Journal of Digital Economy最新文献_第2页

Gig work and women's empowerment in rural Pakistan 巴基斯坦农村的零工和妇女赋权

Journal of Digital Economy

Pub Date : 2025-01-01 DOI: 10.1016/j.jdec.2025.09.002

Salman Bashir Memon , Helena Nobre , Nawaz Ahmad

Grounded on 'Capability Approach,' which emphasises the importance of expanding women's capacities, including access to education, healthcare, employment, and political engagement, this study aims to investigate how platforms for the gig economy are empowering women. The research used a sequential exploratory design with three main phases. The first phase corresponds to a qualitative study (Study I) that followed an inductive approach, through netnographic methods, including observation and post-analysis on gig platforms, and semi-structured interviews with 47 women entrepreneurs. Several themes emerged from this exploratory phase, which provided crucial insight into the specific traits, actions, and mindsets that participants felt empowered by and that had an impact on their lives as gig workers. The second phase corresponds to a quantitative study (Study II) grounded on the actual experiences of 338 participants and consists of establishing the factors that impact gig work adoption. The contributing factors that have a substantial impact on how gig workers view and approach their employment are flexibility, autonomy, social networking, decision-making, and gendered barriers. In a third phase (Study III), the relationships between the observed traits and their potential impacts on women's empowerment in the gig economy are tested. The study's conclusions shed light on the intricate and complex relationship between a variety of factors and women's entrepreneurship in the gig economy.

该研究以“能力方法”为基础，强调扩大妇女能力的重要性，包括获得教育、医疗、就业和政治参与的机会，旨在调查零工经济平台如何赋予妇女权力。该研究采用了顺序探索性设计，分为三个主要阶段。第一阶段对应于一项定性研究（研究一），该研究采用归纳方法，通过网络方法，包括对零工平台的观察和后期分析，以及对47名女性企业家的半结构化访谈。在这个探索阶段出现了几个主题，这些主题为参与者提供了重要的见解，让他们了解自己的具体特征、行为和心态，这些特征、行为和心态对他们作为零工的生活产生了影响。第二阶段对应于基于338名参与者的实际经验的定量研究（研究II），并包括建立影响零工工作采用的因素。对零工员工如何看待和对待自己的工作有重大影响的因素是灵活性、自主性、社交网络、决策和性别障碍。在第三阶段（研究III），观察到的特征及其对零工经济中女性赋权的潜在影响之间的关系进行了测试。该研究的结论揭示了各种因素与零工经济中女性创业之间错综复杂的关系。

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引用次数: 0

Committed random double blinded coalition-proofed sampling 承诺随机双盲联合检验抽样

Journal of Digital Economy

Pub Date : 2025-01-01 DOI: 10.1016/j.jdec.2025.05.007

Shengzhe Meng , Jintai Ding

The digital economy, including data trading, auditing, and trust, is an essential and rapidly growing field. A secure and committed data sampling process is necessary for those processes. We introduce a novel committed random double-blind sampling methodology for data auditing and transactions, which utilizes cryptography and blockchain technologies. This approach ensures that the sampler only has access to the sampled data. The sampling method we propose is also double-blind, meaning that neither the sampler nor the data owner can independently determine the positions of the sampled data. Instead, they are jointly decided by both parties. Additionally, the method permits the data sampler to detect if the data owner has intentionally chosen high-quality data or provided data extraneous to the data set. This innovative methodology guarantees that the data sampling process is both trustworthy and traceable. We supply a security analysis and offer solutions for various scenarios, such as multi-file and three-party sampling. We also present a sampling process designed to prevent collusion when sampling occurs among three parties.

