Search Results (92)

In the era of the digital economy, enhancing enterprise resilience has become a strategic imperative for sustainable manufacturing development. However, the micro-level mechanisms through which data element policies, specifically China’s National Big Data Comprehensive Pilot Zone, empower enterprise resilience remain insufficiently explored. To address this gap, this study leverages the policy rollout as a quasi-natural experiment and employs a multi-period difference-in-differences approach to analyze panel data of listed manufacturing firms. The results reveal that enterprises within pilot zones exhibit a 2.3% average increase in resilience compared to non-pilot counterparts. This effect is significantly amplified by enterprise digital transformation and regional innovation-entrepreneurship vitality. Mechanism analysis further identifies that the policy enhances resilience primarily by reducing supply chain coordination costs and improving relationship stability, with additional positive spillovers observed in adjacent cities. These findings highlight the disruptive potential of big data in reshaping corporate resilience paradigms and provide empirical support for scaling data-driven industrial policies to foster high-quality economic development. Full article

In the context of the growing urgency of sustainable industrial transformation under global climate goals, this study examines how digitalization enables and amplifies industrial low-carbon transition through the synergistic interaction of policy tools, technological pathways, and financial innovation. Addressing the challenge of reconciling emissions reduction with industrial efficiency, the study employs a mixed-method approach that combines panel econometric analysis of manufacturing enterprises in China’s Yangtze River Delta with representative case studies. The empirical results demonstrate significant synergistic effects among policy, technology, and finance under digital enablement. Coordinated policy instruments, including emissions trading and green credit, reduce decarbonization costs by 18–23%, while digitally enabled mechanisms such as Zhejiang’s “Carbon Efficiency Code” lower carbon intensity by over 15% for nearly half of participating firms. Technological pathways exhibit sectoral heterogeneity: digital twin optimization reduces emissions by 12% in the steel industry, whereas IoT-based monitoring cuts energy consumption by 9.7% in textiles. Financial innovations further reinforce these outcomes by increasing green R&D intensity and enhancing firms’ climate risk resilience. From a sustainability perspective, the study shows that digitalization strengthens real-time carbon measurement, monitoring, and verification (MRV), thereby improving sustainability performance assessment and governance effectiveness. By integrating digital tools with policy and financial incentives, the findings provide actionable guidance for supporting sustainable industrial operations and designing more precise, scalable, and data-driven sustainability-oriented policy instruments. Full article

Small- and medium-sized enterprises (SMEs) are central to sustainable development in transition economies, yet their financial fragility often limits resilience and the capacity to invest in innovation and responsible practices. Despite growing interest in SME, financial health and its role in sustainability, empirical evidence from small transition economies like Montenegro remains scarce, particularly on how liquidity and profitability dynamics underpin conditions for SDG-aligned growth. This study addresses this gap by analyzing how core financial indicators—cash position, capital structure, and working capital efficiency—affect liquidity and profitability among 345 Montenegrin SMEs across manufacturing, services, and trade. Using OLS and robust regression models, results reveal that a higher cash-to-revenue ratio and moderate leverage significantly enhance both short-term solvency and profitability, while working capital efficiency shows nuanced effects and sector-specific patterns emerge in capital-intensive industries. These findings highlight financial management as a foundation for SME resilience, creating financial preconditions for innovation and digital investments in aligned with SDGs (goals 8, 9, 12). Policy recommendations focus on improving finance access and financial literacy to foster innovation-driven, sustainable SME models aligned with the 2030 Agenda. Full article

