Search Results (141)

Cross-border equipment manufacturers in Shandong are under growing pressure to maintain supply chain continuity and long-term sustainability amid geopolitical uncertainty and industrial restructuring. Using quarterly data for 149 listed firms from 2001Q1 to 2024Q3, this study develops an interpretable early-warning model for firms’ relative vulnerability. Because firm-level disruption events are not consistently observable, vulnerability is proxied by return-on-assets underperformance relative to the industry median. We compare a multilayer perceptron (MLP) with logistic regression, decision tree, random forest, XGBoost, and LightGBM, and then use Shapley additive explanations (SHAP) to interpret the selected model. Under the study’s F1-oriented early-warning objective, the multilayer perceptron achieves the highest observed F1 score (the harmonic mean of precision and recall) in our evaluation setting, whereas XGBoost performs slightly better on threshold-independent ranking metrics. The interpretation results show that stronger profitability is associated with lower predicted vulnerability, policy-backed export demand with greater stability, and India-related geopolitical risk with higher predicted vulnerability. These findings suggest that interpretable early-warning tools may help support continuity-oriented operations, resilience investment, and sustainability-oriented industrial upgrading in export-dependent manufacturing regions. Full article

The aim of this study is to identify logistics supply chain criteria by considering the sustainability factor and to conduct a performance evaluation based on these criteria. The application analyzes 15 sub-criteria under the five main criteria of sustainable logistics: procurement logistics, production logistics, reverse logistics, distribution logistics, and disposal logistics. Accordingly, the importance weights of the logistics criteria were determined using the Fuzzy AHP (Analytic Hierarchy Process) method. Based on the determined criterion weights, an integrated model for performance evaluation was proposed using the Spherical Fuzzy MULTIMOORA (Multi-Objective Optimization by Ratio Analysis plus the Full Multiplicative Form) and Heuristic Fuzzy COPRAS (Complex Proportional Assessment) methods. The application ranked the sustainable logistics performance of three major logistics firms, and the results obtained from both methods were consistent. The findings highlight that the three criteria with the highest importance levels are, in order, as follows: green purchasing strategies (0.356), green design (0.151), and integration of supplier into environmental management processes (0.125). This demonstrates that firms aim to foster environmental responsibility not only in their internal processes but also throughout the supply chain. This study provides a reliable model for evaluating and improving sustainable logistics performance, contributing both to the academic literature and to practical applications in logistics firms. Full article

National competitiveness has become a central policy concern for resource-dependent economies pursuing structural transformation. Saudi Arabia’s Vision 2030 represents a comprehensive national strategy aimed at diversifying the economy, upgrading productivity, and strengthening institutional capacity. Despite extensive discussion of individual reforms, there remains a lack of integrated, theory-guided analysis that explains how these changes interact systemically at the national level. This study addresses this gap by applying Porter’s Diamond Model as a conceptual descriptive analytical framework to examine Saudi Arabia’s economic transformation. The analysis treats the Diamond determinants—factor conditions, demand conditions, related and supporting industries, and firm strategy, structure, and rivalry—as an interconnected system shaped by government intervention. Drawing on secondary data from official policy documents, international competitiveness indicators, (including the Global Innovation Index, IMD World Competitiveness Rankings, Logistics Performance Index, and Worldwide Governance Indicators), and institutional reports, the study maps key reform dynamics onto each determinant and examines their cross-determinant interactions and feedback loops. The findings suggest that Saudi Arabia has made substantial progress in upgrading factor conditions and generating sophisticated domestic demand, while systemic challenges remain in firm level rivalry and innovation ecosystem depth. The study highlights that sustainable national competitiveness depends on coordinated upgrading across all determinants rather than isolated reforms. By reframing Porter’s Diamond as a dynamic, systems-oriented analytical tool, this paper contributes to the literature on national competitiveness in transformation economies and provides policy relevant insights for advancing productivity driven growth under Vision 2030. Full article

