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This paper aims to assess the findings of a research project that investigates the scope for lean strategies to be adopted in beef, lamb and pig supply chains.

The paper reports on action research carried out in three red meat supply chains. The methodology is inductive and qualitative, using a multi‐case, multi‐site approach. Each of the supply chains was analysed from farm gate to consumer, interviewing multiple participants at each stage of the supply chain.

The analysis demonstrates that, although a lean approach has been introduced in the pig supply chain, it is much more problematic in beef and lamb supply chains. Furthermore, the majority of participants in the UK pig supply chain – the first to adopt lean strategies – have not received the commercial improvement (the “stairway to heaven” of higher returns) that was anticipated. On the contrary, the majority of participants in this supply chain are experiencing a strategic “treadmill to oblivion” of continuous lean operational efficiency, but with low commercial returns.

The research is based upon three red meat supply chains – beef, lamb and pig. It would be beneficial if further in‐depth studies could be undertaken in other agri‐food supply chains to further validate the findings.

If government agencies and/or multiple retailers develop lean strategies in UK beef and lamb supply chains, it is not at all clear that this will benefit all parties in these chains. This raises important questions about the efficacy and appropriateness of lean strategies in supply chains that do not have the same demand, supply and power and leverage characteristics as those in which lean principles were first developed.

This paper should be of value to researchers in this area and to managers responsible for strategy formation in UK agri‐food supply chains.

Supply chain management (SCM) proficiency is generally associated with superior business performance. Yet, SCM research continues to focus predominantly on the performance of individual firms, rather than on the collective performance of multiple supply chain participants as espoused by the extended enterprise (EE) concept. In response to calls for quantitative studies that examine the collective performance of multiple supply chain participants, this research study compares the combined performance of triads comprising focal firms recognized for their relative SCM proficiency and their upstream (supplier) and downstream (customer) supply chain partners with that of their close industry competitors' triads.

The triadic, longitudinal examination of multiple supply chain participants' collective performance utilized archival financial data of the period 2007–2017 from the Compustat database and the supply chain (SPLC) function of Bloomberg.

Findings of this study indicated that supply chain triads that included focal firms recognized for their relative SCM proficiency experienced significantly lower sales and general administrative expenses and significantly higher productivity, return on assets and profitability over time than their close industry competitors' triads. However, contrary to expectations, the performance advantages identified did not extend to revenue growth.

Supply chain triads cannot fully represent entire supply chains or EEs. However, this study’s triadic analysis can be viewed as a practically achievable proxy for further validating the EE concept. Moreover, based on assertions that triadic studies are suitable for SCM research and on empirical studies that consistently show individual firms recognized for their relative SCM proficiency outperform competitors, the authors contend that the study’s findings appropriately corroborate the value of the EE concept.

Because such empirical evidence is so rare, the consistent, collective performance advantages identified in this study should be highly significant to managers.

Robust, longitudinal evidence that supply chain triads which include focal firms recognized for relative SCM proficiency collectively outperform their close industry competitors' triads extends generally accepted associations between SCM proficiency and business performance, suggesting that the application of extended resource-based view (ERBV) in supply chain contexts warrants further examination and further substantiates the efficacy of the EE concept.

Supply chain is an important aspect for all the companies and can affect many aspects of companies. Especially the disruption in supply chain is causing huge impacts and consequences that are difficult to deal with. This chapter presents a review of selected multiple criteria problems used in supply chain optimization. Research analyzed the multiple criteria decision-making methods to tackle the problem of supplier evaluation and selection. It also focuses on the problem of supply chain when a disruption happens and presents strategies to deal with the issue of disruptions in supply chain and how to mitigate the impact of disruptions. Prevention, response, protection, and recovery strategies are explained. Practical part is focused in the risk-averse models to minimize expected worst-case scenario by single sourcing. Computational experiments for practical examples have been solved using CPLEX solver.

The purpose of this paper is to study various combination forms of the three basic sharing elements (i.e. orders sharing, manufacturers capacity sharing and suppliers capacity sharing) in the cluster supply chain (CSC), formulate a distributed model to protect enterprises’ decision privacy and seek to develop an effective method for solving the distributed complex model.

A distributed assembly cluster supply chain configuration (ACSCC) model is formulated. An improved augmented Lagrangian coordination (ALC) is proposed and used to solve the ACSCC model. A series of experiments are conducted to validate the improved ALC and the model.