As the supply chain of the electric vehicle (EV) industry becomes increasingly complex and vulnerable, traditional supplier evaluation methods reveal inherent limitations. These approaches primarily emphasize static performance while neglecting dynamic future risks. To address this issue, this study proposes a comprehensive supplier evaluation model that integrates a hybrid Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) framework with the Extreme Gradient Boosting (XGBoost) algorithm, contextualized for the EV sector. The hybrid AHP-TOPSIS framework is first applied to rank suppliers based on multidimensional performance criteria, including quality, delivery capability, supply stability and scale. Subsequently, the XGBoost algorithm uses historical monthly data to capture nonlinear relationships and predict future supplier risk probabilities. Finally, a risk-adjusted framework combines these two components to construct a dynamic dual-dimensional performance–risk evaluation system. A case study using real data from an automobile manufacturer demonstrates that the hybrid AHP–TOPSIS model effectively distinguishes suppliers’ historical performance, while the XGBoost model achieves high predictive accuracy under five-fold cross-validation, with an AUC of 0.851 and an F1 score of 0.928. After risk adjustment, several suppliers exhibiting high performance but elevated risk experienced significant declines in their overall rankings, thereby validating the robustness and practicality of the integrated model. This study provides a feasible theoretical framework and empirical evidence for EV enterprises to develop supplier decision-making systems that balance performance and risk, offering valuable insights for enhancing supply chain resilience and intelligence. Full article

(1) Background. The rapid development of the digital economy provides a new perspective for enhancing industrial chain resilience. This study examines how manufacturing firms’ digitalization affects their industrial chain resilience, drawing on resource dependence and dynamic capability theories, and explores spillover effects on upstream and downstream enterprises. (2) Data and Methods. Using panel data from Chinese listed manufacturing firms (2011–2023), we employ ordinary least squares (OLS) models to analyze the relationship, its mechanisms, and heterogeneity. We further match firms with their suppliers and customers to identify spillover effects. (3) Results. Digitalization significantly improves resilience, particularly by enhancing supply–demand matching and competitive capabilities. Effects are stronger for small, labor-intensive, and high-environment, social and governance (ESG) firms. Bargaining power and governance capability are key channels. Spillover effects are heterogeneous, with a stronger impact on downstream customers. (4) Discussion. The positive impact of digitalization varies by firm characteristics, and spillovers differ across the chain. These findings offer precise insights and policy implications for leveraging digitalization to strengthen industrial chain resilience. Full article

In recent years, global supply chains have become increasingly vulnerable to geopolitical tensions, pandemics, and energy crises, particularly in resource-constrained regions characterized by weak infrastructure and high transaction costs. Using panel data on A-share listed firms in China’s central and western regions from 2010 to 2022, this study examines the effect of firm-level digital transformation on supply chain resilience. We construct a digital transformation index and employ an instrumental-variable approach based on the interaction between terrain ruggedness and lagged digital transformation to address endogeneity concerns. Empirical results show that the digital transformation of enterprises has significantly enhanced the resistance and recovery capabilities of the supply chain, verifying its effectiveness in resource-constrained environments. Mechanism analyses reveal that this effect operates through increased supply chain diversification—especially customer diversification—and improved supply–demand matching enabled by more accurate demand forecasting and inventory management. Heterogeneity tests indicate that the resilience-enhancing effects are more pronounced among non-state-owned firms, manufacturing enterprises, and firms in less technology-intensive industries. Overall, our findings provide empirical support for transaction cost economics, dynamic capability theory, and the resource-based view, highlighting the strategic role of digital investment in strengthening supply chain resilience in infrastructure-constrained settings and contributing to the aims of Sustainable Development Goal 9. Full article

Against the backdrop of China’s economic transformation and the transition towards sustainable industrial systems, optimizing ownership structures to enhance the resilience and bargaining power of manufacturing suppliers has become crucial for building sustainable supply chains. This study empirically examines the impact of ownership concentration on supplier bargaining power using data from manufacturing companies listed on the Shanghai and Shenzhen A-share markets from 2008 to 2022, integrating insights from principal-agent theory and industrial dynamics within a sustainability-oriented framework. The findings reveal: (1) Ownership concentration significantly strengthens the bargaining power of supplier enterprises, contributing to more stable and equitable supply chain relationships. (2) R&D investment plays a partial mediating role between ownership concentration and supplier bargaining power, suggesting that innovation efforts—often aligned with green and sustainable technologies—can reshape dependency dynamics. (3) Industry competitiveness negatively moderates the relationship between ownership concentration and supplier bargaining power, indicating that intense competition may undermine the governance advantages of concentrated ownership in sustainable value creation. (4) Heterogeneity analysis shows that the positive effect of ownership concentration is more pronounced in central and western regions, state-owned enterprises, and large firms, highlighting contextual factors in achieving sustainable supply chain governance. Full article

