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The emergence of renewable energy microgrids (REM)-supported logistics parks reflects the urgent social requirement for sustainability facing energy crisis and climate change. Focusing on the emergency REM capacity planning and dynamic inventory operations problem for a REM-supported cold warehouse, this paper constructs a novel two-stage stochastic optimization method to comprehensively minimise long-term investment and short-term emergency operation costs of the system, while improving the resilience of energy-constrained supply chain management of perishable products. In particular, we formulate the second stage emergency operation problem as a Markov decision process that considers the interaction between energy and operational decisions constrained by intermittent of renewable energy, the randomness of the occurrence time, and the balance between power supply and temperature changes of the cold warehouse. We propose a novel two-phase PSO-based MPC algorithm to solve the entire problem. We also examine the effectiveness of our algorithm via an empirical study based on the data in East China. Nine typical scenarios clustered from the real data suggest different optimal capacity planning and operational policies. The empirical results show that it can reduce an overall 9% of operating costs on average compared to other heuristic policies. Moreover, installing REM can improve the resilience of power systems by 23% (risk impact area reduction ratio) and improve the resilience of inventory systems by 49%. [ABSTRACT FROM AUTHOR]

Predictive analytics is the approach to business analytics that answers the question of what might happen in the future. Although predictive information is critical for making forward-looking decisions, traditional approaches struggle to cope with the increasing uncertainty and complexity that characterise modern supply chains. Simulation is limited by insufficient timeliness, while machine learning is constrained by poor interpretability and data scarcity. Inspired by the complementary nature of simulation and machine learning, an integrated predictive analytics approach is proposed and applied to a humanitarian supply chain. By coupling simulation and machine learning, predictive models can be developed with limited historical data, and pre-crisis performance assessment can be performed to facilitate timely and informed decisions. The proposed approach enables managers to gain valuable insights into the complex evolution of the uncertain future, which also opens up the possibility of further integration with optimisation and digital twins. [ABSTRACT FROM AUTHOR]

Based on the policy incentives for equity financing and firms' awareness of managing supply disruption risk, this paper examines a two-tier supply chain. A large manufacturer can purchase products either from a capital-constrained unreliable supplier who has disruption risk or a reliable backup supplier with a higher cost. We investigate the value and interactive use of the backup supplier and equity financing on firms' performances. The results show both the backup supplier and equity financing alone can always benefit the manufacturer, but the unreliable supplier can become worse off. However, when the backup supplier and equity financing interact, their impact changes dramatically. Under equity financing, the backup supplier can make the unreliable supplier better, and the effect of the backup supplier on disruption risk management differs with different wholesale prices. Moreover, with a backup supplier, equity financing can benefit both the manufacturer and the unreliable supplier. Specifically, with the backup supplier, the unreliable supplier can lose all autonomy on whether or not to raise equity financing. Then, the manufacturer and unreliable supplier can achieve Pareto optimality due to 'bidirectional free riding'. These insights provide strategic guidance for product ordering, enabling firms to manage disruption risk better and achieve high profitability. [ABSTRACT FROM AUTHOR]

Blockchain has gained momentum as a disruptive technology in supply chain management against its introduction as a finance-related instrument. Nevertheless, the developing academic understanding and the limited practical implications lead to insufficient insights into the use of blockchain technology, particularly in the supply chain finance (SCF) domain. Thus, the expected potential of blockchain technology remains underexplored. Accordingly, this study explicates this situation by examining the extant literature findings and web-based big data that can provide evidence about the real needs in supply chains, and investigating how blockchain emerges as a disruptive SCF-oriented technology. The study employs a web analytics method, Search Engine Results Page (SERP) analysis which considers the trends in blockchain technology use and the interactions between blockchain, supply chain and finance appearing in Google searches. The SERP method examined real-time clicks, web traffics and most commonly asked questions about blockchain. The SERP findings revealed that the interest in blockchain technology neither focused on finance nor data privacy as emphasised in the literature but mainly on the benefits of increasing digitalisation and efficiency in supply chains. The results offered practical implications for capturing recent blockchain- and supply chain-related trends and designing more digital and efficient supply chains. [ABSTRACT FROM AUTHOR]

The supply chain is an important source of knowledge that enables potential emerging technologies and, in this ecosystem, logistics are regarded as an intermediary for disseminating innovative solutions in a coordinated manner. As an emerging solution in the supply chain area, blockchain has recently been discussed as a disruptive technology and has received growing attention from academics and practitioners. Despite this interest, insufficient knowledge on the potential benefits and risks of blockchain technology causes vagueness for its successful implementation. Therefore, since effective management of logistics and supply chain operations through advanced solutions is of utmost importance, adopting an innovative approach rather than providing anectodal evidences or narrative expressions plays a critical role in blockchain adoption. Accordingly, this research aims to an in-depth analysis of the blockchain in logistics and supply chain by investigating enablers, barriers, and risks of this adoption. To this end, through employing both the Methodi Ordinatio and the narrative network analyses, the future direction of blockchain adoption is presented in light of the presented current state of knowledge. Consequently, the obtained findings offer academic and practical insights into the ambiguous, insufficiently explained, and conflicted areas in the relationship between blockchain technologies and logistics and supply chain contexts. [ABSTRACT FROM AUTHOR]