Two major findings are obtained. First, the market order’s quantity change and the sales price of the product have a great impact on both the optimal results of the ACSCC and the cooperative strategy, especially, when the market order increases sharply, enterprises have to adopt multiple cooperative strategies to complete the order; meanwhile, the lower sales price of the product helps independent suppliers to get more orders. Second, the efficiency and computational accuracy of the improved ALC method are validated as compared to the centralized ALC and Lingo11.

This paper formulated the single-period ACSCC model under certain assumptions, yet a multi-period ACSCC model is to be developed, a more comprehensive investigation of the relationships among combination forms is to be extended further and a rigid proof of the improved ALC is necessary.

Enterprises in the industrial cluster should adopt different cooperative strategies in terms of the market order’s quantity change and the sales price of the product.

The proposed various combination forms of sharing elements and the formulated ACSCC model provide guidance to managers in the industrial cluster to choose the proper policy.

This research studies various combination forms of the three basic sharing elements in the CSC. A distributed ACSCC model has been established considering simultaneously multiple sharing elements. An improved ALC is presented and applied to the ACSCC problem.

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.

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.

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.

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.

From a supply chain perspective, logistics firms collaborate with other supply chain members to extend their business scope. Investment in circular economy projects in the supply chain can not only broaden the scope of business but also increase the value of the entire supply chain. Third-party logistics companies are gradually participating in the construction and operation of many circular economy projects. How to coordinate multiple circular economy supply chain projects is at the core of its operation.

This paper first analyzes some typical supply chain projects in China and summarizes the main features of these projects. Secondly, considering the benefits of the project and the stakes of each project, a multi-stage stochastic programming model is established. Finally, Cplex, nested decomposition, LocalSolver and other methods are adopted to simulate and analyze the model.

The final experimental results find that the importance of coordinating multiple circular economy supply chain projects to increase the value of the entire supply chain. The multi-stage stochastic programming model presented in this research can provide a useful tool for logistics enterprises and third-party logistics companies to optimize their investment decisions and maximize their profits in the context of a circular economy.

There are still some limitations to this study; for example, it is limited to the analysis of circular economy supply chain projects in China. The study focused on third-party logistics companies, and other enterprises in the circular economy supply chain were not considered. The research also assumed that the benefits of each circular economy project and the stakes of each project were known, which may not always be the case in real-world scenarios.

This manuscript found that investing in other circular economy projects in the supply chain can broaden the scope of business and increase the value of the entire supply chain. Third-party logistics companies are gradually participating in the construction and operation of many circular economy projects, such as recycling and repurposing initiatives. It highlights the importance of coordinating multiple circular economy supply chain projects to increase the value of the entire supply chain. The multi-stage stochastic programming model presented in this research can provide a useful tool for logistics enterprises and third-party logistics companies to optimize their investment decisions and maximize their profits in the context of a circular economy.

A review of the literature reveals that previous research on capabilities has been limited to static capabilities and have largely been firm‐centric, which neglect today's evolving supply chain environment. To address this shortcoming, this paper aims to explore dynamic supply chain capabilities (DSCCS) as a path to achieving sustainable competitive advantage.

Logistics and supply chain literature is reviewed to provide a foundation for introducing a model of DSCCS driving competitive advantage. Propositions for future research are presented based upon the theoretical model.

The need to continuously renew boundary spanning supply chain capabilities may be facilitated by the presence of a supply chain orientation and a learning orientation found across the multiple partners.

Supply chain organizations exist in a continually evolving environment with the best‐performing firms often being characterized as agile and continually improving. The dynamic capabilities perspective provides a theoretical foundation that may be used to better understand and predict the success of supply chain firms. The work presented here is conceptual and empirical examination of the propositions should occur before any broad generalization can be drawn.

Long‐term organizational success may be facilitated by continuous renewal and creation of new static capabilities through the use of DSCCS.

The paper demonstrates that dynamic capabilities may be extended beyond the traditional single‐firm view to exist across the relationships developed by multiple organizations in a supply chain.

This paper aims to empirically explore demand-related information sharing in the extended supply chain.

Through a single, embedded case design, a range of methods are used to collect data from companies representing three different supply chain tiers, including focal company, first-tier suppliers and first-tier customers. The collected data are analysed through the theoretical lens of interdependence.

The findings indicate that the supply chain actors adapt information sharing to the pooled, serial or reciprocal type of interdependence. Information sharing is thus increased with key dyadic partners representing, for example, unique offerings and high market shares as percentage of total expenditure/sales. The study also unearths several barriers to information sharing beyond dyadic ties, including problems related to dis-aggregated, misinterpreted and/or incomplete information.

