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In the current era of turbulence, demand uncertainty and significant supply delays have become recurrent challenges for every global supply chain, which are accentuated by geopolitical issues, regional conflicts, natural disasters, etc. Companies are keen to decide when and where nearshoring and offshoring their supply locations and to adapt their inventory control policies to cope with significant perturbations. To deal with these challenges, we investigate the integration of inventory planning at the strategic level through a novel setting of the location-inventory problem under uncertainty. This problem is characterised by inbound multi-sourcing, order splitting among multiple suppliers, and optimised inventory decisions from sourcing to customers under uncertain demand and lead time. A two-stage stochastic optimisation model is proposed and solved using a Benders decomposition algorithm, supported by a sample average approximation approach. The results show that both lead time and demand uncertainties impact strategic and tactical decisions of the global supply network. Specifically, multi-sourcing and inbound order splitting policies have proven beneficial when the network faces a high lead time uncertainty. Based on an illustrative case of a global automobile spare parts supply network under different supply-side scenarios, managerial insights are gained on the benefit of onshore, nearshore, and offshore decisions. When facing a high lead time uncertainty, as in the pandemic case or any geopolitical episode, our findings suggest the necessity to rely on nearshoring for the supply side. [ABSTRACT FROM AUTHOR]

Cybersecurity presents non-negligible challenges for firm collaboration and supply chain viability, as information exchange among nodes introduces potential interdependent risks. How to make appropriate decisions on security investments and information exchange modes is a significant issue for supply chain members. Considering two information exchange modes: system interconnection and system independence, this study develops two game models to investigate the cybersecurity investments in a vertical supply chain composed of a retailer and n suppliers. Initial analysis shows that although firms learn investment decisions mutually in the face of a changing cybersecurity environment, suppliers always take a free ride on the efforts of retailer in two cases and the increased interdependent risks will damp nodes enthusiasm for security investments. Next, to compare the two cases, we introduce information exchange efficiency as the mediate parameter to link degree of system interconnection and proportion of information shared. We found that under the system independence mode, firms with high information-exchanging demand in the large-scale supply chain are more motivated to invest in cybersecurity. Furthermore, we extend our models to a centralised decision-making scenario. We find that security investment efficiency is greatly improved, and the free-riding behaviour of supplier is significantly reduced when systems are interconnected. [ABSTRACT FROM AUTHOR]

Supply chains are widely studied as carriers of value, but their potential to create value remains underappreciated. This study conceptualizes supply chain orchestration as a business model that allows a firm to create value in a supply chain with high market uncertainty by matching demand and supply more effectively than the present norm, and without relying on product innovation. Building on contingency theory, this study theorizes supply chain orchestration and articulates three defining qualities of its activity system. Next, it describes the evolution of this business model: its creation requires architectural market knowledge; however, sustained belief in the architectural market knowledge, ironically, can hinder its adaptation to changes in the firm's environment and lead to its abandonment. The study, I hope, will promote management practice and research at the largely untapped intersection of business models and strategic supply chain management to foster novel value creation by orchestrating supply chains. [ABSTRACT FROM AUTHOR]

Motivated by the COVID-19 pandemic, this paper explores the supply chain viability of medical equipment, an industry whose supply chain was put under a crucial test during the pandemic. This paper includes an empirical network-level analysis of supplier reachability under Random Failure Experiments (RFE) and Intelligent Attack Experiments (IAE). Specifically, this study investigates the effect of RFE and IAE across multiple tiers and scales. The global supply chain data was mined and analysed from about 45,000 firms with about 115,000 intertwined relationships spanning across 10 tiers of the backward supply chain of medical equipment. This complex supply chain network was analysed at four scales, namely: firm, country-industry, industry, and country. A notable contribution of this study is the application of a supply chain tier optimisation tool to identify the lowest tier of the supply chain that can provide adequate resolution for the study of the supply chain pattern. We also developed data-driven-tools to identify the thresholds for breakdown and fragmentation of the medical equipment supply chain when faced with random failures or different intelligent attack scenarios. The novel network analysis tools utilised in the study can be applied to the study of supply chain reachability and viability in other industries. [ABSTRACT FROM AUTHOR]

The paper investigates the resilience of an agriculture supply chain through the lens of complex network perspective. Given the susceptibility of these supply chains to bothrandom events (rainfall and yield uncertainty), and targeted events (income tax raids on millers, strikes, and lockouts), as well as spillover effects of disruptions; we propose a supply chain architecture that helps in achieving a balanced performance against these disruptions. For this, we propose a new attachment rule—'price/cost-based attachment rule', which we use along with degree-based and distance-based attachment rules in generating a resilient supply chain topology. We call the proposed supply chain network—'Balanced Supply Network' whose performance is compared with a scale-free network (BA Network) and a random network (ER Network). The comparison is based on critical performance indicators such as availability (demand and supply availability rate) and connectivity (size of largest all-role connected component). The findings, on expected lines, reveal that our proposed network exhibits a performance trade-off between BA Network and ER Network when subjected to targeted disruptions and disruption propagation scenarios. However, in case of random disruptions, it ensures maximum resilience and even outperforms BA Network due to its construction properties. Further, to optimize resilience, we introduce weights to the attachment rules of our proposed network. These weight assignments enable us to identify the most effective configuration among the three attachment rules for enhancing the network's ability to withstand disruptions. [ABSTRACT FROM AUTHOR]