Small and medium enterprises (SMEs) play a critical role in supply chains and social stability. Unfortunately, SMEs often lack access to traditional bank financing. To develop SME suppliers, some creditworthy companies have built platforms to coordinate banks and suppliers by employing purchase order financing (POF). After noting that SMEs differ in terms of their operational flexibility and uncertainty, this research examines optimal purchasing portfolios on such platforms. Specifically, we construct a Stackelberg model involving one buyer and two suppliers and analyse the Karush–Kuhn–Tucker necessary conditions for a buyer's strategy upon which the optimal portfolio can be achieved. According to the experiments that we design to simulate about 200,000 various scenarios, the large buyer only needs to consider the top five strategies. The choice of strategy mainly depends on cost differences of suppliers, and flexibility can be used as an identifier of the purchase quantity. [ABSTRACT FROM AUTHOR]

This paper proposes a service-oriented manufacturing strategy in a two-echelon supply chain with random demand. When there is no inventory for the retailer to meet demand, customers can choose to order products through the retailer and products will be delivered to them by the manufacturer directly in the promised time, and we call this delivery service in service-oriented manufacturing. We employ a Stackelberg game-theoretic model to analyse the procurement quantity and delivery time decisions by the manufacturer as the leader and the retailer as the follower. Using the performance of the pure-manufacturing strategy as a benchmark, our main results follow. First, the equilibrium strategies of the two players are obtained. Clear decision rules are also given. Second, delivery service in service-oriented manufacturing can be an effective way to reduce the holding cost of the retailer. Third, we describe the customer loss caused by waiting and find how the manufacturer influences procurement quantity of the retailer through the decision of delivery time. Finally, delivery service in service-oriented manufacturing cannot always improve the profit of the manufacturer and the retailer. We give guidance for managers to provide it. [ABSTRACT FROM AUTHOR]

To overcome product homogenisation issues, an increasing number of supply chain members have been binding their competitive advantages to services which extend supply chain competition to a new dimension. This paper proposes a product service supply chain (PSSC) network competition model with multiple competing manufacturers and retailers offering demand-enhancing and costly services. In order to obtain the decision-making results in a non-cooperative game context, equilibrium conditions are established using variational inequality, and the qualitative properties are discussed. We compare the two competition scenarios, price competition only and simultaneous price and service competition, to discover the impact of service-offering on supply chain members. After introducing the service competition, both manufacturers and retailers realise higher profits and marginal profits with the same service costs. In contrast, the manufacturers' marginal profits achieve higher growth rates. We also find that (a) the increase of the demand sensitivities to the service levels of retailers would contribute more to the revenue growth of the whole PSSC network and (b) when service costs are different for manufacturers and retailers, the optimal decision-making on service levels are not only affected by the service costs of the members in the same tier but also correlated with those in other tiers. [ABSTRACT FROM AUTHOR]

The booming development of customised e-commerce makes e-commerce supply chains experience a severe test of consumer service level (CSL). An efficient e-commerce supply chain resilience optimisation method addressing economic performance and service performance is proposed to improve customised services under disruption risks. The proposed method includes a hybrid strategy considering both a resistance strategy with blockchain (BCT) adoption and time-dependent recovery strategies simultaneously. A two-stage multi-period multi-product stochastic programming with BCT adoption is then proposed, which (1) implements BCT as the resistance strategy in the pre-disruption stage; (2) collaborates four recovery strategies in the post-disruption stage; (3) supports the e-tailer in making decisions and optimises his profit and order fulfillment time while taking product priorities into account. Using the actual data of Chinese e-commerce during the public health emergency in 2020, it is demonstrated that (1) the applicability of the model with BCT adoption in both supply chain resilience and CSL improvement; (2) the performance of the hybrid strategy in long-term disruption management; (3) the efficiency and robustness of the proposed solution approach for multi-objective high-dimensional stochastic programming problems. E-tailers can optimise decision-making under long-term disruptions by the proposed methodology in practices. [ABSTRACT FROM AUTHOR]

This study examines the relationship between advertising and financing decisions in an online supply chain consisting of an e-platform and a capital-constrained retailer. The e-platform is the leader in a Stackelberg game, and the interaction is modelled in two advertising scenarios. The results indicate that advertising can reduce risk and is always beneficial, with an e-platform willing to support the retailer only when the former decides on the advertising level. When providing both advertising and financing services, the e-platform gains the ability to directly regulate the retailer's ordering decisions, thereby increasing its strategic flexibility. [ABSTRACT FROM AUTHOR]

Compared to the traditional channel, where a retailer bears the inventory risk, the drop-shipping channel operates with a distinct approach: the retailer avoids stocking products while the manufacturer directly handles stocking and shipping to consumers. Due to the different inventory risk allocations, the two channels have different product qualities and profits for the manufacturer and retailer. In this study, we investigate product quality decision of the manufacturer and delve into the impact of product quality on the manufacturer's and retailer's profitability. First, we find that product quality can be weakly higher in the drop-shipping channel than that in the traditional channel. This is because the drop-shipping channel allows the manufacturer who undertakes demand uncertainty to charge a higher wholesale price, resulting in a higher product quality. Second, our study reveals that the traditional channel can concurrently yield higher profits for the manufacturer and retailer when product quality is considered, which is in contrast to the previous works. Third, in the traditional channel, as demand uncertainty rises, the retailer's production quantity increases, while the manufacturer's product quality decreases. Finally, our results indicate that the product quality is more sensitive to the shipping cost when demand uncertainty is low. [ABSTRACT FROM AUTHOR]

