Journal of Theoretical and Applied Electronic Commerce Research

31 pages, 24237 KiB

Open AccessArticle

Forecasting Sales in Live-Streaming Cross-Border E-Commerce in the UK Using the Temporal Fusion Transformer Model

by Qi Zhang, Xue Li and Pengbin Gao

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 92; https://doi.org/10.3390/jtaer20020092 (registering DOI) - 2 May 2025

Abstract

As globalization deepens and the digital economy rapidly develops, cross-border e-commerce, especially live-streaming e-commerce, has emerged as a significant driver of international trade growth. However, the highly unpredictable sales demand in this sector and external factors such as the COVID-19 pandemic and Brexit [...] Read more.

As globalization deepens and the digital economy rapidly develops, cross-border e-commerce, especially live-streaming e-commerce, has emerged as a significant driver of international trade growth. However, the highly unpredictable sales demand in this sector and external factors such as the COVID-19 pandemic and Brexit have posed significant challenges in accurately forecasting sales within the UK live-streaming e-commerce market. To address these challenges, we propose a novel sales forecasting framework utilizing the Temporal Fusion Transformer (TFT) model. Our multimodal approach integrates diverse time series data, including historical sales, key opinion leader (KOL) influence, and seasonal patterns. The Temporal Fusion Transformer (TFT) model demonstrated consistently lower Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Squared Error (MSE) across all forecasting horizons compared to other machine learning approaches, including Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and Gated Recurrent Unit(GPU)-accelerated architectures. Furthermore, it exhibited significantly superior performance over traditional time-series methods such as the Autoregressive Integrated Moving Average (ARIMA) model. This research proposes a phased framework for short-term, medium-term, and long-term forecasting, providing a fresh perspective for product forecasting studies and offering significant theoretical support for cross-border e-commerce enterprises in product life cycle management. Full article

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28 pages, 1456 KiB

Open AccessArticle

Investigation of Users’ Information Adoption Intention in Short Video Applications: A Perspective on Flow Experience

by Shengtai Zhang, Yang Yang and Yiwei Yuan

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 91; https://doi.org/10.3390/jtaer20020091 (registering DOI) - 2 May 2025

Abstract

Short video applications have gained increasing prominence as pivotal channels for information acquisition and knowledge dissemination, capturing the attention of scholars. Despite the increasing interest in this area, a general investigation of the factors that facilitate users’ information adoption on TikTok remains insufficient. [...] Read more.

Short video applications have gained increasing prominence as pivotal channels for information acquisition and knowledge dissemination, capturing the attention of scholars. Despite the increasing interest in this area, a general investigation of the factors that facilitate users’ information adoption on TikTok remains insufficient. We combine the flow experience and information adoption theory to construct a novel theoretical model for investigating the antecedents of information adoption intentions within the realm of short video applications. A total of 386 data were collected from TikTok’s users and analyzed using the partial least squares (PLS) approach. The analysis of the data revealed that technology affordance (i.e., accuracy, serendipity, and perceived ease of use) and information quality influence users’ information adoption intentions via flow experience. Users’ interest-type epistemic curiosity can moderate the effect of serendipity on information adoption intentions. This study investigates the interactive effects of individuals, technology, and information on flow and information adoption intentions, offering implications for platform administrators, content creators, and government agencies to understand users’ information adoption. Full article

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22 pages, 852 KiB

Open AccessArticle

Virtual Influencers as Brand Endorsers: Developing and Validating a Multidimensional Evaluation Scale

by Yoon Y. Cho

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 90; https://doi.org/10.3390/jtaer20020090 (registering DOI) - 1 May 2025

Viewed by 77

Abstract

Virtual influencers are emerging as a powerful tool in strategic communication, yet their effectiveness as brand endorsers remains underexplored. This study aims to develop a consumer-centric scale to assess virtual influencers’ effectiveness in social media marketing campaigns. The research methodology follows a systematic [...] Read more.

Virtual influencers are emerging as a powerful tool in strategic communication, yet their effectiveness as brand endorsers remains underexplored. This study aims to develop a consumer-centric scale to assess virtual influencers’ effectiveness in social media marketing campaigns. The research methodology follows a systematic scale-development process. First, an integrated literature review was conducted to establish a conceptual model for evaluating virtual influencers. Second, an initial pool of evaluation items was developed and validated by experts. Third, an exploratory factor analysis (EFA) with 208 participants was conducted to assess the reliability and validity of the preliminary items. Finally, a confirmatory factor analysis (CFA) with 209 participants was performed to finalize the scale. The resulting measurement scale comprises four key dimensions: communication skills, narrative strategies, visual appearance, and human-like movement. By introducing a structured scale-development method grounded in anthropomorphism, this study enhances the assessment of virtual influencers’ effectiveness in digital marketing campaigns. Full article

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

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31 pages, 4132 KiB

Open AccessArticle

Research on the Optimal Live-Streaming Strategy Under the Influence of Consumer Preferences: Taking Agriculture and Cultural Tourism Enterprise as an Example

by Fanyong Meng and Yu Wu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 89; https://doi.org/10.3390/jtaer20020089 (registering DOI) - 1 May 2025

Viewed by 71

Abstract

A series of policy measures have been implemented to support the integration of agriculture and cultural tourism (ACT), positioning it as a pivotal component of the modern rural industrial system. Additionally, the rapid growth of e-commerce live streaming has surpassed the limitations of [...] Read more.

A series of policy measures have been implemented to support the integration of agriculture and cultural tourism (ACT), positioning it as a pivotal component of the modern rural industrial system. Additionally, the rapid growth of e-commerce live streaming has surpassed the limitations of traditional promotional methods in terms of geographic and media reach. The enterprise can attract more consumer groups through live streaming. This article analyzes the signal game between the ACT enterprise and consumers and discusses how consumer types affect enterprise decision-making in both static and dynamic contexts. We have come to the following conclusion: (1) The severity of punishment for companies that transmit incorrect signals is the main influencing factor for the balance to be established. (2) The more types of consumers an enterprise attracts, the lower its price. (3) The comparison of profits in static and dynamic contexts depends on changes in consumer types and the impact of the first-stage strategy on the second stage. Full article

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20 pages, 593 KiB

Open AccessArticle

Antecedents of Electronic Word of Mouth (eWOM) Adoption in the Purchase of Cosmetics in Ecuador: Does Gender Moderate Relationships?

by Madelyn Mendoza-Moreira, Beatriz Moliner-Velázquez, Gloria Berenguer-Contri and Irene Gil-Saura

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 88; https://doi.org/10.3390/jtaer20020088 (registering DOI) - 1 May 2025

Viewed by 69

Abstract

Social networks have emerged as a powerful tool for communication and marketing, enabling two-way user participation and fostering a conducive environment for electronic word of mouth (eWOM). This study examines how social influence, eWOM engagement, and perceived eWOM credibility affect its adoption, while [...] Read more.