The mismatch between production, order, and demand seriously affects supply chain performance. However, most research focus on the mismatch between the retailer's order and customer's demand, which ignores the influence of the supplier's random yield on supply chain members' decision‐making. This paper investigates a two‐stage optimization problem within a two‐echelon supply chain, featuring a supplier with random yield and a retailer updating demand information in real‐time. Faced with a long production lead time, the retailer can either place advance orders at the production season's onset (first‐stage advance order) or opt for instant orders at the beginning of the sales season (second‐stage instant order). To ensure timely order fulfillment, the supplier initially employs a cost‐effective regular production mode with random yield during the production season. If yields are insufficient during sales, a pricier emergency production mode with guaranteed output becomes available. Utilizing a dynamic programming approach, we formulate the two‐stage optimization problem to derive optimal production and order decisions. Our analysis uncovers how realized random yield and stochastic market signals influence emergency production and instant order quantities in the second stage. We compare expected profits in scenarios with perfect and imperfect market signals, probing the members' preferences regarding order strategies. An intriguing finding emerges: as instant wholesale prices rising, the supplier's preferred order strategy diverges from the retailer. By strategic adjustments to the instant wholesale price, we demonstrate the potential for unanimous agreement on preferred order strategies among supply chain members — a quality enhancing the chain's flexibility and performance. Moreover, we extend the model to hybrid order strategies and identify conditions for unanimous preference among the three strategies. To bolster our theoretical findings, we provide numerical examples, lending practical support to our study. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic poses various challenges to the sustainable operation of supply chains in different sectors. Especially, the impacts and response strategies of COVID-19 on supply chain operations have attracted much research attention. Nevertheless, a comprehensive review of related studies is still lacking. To address this research gap, this article systematically reviewed 94 historical papers relevant to the impacts and response strategies of COVID-19. It was found that the COVID-19 pandemic has caused supply and demand contradiction or disruptions in four types of supply chains. In addition, the epidemic response measures were also considered from the two dimensions of practice and theory. Based on the research findings, future research directions were also proposed, such as the dynamic evolution process of impacts. The research findings not only help to mitigate or eliminate the negative impacts of COVID-19 on supply chain operations but also provides future research directions in the studied field. [ABSTRACT FROM AUTHOR]

As 'Internet+' technology and e-commerce third-party platforms evolve, consumer options for purchasing fresh products now include both offline and online channels, giving rise to a mixed dual-channel supply chain. We examine this dual-channel supply chain, constructing a market demand function influenced by fresh produce pricing and preservation efforts.Optimal strategies for each stakeholder and the supply chain's maximum profit are analyzed through both classical and quantum game theory. The results indicate that under centralized decision-making, the equilibrium solutions are identical for classical and quantum games, with the quantum entanglement degree $ \gamma = 0 $. In scenarios where market demand exhibits low sensitivity to freshness preservation efforts, the entanglement degree between suppliers and retailers can be elevated by implementing a 'freshness preservation cost-sharing + revenue-sharing contract, ' thereby enhancing supply chain efficiency and profit. This study contributes to the literature by offering new theoretical insights into mitigating free-riding behavior in fresh food retail and explores the potential applications of quantum games in economics. [ABSTRACT FROM AUTHOR]

In the new normal of the supply chain, shortage risk is increasingly becoming a primary concern for operations management. While increasing order quantities can help alleviate shortage costs, surplus order quantity concurrently raises the risk of overstocking. Shortage and holding risk are affected by both demand and supply uncertainty, and the distributions of the random variables remain unknown. Consequently, solving the stochastic optimization problem analytically proves to be challenging. This study aims to exploit the data-driven stochastic optimization method and to analyze the optimal ordering decisions under different demand and supply scenarios. Numerical results indicate that the linear machine learning (LML) method incorporating data features outperforms the sample average approximation (SAA) method in terms of optimization performance. Incorporating $ l_2 $ regularization into the LML method effectively mitigates overfitting and produces similar results under different scenarios. In addition, the optimal order quantity may decrease as the supply variance increases when the unit shortage cost is relatively low, while the optimal order quantity may increase as the supply variance increases when the unit shortage cost is high. The opposite is true in the context of demand research. Finally, smaller supply and demand variances, together with larger supply means, lead to lower firm costs. The effect of the demand mean on the firm's costs is negligible. At the same time, the effect of the supply mean on the firm's costs is more pronounced than that of the supply variance. [ABSTRACT FROM AUTHOR]

As the market environment becomes increasingly complex, the demands for supply chain performance and security are continuously rising. Consequently, it is crucial to consider the role of trust factors within the system. This paper introduces a trust mechanism in the interaction between supply and demand within supply chain logistics and information flow. The supply chain system, characterized by varying degrees of trust, is modeled as multiple subsystems using the T-S fuzzy model. The challenge of mitigating the bullwhip effect, which refers to the amplification of demand variability within the supply chain, is reformulated as an H ∞ consistency problem. A productivity and distributed consistency protocol switching controller based on fuzzy rules is designed, providing sufficient conditions for the entire system to achieve consistency. The proposed method effectively suppresses the bullwhip effect and allows certain nodes in the system to be temporarily in an abnormal state. Finally, the method's effectiveness is validated through simulation examples. [ABSTRACT FROM AUTHOR]

With the deepening of industrial division of labor, supply chain efficiency has become a critical driver of companies' core competitiveness. Using a sample of Chinese A‐share listed companies from 2007 to 2023, this paper empirically investigates the impact of digital transformation on supply chain efficiency. We find that firms with a higher degree of digital transformation are associated with higher supply chain efficiency. Mechanism tests show that digital transformation facilitates supply chain efficiency via lower customer demand uncertainty as well as raw material disruption risk. The positive effect of digital transformation is more pronounced for non‐state‐owned enterprises and for firms with less stable customers and more geographically dispersed suppliers. Moreover, there is much degree prompt in supply chain efficiency for firms located in a better digital environment. This paper sheds light on how digital transformation influences supply chain efficiency and provides significant insights for firms to improve supply chain efficiency. [ABSTRACT FROM AUTHOR]