This document discusses the importance of carbon reduction engineering in combating global climate change. It highlights the role of production and supply chain management in achieving carbon neutrality and reducing carbon emissions. The document presents 20 selected research papers that cover various aspects of production optimization in carbon reduction engineering, including carbon reduction in the production process, low-carbon and sustainable supply chains, assessment and optimization methodologies, and policy instruments. The papers provide insights into topics such as scheduling optimization, renewable energy production, carbon emission efficiency, sustainable consumption, government subsidizing arrangements, and the impact of policy instruments on carbon reduction. The document expresses gratitude to the authors and reviewers for their contributions and acknowledges the support of the International Journal of Production Research. [Extracted from the article]

The customer order decoupling point (CODP) is the point in the supply chain where the product is linked to a customer order and is, by definition, the last stock point along the supply chain. The CODP decouples the upstream operations that are made to stock from the downstream operations that are triggered by customer orders. We employed a systematic literature review of the empirical research on the CODP in operations and supply chain management (OSCM). We identified 40 articles that explicitly contributed with empirical results concerning factors and characteristics for the operations upstream versus downstream of the CODP, or between make-to-stock (MTS) and make-to-order (MTO) operations. The 32 factors that were identified were grouped into four main categories: market and product factors, operations factors, supply chain factors, and performance measures. Based on the content analysis, we propose a framework that provides a holistic view on the CODP. The distinctive differences between MTS and MTO characteristics strongly suggest that there are two configurations: one for the upstream MTS-type operations and another for the downstream MTO-type operations. We discuss implications for research and practice and provide suggestions for further research. [ABSTRACT FROM AUTHOR]

Inspired by the global budget concept in health care, we propose an innovative subsidy scheme in which governments do not commit the subsidy amount in advance but determine it by the end of the subsidy period. The performance of the traditional and proposed subsidy schemes is evaluated in an oligopoly without competition, where each manufacturer decides its product quality and production quantity under the diseconomies of scale in production. Both types of schemes can take into account product quality or not. Our results show that compared to the traditional scheme, the proposed scheme drives manufacturers to reduce production quantity but improves product quality and brings them higher profits. Furthermore, the scheme results in greater social welfare when the subsidy budget is large. Finally, we conduct robustness checking by considering the market competition and absence of the diseconomies of scale, respectively. The result shows that the main findings in the basic model continue to hold, while there are additional findings. In the first scenario, as the market competition intensity increases, our proposed scheme becomes more preferable to the manufacturers and the government. In the second scenario, subsidy schemes that take product quality into account are never preferable. [ABSTRACT FROM AUTHOR]

This research examines the transformative potential of artificial intelligence (AI) in general and Generative AI (GAI) in particular in supply chain and operations management (SCOM). Through the lens of the resource-based view and based on key AI capabilities such as learning, perception, prediction, interaction, adaptation, and reasoning, we explore how AI and GAI can impact 13 distinct SCOM decision-making areas. These areas include but are not limited to demand forecasting, inventory management, supply chain design, and risk management. With its outcomes, this study provides a comprehensive understanding of AI and GAI's functionality and applications in the SCOM context, offering a practical framework for both practitioners and researchers. The proposed framework systematically identifies where and how AI and GAI can be applied in SCOM, focussing on decision-making enhancement, process optimisation, investment prioritisation, and skills development. Managers can use it as a guidance to evaluate their operational processes and identify areas where AI and GAI can deliver improved efficiency, accuracy, resilience, and overall effectiveness. The research underscores that AI and GAI, with their multifaceted capabilities and applications, open a revolutionary potential and substantial implications for future SCOM practices, innovations, and research. [ABSTRACT FROM AUTHOR]

ChatGPT and generative artificial intelligence (Gen-AI) are transforming firms and supply chains. However, the empirical literature reporting the benefits, challenges, and outlook of these nascent technologies in operations and supply chain management (OSCM) is limited. This study surveys current projects and perceptions of these technologies in US (n = 119) and UK (n = 181) supply chains. We found that projects range from proof-of-concept to full implementation, with a main focus on operational gains, such as improved customer satisfaction, cost minimisation, and process efficiencies. The main challenges concern data, technological and organisational issues. Expected benefits are dominated by cost savings and enhanced customer experience, but also include increased automation and sustainability. Industries were found to cluster around six groups according to perceived benefits and implementation challenges. Our findings contribute to the emerging literature on Gen-AI use in OSCM, and to management practice by mapping the benefits, challenges, outlook, and maturity level of Gen-AI projects in supply chains. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is becoming a critical engine that powers a range of technology solutions. It is rapidly playing a vital role in supply chain and operations management. In this paper, we present a research agenda of how researchers and practitioners alike can study the potential adoption of AI-powered tools for benefits in the supply chain. We draw on the unified theory of acceptance and use of technology and suggest directions for research that leverage a mixed-methods research approach. Because these technologies are in a nascent stage and evolving rapidly, a mixed-methods approach will allow for a careful examination of potential features and how their adoption can be fostered, with specific benefits in mind. We present three-specific research directions rooted in the developmental, completeness, and expansion purposes of mixed-methods research. [ABSTRACT FROM AUTHOR]