Social networks have emerged as a powerful tool for communication and marketing, enabling two-way user participation and fostering a conducive environment for electronic word of mouth (eWOM). This study examines how social influence, eWOM engagement, and perceived eWOM credibility affect its adoption, while also exploring the moderating role of gender in these relationships. Using a sample of 371 cosmetics consumers in Ecuador, a causal model was estimated using the PLS method. The findings confirm that social influence significantly impacts eWOM engagement and credibility, contributing to its adoption. Additionally, gender moderates the relationship between informational influence and eWOM credibility. This study also highlights the need to replicate the model in different contexts and with more diverse samples to enhance the generalizability of the findings. By enriching Erkan and Evans’ IACM theoretical framework, this research extends the understanding of eWOM dynamics in the cosmetics sector. Moreover, it offers a comprehensive perspective on the eWOM adoption process by incorporating underexplored variables and providing empirical evidence from an understudied region, such as Latin America. Full article

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

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23 pages, 1093 KiB

Open AccessArticle

Spillover Effects of Physicians’ Prosocial Behavior: The Role of Knowledge Sharing in Enhancing Paid Consultations Across Healthcare Networks

by Yuting Zhang and Jiantong Zhang

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 87; https://doi.org/10.3390/jtaer20020087 (registering DOI) - 1 May 2025

Viewed by 64

Abstract

This study investigates the spillover effects of physicians’ prosocial behavior, specifically knowledge sharing, on the paid consultations of other physicians within the same specialty and offline hospital. Using data from an online healthcare platform, we apply propensity score matching to explore how the [...] Read more.

This study investigates the spillover effects of physicians’ prosocial behavior, specifically knowledge sharing, on the paid consultations of other physicians within the same specialty and offline hospital. Using data from an online healthcare platform, we apply propensity score matching to explore how the sharing of medical knowledge by physicians influences the consultation outcomes of their colleagues. The results reveal significant positive spillover effects, indicating that prosocial behavior benefits other physicians within the same specialty and healthcare institution, thereby enhancing collaboration within the healthcare ecosystem. The spillover effect is stronger within the same offline hospital’s physicians on the online healthcare platform, suggesting that knowledge sharing has a more localized impact within the same healthcare institution. Furthermore, the study examines heterogeneity across both physician-level characteristics (e.g., popularity, title, price, gender) and contextual factors (e.g., specialty type, hospital level, wait time, regional GDP). The findings show that the magnitude and direction of spillover effects differ by subgroup, shaped by professional visibility, authority, and organizational structure. These insights contribute to the understanding of how prosocial behavior can foster collaboration and benefit healthcare networks beyond individual physicians, offering practical implications for healthcare platforms, administrators, and policymakers. Full article

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

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28 pages, 1408 KiB

Open AccessArticle

Influencing Factors of Consumers’ Impulse Purchase Intentions in Livestream E-Commerce Based on DEMATEL-AISM

by Sijie Ma, Wanjing Wei, Jiahui Wang, Haoyu Liu, Yujie Song and Lei Yang

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 86; https://doi.org/10.3390/jtaer20020086 (registering DOI) - 30 Apr 2025

Viewed by 110

Abstract

As the online shopping user base continues to grow rapidly, livestream e-commerce has emerged as a pivotal commercial phenomenon. However, consumers’ impulse purchase intentions in this environment are influenced by numerous interrelated factors, and the underlying mechanisms remain complex. To address the limitations [...] Read more.

As the online shopping user base continues to grow rapidly, livestream e-commerce has emerged as a pivotal commercial phenomenon. However, consumers’ impulse purchase intentions in this environment are influenced by numerous interrelated factors, and the underlying mechanisms remain complex. To address the limitations of traditional approaches in modeling nonlinear relationships and hierarchical structures, this study introduces an integrated DEMATEL-AISM approach tailored for the livestream e-commerce context. The

λ

-intercept method is applied to simplify the system structure and highlight key influencing factors. Based on prior literature, we designed and distributed structured questionnaires to 558 consumers and industry experts, followed by in-depth interviews with five domain experts. Through this process, an indicator system was developed encompassing 15 factors across three dimensions: product, consumer, and livestream room. Using DEMATEL-AISM, we conducted a causal analysis of these factors. The results reveal that: (1) discount intensity, livestream promotional frameworks, and time pressure are the three most critical factors influencing impulse purchase intentions; (2) product monetary value and design features act as fundamental drivers; and (3) consumer upward and downward anticipated regret, perceived product quality, perceived product scarcity, and perceived streamer’s product knowledge have direct impacts on impulse purchase. By identifying these key factors and revealing their interconnections, this study offers strategic, evidence-based recommendations for enhancing consumer engagement and profitability in livestream e-commerce. The proposed DEMATEL-AISM also provides a novel and effective methodological contribution for analyzing the complex influencing factors of impulse purchase intentions in the e-commerce environment. Full article

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25 pages, 1145 KiB

Open AccessArticle

How Social Scene Characteristics Affect Customers’ Purchase Intention: The Role of Trust and Privacy Concerns in Live Streaming Commerce

by Wenjian Li, Steiner Cujilema, Lisong Hu and Gang Xie

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 85; https://doi.org/10.3390/jtaer20020085 (registering DOI) - 30 Apr 2025

Viewed by 114

Abstract

(1) Live streaming commerce has refined online consumer engagement by fostering a real-time, socially enriched shopping environment. Despite its growing prominence, the role of social scene characteristics in consumer purchase decisions in live streaming remains insufficiently examined. (2) This study uses the Cognition-Affection-Conation [...] Read more.

