the study examines how monetization cues are embedded [...] Read more.

This article examines how DressGO, a fashion game developed by DRESSX on Roblox, organizes immersive fashion commerce for youth-oriented audiences through persuasive and gamified interface design. Rather than treating purchase as a discrete transactional event, the study examines how monetization cues are embedded in progression loops, cosmetic status, and habitual return within a platform-mediated retail environment. Methodologically, the article adopts a qualitative single-case study and interface analysis based on a primary corpus of 12 screenshots selected from an initial pool of 34 screenshots collected across six gameplay sessions in January 2026, complemented by observational notes and contextual documentary triangulation and supplementary verification material for Robux/payment-route visibility. The analysis identifies four operational mechanisms: staged unboxing as a sensory gateway to acquisition, daily rewards and quantified tasks as retention infrastructure, rankings and rarity displays as social comparison cues, and accelerators, probability boosters, and waiting timers as conversion pressure mechanisms. The findings indicate that the interface integrates virtual fashion consumption into ordinary play and social visibility, while monetization cues operate through playful aesthetics, repetition, scarcity cues, and low-friction prompts embedded in progression systems. The article contributes to immersive commerce research by examining how gamification, interface design, and symbolic fashion value converge in a youth-oriented virtual retail environment. It further argues that randomized access, temporal friction, and comparative visibility should be understood not only as engagement features, but also as matters of digital fairness, platform trust, and responsible interface design. Full article

(This article belongs to the Special Issue Immersive Digital Commerce and Socio-Technical Futures: Beyond Traditional AI and Metaverse Paradigms)

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25 pages, 856 KB

Open AccessArticle

Behavioural and Deep Reinforcement Learning Perspectives on Consumer Resistance in E-Commerce Social Media Marketing Across Generations Z and Y

by Mostafa Aboulnour Salem and Zeyad Aly Khalil

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 217; https://doi.org/10.3390/jtaer21070217 - 8 Jul 2026

Abstract

Consumer resistance remains a major barrier to the effectiveness of AI-enabled social media marketing despite advances in content personalisation, influencer marketing, and intelligent recommendation systems. This study investigates how content personalisation, influencer trust, and platform interactivity influence consumer resistance, user engagement, and purchase [...] Read more.

Consumer resistance remains a major barrier to the effectiveness of AI-enabled social media marketing despite advances in content personalisation, influencer marketing, and intelligent recommendation systems. This study investigates how content personalisation, influencer trust, and platform interactivity influence consumer resistance, user engagement, and purchase intention by proposing a behaviourally informed Deep Reinforcement Learning (DRL) framework that integrates empirical behavioural modelling with adaptive optimisation. Survey data were collected from 619 higher education students in Saudi Arabia and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM), Multi-Group Analysis (MGA), and a Deep Q-Network (DQN)-based optimisation framework. The results show that content personalisation, influencer trust, and platform interactivity significantly increase user engagement while reducing consumer resistance. User engagement positively influences purchase intention, whereas consumer resistance negatively affects purchasing behaviour. Multi-Group Analysis revealed that Generation Z responded more strongly to personalisation and platform interactivity, whereas Generation Y showed greater responsiveness to influencer trust. The proposed behaviourally informed DQN framework incorporated latent behavioural constructs and statistically validated structural relationships into the reinforcement learning environment to generate adaptive marketing policies. Compared with conventional static and rule-based strategies, the proposed framework achieved approximately 36% higher optimisation performance across repeated behavioural simulations. The study contributes by positioning consumer resistance as the central behavioural construct, introducing an integrated behavioural–computational framework that embeds empirical behavioural relationships into the DRL state representation, reward mechanism, and policy-learning process, and providing practical guidance for developing transparent, trust-sensitive, and adaptive social media marketing strategies that enhance user engagement, reduce consumer resistance, and improve purchase intention in digital commerce environments. Full article

(This article belongs to the Special Issue Exploring Consumer Resistance to Digital Marketing Tactics and Technology)

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33 pages, 2668 KB

Open AccessArticle

Perception and Trust Construction in Rural Livestreaming E-Commerce: Evidence from Consumer Purchase Intention in Emerging Economies

by Miao Wang, Zixuan Zhou, Qingjun Chen, Delian Xu, Shiqun Yuan and Guangfan Sun

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 216; https://doi.org/10.3390/jtaer21070216 - 8 Jul 2026

Abstract

Against the backdrop of the rapid development of digital marketing in emerging economies, livestreaming e-commerce provides a new pathway for products from resource-constrained regions to overcome geographical limitations and expand market channels. Existing studies have largely focused on the sales performance, platform models, [...] Read more.