Despite the exponential growth of artificial intelligence (AI) research in operations, supply chain, and productions management literature, empirical insights on how organisational behavioural mechanisms at the human–technology interface will facilitate AI adoption in small- and medium-sized enterprises (SMEs), and subsequent impact of the adoption on sustainable practices and supply chain resilience (SCR) is under-researched. To bridge these gaps, we integrate resource orchestration and knowledge-based view theoretical perspectives to develop a novel structural model examining antecedents to SCR and AI adoption, considering AI adoption as a pivot for facilitating SCR. The structural equation modelling technique was employed on the data collected from 280 Vietnamese manufacturing SMEs' operations managers. Our results demonstrate that leadership will drive AI adoption by creating a data-driven, digital and conducive culture, and strengthening employee skills and competencies. Furthermore, AI adoption positively influences CE practices, SC agility and risk management, which will help to achieve SCR. For managers, the importance of internal organisational employee-centric mechanisms to create value from AI adoption without impeding business value is highlighted. We reveal the enablers that will help in transforming SMEs to become resilient by deriving appropriate responses to unprecedented disruptions through data-driven decision-making leveraging AI adoption. [ABSTRACT FROM AUTHOR]

Modern supply chains are complex, interconnected systems that contain emergent, invisible dependencies. Lack of visibility often hinders effective risk planning and results in delayed discovery of supply chain problems, with examples ranging from product contamination, unsustainable production practices, or exposure to suppliers clustered in geographical areas prone to natural or man-made disasters. Initiatives that rely on manual collection of data often fail due to supply chain complexity and unwillingness of suppliers to share data. In this paper, we propose a neurosymbolic machine learning technique to proactively uncover hidden risks in supply chains and discover new information. Our method uses a combination of graph neural networks and knowledge graph reasoning. Unlike existing research our model is able to infer multiple types of hidden relationship risks, presenting a step change in automated supply chain surveillance. The approach has been tested on two empirical datasets from the automotive and energy industries, illustrating that it can provide inference in multiple types of links such as companies, products, production capabilities, certifications; thereby facilitating complex queries that go beyond who-supplies-whom. As such, additional risk insights can emerge from graph structure, providing practitioners with new knowledge. [ABSTRACT FROM AUTHOR]

This study posits that the use of artificial intelligence (AI) enables supply chains (SCs) to dynamically react to volatile environments, and alleviate potentially costly decision-makings for small-medium enterprises (SMEs). Building on a resource-based view, this work examines the impact of AI on SC risk management for SMEs. A structural model comprising of AI-risk management capabilities, SC re-engineering capabilities and supply chain agility (SCA) was developed and tested based on data collected from executives, managers and senior managers of SMEs The main methodological approach used in this study is partial least squares-based structural equation modelling (PLS-SEM) and artificial neural network (ANN). The results identified the use of AI for risk management influences SC re-engineering capabilities and agility. Re-engineering capabilities further affect and mediate agility. PLS-SEM and ANN were compared and the results revealed consistency for models A and B. Current levels of demand uncertainties in the SC challenges managers in making complex trade-off decisions that require huge management resources in very limited time. With AI, it is possible to model various scenarios to answer crucial questions that archaic infrastructures are not able to. This study combines a multi-construct agility concept and identified non-linear relationships in the model. [ABSTRACT FROM AUTHOR]

With the rapid development of e-commerce, both gray products and counterfeit products are particularly serious in the luxury industry. This paper develops an analytical framework to investigate the interaction among the gray market, the counterfeit market and the authorised market, and examines how luxury manufacturers should manage unfair competition from gray products and/or counterfeit products. First, regardless of the existence of counterfeit products, the manufacturer can benefit from gray products when the status utility is moderate. Second, counterfeit products may benefit the manufacturer, depending on the availability of gray products and the physical resemblance of counterfeit products. Third, gray product may benefit the counterfeiter while counterfeit product always harms the gray marketer. Finally, we reveal that gray products can help luxury manufacturers fight against counterfeit products. In particular, gray products can reduce the demand for counterfeit products and even drive counterfeit products out of the market when the physical resemblance of counterfeit products is sufficiently low. Our findings provide several new managerial insights for luxury manufacturers and gray marketers. [ABSTRACT FROM AUTHOR]

This document is a special issue of the International Journal of Production Research focused on service-oriented manufacturing supply chain management in the context of Industry 4.0. Service-oriented manufacturing (SOM) is an emerging paradigm where manufacturers transform their products into platforms using Industry 4.0 technologies, allowing for communication between customers and manufacturers. This shift enhances the flow of information through the supply chain and creates new operational challenges. The special issue includes 16 articles covering various sub-areas such as mechanism design, supply chain contracts, behavioural modelling, emerging business models, optimisation techniques, product design, and smart manufacturing. The papers provide insights and practical applications to advance service-oriented manufacturing supply chain management in the Industry 4.0 era. [Extracted from the article]

Artificial intelligence (AI) is increasingly considered a source of competitive advantage in operations and supply chain management (OSCM). However, many organisations still struggle to adopt it successfully and empirical studies providing clear indications are scarce in the literature. This research aims to shed light on how AI applications can support OSCM processes and to identify benefits and barriers to their implementation. To this end, it conducts a multiple case study with semi-structured interviews in six companies, totalling 17 implementation cases. The Supply Chain Operations Reference (SCOR) model guided the entire study and the analysis of the results by targeting specific processes. The results highlighted how AI methods in OSCM can increase the companies' competitiveness by reducing costs and lead times and improving service levels, quality, safety, and sustainability. However, they also identify barriers in the implementation of AI, such as ensuring data quality, lack of specific skills, need for high investments, lack of clarity on economic benefits and lack of experience in cost analysis for AI projects. Although the nature of the study is not suitable for wide generalisation, it offers clear guidance for practitioners facing AI dilemmas in specific SCOR processes and provides the basis for further future research. [ABSTRACT FROM AUTHOR]

