This study aimed to investigate the influence of green supply chain management practices on the environmental performance of manufacturing firms, with a specific focus on understanding how institutional pressure moderated this relationship. The research design encompassed a holistic approach, incorporating an in-depth examination of the current literature and data collection via a well-structured questionnaire. Random sampling was utilized to gather data from manufacturing companies in Pakistan, and the data analysis employed PLS-SEM. The findings revealed a significant relationship between GSCM practices and the environmental performance of manufacturing firms. Moreover, the study identified that institutional pressure played a moderating role, influencing the strength of this relationship. Notably, the impact of GSCM practices on environmental performance varied under different levels of institutional pressure. This research underscored the importance of considering institutional pressure in understanding the link between GSCM practices and environmental performance. The implications extended to academics and practitioners, providing insights into the nuanced dynamics of sustainable practices in manufacturing settings. Practical implications involved tailoring GSCM strategies based on varying degrees of institutional pressure for optimal environmental outcomes. The original contribution of this study lies in its comprehensive exploration of the interplay between GSCM practices, institutional pressure, and environmental performance. By incorporating institutional pressure as a moderator, the research provided a nuanced understanding of how external influences shaped the effectiveness of GSCM in fostering ecological sustainability within manufacturing firms.

Supply chain resilience (SRES) is essential for firms aiming to alleviate the impact of interruptions and maintain operational continuity and sustainability in performance. In the context of the FMCG industries of Pakistan and Saudi Arabia, characterized by intricate and vulnerable supply chains, there exists an urgent necessity for solutions that bolster resilience. This study examines the influence of critical factors resilient suppliers (RS), transportation capacity (TC), flexibility (FLEX), network complexity (NC), and supply chain dynamism (SPD) on SRES. A quantitative methodology was utilized, examining survey data from 611 participants with Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA). The results indicate that RS and TC are essential for directly improving SRES, whereas FLEX and SPD facilitate increased adaptability and reactivity. The NCA emphasizes the need to control NC to avert bottlenecks that may impede resilience. This study indicates that SRES emerges from the dynamic interplay of several elements, rather than from separate enhancements. Although NC exerts a negligible direct influence, adeptly managing complexity is crucial for reducing disruptions and inefficiencies. The results underscore that fortifying RS, TC, and FLEX in unison improves resilience and adaptation to market volatility and disturbances. This study provides various theoretical and managerial insights. A systems theory approach highlights the interdependence of supply chain components, whereas the Theory of Constraints (TOC) posits that excessive NC can hinder resilience. Management should concentrate on maximizing RS and TC until declining returns are evident, thereafter redirecting efforts towards improving FLEX and minimizing NC. Furthermore, optimizing processes and facilitating swift decision-making are essential for maintaining resilience.

The durable nature of supply chains in the Middle Eastern region is critical, given the region’s strategic role in global trade corridors, yet geopolitical conflicts, territorial disputes, and governance challenges persistently disrupt key routes like the Suez Canal, amplifying vulnerabilities. This study addresses the urgent need to predict and mitigate supply chain risks by evaluating machine learning (ML) models for forecasting economic complexity as a proxy for resilience across 18 Middle Eastern countries. Using a multidimensional secondary dataset, we compare gated recurrent unit (GRU), support vector regression (SVR), gradient boosting, and other ensemble models, assessing performance via MSE, MAE, RMSE, and R². The results demonstrate the GRU model’s superior accuracy (R² = 0.9813; MSE = 0.0011), with SHAP, sensitivity, and sensitivity analysis confirming its robustness in identifying resilience determinants. Analyses reveal infrastructure quality and natural resource rents as pivotal factors influencing the economic complexity index (ECI), while disruptions like trade embargoes or infrastructure failures significantly degrade resilience. Our findings underscore the importance of diversifying infrastructure investments and stabilizing governance frameworks to buffer against shocks. This research advances the application of deep learning in supply chain resilience analytics, offering actionable insights for policymakers and logistics planners to fortify regional trade corridors and mitigate global ripple effects.

Logistics public information platform as the neural center of regional logistics system plays an important role for the integration of logistics information resources. But operation practices of the current regional logistics information platform did not consider the operating efficiency and sustainable development issues. From a sustainable perspective, the paper analyzes the development status and the problem of regional logistics informatization. With the basic theory of system engineering, using the method of horizontal contrast, the core content and construction operation model of domestic and foreign typical regional logistics information platform is analyzed, also on the basis of user requirements and function orientation of regional logistics public information platform, the PPP operation model is put forward. The study is helpful to guiding the construction of regional logistics public information platform scientifically, promoting the standardization of the exchange of information and logistics industry, and ensuring the sustainable development of the logistics public information platform.