Journal of Theoretical and Applied Electronic Commerce Research

36 pages, 565 KB

Open AccessArticle

Unlocking the Cashless Shift: Retailers’ Adoption of Digital Payment Systems in Emerging Markets

by Sirajul M. Islam and Mario A. Ferrer

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 359; https://doi.org/10.3390/jtaer20040359 - 18 Dec 2025

Retailers play a pivotal role in advancing digital commerce in emerging markets, yet their adoption of digital payment systems remains inconsistent. Drawing on the Technology–Organization–Environment (TOE) framework, this study examines how technological readiness, organizational capability, and environmental influences shape retailers’ adoption behavior in [...] Read more.

Retailers play a pivotal role in advancing digital commerce in emerging markets, yet their adoption of digital payment systems remains inconsistent. Drawing on the Technology–Organization–Environment (TOE) framework, this study examines how technological readiness, organizational capability, and environmental influences shape retailers’ adoption behavior in Saudi Arabia. Survey data from retailers in Riyadh indicates that transaction speed, convenience, and perceived usefulness function as key enablers, while transaction fees, limited digital skills, and security concerns act as barriers. Although institutional trust and supportive government initiatives encourage adoption, many retailers remain unaware of formal compliance expectations, illustrating a pattern of compliance without awareness. To account for this dynamic, the TOE framework is extended by incorporating regulatory literacy and institutional trust as contextual dimensions. The study therefore offers theoretical refinement to TOE in policy-driven adoption settings and provides practical implications for improving merchant training, usability support, and regulatory communication to better sustain digital payment usage in emerging digital commerce ecosystems. Full article

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20 pages, 718 KB

Open AccessArticle

Does Cross-Border E-Commerce Broaden the Innovation Boundaries of Firms? Evidence from a Quasi-Natural Experiment in China

by Yanzhe Zhang and Yushun Han

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 358; https://doi.org/10.3390/jtaer20040358 - 11 Dec 2025

Viewed by 291

Abstract

Cross-border e-commerce (CBEC) is a driving force behind international trade and corporate upgrading in the era of global digital transformation. This research aims to investigate the extent to which the establishment of China’s Cross-Border E-Commerce Comprehensive Pilot Zones (CBECPZs) expands the innovation boundaries [...] Read more.

Cross-border e-commerce (CBEC) is a driving force behind international trade and corporate upgrading in the era of global digital transformation. This research aims to investigate the extent to which the establishment of China’s Cross-Border E-Commerce Comprehensive Pilot Zones (CBECPZs) expands the innovation boundaries of firms. We employ a multi-period difference-in-differences (DID) model to analyse panel data for Chinese A-share listed companies from 2010 to 2023, viewing the phased introduction of CBECPZs as a quasi-natural experiment. The empirical results indicate that the establishment of CBECPZs substantially expands the innovation boundaries of firms, as evidenced by an increase in patent applications in new technological domains. This finding is confirmed by parallel-trend checks, propensity-score-matching DID, placebo testing, and double-machine-learning calculations. The mechanism analysis shows that CBEC mainly fosters innovation by improving enterprises’ digital-marketing capacities, reducing information asymmetry, promoting technology spillovers, and encouraging human-capital investment. In addition, the strategy promotes innovation more effectively for eastern Chinese companies, high-technology firms, and non-state-owned enterprises. This study provides micro-level evidence from China regarding the innovative effects of cross-border e-commerce and clarifies how digital trade redefines organisational innovation parameters. In doing so, it offers both theoretical and practical insights for policymakers refining CBEC regulations and businesses leveraging digital platforms for innovation advancement. Full article

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30 pages, 822 KB

Open AccessArticle

Convergence of Corporate Digital Innovation: Herding Behavior or Peer Effects?

by Zuhan Meng, Anna Shi, Sixuan Du and Zhiqi Shen

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 357; https://doi.org/10.3390/jtaer20040357 - 8 Dec 2025

Viewed by 309

Abstract

Following and imitating others’ digital innovation decisions is not always grounded in rational judgment; it may also arise from blind conformity, reflecting a “herding behavior”. Drawing on a panel dataset of Chinese listed firms from 2010 to 2022, this study takes firms in [...] Read more.

Following and imitating others’ digital innovation decisions is not always grounded in rational judgment; it may also arise from blind conformity, reflecting a “herding behavior”. Drawing on a panel dataset of Chinese listed firms from 2010 to 2022, this study takes firms in the same industry as the reference group to investigate the existence, driving mechanisms, and economic consequences of corporate digital innovation convergence. The findings show that both breakthrough and incremental digital innovation exhibit convergence at the firm level and are jointly driven by information transmission, market competition, and resource dependence. However, the economic consequences of these two types of innovation convergence differ significantly. The convergence of breakthrough digital innovation enhances firms’ total factor productivity, return on equity, and capital market value, representing a positive peer effect, whereas the convergence of incremental digital innovation weakens these core indicators, reflecting a herding behavior. The heterogeneity analysis indicates that breakthrough digital innovation convergence is more pronounced in regions with stronger intellectual property protection and in industries with higher technology intensity, while incremental digital innovation convergence is more pronounced among private firms and in industries with lower technology intensity. Our findings provide valuable insights into the interactive dynamics of corporate digital innovation decisions and carry important implications for both theory and practice. Full article

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21 pages, 342 KB

Open AccessArticle

The Use of Selected Automated Tools for Creating PPC Advertising in Chosen Markets in the Czech Republic and Slovakia

by Michal Urbanovič, Martin Holubčík, Jakub Soviar and Gabriel Koman

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 356; https://doi.org/10.3390/jtaer20040356 - 5 Dec 2025

Viewed by 503

Abstract

Online paid advertising is a dynamic form of online marketing that requires precision and a quick response to market changes. Automated tools are used to greatly simplify the process of creating and managing Pay-Per-Click (PPC) campaigns. The purpose of this research is to [...] Read more.