Background: The blood supply chain (BSC) is crucial for providing safe and sufficient blood, but it faces numerous challenges and needs to be robust and resilient. This study provides a comprehensive model for managing and optimizing the BSC in real-world scenarios, including emergency and routine circumstances and with consideration of health equity concepts. Method: Classic time-series models are applied to predict future supply chain circumstances, addressing uncertainty in blood demand and the need for timely supply. A structured framework and medical preferences are prioritized to optimize distribution, minimize blood shortages, minimize wastage due to expiry, and maximize blood freshness. Genetic algorithms (GA) and particle swarm optimization (PSO) are used to solve mathematical models quickly and efficiently, ensuring reliable operation. Result: The model's outcomes can effectively meet the daily needs of the BSC and assist decision-makers managing blood inventory and distribution, improving robustness and resilience. Conclusions: Utilizing weights allows for the effective management of each objective function to convert the model into a single-objective mixed-integer linear programming (SO-MILP) based on unique conditions, enabling the system to self-adjust for optimal performance, boosting the sustainability of the blood supply chain, and promoting the principle of health equity under diverse real-world settings. [ABSTRACT FROM AUTHOR]

Prefabricated construction has gained traction in sustainable construction practices. As a modular construction method, the prefabricated component (PC) supply chain involves key participants—producer, transporter, and assembler—operating in a point-to-point cooperation pattern (i.e., single project–single producer–single transporter). However, a disparity in resource allocation between the supply and demand sides leads to inefficiencies within the PC supply chain. Thus, this paper introduces the platform service pattern concept combined with evolutionary game theory, constructing a tripartite evolutionary game model to analyze the dynamic evolution mechanism of their behavioral strategies. Extending from a point-to-point cooperation pattern, this paper analyzes a multi-to-multi network structure (i.e., multiple projects–multiple producers–multiple transporters) and utilizes evolutionary game theory to simulate a stakeholder's strategies. Beyond maximizing the economic profits, we also include sustainable objectives into consideration, and we explore how project and environmental subsidies impact multiparty collaborations and their strategy selections. Specifically, three prefabricated components supply chain cooperation patterns (PCSCCPs) with multiparty dynamics are derived: standardized PC supply chain cooperation pattern (ST-PCSCCP), green and standardized PC supply chain cooperation pattern (GS-PCSCCP), and mixed PC supply chain cooperation pattern (MX-PCSCCP). They are developed and compared by using empirical data for model parameter selections. The results show that all patterns achieved simultaneous production and transportation for multiple project orders and all ensure that construction projects meet sustainability requirements. Additionally, MX-PCSCCP requires the minimum subsidies. [ABSTRACT FROM AUTHOR]

Ensuring a stable supply and demand of food represents a pivotal challenge for sustainable development. This study seeks to delineate the spatiotemporal distribution and circulation patterns of supply and demand for staple crops, identify the major producing and consuming zones in China, and investigate the drivers underpinning efficient coordination of food supply and demand. Results indicate that between 2000 and 2020, China's food supply and demand expanded by 73.8% and 36.62%, respectively, achieving a supply surplus. However, the most significant threats to supply–demand coordination are the extensive use of feed and industrial crops, compounded by the import vulnerabilities arising from global supply chain uncertainties. In terms of major producing and consuming zones, Northeast China plays a vital role in the national food supply, contributing 71% of domestic soybeans, 55% of its maize, and 34% of its rice. Climatic conditions and self‐sufficiency rates are key determinants of provincial supply and demand for staple crops. Provinces such as Sichuan, Hubei, Anhui, and Shandong represent balanced producing–consuming zones for these staple crops. To enhance food supply–demand coordination, tailored and adaptive measures for different provinces are imperative. This study offers theoretical insights to understand the trends of food supply and demand and further contributes to adaptive strategies to address climate change for sustainable food systems. [ABSTRACT FROM AUTHOR]

Farms usually plan the planting and harvest of crops independently and without considering the plans of the rest of supply chain (SC) members. This generates large imbalances between crops' supply and demand in markets, as well as significant price fluctuations. Shifting how crop production is planned to joint SC decision-making would offer significant advantages in preserving agricultural SC sustainability. This paper explores this idea by proposing a multi-objective optimisation model for planning the planting, cultivation, harvesting, storage, packaging, transport, labouring, and sale of fresh crops. The tool considers five objectives aligned with sustainability: maximising SC profits (economic), minimising waste (environmental), minimising unsatisfied demand (social), maximising sold crops' freshness (environmental and social), and minimising economic injustice perceived by farmers (social). The tool is validated through its application to the La Plata fresh tomato SC case study in Argentina and it is shown how the tool could be used by real decision-maker(s). [ABSTRACT FROM AUTHOR]

Purpose: Supply chains are increasingly incorporating social perspectives into their activities. It is often argued that social initiatives in supply chain management (SCM) are a response to external pressures. However, it is still undetermined whether these initiatives can improve economic performance. Additionally, it is proposed that digital transformation in supply chains, also described as Smart Supply Chain, can support social performance. Therefore, this study aims to analyze the association between digital transformation, social performance in SCM and economic performance. Design/methodology/approach: The study is based on a survey of 473 companies in Brazil, a country where social needs create high pressures on companies to respond to the country's challenges. The data collected underwent testing using ordinary least squares regression and bootstrapping techniques to examine the mediation effects between Smart Supply Chain, social performance and economic performance. Findings: The findings indicate that digital transformation supports social performance. Additionally, adopting social initiatives helps to increase firm performance in the context of an emerging economy, while social initiatives mediate between digital transformation and firm performance. Originality/value: This paper provides a new perspective on the social side of supply chains by demonstrating the close relationship between digital transformation and social engagement initiatives. It argues that aligning digital transformation strategies and technologies with social performance is crucial for companies to establish stronger connections with stakeholders. [ABSTRACT FROM AUTHOR]