Financial reporting irregularities and audit modifications represent important warning signals of elevated fraud and financial distress risk. While recent studies report high predictive accuracy in fraud detection, most approaches frame the problem as a purely algorithmic classification task and offer limited interpretability for auditors, regulators, and decision-makers. This study reframes financial statement analysis as a human-interpretable audit modification risk prediction problem. It integrates domain-informed feature engineering with machine learning models. Using firm-level financial data and audit disclosures, audit opinions are used as a proxy indicator of elevated fraud-related reporting risk rather than confirmed fraudulent behavior. Logistic Regression, Random Forest, and Gradient Boosting models are trained under class imbalance using cost-sensitive learning and evaluated with recall, ROC–AUC, precision, F1-score, and accuracy. The results demonstrate that humanized categorical representations preserve predictive performance while substantially enhancing interpretability. Permutation-based feature importance analysis further identifies financially intuitive risk patterns and threshold-like conditions associated with elevated audit modification risk. The findings suggest that interpretable, risk-oriented machine learning frameworks can support more transparent and actionable financial reporting risk monitoring systems. Beyond predictive performance, the study discusses human-centered challenges related to model interpretability, decision support, and the integration of machine-learning systems into real-world financial reporting and audit-risk assessment workflows. Full article

This study addresses the gap between predictive optimization and monitoring-oriented risk concentration by introducing a hierarchical Fuzzy Cognitive Map (FCM) framework for financial risk assessment. Financial distress prediction models are employed to estimate firm-level default probabilities and are required to comply with regulatory standards. IFRS 9 and Basel III/IV frameworks emphasize model explainability, scenario analysis and causal transparency, which are essential for compliance purposes. The methodology aggregates correlated financial ratios into financial concepts through unsupervised clustering. Concepts interact through a learned coupling matrix and a controlled multi-step propagation, which enables the amplification of risk signals. A small residual correction is applied at the final readout, preserving the interpretability of the proposed framework. The framework was applied to two severely imbalanced benchmark bankruptcy datasets. It achieved higher precision–recall performance than Logistic Regression (PR–AUC $\approx 0.32$ vs. $0.27$), improved calibration (Brier score $\approx 0.046$ vs. $0.089$) and maintained competitive Recall@Top–K under tight supervisory monitoring budgets. Hierarchical FCM achieved predictive performance comparable to nonlinear models while maintaining concept-level interpretability. Our findings demonstrate that structured concept aggregation combined with interaction-based propagation provides a transparent alternative to purely predictive black-box models in financial distress assessment and is aligned with regulatory frameworks. Full article

In response to escalating global volatility, organizations are prioritizing the adoption of Digital Industry 4.0 Technologies (DI4Ts) to improve efficiency and enhance decision-making capabilities. Refining Organizational Adaptation Theory (OAT), this research examines the factors influencing DI4Ts implementation success and their impact on organizational performance and resilience within Saudi Arabia’s food logistics firms. Using data from 191 managerial respondents processed through Partial Least Squares Structural Equation Modeling, the findings indicate that dynamic digital capability and effective digital leadership significantly promote the implementation of DI4Ts. Additionally, supply chain security and anti-counterfeiting strategies were shown to exert a stronger influence on operational outcomes and organizational resilience than technology adoption alone. In an institutional environment characterized by a high food import reliance and strict traceability mandates, government policies moderate the relationship between organizational digital adaptability and implementation success. Our research outcomes establish a comprehensive framework for the incorporation of DI4Ts where supply chain security functions as a foundational capability predicating digital effectiveness. Full article

Background: Amid global sustainability imperatives, the logistics sector serves as a key economic enabler while remaining a major contributor to greenhouse gas emissions. This study investigates the causal relationships between green logistics practices and sustainable business performance in Vietnamese small- and medium-sized enterprises, mediated by competitiveness, and forecasts future trends to inform transitions aligned with net-zero goals. Methods: A mixed-methods design integrates structural equation modeling with the gray model. Primary data were collected via Likert-scale questionnaires administered to 350 managers to measure latent variables. Secondary financial metrics (revenue, costs, assets, profits) from 15 firms spanning 2021–2024 enabled forecasting. Results: SEM, employing bootstrapping for path estimation, revealed positive direct effects, with the strongest effects for green transportation and weaker effects for technology, packaging, and warehousing. Mediation via competitiveness yielded mixed indirect effects: positive for warehousing and transportation, but negative for technology. GM(1,1) projected moderate performance growth under conditions of data uncertainty. Conclusions: The hybrid framework advances the resource-based view in emerging market contexts, recommending prioritization of transportation and technology initiatives alongside policy incentives to align with sustainable development goals and enhance resilience in Vietnam’s logistics sector. Full article