Online paid advertising is a dynamic form of online marketing that requires precision and a quick response to market changes. Automated tools are used to greatly simplify the process of creating and managing Pay-Per-Click (PPC) campaigns. The purpose of this research is to evaluate the impact of implementing an automated PPC management tool (Dotidot) on campaign performance in a travel agency compared with standard Google Ads campaigns. A structured multi-criteria procedure is first applied to select the most suitable tool for the Czech and Slovak markets. The core contribution of the paper is the observational case study of Dotidot and its performance comparison. The subject of the research is a comparative analysis of three PPC automated tools: Conviu, Dotidot, and BlueWinston. The significance of this topic lies in highlighting the relatively new possibilities of digital marketing and choosing the right tool for using automation. This research can also stimulate other researchers in this field and expand knowledge. The analysis is carried out using the method of systematic comparison based on established criteria, the result of which is a recommendation of the preferred tool and a brief discussion of its implementation options. The analyzed tools are used mainly on the Czech and Slovak markets and are oriented towards e-commerce (electronic commerce). In addition to e-commerce, a case study of the use of digital promotion in sports organizations is also presented. The research results in a systematic comparison of Conviu, Dotidot, and BlueWinston tools according to predefined criteria. The research also includes a brief discussion on the possibilities of implementing the recommended tool in practice, as well as an assessment of its benefits and limitations. Full article

22 pages, 1934 KB

Open AccessArticle

The Effect of Digital Literacy on Online Purchase Intention: The Mediating Role of Social Media Use

by Hüseyin Kocarslan and Bozhana Stoycheva

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 355; https://doi.org/10.3390/jtaer20040355 - 5 Dec 2025

Viewed by 600

Abstract

The rapid advancement of information technologies and the widespread use of the Internet have profoundly transformed individuals’ daily practices and consumer behaviors. Notably, the growing influence of social media platforms has shifted a significant portion of commerce to digital environments and deeply affected [...] Read more.

The rapid advancement of information technologies and the widespread use of the Internet have profoundly transformed individuals’ daily practices and consumer behaviors. Notably, the growing influence of social media platforms has shifted a significant portion of commerce to digital environments and deeply affected online purchasing processes. In this context, the purpose of this study is to examine the direct effect of digital literacy on online purchase intention and to investigate the mediating role of social media use within this relationship. The study sample consists of 401 participants from various cities across Türkiye who actively use social media. Data were collected through an online survey and analyzed using the Structural Equation Modeling (SEM) approach. The findings reveal that digital literacy significantly predicts both online purchase intention and social media use. Moreover, social media use has a positive and statistically significant effect on online purchase intention. Importantly, it was found that social media use partially mediates the relationship between digital literacy and online purchase intention. By highlighting how digital literacy and social media jointly influence online consumer behavior in an era of emerging digital technologies and marketing innovation, this study contributes to both the academic literature and practitioners developing effective digital marketing strategies. Full article

(This article belongs to the Special Issue Emerging Technologies and Marketing Innovation)

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29 pages, 1208 KB

Open AccessArticle

The Alchemy of Digital Transformation: How Computing Power Investment Fuels New Quality Productivity

by Yu Hu, Kaiti Zou and Xiaofang Chen

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 354; https://doi.org/10.3390/jtaer20040354 - 5 Dec 2025

Viewed by 351

Abstract

Against the backdrop of China’s “East-West Computing Resource Transfer” and “Digital-Real Integration” national strategies, computing power has emerged as a core engine driving the digital economy. However, existing research lacks in-depth exploration of the micro-level mechanisms through which computing power operates as a [...] Read more.

Against the backdrop of China’s “East-West Computing Resource Transfer” and “Digital-Real Integration” national strategies, computing power has emerged as a core engine driving the digital economy. However, existing research lacks in-depth exploration of the micro-level mechanisms through which computing power operates as a strategic digital resource at the firm level and transforms into competitive advantages. This study examines a sample of manufacturing firms listed on China’s A-share markets from 2011 to 2022, treating the establishment of intelligent computing centers by firms as a quasi-natural experiment. Employing a staggered difference-in-differences model combined with causal inference strategies such as double machine learning, we empirically test the impact of computing power investment on firms’ new quality productivity. The findings reveal that computing power investment significantly enhances new quality productivity, primarily through enabling dynamic capabilities: it strengthens risk perception capabilities by improving information environments, enabling intelligent risk monitoring, and enhancing decision-making resilience; it elevates innovation opportunity-capturing capabilities by expanding the scope of innovation search, accelerating innovation iteration, and facilitating cross-domain knowledge integration; and it achieves data element reconstruction through constructing data infrastructure capabilities, improving data operational efficiency, and optimizing data ecosystem collaboration. Further analysis demonstrates that this promotional effect is more pronounced in firms with strong executive digital cognition and intense market competition, and is more significant among non-heavily polluting, high-tech firms with high absorptive capacity, those located in eastern regions, and those with superior digital endowments. Extended analysis also reveals that the new quality productivity gains from computing power investment drive optimal allocation of human capital while potentially inducing strategic information concealment behaviors as firms seek to protect competitive advantages. By conceptualizing computing power as a contestable strategic resource at the micro level, this study unveils the micro-mechanisms of digital transformation through a dynamic capability framework, offering important implications for firms and governments in optimizing digital strategies. Full article

(This article belongs to the Special Issue Digital Intelligence Empowering the Dual Carbon Strategy and E-Commerce)

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24 pages, 1367 KB

Open AccessArticle

Algorithmic Empowerment and Its Impact on Circular Economy Participation: An Empirical Study Based on Human–Machine Collaborative Decision-Making Mechanisms

by Xingjun Ru, Le Liu and Min Chen

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 353; https://doi.org/10.3390/jtaer20040353 - 5 Dec 2025

Viewed by 349

Abstract

At the intersection of the circular economy and artificial intelligence (AI), high-value secondhand trading faces a “triple decision dilemma” of cognitive overload, trust risk, and emotional attachment. To address the limits of traditional human-centered theories, this study develops and empirically tests a novel [...] Read more.

At the intersection of the circular economy and artificial intelligence (AI), high-value secondhand trading faces a “triple decision dilemma” of cognitive overload, trust risk, and emotional attachment. To address the limits of traditional human-centered theories, this study develops and empirically tests a novel framework of Algorithmic Empowerment. Drawing on data from 1396 users of Chinese secondhand luxury platforms and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings reveal that users’ empowerment perception arises from three dimensions—Algorithmic Connectivity (AC), Human–Agent Symbiotic Trust (HAST), and Algorithmic Value Alignment (AVA). This perceived empowerment affects participation willingness through two parallel pathways: the social pathway, where algorithmic curation shapes social norms and recognition, and the cognitive pathway, where AI enhances decision fluency and reduces cognitive friction. The results confirm the dual mediating effects of these mechanisms. This study advances understanding of human–AI collaboration in sustainable consumption by conceptualizing empowerment as the bridge linking algorithmic functions to user engagement, and provides actionable implications for designing AI systems that both enhance efficiency and foster user trust and identification. Full article

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30 pages, 1057 KB

Open AccessArticle

An Attention-Seq2Seq Model for New Energy Vehicle Sales Prediction

by Yanji Piao and Jiawen Wu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 352; https://doi.org/10.3390/jtaer20040352 - 4 Dec 2025

Viewed by 213

Abstract

With worsening energy and environmental issues, new energy vehicles (NEVs) have emerged as the future of the automotive industry, as they aim to address the high energy consumption and carbon emissions of traditional fuel vehicles. However, due to the industry’s short development history, [...] Read more.