Whether the New Energy Vehicle Promotion Policy (NEVPP) enhances supply chain resilience is pivotal to China’s green transition and global industrial security. Using data on A-share listed automobile manufacturers from 2012 to 2024, this study employs a multi-period difference-in-differences approach to identify the policy’s impact. Results show that NEVPP significantly strengthens supply chain resilience, and the findings remain robust across alternative specifications. Mechanism analysis reveals that the policy raises managerial attention, eases financing constraints, and stimulates technological innovation, thereby enhancing resilience through managerial, financial, and technological channels. Heterogeneity analysis by ownership, geography, R&D intensity, analyst coverage, and institutional ownership shows that the effect is stronger for state-owned enterprises, firms in central and western regions, low-R&D firms, those without analyst coverage, those with high analyst attention, and firms with low institutional ownership. This study provides firm-level evidence on the economic consequences of NEVPP, advances understanding of industrial policy and corporate resilience, and offers policy implications for supporting the global energy transition and safeguarding supply chain stability. Full article

This study examines the synergistic interaction between technology-driven digitalization and circular economy principles in enhancing sustainable supply chain performance among small and medium-sized enterprises (SMEs). Rather than examining digital technologies in isolation, we adopt an integrative systems perspective that conceptualizes digitalization as a multi-layered ecosystem comprising sensing (Internet of Things), intelligence (Artificial Intelligence and Big Data Analytics), verification (Blockchain), and coordination (Digital Collaboration Capability) layers. Through empirical analysis of 168 Tunisian SMEs across manufacturing and service sectors, this paper investigates the indirect impact of these complementary digital capabilities on sustainable supply chain performance, mediated by three dimensions of circular economy integration: waste reduction, resource efficiency, and sustainable design. The results indicate that digitalization has a positive influence on both environmental and economic performance, operating indirectly through the adoption of circular economy practices. By enhancing transparency, traceability, and operational efficiency, digital innovations reinforce circular economy practices, which consequently promote greater resilience and sustainability in supply chains. Sub-dimensional analyses reveal technology-specific mechanisms: IoT most strongly enables resource efficiency, AI and BDA drive waste reduction, Blockchain facilitates sustainable design, and Digital Collaboration Capability exhibits balanced effects across all circular dimensions. These findings underscore the critical role of integrated technological ecosystems, rather than isolated technology adoptions, in advancing sustainable supply chain management, particularly in resource-constrained SME contexts. Full article

This study develops and validates the concept of Regulatory Cultural Stewardship (RCS) as a dynamic capability that enables small and medium-sized enterprises (SMEs) to achieve sustainable AI-enabled digital transformation (AIEDT) in a volatile emerging economy. RCS empowers SMEs to harmonize regulatory compliance with cultural legitimacy, a critical nexus for fostering sustainable business practices and long-term resilience (economic viability and social legitimacy), in line with the global sustainable objectives. Using survey data from 391 Pakistani SMEs and Partial Least Squares Structural Equation Modeling (PLS-SEM), we find that four key AIEDT drivers explain 65.1% of the variance in AI innovation, with Technological Infrastructure and Policy and Ecosystem Support as dominant enablers. AI innovation fully mediates the relationship between AIEDT drivers and sustainable business performance. RCS not only enhances SME performance directly but also strengthens the AI innovation–business performance linkage as a significant moderator. Sectoral analysis reveals that services benefit most from Socio-Cultural Readiness, while manufacturing and primary sectors depend more on policy infrastructure and RCS. Significantly, RCS is validated as a distinct construct, integrating compliance and cultural alignment, rather than a subset of existing factors like policy support or cultural readiness. The study emphasizes the importance of scalable AI infrastructure, workforce upskilling, and internal cultural adaptation, while urging policymakers to stabilize AI governance frameworks to ensure a sustainable and equitable digital transition. The findings advance theory by conceptualizing RCS as a meta-capability bridging institutional voids and socio-cultural dynamics and offer practical insights for policymakers and managers seeking to implement ethically aligned and sustainable AIEDT strategies in emerging markets. At a conceptual level, RCS is ethically grounded in global AI principles, including fairness, accountability, and transparency, ensuring that cultural alignment never overrides human-centered values. Full article

