Journal of Theoretical and Applied Electronic Commerce Research

23 pages, 3925 KB

Open AccessArticle

From Visibility to Trust: The Impact of Agricultural Product Packaging Images in Livestreaming on Consumer Perception and Repurchase Intention

by Huanchen Tang, Jingwen Liang, Jinjin Liu, Miqi Shen and Xiaodong Liu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 248; https://doi.org/10.3390/jtaer20030248 - 11 Sep 2025

Abstract

This study investigates how the packaging image of agricultural products in livestreaming commerce influences consumers’ repurchase intentions and, on this basis, formulates effective packaging improvement strategies to enhance repurchase intention. Focusing on agricultural product packaging, we conducted an online survey of 392 consumers [...] Read more.

This study investigates how the packaging image of agricultural products in livestreaming commerce influences consumers’ repurchase intentions and, on this basis, formulates effective packaging improvement strategies to enhance repurchase intention. Focusing on agricultural product packaging, we conducted an online survey of 392 consumers with livestream shopping experience and employed a combined approach of structural equation modeling (SEM) and artificial neural networks (ANNs) to analyze the effects of packaging image on repurchase intention. Starting from elements of packaging design—such as external appearance, cultural cues, imagery, and materials—we examined color schemes, typography, and illustration styles and further explored how these factors shape repurchase intention by elevating consumers’ perceived value. The findings indicate that the information-conveying functions of packaging—namely the communication of product culture, quality, and distinctive attributes—have a significant impact on repurchase intention. SEM results reveal that perceived value plays a pivotal mediating role between packaging image and repurchase intention. Complementarily, ANN analysis identifies visual appearance as the strongest predictor of repurchase intention among all packaging elements. Building on these insights, the study proposes concrete packaging design strategies, including optimizing visual appearance to highlight brand distinctiveness; distilling design symbols to narrate brand stories; and mining cultural connotations to strengthen cultural expression. This research not only verifies the importance of packaging design in boosting consumers’ repurchase intentions but also offers a practical strategic framework that can be extended to packaging design practices for other agricultural products. It provides new theoretical support and practical guidance for the field, offering a valuable reference for future research and practice. Full article

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

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25 pages, 1886 KB

Open AccessSystematic Review

Examining the Predictors of Consumer Trust and Social Commerce Engagement: A Systematic Literature Review

by Asiri Ahmad, Norjihan Abdul Ghani and Suraya Hamid

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 247; https://doi.org/10.3390/jtaer20030247 - 8 Sep 2025

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Abstract

Trust and engagement in social commerce are increasingly recognized as critical drivers of consumers’ purchase intentions. This study aims to review the existing literature on consumer trust and engagement in social commerce by identifying the main predictors, examining research trends and gaps, and [...] Read more.

Trust and engagement in social commerce are increasingly recognized as critical drivers of consumers’ purchase intentions. This study aims to review the existing literature on consumer trust and engagement in social commerce by identifying the main predictors, examining research trends and gaps, and suggesting clear directions for future studies to better understand and support consumer behavior in this context. The study conducted a systematic literature review and a thematic analysis. The findings showed that four main themes were identified, including technological, organizational, social, and motivational. Under these four themes, eighteen sub-themes were identified. This study is innovative in systematically integrating predictors of consumer trust and engagement into a unified framework that positions trust as a mediator, and in developing a thematically grounded synthesis of four themes and eighteen sub-themes, highlighting underexplored areas such as entertainment and emerging technologies for future research. The studies of consumer trust and engagement are increasing in emerging economies. The study highlights the gaps in the current literature, including inadequate integration across theme categories, insufficient focus on emerging technologies such as blockchain and artificial intelligence, and a lack of examination of cultural and emotional aspects. Future research should deploy longitudinal designs, cross-cultural comparisons, and mixed-methods techniques to address these gaps. This study enhances the comprehension of trust and engagement in social commerce, offering significant insights for platform developers, marketers, and policymakers. Full article

(This article belongs to the Section e-Commerce Analytics)

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32 pages, 1736 KB

Open AccessArticle

AI Digital Human Responsiveness and Consumer Purchase Intention: The Mediating Role of Trust

by Jinpeng Wen and Xiaohua Li

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 246; https://doi.org/10.3390/jtaer20030246 - 8 Sep 2025

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Abstract

This study investigates how AI-driven virtual anchors affect consumers’ purchase intentions by identifying their key attributes, underlying mechanisms, and configurational interplay. We integrate latent Dirichlet allocation (LDA), structural equation modeling (SEM), and fuzzy-set qualitative comparative analysis (fsQCA) into a unified methodological framework. Empirical [...] Read more.

This study investigates how AI-driven virtual anchors affect consumers’ purchase intentions by identifying their key attributes, underlying mechanisms, and configurational interplay. We integrate latent Dirichlet allocation (LDA), structural equation modeling (SEM), and fuzzy-set qualitative comparative analysis (fsQCA) into a unified methodological framework. Empirical evidence demonstrates that the public visibility of virtual anchors exerts a significant positive impact on purchase intention, whereas professionalism, responsiveness, and personalization primarily cultivate consumer pleasure and trust, yet exert limited direct influence on purchase decisions. Emotional states—arousal, pleasure, and trust—mediate the relationship between anchor characteristics and purchase intention. fsQCA further reveals that high purchase intention emerges when responsiveness serves as a necessary condition, trust operates as a pivotal hub, and arousal/pleasure function as emotional conduits; conversely, low purchase intention is chiefly attributable to deficiencies in visibility, responsiveness, and trust. By synthesizing the SOR (stimulus-organism-response) model with the PAD (Pleasure-Arousal-Dominance) emotion theory, this research extends theoretical insights into consumer behavior within e-commerce live-streaming contexts and provides actionable guidance for optimizing virtual anchor strategies, thereby advancing both standardization and innovation in the industry. Full article

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

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37 pages, 836 KB

Open AccessArticle

Unpacking Customer Experience in Online Shopping: Effects on Satisfaction and Loyalty

by Paulo Botelho Pires, Beatriz Martins Perestrelo and José Duarte Santos

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 245; https://doi.org/10.3390/jtaer20030245 - 6 Sep 2025

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Abstract

Drawing on experience–satisfaction–loyalty, this study models how specific digital retail interface attributes translate into behavioural outcomes. Survey data from Portuguese online shoppers were analysed with PLS-SEM to test a formative–reflective framework linking Interactivity and Technologies, Trust–Security–Privacy, Fulfilment and Service Quality, Usability and Web [...] Read more.