Inventory planning in fashion markets is highly challenging, owing to uncertain demand; yet, in making inventory decisions, retailers may be able to capitalise on high substitutability between products. This research develops single-period inventory-management models describing a market with two substitutable products, under stockout-based substitution; i.e. when a customer's preferred product is out-of-stock, s/he may choose to purchase the substitute. Two settings are considered: centralised (a single retailer who sells both products) and competitive (two retailers, each selling one product). For each setting, we derive closed-form analytical solutions for the inventory levels that maximise expected profit. The model is further enriched with sales data from an online apparel retailer offering substitutable products (a sneaker in different colours), and we analyse the sensitivity of the optimal inventory levels and profits to parameter values. Key findings include the following: (i) Under competitive conditions, both retailers always order positive inventory so as not to lose customers. However, in a single-retailer setting, there are situations in which the retailer orders inventory for only one product. (ii) The optimal inventory levels and corresponding profits are highly sensitive to consumers' willingness to substitute between products. These findings provide concrete insights that can guide fashion brands' inventory-management decisions. [ABSTRACT FROM AUTHOR]

In the rapidly evolving landscape, digitising the operations and facilities in a supply chain network is essential to make the system autonomous and develop strategies for enhancing resilience, transparency, and efficiency. The COVID-19 pandemic highlights the necessity of sustainable solutions for the hybrid mode of operations. To overcome several challenges, including price optimisation, demand forecasting under uncertainty, supply-demand gap reduction, take into account vulnerability, competitive business environment and risk, the supply chain needs to be streamlined with technology-driven infrastructures incorporating physical and information flow into overall supply chain processes. The digitisation aspect encompasses adopting cutting-edge technologies such as enterprise resource planning (ERP) for supply chain visibility, e-hailing platforms, real-time data analytics, the Internet of Things (IoT) and Internet of Behaviour (IoB), blockchain-driven technology, as well as additive manufacturing, enabling seamless connectivity and communication among diverse stakeholders. This revolution enables strategic integration of various entities and state of the art data-driven decision-making, providing real-time insights into logistics movements, demand forecasting, production planning and inventory levels. Supply chain digitisation and management emphasises collaboration with supply chain partners to identify important factors, optimise costs and enhance overall supply chain resilience. Digitisation and management are technological evolutions and strategic shifts integrating analytical tools, allowing businesses to formulate models to improve performance. The implementation of blockchain-driven technology solidifies trust and safety transactions by creating an immutable and transparent log, mitigating threats and enhancing traceability. Digitisation and management exemplify a transformative journey towards a more connected, data-driven, and agile global supply chain ecosystem. [ABSTRACT FROM AUTHOR]

Although supply chain ecosystem health (SCE Health) is receiving attention in relation to environmental uncertainty, its conception and measurement are largely undocumented, and how to pursue SCE Health under environmental turbulence is unclear. Supply chain learning (SCL) is an important way to build dynamic capabilities, and whether it can empower the achievement of SCE Health is worthy of investigative study. Therefore, grounded in the dynamic capabilities theory, a survey data-based structural equation modelling (SEM) approach is employed. Based on four experts' opinions and an in-depth literature review, 47 measurement items (11 for SCL, 28 for SCE Health, and 8 for environmental turbulence) were identified in the questionnaire design. Further, 208 valid questionnaires from the field survey of supply chain management (SCM)-related firms in China were collected and used for SEM analysis. The results show that the internal learning of SCL stimulates its external learning. SCL empowers the pursuit of SCE Health, which is strengthened under higher environmental turbulence. The theoretical framework and results also derive practical insights and support from 11 interviewees of five companies. [ABSTRACT FROM AUTHOR]

International trade, through global supply chains, is central to global sustainable production and consumption. Redistribution of environmental resources impacts through international trade has become apparent in ecological research – and may have long-term design and planning implications for production and supply chain management. However, current trade and production accounting methods are still incapable of providing accurate and reliable results for policymakers and organisational decision makers to manage global and supply chain trade issues. In this study, a blockchain-based conceptual framework for embodied environmental resources accounting in trade is proposed to address global supply chain and trade issues. Framework design, benefits, and challenges are also discussed. Future research and linkage to theory are also provided. This study provides a strong systemic foundation for managing environmental resources at the nexus of international trade, sustainable production, and global supply chains. [ABSTRACT FROM AUTHOR]

This paper studies the universal point scheme with multiple retailers and a platform that implements the points within a channel. First, we analysed the equilibriums of the channel under the decentralised control and the mode of lateral cost-sharing among retailers. We found that retailers are willing to set the lowest point conversion ratios under the lateral cost-sharing mode compared with the decentralised and centralised control modes. The optimal conversion ratio of a retailer under the decentralised control is greater than the one under the centralised control when the cost spillover and double marginalisation are not significant. Next, we extended the model by considering the participation of new retailer. In this dynamic channel, the impact of the cost spillover phenomenon on the channel members' preferences is discussed. Third, we showed that the wholesale price contract for point management used in the real world has a limitation in terms of profit split. Following this, we proposed a buyback contract and showed the optimal contract parameters under which the channel's profit could be maximised and arbitrarily split. The managerial insights we obtained shed light on how to design a universal point scheme and select channel members to achieve an all-win scenario. [ABSTRACT FROM AUTHOR]

