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This study examines the direct and indirect effects of social capital on supply chain performance via supply chain quality integration (SCQI), which refers to integrating supply chain partners from the perspective of quality management. It also examines the moderating role of environmental uncertainty in the link between social capital and SCQI and determines the conditional indirect effect of social capital on supply chain performance via SCQI.

Data were collected using a time-lagged research design through a self-administered survey of supply chain professionals in manufacturing firms in Pakistan. Hayes’ PROCESS Macro was used to test the hypotheses.

The results show a positive relationship between social capital and supply chain performance. SCQI partially mediates the relationship between social capital and supply chain performance. Environmental uncertainty significantly moderates that relationship in such a way that firms that operate under high environmental uncertainty are more likely to use their social capital to develop SCQI than firms that operate under low environmental uncertainty.

The study has practical implications for managers who seek to implement SCQI practices using social capital. Leveraging social capital across the supply chain fosters strong connections and a quality-oriented approach across the supply chain, and improves overall performance. Managers can use the power of social capital to navigate environmental uncertainty.

This study’s originality lies in its drawing on the dynamic capability theory and contingency theory and integrating the dispersed scholarly work on social capital, SCQI, and supply chain performance under the boundary condition of environmental uncertainty.

Supply chain management has become critical in today’s globalized environment, with growingly intense competition on the international level. The particular characteristics of modern trade have led companies to globalize and devise increasingly sophisticated supply chains to meet customer demand worldwide. Motivated by the need to address these challenges, we have developed a new model for a global supply chain that incorporates uncertainties in exchange rates, demand fluctuations, and the quantity of produce.

The objective of the proposed model is to maximize supply chain profitability. Our model optimizes several critical decisions in the proposed global supply chain, including the location of domestic and foreign distribution centers, allocating the centers to customers, transportation mode selection, storage temperature, optimal farm purchase quantities, product flows across the network, and the shelf-life of products. Scenario-based stochastic programming approach is employed to account for the inherent uncertainties within the model. A pistachio supply chain is examined as a case study in this article, and the efficiency of the proposed model is demonstrated through computational results.

The model was solved using the CPLEX solver in GAMS and the results, the Sirjan DDC and Turkey FDC have been selected. In general, 40% of demand for customers from FDC (turkey) and 60% of demand from DDC (sirjan) is provided. Changes in the demand of foreign customers make the net profit more effective than changes in the demand for domestic customers. The decrease in exchange rate decreases the network profit with a higher slope and the increase in exchange rate will increase network profit with a relatively stable slope.

While research on GSCs for perishable products has been ongoing for several years, the importance of the subject necessitates continued investigation in this area. This paper aimed to address this gap by presenting an optimization model for designing GSCs for perishable products under uncertainty and with various transportation modes. The proposed model was designed with the aim of improving supply chain performance and real-world applicability.

Eco-innovation products, which means achieving more efficient and responsible use of resources and reducing the detrimental impact on the environment, can win a competitive advantage for the enterprises. But it is not easy to implement due to the high cost of eco-innovative technologies development, the uncertainty of market needs and return risk of investment. Many enterprises seek collaborations from their upstream suppliers to jointly carry out eco-innovation, such as Apple, IBM and Nike. A unique feature of collaboration is that efforts by one party enhance the marginal value of the other party's efforts. However, the collaboration will make the partner know the eco-innovation technology and prompt the partner to encroach the market to sell competitive products by herself. Motivated by this observation, this paper considers the optimal collaboration strategy on eco-innovation between upstream and downstream supply chain member and the optimal encroachment strategy of upstream supplier in a supply chain.

This paper models a supply chain wherein a supplier provides products or materials for her manufacturer and cooperates with her manufacturer in eco-innovation. Also, the supplier could encroach on the market to sell similar products by herself. Then this paper uses game theory and mathematical modeling to do relative analysis.

The analysis reveals several interesting insights. First, eco-innovation collaboration makes supplier encroachment no longer only rely on the encroachment cost. The delayed realized eco-innovation efficiency information also plays a vital role. Second, different from previous research, the authors find the manufacturer's preference for supplier encroachment depends on the uncertainty of eco-innovation efficiency and potential market demand. Third, both partial and full encroachment strategies of the supplier can effectively improve the eco-innovation level.