Drawing on experience–satisfaction–loyalty, this study models how specific digital retail interface attributes translate into behavioural outcomes. Survey data from Portuguese online shoppers were analysed with PLS-SEM to test a formative–reflective framework linking Interactivity and Technologies, Trust–Security–Privacy, Fulfilment and Service Quality, Usability and Web Design, Personalisation and Customisation and Omnichannel Integration to customer experience (CX), customer satisfaction (CS), customer loyalty (CL) and electronic word of mouth (eWOM). The model explains 62.6% of CX, 70.1% of CS and 66.7% of CL. CX is strongly associated with CS and CS, in turn, with CL; associations with eWOM are non-significant, revealing a theoretical blind spot around advocacy. Interactivity and Technologies, Trust–Security–Privacy and Fulfilment and Service Quality emerge as the most significant antecedents of CX, whereas Omnichannel Integration is inert. The findings advance digital commerce theory by decoupling advocacy from evaluative satisfaction and by reconceptualising integration as multidimensional. Practically, they prioritise investment in interactive, secure and fulfilment capabilities while signalling that loyalty is not associated with advocacy. This study concludes by outlining measurement refinements and longitudinal avenues to capture social–motivational drivers of eWOM. Full article

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18 pages, 819 KB

Open AccessArticle

The Impact of Mobile Advertising Cue Types on Consumer Response Behaviors: Evidence from a Field Experiment

by Yuan Li, Xiaoyu Deng and Banggang Wu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 244; https://doi.org/10.3390/jtaer20030244 - 5 Sep 2025

Viewed by 355

Abstract

This study investigates how different mobile advertising cues (WOM, product, and price cues) affect consumer responses in terms of advertisement clicks and purchases. A large-scale field experiment was conducted on a mobile online learning platform with 45,000 users representing different customer life cycle [...] Read more.

This study investigates how different mobile advertising cues (WOM, product, and price cues) affect consumer responses in terms of advertisement clicks and purchases. A large-scale field experiment was conducted on a mobile online learning platform with 45,000 users representing different customer life cycle stages, in which users were randomly assigned to one of three mobile advertisement types. Behavioral data on clicks and purchases were collected, and the dual-system processing model was used to analyze mediating effects. Consumers were more likely to click on adverts featuring WOM and price cues than product cues, but less likely to purchase. Purchasing experience moderated this effect: experienced consumers showed higher purchase probabilities for WOM and price cues. Affective processing mediated click behavior, while cognitive processing mediated purchases. This study advances cue theory in the mobile context by identifying distinct psychological and behavioral mechanisms driving consumer engagement and conversion. It highlights the importance of tailoring mobile advert strategies based on cue type and user experience. Full article

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

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18 pages, 850 KB

Open AccessArticle

Research on the Influence Mechanism of AI Sound Cues on Decision Outcomes from the Perspective of Perceptual Contagion Theory

by Xintao Yu, Qing Gu and Xiaochen Liu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 243; https://doi.org/10.3390/jtaer20030243 - 5 Sep 2025

Viewed by 264

Abstract

As AI recommendation systems become increasingly important in consumer decision-making, leveraging sound cues to optimize user interaction experience has become a key research topic. Grounded in the theory of perceptual contagion, this study centers on sound cues in AI recommendation scenarios, systematically examining [...] Read more.

As AI recommendation systems become increasingly important in consumer decision-making, leveraging sound cues to optimize user interaction experience has become a key research topic. Grounded in the theory of perceptual contagion, this study centers on sound cues in AI recommendation scenarios, systematically examining their impact on consumer choice and choice satisfaction, as well as the underlying psychological mechanisms. Study 1 (hotel recommendation, N = 155) demonstrated that embedding sound cues into recommendation interfaces significantly increased consumer choice and choice satisfaction. Study 2 (laptop recommendation, N = 155) further revealed that this effect was mediated by preference fluency. Contrary to expectations, AI literacy did not moderate these effects, suggesting that sound cues exert influence across different user groups regardless of technological expertise. Theoretically, this study (1) introduces the theory of perceptual contagion into AI-human interaction research; (2) identifies preference fluency as the core mediating mechanism; and (3) challenges the traditional assumptions about the role of AI literacy. Practically, this study proposes a low-cost and highly adaptable design strategy, providing a new direction for recommendation systems to shift from content-driven to experience-driven. These findings enrich the understanding of sensory influences in digital contexts and offer practical insights for optimizing the design of AI platforms. Full article

(This article belongs to the Topic Neuromarketing and Sensory Experience in the Age of Emerging Technologies)

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27 pages, 2304 KB

Open AccessArticle

“Sharing Is Bonding”: How Influencer Self-Disclosure Fuels Word-of-Mouth via Consumer Identification

by Xiaoxue Wang, Xin Chen, Miao Miao and Muhammad Khayyam

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 242; https://doi.org/10.3390/jtaer20030242 - 5 Sep 2025

Viewed by 371

Abstract

The growing influence of social media personalities in shaping consumer behavior presents significant opportunities and challenges for marketers. This research integrates Social Identity Theory with the influencer marketing literature to investigate how influencer self-disclosure affects word-of-mouth intentions through consumer identification. Across four experiments [...] Read more.

The growing influence of social media personalities in shaping consumer behavior presents significant opportunities and challenges for marketers. This research integrates Social Identity Theory with the influencer marketing literature to investigate how influencer self-disclosure affects word-of-mouth intentions through consumer identification. Across four experiments (N = 1048), we demonstrate that high influencer self-disclosure consistently increases consumers’ word-of-mouth intentions compared to low self-disclosure. Consumer identification with the influencer mediates this relationship, providing a psychological mechanism through which personal narratives translate into advocacy behaviors. Furthermore, we identify two important boundary conditions: self-concept clarity moderates the relationship between self-disclosure and identification, with stronger effects for consumers experiencing identity uncertainty; and cultural collectivism orientation moderates the identification-to-WOM pathway, with collectivistic mindsets amplifying the translation of identification into advocacy. These findings contribute to both theory and practice by elucidating the psychological processes underlying influencer effectiveness and offer strategic guidance for optimizing influencer communication across diverse consumer segments and cultural contexts. Full article

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

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26 pages, 3206 KB

Open AccessArticle

User Psychological Perception and Pricing Mechanism of AI Large Language Model

by Xu Yan, Yiting Hu, Jianhua Zhu and Xiaodong Yang

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 241; https://doi.org/10.3390/jtaer20030241 - 4 Sep 2025

Viewed by 368

Abstract

With the rapid growth of user demand for large language models (LLMs) in their work, the application market is driving intense competition among large language model providers (LLMPs). Users have different preferences and psychological perceptions towards the charging models of different LLMPs. LLMPs [...] Read more.