Enhancing the supply chain resilience of the information and communications manufacturing industry is closely related to the competitiveness of enterprises and the security of the national economy, and has attracted widespread attention from all sectors of society. This study develops a multidimensional synergistic resilience framework based on the Technology-Organization-Environment theory. Using panel data from 29 Chinese provinces over the 2011–2022 period, it empirically examines the impact of artificial intelligence technology on supply chain resilience in the information and communication technology manufacturing industry and investigates its underlying mechanisms. Research findings: Artificial intelligence significantly enhances supply chain resilience, and this conclusion holds after a series of endogeneity and robustness tests. Mechanism analysis reveals that artificial intelligence promotes the low-carbon transition by optimizing energy intensity and synergistically enhances resilience effects through technological innovation. Heterogeneity analysis shows that the impact of artificial intelligence on supply chain resilience is stronger in eastern China, significantly outperforming western China, but its effect in central China is not significant. Supply chain disruptions weaken the positive effects generated by artificial intelligence when they occur. The research provides a theoretical foundation and practical basis for improving the resilience of information and communications manufacturing supply chain networks, thereby contributing to the development of intelligent, resilient and sustainable supply chain networks. Full article

Economic development and its sustainability are influenced not only by material, human, financial, and intellectual factors, but also by psychological factors. In particular, the levels of business expectations, trust, and confidence significantly affect the resilience of the economy, especially in crucial sectors such as industry and, more specifically, industrial production. Based on political, economic, social, and legal stability, businesses are likely to assess their opportunities more optimistically and realistically. This, in turn, enables them to look confidently toward the future and provides a foundation for investing in further development. Conversely, a decline in business expectations and confidence can slow socio-economic development, potentially leading to recession or depression. The purpose of the article is to identify the association between business confidence (Impact of the Business Confidence Indicator, IBCI) and the level of industrial production (Industrial Production Index, IPI), as a crucial aspect of ensuring sustainable economic development. A correlation–regression analysis conducted using Ukraine as a case study—a country candidate for EU accession—and statistical data from the State Statistics Service of Ukraine (SSSU) for the period from 1 February 2022 to 1 September 2024 demonstrated that there is a stable, positive, and strong relationship between IBCI and IPI levels (r = 0.7; D = 0.49). The constructed linear correlation model indicates that, with other factors held constant, a one-percentage-point increase in positive business expectations may lead to a 2.23-point rise in the industrial production activity of enterprises in Ukraine’s manufacturing sector. Furthermore, approximately 49.0% of the variation in industrial production levels is likely explained by changes in business expectations. Verification of the constructed regression equation and assessment of its parameters indicate that it is statistically reliable and consistent with real economic processes. Specifically, the Fisher coefficient (F = 5.30) exceeds the critical (tabular) value (Ft = 2.04), with Se = 0.45 and C_95% = 1.96; the causality test based on the Granger methodology revealed the presence of a causal relationship, indicating that the IBCI influences the IPI. The obtained statistical results for the applied models and tests are as follows: MDF (p < 0.05), KPSS (p > 0.10), Durbin–Watson ≈ 2.0, Breusch–Godfrey (p = 0.32), White (p = 0.41), ARCH (p = 0.27), and SER (p = 0.36). The constructed correlation–regression equation also allowed forecasting based on trend line modeling—how IPI levels will change depending on business confidence. According to the forecast, the IPI in Ukraine at the beginning of 2030 is expected to increase by 63.48 percentage points compared to the beginning of 2024, reaching 153.6%. Full article

