Journal of Digital Economy最新文献

COVID-19 has brought unprecedented impacts on global logistics and left supply chain management on the verge of collapse, which highlights the research importance of supply chain resilience (SCRE). To provide more insights into SCRE in the pandemic context, this paper uses information processing theory (IPT) as a theoretical lens and attempt to explore how SCRE can be achieved through information processing ‘fit’, that is, the fit between information processing capability and its information processing capability. We conducted a single-case analysis by choosing Zong-Teng Group, one of the biggest cross-border e-commerce enterprises in China, as our sample. Data were mainly collected from interviews with Zong-Teng’s managers and open online resources. Through this single-case analysis, this paper identifies supply chain collaborative innovation as a new mechanism between information processing ‘fit’ and SCRE. Specifically, a firm’s information processing ‘fit’ can lead to three modes of innovative collaborations (i.e., technology, management and market innovation), which further improves SCRE. These findings provide some valuable implications for both researchers and practitioners in operations and supply chain management (OSCM) realms.

This study comprises a systematic literature review that offers a thorough analysis of the present state-of-the-art knowledge regarding the adoption and application of blockchain technology within the context of supply chain management. Based on an extensive review of 133 articles from highly-regarded journals, we developed a framework where we highlight the integration of the transition from blockchain technology adoption to its application. This transition process is explained by two theories: the Technology Acceptance Model and the Diffusion of Innovation Theory. In the adoption phase, we identified eight internal drivers and seven external drivers, together with comprehensive barriers. Our framework also integrates and examines the blockchain technology application stage, focusing not only on the current development of benefits of blockchain technology implementation but also on the challenges that impede the successful implementation of blockchain technology in supply chain management. The future development prospects are also highlighted which include standardization, platform development, regulation system development, cost reduction, and talent cultivation. These future developments were critical yet were missing in the current academic literature. By providing an in-depth analysis of these challenges, our study can assist supply chain practitioners in making informed decisions about blockchain-enabled supply chain management initiatives.

In recent years, our food supply chain facing various disruptions shows a need for higher resilience and sustainability. To better prepare for future uncertainties the food supply chain may encounter, it is imperative to understand the status quo of the food supply chain resilience literature, which focuses on deploying digital technology and integrating sustainability in supply chain management. Motivated by this, our study critically reviews the literature on food supply chain resilience against different types of disruptions, identifies research gaps, and provides a reference for the food supply chain to respond to uncertainties more effectively through digital technology and sustainability integration. To fulfil this objective, we perform a systematic literature review of academic journal articles from 2010 to 2020. Our study is novel in investigating different potential strategies to respond to various disruptions, emphasising the role of digital technologies and sustainability. The findings complement existing literature on supply chain resilience and serve as guides to supply chain practitioners facing disruptions. In addition, we investigate possible ways of adopting and optimising digital technologies to enhance food supply chain resilience and indicate areas where a sustainable future can be achieved through a more resilient food supply chain powered by digital innovations.

COVID-19 has been an exogenous shock for several businesses. Pandemic pushed firms to operate in an uncharted territory. Firms had to adapt quickly to survive in an unpredictable market and in conditions of uncertainty further fueled by political instability and environmental challenges. Based on a quantitative survey carried out during the pandemic period, the study aims at assessing how small and medium-sized enterprises (SMEs) responded to the challenges emerged during the COVID-19 outbreak, focusing on diversification and servitization strategies to outline potential new theoretical insights related to these strategies developed in turbulent times considering the function of digitalization in this respect. Through a cluster analysis the study identifies 4 groups of firms (unresponsive, defender, analyzer and prospector) that have shown different responses to the crisis related to diversification and servitization, highlighting the key role of digital technologies (both ICT and Industry 4.0) as well as of customers. The findings allowed to define theoretical and practical implications.

In the context of China's rapidly growing digital economy, exploring the potential to reduce carbon emissions from the perspective of enterprise digitization is of vital practical significance for achieving ambitious "carbon peak" and "carbon neutrality" goals. This paper uses data from A-share listed companies as a sample pool spanning the years 2014–2020 and finds that a nonlinear, inverted U-shaped relationship exists between enterprise digital transformation and carbon emissions. We further construct several robustness tests and show that the effect remains significant after accounting for the endogeneity issue using IV regressions. Heterogeneity analysis indicates that the effect of digital transformation on carbon emissions is influenced by the regional economic development level and the ownership structure of enterprises. Notably, in non-state-owned enterprises and economically advanced regions, the influence of digital transformation on carbon emissions becomes more pronounced. This paper provides explicit policy implications. It is suggested that enterprises accelerate their digital transformation by integrating smart device development into their production and operations and government should give support to digital transformation to facilitate industrial upgrading, and further promote China's pursuit of high-quality and sustainable economic development.