With the rapid growth of user demand for large language models (LLMs) in their work, the application market is driving intense competition among large language model providers (LLMPs). Users have different preferences and psychological perceptions towards the charging models of different LLMPs. LLMPs with different intelligence levels must design pricing strategies based on diverse user characteristics. To investigate the impact of user heterogeneity on the strategic pricing of competing LLMPs, this paper establishes a competitive model with two providers, comprising a highly intelligent initial LLM provider and a follower provider. Both providers can independently decide to adopt either a subscription model or a pay-per-use model, resulting in four pricing mode combinations (dual subscription SS, subscription-pay-per-use SD, pay-per-use-subscription DS, dual pay-per-use DD). The study shows that when the pay-per-use model is adopted, the user’s psychological perception of the “tick-tock effect” reduces the provider’s service price and profit, as the perceived psychological cost lowers the user’s valuation of the product, thereby decreasing demand. Furthermore, we analyze the equilibrium strategies for pricing mode selection by the two providers. The results indicate that the subscription model is not always advantageous for providers. Both providers will only choose to adopt the subscription model when both user usage frequency and perceived psychological cost are high. Conversely, when both user usage frequency and perceived psychological cost are low, the two providers will not simultaneously adopt the subscription model. Interestingly, as the product intelligence levels of the two providers converge, their choices of pricing modes are also more inclined to diverge. These insights guide LLMPs to strategically adjust their pricing models based on user behavioral patterns to maximize profitability in the competitive AI market. Full article

(This article belongs to the Special Issue ICEC 2025: Transforming E-Commerce with AI: Navigating Innovation, Personalization, and Ethical Challenges)

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38 pages, 2474 KB

Open AccessArticle

Generative and Adaptive AI for Sustainable Supply Chain Design

by Sabina-Cristiana Necula and Emanuel Rieder

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 240; https://doi.org/10.3390/jtaer20030240 - 4 Sep 2025

Viewed by 340

Abstract

This study explores how the integration of generative artificial intelligence, multi-objective evolutionary optimization, and reinforcement learning can enable sustainable and cost-effective decision-making in supply chain strategy. Using real-world retail demand data enriched with synthetic sustainability attributes, we trained a Variational Autoencoder (VAE) to [...] Read more.

This study explores how the integration of generative artificial intelligence, multi-objective evolutionary optimization, and reinforcement learning can enable sustainable and cost-effective decision-making in supply chain strategy. Using real-world retail demand data enriched with synthetic sustainability attributes, we trained a Variational Autoencoder (VAE) to generate plausible future demand scenarios. These were used to seed a Non-Dominated Sorting Genetic Algorithm (NSGA-II) aimed at identifying Pareto-optimal sourcing strategies that balance delivery cost and CO₂ emissions. The resulting Pareto frontier revealed favorable trade-offs, enabling up to 50% emission reductions for only a 10–15% cost increase. We further deployed a deep Q-learning (DQN) agent to dynamically manage weekly shipments under a selected balanced strategy. The reinforcement learning policy achieved an additional 10% emission reduction by adaptively switching between green and conventional transport modes in response to demand and carbon pricing. Importantly, the agent also demonstrated resilience during simulated supply disruptions by rerouting decisions in real time. This research contributes a novel AI-based decision architecture that combines generative modeling, evolutionary search, and adaptive control to support sustainability in complex and uncertain supply chains. Full article

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

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18 pages, 574 KB

Open AccessArticle

When AI Meets Livestreaming: Exploring the Impact of Virtual Anchor on Tourist Travel Intention

by Zhengan Zhu, Colin M. Hall, Li Tao, Zichan Qin and Yue Li

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 239; https://doi.org/10.3390/jtaer20030239 - 3 Sep 2025

Viewed by 1001

Abstract

The development of Artificial intelligence (AI) technology has brought new ideas and opportunities to destination marketing. However, existing studies lack sufficient empirical research to explore the impact of AI anchors on tourists’ travel intentions. To fill this research gap, this study explores the [...] Read more.

The development of Artificial intelligence (AI) technology has brought new ideas and opportunities to destination marketing. However, existing studies lack sufficient empirical research to explore the impact of AI anchors on tourists’ travel intentions. To fill this research gap, this study explores the influence of perceived anthropomorphism and perceived playfulness on tourists’ telepresence, inspiration, and travel intention in AI virtual anchor-based travel livestreaming. Through the analysis of 291 valid data sets, it was found that in AI virtual anchor-based travel livestreaming, perceived anthropomorphism positively affects telepresence but does not affect tourists’ inspiration. Playfulness positively affects tourists’ telepresence and inspiration in AI virtual anchor-based travel livestreaming. This study also found that neither perceived anthropomorphism nor perceived playfulness directly affects tourists’ travel intention, but both can be achieved through the mediating effect of telepresence. The findings provide empirical evidence of the value for tourism researchers and destinations in adopting AI technology for livestreaming. Full article

(This article belongs to the Special Issue Emerging Digital Technologies and Consumer Behavior)

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18 pages, 335 KB

Open AccessArticle

Digital Selves and Curated Choices: How Social Media Self-Presentation Enhances Consumers’ Experiential Consumption Preferences

by Yun Zou, Shengqi Zhang and Yong Wang

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 238; https://doi.org/10.3390/jtaer20030238 - 3 Sep 2025

Viewed by 374

Abstract

With the rise of e-commerce, mobile devices, and social media, consumers’ online social and shopping behaviors have become increasingly integrated, making social commerce a major force in the digital marketplace. In this context, consumer behaviors on social media can exert a profound influence [...] Read more.

With the rise of e-commerce, mobile devices, and social media, consumers’ online social and shopping behaviors have become increasingly integrated, making social commerce a major force in the digital marketplace. In this context, consumer behaviors on social media can exert a profound influence on purchase decisions. This research investigates the impact of social media self-presentation, a key social behavior on social media, on consumers’ preference for experiential consumption. Drawing on one survey study and one experimental study, the findings reveal that social media self-presentation significantly predicts a stronger preference for experiential consumption (e.g., travel) over material consumption (e.g., tangible goods), with this effect being particularly salient among female participants. Furthermore, self-concept clarity mediates this relationship: both positive and authentic self-presentation enhance individuals’ clarity of self-concept, which in turn promotes a greater inclination toward experiential purchases. These findings highlight the key role of social media behavior in shaping consumer behaviors. The results offer important theoretical and practical insights into consumer decision-making in digital contexts and guide platform design and personalized recommendation systems. Full article

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

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24 pages, 1916 KB

Open AccessArticle

Influence of Goal-Framing Type and Product Type on Consumer Decision-Making: Dual Evidence from Behavior and Eye Movement

by Siyuan Wei, Jing Gao, Taiyang Zhao and Shengliang Deng

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 237; https://doi.org/10.3390/jtaer20030237 - 3 Sep 2025

Viewed by 356

Abstract

In today’s fierce market competition, enterprises must quickly attract consumers’ attention to products and prompt them to make purchases. Based on regulatory focus theory, this study examines the impact of the congruence between different types of goal framing in advertising (promotion vs. prevention) [...] Read more.