The paper is the first to take the interplay between collaboration and encroachment into account in a supply chain. The results caution enterprises and policymakers to take vertical collaboration and delayed realized information into account in the competitive supply chain before making any operational decisions. Furthermore, the authors propose that governmental intervention aimed at stimulating supplier encroachment in appropriate circumstances can contribute to the improved environmental performance of products.

Although many countries are focusing on the management of construction and demolition waste (CDW) resource utilization, the effect of risk aversion of the green innovation-led enterprise on the performance of the CDW resource utilization supply chain is unclear when considering different green innovation contexts (green innovation led by the building materials remanufacturer or by the construction waste recycler). This study aims to investigate how the level of risk aversion of the green innovation-led enterprise affects CDW resource utilization under different green innovation contexts based on contingency theory.

Using Stackelberg game theory, this study establishes a decision model consisting of a building materials remanufacturer, construction waste recycler and CDW production unit and investigates how the level of risk aversion of the green innovation-led enterprise under different green innovation contexts influences the performance level of the supply chain.

The conclusions are as follows. (1) For the green innovation-led enterprise, the risk-averse behaviour is always detrimental to his own profits. (2) For the follower, the profits of the construction waste recycler are negatively correlated with the level of risk aversion of the green innovation-led enterprise in the case of a small green innovation investment coefficient. If the green innovation investment coefficient is high, the opposite result is obtained. (3) When the green innovation investment coefficient is low, the total supply chain profits decrease as the level of risk aversion of the green innovation-led enterprise increases. When the green innovation investment coefficient is high, total supply chain profit shows an inverted U-shaped trend with respect to the degree of risk aversion of the green innovation-led enterprise.

(1) This study is the first to construct a green innovation context led by different enterprises in the CDW resource utilization supply chain, which provides a new perspective on green management and operation. (2) This study is the first to explore the operation mechanism of the CDW resource utilization supply chain based on contingency theory, which provides new evidence from the CDW resource utilization supply chain to prove contingency theory. At the same time, this study examines the interactive effects of the green innovation cost coefficient and the degree of risk aversion of green innovation-led enterprises on the performance of supply chain members, expanding the contingency theory research on contingencies affecting enterprise performance. (3) This study will guide members of the CDW resource utilization supply chain to rationally face risks and achieve optimal supply chain performance.

This paper aims to synthesise the latest literature on supply chain operations of offsite manufacturing in the construction industry to identify and evaluate the uncertainties at each stage of the offsite construction supply chain (OSC-SC) to compile contributions to knowledge and thereby determine the future research directions to improve supply chain resilience (SCR).

The study was conducted as a systematic literature review. In total, 99 peer-reviewed journal papers published between 2015 and mid-2022 were shortlisted and analysed through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

The bibliometric analysis revealed that the research focusing on supply chain issues and developing best practices in offsite construction adopt case study approaches to investigate the research problems comprehensively. The content analysis revealed the lack of up-to-date knowledge in the construction workforce regarding OSC; low preparedness for the changes brought by the SC uncertainties; the lack of a proper procurement model for OSC; lack of end-to-end visibility of the supply chain to identify uncertainties and lack of national or government standards on OSC-SC, as some of the key problems instigating the identified the uncertainties.

This study clarifies the current knowledge by systematically presenting uncertainties at each stage of the OSC-SC. Moreover, it provides a framework and proposes that future research should focus specifically on individual/team, organisational, supply chain/network and sector/national/supranational levels to improve SCR.

The agricultural supply chain is susceptible to disruptive geopolitical events. Therefore, agri-food firms must devise robust resilience strategies to hasten recovery and mitigate global food security effects. Hence, the central aim of this paper is to investigate how supply chains could leverage digital technologies to design resilience strategies to manage uncertainty stemming from the external environment disrupted by a geopolitical event. The context of the study is the African agri-food supply chain during the Russian invasion of Ukraine.

The authors employ strategic contingency and dynamic capabilities theory arguments to explore the scenario and conditions under which African agri-food firms could leverage digital technologies to formulate contingency strategies and devise mitigation countermeasures. Then, the authors used a multi-case-study analysis of 14 African firms of different sizes and tiers within three main agri-food sectors (i.e. livestock farming, food-crop and fisheries-aquaculture) to explore, interpret and present data and their findings.

