OR driven technology innovation for efficient decarbonized supply chains in a digital economy, part 2

Digital economy is a vital driving force for countries to promote economic recovery, rebuild competitive advantages and enhance governance capacity. Extensive research has been conducted in this field. In this paper, the text analysis tool of Bicomb2.04 and the knowledge graph visualization tool of CiteSpace are applied to analyze the digital economy research from 1992 to 2022, and a total of 7874 articles retrieved from the SSCI and SCI of the WOS core database are collected as the research data. The analysis provides a comprehensive overview of the research status of the digital economy, including the distribution of literature, research institutions and regions, research funds and publications, research authors, and cooperation networks. The core progress and frontier of international research are further analyzed according to the evolution of hot keywords, core system clustering, and the hot emergent words frontier. The results show that (1) the academic circle has a good overall research trend on the digital economy, which can be divided into three steadily rising research stages. The researchers take digital innovation as the core and extend it to the application of digital innovation, which has made groundbreaking theoretical contributions, but has not yet formed a team with field influence. (2) The evolution of hot keywords can be divided into four stages. Through hot clustering analysis, a basic theoretical system is constructed with digital technology and innovation as the core and digital governance, digital application, and digital path as the means. (3) The analysis of frontier areas also identified the digital platform economy, big data technology innovation, digital economy statistics, and the gig economy as potential research directions for the future. This study provides a guide for researchers to promote further research on the digital economy and is of great significance for promoting digital development level and constructing global digital ecosystem.

In the context of global warming and the clean energy transition, the rapid development of the digital economy, a highly technology-intensive economic form, has an important impact on the clean energy transition. Examining how the growth of the digital economy has affected the renewable energy transition has broad implications for the creation of national policies, business planning and design, and everyday human behavior. The paper uses a two-way fixed-effect model to empirically investigate the impact of the development of the digital economy on the clean energy transition based on Chinese municipal panel data from 2013 to 2022. It also sorts out the intrinsic mechanism of the digital economy affecting the clean energy transition from a theoretical level. Finally, it tests the indirect effects of technological innovation and upgrading industrial structure using endogeneity analysis and a robustness test. The study finds that (1) digital economy development effectively promotes clean energy transition; (2) the digital economy influences the transformation of renewable energy through two intermediary channels: technological innovation and upgrading of industrial structures; (3) there is geographical variation in how the digital economy affects the growth of the clean energy transformation. Lastly, policy recommendations are provided for boosting investment in digital infrastructure, strengthening the digital technology base, and deepening and broadening the interaction of the digital and real economies.

The widespread application of new-generation information technology, such as big data and artificial intelligence, has promoted the development of economic and technological transformation and the deep integration of digital and real economies. The digital economy is an essential force of China in the new era and it is promoting China’s economic development in a high-quality way. In this study, we theoretically describe the mechanism of the digital economy that affects total-factor energy efficiency and empirically analyze the impact of digital economy development on total-factor energy efficiency using data from 275 cities at the prefecture level and above in China from 2011 to 2019. We found that the digital economy has significantly improved total-factor energy efficiency. We used instrumental variable estimation and the replacement of explanatory variables to test the robustness of our results, finding that our conclusions were valid. Technological innovation, industrial structure optimization, and resource misallocation improvement are the channels through which the digital economy affects total-factor energy efficiency. Resource misallocation at the city level as the intermediary variable was this paper’s research gap. Further research showed that the improvement effect of the total-factor energy efficiency in eastern regions and megacities was more evident under the influence of the digital economy. All regions in China should combine their resource endowments to further release the dividends of the digital economy, enabling it to best promote total-factor energy efficiency. The relevant departments of the government should also stimulate market demand and promote the deep integration and balanced development of the digital economy and energy industry in low-energy-efficiency cities.