Contract manufacturing is a pivotal strategy for brand owners, yet small-to-medium enterprises (SMEs) in emerging economies struggle to evolve beyond transactional roles into sustainable strategic partners. This study addresses this gap by empirically validating and refining the Mahove–Matope Sustainable Contract Manufacturing Company Maturity Model (SCMC-MM), a novel framework designed to guide SMEs through a holistic transformation. Through a seven-month longitudinal case study grounded in design science research approach within a South African food manufacturing SME, the model was implemented and evaluated using structured assessments, in-depth interviews, and longitudinal operational data. The application catalysed a system-wide transformation, yielding significant results, including a 133% increase in revenue, ISO 22000 certification, and perfect delivery reliability. Furthermore, the study theoretically refines the framework by identifying and incorporating novel critical success factors for contract manufacturing companies, such as industrial clustering and transformational leadership. The results demonstrate that the SCMC-MM offers a practical, actionable, and scalable tool for building resilient supply chain partnerships. It provides a structured pathway for SMEs to achieve simultaneous gains in economic performance, social equity through enhanced workforce capability and ethical practices, and environmental stewardship via formalised safety, health, and environmental and risk management systems, thereby contributing directly to the United Nations Sustainable Development Goals (SDGs) 8 and 9 in emerging markets. Full article

Artificial intelligence (AI) is of enormous significance for enhancing the resilience of the manufacturing industry chain, providing opportunities and momentum. We examine the impact of AI on the resilience of the manufacturing industry chain using a sample of listed manufacturing companies from 2011 to 2023. The results indicate that AI significantly improves the resilience of the manufacturing industry chain. Heterogeneity analysis reveals that the promoting effect of AI on manufacturing industry chain resilience is more pronounced in growth-stage enterprises, large-scale enterprises, enterprises in eastern regions, regions with high marketization levels, and financially distressed enterprises. Furthermore, mechanism tests indicate that AI enhances the resilience of the manufacturing industry chain by promoting firms’ ESG performance, facilitating knowledge spillovers, and increasing stock price synchronicity. The findings provide empirical evidence for the mechanisms and pathways to enhance the resilience of the manufacturing industry chain, offering insights into how AI can empower the high-quality development of China’s economy. Full article

Against the backdrop of global sustainable development goals, the resilience of manufacturing enterprises has become a critical topic. It serves as an important benchmark for assessing ability to coordinate environmental responsibilities and economic benefits. It also plays a pivotal role in driving the green transformation of industries and sustainable social development. To examine the relationship between environmental, social, and governance (ESG) performance and corporate resilience, as well as their underlying mechanisms, this study develops a research model incorporating moderating and mediating effects. Using a sample of manufacturing listed companies in China’s Shanghai and Shenzhen A-share markets covering the period 2011–2023, the study systematically investigates the impact of ESG performance on corporate resilience. The results indicate that ESG performance significantly enhances corporate resilience, and this conclusion remains valid under various robustness tests. Further mechanism analysis reveals that ESG performance effectively promotes corporate resilience by improving resource allocation efficiency, with analyst attention exerting a positive moderating effect in this process. Heterogeneity analysis reveals that the promoting effect of ESG performance on corporate resilience is more significant in technology-intensive and labor-intensive industries, high environmental sensitivity industries, markets with intense competition, and firms with low resource slack. This study not only expands the theoretical explanatory framework in the fields of corporate sustainable development and organizational resilience but also provides policy and management implications for manufacturing firms to achieve green transformation and sustainable competitiveness through ESG practices in an uncertain environment. Full article