The study empirically contributes to the existing literature by exploring information sharing in the extended supply chain and by suggesting different approaches to information sharing depending on the type and intensity of interdependence between supply chain partners. Further, the paper contributes to the existing literature on barriers of information sharing in supply chains by identifying barriers specific to multi-tier information sharing. “Meta-information” (i.e. information about the shared information) is needed to overcome some of the barriers of sharing information in cases of weak, pooled interdependencies in the supply chain.

Similar to previous empirical research, this exploratory study indicates that companies, in general, refrain from sharing information beyond dyadic ties. Supply chain managers would instead mostly focus on stronger, reciprocal interdependencies and emphasise dyadic information sharing. To further guide managers, a demand profiling framework considering market share and demand uncertainty is presented. It may be interesting to engage in multi-tier information sharing in particular cases where strong interdependence exists between three or more partners.

This study contributes to existing research on information sharing in supply chains by empirically studying information sharing in an extended supply chain, applying interdependence theory as its analytical framework and unearthing several barriers that are specific to multi-tier information sharing.

The spatial and psychological distance within agri-food chains provides both profit and risk for supply chain members. Grounded on the transaction cost economics (TCE) and institutional theory (IT), the purpose of this paper is to test whether the adoption of multiple supply chains (MSCs), which adopt both traditional and shortened supply chains, can be used to manage uncertainty and mitigate the risk associated with a supply chain.

In order to test the hypothesis, matched questionnaire surveys were developed to collect the data from farm managers and consumers. Completed questionnaires were received from 112 respondents. The hierarchical regression analysis was performed to test hypotheses.

The result shows the positive effects of environmental and behavioral uncertainties on MSC adoption and represents the diminished moderating effects of institutions (industrial and consumption tendency) on the relationship between uncertainties and MSA adoption.

This study only explored producers and their recommended consumers; future studies can undertake questionnaire designs (one producer-to-many consumers) and empirical analyses with analytic hierarchy process theory to reexamine the hypotheses proposed in this study.

MSC adoption is a way to manage uncertainties resulting from spatial and psychological distance in the supply chain. Producers and consumers show their risk preferences by SC adoption after considering pre-constructed societal norms. Therefore, the consumers’ and producers’ choice of a supply chain reflects a process of communicating risk. The adoption of a mixed governance mode (MSC adoption) and accessing information about common practices are two ways to decrease such uncertainties.

There are multiple goals (traceability, fairness, efficiency, well-being) in the food supply chain that may be satisfied by MSC adoption. Therefore, policymakers should understand the different values of various supply chains and facilitate the development of various supply chain modes.

This study integrated the undersocialized and oversocialized perspectives (TCE and IT) to understand how uncertainties of supply chains may be diminished. Based on these perspectives, it found that the adoption of the mixed governance mode and accessing of institutional information are two ways to decrease such uncertainties.

Reshoring is one of the supply chain risk management techniques suggested in literature. However, literature suggests that the decision-making involved in reshoring is complex and not fully understood. In the context of the COVID-19 pandemic, reshoring may represent a way to reduce reliance on global sources and improve resilience of their supply chains. This paper aims to explore if the pandemic is driving reshoring decisions and if the pandemic will actually lead to companies reshoring parts of their supply chain.

This paper critically engages with senior(-most) supply chain managers from three manufacturing companies as they proceed through reshoring decision-making. This enables to develop experiential knowledge about reshoring decision-making processes and their context, as well as insights into the relevance of existing knowledge about reshoring. While not a full multiple case study, the opportunity to engage directly with senior(-most) supply chain managers as they consider reshoring, enables near real-time learning. Not only is reshoring a very timely topic literature has also called for more event-based empirical research. Further to that, it is hoped that this can complement this special issue and support, in a timely manner, the many researchers that are actively studying the impact of the pandemic on supply chains.

Reshoring was being actively considered by all three companies during the research process in Q3 and Q4 of 2020. During this period the pandemic has not yet led to substantial implementation of reshoring, at least by the companies studied in this paper. In response to tariffs on Chinese imports, companies had been diversifying their supply base away from China, but doing so by developing alternative, global sources. Additionally, companies are using alternative risk management techniques, such as supplier collaboration, in the short to medium term. Reshoring decision-making is indeed found to be complex and requires a longer-term time horizon for decision-making and implementation. Logistical challenges and growth in demand do drive a willingness of consumers to pay a premium for locally sourced products. However, when supply normalizes these considerations might lose relevance well before reshoring decision-making and implementation can be completed.

This paper studies reshoring in a real-world setting, learning directly from insights from industry as they emerge. This paper develops four extensions to existing knowledge, develop these in frameworks and hope that this will support ongoing consideration in industry and support the many researchers that are active in this domain today. This paper also suggests several directions for further research.