Pub Date : 2025-01-01DOI: 10.1016/j.jdec.2025.12.001
Tianyu Tong, Kai Hu, Zhilun Chen, Qizhen Liu
Data is widely recognized as a key productive resource in the digital economy, limited empirical work has examined the mechanisms through which data transaction, affects regional economic growth. Exploiting the establishment of China's Data Exchange as a quasi-natural experiment, we employ a difference-in-differences (DID) approach to estimate its causal impact and mechanism. We find that the establishment of Data Exchange raises regional GDP by approximately 7 %, and this effect remains robust to a series of tests. However, contrary to theoretical expectations, our empirical results indicate that this growth is not mediated by increase in regional innovation. Heterogeneity analysis further shows that the positive effect is significantly amplified in cities with stronger complementary endowments. In contrast, regions with less complementary capabilities have not translated data transaction into economic growth. These findings provide causal evidence on the value of data transaction platforms and highlight the need for targeted policies to dismantle structural barriers in data-driven innovation and invest in complementary capabilities, thereby fostering inclusive data-driven growth.
{"title":"How do data transactions promote economic growth? Evidence from China","authors":"Tianyu Tong, Kai Hu, Zhilun Chen, Qizhen Liu","doi":"10.1016/j.jdec.2025.12.001","DOIUrl":"10.1016/j.jdec.2025.12.001","url":null,"abstract":"<div><div>Data is widely recognized as a key productive resource in the digital economy, limited empirical work has examined the mechanisms through which data transaction, affects regional economic growth. Exploiting the establishment of China's Data Exchange as a quasi-natural experiment, we employ a difference-in-differences (DID) approach to estimate its causal impact and mechanism. We find that the establishment of Data Exchange raises regional GDP by approximately 7 %, and this effect remains robust to a series of tests. However, contrary to theoretical expectations, our empirical results indicate that this growth is not mediated by increase in regional innovation. Heterogeneity analysis further shows that the positive effect is significantly amplified in cities with stronger complementary endowments. In contrast, regions with less complementary capabilities have not translated data transaction into economic growth. These findings provide causal evidence on the value of data transaction platforms and highlight the need for targeted policies to dismantle structural barriers in data-driven innovation and invest in complementary capabilities, thereby fostering inclusive data-driven growth.</div></div>","PeriodicalId":100773,"journal":{"name":"Journal of Digital Economy","volume":"4 ","pages":"Pages 351-365"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jdec.2025.11.004
Chengliang Zhang , Chenqi Liu , Yuya Liu
Despite substantial investment in omnichannel systems, customer loyalty remains unstable, raising questions about how technology-enabled features influence long-term brand commitment. This study investigates how three omnichannel innovation characteristics, namely, channel integration, system flexibility, and service personalization, affect brand loyalty through customer empowerment. Drawing on Innovation Diffusion Theory, these characteristics are conceptualized as service-related innovation attributes evaluated during the adoption process. Survey data from 355 Chinese consumers were analyzed using structural equation modeling. Results show that each attribute increases customer empowerment, which partially mediates their impact on loyalty. Personal innovativeness and product category involvement further moderate these effects. The study contributes to the literature by identifying service-specific innovation attributes relevant to omnichannel contexts, clarifying the psychological role of empowerment in loyalty formation, and specifying individual-level conditions under which these effects are strengthened.
{"title":"Omnichannel innovation characteristics and brand loyalty: An innovation diffusion theory perspective on customer empowerment","authors":"Chengliang Zhang , Chenqi Liu , Yuya Liu","doi":"10.1016/j.jdec.2025.11.004","DOIUrl":"10.1016/j.jdec.2025.11.004","url":null,"abstract":"<div><div>Despite substantial investment in omnichannel systems, customer loyalty remains unstable, raising questions about how technology-enabled features influence long-term brand commitment. This study investigates how three omnichannel innovation characteristics, namely, channel integration, system flexibility, and service personalization, affect brand loyalty through customer empowerment. Drawing on Innovation Diffusion Theory, these characteristics are conceptualized as service-related innovation attributes evaluated during the adoption process. Survey data from 355 Chinese consumers were analyzed using structural equation modeling. Results show that each attribute increases customer empowerment, which partially mediates their impact on loyalty. Personal innovativeness and product category involvement further moderate these effects. The study contributes to the literature by identifying service-specific innovation attributes relevant to omnichannel contexts, clarifying the psychological role of empowerment in loyalty formation, and specifying individual-level conditions under which these effects are strengthened.</div></div>","PeriodicalId":100773,"journal":{"name":"Journal of Digital Economy","volume":"4 ","pages":"Pages 302-318"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145622930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":100773,"journal":{"name":"Journal of Digital Economy","volume":"4 ","pages":"Pages 108-122"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147197069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":100773,"journal":{"name":"Journal of Digital Economy","volume":"4 ","pages":"Pages 268-288"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147197084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jdec.2025.11.003
Bingbing Yang , Dengxi Huang , Xuefang Pan , Xiyue Cui , Hening Zhang
Data, as a new type of asset, has huge potential value. However, due to the non-traditional material asset attributes of data assets, there are many difficulties in their valuation. This paper introduces optimized cost approach, optimized income approach, and optimized market approach, to address key challenges in data asset valuation, including low accuracy, inefficiency, limited applicability, lack of theoretical grounding, and implementation difficulties. Considering characteristics of data assets, this paper proposes a series of optimized approaches to evaluate data assets in real world. A case study involving a commercial bank is presented to validate the optimized approaches for evaluating the internal data assets of enterprises.