In today’s fierce market competition, enterprises must quickly attract consumers’ attention to products and prompt them to make purchases. Based on regulatory focus theory, this study examines the impact of the congruence between different types of goal framing in advertising (promotion vs. prevention) and product types (hedonic vs. utilitarian) on individual consumer decision-making, as well as the underlying psychological mechanisms. The findings are as follows: (1) A goal-framing effect was observed, such that individuals allocated more attention and exhibited higher purchase intentions toward products presented with promotion-framed advertising. (2) A matching effect between goal-framing type and product type was identified: promotion framing increased purchase intentions for hedonic products, whereas prevention framing increased purchase intentions for utilitarian products. (3) Processing fluency mediated the effect of goal–product matching on consumer decision-making. (4) The presence of time pressure amplified the goal-framing effect, leading to stronger preferences under promotion-framed advertisements, as reflected in both longer fixation durations and higher purchase intentions. By integrating regulatory focus theory with product type matching, this study leverages eye-tracking data to reveal the cognitive processes underlying consumer decision-making and the moderating role of time pressure on goal-framing effects. The findings enrich the motivational perspective in consumer behavior research and provide empirical guidance for designing differentiated advertising strategies and optimizing advertising copy. Full article

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

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26 pages, 936 KB

Open AccessArticle

The Impact of Digital Marketing Capability on Firm Performance: Empirical Evidence from Chinese Listed Manufacturing Firms

by Zhihao Liang, Jinming Du and Ying Hua

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 236; https://doi.org/10.3390/jtaer20030236 - 3 Sep 2025

Viewed by 455

Abstract

The rapid expansion of e-commerce has pushed firms to adopt more sophisticated digital marketing strategies to reach, engage, and retain consumers. Research has shown that digital marketing significantly enhances firm performance by enhancing marketing-related capabilities, yet overlooks its role in driving transformation across [...] Read more.

The rapid expansion of e-commerce has pushed firms to adopt more sophisticated digital marketing strategies to reach, engage, and retain consumers. Research has shown that digital marketing significantly enhances firm performance by enhancing marketing-related capabilities, yet overlooks its role in driving transformation across other business functions. Grounded in resource orchestration theory, this study examines how digital marketing resources and capabilities support broader business transformation and comprehensively improve firm performance. Drawing on empirical data from Chinese A-share listed manufacturing firms from 2010 to 2023, this study demonstrates that there is a significant positive relationship between digital marketing capability and firm performance. Notably, this relationship is mediated by production capability and R&D capability. Moreover, the effect is more pronounced in firms operating in highly marketized regions, within competitive industries, and among digitally advanced firms. This study contributes to the digital marketing literature by developing a novel framework for measuring digital marketing capability, and uncovering the mechanisms through which it influences firm performance. In addition, this study contributes to the digitalization literature in the manufacturing sector by demonstrating the strategic role of digital marketing in driving value creation. Implications for digital marketing in manufacturing industry are discussed. Full article

(This article belongs to the Special Issue ICEC 2025: Transforming E-Commerce with AI: Navigating Innovation, Personalization, and Ethical Challenges)

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20 pages, 988 KB

Open AccessArticle

The Impacts of Rural E-Commerce on County Economic Development: Evidence from National Rural E-Commerce Comprehensive Demonstration Policy in China

by Yan Yu, Hongbo Tu and Qingsong Tian

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 235; https://doi.org/10.3390/jtaer20030235 - 2 Sep 2025

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Abstract

County economies are essential drivers of national economic development, acting as critical engines for growth and regional equilibrium. This study uses the National Rural E-commerce Comprehensive Demonstration policy, initiated by the Ministry of Finance and the Ministry of Commerce, China to empirically investigate [...] Read more.

County economies are essential drivers of national economic development, acting as critical engines for growth and regional equilibrium. This study uses the National Rural E-commerce Comprehensive Demonstration policy, initiated by the Ministry of Finance and the Ministry of Commerce, China to empirically investigate the impact of rural e-commerce on county economic development and inequality, based on economic and night light data from 2000 to 2021. By applying a staggered difference-in-differences (DID) model, we find that rural e-commerce significantly boosts county economic development. This result remains robust after a series of robustness tests. The impact is stronger on the primary sector compared to the secondary and tertiary sectors, and the effect is more pronounced in the central and western regions than in the eastern regions. Furthermore, rural e-commerce effectively reduces economic inequality, contributing to inclusive development. Mechanistically, e-commerce into rural demonstration policy fosters county economic development by enhancing human capital mobility, accelerating logistics development, and promoting the growth of local enterprises. Full article

(This article belongs to the Section e-Commerce Analytics)

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27 pages, 761 KB

Open AccessArticle

A Novel Framework Leveraging Social Media Insights to Address the Cold-Start Problem in Recommendation Systems

by Enes Celik and Sevinc Ilhan Omurca

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 234; https://doi.org/10.3390/jtaer20030234 - 2 Sep 2025

Viewed by 447

Abstract

In today’s world, with rapidly developing technology, it has become possible to perform many transactions over the internet. Consequently, providing better service to online customers in every field has become a crucial task. These advancements have driven companies and sellers to recommend tailored [...] Read more.

In today’s world, with rapidly developing technology, it has become possible to perform many transactions over the internet. Consequently, providing better service to online customers in every field has become a crucial task. These advancements have driven companies and sellers to recommend tailored products to their customers. Recommendation systems have emerged as a field of study to ensure that relevant and suitable products can be presented to users. One of the major challenges in recommendation systems is the cold-start problem, which arises when there is insufficient information about a newly introduced user or product. To address this issue, we propose a novel framework that leverages implicit behavioral insights from users’ X social media activity to construct personalized profiles without requiring explicit user input. In the proposed model, users’ behavioral profiles are first derived from their social media data. Then, recommendation lists are generated to address the cold-start problem by employing Boosting algorithms. The framework employs six boosting algorithms to classify user preferences for the top 20 most-rated films on Letterboxd. In this way, a solution is offered without requiring any additional external data beyond social media information. Experiments on a dataset demonstrate that CatBoost outperforms other methods, achieving an F1-score of 0.87 and MAE of 0.21. Based on experimental results, the proposed system outperforms existing methods developed to solve the cold-start problem. Full article

(This article belongs to the Collection Utilizing Models for e-Business Decision-Making: From Data to Wisdom)

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24 pages, 710 KB

Open AccessArticle

Hesitant Fuzzy-BWM Risk Evaluation Framework for E-Business Supply Chain Cooperation for China–West Africa Digital Trade

by Shurong Zhao, Mohammed Gadafi Tamimu, Ailing Luo, Tiantian Sun and Yongxing Yang

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 233; https://doi.org/10.3390/jtaer20030233 - 2 Sep 2025

Viewed by 318

Abstract

This paper examines the risks linked to E-business collaboration between China and West Africa, with particular emphasis on Ghana as a pivotal digital commerce centre. This research employs the Hesitant Fuzzy Best–Worst Method (HF-BWM) to systematically identify and prioritise the institutional, technological, sociocultural, [...] Read more.