Carbon neutrality and resilience are two of important goals pursued by supply chains today. This study seeks to determine how carbon footprint reduction (CFR) can be achieved in a resilient supply chain from a process integration perspective. Based on contingency theory, we employed the decision-making trial and evaluation laboratory (DEMATEL) approach to examine the critical influencing factors of process integration using evaluations from academic and professional experts. Our findings reveal that, first, at the strategic level, supply chain collaboration (SCC) and supply chain agility and responsiveness (SCAR) have the highest contributions to process integration. Second, process and control risks have the highest contributions in supply chain risk management; herein, collaborative planning, forecasting, and replenishment (CPFR) holds the highest contribution in the SCC, visibility and velocity have the highest contributions in the SCAR, and supply chain efficiency holds the highest contribution in supply chain flexibility (SCF). Finally, CPFR has a significant influence on both supplier and customer engagement, with supply chain intelligence influencing customer engagement in the SCC. Both the standardisation and parallel processes influence supplier spending in the SCF. These findings provide a new conceptual framework for empirical research and an action plan for supply chains to pursue carbon neutrality. [ABSTRACT FROM AUTHOR]

Warehouses are key elements of supply chain networks, and great attention is paid to increase their efficiency. Highly volatile space requirements are enablers of innovative resource sharing concepts, where warehouse capacities are traded on online platforms. In this context, our paper introduces the on-demand warehousing problem from the perspective of platform providers. The objective prioritises demand-supply matching with maximisation of the number of transactions. If there is a tie, the secondary objective maximises the number of suppliers matched with at least one customer and the number of customers that have matches within a specific threshold with respect to the minimum achievable cost. Besides the mathematical integer programming formulation, a myopic list-based heuristic and an efficient matheuristic approach are presented and benchmarked against the performance of a commercial optimisation solver. The impact of several parameters on the platform's objective is analysed. A particularly relevant finding is that the pricing flexibility on the demand side does not necessarily imply higher payments to the supply side. All data instances are made available publicly to encourage more researchers to work on this timely and challenging topic. [ABSTRACT FROM AUTHOR]

This paper aims to unveil the role of openness in fostering enterprises to achieve technological progress. By conducting a comparative analysis of Chinese and Western companies' supply chain strategies in the internet and new energy industries, the article finds that American enterprises have a higher level of supply chain openness than Chinese enterprises in both two industries. Based on the case analysis, that paper argues that openness plays a vital role in promoting technological innovation in enterprises. The profound influence of openness in promoting technological advancement may be observed through three aspects: openness at the technical level, openness in attracting talent, and openness in facilitating the development of rules and regulations. Accordingly, suggestions are proposed to assist Chinese enterprises in avoiding the "Middle-Technology Trap" through openness on the basis of legislation and public policy intervention. Meanwhile, the Chinese government is suggested to promote national coordination to establish a national unified market to realize the three levels of openness of the supply chain and industrial chain strategies: enterprise-level, domestic regional level, and international level. [ABSTRACT FROM AUTHOR]

This research endeavored to provide an analysis of the barriers related to the agri-food supply chain in the context of the Indian agro-industry. The methodology used is based on an Interpretive Structural Modeling with a Matrix of Cross Impacts-Multiplication Applied to a Classification (MICMAC) technique. There is a need for specificity in defining Agro-food supply chain barriers before they can be eliminated. Therefore, the goal of this study is to look at the factors which are emerging as constraints to the growth of the agri-food supply chain. The findings show that transparency and traceability, inadequate infrastructure, difficulty in implementing government schemes, and inadequate risk management measures constitute important barriers to agri-food supply chains. This study provides an understanding of supply-chain barriers related to the agro-food industry. Managers/owners of agricultural enterprises can use the findings of this study to more easily identify the prominent barriers which affect agri-food supply chains. Furthermore, this study can be used as a guide to deal with the supply chain problems facing agri-enterprises in the face of high demand for agri-products. [ABSTRACT FROM AUTHOR]

This research focuses on determining the level of inventory in a downstream supply chain for fuel products in Indonesian oil and gas company prespective. The variability in supply and demand is a problem in maintaining the stability of services to the consumers. High inventory costs that are completely borne by the company are also a problem that needs to be controlled. Therefore, determining inventory levels is very important to mitigate the variability of supply and demand that occurs with optimum inventory costs. This research designs a probabilistic model by considering variability in supply and demand to determine safety stock so that the correct level of Fuel Product inventory at each Storage Point can be determined. This research method is quantitative research based on empirical data. It is hoped that the research results will be able to obtain inventory control which can be taken into consideration by oil and gas company in managing the downstream supply chain of fuel products. [ABSTRACT FROM AUTHOR]

The free nutritious food program initiated by President-elect Prabowo and his cabinet aims to improve the quality of life of Indonesians, especially vulnerable groups. Various factors, including good demand and supply matching practices, largely determine the success of this program. The objective of this research is to analyze the best strategies and techniques for matching demand and supply, as well as for effective inventory management for this program. The research method used is qualitative, with data collection through literature study. After collecting the data, the analysis is done through several stages: filtering, data presentation, and conclusion drawing. The results show that good inventory management and supply-demand matching are key factors for the success of this program. Some strategies and techniques identified include careful planning, robust information systems, efficient supply chain management, good inventory management techniques, and diversification of supply sources. Diversifying supply sources helps the government reduce costs, improve food quality, support local economies, and strengthen national food security. By implementing these strategies, the government can ensure that the free nutritious food program can run efficiently and effectively and provide optimal benefits to the wider community. [ABSTRACT FROM AUTHOR]

The objective of this study is to enhance the resilience of the coal-to-liquids (CTL) industrial chain and supply chain to withstand increasing shock pressures. There is an urgent need to improve the resilience of the industrial chain and supply chain. This paper identifies 21 resilience-influencing factors from 4 perspectives: absorption capacity, adaptability, recovery capacity, and self-learning capacity; it then constructs an evaluation indicator system. The Interval Type 2 Fuzzy-Decision-Making Trial and Evaluation Laboratory-Analytic Network Process (IT2F-DEMATEL-ANP) method is adopted to determine the weights of the indicator system, and a resilience evaluation is performed based on the Interval Type 2 Fuzzy-Prospect Theory-Technique for Order Preference by Similarity to an Ideal Solution (IT2F-PT-TOPSIS) method. Furthermore, in the case of the CTL industrial chain and supply chain of China Shenhua Energy Group Ningxia Coal Industry Co., Ltd. (CENC) (Ningxia, China), this study ranks the resilience level from 2018 to 2022 to identify the factors that have contributed to a reduction in resilience and to implement measures to enhance the resilience of the CTL industrial chain and supply chain. The results show that the level of the CTL industrial chain and supply chain resilience was lowest in 2020, while it was highest in 2021. Factors such as the degree of domestication of key technologies, the rationality of the CTL industry layout, and the stability of supply and demand chains are identified as significant determinants of resilience levels. This points the way to enhancing the resilience of the CTL industry and supply chain. [ABSTRACT FROM AUTHOR]