With worsening energy and environmental issues, new energy vehicles (NEVs) have emerged as the future of the automotive industry, as they aim to address the high energy consumption and carbon emissions of traditional fuel vehicles. However, due to the industry’s short development history, limited available data, and incomplete supporting systems, most existing NEV research focuses on theoretical analysis, which hinders the achievement of accurate sales predictions. Today, online reviews influence consumer decisions and thus provide a new perspective for sales forecasting. Based on consumer behavior theory and neural network principles, our research selects factors influencing NEV sales (covering economics, technological, policy, and consumer dimensions, including preprocessed crawled online reviews), constructs an index system screened via grey relational analysis, and establishes five models (SARIMA, GRU, Seq2Seq, Attention-GRU, Attention-Seq2Seq) for training and testing. The study supports the use of online reviews in NEV sales prediction and proves that the model based on cutting-edge technology of Attention-Seq2Seq can outperform the other four methods presented above. Through this, the current contributions advance marketing innovation by helping NEV stakeholders understand relevant information using a predictive model from online reviews, which leads to precise product improvement and optimal distribution of resources as well as precise adoption of marketing strategies. Full article

(This article belongs to the Special Issue Emerging Technologies and Marketing Innovation)

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26 pages, 762 KB

Open AccessArticle

Digital Ripples in Industries: An Institutional Theory Perspective on How Peer Transformation Dismantles Greenwashing Behavior

by Jiajun Xu, Rui Li and Zixuan Peng

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 351; https://doi.org/10.3390/jtaer20040351 - 4 Dec 2025

Viewed by 263

Abstract

This study examines if peers’ digital transformation affects focal firms’ greenwashing, addressing the literature gap of insufficient focus on industry interactions via institutional theory. Using a sample of Chinese listed companies, the paper conducts an empirical analysis and finds that the digital transformation [...] Read more.

This study examines if peers’ digital transformation affects focal firms’ greenwashing, addressing the literature gap of insufficient focus on industry interactions via institutional theory. Using a sample of Chinese listed companies, the paper conducts an empirical analysis and finds that the digital transformation of peer enterprises significantly inhibits the greenwashing behavior of focal enterprises. This inhibitory effect is realized through three key mechanisms: the competitive peer spillover effect of digital transformation, the suppression of peer spillover in greenwashing behavior, and the convergence effect of industry-wide information disclosure quality. Moreover, this inhibitory effect is particularly pronounced in industries characterized by low short-termism tendencies, high technology intensity, high pollution levels, and fierce competition. Further research confirms that the initial emergence of highly digitalized enterprises in an industry triggers a “catfish effect,” and once the proportion of digitalized enterprises exceeds 50%, the inhibitory effect on greenwashing behavior becomes significantly stronger. Full article

(This article belongs to the Special Issue Digital Intelligence Empowering the Dual Carbon Strategy and E-Commerce)

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24 pages, 2794 KB

Open AccessArticle

Crossing Boundaries: How Cross-Niche Influencer Collaborations Enhance Brand Attitude Through Perceived Innovation

by Xiaoxue Wang, Hongyu Zhang, Jiao Feng and Muhammad Khayyam

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 350; https://doi.org/10.3390/jtaer20040350 - 4 Dec 2025

Viewed by 306

Abstract

Influencer marketing practice predominantly favors same-niche partnerships; however, industry evidence suggests that unconventional pairings can sometimes outperform traditional matches, highlighting a knowledge gap regarding how collaboration structure influences consumer response. Drawing on Optimal Distinctiveness Theory, this research examines whether cross-niche collaborations enhance brand [...] Read more.

Influencer marketing practice predominantly favors same-niche partnerships; however, industry evidence suggests that unconventional pairings can sometimes outperform traditional matches, highlighting a knowledge gap regarding how collaboration structure influences consumer response. Drawing on Optimal Distinctiveness Theory, this research examines whether cross-niche collaborations enhance brand evaluations by fulfilling concurrent desires for inclusion and differentiation. Four controlled experiments (total N = 1482) employing Instagram-style stimuli and behavioral intention measures compare same- versus cross-niche alliances while manipulating or measuring consumers’ need for uniqueness and category expertise. Across studies, cross-niche (versus same-niche) collaborations consistently improve brand attitude, an effect fully mediated by heightened perceptions of brand innovation. Moderation analyses reveal that this indirect effect is amplified among consumers high in need for uniqueness but attenuated—and in some cases reversed—among category experts, who tend to prefer the depth signaled by same-niche partnerships. Alternative explanations, including curiosity, source credibility, and message liking, are empirically ruled out. These findings extend Optimal Distinctiveness Theory to influencer branding by identifying collaboration type as a market-level cue signaling innovation while refining influencer effectiveness models through a dual-contingency framework that incorporates motivational and knowledge-based audience factors. From a managerial perspective, the results suggest deploying cross-niche alliances when targeting novelty-seeking or novice segments while preserving niche purity or offering technical justification when addressing expert consumers, thereby aligning collaboration strategies with audience composition. Full article

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23 pages, 405 KB

Open AccessArticle

Research on the Effects of Social Learning and Risk Attitudes on Rural Households’ Participation in Agricultural Product E-Commerce

by Jiaxiang Hu, Jiayi Liu and Yanghe Liu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 349; https://doi.org/10.3390/jtaer20040349 - 4 Dec 2025

Viewed by 284

Abstract

E-commerce for agricultural products serves as a critical link connecting smallholders with markets; however, technological barriers and market uncertainties during its transitional phase have led to low participation rates among farmers, creating a key bottleneck for industrial upgrading. The social learning mechanisms inherent [...] Read more.

E-commerce for agricultural products serves as a critical link connecting smallholders with markets; however, technological barriers and market uncertainties during its transitional phase have led to low participation rates among farmers, creating a key bottleneck for industrial upgrading. The social learning mechanisms inherent in rural communities may influence farmers’ decisions by reshaping risk attitudes—a pathway that has not been sufficiently empirically examined. This study examines how rural social learning affects farmers’ participation in agricultural e-commerce through the channel of risk attitude. Using survey data from 327 peach growers in Qingdao, Shandong, we construct an analytical framework of “social learning–risk attitude–e-commerce participation” and identify the mechanisms with a Heckman two-step model, IV-Probit, and mediation analysis. The results show that both observational and reinforcement learning significantly increase farmers’ probability and intensity of participation; risk attitude partially mediates this relationship, and contextual factors such as logistics accessibility also matter. The contribution lies in embedding social learning and risk attitude in a single empirical framework and providing evidence from a highly digitized yet agricultural Chinese context for tiered rural e-commerce training and risk education. Full article

(This article belongs to the Section Data Science, AI, and e-Commerce Analytics)

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37 pages, 16509 KB

Open AccessArticle

Reselling or Agency Selling: Technology Investment and Information Sharing Strategies in Live Streaming E-Commerce

by Yu-Wei Li, Gui-Hua Lin and Xide Zhu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 348; https://doi.org/10.3390/jtaer20040348 - 4 Dec 2025

Viewed by 416

Abstract

With the rapid development of live streaming e-commerce, opening live streaming sales channels for online product sales has become an important strategic priority for enterprises. This paper examines information technology-driven operational decisions in live streaming e-commerce supply chains, including sales mode selection, technology [...] Read more.