This paper examines the risks linked to E-business collaboration between China and West Africa, with particular emphasis on Ghana as a pivotal digital commerce centre. This research employs the Hesitant Fuzzy Best–Worst Method (HF-BWM) to systematically identify and prioritise the institutional, technological, sociocultural, and legal issues affecting cross-border e-business operations. This study combines Transaction Cost Theory (TCT), the Technology Acceptance Model (TAM), and Commitment–Trust Theory to create a comprehensive framework for analysing the interplay of these risks and their effects on transaction costs and company sustainability. The findings indicate that institutional risks constitute the most substantial obstacles, with deficient digital transaction legislation and inadequate data governance recognised as the principal drivers of uncertainty and increased transaction costs. The research indicates that these institutional challenges necessitate immediate focus, as they immediately affect corporate operations, especially in international digital commerce. Technological risks, such as cybersecurity vulnerabilities, insufficient IT skills, and deficiencies in digital infrastructure, were identified as the second most critical factors, leading to considerable operational disruptions and heightened expenses. Sociocultural hazards, such as language difficulties and varying consumer behaviours, were recognised as moderate concerns that, although significant, exert a weaker cumulative impact than technological and institutional challenges. Eventually, legal risks, especially concerning cybercrime legislation and the protection of intellectual property, were identified as substantial complicators of e-business activities, increasing the intricacy of legal compliance and cross-border contract enforcement. The results underscore the imperative for regulatory reforms, investments in cybersecurity, and methods for cultural adaptation to alleviate the identified risks and promote sustainable growth in China–West Africa e-business relationships. This study offers practical insights for governments, business leaders, and investors to effectively manage the intricate risk landscape and make educated decisions that foster enduring collaboration and trust between China and West Africa in digital trade. Full article

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23 pages, 692 KB

Open AccessArticle

Optimizing Distinctiveness in Global E-Commerce: How Textual Marketing Signals Drive Foreign Customer Engagement on Digital Platforms

by Jungwon Lee

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 232; https://doi.org/10.3390/jtaer20030232 - 2 Sep 2025

Viewed by 302

Abstract

This study investigates how new ventures on global e-commerce platforms use textual marketing signals to attract foreign consumers, a critical challenge characterized by information asymmetry. Integrating Signaling Theory and Optimal Distinctiveness Theory (ODT), we examine how two key creator-controlled textual signals—International Orientation Expression [...] Read more.

This study investigates how new ventures on global e-commerce platforms use textual marketing signals to attract foreign consumers, a critical challenge characterized by information asymmetry. Integrating Signaling Theory and Optimal Distinctiveness Theory (ODT), we examine how two key creator-controlled textual signals—International Orientation Expression (IOE) intensity (a signal of legitimacy) and Project Genre Atypicality (GA) (a signal of differentiation)—non-linearly and interactively influence foreign customer engagement. Analyzing a large-scale dataset of 17,084 Kickstarter projects using computer-aided text analysis and fixed-effects regression models, we yield several key insights. First, we find a robust inverted U-shaped relationship between IOE intensity and foreign backer engagement, suggesting that while moderate international emphasis enhances legitimacy, excessive claims can undermine credibility. Second, GA exhibits a positive linear relationship with foreign engagement, indicating that novelty-seeking foreign consumers consistently value textual differentiation. Third, and most critically, we uncover a significant negative interaction, termed the “cost of dual extremes”, where simultaneously signaling extreme international ambition and extreme product novelty deters foreign consumers, likely due to perceived strategic incoherence and heightened execution risk. Finally, we confirm that attracting a diverse foreign audience is a strong predictor of overall project funding success. This research extends ODT by identifying a novel interactive boundary condition for distinctiveness in digital markets and advances signaling theory by demonstrating the complex, non-linear effectiveness of textual signals, offering actionable insights for optimizing communication strategy in global e-commerce. Full article

(This article belongs to the Section Entrepreneurship, Innovation, FinTech Accounting and Industry 4.0)

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16 pages, 1010 KB

Open AccessArticle

Facilitating Patient Adoption of Online Medical Advice Through Team-Based Online Consultation

by Xiaofei Zhang, Lulu Zhou, Siqi Wang, Cunda Fan and Dongdong Huang

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 231; https://doi.org/10.3390/jtaer20030231 - 2 Sep 2025

Viewed by 296

Abstract

The emergence of online medical teams (OMTs) as a multidisciplinary approach to addressing complex health issues has gained increasing academic recognition. However, the factors influencing patient adoption of medical advice in this new communication context remain underexplored. This study investigates how multi-doctor involvement [...] Read more.

The emergence of online medical teams (OMTs) as a multidisciplinary approach to addressing complex health issues has gained increasing academic recognition. However, the factors influencing patient adoption of medical advice in this new communication context remain underexplored. This study investigates how multi-doctor involvement in OMTs affects patient adoption of medical advice and examines the moderating roles of leader participation, disciplinary diversity, and illness complexity. The results indicate that multi-doctor involvement positively influences patient adoption of medical advice. This relationship is strengthened by leader participation and disciplinary diversity, while illness complexity exerts no significant moderating effect. As the first study to explore patient adoption of medical advice in the OMT context, these findings advance theoretical understanding and offer practical implications for improving online healthcare services. Full article

(This article belongs to the Special Issue ICEC 2025: Transforming E-Commerce with AI: Navigating Innovation, Personalization, and Ethical Challenges)

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28 pages, 2653 KB

Open AccessArticle

Evaluating Digital Empowerment Models for Multi-Homing Content Creators on UGC Platforms

by Yongtao Liang and Zhiqiang Ma

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 230; https://doi.org/10.3390/jtaer20030230 - 1 Sep 2025

Viewed by 368

Abstract

With the rapid expansion of user-generated content (UGC) platforms, digital empowerment has emerged as a crucial strategy for enhancing platform competitiveness. This study investigates how different digital empowerment models—no digital empowerment, free digital empowerment, and paid digital empowerment—affect platform outcomes. Employing a Salop [...] Read more.