Purpose: We present configurational theorising as a novel approach to developing middle-range theory in two steps: (1) we illustrate configurational theorising as a new form of supply chain inquiry by connecting its philosophical assumptions with a methodological execution, and (2) we generate new insights underpinning a middle-range theory for supply chain resilience. Design/methodology/approach: We synthesise information from a range of sources and invoke 'critical realism" to suggest a five-phase configurational theorising roadmap to develop middle-range theory. We demonstrate this roadmap to explain supply chain resilience by analysing qualitative data from 22 organisations within the Australian food supply chain. Findings: Coopetition and supply chain collaboration are necessary causal conditions, but they need to combine with either supply chain agility or multi-sourcing strategy to build supply chain resilience. Asymmetrical analyses showed that the simultaneous absence of supply chain collaboration, supply chain agility and multi-sourcing results in low supply chain resilience, but coopetition was indifferent to low supply chain resilience. Similarly, high supply chain resilience is possible with the non-presence of supply chain agility and multi-sourcing. Research limitations/implications: The configurational middle-range theorising roadmap presented and empirically tested in this paper constitutes a substantial advancement to both theory and the methodological domain. Originality/value: This is the first attempt at developing a middle-range theory for supply chains by explicitly drawing on configurational theorising. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic created an unprecedented demand and supply shock to the world economies. To understand its impact on corporate prices, we define a partial equilibrium model where non‐financial corporations operating in three sectors (suppliers, end‐producers and service providers) optimize their production under monopolistic competition and are subject to demand and supply shocks of different intensities. Our model confirms that when the demand shock dominates, prices tend to decrease. We then introduce data from the COVID‐19 pandemic in the European Union into our model and find that prices are expected to fall in the most acute phase of the pandemic, when lockdowns and similar health measures decrease demand, and to increase later as a result of tensions in the supply of intermediate goods and of the persistence of the supply shock. Inventories could play a decisive role in avoiding price increases in the moderate phase of the pandemic. In the post‐pandemic period, higher prices may continue for a time until the shock to suppliers vanishes. These are relevant insights on the macroeconomic impact of worldwide pandemics, also considering the current macroeconomic environment. [ABSTRACT FROM AUTHOR]

This study examines the literature on supply chain management and corporate social responsibility within football. A systematic search of eight databases yielded 1222 articles, subsequently reduced to 107 after a combination of duplication removal and both abstract and full-text analysis. The review showed that only some studies have investigated CSR, SCM, and football simultaneously. Clustering reveals the current state of scholarly research on CSR in football industry supply chains and some significant areas where the authors discuss several sub-themes emerging with each cluster. The synergistic and miraculous role of attention to the trilogy between SCM, CSR, and the football business is crucial in creating the most advantages in society. We conclude that CSR, with the firm's Environmental, and Governance-based engagement, can lead to sustainable supply chains and higher efficiency. We have suggested that CSR in football supply chains helps develop the football industry and increase public trust and social welfare. [ABSTRACT FROM AUTHOR]

This research discusses the publication trend on the topic of green supply chain management with "Green Supply Chain Management" as the keyword. Search using the title and abstract categories listed in Dimension from 2014 to 2023 analyzed in a bibliometric study. This bibliometric study can guide academics and practitioners to take relevant steps in managing environmentally friendly supply chains. Therefore, this research could contribute to understanding developments and challenges in the green supply chain field. The results of this study are expected to provide insights for decision-makers and practitioners in managing supply chain sustainably. There are 4,017 articles. This number is very impressive and almost every year there is a significant development in this research topic. The analysis of this study is focused on the number of publications, authors, and journals. This study aims to observe the development map of Green Supply Chain Management research in the world. Results show that the number of publications on Green Supply Chain Management has increased quite steadily and was the most published in 2023 with a total of 803 journals. As for the lowest number of publications, there was in 2014 with the number of publications as many as 179. Thus, it can be concluded that the topic of this theme has developed from year to year, and this concept has great potential to develop further in the future. [ABSTRACT FROM AUTHOR]

Background: Ensuring the consistent availability of essential medicines is crucial for effective healthcare systems. However, Ethiopian public health facilities have faced frequent stockouts of crucial medications, highlighting systemic challenges such as inadequate forecasting, prolonged procurement processes, a disjointed distribution system, suboptimal data quality, and a shortage of trained professionals. This study focuses on the Ethiopian Pharmaceutical Supply Services (EPSS), known for its highly unstable and volatile supply chain, aiming to identify risks and mitigation strategies. Methods: Using a mixed-method approach involving surveys and interviews, the research investigates successful and less successful strategies, key success factors, and barriers related to pharmaceutical shortages. Results: Proactive measures such as communication, stock assessment, supervision, and streamlined procurement are emphasized as vital in mitigating disruptions, while reactive strategies like safety stock may lack long-term efficacy. The study highlights the importance of aligning supply chain strategies with product uncertainties, fostering collaboration, and employing flexible designs for resilience. Managerial implications stress the need for responsive structures that integrate data quality, technology, and visibility. Conclusions: This study contributes by exploring proactive and reactive strategies, elucidating key success factors for overcoming shortages in countries with unstable supply chains, and offering actionable steps for enhancing supply chain resilience. Embracing uncertainty and implementing proactive measures can help navigate volatile environments, thereby enhancing competitiveness and sustainability. [ABSTRACT FROM AUTHOR]