With the rapid development of live streaming e-commerce, opening live streaming sales channels for online product sales has become an important strategic priority for enterprises. This paper examines information technology-driven operational decisions in live streaming e-commerce supply chains, including sales mode selection, technology investment, and information sharing. We develop game-theoretic models for reselling and agency selling modes under three scenarios: no technology investment, investment without information sharing, and investment with information sharing. Our findings show that under the reselling mode, e-tailers tend to accept information sharing when the live streaming creates high extra value or when the market demand is underestimated. Under the agency mode, e-tailers usually reject sharing. Regarding technology investment, platforms are motivated to invest under the reselling mode when the market is underestimated regardless of sharing; in contrast, under the agency mode, platforms only invest when e-tailers accept sharing and the market is severely underestimated, the sharing fee is moderate, and the agency fee and hassle cost are low. A win-win outcome arises when the agency fee is low and live streaming generates low extra value with high hassle costs, making the agency optimal for both e-tailers and platforms; conversely, when the agency fee is high and live streaming generates high extra value with low hassle costs, the reselling becomes optimal. This study provides important strategic guidance and policy insights for supply chain members, enabling firms to make better decisions and thus gain a competitive advantage in the face of fierce market competition. Full article

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18 pages, 513 KB

Open AccessArticle

Watching Ad or Paying Premium: Optimal Monetization of Online Platforms

by Hoshik Shim, Jinhwan Lee and Young Soo Park

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 347; https://doi.org/10.3390/jtaer20040347 - 3 Dec 2025

Viewed by 413

Abstract

Digital platforms face a fundamental strategic decision between subscription-only, advertising-only, and freemium (hybrid) monetization models. We develop a game-theoretic framework that unifies these strategies, explicitly modeling consumer heterogeneity in both willingness-to-pay and advertising disutility, while incorporating network effects through the platform’s valuation of [...] Read more.

Digital platforms face a fundamental strategic decision between subscription-only, advertising-only, and freemium (hybrid) monetization models. We develop a game-theoretic framework that unifies these strategies, explicitly modeling consumer heterogeneity in both willingness-to-pay and advertising disutility, while incorporating network effects through the platform’s valuation of user-base size. Our analysis yields closed-form solutions identifying optimal strategy thresholds based on advertising market conditions. We show that subscription-only dominates when advertising prices are low, advertising-only prevails when prices are high, and freemium emerges as strictly optimal in the intermediate region. Under freemium, we demonstrate strategic complementarity: both subscription fees and advertising intensity exceed their levels in pure strategies because each instrument’s effectiveness is amplified by the other through user reallocation across tiers. Network effects universally reduce monetization intensity but alter instruments’ relative sensitivities differently across regimes—when advertising prices are moderate, freemium adjusts ad length more aggressively, while the opposite holds at high prices. Critically, freemium’s profitability requires sufficient consumer heterogeneity in ad tolerance. As consumer preferences converge, the screening mechanism fails and freemium collapses to the superior pure strategy. These results provide operational guidance for platform monetization decisions and clarify when hybrid models create value beyond traditional approaches. Full article

(This article belongs to the Special Issue Electronic Commerce and Information Management Towards the Digital Era)

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19 pages, 891 KB

Open AccessArticle

The Influence of Personalized AI on Users’ Intention to Continue Using Mobile Payments: A Contingency Perspective

by Na Liang and Eunmi Tatum Lee

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 346; https://doi.org/10.3390/jtaer20040346 - 3 Dec 2025

Viewed by 291

Abstract

Although the use of mobile payments has become increasingly prevalent, understanding the factors that persuade users to continue to rely on the transaction method remains limited. This study applied the Uses and Gratifications Theory and a contingency perspective to examine the relationship between [...] Read more.

Although the use of mobile payments has become increasingly prevalent, understanding the factors that persuade users to continue to rely on the transaction method remains limited. This study applied the Uses and Gratifications Theory and a contingency perspective to examine the relationship between personalized artificial intelligence and users’ intention to continue using mobile payments. Drawing on the contingency perspective, we also assessed four moderating factors: age, educational level, social network, and technological diversity. Using survey data collected from 515 Chinese users and applying hierarchical regression analysis, our results reveal that personalized artificial intelligence significantly enhances users’ intention to continue using mobile payments. Educational level, social network, and technological diversity also have a positive influence but age has a deterring effect. Our empirical findings constitute an academic contribution to a deeper understanding of the dynamics that persuade mobile payment users not to change their routine. Full article

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27 pages, 1840 KB

Open AccessArticle

Investigating the Role of Logistics Delivery Services in Shaping Customer Satisfaction: LLM-Aspect-Based Sentiment Analysis of Perceived Quality in Indonesian E-Commerce

by Arbi Setiyawan, Youshi He and Ray Sastri

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 345; https://doi.org/10.3390/jtaer20040345 - 3 Dec 2025

Viewed by 379

Abstract

A significant challenge in e-commerce is the inability of consumers to physically inspect products, forcing them to rely on perceived quality derived from other consumers’ experiences. However, gaps remain in understanding which dimensions of perceived quality are most frequently mentioned and influential for [...] Read more.

A significant challenge in e-commerce is the inability of consumers to physically inspect products, forcing them to rely on perceived quality derived from other consumers’ experiences. However, gaps remain in understanding which dimensions of perceived quality are most frequently mentioned and influential for customer satisfaction, particularly in emerging markets like Indonesia. This study investigates these gaps by identifying key perceived quality aspects and examining their impact on satisfaction, with a specific focus on the moderating role of logistics delivery services. Using a large language model (LLM), specifically Google’s Gemma 2, we performed aspect-based sentiment analysis on 5000 smartphone reviews from Indonesian e-commerce. Logistic regression models incorporating interaction variables were employed to evaluate the relationships. The results identify the most frequently mentioned aspects of perceived quality: Logistics delivery services, Functionality, Originality, Responsiveness, and Packaging. While Logistics delivery services was the most mentioned aspect, Packaging had the most significant direct influence on satisfaction. Notably, Logistics delivery services also play a significant moderating role, enhancing the positive effect of other perceived quality aspects on satisfaction. These findings suggest that Logistics delivery services contribute directly to satisfaction and amplify other aspects, resulting in greater customer satisfaction. The study contributes to the literature by demonstrating LLM-driven aspect-based sentiment analysis methods and expanding the concept of perceived quality to include service aspects, thus promoting a more complete consideration of perceived quality in e-commerce. Full article

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24 pages, 1386 KB

Open AccessArticle

Social Media Marketing Drives Brand Love and Customer Behavioral Engagement: Gender as a Moderator

by Muhammad Sohaib, Muhammad Asghar Ali and Muhammad Ahmad-ur-Rehman

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 344; https://doi.org/10.3390/jtaer20040344 - 3 Dec 2025

Viewed by 896

Abstract

This study investigates the impact of social media marketing activities on customers’ behavioral engagement with fashion clothing brands in Pakistan. Drawing on the Stimulus–Organism–Response (S–O–R) framework, this study examined how social media marketing activities affect brand love and subsequent consumers’ behavioral engagement, and [...] Read more.