Concerns over the environmental footprint of logistics operations have increasingly shaped the adoption of sustainability-oriented practices within supply chains. This research develops and empirically tests a model linking green practices to environmental and financial performance in supply chains. Using variance-based structural equation modeling (SEM), the study tests six hypotheses addressing both the direct effects of green practices on supply chain performance and the mediating role of competitive advantage. Data were collected from a sample of 148 Romanian firms operating across multiple industries. The results indicate that green practices positively influence environmental outcomes and support the development of green competitive advantage, which in turn is associated with stronger financial results. Policy implications suggest that sustainability initiatives should strategically leverage green practices to build enduring competitive advantages in supply chains. Full article

This conceptual article examines the shift of circular business models from policy-driven sustainability initiatives to commercially viable strategies in fast-moving product categories, with particular attention to repair, refurbishment, remanufacturing, and end-of-life recovery. Drawing on a structured narrative review and theoretical synthesis, it argues that circular models seldom scale within a single firm because slowing and closing resource loops require ecosystems that integrate product design, reverse logistics, and secondary markets. The paper develops an analytical framework that combines ecosystem strategy, complex adaptive systems, and common agency theory to explain how distributed complementarities, feedback dynamics, and multi-principal incentives jointly shape ecosystem trajectories. Reinforcing and balancing loops can accelerate, stabilise, or lock ecosystems into low-value routines, while incomplete contracts and divergent metrics may fragment effort and produce measurement traps. To address these coordination externalities, the framework introduces the super-principal as a meta-governance role that aligns principals through shared performance indicators, pooled funding rules, and investments in enabling infrastructures such as traceability. The framework offers implications for circular economy policy and ecosystem strategy aimed at sustaining higher-value circular loops. Full article

This paper proposes a two-stage framework integrating Data Envelopment Analysis (DEA) and fuzzy multi-criteria decision-making methods to evaluate the performance of logistics firms in Vietnam. In the first stage, DEA models (CCR, BCC, and SBM) are employed to measure relative efficiency and identify benchmark firms among 15 leading logistics companies. In the second stage, FAHP–FTOPSIS is used to incorporate qualitative and sustainability-oriented criteria and to provide a comprehensive ranking of the efficient firms. The results indicate that a considerable proportion of firms operate below the efficiency frontier, implying substantial opportunities for resource optimization. Environmental and technological dimensions are found to be the most influential factors, while companies implementing green distribution strategies and strong data security practices consistently achieve higher rankings. Sensitivity analysis confirms the robustness and stability of the proposed framework. This study contributes by bridging operational efficiency assessment with broader strategic and sustainability considerations, overcoming the limitations of single-method evaluations used in prior research. The integrated DEA–FAHP–FTOPSIS approach offers managers a practical tool to diagnose weaknesses, prioritize improvement actions, and benchmark against top performers. In addition, it offers policymakers valuable insights to support digital transformation and green logistics initiatives in developing economy contexts. Full article

The growing prevalence of severe and unpredictable disruptions has prompted logistics firms to restructure their supply chain strategies to ensure long-term sustainability. Therefore, this study developed a research framework with factors including supply chain innovation, supply chain empowerment, risk management capability, supply chain collaboration, and supply chain disruption, and investigated supply chain robustness. Moreover, this study conceptualized supportive HR practices as a moderating factor between supply chain robustness and supply chain velocity, highlighting their role in supporting sustainable supply chain performance. The study design is grounded in a quantitative research approach. Sample size was estimated using a priori power analysis. A research survey was administered using a purposive sampling approach. Overall, 253 valid responses were retrieved during the months of April and May 2024. These numerical responses were further analyzed with a structural equation modeling approach. The structural assessment indicated that supply chain innovation, risk management capability, supply chain disruption, supply chain empowerment, and supply chain collaboration explained 77.7% of the variance in supply chain robustness. Practically, this study proposes that supply chain innovation, risk management capability, supply chain disruption, and supply chain empowerment are key factors that boost supply chain robustness, contribute to sustainable operational performance, and hence need managerial attention. Similarly, this study suggests that managers could achieve supply chain velocity through supportive HR practices, which must be considered while developing sustainable supply chain strategies. This research is unique as it develops an integrated research model to investigate factors that impact supply chain robustness and supply chain velocity from a sustainability-oriented perspective. Full article