This research presents a uni-regression deep approximate forecasting model for predicting future demand in supply chains, tackling issues like complex patterns, external factors, and nonlinear relationships. It diverges from traditional models by employing a deep learning strategy through recurrent bidirectional long short-term memory (BiLSTM) and nonlinear autoregressive with exogenous inputs (NARX), focusing on regression-based approaches. The model can capture intricate dependencies and patterns that elude conventional approaches. The integration of BiLSTM and NARX provides a robust foundation for accurate demand forecasting. The novel uni-regression technique significantly improves the model's capability to detect intricate patterns and dependencies in supply chain data, offering a new angle for demand forecasting. This approach not only broadens the scope of modeling techniques but also underlines the value of deep learning for enhanced accuracy in the fluctuating supply chain sector. The uni-regression model notably outperforms existing models in accuracy, achieving the lowest errors: mean average error (MAE) at 1.73, mean square error (MSE) at 4.14, root mean square error (RMSE) at 2.03, root mean squared scaled error (RMSSE) at 0.020, and R-squared at 0.94. This underscores its effectiveness in forecasting demand within dynamic supply chains. Practitioners and decision-makers can leverage the uni-regression model to make informed decisions, optimize inventory management, and enhance supply chain resilience. Furthermore, the findings contribute to the ongoing evolution of supply chain demand forecasting methodologies. [ABSTRACT FROM AUTHOR]

Effective supply and demand matching for construction materials is a crucial challenge in large-scale railway projects, particularly in complex and hazardous environments. We propose a two-stage stochastic programing model that incorporates environmental uncertainties, such as natural disasters, into the supply chain optimization process. The first stage determines optimal locations and capacities for material supply points, while the second stage addresses material distribution under uncertain demand. We further enhance the model's efficiency with Benders decomposition algorithm. The performance of our model is rigorously compared with existing optimization approaches, demonstrating its superior capability in handling environmental uncertainties and complex logistical scenarios. This study provides a novel framework for optimizing supply chains in challenging environments, offering significant improvements over traditional models in both adaptability and robustness. [ABSTRACT FROM AUTHOR]

Demand fulfillment and order management are important functions in semiconductor supply chains to interact with customers. In this paper, an iterative short-term demand supply matching (STDSM) algorithm based on mixed-integer linear programming (MILP) is proposed. This approach repromises orders taking into account the finite capacity of the shop floor. Decomposition is used to obtain computationally tractable subproblems. The STDSM approach is applied together with master planning and allocation planning in a rolling horizon setting. A simulation model of a simplified semiconductor supply chain is used for the rolling horizon experiments. The experiments demonstrate that the proposed STDSM scheme outperforms conventional business rule-based heuristics with respect to several delivery performance-related measures and with respect to stability. [ABSTRACT FROM AUTHOR]

This study investigates manufacturers' vertical integration strategies within two competing three‐tier supply chains, focusing on the dynamics of asymmetric supply chains. This asymmetry stems from varying customer loyalties toward two products engaged in pricing and quality competition. By characterizing the equilibrium operational decisions and integration choices, we provide insights into how asymmetric customer loyalty compares and price–quality competition collectively influence the equilibrium channel structure. Our findings highlight that the option for backward integration can lead to an asymmetric equilibrium channel structure, driven by disparities in customer loyalty. In cases marked by significant differences in customer loyalty and a high market demand for product quality, the manufacturer with weaker customer loyalty might unilaterally implement decentralization. This analysis illuminates scenarios where manufacturers diverge from conventional integration norms and offers valuable insights into evolving supply chain dynamics. [ABSTRACT FROM AUTHOR]

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The global supply chains sustainability and viability has been severely impacted due to the emergence of black swan events such as COVID‐19. Previous studies have examined how to enhance supply chain sustainability from a single internal capability perspective or an external relationship perspective, few studies have examined the combined effects of internal and external factors to enhance supply chain sustainability. To fill this research gap, this study investigates the multivariate relationship from internal capabilities and external relationships mutually complementary perspective to improve supply chain sustainability. Grounded on dynamic capabilities theory and relational view, we put forward the supply chain dynamic capability construct under the internal perspective, and relationship construct with supply chain members under the external perspective. Based on the configuration theory, 270 data from enterprises were analyzed using fsQCA (fuzzy set qualitative comparative analysis), and the results shows that: first, there is no necessary condition for generating high supply chain sustainability, which means that individual factors do not lead to high supply chain sustainability; second, this study identified two paths to achieve high supply chain sustainability: capability‐driven and relationship‐driven, which reflects the multiple paths and complex mechanisms to achieve high supply chain sustainability; third, this study finds the important role of supply chain dynamic reconfiguring capability in forming high supply chain sustainability. These results can provide some theoretical guidance for enterprises to improve supply chain sustainability and achieve high quality economic development. [ABSTRACT FROM AUTHOR]

In order to maximize the benefit of building supply chain, the topology optimization method of building digital supply chain based on genetic neural network is studied. According to the overall structural characteristics of the building digital supply chain, customer demand data, supplier sales data, manufacturer production management data, and environmental policy exception data are collected to form a building digital supply chain data set. As input data, a building digital supply chain demand prediction model based on improved genetic LSTM neural network is constructed. Capture the needs of the building digital supply chain; according to the demand of suppliers, manufacturers and customers in building digital supply chain, a nonlinear 0–1 mixed integer programming model based on the newsboy model is established. According to the various information provided by the supplier, the ant colony algorithm is used to calculate the optimal supplier. After all suppliers are identified, the topology of the digital supply chain is constructed. So far, the optimization of the supply chain has been completed. The experimental data show that this method can accurately predict the demand of construction projects, the maximum error is less than 1.5%, and can obtain the best supplier selection results. Compared with before optimization, the profit of the structural digital supply chain after topology optimization increases the most. [ABSTRACT FROM AUTHOR]

