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This paper is motivated by the need to assess the risk profiles associated with the substantial number of items within military supply chains. The scale of supply chain management processes creates difficulties in both the complexity of the analysis and in performing risk assessments that are based on the manual (human analyst) assessment methods. Thus, analysts require methods that can be automated and that can incorporate on-going operational data on a regular basis.

The approach taken to address the identification of supply chain risk within an operational setting is based on aspects of multiobjective decision analysis (MODA). The approach constructs a risk and importance index for supply chain elements based on operational data. These indices are commensurate in value, leading to interpretable measures for decision-making.

Risk and importance indices were developed for the analysis of items within an example supply chain. Using the data on items, individual MODA models were formed and demonstrated using a prototype tool.

To better prepare risk mitigation strategies, analysts require the ability to identify potential sources of risk, especially in times of disruption such as natural disasters.

Nowadays, the agri-food industry is called to face several sustainability challenges that require the development of new sustainable models. The adoption of new technological assets from Industry 4.0 supports the companies during the implementation of sustainability practices. Several models design the operation management of the food supply chains (FSCs). Because none extant models resulted complete in technological and sustainability elements, this paper aims to propose an innovative and sustainable agri-food value chain model, contributing to extend understating of how supply chains can become more sustainable through the Industry 4.0 technologies.

Thanks to a well-structured and replicable systematic literature review and sequent content analysis, this work recognized and compared the extant FSC models, focusing on the interaction of five key elements: activities, flows, stakeholders, technologies and sustainability. The output of the comparison leading in the definition of the proposed model is discussed in a focus group of 10 experts and tested in a case study.

Fifteen extant models were recognized in literature and analysed to discover their features and to putt in light peculiarities and differences among them. This analysis provided useful insights to design and propose a new innovative and sustainable agri-food value chain model; an example for the olive oil business case is provided.

The adding value of the work is the proposed model which regards innovative elements such as recirculation flows, external stakeholders and Industry 4.0 technologies usage which allows enhancing the agri-FSCs operational efficiency and sustainability.

This study aims to explore how green supply chain management (GSCM) strategies can be effectively implemented for business supply chain operations, relationship management and product design to gain green competitive advantages.

An exploratory in-depth case study was conducted with one of the largest Chinese electronics manufacturers that is considered a leading GSCM adopter in the industry, to understand how the company adopts green supply chain practices across its multiple product lines.

The findings show that businesses can build different green focuses across GSCM elements of green operation, green relationship management and green product design to form diverse hybrid strategic solutions. They include green control, lean, leagile, agile and clean innovation while taking consideration of supply chain type and product lifespan. A taxonomy of four key GSCM strategic combinations is proposed based on the findings. The strategies align with green demand and supply chain characteristics balancing a series of business competitive objectives in terms of reducing pollution and waste, improving green cost efficiency, enhancing green demand innovation and building green service effectiveness.

This study lends insight into the strategic alignment relationships between product supply chain types and approaches to GSCM.

The findings of this study can support industry practitioners in formulating aligned GSCM strategies based on product types to achieve optimal results.

Optimised green supply chain design, operations and relationship management incorporating product attributes can help further minimise negative impacts of business activities on the environment.

This research provides a systematic understanding of how product supply chain types can influence GSCM strategy formulation. It gives a holistic picture of how hybrid choices of strategies with green supply chain operations, relationship management and product design can be formulated based on product and supply chain characteristics.

This study aims to comprehend the role of leagility and resilience in developing sustainable global supply chains, mitigating short-term disruptions and long-term economic impacts from various disasters, in the context of Australian civil infrastructure projects.

The study employs systematic review approach to establish that addressing project success dimensions (i.e. leagility, resilience and sustainability) requires an integrated and extended supply chain approach, encompassing traditional supply chain strategic model elements (i.e. cost/capital, quality and service goals) and supply chain eco-system (i.e. organisations, societies, economies and nature).

The study underscores the need to enhance supply chain leagility and resilience to achieve sustainability. This can be achieved by developing skills needed to plan across project phases and time frames, aligning with short and long-term organisational goals, assuming smart risks in the face of uncertainty.

This study extends the traditional supply chain strategic model by introducing new priorities to minimise the consequences of disruptions and to effectively respond to them. The integration of leanness, agility and resilience ensures a sustainable supply chain even in the times of uncertainty, disruption and volatility.

This research provides an opportunity for practitioners and policymakers to rethink and redesign the conventional supply chain model of cost, capital, quality and service objectives. It introduces pioneering concepts by acknowledging and incorporating emerging priorities, especially in Australian civil infrastructure projects. The study integrates leagility and resilience into the existing strategic framework, adding crucial dimensions for sustainable supply chains in infrastructure companies.