This study investigates the impact of social media marketing activities on customers’ behavioral engagement with fashion clothing brands in Pakistan. Drawing on the Stimulus–Organism–Response (S–O–R) framework, this study examined how social media marketing activities affect brand love and subsequent consumers’ behavioral engagement, and to what extent gender moderates the association between social media marketing activities and brand love. Data were collected through a cross-sectional survey using convenience sampling, resulting in 297 valid responses. Partial Least Squares Structural Equation Modeling using SmartPLS 4 software was employed for the data analysis. The findings revealed that social media marketing activities have a substantial impact on brand love, and brand love, in turn, influences customers’ behavioral engagement. Specifically, social media marketing dimensions, such as entertainment, trendiness, customization, and word of mouth, emerged as statistically significant drivers of brand love, whereas interaction did not exhibit any effects. Furthermore, brand love also serves as a predictor of behavioral engagement. Regarding the moderating role of gender, the results confirm that the effect of customization on brand love is higher for females than for males. Similarly, gender acts as a moderator, indicating that the effect of word of mouth on brand love is stronger for males than for females. This study contributes to the literature by emphasizing the significance of brand love in formulating strategies to enhance consumer engagement in the digital landscape. Full article

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

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28 pages, 2792 KB

Open AccessArticle

Multimodal Deep Learning Framework for Automated Usability Evaluation of Fashion E-Commerce Sites

by Nahed Alowidi

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 343; https://doi.org/10.3390/jtaer20040343 - 3 Dec 2025

Viewed by 467

Abstract

Effective website usability assessment is crucial for improving user experience, driving customer satisfaction, and ensuring business success, particularly in the competitive e-commerce sector. Traditional methods, such as expert reviews and user testing, are resource-intensive and often fail to fully capture the complex interplay [...] Read more.

Effective website usability assessment is crucial for improving user experience, driving customer satisfaction, and ensuring business success, particularly in the competitive e-commerce sector. Traditional methods, such as expert reviews and user testing, are resource-intensive and often fail to fully capture the complex interplay between a site’s aesthetic design and its technical performance. This paper introduces an end-to-end multimodal deep learning framework that automates the usability assessment of fashion e-commerce websites. The framework fuses structured numerical indicators (e.g., load time, mobile compatibility) with high-level visual features extracted from full-page screenshots. The proposed framework employs a comprehensive set of visual backbones—including modern architectures such as ConvNeXt and Vision Transformers (ViT, Swin) alongside established CNNs—and systematically evaluates three fusion strategies: early fusion, late fusion, and a state-of-the-art cross-modal fusion strategy that enables deep, bidirectional interactions between modalities. Extensive experiments demonstrate that the cross-modal fusion approach, particularly when paired with a ConvNeXt backbone, achieves superior performance with a 0.92 accuracy and 0.89 F1-score, outperforming both unimodal and simpler fusion baselines. Model interpretability is provided through SHAP and LIME, confirming that the predictions align with established usability principles and generate actionable insights. Although validated on fashion e-commerce sites, the framework is highly adaptable to other domains—such as e-learning and e-government—via domain-specific data and light fine-tuning. It provides a robust, explainable benchmark for data-driven, multimodal website usability assessment and paves the way for more intelligent, automated user-experience optimization. Full article

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27 pages, 792 KB

Open AccessArticle

The Persuasive Power of AI Avatars Through Trust Transfer and the Elaboration Likelihood Model

by Ching-Jui Keng, Hsiao-Po Bao and Chia-Hung Lin

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 342; https://doi.org/10.3390/jtaer20040342 - 3 Dec 2025

Viewed by 1259

Abstract

Drawing upon the Elaboration Likelihood Model (ELM) and Trust Transfer Theory, this study investigates how AI digital avatars influence consumer trust and purchase intention. Using survey data collected from 378 valid respondents, the proposed model was tested with Partial Least Squares Structural Equation [...] Read more.

Drawing upon the Elaboration Likelihood Model (ELM) and Trust Transfer Theory, this study investigates how AI digital avatars influence consumer trust and purchase intention. Using survey data collected from 378 valid respondents, the proposed model was tested with Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that brand awareness and perceived quality significantly affect purchase intention through product trust, while social endorsement cues, anthropomorphism, and interaction quality indirectly influence purchase intention through AI Avatar trust. Furthermore, both AI Avatar trust and product trust have significant direct effects on purchase intention, highlighting the critical role of trust in AI-driven persuasion processes. This study validates the dual-route persuasion mechanism of the ELM in AI marketing contexts and extends the application of trust theory to human–AI interactions, offering valuable insights for future research on AI brand endorsement and consumer psychology. Full article

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41 pages, 3943 KB

Open AccessArticle

When AI Chatbots Ask for Donations: The Construal Level Contingency of AI Persuasion Effectiveness in Charity Human–Chatbot Interaction

by Jin Sun and Jia Si

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 341; https://doi.org/10.3390/jtaer20040341 - 3 Dec 2025

Viewed by 593

Abstract

As AI chatbots are increasingly used in digital fundraising, it remains unclear which communication strategies are more effective in enhancing consumer trust and donation behavior. Drawing on construal level theory and adopting a human-AI interaction perspective, this research examines how message framing in [...] Read more.

As AI chatbots are increasingly used in digital fundraising, it remains unclear which communication strategies are more effective in enhancing consumer trust and donation behavior. Drawing on construal level theory and adopting a human-AI interaction perspective, this research examines how message framing in AI-mediated persuasive communication shapes trust and donation willingness. Across four studies, we find that when AI chatbots employ high-level construal (abstract) message framing, consumers perceive the information as less credible compared to when the same message is delivered by a human agent. This reduced message credibility weakens trust in the charitable organization through a trust transfer mechanism, ultimately lowering donation intention. Conversely, low-level construal (concrete) framing enhances both trust and donation willingness. Moreover, the negative impact of abstract message framing by AI chatbots is significantly attenuated when the chatbot features anthropomorphic visual cues, which increase perceived credibility and restore trust and donation willingness. These findings reveal potential risks in deploying AI chatbots for interactive fundraising marketing and offer practical insights for nonprofit organizations seeking to leverage AI in donor engagement. Full article

(This article belongs to the Topic Innovations in New Media: Shaping the Future of Interactive Marketing)

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49 pages, 1419 KB

Open AccessArticle

Digital Nomads as Unintentional Influencers in Destination Branding: A Multi-Method Study of Ambient Influence

by Ioanna Simeli, Evangelos Christou and Chryssoula Chatzigeorgiou

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 340; https://doi.org/10.3390/jtaer20040340 - 2 Dec 2025

Viewed by 559

Abstract

This study examines how digital nomads act as unintentional brand ambassadors shaping destination image via lifestyle content. Although nomads influence place perceptions through blogs, vlogs, and social media, tourism institutions rarely acknowledge their role. We theorize this diffuse effect as ambient influence—the cumulative, [...] Read more.