Research has called for firms to prioritize reducing carbon emissions, however strategies to do so with external partners through institutional conformity and integration are lacking in research and practice. Drawing upon the resource-based view and institutional theory, the study in this paper proposes and tests a series of research hypotheses with Chinese firms. Structural equation modelling was used to analyse data and findings reveal carbon emissions reduction and low carbon institutional pressures are crucial forces driving external low carbon supply chain integration with external suppliers and customers. Further, low carbon supply chain integration overall positively impacts a firm's environmental performance, external customer integration positively impacts a firm's financial performance, and environmental performance plays a mediating role between external low carbon supply chain integration and financial performance. This study contributes by shedding new light on two patterns of external low carbon supply chain integration compared to prior studies. [ABSTRACT FROM AUTHOR]

Blockchain technology has reshaped how members of supply chains transfer information, effectively avoiding the phenomenon of information silos and helping to improve the emissions reduction performance and profit of each subject in the supply chain. It is now critical to understand how supply chain members can be encouraged to collaboratively invest in low-carbon service platforms based on blockchain technology to realise chain-wide systematic carbon reduction. In this regard, considering the time-dynamic characteristics of enterprise emissions reduction, this paper establishes a differential game model of collaborative emissions reduction in a low-carbon supply chain composed of a Stackelberg leader manufacturer and a supplier. We compare and analyse the four investment decision scenarios regarding whether the supplier and manufacturer invest in the blockchain low-carbon service platform under decentralised decision-making, as well as the equilibrium solutions of supply chain members under centralised decision-making scenarios by solving the Hamilton function. Finally, we introduce a bilateral cost-sharing contract to make the supply chain perfectly coordinated. We find that the significant unit return is an important incentive for supply chain members to take the lead in investing in a low carbon service platform (LCSP). In this regard, when only one member invests, the other one demonstrates free-riding behaviour. Under centralised decision-making, the supply chain can achieve Pareto optimality, and the bilateral cost-sharing contract can achieve perfect coordination of the supply chain, which is the best choice for the decision-makers of low-carbon supply chains. As the influence level of the LCSP gradually increases from small to large, the optimal decision-making of supply chain members gradually transitions from waiting for the right time to "hitchhike" to a strong willingness to cooperate. This study is of great reference value and practical significance for economic entities to improve profits, promote systematic carbon reduction in the whole chain and promote the sustainable development of low-carbon supply chains. [ABSTRACT FROM AUTHOR]

This paper considers an infinitely repeated competition between manufacturer‐retailer supply chains. In every period, retailers privately observe the demand and manufacturers pay retailers 'information rents'. I study collusive equilibria between the supply chains that may or may not involve the retailers. I find that including forward‐looking retailers in the collusive scheme may facilitate or hinder collusion, depending on the likelihood of a high demand and the gap between a high and a low demand. Moreover, collusion on monopoly profits can be easier or more difficult to implement than collusion on upstream profits. [ABSTRACT FROM AUTHOR]

Efficient inventory management is essential for maintaining a balance between supply and demand in various industries. This research study aims to quantitatively examine the impact of supply chain delays, with a specific emphasis on lead times and in-transit amounts, inventory levels, and the ability to meet sales demands. Mathematical modeling and statistical analysis are utilized to create prediction models that assess the impact of variations in lead time and quantities in transit on inventory stability and fulfillment rates. The study used regression analysis to ascertain the relationships between the indicated parameters and inventory outcomes. Also, machine learning algorithms like Random Forest and Linear Regression are applied to predict possible disruptions and optimize inventory levels. The methodology followed focuses on the Tri-Model Fusion Stacking approach, which combines various models to improve the predicted accuracy and offer a more comprehensive analysis. The main goal of this research is to provide practical insights that help organizations optimize their inventory management techniques, resulting in cost reduction and enhanced service levels. The findings aim to simplify the modification of inventory management techniques in light of up-to-date supply chain information, providing a notable improvement in the resources available to supply chain experts. [ABSTRACT FROM AUTHOR]

Purpose: Neo-institutional theories and their constructs have so far only received limited attention in supply chain management literature. As recent supply chain disruptions and their ripple effects affect actors on a broader institutional level, supply chains are confronted with multiple new and emerging, often conflicting, institutional demands. This study aims to unpack the notion of institutional complexity behind supply chain disruptions and present a novel institutional framework to lower supply chain susceptibility and increase supply chain resilience. Design/methodology/approach: The authors identify the patterns of complexity that shape the supply chain susceptibility, namely, distance, diversity and ambiguity, and present three institutional responses to susceptibility to increase supply chain resilience, namely, institutional entrepreneurship, institutional alignment and institutional layering. Findings: This paper analyses the current situational relevance to better understand the various and patterned ways how logics influence both supply chain susceptibility and the supply chain resilience. The authors derive six propositions on how complexity can be reduced for supply chain susceptibility and can be increased for supply chain resilience. Originality/value: By expanding and extending research on institutional complexity to supply chains, the authors broaden how researchers in supply chain management view supply chain susceptibility, thereby providing managers with theory to think differently about supply chains and its resilience. [ABSTRACT FROM AUTHOR]

In a collaborative supply chain arrangement like vendor‐managed inventory, information on product demand at the point of sale is expected to be shared among members of the supply chain. However, in practice, obtaining such information can be costly, and some members may be unwilling or unable to provide the necessary access to the data. As such, large collaborative supply chains with multiple members may operate under a mixed‐information scenario where point‐of‐sale demand information is not known for all customers. Other sources of demand information exist and are becoming more available along supply chains using Industry 4.0 technologies and can serve as a substitute, but the data may be noisy, distorted, and partially missing. Under mixed information, leveraging existing customers' point‐of‐sale demand to improve the intermittent demand forecast of customers with missing information has yet to be explored. We propose a supervised demand forecasting method that uses multivariate time series clustering to map multiple sources of demand data. Members with missing downstream demand data have their resulting demand forecast improved by averaging over customers with similar delivery patterns for their final demand forecast. Our results show up to a 10% accuracy improvement over traditional intermittent demand forecasting methods with missing information. [ABSTRACT FROM AUTHOR]

