Search Results (3,656)

This study synthesises evidence on whether, why, and under what conditions digital technologies improve resource efficiency across multi-tier global value chains (GVCs) and examines the theoretical adequacy of dominant explanatory lenses. Following the PRISMA 2020 protocol, we searched Web of Science, Scopus, IEEE Xplore, and ProQuest, retaining 150 articles for qualitative synthesis and 137 for bibliometric science-mapping; themes were developed via multi-cycle coding and triangulated with co-citation and keyword co-occurrence networks. Reported efficiency gains are strongest when firms deploy integrated digital stacks combining IoT sensing, AI analytics, blockchain traceability, and digital twins that jointly enable visibility, verification, and simulation-based optimisation, a pattern based predominantly on observational and cross-sectional evidence. Outcomes are contingent on cross-firm capability complementarities, data-governance arrangements, regulatory congruence, and cyber-risk maturity. A key structural finding is the digital-regionalisation paradox: stringent data-compliance demands can re-anchor sourcing within regulatory blocs, concentrating rather than extending GVC geography. Building on these findings, we propose three theoretical extensions, namely ecosystemic capability bundling, digital-sustainability spillovers, and distributed eco-innovation, that advance Transaction Cost Economics, the Resource-Based View, Dynamic Capabilities, and GVC governance theories to better account for the sustainability and platform dimensions of contemporary digitalised value chains. Full article

Against the backdrop of geopolitical restructuring and rapid digital transformation, foreign investment security reviews in host countries have become an increasingly important institutional constraint on cross-border business activities. From a broader organizational perspective, such regulatory mechanisms shape the external environment in which emerging market multinational enterprises (EMNEs) make international investment decisions and conduct cross-border acquisitions. This paper explores the moderating effects of EMNE network and internal agency problems on the duration of reverse cross-border M&A (CBMA) under host country security reviews. Utilizing a Negative Binomial regression model, we empirically analyze 503 reverse CBMAs undertaken by Chinese firms in developed economies from 2003 to 2022. The findings reveal that host country security reviews significantly prolong M&A duration. Notably, business group affiliation weakens this positive relationship, whereas political networking strengthens it. Regarding internal governance factors, Type I agency problems reinforce the delaying effect of foreign investment security reviews, while Type II agency problems weaken it. This study provides practical implications for managers and policymakers seeking to improve firms’ responses to increasingly complex regulatory environments. Full article

This study examines the impact of blockchain adoption and financial transparency on corporate performance in Jordan’s banking sector, with a focus on the mediating role of digital accounting systems. Targeting senior managers and financial analysts from Jordan’s banking sector, a sample of 152 participants is analyzed using a quantitative, cross-sectional research design. Data is evaluated through Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrate that blockchain adoption and financial transparency significantly improve corporate performance, both directly and indirectly, through the mediating effect of digital accounting systems. These findings underscore the importance of integrating blockchain and digital accounting systems to enhance financial transparency, reduce inefficiencies, and build stakeholder trust. This study addresses a critical gap in the literature by exploring the mediating role of digital accounting systems in the relationship between blockchain adoption, financial transparency, and corporate performance, particularly in developing economies. This research offers valuable insights for managers, policymakers, and regulators, emphasizing the strategic value of blockchain and digital accounting systems in driving corporate performance. Its originality lies in combining the Technology–Organization–Environment (TOE) framework and Institutional Theory to provide a comprehensive understanding of these dynamics in Jordan’s banking sector. Full article