This study examines how digital nomads act as unintentional brand ambassadors shaping destination image via lifestyle content. Although nomads influence place perceptions through blogs, vlogs, and social media, tourism institutions rarely acknowledge their role. We theorize this diffuse effect as ambient influence—the cumulative, non-promotional impact of lifestyle posts—and test whether nomads operate as unintentional brand intermediaries affecting destination image and travel intention. A multi-method design includes a survey of 487 international travelers modeling links among exposure, perceived authenticity, destination image, and travel intention; an experiment with 210 participants comparing nomad versus influencer videos; and interviews with 14 DMO professionals examining institutional responses. Results indicate that nomad content improves destination image and travel intention via perceived authenticity and relational trust. Relative to influencers, nomads are viewed as more credible and less commercially motivated. However, qualitative evidence shows that DMOs often overlook this influence due to ambiguity, control-oriented branding, and reliance on performance metrics ill-suited to informal media. The study formalizes ambient influence to capture the cumulative, non-promotional impact of nomad content and identifies a strategic blind spot in institutional engagement. It contributes by reconceptualizing influence beyond formal marketing and offers guidance for tourism management, including broader recognition frameworks and updated evaluation of user-generated content. Full article

(This article belongs to the Special Issue Emerging Technologies and Marketing Innovation)

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44 pages, 5778 KB

Open AccessArticle

Trust or Skepticism? Unraveling the Communication Mechanisms of AIGC Advertisements on Consumer Responses

by Shoufen Jiang, Wanqing Zheng and Haiyan Kong

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 339; https://doi.org/10.3390/jtaer20040339 - 2 Dec 2025

Viewed by 538

Abstract

In the era of Artificial Intelligence-Generated Content (AIGC) transforming advertising production, existing research lacks comprehensive exploration of how AIGC advertisements shape consumer responses. This study integrates attention allocation theory and the Elaboration Likelihood Model (ELM) to investigate dual cognitive processing mechanisms of relevant [...] Read more.

In the era of Artificial Intelligence-Generated Content (AIGC) transforming advertising production, existing research lacks comprehensive exploration of how AIGC advertisements shape consumer responses. This study integrates attention allocation theory and the Elaboration Likelihood Model (ELM) to investigate dual cognitive processing mechanisms of relevant and divergent AI advertisements via eye-tracking experiments and questionnaires. Findings reveal that relevant AI advertisements enhance perceived usefulness (PU) through product area attention allocation, improving purchase intention; Divergent AI advertisements boost perceived entertainment (PE) via non-product creative cues, positively influencing ad attitudes; and product involvement (PI) moderates these paths as high PI strengthens PU’s role in central processing, while low PI amplifies PE’s effect in peripheral processing. By constructing a dual-path cognitive model, this research bridges gaps in understanding AI advertising’s implicit attention mechanisms and explicit perceptual outcomes. The findings provide theoretical guidance for advertisers to optimize AIGC strategies, balancing technological utility and creative appeal to achieve precise attention guidance and enhance smart marketing effectiveness. Full article

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24 pages, 2996 KB

Open AccessArticle

What Does Bullet Screen Bring to Video Platform? A Theoretical Analysis Comparing Different Bullet Screen Modes

by Xingzhen Zhu and Li Li

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 338; https://doi.org/10.3390/jtaer20040338 - 2 Dec 2025

Viewed by 293

Abstract

Many video platforms (e.g., TikTok and Bilibili) choose to provide bullet screens on their video content. With the different types of bullet screen features, platforms face the challenge of choosing an appropriate bullet screen strategy, especially when consumers have different preferences for bullet [...] Read more.

Many video platforms (e.g., TikTok and Bilibili) choose to provide bullet screens on their video content. With the different types of bullet screen features, platforms face the challenge of choosing an appropriate bullet screen strategy, especially when consumers have different preferences for bullet screens. To address this challenge, this paper constructs a game-theoretic model to analyze the optimal bullet screen strategy for video platforms with two-sided market characteristics. Although there are some arguments that bullet screens can be detrimental to the platform’s advertising business, our study shows that when the bullet screen feature can attract more consumers, it is beneficial for both the platform and the advertisers. Additionally, we found that as consumers’ attention levels toward bullet screens increase or the proportion of bullet screen preference consumers rises, the video platform will enhance the quality of bullet screens provided to consumers and raise advertising pricing for advertisers. However, the platform’s profits do not necessarily increase accordingly and are also influenced by the platform’s bullet screen cost coefficient. Our comparative analysis of the three bullet screen models reveals that when consumers in the market are ad-fatigued, the model that allows bullet screens to cover ads is the optimal choice for the platform, and when there are differences in the cross-side network effects of advertiser to consumers, the model that maximizes the platform’s profits depends on the size of the cross-side network effects of advertiser to consumers. Our study provides important managerial insights for video platforms, especially on how to provide bullet screens under two-sided market structures. In future research, we will strive to better integrate consumer attention theory with theoretical modeling. Full article

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24 pages, 4396 KB

Open AccessArticle

A Two-Stage Deep Reinforcement Learning-Driven Dynamic Discriminatory Pricing Model for Hotel Rooms with Fairness Constraints

by Xinmin Wang, Yuwei Xie, Ling Jian, Wei Liu and Wenting Lv

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 337; https://doi.org/10.3390/jtaer20040337 - 2 Dec 2025

Viewed by 397

Abstract

Big data-driven discriminatory pricing not only creates opportunities to boost hotel profits but also amplifies consumers’ negative perceptions of price fairness. Developing a dynamic discriminatory pricing model with fairness constraints helps hotel room managers formulate optimal pricing strategies. This paper proposes a dynamic [...] Read more.