In the context of a supply chain, individuals engage in cooperative efforts to optimize their financial gains. The present article represents a study of a supply chain model that incorporates a two-level trade credit policy. The model focuses on a scenario where a supplier offers a product with a market demand that is reliant on the credit duration. The study centers on the strategies employed by suppliers to motivate retailers to increase their orders through the use of trade credit, with the aim of maximizing their own profits. The analysis takes into account the influence of credit perioddependent default customers. A set of examples is provided and the sensitivity is studied to show the recommended technique. Finally, the equilibrium solution has been derived from the supplier Stackelberg game and examined using numerical examples in the scenario when the supply offers a higher credit than the retailer. The outcomes of the numerical illustrations indicate that a supplier can achieve greater profitability by electing an adequate range of credit periods. Furthermore, this study demonstrates a significant correlation between the duration of credit, market demand, and the profitability of both the retailer and supplier with the demand coefficient, the price involved in the model, and the coefficient of default risk. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Current environmental issues and government requirements, together with pressure from the market and other stakeholders, emphasise the importance of partner selection in constructing and operating sustainable supply chains. Strategic items, which carry both high supply risk and high importance of purchase, are particularly important in sustainable supply chains. This paper presents an integrated decision-making model, which aims to solve the partner selection and order allocation problem for strategic items in sustainable supply chains. In the proposed model, weightings of different decision-makers are first calculated using Trapezoidal Fuzzy Numbers. Then, Taguchi loss function is used to evaluate the relative importance of potential partners, with the weighting results of criteria by Best-Worst Method. Finally, considering the weights of different potential partners, Particle Swarm Optimisation (PSO) is used to solve the multi-objective programming problem, and Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) is applied to identify the most appropriate Pareto solution for sustainable partner selection and order allocation of strategic items. An illustrative application of the proposed model is undertaken in a leading Chinese LED lighting manufacturer to show its effectiveness and applicability. [ABSTRACT FROM AUTHOR]

The bullwhip effect represents a major source of supply chain inefficiency. Traditional OM analytical approaches and theories view vertical integration as a countermeasure to the bullwhip effect. Despite its intuitive appeal, this relationship has yet to be rigorously examined. To be specific, a firm may choose backward integration to tighten its grip on the supply and production side, or forward integration to control over the demand and distribution side. The effect of different integration could be diverse depending on the firm's supply chain position, but research on this link is limited. Driven by a large dataset containing 292,080 detailed business information of listed firms in China, we empirically examine the impact of forward and backward vertical integration on the bullwhip effect, as well as the moderating role of the firms' supply chain positions. We find that: (1) forward vertical integration does reduce the bullwhip effect, and this mitigation effect is more pronounced for firms located further downstream; (2) the magnitude and direction of backward vertical integration effects are diverse. It has a strong mitigation effect on the bullwhip effect for upstream firms, and when firms are located further downstream, backward vertical integration will surprisingly increase the bullwhip effect. [ABSTRACT FROM AUTHOR]

This study mainly investigates the effects of supply chain network centrality on firm innovation output. We uncover that supply chain network centrality has a negative impact on firm innovation. The negative impact of network centrality on corporate innovation quantity is stronger when economic policy uncertainty is higher and the firm belongs to high-tech industries. Similarly, the detrimental effect of network centrality on corporate innovation quality is magnified when the level of marketization is lower and the firm belongs to high-tech industries. Firms with high supply chain network centrality are associated with more severe short-sightedness, higher transaction costs, and greater operational risks, and thus inhibits firm innovation output. [ABSTRACT FROM AUTHOR]

The construction supply chain confronts interruption risks that raise significant concerns regarding industry safety and stability. Consequently, exploring risk management strategies from both enterprise and supply chain network perspectives is crucial. This study employs complex network theory and the cascade failure model to propose a methodology tailored to the unique characteristics of the construction supply chain, facilitating the identification of key risk nodes and the conduct of invulnerability analyses. By evaluating the importance of construction enterprise nodes and their risk propagation ability during cascade failures, this method enables the comprehensive identification of key risk node enterprises within the construction supply chain network. Furthermore, this study examines and discusses strategies for enhancing network invulnerability by taking into account node capacity, load, and resilience. Empirical results indicate that the key nodes and risk nodes in the construction supply chain network are mainly located upstream and downstream, displaying specific distribution patterns. In addition to core enterprises, key risk nodes comprise some strong suppliers at the intermediary and lower tiers of the supply chain. Adjustments to node enterprise parameters like capacity, load, and resilience have diverse impacts on the invulnerability of the construction supply chain network. This study clarifies the distribution patterns of key risk nodes within the construction supply chain network and the variations in network invulnerability under particular conditions, providing valuable insights for risk management decision-making. [ABSTRACT FROM AUTHOR]

The demand for fresh food has become a frequent high demand commodity in everyday living and accounts for a larger share of the retail consumer market. As the quality of fresh foods deteriorates from harvest to consumption due to internal or external factors, it is important to label or mark fresh products or their package directly on the surface or on the top. In recent years, there has been a growing demand for labels to monitor the quality of various fresh food products. Sellers and consumers can easily determine whether a product is edible by observing visual changes in the detection label without opening the package for visual or olfactory inspection. This review summarizes the latest research findings on advances in fresh food quality deterioration and the application of suitable detection labels in the supply chain. It highlights diverse detection labels, modification of label functionality, and several latest shelf-life prediction systems. Finally, recommendations and prospects for future research in the development of fresh detection labels are provided. This paper allows relevant researchers to quickly obtain information on food quality inspection labels and their problems to be solved. [ABSTRACT FROM AUTHOR]