(1) Live streaming commerce has refined online consumer engagement by fostering a real-time, socially enriched shopping environment. Despite its growing prominence, the role of social scene characteristics in consumer purchase decisions in live streaming remains insufficiently examined. (2) This study uses the Cognition-Affection-Conation (C-A-C) framework to examine how these social characteristics influence purchase intention through the mediating roles of emotional and cognitive trust, with privacy concerns as a moderator factor. The research employs Structural Equation Modeling (SEM) to test the hypothesis using data from 504 valid responses. (3) The results demonstrate that the characteristics of social scenes proposed in this study enhance consumer trust and positively impact purchase intention. Moreover, privacy concerns weaken the effect of interactivity atmosphere and scene immersion on emotion trust, though they do not weaken the effect of social identity on emotion trust. (4) These findings contribute to the theoretical understanding of live commerce by identifying the psychological mechanisms linking the social service scene to purchasing behavior. They also offer practical implications for platforms and merchants seeking to improve consumer engagement and trust in competitive digital marketplaces. This research highlights the importance of integrating social scenes and privacy management into the strategic design of live streaming commerce services. Full article

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28 pages, 649 KiB

Open AccessArticle

Play to Participate: Effects of Gamification Affordances on Consumer Participation in Livestreaming Commerce

by Congcong Yang, Yuanyue Feng, Xiaona Li and Ben Niu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 84; https://doi.org/10.3390/jtaer20020084 - 25 Apr 2025

Viewed by 474

Abstract

Despite the ubiquitous application of gamification in livestreaming commerce, the mechanisms driving its impact on consumer participation remain underexplored. To address this research gap, this study integrated two theoretical frameworks: the “Gamification Affordances–Psychological Outcomes–Behavioral Outcomes” framework and the Uses and Gratifications Theory. We [...] Read more.

Despite the ubiquitous application of gamification in livestreaming commerce, the mechanisms driving its impact on consumer participation remain underexplored. To address this research gap, this study integrated two theoretical frameworks: the “Gamification Affordances–Psychological Outcomes–Behavioral Outcomes” framework and the Uses and Gratifications Theory. We investigated how gamification affordances (achievement visualization, rewards, interaction, and competition) relate to the fulfillment of consumers’ diverse psychological needs (cognitive, affective, social, personal integrative, and social integrative). Furthermore, we examined whether meeting these psychological needs influences consumers’ intentions to continue watching and to purchase. We surveyed 354 livestreaming commerce consumers and employed structural equation modeling to analyze the data. The findings revealed that gamification affordances can motivate consumers’ continuous watching and purchasing behavior by satisfying their different psychological needs. We conclude by discussing the theoretical and managerial implications of our findings. Full article

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

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30 pages, 4312 KiB

Open AccessArticle

Research on Adoption Intention Toward Intelligent Messaging Service: From Self-Determination Theory Perspective

by Jianming Wu and Zhiyuan Yu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 83; https://doi.org/10.3390/jtaer20020083 - 25 Apr 2025

Viewed by 264

Abstract

Empowered by artificial intelligence and 5G technologies, intelligent messaging service instead of the existing short messaging service could provide an omni-channel service, thus achieving higher interconnection for mobile users. In this paper, we adopted mixed methods research and explored the psychological factors that [...] Read more.

Empowered by artificial intelligence and 5G technologies, intelligent messaging service instead of the existing short messaging service could provide an omni-channel service, thus achieving higher interconnection for mobile users. In this paper, we adopted mixed methods research and explored the psychological factors that affect adoption intention to adopt intelligent messaging services among mobile users based on self-determination theory. After semi-structured interviews, we constructed a partial least squares structural equation model from the perspectives of intrinsic and extrinsic motivations. In addition, openness and perceived complexity were also introduced as an extended dimension. Through an online survey, 548 valid questionnaires were obtained. The results show that intrinsic motivation has a greater effect on adoption intention. Specifically, attitude, perceived autonomy, perceived relatedness, and perceived system quality have significant positive impacts on the adoption intention of intelligent messaging, while perceived complexity has a negative direct impact on adoption intention. Although perceived competence and perceived media richness have no significant effects on adoption intention, an indirect effect on adoption intention through attitude was observed. Notably, perceived interactivity and openness have no effect on adoption intention. Through this study, we aim to provide guidance for developers to focus on mobile users’ psychological needs regarding upgraded interactive channels, which can accelerate the construction of an omni-channel media environment. Full article

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

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30 pages, 4619 KiB

Open AccessArticle

How AI Brand Endorsers Influence Generation MZ’s Consumer Behavior in Metaverse Marketing Scenarios

by Junping Xu, Yuxi Feng, Wei Li, Qianghong Huang and Zhizhong Fan

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 82; https://doi.org/10.3390/jtaer20020082 - 24 Apr 2025

Viewed by 372

Abstract

With the rapid development of metaverse technology in the marketing field, it has become increasingly important to understand consumer purchase intentions for AI Brand Endorsers (AIBEs) within this digital environment. Based on cognitive–affective–behavioral (CAB) theory, this study constructs a new theoretical framework to [...] Read more.

With the rapid development of metaverse technology in the marketing field, it has become increasingly important to understand consumer purchase intentions for AI Brand Endorsers (AIBEs) within this digital environment. Based on cognitive–affective–behavioral (CAB) theory, this study constructs a new theoretical framework to explore the key factors influencing consumer purchase intentions for AIBE-recommended products in the context of the metaverse. We conducted an online survey with 302 Generation MZ consumers who have purchasing experience, employing Partial Least Squares Structural Equation Modeling (PLS-SEM) for in-depth data analysis and model evaluation. Additionally, we performed Multi-Group Analysis (MGA) to reveal differences among various occupations and generations. The findings indicate that attractiveness (ATT), anthropomorphism (ANT), and interactivity (INT) significantly influence hedonic motivation (HM) and social presence (SP). Furthermore, authenticity (AUT) positively affects both SP and trust in AIBEs (TAI). Consumer purchase intention (PI) is significantly impacted by SP but is not directly influenced by HM and TAI. Notably, technology readiness (optimism and innovativeness) positively and significantly influences consumer PI but does not alter the potential moderating effects of HM, SP, and TAI. This study not only broadens and deepens the application of CAB theory but also elucidates the potential development of AIBEs in future metaverse research, providing practical implications and guidance for marketers to enhance consumer purchase intentions and boost product sales. Full article

(This article belongs to the Topic Digital Marketing Dynamics: From Browsing to Buying)

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22 pages, 468 KiB

Open AccessArticle

Adoption of Buy Now, Pay Later (BNPL): A Time Inconsistency Perspective

by Yini Cheng and Jiazhen Huo

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 81; https://doi.org/10.3390/jtaer20020081 - 23 Apr 2025

Viewed by 358

Abstract

Buy Now, Pay Later (BNPL) is a rapidly growing fintech tool, which is particularly popular among young consumers, with the potential to support more sustainable retail consumption. While firms increasingly adopt BNPL, its impact on time-inconsistent consumers remains underexplored. We address this gap [...] Read more.