As an emerging technology-intensive industry, the low-altitude economy (hereafter LAE) has attracted growing attention for its potential contribution to sustainable development. However, little is known about whether its expansion can simultaneously promote environmental improvement and economic growth. Using panel data from 30 Chinese provinces from 2012 to 2023, this study examines the relationship between the LAE and the synergistic development of carbon reduction, pollution mitigation, green transition, and economic growth (hereafter CPGE). Green technological innovation (hereafter GT) is incorporated as a mediating variable, while artificial intelligence (hereafter AI) is introduced as both a moderating and a threshold variable to explore the underlying mechanisms and nonlinear effects. The results show that the LAE is significantly and positively associated with CPGE. GT exhibits a significant negative mediating effect, suggesting that the benefits of green innovation may not yet have been fully translated into coordinated green development outcomes during the sample period. AI not only strengthens the positive association between the LAE and CPGE but also exhibits a significant threshold effect. The contribution of the LAE becomes substantially stronger once AI development surpasses a critical level, highlighting the important role of digital intelligence in amplifying the environmental benefits of emerging industries. In addition, the impact of the LAE displays pronounced regional heterogeneity, with stronger effects observed in non-resource-based and non-central regions. This study contributes to the literature by revealing that the environmental effects of the LAE depend not only on innovation channels but also on the level of digital intelligence development. AI serves as a critical enabling condition for translating the growth potential of the LAE into coordinated green development. By revealing the mediating role of GT and the moderating and threshold effects of AI, this study provides new evidence on how emerging industries contribute to sustainable development. The findings underscore the importance of aligning LAE development with AI-driven digital transformation to advance sustainable regional development. Full article

Data has become a strategic production factor, but the institutional logic underlying data’s tradability, priceability, and governability remains insufficiently theorized. In response, this study develops a coevolutionary framework that connects conventional factor market theory with digital political economy, platform theory, and comparative institutional analysis. This study adopts a conceptual–analytical research design, integrating three research methods: theory synthesis, comparative institutional analysis, and policy-process interpretation. Through theoretical synthesis, institutional comparison, and policy-process interpretation, it analyzes the conditions under which data circulation becomes feasible, lawful, and economically sustainable. In addition, by combining transaction data, exchange listings, property rights registrations, network indicators, and regional policy variations, it formulates testable propositions and an empirical agenda. The study finds that data factor markets do not emerge automatically with digitalization; their formation requires three mutually reinforcing conditions: technologically reducing search, verification, privacy protection, and contract enforcement costs; institutionally realizing a modular definition of rights and establishing compliance boundaries; and market demand from firms, public agencies, and research organizations generating use-case-specific value. Meanwhile, this study revises the three-stage model of market evolution as a contingent and testable pathway—from administrative pilot allocation, through hybrid state–market professionalization, to ecosystem-based cross-domain circulation. It also clarifies a closed-loop dynamic mechanism consisting of external shocks, internal strategic feedback, and adaptive governance, which jointly shapes market boundaries, pricing rules, and competition patterns. Full article

The transition to a circular economy (CE) in the automotive sector is increasingly critical amid rising resource pressures and climate imperatives. In India, this shift is influenced by regulatory initiatives, corporate sustainability goals, and life-cycle-wide environmental challenges. However, current studies remain fragmented, often neglecting the linkages between policy drivers, material issues, and firm-level responses. This study aims to evaluate how CE strategies are operationalized across the Indian automotive value chain using a Drivers–Materiality–Response (DMR) analytical framework. A multiple-case qualitative analysis was conducted involving six major automotive firms and associated ecosystem actors, with data sourced from corporate reports, national policies, and third-party assessments from 2018 to 2024. Semi-structured interviews with 11 industry experts were incorporated to strengthen triangulation, validate firm-level circular economy claims, and support the reliability of the DMR-based interpretation. Findings reveal strong alignment with national CE policies among leading firms, particularly Tata Motors and Mahindra, with comprehensive integration of electrification, battery reuse, zero-waste goals, and digital mobility solutions. However, challenges remain in end-of-life vehicle (ELV) formalization and circularity in downstream systems. The DMR model effectively bridges gaps in existing frameworks by offering a life-cycle-based lens that links Environmental, Social and Governance (ESG), Life Cycle Assessment (LCA), and policy–firm dynamics. The study contributes a scalable diagnostic tool for assessing CE maturity in emerging economies. While limited by reliance on secondary data, the triangulated approach enhances reliability and provides actionable insights for policymakers and industry leaders. Full article