With the rapid expansion of user-generated content (UGC) platforms, digital empowerment has emerged as a crucial strategy for enhancing platform competitiveness. This study investigates how different digital empowerment models—no digital empowerment, free digital empowerment, and paid digital empowerment—affect platform outcomes. Employing a Salop model with multi-homing content creators, we analyze the impact of empowerment strategies on content quality, consumer engagement, and platform profitability. The findings reveal that digital empowerment functions not only as a technical tool but also as an incentive mechanism and structural supply adjustment strategy. It creates a behavioral feedback loop whereby empowered creators improve content quality, which increases consumer retention and word-of-mouth dissemination, thereby boosting traffic, advertising revenue, and overall platform profit. Among the three models, paid digital empowerment generally yields the highest content quality and platform profitability. The effectiveness of each strategy is moderated by creators’ data utilization capability, market competition intensity, advertising monetization potential, and word-of-mouth effects. These results provide theoretical and managerial insights into the design of differentiated empowerment strategies that align with platform goals and creator characteristics in competitive UGC environments. Full article

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24 pages, 1246 KB

Open AccessArticle

A Dynamic Analysis of Cross-Category Innovation in Digital Platform Ecosystems with Network Effects

by Shuo Sun, Bing Gu and Fangcheng Tang

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 229; https://doi.org/10.3390/jtaer20030229 - 1 Sep 2025

Viewed by 303

Abstract

Cross-category innovation in digital platform ecosystems is increasingly pivotal for competitive reconfiguration, and the value it generates for users primarily stems from the benefits of network effects. By extending the spatial competition framework of the Hotelling model through a four-stage sequential game comprising [...] Read more.

Cross-category innovation in digital platform ecosystems is increasingly pivotal for competitive reconfiguration, and the value it generates for users primarily stems from the benefits of network effects. By extending the spatial competition framework of the Hotelling model through a four-stage sequential game comprising category competition, we formalize the strategic mechanism for expanding network effects governing benchmark competition and category dynamics. The cross-category innovation strategy proposed in this paper offers valuable insights in three key areas: investment in core technological advantages, reconstruction of user cognitive boundaries, and strengthening ecological dependency within the ecosystem. By transcending the limitations in the explanatory power of traditional management theories for cross-organizational boundary issues, this study integrates digital contexts into its analytical framework, thus providing a novel perspective for understanding the dynamic processes of cross-category innovation in digital platform ecosystems. Full article

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22 pages, 693 KB

Open AccessArticle

How Perceived Motivations Influence User Stickiness and Sustainable Engagement with AI-Powered Chatbots—Unveiling the Pivotal Function of User Attitude

by Hua Pang, Zhuyun Hu and Lei Wang

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 228; https://doi.org/10.3390/jtaer20030228 - 1 Sep 2025

Viewed by 342

Abstract

Artificial intelligence (AI) is reshaping customer service, with AI-powered chatbots serving as a critical component in delivering continuous support across sales, marketing, and service domains, thereby enhancing operational efficiency. However, consumer engagement remains suboptimal, as many users favor human interaction due to concerns [...] Read more.

Artificial intelligence (AI) is reshaping customer service, with AI-powered chatbots serving as a critical component in delivering continuous support across sales, marketing, and service domains, thereby enhancing operational efficiency. However, consumer engagement remains suboptimal, as many users favor human interaction due to concerns regarding chatbots’ ability to address complex issues and their perceived lack of empathy, which subsequently reduces satisfaction and sustainable usage. This study examines the determinants of user attitude and identifies factors influencing sustainable chatbot use. Utilizing survey data from 735 Chinese university students who have engaged with AI-powered chatbots, the analysis reveals that four key motivational categories: utilitarian (information acquisition), hedonic (enjoyment and time passing), technology (media appeal), and social (social presence and interaction) significantly influence user attitude toward chatbot services. Conversely, privacy invasion exerts a negative impact on user attitude, suggesting that while chatbots provide certain benefits, privacy issues can significantly undermine user satisfaction. Moreover, the findings suggest that user attitude serves as a pivotal determinant in fostering both user stickiness and sustainable usage of chatbot services. This study advances prior U&G-, TAM-, and ECM-based research by applying these frameworks to AI-powered chatbots in business communication, refining the U&G model with four specific motivations, integrating perceived privacy invasion to bridge gratification theory with risk perception, and directly linking user motivations to business outcomes such as attitude and stickiness. This study underscores that optimizing chatbot functionalities to enhance user gratification while mitigating privacy risks can substantially improve user satisfaction and stickiness, offering valuable implications for businesses aiming to enhance customer loyalty through AI-powered services. Full article

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32 pages, 2062 KB

Open AccessArticle

Faster Delivery? You May Be Paying a Higher Price than Others!

by Tao Jiang, Kaigeng Shen, Wenxiao Fu, Wenshuo Liu and Shuwei Wang

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 227; https://doi.org/10.3390/jtaer20030227 - 1 Sep 2025

Viewed by 406

Abstract

The development of information technology allows firms to access consumer purchase records, enabling them to distinguish between new and old consumers. Firms can then provide these groups with respective product pricing and promised delivery time. This paper develops a two-period dynamic model based [...] Read more.

The development of information technology allows firms to access consumer purchase records, enabling them to distinguish between new and old consumers. Firms can then provide these groups with respective product pricing and promised delivery time. This paper develops a two-period dynamic model based on game theory to examine the effects of behavior-based pricing and behavior-based promised delivery time strategies on product price, promised delivery time, firm profits, consumer surplus, and social welfare under conditions where consumers exhibit time-sensitive preferences. We find, first, when firms opt to implement behavior-based pricing and promised delivery time strategies, they should offer lower (higher) prices and longer (shorter) delivery times to new (old) consumers. Second, the implementation of behavior-based pricing and promised delivery time strategies may decrease firm profits while enhancing consumer surplus. Third, when consumers exhibit stronger time-sensitive preferences, behavior-based pricing and promised delivery time strategies can enhance social welfare; conversely, they may have a detrimental impact on social welfare. Finally, we extend the model into three aspects—asymmetric strategy selection, firm logistics service costs, and myopic consumer behavior—to enrich our research and test the robustness of the model. The results of this paper supply managerial implications and theoretical references for firms’ strategic implementation and policy-making by relevant government departments. Full article

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29 pages, 5415 KB

Open AccessArticle

How Doctors’ Proactive Crafting Behaviors Influence Performance Outcomes: Evidence from an Online Healthcare Platform

by Wenlong Liu, Yashuo Yuan, Zifan Bai and Shenghui Sang

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 226; https://doi.org/10.3390/jtaer20030226 - 1 Sep 2025

Viewed by 271

Abstract

With the steady global progress in integrating technology into healthcare delivery, doctors’ behavioral patterns on online healthcare platforms have increasingly become a focal point in the fields of digital health and healthcare service management. Grounded in Job Crafting Theory, this study constructs a [...] Read more.