Big data-driven discriminatory pricing not only creates opportunities to boost hotel profits but also amplifies consumers’ negative perceptions of price fairness. Developing a dynamic discriminatory pricing model with fairness constraints helps hotel room managers formulate optimal pricing strategies. This paper proposes a dynamic discriminatory pricing model with fairness constraints that unifies four pricing models: fixed pricing, dynamic pricing, discriminatory pricing, and dynamic discriminatory pricing. It further proposes a two-stage deep reinforcement learning algorithm to efficiently solve the model and generate optimal pricing strategies. Finally, a case study is conducted to validate the proposed model and algorithm. The results show that the two-stage deep reinforcement learning algorithm can instantaneously derive optimal pricing schemes that satisfy both group and temporal fairness constraints, following a reasonably time-efficient training process. By adjusting the fairness parameters, our model can be transformed into the four types of pricing models, and the performance of the algorithm is validated for the commonly used dynamic pricing and dynamic discriminatory pricing models. Compared to traditional nonlinear programming solution algorithms, this algorithm generates optimal daily prices based on real-time market changes, making it more practically applicable. Full article

(This article belongs to the Special Issue Emerging Technologies and Marketing Innovation)

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24 pages, 761 KB

Open AccessArticle

Application of the Fuzzy MCDM Model for Ranking Social Networks from the Aspect of Perfumery Promotion

by Žaneta Kavaliauskienė, Erika Jonuškienė, Željko Stević and Boris Novarlić

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 336; https://doi.org/10.3390/jtaer20040336 - 1 Dec 2025

Viewed by 394

Abstract

In modern business conditions, where competitiveness is evident across all operational segments, it is necessary to adopt a proactive management approach, i.e., to actively manage business performance. To keep pace with evolving trends and technologies, a daily presence on social networks and an [...] Read more.

In modern business conditions, where competitiveness is evident across all operational segments, it is necessary to adopt a proactive management approach, i.e., to actively manage business performance. To keep pace with evolving trends and technologies, a daily presence on social networks and an adequate level of product promotion are necessary. This paper proposes a Fuzzy MCDM (Multi-Criteria Decision-Making) model to define the future direction of a perfumery regarding the application of digital marketing, using a two-phase group decision-making process. A total of ten digital advertising variants were considered, combining five social networks: Facebook, Instagram, TikTok, YouTube, and Threads. The results obtained through the application of the original Fuzzy MCDM model indicate that companies should focus their efforts on promoting designer and oriental perfumes via Facebook, Instagram, and TikTok in order to enhance growth and potentially expand their business operations. Full article

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18 pages, 822 KB

Open AccessArticle

From Scroll to Store: How Short-Form Video Drives Foot Traffic in Destination Retail

by Kelcie Slaton and Harold Lee

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 335; https://doi.org/10.3390/jtaer20040335 - 1 Dec 2025

Viewed by 586

Abstract

Short-form video platforms such as TikTok, Instagram Reels, and YouTube Shorts have become influential social commerce and interactive marketing tools, shaping consumer attitudes and behaviors beyond the digital environment. This study examines how short-form video content affects consumers’ intention to visit destination retail [...] Read more.

Short-form video platforms such as TikTok, Instagram Reels, and YouTube Shorts have become influential social commerce and interactive marketing tools, shaping consumer attitudes and behaviors beyond the digital environment. This study examines how short-form video content affects consumers’ intention to visit destination retail stores by integrating the Theory of Planned Behavior (TPB) with the constructs of perceived usefulness, curiosity, and envy. Data from 423 Gen Z and Millennial consumers were collected through an online survey and analyzed using structural equation modeling. The findings indicate that perceived usefulness, curiosity, and envy significantly influence attitudes toward short-form video content, which subsequently drive intentions to visit destination retailers. Social influence also emerged as a stronger predictor of behavioral intention than practical barriers such as cost or accessibility, underscoring the importance of peer validation in motivating digital-to-physical consumer behavior. This study advances electronic commerce research by extending TPB to short-form video marketing and identifying key emotional and cognitive triggers that facilitate consumer engagement. Practically, the results highlight strategies for retailers to develop video campaigns that spark curiosity, evoke aspirational emotions, and leverage social endorsement. More broadly, the study demonstrates how short-form video platforms operate as interactive ecosystems that merge emotional engagement, social validation, and technological affordances to shape hybrid consumer journeys from digital exposure to in-store action. Full article

(This article belongs to the Topic Innovations in New Media: Shaping the Future of Interactive Marketing)

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17 pages, 14022 KB

Open AccessArticle

Aggregate Sales Forecasting Based on Spatial Correlation in Retail

by Bing Zhu, Zhengqian Sun, Seppe vanden Broucke, Keyi Lan and Duoxi Xiao

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 334; https://doi.org/10.3390/jtaer20040334 - 1 Dec 2025

Viewed by 321

Abstract

Aggregated sales forecasting is an important research topic in the highly competitive retail industry. With the availability of different data sources, various techniques and models have been proposed for aggregated sales forecasting. However, existing methods often overlook the spatial correlation in sales between [...] Read more.

Aggregated sales forecasting is an important research topic in the highly competitive retail industry. With the availability of different data sources, various techniques and models have been proposed for aggregated sales forecasting. However, existing methods often overlook the spatial correlation in sales between neighboring retailers. In this paper, we propose a new framework for aggregated sales forecasting based on the deep learning technique ConvLSTM with an attention mechanism to solve this challenge. In the new framework, ConvLSTM is utilized to fully leverage spatially relevant information from adjacent retailers, while the attention mechanism is employed to capture spatial dependencies and select the most pertinent data from spatial inputs. Furthermore, a spatial sliding window technique is designed to augment the sample size. To validate the efficacy of our proposed framework, we conducted experiments using real-world retail sales data and compared our model with established benchmarks. Additionally, we conducted an ablation study to assess the contributions of key components, including the attention mechanism and spatial data augmentation. The experimental results demonstrate that our proposed model effectively improves the prediction performance, offering a novel approach to aggregate sales forecasting for both industry and academia. Full article

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19 pages, 1365 KB

Open AccessArticle

Strategies for Live-Streaming E-Commerce in an E-Platform Supply Chain: Key Opinion Leader Live-Streaming or Manufacturer Self-Broadcasting?

by Wenting Yang, Lu Liu, Wenjuan Yang and Song Xu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 333; https://doi.org/10.3390/jtaer20040333 - 1 Dec 2025

Viewed by 427

Abstract

Live-streaming e-commerce is a popular promotional method for attracting more customers in the era of the platform economy. This study investigates a better strategy for live-streaming sales for a manufacturer in an e-platform-based supply chain. Specifically, the manufacturer has two options—self-broadcasting or key [...] Read more.