Buy Now, Pay Later (BNPL) is a rapidly growing fintech tool, which is particularly popular among young consumers, with the potential to support more sustainable retail consumption. While firms increasingly adopt BNPL, its impact on time-inconsistent consumers remains underexplored. We address this gap using two game-theoretic models: one with traditional payment and one with BNPL. In both models, time-inconsistent consumers decide whether to purchase and then whether to return a product after learning about their fitness. In the traditional model, greater time inconsistency reduces optimal price, demand, and profit. In contrast, these outcomes remain unaffected by time inconsistency under BNPL. Comparing the equilibrium results of the two models, we find that the firm always benefits more from offering BNPL than traditional payment when consumers are time-inconsistent. By deferring payment, BNPL increases consumers’ present willingness to buy, enabling firms to charge higher prices without reducing demand, and thereby achieve higher profits. Although BNPL can improve firm revenue and overall welfare, it may reduce consumer surplus by encouraging over-consumption. We also consider the presence of the BNPL provider and default of payments to make our results more robust. These findings highlight the need for caution and potential regulation to protect consumers with self-control problems. Full article

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18 pages, 728 KiB

Open AccessArticle

Understanding the Impact of Inconsistency on the Helpfulness of Online Reviews

by Junsung Park and Heejun Park

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 80; https://doi.org/10.3390/jtaer20020080 - 22 Apr 2025

Viewed by 299

Abstract

This study investigates how review inconsistency influences perceived helpfulness in online restaurant reviews both in ratings and specific aspects of service attributes. Drawing on 106,464 Yelp reviews spanning 666 restaurants, we employed aspect-based sentiment analysis and Tobit regression to capture not only rating [...] Read more.

This study investigates how review inconsistency influences perceived helpfulness in online restaurant reviews both in ratings and specific aspects of service attributes. Drawing on 106,464 Yelp reviews spanning 666 restaurants, we employed aspect-based sentiment analysis and Tobit regression to capture not only rating inconsistencies but also differences in sentiment toward décor, taste, service, and price. Results indicate that rating inconsistency negatively affects review helpfulness, suggesting that highly divergent ratings reduce credibility. However, aspect inconsistency shows mixed effects. Discrepancies in décor and taste positively influence perceived helpfulness by offering novel information, whereas service-related inconsistencies diminish review helpfulness, due to heightened consumer sensitivity to possible service failures. Reviewer expertise further strengthens the negative influence of inconsistency as readers expect experienced reviewers to provide objective feedback. These findings extend current research by shifting the analytical lens from individual reviews to sets of reviews, thereby capturing the relational dynamics that shape consumers’ perceptions of review credibility. The results also highlight the importance of analyzing review content by specific aspects to uncover nuanced effects. Practically, platforms can benefit from grouping reviews by attributes and alerting users to noteworthy inconsistencies, facilitating more informed consumer decision-making. Full article

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

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24 pages, 1002 KiB

Open AccessArticle

Does Gender Matter for Electronic Word-of-Mouth Interactions in Social Media Marketing Strategies? An Empirical Multi-Sample Approach

by Simona Vinerean, Alin Opreana, Camelia Budac and Diana Marieta Mihaiu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 79; https://doi.org/10.3390/jtaer20020079 - 21 Apr 2025

Viewed by 366

Abstract

Considering social media’s expansion worldwide, marketing academics and marketers emphasize the need to consider electronic word of mouth (eWOM) for strategic marketing decisions. However, there is limited research regarding the ways in which male and female consumers engage in eWOM behaviors. This research [...] Read more.

Considering social media’s expansion worldwide, marketing academics and marketers emphasize the need to consider electronic word of mouth (eWOM) for strategic marketing decisions. However, there is limited research regarding the ways in which male and female consumers engage in eWOM behaviors. This research aims to explore the gender-specific dynamics of eWOM drivers in social media marketing, by validating a proposed model of key predictors for two samples (of female and male respondents). Data were gathered from two samples of social media users. For this empirical research, we integrated structural equation modeling and an artificial neural network (PLS-SEM-ANN) for a comprehensive approach intended to generate practical and theoretical insights for eWOM. Hypothesis testing reflected contrasting results—for female respondents, the key eWOM drivers were customer participation, involvement, loyalty, and customer satisfaction; whereas, for male respondents, the key predictors were brand familiarity, loyalty, and satisfaction. The significant variables supported by SEM were included in ANN models as input neurons, showcasing nonlinear relationships among constructs for both samples. Thus, this research provides theoretical contributions regarding eWOM, gender assessments, and the social media marketing literature. From a practical perspective, this study advances targeted social media marketing strategies to enhance consumer–brand interactions. Full article

(This article belongs to the Collection Enhancing Consumer Experience through Mobile Commerce: Challenges and Opportunities)

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18 pages, 1093 KiB

Open AccessArticle

An Investigation into the Critical Factors’ Impact on Digital Technology Transformation in Taiwanese Family Enterprises

by Thi-Them Hoang, Yung-Fu Huang and Manh-Hoang Do

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 78; https://doi.org/10.3390/jtaer20020078 - 21 Apr 2025

Viewed by 319

Abstract

The study aims to evaluate the factors influencing digital technology transformation in Taiwanese family companies. Data were obtained from nine Taiwanese experts with extensive expertise in family businesses and analyzed using the TOPSIS approach. The research findings identify twelve essential factors that influence [...] Read more.

The study aims to evaluate the factors influencing digital technology transformation in Taiwanese family companies. Data were obtained from nine Taiwanese experts with extensive expertise in family businesses and analyzed using the TOPSIS approach. The research findings identify twelve essential factors that influence digital technology transformation and provide the best recommendations for organizations. The study identified and analyzed four key elements deemed most critical in influencing the digital transformation of Taiwanese family businesses: education and training, technological complexity, technological advancements, and management support. Importantly, the organizational group is the primary driver of digital transformation through the case of Taiwanese family enterprises. This study adds to the existing literature by identifying the most essential criteria and ranking them. The Taiwanese family enterprises should use this model cautiously, considering the potential relationships among group factors in the TOE model. Moreover, the findings also offer potential suggestions for policymakers to enhance the integration of digital technologies across all facets of society and business. Full article

(This article belongs to the Section Digital Business Organization)

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27 pages, 4436 KiB

Open AccessArticle

Leveraging Large Language Models for Sentiment Analysis and Investment Strategy Development in Financial Markets

by Yejoon Mun and Namhyoung Kim

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 77; https://doi.org/10.3390/jtaer20020077 - 20 Apr 2025

Viewed by 652

Abstract

This study investigates the application of large language models (LLMs) in sentiment analysis of financial news and their use in developing effective investment strategies. We conducted sentiment analysis on news articles related to the top 30 companies listed on Nasdaq using both discriminative [...] Read more.