包括数据交易、审计和信任在内的数字经济是一个重要且快速增长的领域。这些过程需要一个安全且已提交的数据采样过程。我们介绍了一种新的用于数据审计和事务的承诺随机双盲抽样方法，该方法利用密码学和区块链技术。这种方法确保采样器只能访问被采样的数据。我们提出的采样方法也是双盲的，这意味着采样者和数据所有者都不能独立地确定采样数据的位置。相反，它们由双方共同决定。此外，该方法允许数据采样器检测数据所有者是否有意选择了高质量数据或提供了与数据集无关的数据。这种创新的方法保证了数据采样过程的可靠性和可追溯性。我们提供安全分析，并为各种场景提供解决方案，例如多文件和三方采样。我们还提出了一个采样过程，旨在防止在三方之间发生采样时串通。

引用次数: 0

A machine learning approach to inventory stockout prediction 库存缺货预测的机器学习方法

Journal of Digital Economy

Pub Date : 2025-01-01 DOI: 10.1016/j.jdec.2025.06.002

Yang Liu , Dimitra Kalaitzi , Michael Wang , Christos Papanagnou

The retail industry continues to experience frequent stockouts, driven by the rise of e-commerce and disruptive events such as the COVID-19 pandemic, which have significantly impacted both profitability and supply chain stability. As a result, developing effective models for stockout prediction has become increasingly critical for enhancing the efficiency and resilience of retail operations. The growing availability of data, challenges posed by data imbalance, and high demand uncertainty underscore the need to transition from traditional forecasting models to more intelligent, data-driven approaches that integrate multiple relevant features alongside sales data. In this study, we utilise a large dataset from a retailer comprising over 1.6 million stock keeping units (SKUs) to develop an analytical model based on classical machine learning algorithms aimed at improving stockout prediction accuracy. Our results demonstrate that the proposed approach performs well in handling large-scale, imbalanced data and significantly enhances predictive performance. Feature importance analysis reveals that current inventory levels, short-term demand forecasts (three months), and recent sales data are the most influential factors in predicting stockouts. Furthermore, the findings suggest that recent demand forecasts and sales data have greater predictive power than longer-term projections (six and nine months), highlighting the importance of near-term indicators in inventory stockout prediction accuracy. To the best of our knowledge, these insights provide valuable contributions to understanding stockout dynamics and improving inventory management strategies within the retail sector.

由于电子商务的兴起和COVID-19大流行等破坏性事件的推动，零售业继续频繁缺货，这些事件严重影响了盈利能力和供应链的稳定性。因此，开发有效的缺货预测模型对于提高零售业务的效率和弹性变得越来越重要。越来越多的数据可用性、数据不平衡带来的挑战以及高需求不确定性都强调了从传统预测模型向更智能、数据驱动的方法过渡的必要性，这种方法将多个相关特征与销售数据集成在一起。在本研究中，我们利用来自一家零售商的大型数据集，其中包括超过160万个库存单位（sku），以开发基于经典机器学习算法的分析模型，旨在提高缺货预测的准确性。我们的研究结果表明，该方法在处理大规模、不平衡数据方面表现良好，显著提高了预测性能。特征重要性分析表明，当前库存水平、短期需求预测（三个月）和近期销售数据是预测缺货最具影响力的因素。此外，研究结果表明，近期需求预测和销售数据比长期预测（6个月和9个月）具有更大的预测能力，突出了近期指标在库存缺货预测准确性方面的重要性。据我们所知，这些见解为理解缺货动态和改善零售部门的库存管理策略提供了宝贵的贡献。

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引用次数: 0

The impact of China's digital financial inclusion on multidimensional poverty of households 中国数字普惠金融对家庭多维贫困的影响

Journal of Digital Economy

Pub Date : 2025-01-01 DOI: 10.1016/j.jdec.2025.11.006

Tianna Yang , Tianxi Yang

Does digital financial inclusion alleviate poverty? This study investigates this question by integrating the Digital Financial Inclusion Index of Peking University with microdata from the China Family Panel Studies (CFPS) to examine how the expansion of digital financial inclusion affects household multidimensional poverty in China. Anchored in Amartya Sen's capability approach and operationalized through the Alkire–Foster (A–F) framework, the study identifies multidimensional poverty across five key dimensions: income, health, education, insurance, and living standards. Probit models are employed to estimate how digital financial inclusion influences both the likelihood and structure of multidimensional poverty, while instrumental variable techniques are used to address potential endogeneity. Beyond the average effects, the study further explores the mechanisms through which digital financial inclusion contributes to poverty alleviation, focusing on three channels—promoting household consumption, increasing financial investment, and enhancing access to credit. The results reveal that digital financial inclusion significantly mitigates multidimensional poverty, particularly by improving income, living standards, and health outcomes, though its effects on education and insurance are limited. These findings underscore the transformative role of digital finance in fostering inclusive growth, suggesting that policies expanding digital financial infrastructure and literacy can amplify its poverty-reducing effects and advance equitable development.