Downstream firms (wholesalers and retailers) of the African agri-food supply chain are found to extensively use digital seizing and transforming capabilities to formulate worst-case assumptions amid geopolitical disruption, followed by proactive mitigation actions. These capabilities are mainly supported by advanced technologies such as blockchain and additive manufacturing. On the other hand, smaller upstream partners (SMEs, cooperatives and smallholders) are found to leverage less advanced technologies, such as mobile apps and cloud-based data analytics, to develop sensing capabilities necessary to formulate a “wait-and-see” strategy, allowing them to reduce perceptions of heightened supply chain uncertainty and take mainly reactive mitigation strategies. Finally, the authors integrate their findings into a conceptual framework that advances the research agenda on managing supply chain uncertainty in vulnerable areas.

This study is the first that sought to understand the contextual conditions (supply chain characteristics and firm characteristics) under which companies in the African agri-food supply chain could leverage digital technologies to manage uncertainty. The study advances contingency and dynamic capability theories by providing a new way of interacting in one specific context. In practice, this study assists managers in developing suitable strategies to manage uncertainty during geopolitical disruptions.

This study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model.

In dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts.

The research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management.

This study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management.

This research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.

Under the digital wave and the new industrial competition pattern, the automobile industry is facing multiple challenges such as the redefinition of new technologies and supply chain changes. The purpose of this study is to link big data analytics and artificial intelligence (BDA-AI) with digital supply chain transformation (DSCT) by taking Chinese automobile industry firms as a sample and to consider the role of supply chain internal integration (SCII), supply chain external integration (SCEI) and supply chain agility (SCA) between them.

Data were collected from 192 Chinese firms in the automotive industry and analyzed using partial least squares structural equation modeling (PLS-SEM). Importance-performance map analysis is used to extend the standard results reporting of path coefficient estimates in PLS-SEM.

The results indicate that BDA-AI, SCII, SCEI and SCA positively influence DSCT. In addition, this study found that SCII, SCEI and SCA play an intermediary role in BDA-AI and DSCT.

The paper enriches the research on the mechanism of digital resources affecting DSCT and expands the research of organizational information processing theory in the context of digital transformation. The paper explores how the resources deployed by firms change the strategic measures of firms from the perspective of responsiveness. By exploring the positive impact of SCA as a response capability on the DSCT strategy and its intermediary role between digital resources and DSCT, which is helpful to the further theoretical development of logistics and supply chain disciplines.

This study presents the impact of Economic Policy Uncertainty (EPU)-induced Trade Supply Chain Vulnerability (TSCV) on the Small and Medium-Sized Enterprises (SMEs) in India by leveraging the World Bank Enterprise Survey data for 2014 and 2022. Applying econometric techniques, it examines firm size’ influence on productivity and trade participation, providing insights for enhancing SME resilience and trade participation amid uncertainty.

The econometric techniques focus on export participation, along with variables such as total exports, firm size, productivity, and capital intensity. It addresses crucial factors such as the direct import of intermediate goods and foreign ownership. Utilizing the Cobb-Douglas production function, the study estimates Total Factor Productivity, mitigating endogeneity and multicollinearity through a two-stage process. Besides, the study uses a case study of North Indian SMEs engaged in manufacturing activities and their adoption of mitigation strategies to combat unprecedented EPU.

Results reveal that EPU-induced TSCV reduces exports, impacting employment and firm size. Increased productivity, driven by technological adoption, correlates with improved export performance. The study highlights the negative impact of TSCV on trade participation, particularly for smaller Indian firms. Moreover, SMEs implement cost-based, supplier-based, and inventory-based strategies more than technology-based and risk-based strategies.

Policy recommendations include promoting increased imports and inward foreign direct investment to enhance small firms’ trade integration during economic uncertainty. Tailored support for smaller firms, considering their limited capacity, is crucial. Encouraging small firms to engage in international trade and adopting diverse SC mitigation strategies associated with policy uncertainty are vital considerations.

This study explores the impact of EPU-induced TSCV on Indian SMEs’ trade dynamics, offering nuanced insights for policymakers to enhance SME resilience amid uncertainty. The econometric analysis unveils patterns in export behavior, productivity, and factors influencing trade participation during economic uncertainty.

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.