With the steady global progress in integrating technology into healthcare delivery, doctors’ behavioral patterns on online healthcare platforms have increasingly become a focal point in the fields of digital health and healthcare service management. Grounded in Job Crafting Theory, this study constructs a proactive crafting index, which captures doctors’ proactive behaviors on the platform across three dimensions: consultation rate, number of consultations, and response speed. We systematically examine the multidimensional impacts of such behaviors on performance outcomes, including online consultation volume, offline service volume, and user evaluation performance. This study collects publicly available records from a major online healthcare platform in China and conducts empirical analysis using the entropy weight method and econometric techniques. The results reveal that there is an optimal level of proactive engagement: moderate proactivity maximizes online consultation volume, while both insufficient and excessive proactivity reduce it. Offline service volume, in contrast, follows a U-shaped relationship, where moderate proactive engagement minimizes offline visits, while too little or too much engagement leads to more offline service needs. These nonlinear patterns highlight the importance of framing doctors’ proactive behavior to optimize both online engagement and offline service. The findings enrich Job Crafting Theory by identifying boundaries in platform-based service environments and provide actionable insights for platform operators to design behavior management and incentive systems tailored to doctors’ professional rank, patient condition, and regional context. Full article

(This article belongs to the Topic Data Science and Intelligent Management)

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25 pages, 554 KB

Open AccessArticle

The Role of AI Technologies in E-Commerce Development: A European Comparative Study

by Claudiu George Bocean, Luminița Popescu, Dalia Simion, Natalița Maria Sperdea, Carmen Puiu, Roxana Cristina Marinescu and Enescu Maria

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 225; https://doi.org/10.3390/jtaer20030225 - 1 Sep 2025

Viewed by 689

Abstract

As global economies accelerate their digital transformation, artificial intelligence (AI) technologies have become a key driver of innovation and economic growth, especially in the electronic commerce sector. This study examines the impact of AI applications in marketing and sales on e-commerce performance across [...] Read more.

As global economies accelerate their digital transformation, artificial intelligence (AI) technologies have become a key driver of innovation and economic growth, especially in the electronic commerce sector. This study examines the impact of AI applications in marketing and sales on e-commerce performance across European economies, using official data from Eurostat. Our methodology includes factor analysis to identify underlying data structures, linear regression to explore causal relationships, generalized linear model (GLM) multivariate analysis to assess the combined effect of multiple factors, and cluster analysis to categorize countries based on their level of digitalization. Our results demonstrate a strong correlation between AI use and e-commerce performance, revealing two distinct clusters with unique characteristics. The findings reveal a positive association between the use of AI and firms’ engagement in e-commerce activities, although the influence on turnover appears more limited. This suggests that while AI facilitates entry into the digital marketplace, financial performance depends on a broader set of factors, including technological infrastructure, market readiness, and strategic alignment. These insights provide a solid basis for developing policies and strategies that support digital transformation and technological innovation in Europe, helping to build competitive and sustainable economies. Full article

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37 pages, 3178 KB

Open AccessArticle

Dynamic Pricing for Internet Service Platforms with Initial Demand Constraints: Unified or Differentiated Pricing?

by Junchang Li, Jiaqing Sun and Jiantong Zhang

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 224; https://doi.org/10.3390/jtaer20030224 - 1 Sep 2025

Viewed by 354

Abstract

Internet service platforms dynamically charge service prices to satisfy the time-varying service demand by leveraging both full- and part-time service providers. This study developed a dynamic pricing model for a monopolistic service platform under two pricing strategies: unified pricing and differentiated pricing. The [...] Read more.

Internet service platforms dynamically charge service prices to satisfy the time-varying service demand by leveraging both full- and part-time service providers. This study developed a dynamic pricing model for a monopolistic service platform under two pricing strategies: unified pricing and differentiated pricing. The model incorporates key factors such as demand fluctuations, initial demand constraints, and service quality. It proved the optimal dynamic pricing scheme aimed at maximizing the platform’s expected revenue and analyzed the equilibrium gap between the two strategies based on the optimal control theory. The results reveal the following: (a) The service quality elasticity coefficient, potential market, and demand fluctuation factor all positively affect the optimal service price under the two types of pricing strategies, whereas service quality has the opposite effect. (b) Regardless of pricing strategy, the initial service demand restriction negatively affects the optimal price of the platform. The gap between the optimal service prices under the two types of pricing strategies narrows as the potential service demand rises when customers are less sensitive to service price. (c) With initial demand restriction, the optimal service price rises over time as long as the service market satisfies specific conditions, but the expected revenue under the two types of pricing strategies evolves in significantly different trajectories. (d) The differentiated pricing strategy can help the platform improve revenue by setting a lower revenue-sharing ratio. Full article

(This article belongs to the Topic Data Science and Intelligent Management)

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26 pages, 840 KB

Open AccessArticle

Building Relationship Equity: Role of Social Media Marketing Activities, Customer Engagement, and Relational Benefits

by Faheem ur Rehman, Hasan Zahid, Abdul Qayyum and Raja Ahmed Jamil

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 223; https://doi.org/10.3390/jtaer20030223 - 1 Sep 2025

Viewed by 559

Abstract

In today’s service-driven economy, brands increasingly turn to social media marketing activities (SMMA) to build meaningful, long-term customer relationships. Grounded in social exchange theory (SET), this study examines how SMMA influences customer engagement (CE), relational benefits (confidence, social, and special treatment), and ultimately [...] Read more.

In today’s service-driven economy, brands increasingly turn to social media marketing activities (SMMA) to build meaningful, long-term customer relationships. Grounded in social exchange theory (SET), this study examines how SMMA influences customer engagement (CE), relational benefits (confidence, social, and special treatment), and ultimately relationship equity—offering new insights for trust-based services, such as banking. SET provides a powerful lens to explain how perceived value in brand-initiated exchanges drives customer reciprocity. A between-subjects experimental design (n = 298) was employed using real social media ads from a bank to enhance ecological validity. Participants were randomly assigned to ad exposure or control conditions, and data were analyzed using PLS-SEM. Results show that SMMA significantly enhances CE and relational benefits. In turn, CE, along with confidence and social benefits, contributes to relationship equity. Special treatment benefits, however, had no significant effect. Ad exposure amplified the impact of SMMA on CE and relationship outcomes. Theoretically, this study advances SET by revealing how digital brand interactions translate into lasting customer bonds. Practically, the findings indicate that banks should prioritize SMMA for increased CE and relational benefits. When combined with targeted advertising efforts, this can significantly improve relationship equity. Full article

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21 pages, 1758 KB

Open AccessArticle

Leadership-Driven Pricing and Customization in Collaborative Manufacturing: A Platform Dynamics Perspective

by Runfang Bi, Feng Wu and Shiqi Yuan

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 222; https://doi.org/10.3390/jtaer20030222 - 1 Sep 2025

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Abstract

Fueled by advances in cloud technologies and industrial platforms, networked collaborative manufacturing platforms (NCMPs) are reshaping how products are priced and customized. As decision rights increasingly shape value creation within these platforms, platform leadership—whether driven by the manufacturer or the designer—emerges as a [...] Read more.