The digital economy has become an emerging driver of rural industrial revitalization. Based on an input-output model and a production-network framework, this study first constructs time-series input-output tables for the digital economy and urban-rural industries from 2002 to 2021. It then identifies key recipient nodes, urban-rural disparity paths, and priority optimization paths of digital value flows. The results show that urban-rural disparities in digital empowerment have narrowed, but the digital divide between urban and rural industries remains substantial. The direct integration of the digital economy into rural industries is still limited, whereas urban-rural industrial integration plays an important mediating role. At the same time, the urban-rural disparity paths in digitally enabled rural industrial revitalization are mainly concentrated in rural capital allocation, asset services, circulation systems, basic agricultural production, and agricultural science and technology services. The counterfactual simulations show that prioritizing the direct embedding of the digital economy into rural manufacturing, agricultural value chains, and public-service sectors, while improving coordinated transmission between urban and rural industries, can strengthen the overall empowerment effect. These findings provide empirical support for more precise and targeted policies to promote rural industrial revitalization through the digital economy. Full article

Although the digital economy (DE) and sustainable urban systems have drawn growing attention, how DE drives urban energy transition (UET) remains insufficiently understood. Employing panel data from 266 Chinese cities spanning 2011–2021, this study applies fixed-effects, mediation, moderation, and spatial Durbin models to examine the impact of DE on UET. UET is measured by a composite index that captures energy system performance and transition readiness. The results show that DE is positively associated with UET, with a one-unit increase in DE corresponding to a 0.1566-unit increase in UET. This finding remains robust after employing an instrumental-variable approach and a battery of robustness checks, including an exogenous policy shock. This positive effect is partially mediated by reduced resource misallocation and industrial structure upgrading. When electricity intensity is treated as a moderating factor, cities with higher electricity intensity exhibit a more pronounced positive effect of DE on UET. Further evidence indicates that DE advances UET in the eastern, central, and western regions, but has a limited impact in the northeastern region. Additionally, DE exerts positive spillover effects, thereby advancing energy transition in neighboring cities. Full article

The security of new energy vehicle (NEV) industry chains has become a strategic issue for industrial competitiveness, the energy transition, and economic security. This study examines how digital economy capabilities jointly support NEV industry chain security across 30 provincial-level administrative regions in China. Drawing on Organizational Information Processing Theory and Dynamic Capability Theory, we conceptualize artificial intelligence capability (AIC), big data analytics capability (BDA), cloud computing infrastructure (CCI), and blockchain application level (BCL) as complementary information-processing and reconfiguration capabilities. We combine Necessary Condition Analysis (NCA), fuzzy-set Qualitative Comparative Analysis (fsQCA), and Random Forest/SHAP analysis. The revised results show that AIC is a practically necessary condition for supply chain resilience, BDA is a necessary condition for achieving a high cybersecurity level, and BCL is a dimension-specific necessary condition for data security. Four sufficient configurational paths—technology-driven, data-driven, infrastructure-driven, and security-synergistic—lead to high comprehensive NEV industry chain security. Robustness checks using alternative calibration anchors and consistency thresholds show that the core configurations are stable. A revised machine learning specification using only digital economy predictors confirms the high relative importance of AIC. It also shows that the marginal contribution of AIC tends to flatten beyond the upper-middle range. The findings provide a configurational and regionally differentiated perspective on digital economy empowerment while avoiding overgeneralization beyond the Chinese provincial context. Full article

Under the background of the steady advancement of the dual-carbon goal and the increasing improvement of the green financial system, green supply chain finance is like a bridge that closely links the capital of the financial market and the low-carbon transformation of the real economy. The following article chooses A-shares traded enterprises from 2014 to 2024 as the study sample, adopts multi-dimensional empirical methods to study the association in green supply chain finance along with corporate emission levels, and analyzes its transmission mechanisms and heterogeneity. The findings demonstrate that green supply chain finance has a substantial inhibitory impact with enterprise emission levels, a finding that remains robust across a series of tests, including parallel trend tests, placebo tests, and propensity score matching (PSM). Mechanism analysis demonstrates that green supply chain finance can indirectly reduce carbon emission intensity by improving both financing levels and supply chain stability. Looking at heterogeneity, we find that the emission-reducing effect tends to be stronger among state-owned firms, non-heavy polluters, enterprises with higher total factor productivity, and enterprises that are more financially oriented. Our theoretical value lies in clarifying the direct relationship between green supply chain finance and micro-enterprise carbon emissions, identifying two differentiated intermediary transmission paths, and defining the boundary conditions of the policy role across multiple dimensions, thereby better coordinating and promoting the digital and low-carbon transformation of enterprises. Full article