{"title":"Data asset valuation: Research and application in commercial banking","authors":"Bingbing Yang , Dengxi Huang , Xuefang Pan , Xiyue Cui , Hening Zhang","doi":"10.1016/j.jdec.2025.11.003","DOIUrl":"10.1016/j.jdec.2025.11.003","url":null,"abstract":"<div><div>Data, as a new type of asset, has huge potential value. However, due to the non-traditional material asset attributes of data assets, there are many difficulties in their valuation. This paper introduces optimized cost approach, optimized income approach, and optimized market approach, to address key challenges in data asset valuation, including low accuracy, inefficiency, limited applicability, lack of theoretical grounding, and implementation difficulties. Considering characteristics of data assets, this paper proposes a series of optimized approaches to evaluate data assets in real world. A case study involving a commercial bank is presented to validate the optimized approaches for evaluating the internal data assets of enterprises.</div></div>","PeriodicalId":100773,"journal":{"name":"Journal of Digital Economy","volume":"4 ","pages":"Pages 319-333"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jdec.2025.05.005
Sintayehu Ermias Lolemo, Hemal B. Pandya
This study investigates the mediating role of customer e-satisfaction in the relationships between e-service quality, brand image, and e-loyalty within Ethiopia's digital banking sector, with a specific focus on the Commercial Bank of Ethiopia. Using a quantitative research design, data were gathered through self-administered surveys and analyzed using structural equation modeling (SEM). To mitigate potential bias, the common latent factor (CLF) approach was used. The results demonstrate that e-service quality significantly enhances e-loyalty, with customer e-satisfaction serving as a crucial mediator. Additionally, brand image exerts both a direct positive effect on e-loyalty and an indirect influence through customer e-satisfaction. By extending the cognitive-affect-conation pattern model to the digital banking context, this study offers valuable theoretical and practical contributions for banks aiming to strengthen customer e-loyalty in a competitive digital landscape.
{"title":"Customer e-satisfaction as a mediator between e-service quality, brand image, and e-loyalty: Insights from Ethiopian digital banking technology","authors":"Sintayehu Ermias Lolemo, Hemal B. Pandya","doi":"10.1016/j.jdec.2025.05.005","DOIUrl":"10.1016/j.jdec.2025.05.005","url":null,"abstract":"<div><div>This study investigates the mediating role of customer e-satisfaction in the relationships between e-service quality, brand image, and e-loyalty within Ethiopia's digital banking sector, with a specific focus on the Commercial Bank of Ethiopia. Using a quantitative research design, data were gathered through self-administered surveys and analyzed using structural equation modeling (SEM). To mitigate potential bias, the common latent factor (CLF) approach was used. The results demonstrate that e-service quality significantly enhances e-loyalty, with customer e-satisfaction serving as a crucial mediator. Additionally, brand image exerts both a direct positive effect on e-loyalty and an indirect influence through customer e-satisfaction. By extending the cognitive-affect-conation pattern model to the digital banking context, this study offers valuable theoretical and practical contributions for banks aiming to strengthen customer e-loyalty in a competitive digital landscape.</div></div>","PeriodicalId":100773,"journal":{"name":"Journal of Digital Economy","volume":"4 ","pages":"Pages 1-15"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jdec.2025.08.002
Gabriel Antonio Moyano-Londoño, Valentina Cardona-Granada, Paola Alzate
Logistics 4.0 and emerging technologies have transformed supply chain management, fostering innovation, operational efficiency, and sustainability. This study conducts a scientometric analysis of 698 publications from 2005 to 2023, indexed in Scopus and Web of Science (WOS), to explore the evolution of Industry 4.0 applications in supply chains. The research follows a two-stage approach using PRISMA and Tree of Science (TOS) methodologies. First, scientific mapping was performed through RStudio Cloud and Bibliometrix. Then, co-citation network analysis in Gephi enabled the construction of the Tree of Science and the identification of three core research clusters. The first cluster links Industry 4.0 to circular economy strategies, emphasizing the integration of technologies such as blockchain and additive manufacturing to enable sustainable and regenerative supply networks. The second cluster focuses on the adoption of specific digital technologies, such as IoT and blockchain, within supply chain operations, highlighting traceability, transparency, and governance. The third cluster centers on the evolution of smart supply chains and digital maturity, integrating strategic frameworks and extending the scope of research to diverse sectors, including SMEs, healthcare, and education. This study contributes to existing knowledge by mapping the conceptual and methodological evolution of Logistics 4.0 research, revealing how digitalization and sustainability have become central to supply chain innovation. Emerging research lines include the development of integrative frameworks for circularity and digitalization, empirical validation of technology adoption models, and expansion of Industry 4.0 applications beyond manufacturing. Future work is encouraged to address regulatory challenges, sectoral adaptations, and socio-environmental impacts, while exploring concepts such as Society 5.0 and smart working.