Against the backdrop of the United Nations Sustainable Development Goals (SDGs), innovation-driven development serves as the core engine of long-term sustainable economic development, while resource misallocation has emerged as a critical bottleneck constraining sustainable innovation and coordinated regional development. Grounded in the neoclassical theory of factor allocation, this paper incorporates capital misallocation, labor misallocation and the digital economy into a unified analytical framework. Using China’s provincial panel data spanning 2001 to 2024, we systematically investigate the impact effects, underlying transmission mechanisms and regional heterogeneity of resource misallocation and the digital economy on scientific and technological innovation through benchmark regression, robustness tests and heterogeneity analysis. The results show that resource misallocation exerts a significant and robust inhibitory effect on technological innovation, with the inhibitory effect of capital misallocation being more pronounced than that of labor misallocation. The digital economy has a significant positive driving effect on technological innovation, and it can also indirectly boost technological innovation by alleviating resource misallocation, with its mitigating effect on resource misallocation presenting obvious structural differences and a stronger correction effect on capital misallocation than on labor misallocation. Economic growth and technological innovation form a mutually reinforcing “growth-innovation” virtuous cycle. In addition, the innovation effects of both resource misallocation and the digital economy exhibit significant regional heterogeneity, where the digital economy’s innovation-driven effect and misallocation-mitigating effect are notably stronger in eastern China than in the central and western regions. The theoretical contribution of this paper lies in constructing a transmission mechanism framework of “digital economy to resource misallocation to technological innovation”, which enriches the connotations of factor allocation and innovation theories. Its practical value is to provide policymakers with differentiated development paths for the digital economy and optimization strategies for factor allocation, thus facilitating the effective implementation of the innovation-driven development strategy.

Currently, China's manufacturing industry development status shows a certain gap compared to the world's leading developed countries, and the industrial structure require s further improvement and development. Therefore, China must prioritize industrial innovation, accelerate the integration of industrial technology, and achieve transformation and upgrading of industrial structure. Simultaneously, China's digital economy is undergoing rapid development, with its impact on the economy and society gradually increasing. The digital economy has become a crucial cornerstone for China to achieve high-quality economic development and industrial modernization. Hence, China should focus on developing the digital economy, enhancing digital infrastructure, and accelerating the integration of manufacturing and digital economy. This study examines the relationship between the development of China's digital economy and the transformation and upgrading of manufacturing industry structure using panel data from 2013 to 2020. Both theoretical analysis and empirical tests are conducted to explore the following aspects: (1) The fundamental relationship between the digital economy and the upgrading of manufacturing industry structure is investigated by reviewing relevant literature and research. (2) The hypothesis that the digital economy can promote the upgrading of industrial structure by facilitating technological innovation is proposed. (3) A two-way fixed-effect model is utilized to test the impact of the digital economy on industrial structure upgrading. (4) The regional heterogeneity of the impact of the digital economy on the upgrading of manufacturing industry structure is examined in the eastern, central, and western regions, as well as the heterogeneous impact of the two from different levels of digital economy development.

The digital economy refers to the economic system built on the basis of digital computing technology, including e-commerce, digital payment, cloud computing services, etc. With the fast development of the network and communication technology, the digital economy dominates the global economic development, which is of great significance for improving economic efficiency, promoting innovation and employment. The research questions in this paper focus on how Alibaba can achieve a leading position in the digital economy through technological innovation and business model innovation. This paper uses case studies and data analysis to comprehensively analyze Alibaba's innovation strategies and practices in the field of digital economy. The study found that Alibaba has successfully promoted the innovation and development of the digital economy by building a strong technology platform, expanding the market, and adjusting its marketing strategy. The conclusion points out that Alibaba's digital innovation has not only enhanced the competitiveness of enterprises, but also set an example for the development of the global digital economy. In addition, this study provides other companies with strategies and methods on how to innovate effectively in the digital economy, especially in the context of rapid changes in technology and markets.

With the continuous advancement of industrialization, global environmental problems are becoming increasingly severe. Maintaining economic growth while improving the environment has been an important issue for many countries, especially developing countries. As industry is a major source of environmental pollution, industrial green transformation and upgrading have become particularly important. In the era of the digital economy (DE), there is a new path for industrial green transformation and upgrading. Based on provincial data on industry from 2008 to 2021, a difference-in-differences (DID) model was constructed to analyze the environmental and economic benefits. New pathways for trade-offs between environmental improvement and economic growth in China are presented. In addition, new ideas are concerning global environmental issues and economic issues in the DE are presented. The present study indicates that the DE has reduced the intensity of pollution emissions and elevated total factor productivity (TFP), which has helped to promote industrial green transformation and upgrading. Further mechanism testing showed that the DE has promoted industrial green transformation and upgrading by improving the utilization of energy and resources and promoting technological innovation. Considering the utilization of energy and resources, the DE has decreased China’s total industrial consumption of energy and coal, reduced industrial water consumption, and reduced the share of coal consumption and increased the share of clean energy consumption in China’s total industrial energy consumption; these effects have optimized the efficiency and structure of China’s energy utilization to contribute to the green transformation and upgrading of industry. Regarding technological innovation, the development of the DE has increased industrial innovation output and R&D input. Furthermore, it has promoted innovation with respect to green processes, accelerating technological innovation, and realized industrial green transformation and upgrading.