数字普惠金融能减轻贫困吗？本研究将北京大学数字普惠金融指数与中国家庭面板研究（CFPS）的微观数据相结合，考察数字普惠金融的扩张对中国家庭多维贫困的影响。该研究以Amartya Sen的能力方法为基础，通过Alkire-Foster （A-F）框架进行操作，从五个关键方面确定了多维贫困：收入、健康、教育、保险和生活水平。Probit模型用于估计数字普惠金融如何影响多维贫困的可能性和结构，而工具变量技术用于解决潜在的内质性问题。除了平均效应之外，该研究还进一步探讨了数字普惠金融有助于减贫的机制，重点关注三个渠道：促进家庭消费、增加金融投资和增加信贷获取。结果显示，数字普惠金融显著减轻了多维贫困，特别是通过提高收入、生活水平和健康结果，尽管其对教育和保险的影响有限。这些发现强调了数字金融在促进包容性增长方面的变革性作用，表明扩大数字金融基础设施和扫盲的政策可以扩大其减贫效果，促进公平发展。

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引用次数: 0

How do data transactions promote economic growth? Evidence from China 数据交易如何促进经济增长？来自中国的证据

Journal of Digital Economy

Pub Date : 2025-01-01 DOI: 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.

数据被广泛认为是数字经济中重要的生产资源，但数据交易影响区域经济增长的机制研究有限。利用中国数据交换的建立作为准自然实验，我们采用差异中的差异（DID）方法来估计其因果影响和机制。我们发现，数据交换的建立使地区GDP提高了约7%，并且这种效应在一系列测试中保持稳健。然而，与理论预期相反，我们的实证结果表明，这种增长并不受区域创新增加的中介作用。异质性分析进一步表明，互补禀赋越强的城市，其正向效应被显著放大。相比之下，互补性较弱的地区并没有将数据交易转化为经济增长。这些发现为数据交易平台的价值提供了因果证据，并强调需要制定有针对性的政策，消除数据驱动创新的结构性障碍，投资于互补能力，从而促进包容性的数据驱动增长。

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引用次数: 0

Omnichannel innovation characteristics and brand loyalty: An innovation diffusion theory perspective on customer empowerment 全渠道创新特征与品牌忠诚：顾客授权的创新扩散理论视角

Journal of Digital Economy

Pub Date : 2025-01-01 DOI: 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.

尽管在全渠道系统上投入了大量资金，但客户忠诚度仍然不稳定，这引发了关于技术支持功能如何影响长期品牌承诺的问题。本研究探讨了三个全渠道创新特征，即渠道整合、系统灵活性和服务个性化如何通过客户授权影响品牌忠诚度。根据创新扩散理论，这些特征被定义为在采用过程中评估的与服务相关的创新属性。采用结构方程模型对355名中国消费者的调查数据进行分析。结果表明，每个属性都增加了客户授权，这部分中介了它们对忠诚度的影响。个人创新和产品类别参与进一步调节了这些影响。本研究通过识别与全渠道环境相关的服务特定创新属性，阐明授权在忠诚形成中的心理作用，并明确这些效应增强的个人层面条件，为文献做出了贡献。

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引用次数: 0

Data asset valuation: Research and application in commercial banking 数据资产评估：在商业银行中的研究与应用

Journal of Digital Economy

Pub Date : 2025-01-01 DOI: 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.