This study investigates the application of large language models (LLMs) in sentiment analysis of financial news and their use in developing effective investment strategies. We conducted sentiment analysis on news articles related to the top 30 companies listed on Nasdaq using both discriminative models such as BERT and FinBERT, and generative models including Llama 3.1, Mistral, and Gemma 2. To enhance the robustness of the analysis, advanced prompting techniques—such as Chain of Thought (CoT), Super In-Context Learning (SuperICL), and Bootstrapping—were applied to generative LLMs. The results demonstrate that long strategies generally yield superior portfolio performance compared to short and long–short strategies. Notably, generative LLMs outperformed discriminative models in this context. We also found that the application of SuperICL to generative LLMs led to significant performance improvements, with further enhancements noted when both SuperICL and Bootstrapping were applied together. These findings highlight the profitability and stability of the proposed approach. Additionally, this study examines the explainability of LLMs by identifying critical data considerations and potential risks associated with their use. The research highlights the potential of integrating LLMs into financial strategy development to provide a data-driven foundation for informed decision-making in financial markets. Full article

(This article belongs to the Topic Artificial Intelligence Applications in Financial Technology, 2nd Edition)

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26 pages, 3678 KiB

Open AccessArticle

Digital Image Copyright Protection and Management Approach—Based on Artificial Intelligence and Blockchain Technology

by Jikuan Xu, Jiamin Zhang and Junhan Wang

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 76; https://doi.org/10.3390/jtaer20020076 - 18 Apr 2025

Viewed by 348

Abstract

The issue of image copyright infringement is prevalent in current e-commerce activities. Users employ methods such as image cropping, compression, and noise addition, making it difficult for traditional copyright detection technologies to identify and track infringements. This study proposes an image copyright registration, [...] Read more.

The issue of image copyright infringement is prevalent in current e-commerce activities. Users employ methods such as image cropping, compression, and noise addition, making it difficult for traditional copyright detection technologies to identify and track infringements. This study proposes an image copyright registration, protection, and management method based on artificial intelligence and blockchain technology, aiming to address the current challenges of low accuracy in digital copyright infringement judgment, the vulnerability of image fingerprints stored on the chain to tampering, the complexity of encryption algorithms and key acquisition methods through contract calls, and the secure storage of image information during data circulation. The research combines artificial intelligence technology with traditional blockchain technology to overcome the inherent technical barriers of blockchain. It introduces an originality detection model based on deep learning technology after conducting both off-chain and on-chain detection of unidentified images, providing triple protection for digital image copyright infringement detection and enabling efficient active defense and passive evidence storage. Additionally, the study improves upon the traditional image perceptual hashing in blockchain, which has poor robustness, by adding chaotic encryption sequences to protect the image data on the chain, and its effectiveness has been verified through experiments. Ultimately, the research hopes to provide e-commerce entities with an effective and feasible digital copyright protection and management solution, safeguarding their intellectual property rights and fostering a legal and reasonable competitive environment in e-commerce. Full article

(This article belongs to the Special Issue Blockchain Business Applications and the Metaverse)

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28 pages, 2825 KiB

Open AccessArticle

Platforms’ Cross-Border Competition and Innovation Are Driven by Data Elements: A Two-Stage Evolutionary Game Analysis

by Meixuan Li, Zhong Yao and Menglei Kong

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 75; https://doi.org/10.3390/jtaer20020075 - 17 Apr 2025

Viewed by 229

Abstract

Driven by data, the cross-border expansion of head platforms (HPs) leveraging their data advantages increasingly impacts small and medium-sized platforms (SMPs) and the market innovation ecosystem. This paper constructs a two-stage evolutionary game model to depict the competitive dynamics between HPs and SMPs [...] Read more.

Driven by data, the cross-border expansion of head platforms (HPs) leveraging their data advantages increasingly impacts small and medium-sized platforms (SMPs) and the market innovation ecosystem. This paper constructs a two-stage evolutionary game model to depict the competitive dynamics between HPs and SMPs from the perspective of platforms’ behaviors and strategies. This study finds that, in the core market, HPs’ expansion and SMPs’ retention depend on three factors: HPs’ expansion costs and their impact on data resources, SMPs’ operational costs and their impact on data resources, and the gap in the data value between the platforms. In related markets, under a competitive environment, HPs with a greater innovation influence tend to choose cross-border innovation, while resource-limited SMPs may opt for non-innovation. However, if SMPs have a greater innovation influence but face high costs, the game will not converge to a specific equilibrium. In a monopolistic environment, stable strategies are driven by the scale of innovation and the innovation influence of each platform. Except in cases of minor innovation with a strong innovation influence from SMPs or major innovation with a strong influence from HPs, SMPs’ innovation influence and innovation costs are decisive in the game. Full article

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17 pages, 254 KiB

Open AccessArticle

Factors That Influence the Use of the Online Channel for the Purchase of Food Products in Spain

by Alberto Luján-Salamanca, Alfonso Infante-Moro, Juan C. Infante-Moro and Julia Gallardo-Pérez

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 74; https://doi.org/10.3390/jtaer20020074 - 15 Apr 2025

Viewed by 343

Abstract

The use of the online channel for the purchase of food products is increasing, which not only creates new opportunities for companies and businesses, but also poses great challenges. This study aimed to identify the factors related to these challenges that influence the [...] Read more.

The use of the online channel for the purchase of food products is increasing, which not only creates new opportunities for companies and businesses, but also poses great challenges. This study aimed to identify the factors related to these challenges that influence the use of the online channel for the purchase of food products in Spain. Through a bibliographic review and a Delphi study with experts, 26 factors were identified and grouped into four contexts: technology, marketing strategies, buyer convenience, and security and reliability. This identification of factors can be of great value in improving the sales of companies or businesses in the food sector that already use the online channel for the sale of their products or intend to use it for this purpose in the future; furthermore, it will help these companies or businesses to implement sales strategies that will truly satisfy the needs of potential consumers in Spain. Full article

(This article belongs to the Section Digital Business Organization)

25 pages, 7161 KiB

Open AccessArticle

Automated Runtime Verification of Security for E-Commerce Smart Contracts

by Yang Liu, Shengjie Zhang and Yan Ma

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 73; https://doi.org/10.3390/jtaer20020073 - 13 Apr 2025

Viewed by 340

Abstract

As a novel decentralized computing paradigm, blockchain is expected to disrupt the existing e-commerce architecture and process. Secure smart contracts are the crucial foundation for e-commerce based on blockchain. However, vulnerabilities in smart contracts occur from time to time and cause significant financial [...] Read more.