Distributed Ledger Technology (DLT) refers to multi-party systems that enables saving encrypted data across a peer-to-peer network of nodes, without central authority. While DLT applications have been mainly studied in finance, we conduct empirical research on DLT application in supply chain management, combining theory testing and theory elaborating case research. Applying the Theory of Affordance Actualisation, we identify five DLT affordances: (1) verify product origin and history, (2) exchange data on digital product models, (3) track and trace products' logistics, (4) simplify supply chain finance, and (5) automate payments. We identify and evaluate these affordances and also outline how these affordances can be actualised. We contribute to the discourse of DLT value creation and provide practical guidance to assess DLT potential in supply chains. We integrate our findings into the academic discussion on collaboration in viable, intertwined supply networks. [ABSTRACT FROM AUTHOR]

The circular economy (CE) seeks to maintain products and materials at their highest utility and value. The organisational and governmental policy have seised onto the CE philosophy to advance socio-economic and environmental development. CE remains an essentially contested concept – making its utilisation as a foundation for managerial and policy decisions challenging. Circularity assessment has not been systematically adopted, especially within supply chain management. Using critical scholarly and practical evidential foundation, we proposed a comprehensive set of metrics that can be utilised in supplier selection, monitoring, and development for circularity. These metrics include the macro, meso, and micro levels. A group decision-making method integrating best-worst method (BWM), regret theory (RT), and dual hesitant fuzzy sets (DHFS) for circular economy and circularity (CEC) supplier evaluation and selection is introduced – providing instrumental value for the identified metrics typology. The proposed BWM-DHFE-RT integrative analytical method can accommodate decisionmaker psychological behaviour under uncertainty while simultaneously capturing divergent or conflicting opinions of different decision-makers. An illustrative business scenario is utilised to demonstrate the application of the proposed method. Though the proposed CE performance metrics and methodology are used for CEC supplier management reasons they have broader applicability. Future research and application directions are discussed. [ABSTRACT FROM AUTHOR]

Digital twins became of greater interest to researchers and practitioners in supply chain and operations management (SCOM). Literature has addressed the need to understand digital twins in SCOM, mostly focusing on fragmented technological solutions and use cases. We start with an integrative literature review to determine which elements belong to research on digital twins in SCOM. We define the seven major elements of a digital twin in SCOM: technology, people, management, organisation, scope, task, and modelling. We also distinguish five major types of digital twins in SCOM: product, process, organisation, supply chain and network-of-networks. Illustration of a SCOM digital twin is provided using an anyLogistix example. We conclude that digital twins in SCOM are not merely a simulation-based replica of a real object but a complex socio-technical phenomenon involved in continuous human-artificial intelligence interactions. This leads to an understanding of the role of digital twins through the lens of Industry 5.0, reconfigurable and viable supply chains. Researchers and practitioners alike can use our framework to structure the knowledge on SCOM digital twins and consider all seven elements when designing and using digital twins. [ABSTRACT FROM AUTHOR]

This paper proposes a white-box perspective that portrays a supply chain delivery process as a network of related activities which remains to be improved. It addresses a critical disadvantage of supply chain delivery performance models, namely considering a delivery process as a whole and ignoring characteristics and relationships between activities in the delivery process. A delivery process is modeled using the Graphical Evaluation and Review Technique based on the characteristic function (CF-GERT). Based on the CF-GERT model, a framework for applying managerial effort to activities to improve overall delivery performance is proposed. Then, particle swarm optimization (PSO) based on the penalty function is used to solve the delivery performance improvement framework. Finally, a numerical case shows how applying efforts to activities can effectively improve delivery performance and demonstrates the influence of several parameters on the related costs. [ABSTRACT FROM AUTHOR]

The concept of the Physical Internet (PI) has been introduced as a vision for globally efficient and sustainable logistics. Examining the activities of the PI since its foundation, enormous efforts can be recognised in the political and business spheres. Furthermore, the topic has received considerable attention from logistics and supply chain management scientists. In this context, a wide variety of dimensions of the PI concept has been investigated. In contrast to some existing qualitative literature reviews, this study focuses on a quantitative review methodology to provide a holistic overview of the PI concept and its underlying dimensions and interrelations. Based on bibliometric performance analysis and science mapping, this research maps and connects the extant PI literature landscape. In doing so, the most important journals, researchers, and institutions in the PI field are identified. Furthermore, eight research topics are grouped thematically, including PI benefits and the challenge of its operationalisation, carriers and shippers in the PI network, PI foundations, smart product-service systems and services, hyperconnected city logistics, information and communication technology requirements, modular PI containers, and organisation and control of PI hubs. Based on the clustering of existing research, the study concludes by providing directions for future research. [ABSTRACT FROM AUTHOR]

While interfunctional collaboration remains well-studied within the marketing literature, this research is the first to empirically explore the effects of sales–supply chain management (S-SCM) collaboration among salespeople selling internationally. Survey data from 310 international salespeople provide initial empirical evidence showing that S-SCM collaboration can positively predict international salesperson performance outcomes. To show that the effect is unique and provide rare empirical evidence, the authors simultaneously account for the effects of multiple forms of cross-functional collaboration (i.e., sales–marketing collaboration and sales–research and development collaboration). Matching the survey responses with objective country-level data, the authors also find that the value of S-SCM collaboration varies across countries. In particular, the positive effects of S-SCM collaboration were amplified by logistics capacity (or "logistics friendliness") at the country level. The study's findings also indicate that the positive performance returns provided by S-SCM collaboration are even stronger for international salespeople focused on customer acquisition (vs. customer retention). Broadly, the study implies that, for optimal firm performance, those who are responsible for managing global supply chains should coordinate activities with those responsible for selling to global customers. [ABSTRACT FROM AUTHOR]