物流4.0和新兴技术已经改变了供应链管理，促进了创新、运营效率和可持续性。本研究对Scopus和Web of Science （WOS）检索的2005年至2023年698篇出版物进行了科学计量分析，以探讨工业4.0在供应链中的应用演变。该研究采用PRISMA和科学树（TOS）两阶段方法。首先，通过RStudio Cloud和Bibliometrix进行科学制图。然后，通过Gephi的共被引网络分析，构建了科学树，确定了三个核心研究集群。第一个集群将工业4.0与循环经济战略联系起来，强调区块链和增材制造等技术的整合，以实现可持续和可再生的供应网络。第二个集群侧重于在供应链运营中采用特定的数字技术，如物联网和区块链，强调可追溯性、透明度和治理。第三个集群以智能供应链和数字成熟度的演变为中心，整合战略框架并将研究范围扩展到包括中小企业、医疗保健和教育在内的各个部门。本研究通过描绘物流4.0研究的概念和方法演变，揭示了数字化和可持续性如何成为供应链创新的核心，从而为现有知识做出了贡献。新兴的研究方向包括开发循环和数字化的综合框架，技术采用模型的实证验证，以及将工业4.0应用扩展到制造业以外。鼓励未来的工作在探索社会5.0和智能工作等概念的同时，解决监管挑战、部门适应和社会环境影响。
{"title":"Logistics 4.0 and emerging technologies: A scientometric perspective on innovation in supply chains","authors":"Gabriel Antonio Moyano-Londoño, Valentina Cardona-Granada, Paola Alzate","doi":"10.1016/j.jdec.2025.08.002","DOIUrl":"10.1016/j.jdec.2025.08.002","url":null,"abstract":"<div><div>Logistics 4.0 and emerging technologies have transformed supply chain management, fostering innovation, operational efficiency, and sustainability. This study conducts a scientometric analysis of 698 publications from 2005 to 2023, indexed in Scopus and Web of Science (WOS), to explore the evolution of Industry 4.0 applications in supply chains. The research follows a two-stage approach using PRISMA and Tree of Science (TOS) methodologies. First, scientific mapping was performed through RStudio Cloud and Bibliometrix. Then, co-citation network analysis in Gephi enabled the construction of the Tree of Science and the identification of three core research clusters. The first cluster links Industry 4.0 to circular economy strategies, emphasizing the integration of technologies such as blockchain and additive manufacturing to enable sustainable and regenerative supply networks. The second cluster focuses on the adoption of specific digital technologies, such as IoT and blockchain, within supply chain operations, highlighting traceability, transparency, and governance. The third cluster centers on the evolution of smart supply chains and digital maturity, integrating strategic frameworks and extending the scope of research to diverse sectors, including SMEs, healthcare, and education. This study contributes to existing knowledge by mapping the conceptual and methodological evolution of Logistics 4.0 research, revealing how digitalization and sustainability have become central to supply chain innovation. Emerging research lines include the development of integrative frameworks for circularity and digitalization, empirical validation of technology adoption models, and expansion of Industry 4.0 applications beyond manufacturing. Future work is encouraged to address regulatory challenges, sectoral adaptations, and socio-environmental impacts, while exploring concepts such as Society 5.0 and smart working.</div></div>","PeriodicalId":100773,"journal":{"name":"Journal of Digital Economy","volume":"4 ","pages":"Pages 108-122"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":100773,"journal":{"name":"Journal of Digital Economy","volume":"4 ","pages":"Pages 95-107"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147197067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":100773,"journal":{"name":"Journal of Digital Economy","volume":"4 ","pages":"Pages 52-71"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147197070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":100773,"journal":{"name":"Journal of Digital Economy","volume":"4 ","pages":"Pages 123-143"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147197074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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