This research investigates how CE initiatives, interpreted as manifestations of corporate social responsibility, shape green value co-creation, green collaborative culture, and green supply chain integration across both supplier and customer contexts. The proposed conceptual framework also explores the possibility that digital maturity can moderate these interrelations, based on signaling theory. Empirical results, obtained through PLS SEM and NCA on a data sample of 493 suppliers and customers, confirm that CE practices have a significant positive impact on green value co-creation, which, in turn, influences the green collaborative behavior of the actors and the integration of the supply chain. The moderating role of digital maturity is reinforced in the linkages between green value co-creation, collaboration, and integration. Thereby, their effectiveness is strengthened. This study adds to the literature by proposing an integrative relationship between CE practices and outcomes within the supply chain dyad, offering a rare empirical study of relationships between suppliers and organizations in an emerging economy, and shedding light on the boundary condition of digital maturity within these relationships. The results have significant implications for managers seeking to maximize their sustainability performance through circular practices and digital capabilities. Full article

Ecuador’s agricultural sector plays a strategic role in the national economy; however, agricultural data remains fragmented across heterogeneous and isolated sources, limiting integrated analysis and evidence-based decision-making. This study proposes and implements a Big Data analytics framework based on the Medallion architecture and interactive dashboards to integrate, process, and visualize agricultural indicators from INEC, ESPAC, Ecuador Open Data, and FAOSTAT for the 2010–2024 period. The proposed framework adopts the Team Data Science Process (TDSP) methodology and structures workflows into Bronze, Silver, and Gold layers using Databricks for scalable data ingestion, transformation, and dimensional modeling. Interactive dashboards were developed in Tableau Public to support dynamic analysis of agricultural production, trade, producer prices, losses, and producer profiles. A comparative performance evaluation between Databricks Free Edition and Azure Databricks was conducted using SQL analytical workloads and dashboard interaction tests. Results showed that Azure Databricks reduced query execution times by up to 57%, especially in aggregation and join operations. Usability validation with 31 agricultural stakeholders reported high acceptance levels, including a 100% recommendation rate and a data trust score of 4.45/5. The findings demonstrate that scalable and low-cost Big Data technologies can effectively support agricultural digital transformation. Full article

Achieving balanced development across economic, social, environmental, and agricultural domains remains a critical challenge for emerging economies. This study conducts a comparative assessment of sustainable development in the agro-industrial complex of China, Russia, and India over the period 2000–2023 within an extended SDG-based framework. The methodological approach combines a multi-dimensional indicator system (37 indicators) with the Entropy Weight Method to identify indicators with high temporal information contribution and the Equal Weighting Method to evaluate long-term performance, ensuring both sensitivity to structural changes and cross-country comparability. The results reveal differentiated development trajectories: China demonstrates steady and balanced growth across all dimensions; India shows consistent improvement driven by progress in social and infrastructure-related indicators; Russia exhibits a more volatile pattern with relatively strong social outcomes but persistent weaknesses in agricultural performance. The entropy-based analysis indicates that the indicators contributing most strongly to temporal differentiation vary significantly across countries, with infrastructure and energy transition prevailing in China, natural resource dynamics in Russia, and social and digital factors in India. These findings suggest that long-term development trajectories in the agro-industrial sector are associated with different configurations of resource interdependence, institutional capacity, and resource-use efficiency. Full article

China’s urban low-carbon transition requires clearer city-level evidence on whether and how digitalization mitigates carbon emission intensity. Using panel data for 288 Chinese prefecture-level and above cities from 2013 to 2022, this study constructs a multidimensional Digital Economy Index and measures carbon emission intensity using EDGAR emissions and GDP at constant 2013 prices. We employ two-way fixed effects, instrumental variables, System GMM, robustness checks, mediation analysis, heterogeneity tests, and a Spatial Durbin Model. The results show that digital economy development significantly reduces urban carbon emission intensity, and this conclusion remains robust across alternative measurements, lag specifications, sample adjustments, fixed-effect structures, and endogeneity corrections. Mechanism analysis indicates that industrial structure rationalization and upgrading are key transmission channels, whereas technological innovation may generate short-term adjustment costs consistent with a “green paradox.” The carbon-reduction effect is stronger in old industrial base cities, cities with weaker initial innovation foundations, and cities with lower initial population density. Spatial analysis shows that digitalization generates significant carbon-reduction spillovers under geographical proximity, while economic-linkage-based spillovers are more complex. These findings provide theoretical and policy implications for digitally enabled and regionally coordinated urban decarbonization. Full article