The arrival of “Internet Plus” and the 5G era has brought rapid digital transformation. Many scenic spots in China are conforming to trends of the times by embarking on this transformation and beginning to become smart scenic spots. Yet these sites continue to face challenges in the process of smart construction. Moreover, theoretical guidance on the smart construction of scenic spots is lacking. We adopted a questionnaire survey method to study smart construction at 5A and 4A scenic spots in China. Based on the results, we established a smart scenic spot evaluation system via the Delphi method and the analytic hierarchy process. Our proposed system included infrastructure construction, smart service, smart management, and smart marketing as primary indicators. With the help of a geographic information system, we also discovered that scenic spots' locations influence smart construction. Findings can inform countermeasures and evaluation standards for China's smart scenic spot construction, offering guidance for improving sites' smartness.

Digital technologies reshape the distribution of value added through global value chains (GVCs). Based on the GVC decomposition method, we calculate the digital technology-related value added implied in GVCs. We find that digital technology-related value added share in service industries is higher and growing more rapidly than overall industries. The share of digital technology-related value added of three trade paths in service industries is higher than its share in overall industries. In service industries, simple and complex value chains have a higher share of digital technology-related value added than traditional value chains. Digital technology-related value added in China's service industries grows faster than overall industries, and digital technology-related value added in China's service industries trade grows faster than in overall industries trade. The share of digital technology-related value added in trade is higher and grows faster than its in domestic demand. The share of digital technology-related value added in China's service industries is higher than that in overall industries. This paper offers new interpretations of digital GVCs.

With the rapid advancement of mobile internet, UGC video platforms have become integral to the daily lives of young generations. For content creators on these platforms, sharing videos sponsored by corporations is the primary method to monetize their work. This research delves into the impact of video content sponsorship and sponsorship disclosure on consumer engagement by analyzing nearly 30,000 videos on the Bilibili platform. The results indicate that video sponsorships have a significantly negative impact on consumer engagement. However, comprehensive disclosure of sponsorship beforehand can improve consumer engagement. Additionally, our study demonstrates that followers of top-tier content creators are more sensitive to video sponsorships. This paper presents a critical empirical investigation of the sponsorship issue within the context of UGC platforms, making valuable contributions to the theories of advertisements' externalities in two-sided markets and information asymmetry.

Through the application of discrete choice and machine learning models, the primary objective of this study is to assess the impact of NGA networks coverage on reducing the risk of contagion during the first wave of COVID-19 across 278 municipalities in mainland Portugal, while controlling for other domains under the tutelage of the local public administration. Benchmark estimations reveal that, while holding everything else constant, each spatial unit is 2.4 p.p. more likely to become a high-risk municipality with additional 10 ​000 cabled houses with NGA networks. In a multinomial discrete choice model setting, the technical novelty of this study lies in providing graphical visualization and economic interpretation of coefficients and average marginal effects as a function of the number of classes used to define the dependent variable, while ensuring the satisfaction of the IIA assumption. The positive and significant coefficients of NGA indicate that additional coverage of NGA networks increases the likelihood of municipalities becoming high-risk for increasing number of spatial units not belonging to the low-risk efficiency frontier. The significant, negative, and decreasing average marginal effects of NGA suggest that the ability to remain a low-risk municipality diminishes with increasing NGA networks coverage as the number of municipalities belonging to the low-risk efficiency frontier decreases. The analysis also confirms that the effect of NGA networks coverage on COVID-19 is statistically significant in the indirect channel. This impact persists due to the mediation of population density, which is directly influenced by NGA networks coverage. All these findings can be explained by the fact that benefits related to productive activities do not outweigh costs associated with leisure time. Hence, this research emphasizes the need for a normative discussion on the intended purpose of digital technologies built on top of NGA networks to ensure a level playing field in the post-pandemic era.

With the growth of the social economy and technology, innovation networks have emerged as one of the most significant methods for analyzing the evolution of industrial innovation. Yet, there is a shortage of studies analyzing the components that influence network creation. By highly integrating digital technology with the traditional medical industry chain, the smart medical industry has become one of the important sectors of the digital economy. With the advent of internet-based diagnosis and treatment technologies, innovation inside the smart medical industry has taken the form of a network. This study aims to construct an innovation network by organizing and analyzing patent data from China's smart medical industry cooperation, covering the period from 2005 to 2022. The data is sourced from the IncoPat database. The analysis utilizes the Exponential Random Graph Model (ERGM) approach to conduct regression analysis on various factors. These factors include endogenous structural characteristics, node feature variables such as node emergence time and institutional attributes, as well as the distance network and IPC attribute network. By examining the driving mechanism and influence mechanism that influence the innovation network, this study contributes to the smart medical industry research by gaining a better understanding of the current status of innovation network, which can be advantageous for businesses in this field to accurately recognize and actively promote their innovation practices.