Fueled by advances in cloud technologies and industrial platforms, networked collaborative manufacturing platforms (NCMPs) are reshaping how products are priced and customized. As decision rights increasingly shape value creation within these platforms, platform leadership—whether driven by the manufacturer or the designer—emerges as a critical determinant of product strategy. However, the effects of different leadership structures on pricing and customization remain unclear. To address this issue, we develop game models comparing manufacturer-led and designer-led platforms. Our analysis reveals that under manufacturer-led platforms, dual-product strategies remain viable across a wider range of customization conditions, ensuring pricing stability and broader demand coverage. In contrast, designer-led platforms are more sensitive to the commission rate—excessive commissions tend to crowd out standard product offerings and distort pricing incentives. Moreover, platform control does not always guarantee superior profit: while designers consistently outperform manufacturers under manufacturer-led platforms, profit dominance in designer-led settings shifts with commission rates. Notably, by jointly optimizing product strategy and pricing mechanisms, firms can achieve more balanced value distribution and sustain collaboration. These findings offer a strategic framework for manufacturers and designers to align platform governance with product architecture, contributing new insights into collaborative pricing, platform leadership, and dual-product innovation in industrial platform ecosystems. Full article

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24 pages, 2394 KB

Open AccessArticle

Extracting Emotions from Customer Reviews Using Text Mining, Large Language Models and Fine-Tuning Strategies

by Simona-Vasilica Oprea and Adela Bâra

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 221; https://doi.org/10.3390/jtaer20030221 - 1 Sep 2025

Viewed by 483

Abstract

User-generated content, such as product and app reviews, offers more than just sentiment. It provides a rich spectrum of emotional expression that reveals users’ experiences, frustrations and expectations. Traditional sentiment analysis, which typically classifies text as positive or negative, lacks the nuance needed [...] Read more.

User-generated content, such as product and app reviews, offers more than just sentiment. It provides a rich spectrum of emotional expression that reveals users’ experiences, frustrations and expectations. Traditional sentiment analysis, which typically classifies text as positive or negative, lacks the nuance needed to fully understand the emotional drivers behind customer feedback. In this research, we focus on fine-grained emotion classification using core emotions. By identifying specific emotions rather than sentiment polarity, we enable more actionable insights for e-commerce and app development, supporting strategies such as feature refinement, marketing personalization and proactive customer engagement. We leverage the Hugging Face Emotions dataset and adopt a two-phase modeling approach. In the first phase, we use a pre-trained DistilBERT model as a feature extractor and evaluate multiple classical classifiers (Logistic Regression, Support Vector Classifier, Random Forest) to establish performance baselines. In the second phase, we fine-tune the DistilBERT model end-to-end using the Hugging Face Trainer API, optimizing classification performance through task-specific adaptation. Training is tracked using the Weights & Biases (wandb) API. Comparative analysis highlights the substantial performance gains from fine-tuning, particularly in capturing informal or noisy language typical in user reviews. The final fine-tuned model is applied to a dataset of customers’ reviews, identifying the dominant emotions expressed. Our results demonstrate the practical value of emotion-aware analytics in uncovering the underlying “why” behind user sentiment, enabling more empathetic decision-making across product design, customer support and user experience (UX) strategy. Full article

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20 pages, 1149 KB

Open AccessArticle

When Positive Service Logistics Encounter Enhanced Purchase Intention: The Reverse Moderating Effect of Image–Text Similarity

by Shizhen Bai, Luwen Cao and Jiamin Zhou

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 220; https://doi.org/10.3390/jtaer20030220 - 1 Sep 2025

Viewed by 418

Abstract

E-commerce platforms offering regional fresh produce often face a trade-off between logistics costs and product quality. Due to limited use of cold chain logistics, consumers frequently receive damaged goods, resulting in negative post-purchase experiences. This study examines how logistics service encounters, as reflected [...] Read more.

E-commerce platforms offering regional fresh produce often face a trade-off between logistics costs and product quality. Due to limited use of cold chain logistics, consumers frequently receive damaged goods, resulting in negative post-purchase experiences. This study examines how logistics service encounters, as reflected in consumer reviews, influence subsequent purchase behaviour, and how the alignment between review images and text moderates this relationship. We analyse sales and review data from 694 fruit products on Tmall between February and April 2024. Latent Dirichlet Allocation (LDA) is applied to extract logistics-related review content. At the same time, image–text similarity is assessed using the Chinese-CLIP model. Regression analysis reveals that positive logistics service encounters significantly enhance purchase intention. However, high image–text similarity weakens this positive effect, suggesting that overly repetitive content may reduce informational value for prospective buyers. These findings advance understanding of consumer behaviour in online fresh produce markets by highlighting the interactive effects of logistics experiences and user-generated content. The results offer practical implications for improving logistics services, enhancing content diversity in review systems, and increasing consumer trust in e-commerce environments. Full article

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

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40 pages, 4926 KB

Open AccessArticle

Using Artificial Intelligence to Determine the Impact of E-Commerce on the Digital Economy

by Florin Cornel Dumiter and Klaus Bruno Schebesch

J. Theor. Appl. Electron. Commer. Res. 2025, 20(3), 219; https://doi.org/10.3390/jtaer20030219 - 27 Aug 2025

Viewed by 1415

Abstract

E-commerce indicators are very complex and have a wide range of levels of complexity and applications. The digital economies that we are oriented towards also have complex features in terms of consumers and businesses. The research objectives are focused on determining the impact [...] Read more.

E-commerce indicators are very complex and have a wide range of levels of complexity and applications. The digital economies that we are oriented towards also have complex features in terms of consumers and businesses. The research objectives are focused on determining the impact of e-commerce on the digital economy within countries with different stages of economic development, digitalization techniques, and e-commerce usage. This study evaluates how AI-based clustering reveals patterns in the e-commerce indicators influencing the digital economy. The research methods used are focused on AI techniques in order to evaluate and assess the usage of e-commerce in the digital economy. In this sense, the methods used in this research are clustering techniques in order to determine the stage of implementation of the digital economy. The research implications have a worldwide impact and soundness in establishing the evolution of the e-economy in different types of countries with different stages and levels of digitalization and different e-commerce development paths. The empirical results show there are significant differences between countries due to cultural, economic, social, and judicial differences. The conclusions of this study highlight that using AI techniques can be a solution for enhancing future digital economy development and labor market consolidation, especially by strengthening e-commerce indicator usage and application. Full article

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J. Theor. Appl. Electron. Commer. Res., Volume 20, Issue 3 (September 2025) – 98 articles

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