As a novel decentralized computing paradigm, blockchain is expected to disrupt the existing e-commerce architecture and process. Secure smart contracts are the crucial foundation for e-commerce based on blockchain. However, vulnerabilities in smart contracts occur from time to time and cause significant financial losses in e-commerce. Some static verification methods have been developed to guarantee security for e-commerce smart contracts at design time, but they cannot support complex scenarios at runtime. As a lightweight verification method, runtime verification is a potential method for secure e-commerce smart contracts. The existing runtime verification methods are based on the manual instrument, which leads to additional overheads and gas consumption. To deal with this, we propose a passive learning-based runtime verification framework for e-commerce smart contracts. Firstly, by exploring the Genetic algorithm to evolve state merging and automaton reorganizing in order to simultaneously split time and gas behaviors, we propose a passive learning method to model runtime information for e-commerce smart contracts (PL4ESC). It directly learns P²TA (priced probabilistic timed automaton) from runtime traces without any prior knowledge. Then, we integrate PL4ESC with the open-source PAT (Process Analysis Toolkit) to automatically verify the security of runtime e-commerce smart contracts. The experiments show that PL4ESC is better at accuracy and precision than state-of-the-art passive learning methods. It improves accuracy by 1 to 4 percent compared to TAG and RTI+. As far as we know, it is not only the first learning method that can learn a P²TA from traces, but it is also the first automated runtime verification framework for e-commerce smart contracts. This will provide security guarantees for blockchain-based e-commerce. Full article

(This article belongs to the Special Issue Blockchain Business Applications and the Metaverse)

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18 pages, 1450 KiB

Open AccessArticle

Inventory Allocation: Omnichannel Demand Fulfillment with Admission Control

by Fangfang Ma, Shaochuan Fu, Yuanyuan Zhang and Benxuan Miao

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 72; https://doi.org/10.3390/jtaer20020072 - 12 Apr 2025

Viewed by 225

Abstract

Ensuring the profitability of retailers utilizing in-store inventory for online fulfillment is a pivotal issue in omnichannel retailing. This study examines the inventory allocation challenges faced by retailers when managing interactions between online and offline channels to identify strategies that maximize revenue. The [...] Read more.

Ensuring the profitability of retailers utilizing in-store inventory for online fulfillment is a pivotal issue in omnichannel retailing. This study examines the inventory allocation challenges faced by retailers when managing interactions between online and offline channels to identify strategies that maximize revenue. The findings enable retailers to address key operational conflicts while implementing omnichannel strategies. We develop an omnichannel newsvendor model, deriving an optimal strategy for retailer inventory level and online acceptance thresholds, demonstrating the economic superiority of this approach over traditional policy. Furthermore, this paper further explores how carry-over inventory influences strategic decisions, particularly in quantifying the trade-off between the cancellation cost and the inventory holding cost. The results reveal that cancellation costs incentivize retailers to increase safety stock and reduce online acceptance thresholds, with strategy sensitivity intensifying as offline demand dispersion grows. Compared to the traditional policy, our policy demonstrates superior performance when the cancellation cost remains below a critical value, though its effectiveness decreases under high offline demand dispersion. Moreover, dynamic strategy adjustments must balance the cancellation cost against the holding cost in the carry-over scenario. The proposed framework systematically integrates inventory allocation with demand admission control, addressing a critical gap in existing literature that has failed to comprehensively link these two operational levers. This dual-focused perspective significantly advances omnichannel inventory management theory. Full article

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21 pages, 1668 KiB

Open AccessArticle

Factors of Customer Loyalty and Retention in the Digital Environment

by Matheus de Sousa Pereira, Beatriz Schmitt de Castro, Brenda Alves Cordeiro, Bruno Schmitt de Castro, Maria Gabriela Mendonça Peixoto, Eugenia Cornils Monteiro da Silva and Marcelo Carneiro Gonçalves

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 71; https://doi.org/10.3390/jtaer20020071 - 12 Apr 2025

Viewed by 741

Abstract

Customer loyalty and retention are crucial for digital platforms, yet systematic studies integrating technological innovation and loyalty strategies remain scarce. This study addresses this gap by conducting a bibliometric analysis of key factors influencing customer retention in the digital environment. Our research employs [...] Read more.

Customer loyalty and retention are crucial for digital platforms, yet systematic studies integrating technological innovation and loyalty strategies remain scarce. This study addresses this gap by conducting a bibliometric analysis of key factors influencing customer retention in the digital environment. Our research employs a quantitative bibliometric approach using the Biblioshiny and Bibliometrix tools (RStudio 2022.02), analyzing 300 scientific articles from the Web of Science database (2021–2024). This study applies bibliometric techniques such as descriptive metrics, bibliographic coupling, co-citation, and scientific collaboration mapping to identify trends and thematic clusters. Our findings indicate that emerging technologies, including artificial intelligence and big data, significantly impact customer experience, trust, and engagement. Personalization and digital innovation emerge as fundamental drivers of customer retention, offering strategic insights for companies aiming to strengthen competitiveness in the global digital market. Full article

(This article belongs to the Topic Interactive Marketing in the Digital Era)

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29 pages, 1712 KiB

Open AccessArticle

Exploring the Influence of Cloud Computing on Supply Chain Performance: The Mediating Role of Supply Chain Governance

by Dan Yang, Ran Li and Sen Liu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 70; https://doi.org/10.3390/jtaer20020070 - 10 Apr 2025

Viewed by 554

Abstract

Cloud computing represents a groundbreaking technological change that transforms traditional IT operational paradigms, driving significant improvements in supply chain efficiency and unlocking new value through digital capabilities. Despite its growing influence, empirical research on this subject remains limited, with unclear explanations of the [...] Read more.