Digital economy, data resources and enterprise green technology innovation: Evidence from A-listed Chinese Firms

The impact of green technology innovation and the digital economy on the sustainability of the green economy is increasing. To delve deeper into this subject, this paper utilizes fixed- effect models and threshold effect models. It examines data from 34 provincial administrative regions of China. The aim is to uncover the patterns of influence the green technology innovation and the digital economy have on the sustainability of the green economy. The research findings are as follows: (1) The green technology innovation, digital economy, and their interaction contribute to promoting the high-quality sustainability of the green economy. The sustainability of the green economy relies on the support of green technology innovation and the digital economy. By optimizing the capabilities of green technology innovation and the level of digital economy, managers could enhance the high-quality sustainability of the green economy. (2) The digital economy exhibits a dual threshold effect in driving the sustainability of the green economy through green technology innovation. When the digital economy surpasses the first threshold, the influence of green technology innovation on the green economy experiences a notable increase. However, once the digital economy surpasses the second threshold, the impact of green technology innovation on the green economy begins to diminish significantly. (3) There are notable regional variations in the impact of green technology innovation and digital economy on the sustainability of the green economy across different regions of China. Considering these findings, it is vital for stakeholders in China to implement customized measures. These measures should aim to actively promote the sustainability of China’s green economy. The relevant stakeholders include businesses and the government.

Digital economy and its spatial effect on green productivity gains in manufacturing: Evidence from China

Mechanism and spatial spillover effect of the digital economy on urban carbon Productivity: Evidence from 271 prefecture-level cities in China.

This study explores the effect of the digital economy driving the development of the health industry and the mechanism behind it. Based on the panel data of 27 Chinese provinces from 2014–2021, this paper uses the entropy weight method to construct a comprehensive indicator evaluation system for the health industry, digital economy, and technological innovation. The two-way fixed effects model and panel threshold model are used to explore the impact of the digital economy on the health industry, and the intermediary effects model is used to analyze the mechanism role of technological innovation in the impact of the digital economy on the health industry. The results show that the digital economy can drive the development of the health industry. The driving effect shows obvious regional heterogeneity, with the strongest in the west, the second strongest in the central part, and the weakest in the east. This driving effect also has non-linear characteristics. Improving technological innovation is an important mechanism for the development of the health industry driven by the digital economy. This study promotes the exploration of the construction path of “Healthy China”, and reflects the importance of implementing dynamic and differentiated digital economy strategies and increasing the R&D of core technologies to drive the development of the health industry.

In the wake of rapid digitalization, the landscape of commerce has undergone a profound transformation, presenting unprecedented challenges to traditional tax systems and legal frameworks. This abstract examines the evolving dynamics of tax compliance within the digital economy through the lens of finance. The digital economy encompasses a broad spectrum of economic activities facilitated by digital technologies, including e-commerce, digital platforms, and virtual currencies. These innovations have blurred the boundaries of traditional tax jurisdictions, leading to complexities in determining tax liabilities and enforcement mechanisms. As such, the adequacy of existing legal frameworks in addressing tax challenges posed by the digital economy has come under scrutiny. From a finance perspective, ensuring tax compliance in the digital economy involves understanding the intricate interplay between technology, business models, and regulatory frameworks. Digital businesses often operate across multiple jurisdictions, exploiting loopholes and jurisdictional discrepancies to minimize tax obligations. Such practices have raised concerns regarding tax fairness and the erosion of tax bases, prompting policymakers to explore new regulatory approaches. One key aspect of addressing tax compliance in the digital economy is the development of international cooperation and coordination mechanisms. Given the transnational nature of digital transactions, effective tax enforcement requires collaboration among countries to combat tax evasion and profit shifting. Initiatives such as the Base Erosion and Profit Shifting (BEPS) project by the OECD seek to establish common standards and guidelines for taxing digital businesses. Moreover, the emergence of innovative technologies, such as blockchain and artificial intelligence, presents both opportunities and challenges for tax authorities. While these technologies offer potential solutions for enhancing tax administration and enforcement, they also introduce new complexities, such as the anonymity of transactions and the difficulty of tracking digital assets. Navigating the complexities of tax compliance in the digital economy requires a multifaceted approach that integrates legal, technological, and financial perspectives. By fostering international cooperation, leveraging technological innovations, and adapting regulatory frameworks, policymakers can mitigate tax challenges and promote a fair and sustainable tax system in the digital age.
 Keywords: Tax, Digital Economy, Finance, Legal, Review.