This chapter of the book aims to achieve sustainability and productivity in light of the interaction between managers and engineers in a lean and agile supply chain management system in today’s organizations. The main innovation of this chapter is the use of the balanced scorecard (BSC) model and fuzzy analysis network process (FANP) to create a suitable platform for the realization of this interaction between managers and engineers and to identify exactly which expert system is ideal for the main purpose. Indeed, this chapter introduces its readers to the application of strategic management tools such as the BSC accompanied by FANP in the elements of supply chain management where data analysis of lean and agile networks in supply chain management can create a competitive advantage in the organization.

This research examines the relationships between the components of supply chain integration (SCI) (i.e. internal integration (INI), customer integration (CI) and supplier integration (SI)), supply chain risk management (SCRM) and supply chain resilience (SCRE), with disruption impact (DI) as the moderator, among small and medium-sized enterprises (SMEs).

271 useable data were collected from Chinese SMEs to test the research model with two statistical approaches of PLS-SEM and ANN analysis.

Results show that SCI (i.e. INI, CI and SI) positively affects SCRM, and subsequently affects SCRE. Moreover, SCRM has also been found to fully mediate the relationship between INI, CI and SI with SCRE. Additionally, DI was also found to moderate the relationship between SCRM and SCRE.

This study expands the supply chain management-related knowledge by empirically validating the mediating role of SCRM between the elements of SCI and SCRE, as well as empirically identifying DI as the moderator between SCRM and SCRE.

The findings offer valuable understanding that can guide SME managers, owners and stakeholders in developing strategies for integrating with customers, suppliers and internal departments, as well as implementing SCRM practices to enhance SCRE performance.

The research expands the existing literature on the elements of SCI and SCRM in maintaining SCRE from an Asian developing country's perspective.

Drawing on paradox theory and the category of the “performing-organizing” paradox, the study investigates the tensions firms experience in the context of organizing the processes involved in managing their indirect GHG emissions.

The authors develop hypotheses to explain why the paradox elements of supply chain transparency and supply chain coordination affect firms' ability to reduce their indirect supply chains GHG emissions. Using a two-stage method based on data from Refinitiv and CDP for 2002 to 2021, the authors test this study’s hypotheses through panel regression analyses.

While greater transparency experience with scope 3 emissions disclosure, GSCM practices and broader supply chain engagement are all associated with higher levels of scope 3 emissions levels, both long-term transparency experience and GSCM practices are also associated with relative reductions in scope 3 emissions over time.

Given growing pressures on firms to demonstrate both transparency and legitimacy regarding their scope 3 emissions, firms must understand the characteristics of this paradox as this has implications for how emissions performance is perceived and managed. This study's results suggested that firms need to take both a long-term perspective and effectively communicate the differences involved in reporting their emissions performance to avoid unwarranted criticism.

Filling a gap in sustainable OSCM studies by providing large-scale quantitative insights into the relationships between organizing and performing, the authors demonstrate that the processes involved in firms' efforts of measuring and managing their indirect scope 3 emissions are paradoxically affected by whether performance outcomes are specified as annual absolute levels of scope 3 emissions, or relative changes over time.

This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.

This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.

This study aims to investigate the impact of I4.0 technologies and their interoperability on supply chains (SCs) performance and how the integration of such technologies and their interoperability can create pathways for SCs resilience post-COVID-19. This is of paramount importance in the context of COVID-19 as the investigation around I4.0 technologies may provide relevant insights on how SCs may better respond to unexpected situations like the current pandemic with the use of digital technologies.

A survey research method was designed based on some constructs extracted from the literature regarding the main disruptive technologies, interoperability, elements of supply chains processes (SCPs) performance such as integration, collaboration, transparency, efficiency, responsiveness and profitability. The data were collected from March to July 2020 from different regions of the world when the peak of the first wave of the pandemic had occurred. The survey resulted in 115 valid responses. The study used a combination of descriptive, correlation and multiple regression methods to analyse the data.

The study indicates that disruptive technologies significantly impact SCPs performance (integration, collaboration, responsiveness and transparency) and their resilience. The findings did not support the notion that these technologies improve the efficiency of SCs, a significant contrast to the existing literature. Our findings also refute the existing understanding that interoperability moderates the impact of disruptive technologies on SCPs performance and enhancing the resilience of SCs. However, the findings show that the integration of I4.0 technologies and their interoperability has a positive impact on SCPs profitability.

The findings strongly advocate that this integration plays an important role in improving SC performance, and a future pathway of SC resiliency post-COVID-19. Considering that the I4.0 trend will impact SCs in the coming years, this study brings a relevant contribution to researchers and practitioners.

This study makes a unique contribution by investigating a novel causal relationship between the main elements (I4.0 technologies, interoperability, processes performance and strategic outcomes) related to the SC in this new context.