Cloud computing represents a groundbreaking technological change that transforms traditional IT operational paradigms, driving significant improvements in supply chain efficiency and unlocking new value through digital capabilities. Despite its growing influence, empirical research on this subject remains limited, with unclear explanations of the specific ways cloud computing enhances supply chain operations. The precise mechanisms through which it influences supply chain dynamics are yet to be fully explored. This study employs survey data from Chinese enterprises utilizing cloud computing, applying Smart PLS 3.0 for partial least squares structural equation modeling (PLS-SEM) to assess how cloud-based technical competencies affect supply chain outcomes. Grounded in IT capability theory, we conceptualize cloud computing’s technical dimensions as Flexible IT Infrastructure and Cloud/Business Synergy while incorporating supply chain governance as a mediator and market uncertainty as a moderator to clarify the relationship between cloud capabilities and performance. Our findings advance both scholarly and managerial perspectives on cloud computing’s role in modern supply chains. Full article

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

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22 pages, 1195 KiB

Open AccessArticle

Harmonizing Sight and Sound: The Impact of Auditory Emotional Arousal, Visual Variation, and Their Congruence on Consumer Engagement in Short Video Marketing

by Qiang Yang, Yudan Wang, Qin Wang, Yushi Jiang and Jingpeng Li

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 69; https://doi.org/10.3390/jtaer20020069 - 8 Apr 2025

Viewed by 701

Abstract

Social media influencers strategically design the auditory and visual features of short videos to enhance consumer engagement. Among these, auditory emotional arousal and visual variation play crucial roles, yet their interactive effects remain underexplored. Drawing on multichannel integration theory, this study applies multimodal [...] Read more.

Social media influencers strategically design the auditory and visual features of short videos to enhance consumer engagement. Among these, auditory emotional arousal and visual variation play crucial roles, yet their interactive effects remain underexplored. Drawing on multichannel integration theory, this study applies multimodal machine learning to analyze 12,842 short videos from Douyin, integrating text analysis, sound recognition, and image processing. The results reveal an inverted U-shaped relationship between auditory emotional arousal and consumer engagement, where moderate arousal maximizes interaction while excessively high or low arousal reduces engagement. Visual variation, however, exhibits a positive linear effect, with greater variation driving higher engagement. Notably, audiovisual congruence significantly enhances engagement, as high alignment between arousal and visual variation optimizes consumer information processing. These findings advance short video marketing research by uncovering the multisensory interplay in consumer engagement. They also provide practical guidance for influencers in optimizing voice and visual design strategies to enhance content effectiveness. Full article

(This article belongs to the Topic Interactive Marketing in the Digital Era)

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21 pages, 661 KiB

Open AccessArticle

Consumer Information-Seeking and Cross-Media Campaigns: An Interactive Marketing Perspective on Multi-Platform Strategies and Attitudes Toward Innovative Products

by Hyunkoo Heo and Sinae Lee

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 68; https://doi.org/10.3390/jtaer20020068 - 8 Apr 2025

Viewed by 500

Abstract

This study investigates how consumers’ information-seeking motivation and perceptions of cross-media campaigns influence their attitudes toward innovative products. Drawing from the perspective of interactive marketing, it highlights the role of consumer–brand interaction in shaping product evaluation and acceptance. The findings indicate that when [...] Read more.

This study investigates how consumers’ information-seeking motivation and perceptions of cross-media campaigns influence their attitudes toward innovative products. Drawing from the perspective of interactive marketing, it highlights the role of consumer–brand interaction in shaping product evaluation and acceptance. The findings indicate that when consumers perceive a product as highly innovative, they tend to experience both curiosity and uncertainty. This activates their need for information-seeking, which subsequently increases their engagement with cross-media campaigns designed with interactive marketing elements. Through this process, consumers develop more favorable attitudes toward the product. The results also reveal a significant dual mediation effect between perceived innovativeness and product attitude, mediated by the need for information-seeking and perception of cross-media campaigns. Although each path may not independently reach significance, the combined sequential mechanism—where consumers actively explore and interact with brand content—plays a critical role in shaping product attitudes. Full article

(This article belongs to the Topic Interactive Marketing in the Digital Era)

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26 pages, 457 KiB

Open AccessArticle

Measuring Localness in E-Commerce Using the Expenses Localness Indicators Model

by Georgia Parastatidou and Vassilios Chatzis

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 67; https://doi.org/10.3390/jtaer20020067 - 7 Apr 2025

Viewed by 337

Abstract

This paper aims to define a model for measuring the localness of a company in an innovative and reliable way, motivated by the growing consumer interest in purchasing local products and supporting local economies. The proposed Expenses Localness Indicators (ELI) model uses existing [...] Read more.

This paper aims to define a model for measuring the localness of a company in an innovative and reliable way, motivated by the growing consumer interest in purchasing local products and supporting local economies. The proposed Expenses Localness Indicators (ELI) model uses existing data from information systems to define Localness Indicators, and incorporates Localness Levels based on geographic and economic criteria. It can be applied to any type of financial entity and overcomes the difficulty of defining localness in e-commerce companies or digital businesses in general. Previous studies have examined the impact of localness and investigated its effectiveness as a branding strategy for managers, mainly through product traceability. The ELI model uses as data the expenses of a company paid to other financial entities. The Expenses Localness Indicators are determined based on the distribution of these payments combined with the localness of the paid financial entities. These Indicators represent the degree of localness as a percentage, ranging from 0% (non-local) to 100% (fully local), and may vary over time. The results of the presented examples indicate that a company’s localness increases as it spends more of its expenses on local financial entities and vice versa. Specific strategies have been tested using synthetic data that demonstrate the correct functioning of the model’s indicators. The ELI model could be used to provide reliable and certifiable information to consumers who want to know where their money goes when they buy products. Implementing the proposed model on a large scale would require acceptance by as many companies and states as possible. However, by making the necessary adjustments, the model could be applied on a smaller scale, supported by consumers and local governments interested in uncovering knowledge about localness. It could also be established as a valid indicator of localness to provide information that researchers, government agencies and professionals can use to promote local entrepreneurship. Full article

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23 pages, 553 KiB

Open AccessArticle

Impact Mechanisms of Consumer Impulse Buying in Accumulative Social Live Shopping: Considering Para-Social Relationship Moderating Role

by Shugang Li, Yuqi Zhang, Yixin Tang, Wenjing Zhao and Zhaoxu Yu

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 66; https://doi.org/10.3390/jtaer20020066 - 7 Apr 2025

Viewed by 585

Abstract

Based on para-social interaction (PSI) theory and social identity perspective, this study explores the mechanisms driving consumers’ impulse buying in social live shopping. It examines how live content design, namely information comprehensiveness (INFCOM) and interactivity (INT), affects consumer cognition and affective experiences, namely [...] Read more.