数据作为一种新型资产，具有巨大的潜在价值。然而，由于数据资产具有非传统的物质资产属性，在对其进行估值时存在诸多困难。本文引入优化成本法、优化收益法和优化市场法，解决数据资产评估中准确性低、效率低、适用性有限、缺乏理论基础、实施困难等关键问题。考虑到数据资产的特点，本文提出了一系列优化的数据资产评估方法。以某商业银行为例，对企业内部数据资产评估的优化方法进行了验证。

引用次数: 0

Customer e-satisfaction as a mediator between e-service quality, brand image, and e-loyalty: Insights from Ethiopian digital banking technology 客户电子满意度是电子服务质量、品牌形象和电子忠诚度之间的中介：来自埃塞俄比亚数字银行技术的见解

Journal of Digital Economy

Pub Date : 2025-01-01 DOI: 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.

本研究调查了客户电子满意度在埃塞俄比亚数字银行部门的电子服务质量、品牌形象和电子忠诚度之间的关系中的中介作用，并特别关注埃塞俄比亚商业银行。采用定量研究设计，通过自我调查收集数据，并使用结构方程模型（SEM）进行分析。为了减轻潜在偏差，使用了共同潜在因素（CLF）方法。结果表明，电子服务质量显著提高了电子忠诚，其中顾客电子满意度是一个重要的中介。此外，品牌形象对电子忠诚既有直接的正向影响，也有通过顾客电子满意产生的间接影响。通过将认知-影响-关注模式模型扩展到数字银行环境中，本研究为银行在竞争激烈的数字环境中加强客户电子忠诚度提供了有价值的理论和实践贡献。

引用次数: 0

Logistics 4.0 and emerging technologies: A scientometric perspective on innovation in supply chains 物流4.0与新兴技术：供应链创新的科学计量学视角

Journal of Digital Economy

Pub Date : 2025-01-01 DOI: 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。

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引用次数: 0

Research on the impact and mechanism of China's digital infrastructure construction on air pollution 中国数字化基础设施建设对大气污染的影响及机制研究

Journal of Digital Economy

Pub Date : 2025-01-01 DOI: 10.1016/j.jdec.2025.05.008

Shaojie Zhou , Chenyao Qu

Reducing air pollution is a major goal of digital infrastructure construction, which is the embodiment of the “new infrastructure construction” strategy in the era of smart economy. This paper systematically summarizes the mechanism by which digital infrastructure construction affects air pollution and empirically analyzes the impact of digital infrastructure construction on air pollution based on Chinese provincial panel data from 2011 to 2023. The study finds that the digital infrastructure construction can exert a significant inhibitory effect on air pollution. The analysis of the moderating effect indicates that environmental policies and regulations positively moderate the relationship between digital infrastructure construction and air pollution. The mechanism analysis shows that digital infrastructure reduces air pollution by promoting technological innovation and driving industrial upgrading. The heterogeneous analysis indicates that the emission reduction effect of digital platform construction is more significant. Meanwhile, the construction of digital infrastructure in central and western regions, resource-based regions, and regions with high environmental regulation intensity has a stronger inhibitory effect on air pollution. Further analysis shows that the construction of digital infrastructure not only improves local air quality, but also has a significant mitigating effect on air pollution in neighboring areas. Meanwhile, digital talents reinforce this spatial impact. Finally, according to the research conclusions, the corresponding policy suggestions are put forward.

减少大气污染是数字基础设施建设的一大目标，是智慧经济时代“新基础设施建设”战略的体现。本文系统总结了数字基础设施建设对大气污染的影响机制，并基于2011 - 2023年中国省级面板数据，实证分析了数字基础设施建设对大气污染的影响。研究发现，数字化基础设施建设对大气污染具有显著的抑制作用。调节效应分析表明，环境政策法规正向调节数字基础设施建设与大气污染的关系。机制分析表明，数字基础设施通过促进技术创新和带动产业升级来减少大气污染。异质性分析表明，数字化平台建设的减排效果更为显著。同时，中西部地区、资源型地区和环境规制强度高的地区的数字基础设施建设对大气污染的抑制作用更强。进一步分析表明，数字化基础设施的建设不仅改善了当地的空气质量，而且对周边地区的空气污染也有显著的缓解作用。与此同时，数字人才加强了这种空间影响。最后，根据研究结论，提出相应的政策建议。

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引用次数: 0