As instability becomes the norm, supply chain management is becoming increasingly complex and critical. As a result, supply chain managers must adapt to complex situations. Managing instability is a key expectation for these managers. One way to help them to manage this instability is to study resilience. Resilience is related to in the literature as the ability of a system to resist, adapt and recover from disruptions. Measuring and controlling supply chain resilience has therefore become a key issue for managers, especially in a context of instability. In 2013, the World Economic Forum [2013. Global Risks 2013. Davos, Switzerland: World Economic Forum] highlighted in its study, this priority for the surveyed companies to master this concept of resilience. To address this need, this paper presents an innovative approach to disruption and resilience management based on physics principles. It considers disruptions as forces that impact supply chain performance. These forces are created as a result of changes in the internal or external attributes of the supply chain. In this approach, supply chain performance is represented and visualised as a physical trajectory modelled in the framework of its performance indicators. Thus, disturbances are considered as forces that displace and deviate the supply chain's performance trajectory in its performance framework. [ABSTRACT FROM AUTHOR]

Operations management researchers and practitioners have shown increasing interest in incorporating sustainability into supply chain (SC) design models. This means that sustainability must be considered in all aspects of the SC, including location, inventory and transportation (LIT) decisions. Hence the aim of this article is to propose an optimisation model that incorporates: (i) LIT decisions in an integrated manner; (ii) the three sustainability (3S) aspects, i.e. economic, environmental and social, into each named decisions; and (iii) a closed-loop supply chain (CLSC) structure. The proposed formulation is a multi-objective mixed integer non-linear programming (MO-MINLP) model whose objectives consider minimisation of economic and social costs (economic aspect) and carbon emissions (environmental aspect), and maximisation of the social impact of SC operations (social aspect). A transformation technique is applied to one of the objective functions, which results in an MO-MILP model solved by the lexicographic method. This article focuses on commodity industries where only one finished product is manufactured. Hence the 3S-LIT model is validated with a randomly generated dataset and against a recently published alternative model applied to the copper mining industry. [ABSTRACT FROM AUTHOR]

Matching the supply of medical equipment with soaring demand caused by an epidemic event is a daunting challenge. Focusing on medical equipment manufacturers, this study empirically examines how supply chain management impacts manufacturers' responses to epidemic-driven demand. This study employs novel supply chain data from South Korea collected before and after the MERS (Middle East Respiratory Syndrome) epidemic event. In the results, we show that such an epidemic positively influences the sales performance of medical equipment manufacturers (i.e. a 10.2 percentage-point increase). To identify the mechanism behind this result, we provide evidence that increasing the supply base (i.e. the number of supply channels) enables medical equipment manufacturers to better respond to epidemic-driven demand and ultimately improves their sales performance. More interestingly, we find that medical equipment manufacturers with lower market status (i.e. lower market shares and lower supplier shares) expand their supply bases more extensively than other medical equipment manufacturers with higher market status do. Interpreting these results, we offer managerial insights into how medical equipment manufacturers can effectively manage their supply chains and improve their performance when responding to epidemic-driven demand. [ABSTRACT FROM AUTHOR]

Fashion knockoffs, which refer to the copycat behaviours of some brands in fashion apparel, are widely seen. It is commonly believed that the presence of fashion knockoffs harms the original-designer-label (ODL) product seller. Motivated by the industrial interviews and real-world observations, we build game-theoretical models to examine the impacts of fashion knockoffs on the ODL product supply chain and its agents with the consideration of risk attitudes. Explicitly, in the basic model, we consider a common manufacturer producing for both a knockoff product seller and a risk sensitive ODL product seller. The ODL product seller and the knockoff product seller make pricing decisions to optimise their own profits. We interestingly find that the presence of fashion knockoffs benefits the ODL product supply chain and its agents when (i) the ODL product seller is risk averse and the ratio of demand uncertainty is relatively small or (ii) the ODL product seller is risk seeking and the ratio of demand uncertainty is sufficiently large. The findings indicate that a risk averse (seeking) ODL product seller is more prone to benefit from the presence of fashion knockoffs when selling fashionable (classic) products. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has emerged as a complementary technology in supply chain research. However, the majority of AI approaches explored in this context afford little to no explainability, which is a significant barrier to a broader adoption of AI in supply chains. In recent years, the need for explainability has been a strong impetus for research in hybrid AI methodologies that combine neural architectures with logic-based reasoning, which are collectively referred to as Neurosymbolic AI. The aim of this paper is to provide a comprehensive overview of supply chain management literature that employs approaches within the neurosymbolic AI spectrum. To that end, a systematic review is conducted, followed by bibliometric, descriptive and thematic analyses on the identified studies. Our findings indicate that researchers have primarily focused on the limited subset of neurofuzzy approaches, while some supply chain applications, such as performance evaluation and sustainability, and sectors such as pharmaceutical and construction have received less attention. To help address these gaps, we propose five pillars of neurosymbolic AI research for supply chains and provide four use cases of applying unexplored neurosymbolic AI approaches to address typical problems in supply chain management, including a discussion of prerequisites for adopting such technologies. We envision that the findings and contributions of this survey will help encourage further research in neurosymbolic AI for supply chains and increase adoption of such technologies within supply chain practice. [ABSTRACT FROM AUTHOR]