Live-streaming e-commerce is a popular promotional method for attracting more customers in the era of the platform economy. This study investigates a better strategy for live-streaming sales for a manufacturer in an e-platform-based supply chain. Specifically, the manufacturer has two options—self-broadcasting or key opinion leader (KOL) live-streaming—to sell products on the e-platform, which acts as a reseller and agency seller in the dual-channel supply chain. We established three Stackelberg models for the supply chain and derived the equilibrium decisions and profits of supply-chain members under three scenarios: without live-streaming, KOL live-streaming, and manufacturer self-broadcasting. After a comparative analysis, we obtained the following key results: First, even if the influence level of the KOL is within a low range, the manufacturer should change the strategy from no live-streaming e-commerce to KOL live-streaming, with a decrease in the agency fee charged from the e-platform. However, with the continued decline in agency fee, the manufacturer should change the strategy from KOL live-streaming to self-broadcasting. Furthermore, we found a win–win zone such that both supply-chain members are better off under the KOL scenario when both the agency fee of the e-platform and the influence level of the KOL are in higher ranges. Our study not only provides a theoretical basis for the enterprise to choose the appropriate live-streaming mode but also helps it to further increase profits and reduce operational risks. In the future, we will further incorporate theoretical analyses into empirical study to discover more interesting results. Full article

(This article belongs to the Topic Livestreaming and Influencer Marketing)

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22 pages, 1519 KB

Open AccessArticle

Open or Modular? The Influence of AIGC Interactive Interface on User Platform Engagement

by Zhiyong Yang, Lianlian Song and Mengnan Qiu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 332; https://doi.org/10.3390/jtaer20040332 - 1 Dec 2025

Viewed by 292

Abstract

How human–AI interactive interfaces affect user engagement with AIGC platforms is a critical underexplored issue. Grounded in signaling theory, this paper constructs a theoretical model to examine the differential effects of two interactive interfaces—modular versus open—on user platform engagement, the mediating role of [...] Read more.

How human–AI interactive interfaces affect user engagement with AIGC platforms is a critical underexplored issue. Grounded in signaling theory, this paper constructs a theoretical model to examine the differential effects of two interactive interfaces—modular versus open—on user platform engagement, the mediating role of AIGC quality, and the moderating role of user type. Through two scenario experiments, our findings reveal that both AI interactive interfaces (open and modular) significantly enhance user platform engagement, with the open interface exhibiting a stronger effect. Specifically, AIGC accuracy serves as a mediator in the relationship between modular interfaces and user engagement, and innovativeness plays a mediating role in the relationship between the open interface and users’ engagement. Furthermore, novice users strengthen the effect of open AIGC interfaces on AIGC innovation and subsequent engagement, Non-novice users amplify the positive impact of modular AIGC interfaces on both AIGC accuracy; however, there is no significant difference for user engagement. These findings theoretically enrich the customer response model in the literature on human–computer interactions and provide actionable insights for AIGC platform enterprises. By designing tailored interactive interfaces, platforms can generate high-quality, user-perceived AIGC for diverse customer segments. This study offers both theoretical contributions and practical implications for the development of AI-driven user engagement strategies. Full article

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17 pages, 308 KB

Open AccessArticle

A Study on the Influence Mechanism of Emotional Interaction and Consumer Digital Hoarding in Agricultural Live Social E-Commerce

by Zhikun Yue, Linling Zhong, Wang Zhang and Xungang Zheng

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 331; https://doi.org/10.3390/jtaer20040331 - 1 Dec 2025

Viewed by 373

Abstract

Consumer digital hoarding is becoming increasingly common in agricultural live social e-commerce, where the abundance of product information, seasonal promotions, and origin-based narratives make consumers more inclined to accumulate digital content such as product links, coupons, and live-stream screenshots. This phenomenon not only [...] Read more.

Consumer digital hoarding is becoming increasingly common in agricultural live social e-commerce, where the abundance of product information, seasonal promotions, and origin-based narratives make consumers more inclined to accumulate digital content such as product links, coupons, and live-stream screenshots. This phenomenon not only affects consumers’ digital mental health, consumption behavior, and decision-making ability, but also poses challenges to agricultural merchants and platforms in terms of customer conversion, precision marketing, and supply chain management. Drawing on the SOR model and integrating construal level theory, this paper constructs a research framework to analyze the key factors influencing consumers’ willingness to digitally hoard in the context of agricultural live social e-commerce. Based on a questionnaire survey of 322 consumers, and using the Ordered Probit (O-Probit) model, the empirical results show that emotional interaction significantly influences digital hoarding intention through the chain mediating effects of emotional attachment and fear of missing out (FOMO). Furthermore, social distance and immersion serve as boundary conditions in this mechanism. Our findings not only deepen the understanding of consumer digital hoarding behavior in agricultural live e-commerce, but also provide new insights for agricultural merchants and platforms to better design interaction strategies, balance consumers’ digital accumulation with actual purchasing conversion, and enhance the efficiency of agricultural product marketing. Full article

(This article belongs to the Topic Livestreaming and Influencer Marketing)

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23 pages, 913 KB

Open AccessArticle

Clicks, Bricks, and Carbon: Digitalization’s Double-Edged Impact on Supply Chain Emissions Intensity

by Raluca Iuliana Georgescu, Maxim Cetulean, Dumitru Alexandru Bodislav and Andrei Hrebenciuc

J. Theor. Appl. Electron. Commer. Res. 2025, 20(4), 330; https://doi.org/10.3390/jtaer20040330 - 1 Dec 2025

Viewed by 229

Abstract

This paper assesses whether national level digitalization is associated with lower greenhouse gas emissions intensity, and under which conditions the association holds, using an unbalanced panel for twenty-seven European countries from 2014 to 2022. Digitalization is measured through a principal component index constructed [...] Read more.

This paper assesses whether national level digitalization is associated with lower greenhouse gas emissions intensity, and under which conditions the association holds, using an unbalanced panel for twenty-seven European countries from 2014 to 2022. Digitalization is measured through a principal component index constructed from enterprise information technology adoption and fixed broadband subscriptions per capita. The outcome is the logarithm of emissions per unit of gross domestic product. Identification is implemented with two-way fixed effects and Driscoll–Kraay standard errors to exploit within country variation, and dynamic bias and potential endogeneity are probed through parsimonious difference GMM designs. Robustness is assessed through alternative outcomes, country specific linear trends, clustered inference, and leave one out checks. Evidence for an unconditional reduction in emissions intensity associated with digitalization is not found. It is predicted that the relationship between digitalization and e-commerce will be positive and statistically significant, thus meaning that at the median and the upper quartile of e-commerce a one standard deviation increase in digitalization relates to increases in intensity of about 2.4% and 3.3%, respectively. More renewable energy shares come with lower intensity and mitigate the digitalization effect. The contribution here attempts to quantify such conditional associations within a multi-country setting and thereby infer design and energy contexts wherein environmental gains from digital expansion would most likely take place. Full article

(This article belongs to the Special Issue Digitalization and Sustainable Supply Chain)

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J. Theor. Appl. Electron. Commer. Res., Volume 20, Issue 4 (December 2025) – 107 articles

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