Against the backdrop of the rapid development of digital marketing in emerging economies, livestreaming e-commerce provides a new pathway for products from resource-constrained regions to overcome geographical limitations and expand market channels. Existing studies have largely focused on the sales performance, platform models, or general determinants of purchase intention in livestreaming e-commerce, while insufficient attention has been paid to the formation mechanism of consumers’ purchase intention within livestreaming interactions. Drawing on the S-O-R model and interaction ritual chain theory, this study constructs a theoretical model of how rural livestreaming e-commerce influences consumer purchase intention. Specifically, live streaming scenario atmosphere, product packaging, anchor interaction, and consumer engagement are identified as key stimulus factors. This study examines how these factors influence purchase intention through affective perception, cultural perception, and consumer trust, and further investigates the moderating role of emotional energy. The results show that: (1) the four livestreaming interaction factors significantly enhance consumers’ affective perception and cultural perception; (2) affective perception and cultural perception each form a chain mediation path with consumer trust, playing an important transmission role between livestreaming stimuli and purchase intention; and (3) emotional energy strengthens the effects of certain livestreaming stimuli on consumers’ psychological perceptions. This study reveals the pathway of “livestreaming stimuli–affective/cultural perception–consumer trust–purchase intention,” and provides strategic implications for livestreaming marketing, local brand communication, and rural economic development. Full article

(This article belongs to the Special Issue Interactive Marketing in Digital Commerce: Consumer Behavior, Engagement and Decision-Making)

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32 pages, 3117 KB

Open AccessArticle

From Service Touchpoint to Governance Interface: Anthropomorphic AI, Complaint Severity, and Trust in C2C Platform Complaint Handling

by Cong Sun, Xinyu Li and Xing Meng

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 215; https://doi.org/10.3390/jtaer21070215 - 8 Jul 2026

Abstract

Unlike B2C service failures, where firms respond to their own failures within a dyadic firm–customer relationship, C2C platform complaints often originate from third-party sellers. In such triadic platform–seller–consumer interactions, AI customer service agents become front-end governance interfaces through which consumers judge platform fairness, [...] Read more.

Unlike B2C service failures, where firms respond to their own failures within a dyadic firm–customer relationship, C2C platform complaints often originate from third-party sellers. In such triadic platform–seller–consumer interactions, AI customer service agents become front-end governance interfaces through which consumers judge platform fairness, rule enforcement, and institutional reliability. This study examines anthropomorphic AI as a task-contingent governance cue in C2C platform complaint handling. Across two scenario-based experiments, we test how AI role framing, anthropomorphism, and complaint severity jointly shape consumer evaluations. Study 1 shows that high anthropomorphism increases service recovery satisfaction when AI is framed as a relational representative, but not when framed as a rule-based arbitrator. Study 2 reveals significant three-way interactions among complaint severity, role framing, and anthropomorphism for satisfaction, platform trust, and continuance intention. Under low severity, high anthropomorphism benefits both roles; under high severity, its benefit remains mainly for the relational representative and weakens for the rule-based arbitrator. Mechanism analyses show that social presence explains responses under low severity, whereas both social presence and procedural justice shape evaluations under high severity. Together, these findings identify governance-task fit as a key condition for the value of anthropomorphic AI in platform complaint handling, showing when human-like AI builds trust and when it may undermine governance credibility. Full article

(This article belongs to the Special Issue Digital Marketing in Practice: Platforms, AI, Trust and Market Solutions)

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30 pages, 369 KB

Open AccessArticle

From Parasocial Relationships to eWOM Advocacy Intention: Customer Engagement and Perceived Brand Transparency in Influencer-Mediated Social Commerce

by Ming-Hsuan Wu

J. Theor. Appl. Electron. Commer. Res. 2026, 21(7), 214; https://doi.org/10.3390/jtaer21070214 - 7 Jul 2026

Abstract

Influencer-mediated social commerce has become a prominent environment in which consumers encounter brands through influencer recommendations, livestreaming, short videos, sponsored posts, and socially embedded interactions. Although influencer campaigns often generate visible engagement metrics, such as views, likes, comments, saves, and livestream participation, these [...] Read more.

Influencer-mediated social commerce has become a prominent environment in which consumers encounter brands through influencer recommendations, livestreaming, short videos, sponsored posts, and socially embedded interactions. Although influencer campaigns often generate visible engagement metrics, such as views, likes, comments, saves, and livestream participation, these engagement responses do not necessarily translate into public brand advocacy. Drawing on the stimulus–organism–response framework, balance theory, and the social risk perspective, this study examines how parasocial relationships with influencers are associated with eWOM advocacy intention through customer engagement and how perceived brand transparency conditions this conversion process. Data were collected through an online self-administered questionnaire targeting consumers in Taiwan with recent influencer-mediated social commerce experience, and 372 valid responses were retained for analysis. The results show that parasocial relationship is positively associated with customer engagement, and customer engagement is positively associated with eWOM advocacy intention. Customer engagement partially mediates the relationship between parasocial relationship and eWOM advocacy intention. In addition, perceived brand transparency strengthens the relationship between customer engagement and eWOM advocacy intention, and the moderated mediation results indicate that the indirect effect of parasocial relationship on eWOM advocacy intention through customer engagement is stronger when perceived brand transparency is higher. These findings clarify the relationship–engagement–advocacy conversion process and identify perceived brand transparency as an assurance condition under which influencer-driven engagement is more likely to develop into public eWOM advocacy. Full article

(This article belongs to the Special Issue Brand Engagement and Social Interaction in Digital Commerce)

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Journal of Theoretical and Applied Electronic Commerce Research

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