Amid the escalating environmental crises and economic disparities, Circular Economy (CE) has garnered recognition as a pragmatic mechanism for achieving Sustainable Development Goals (SDGs). In response, several supply chain organisations are integrating CE strategies into their business operations and production processes. Despite these developments and since the introduction of Business Charter for Sustainable Development by the International Chamber of Commerce in 1991, the academic corpus comprehensively connecting CE research themes, catalysts, deterrents, practices with the SDGs has remained limited. To bridge this gap, we present a systematic literature review (SLR) of CE research in operations, supply chain and production management encompassing a time span of 31 years (January 1991 – June 2022), by sourcing, screening, and analysing articles obtained from multiple research databases. Our thematic coding analysis generated ten research themes, and subsequently linking them with relevant SDGs. Additionally, we interweaved CE catalysts and deterrents, establishing a connection with the SDGs. This is further enriched with CE strategies aimed at equipping business practitioners to enhance sustainable business performance and contributing to specific SDGs. Lastly, we delineate CE knowledge data management and priority actions frameworks to aid organisations to enhance employee capability and actively leverage digital technologies for implementing CE strategies. [ABSTRACT FROM AUTHOR]

Supply chain decarbonisation has become a strategic requirement in the era of a net-zero economy. Despite the significant role of Big Data Analytics (BDA) in decarbonising the supply chain (SC), no prior study has evaluated it systematically. The present study aims to provide a systematic literature review on the applications and outcomes of big data analytics in SC decarbonisation. A total of 69 papers on applying BDA technology for supply chain decarbonisation published between 2016 and 2021 have been selected following the PRISMA protocol. The findings show that the topic is evolving. Studies employed methods such as surveys (30), case studies (11), and conceptual research designs (8). Thematic analysis reveals that 65% of the studies are grounded in resource-advantage theories, organisational theories, and system theories. Studies from India and China (35%) dominate the topic, while most studies have been conducted on the food and manufacturing industries. Further, this study applied the Antecedent-Decision-Outcomes (ADO) framework in BDA-based SC decarbonisation. Antecedents include BDA resources and capabilities, workforce skills, and supplier capabilities. Decisions refer to improving decision-making across the supply chain. Outcomes refer to improving decarbonisation, sustainable growth, and sustainable innovativeness. Future research directions and questions are provided using the Theory-Context-Methodology (TCM) framework. [ABSTRACT FROM AUTHOR]

Catastrophe-related insurance (e.g. business interruption insurance) is an effective financing tool for global corporations to reduce economic losses caused by high impact events. Flexible operational planning is an often-used tool enabling rapid adjustment of operational plans for reducing catastrophe-related damage costs. The interaction between catastrophe insurance and flexible operations planning has rarely been studied. In this paper, we develop a stochastic programming model for a multi-echelon global supply chain network that we solve to investigate the impact of purchasing catastrophe insurance on supply chain operational planning in a catastrophe-prone environment. Computational simulations are developed for evaluating solution quality and measuring catastrophe-related damage costs. We find that it may be optimal for supply chains to scrap redundant products in catastrophes when customer demand falls below the expected level. Purchasing catastrophe insurance may encourage supply chains to scrap more products, which results in more catastrophe-related damages. From analysing supply chain costs, catastrophe-related damage costs, and operational plans, we find that a higher compensation rate of catastrophe insurance triggers more production activities being planned at the vulnerable node just before the vulnerable time period, especially for low residual value products. Finally, we give managerial insights to help reduce unnecessary damages in catastrophes. [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]

Traditional supply chain management faces challenges such as low level of information sharing and lack of transparency. Due to the features such as tamper-proof, reliability and traceability, the blockchain technology enhances the trust among stakeholders and enables transparent transactions and open collaboration, which can reduce the risk of supply chain disruptions. Accordingly, blockchain technology-based supply chain management has attracted more attention from academics and practitioners. However, existing review studies mainly focus on different industries or topics and lack a more comprehensive analysis. Therefore, this paper presents a systematic review integrating bibliometric analysis with theme analysis to understand the current research state in BT-SCM and discuss its future research trends. On the one hand, VOSviewer is used to conduct bibliometric analysis to explore the influences of existing studies from six aspects: publication year, author, country, keyword, journal, and article citation. On the other hand, the functional application of BT-SCM is discussed from logistics traceability, supply chain finance, supply chain collaboration, sustainable management and risk management to determine the research status, and the enablers and barriers of blockchain application in SCM are summarised to facilitate practitioners to adopt BT, and finally the potential research directions are proposed for scholars in this field. [ABSTRACT FROM AUTHOR]

The digital transformation involves both risks and opportunities for the sustainability of global supply chains. This systematic literature review of 64 peer-reviewed English journal articles aims to show how the adoption of digital technologies is related to (sustainable) supply chain management practices and associated sustainable outcomes. (Non)existing relationships between these constructs will be examined, which has not been done previously. Content, frequency, and contingency analyses are conducted from a practice-based view. The study reveals three main topics in the literature: (1) a mainstream eco-efficiency debate; (2) supplemented by a data-driven, comprehensive long-term perspective on environmental sustainability; and (3) hard-to-measure substantive sustainability aspects that can be fostered by communication, selective monitoring and certification. An integrated perspective of these three topics is proposed to facilitate a more viable sustainability approach. Based on the identified (non)existing relationships, researchers and practitioners learn about the digital technologies and practices they can use to improve supply chain sustainability. Importantly, it should be recognised that hardly quantifiable targets and related practices are obscured by large datasets. Future research should focus on the integration of economic aspects to ensure the compatibility of long-term substantial sustainability goals and the profitability of the entire supply chain. [ABSTRACT FROM AUTHOR]