Background and Purpose: Contemporary digital government initiatives in China face a well-documented real-world paradox: massive fiscal outlays on digital governance coexist with marked disequilibrium in regional innovation returns. Two structural mismatches define this paradox. First, local governments overwhelmingly prioritize high-visibility hardware investments such as data centers and large AI models, while neglecting deep-seated institutional reforms including cross-departmental business process reengineering and factor market liberalization. The pervasive phenomenon of “aggregated but non-interoperable data, and interoperable data left unused” reflects a severe asynchrony between rapid technological deployment and lagging institutional restructuring. Second, comparable digital investments yield vastly divergent innovation dividends across eastern, central, and western regions, with regional divergence entrenching into a rigid “higher in the east lower in the west, higher in the south lower in the north” pattern. Extant literature, largely confined to the lens of “instrumental rationality,” reduces digital government to an exogenous technological variable, leaving it unable to explain this core practical puzzle of “homogeneous inputs generating heterogeneous returns.” Moving beyond the narrow “technology-enabled governance” narrative, this study draws on the Digital-Era Governance (DEG) paradigm to investigate the actual impact of institutional restructuring on regional scientific and technological innovation capacity, aiming to provide empirical evidence to unlock the inefficiency lock-in prevalent in digital governance practices. Research Methods: This study uses 280 prefecture-level cities and above in China from 2018 to 2023 as the research sample and constructs a two-way fixed-effects model for benchmark regression analysis. To address endogeneity, the average level of digital government development in other cities within the same province is used as an instrumental variable, and the 2SLS method is employed to identify the causal effect. On this basis, a series of robustness checks are conducted, including excluding the special impact of the COVID-19 pandemic, substituting core variable measures, and decomposing the dimensions of the core explanatory variables, to ensure the reliability of the research conclusions. For mechanism identification, the Bootstrap sampling method is used to test the dual mediating effects of “digital industry agglomeration” and “resource misallocation alleviation”; furthermore, moderating effects and heterogeneity analysis models are introduced to reveal the boundary constraints of regional economic development levels and city types on the empowerment effect. Main Findings: Empirical results show that: (1) Digital government construction significantly improves regional scientific and technological innovation capacity, and this conclusion remains valid after endogeneity treatment and robustness checks. (2) Mechanism analysis demonstrates that digital government drives innovation through the dual paths of “promoting digital industry agglomeration” and “alleviating resource misallocation,” with the marginal contribution of alleviating resource misallocation being significantly higher than that of industrial agglomeration. This suggests that, in transitional economies, eliminating institutional frictions in factor mobility brings greater innovation dividends than simply building physical spatial clusters. (3) Moderating effects indicate that the higher the level of regional economic development, the stronger the innovation empowerment effect of digital government. (4) Heterogeneity analysis further reveals that the innovation dividends of digital government are significant only in non-resource-based cities, non-central cities, and large and medium-sized cities, while in resource-based cities, central cities, and small cities, the effects are systematically absorbed and not significant. Research Conclusions and Contributions: This study breaks through the ontological limitations of existing research that views digital government as a technological tool, grounding it within the DEG theoretical framework and confirming that digital government is an institutional force in the reconstruction of regional innovation ecosystems. The findings suggest to policymakers that digital government construction should promote a shift from a “technology-oriented” to an “institution-oriented” approach. The policy focus should shift from mere infrastructure expansion to the elimination of deep-seated institutional frictions, the improvement of factor allocation efficiency, and the advancement of gradients and the implementation of classified governance, all guided by regional economic foundations and heterogeneity characteristics. Full article