Based on para-social interaction (PSI) theory and social identity perspective, this study explores the mechanisms driving consumers’ impulse buying in social live shopping. It examines how live content design, namely information comprehensiveness (INFCOM) and interactivity (INT), affects consumer cognition and affective experiences, namely perceived usefulness (PU), PSI, and sense of belonging (SOB), to generate the influence of the urge to buy impulsively (UBI), and further explores the moderating role of the consumer–broadcaster para-social relationship (PSR) between live content design and consumer experience. Findings indicate that in an accumulative social live shopping environment, comprehensive information and strong interactivity enhance consumer social identity, reduce shopping hesitations and obstacles, and encourage UBI. Forming a close consumer–broadcaster relationship is crucial for promoting social identity and increasing UBI. Even without interactive engagement, consumers who feel a close connection with the broadcaster still experience interaction and SOB. PSR influences impulse buying by enhancing consumer perceptions and thereby promoting UBI. This study advances the understanding of impulse buying from a social identity perspective and suggests that merchants and livestream designers can improve quality and sales by providing comprehensive product information and incorporating diverse interactive elements in live broadcasts. Full article

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26 pages, 929 KiB

Open AccessArticle

Content Characteristics and Customer Purchase Behaviors in Nonfungible Token Digital Artwork Trading

by Zi-Hui Bai, Chao Xu and Sung-Eui Cho

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 65; https://doi.org/10.3390/jtaer20020065 - 4 Apr 2025

Viewed by 398

Abstract

Despite the growing popularity of digital artworks that use nonfungible tokens (NFTs), systematic frameworks for analyzing the content characteristics driving NFT artworks’ creation, sale, and collection remain underdeveloped. Drawing on key insights from a diffusion of innovations, social identity, and value-based adoption theories, [...] Read more.

Despite the growing popularity of digital artworks that use nonfungible tokens (NFTs), systematic frameworks for analyzing the content characteristics driving NFT artworks’ creation, sale, and collection remain underdeveloped. Drawing on key insights from a diffusion of innovations, social identity, and value-based adoption theories, this study constructed a conceptual model that identified six key factors: uniqueness, profitability, prestige, community engagement, collectability, and compatibility. These factors’ effects on consumer purchasing behavior were investigated using perceived value as a mediator. Empirical data were collected from 300 Chinese participants and analyzed using multiple regression analysis. The significant direct effects of profitability, community engagement, collectability, and compatibility on purchasing behavior were identified. Uniqueness and prestige were found to exert indirect effects mediated by perceived value. Furthermore, a fuzzy-set qualitative comparative analysis uncovered configurations of content characteristics sufficient for driving high purchasing behavior. It highlighted low community engagement as a necessary condition for low purchasing behavior and underscored multiple attributes’ synergistic interplay in shaping consumer decisions. By integrating these attributes into the conceptualization of NFT content characteristics and synthesizing theoretical insights, this study enhances the understanding of consumer behavior. Recommendations are provided for NFT creators and platforms to improve content quality, cater to diverse preferences, and enhance user experiences, thereby promoting adoption and sustainable growth. Full article

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

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25 pages, 659 KiB

Open AccessArticle

Market Phases and Price Discovery in NFTs: A Deep Learning Approach to Digital Asset Valuation

by Ho-Jun Kang and Sang-Gun Lee

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 64; https://doi.org/10.3390/jtaer20020064 - 3 Apr 2025

Viewed by 466

Abstract

This study introduces the Channel-wise Attention with Relative Distance (CARD) model for NFT market prediction, addressing the unique challenges of NFT valuation through a novel deep learning architecture. Analyzing 26,287 h of transaction data across major marketplaces, the model demonstrates superior predictive accuracy [...] Read more.

This study introduces the Channel-wise Attention with Relative Distance (CARD) model for NFT market prediction, addressing the unique challenges of NFT valuation through a novel deep learning architecture. Analyzing 26,287 h of transaction data across major marketplaces, the model demonstrates superior predictive accuracy compared to conventional approaches, achieving a 33.5% reduction in Mean Absolute Error versus LSTM models, a 29.7% improvement over Transformer architectures, and a 30.1% enhancement compared to LightGBM implementations. For long-term forecasting (720-h horizon), CARD maintains a 35.5% performance advantage over the next best model. Through SHAP-based regime analysis, we identify distinct feature importance patterns across market phases, revealing how liquidity metrics, top trader activity, and royalty dynamics drive valuations in bear, bull, and neutral markets respectively. The findings provide actionable insights for investors while advancing our theoretical understanding of NFT market microstructure and price discovery mechanisms. Full article

(This article belongs to the Special Issue Blockchain Business Applications and the Metaverse)

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29 pages, 7747 KiB

Open AccessArticle

Empowering Retail in the Metaverse by Leveraging Consumer Behavior Analysis for Personalized Shopping: A Pilot Study in the Saudi Market

by Monerah Alawadh and Ahmed Barnawi

J. Theor. Appl. Electron. Commer. Res. 2025, 20(2), 63; https://doi.org/10.3390/jtaer20020063 - 2 Apr 2025

Viewed by 729

Abstract

The integration of advanced technologies, such as the Metaverse, has the potential to revolutionize the retail industry and enhance the shopping experience. Understanding consumer behavior and leveraging machine learning predictions based on analysis can significantly enhance user experiences, enabling personalized interactions and fostering [...] Read more.

The integration of advanced technologies, such as the Metaverse, has the potential to revolutionize the retail industry and enhance the shopping experience. Understanding consumer behavior and leveraging machine learning predictions based on analysis can significantly enhance user experiences, enabling personalized interactions and fostering overall engagement within the virtual environment. In our ongoing research effort, we have developed a consumer behavior framework to predict interesting buying patterns based on analyzing sales transaction records using association rule learning techniques aiming at improving sales parameters for retailers. In this paper, we introduce a validation analysis of our predictive framework that can improve the personalization of the shopping experience in virtual reality shopping environments, which provides powerful marketing facilities, unlike real-time shopping. The findings of this work provide a promising outcome in terms of achieving satisfactory prediction accuracy in a focused pilot study conducted in association with a prominent retailer in Saudi Arabia. Such results can be employed to empower the personalization of the shopping experience, especially on virtual platforms such as the Metaverse, which is expected to play a revolutionary role in future businesses and other life activities. Shopping in the Metaverse offers a unique blend of immersive experiences and endless possibilities, enabling consumers to interact with products and brands in a virtual environment like never before. This integration of cutting-edge technology not only transforms the retail landscape but also paves the way for a new era of personalized and engaging shopping experiences. Lastly, this empowerment offers new opportunities for retailers and streamlines the process of engaging with customers in innovative ways. Full article

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

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