In the world of digital commerce, Artificial intelligence (AI) is starting to shift the game and transform how organizations run. AI benefits firms and consumers both in retail and digital commerce. This review provides a comprehensive analysis of the critical role AI plays in fostering value creation in the digital commerce industry, with a particular emphasis on the ways in which task and information complexity affect the application of AI technologies. The review then looks at AI possibilities in digital commerce from a variety of angles, such as supply chain efficiency, cost savings, product recommendation, enhanced customer experience and marketing plans. The aim of this review is to exploring how AI applications create value in e-commerce. The approach that was employed described the search technique for locating pertinent academic sources and was based on a survey of the literature on recent 15 studies about the effect of AI for Value Creation in Digital Commerce. Finally, the findings demonstrate that utilizing AI as an advanced instrument in the digital commerce sector appears to be a positive move since it applying AI may foster creativity, improve decision-making, and enhance overall marketing performance.

Community building and community development, i.e., community management are a key success factor in the digital economy. They differentiate business models in the digital economy from traditional ones. These communities may be constituted as Internet shops, portal sites, groupware systems, electronic auctions, billboards, enterprises or organizations. Product-centered communities as well as communities of interest are relevant for electronic marketing, as for example the reader communities at Amazon.com, The Well, or Dreamworks. Another example are communities that form value chains, such as single product manufacturing consortia or flexible consumer-driven organization of global supply chains. Further examples are topic and technology oriented communities such as Open-EDI trading communities, Open Trading on the Internet (OTP), or EDI/XML, in addition to the community-oriented programming of Linux. Communities of practice or learning communities are pivotal for knowledge management.As the mentioned examples show, online communities differ in their orientation. The features that all types of communities share are common interests, practices, languages and ontologies with common semantics as well as normative issues. The platform plays a special role for those communities. Thus, the relation, interplay or symbiosis between communities and platforms is of particular interest.This minitrack comprises a series of papers that address communities, their platforms and community-related business models as critical success factors in the digital economy. It covers a variety of novel concepts, models and platforms for communities. This minitrack deals with: Community-related business models, best practices and lessons learned. Case studies and topologies of Online Communities. Conceptual frameworks, formal and semi-formal models of communities, the behavior of agents and the platforms. Design principles for interaction and community platforms: Coordination, trust, normative values, design patterns and methods, implementations, architectures and components.The first session of this minitrack comprises three papers on communities in general. Katarina Stanoevska and Beat F. Schmid present a typology of communities and community supporting platforms. Yao Hua Tan and Cristiano Castelfranchi discuss with trust and deception two of the most crucial issues in Electronic Commerce. The third paper of the first session, written by Bernd Simon, Susanne Guth and Gustaf Neumann presents a general framework for Learning Media.The second session comprises three case studies of communities in the digital economy. Dorine Andrews and Jennifer Preece present an analysis of communities that are resistant to Online Interaction. The second paper by Alexander Hars and Shaosong Ou is an empirical study on the motivation for participation in communities arising around open source projects. Ulrike Lechner and Beat Schmid analyze in a series of case studies the relation of business models and system architectures in communities.The third session presents two papers that deal with application specific issues in communities. Steven O. Kimbrough, D.J. Wu and Fang Zhong present a simulation framework for software agents in supply chain management. The second paper of this section authored by Sue Newell and Jacky Swan deals with communities in innovation and knowledge management.The paper of Dorine Andrews and Jennifer Preece entitled ?A Conceptual Framework for Communities Resistant to Online Interaction? was nominated for the best paper award of this minitrack.