Background: In the era of rapid technological advancement, digital transformation has emerged as a pivotal strategy for enhancing operational efficiency and competitiveness in logistics enterprises, particularly amid globalization and post pandemic recovery; this study aims to evaluate its multifaceted impact on business performance using a multi-criteria framework focused on Vietnamese firms. Methods: Employing structural equation modeling on primary survey data from 346 middle and senior level managers, alongside the Malmquist productivity index derived from data envelopment analysis on secondary financial indicators spanning 2020 to 2024, the research integrates latent variables such as organizational capability, technological innovation capability, institutional pressure, digital transformation, and business performance. Results: Key findings reveal a strong positive correlation between technological innovation capability and organizational capability (path coefficient 0.522), with organizational capability directly influencing business performance (0.359), while institutional pressure positively affects digital transformation (0.321) but negatively impacts business performance (−0.152); overall, digital transformation exhibits limited optimization, contributing to modest productivity gains and a potential 23% cost reduction through technologies like Internet of Things and artificial intelligence. Conclusions: These results underscore the necessity for logistics enterprises to strengthen organizational integration and training to maximize digital transformation benefits, thereby fostering sustainable competitiveness in global supply chains. Full article

This study examines whether environmental assurance and environmental management certifications are associated with subsequent environmental performance and reputational exposure in European Union listed firms. Using Refinitiv Eikon panel data for 441 firms (1773 firm-year observations) from 2017–2023, we analyze environmental pillar sub-scores (Emissions, Resource Use, and Innovation) and three intensity indicators (energy, pollution, and recycled waste intensity). We estimate firm fixed-effects models for performance outcomes and Firth’s logistic regression models for media-reported environmental controversies, using lagged assurance/certification indicators. Environmental assurance is consistently associated with higher environmental sub-scores and with lower energy and pollution intensity, alongside higher recycled waste intensity. In contrast, certification effects are weaker and more heterogeneous across intensity-based indicators. Regarding reputational exposure, assured firms show a higher likelihood of subsequent media-reported environmental controversies, which is consistent with heightened scrutiny and visibility rather than evidence of intent. These findings inform boards, assurance providers, investors, and policymakers seeking to strengthen the credibility and use of corporate environmental information. Full article

Environmental, Social, and Governance (ESG) factors have become central to international trade, transforming how firms, industries, and governments engage in global markets. This study conducts a systematic literature review to synthesize current knowledge on the ESG–trade nexus. Using content analysis, three key thematic clusters were identified: (i) ESG in supply chains and logistics, (ii) ESG in export performance and international competitiveness, and (iii) ESG and trade within geopolitics, energy, and resource security. The synthesis reveals that ESG has evolved from a voluntary corporate initiative into a structural determinant of global competitiveness, resilience, and legitimacy. Building on these findings, the study proposes an integrative ESG–Trade framework, which conceptualizes ESG as a multidimensional governance ecosystem comprising (i) institutional and regulatory, (ii) technological and operational, and (iii) geopolitical and strategic dimensions. This framework explains how sustainability regulations, digital transformation, and global political economy dynamics co-evolve to shape trade flows and industrial upgrading. The study highlights the need for greater regulatory coherence and strategic ESG integration while offering a foundation for future interdisciplinary and empirical research on sustainable trade governance. Full article

Based on survey data from 320 Azerbaijani enterprises operating across the organic product value chain—including producers, sellers, and key supporting firms such as logistics, financial, and ICT service providers—this study investigates how digital platform capability influences firms’ innovation and performance outcomes and their perceived high-quality economic development within an emerging digital economy context. Four constructs—Digital Platform Capability, Enterprise Digital Transformation, Innovation and Performance Outcomes, and Perceived High-Quality Economic Development—are measured using multi-item Likert scales. Confirmatory factor analysis and Structural Equation Modeling (SEM) are employed to test the proposed relationships. The results show that Digital Platform Capability exerts a strong positive effect on Innovation and Performance Outcomes (β = 0.574) and on Perceived High-Quality Economic Development (β = 0.512). In addition, Innovation and Performance Outcomes have a direct positive impact on Perceived High-Quality Economic Development (β = 0.313). Mediation analysis further indicates that Enterprise Digital Transformation partially mediates this relationship, transmitting approximately 52% of the total effect of Innovation and Performance Outcomes on Perceived High-Quality Economic Development. These findings underscore digital transformation as a key structural mechanism through which firm-level innovation and performance contribute to broader perceptions of high-quality economic development. The study provides novel empirical evidence from Azerbaijan and offers practical implications for digital policy design and enterprise strategies aimed at promoting innovation-driven, inclusive, and sustainable growth. Full article