Explore the vast range of titles available.

The aim of this study is to identify the readiness factors of Lean Six Sigma (LSS) for the food manufacturing industry. A multi-method qualitative approach was used. Semi-structured interviews were conducted with twelve quality practitioners and three case food companies to identify and explore the LSS readiness factors in the food manufacturing industry. Twenty-eight factors were identified and classified into six LSS readiness factors (RF) in the food manufacturing industry context, namely, management support and leadership, organisational culture readiness, process management, project management, employee involvement, and external relations. This study could benefit managers in the food business as a diagnostic tool to evaluate their readiness to implement LSS prior to investing in the programme. The proposed framework identifies LSS readiness dimensions and their attributes to enable food businesses to conduct readiness level self-assessments, thereby contributing to the successful implementation of LSS in the food manufacturing industry. The determined readiness factors will potentially enable an organisational transformation to be better understood, making the implementation of LSS practices in food businesses more successful and sustainable.

Smart technologies have dramatically improved environmental risk perception and altered the way organizations share knowledge and communicate. As a result of the increasing amount of data, there is a need for using business intelligence and data mining (DM) approaches to supply chain risk management. This paper proposes a novel environmental supply chain risk management (ESCRM) framework for Industry 4.0, supported by data mining (DM), to identify, assess, and mitigate environmental risks. Through a systematic literature review, this paper conceptualizes Industry 4.0 ESCRM using a DM framework by providing taxonomies for environmental risks, levels, consequences, and strategies to address them. This study proposes a comprehensive guide to systematically identify, gather, monitor, and assess environmental risk data from various sources. The DM framework helps identify environmental risk indicators, develop risk data warehouses, and elaborate a specific module for assessing environmental risks, all of which can generate useful insights for academics and practitioners.

This study examines the effects of intertwining and circularity on the design of resilient and viable sourcing and recovery strategies in supply chains. We first construct a case study where the supply chains of three industries (i.e., automotive, healthcare, and electronics) frame an intertwined supply network (ISN). Through a discrete-event simulation model developed in anyLogistix, we examine the impact of disruptions in supply and demand on the performance of individual supply chains and the ISN as a whole. We test the performance of several sourcing strategies and their combinations. A special focus is directed toward shared reverse flows. The results show that disruption impact and recovery processes in the Circular ISN do not always follow conventional patterns known from the resilience of individual supply chains due to intertwining and circularity effects. We offer some managerial recommendations for the design of resilient sourcing strategies in the ISN context that are triangulated around collaborative sourcing practices, coordinated production planning, shared reverse flows, and visibility in inventory management.

PurposeThis article presents a review of the existing state-of-the-art literature concerning Supply Chain Management 4.0 (SCM 4.0) and identifies and evaluates the relationship between digital technologies and Supply Chain Management.Design/methodology/approachA literature review of state-of-the-art publications in the subject field and a bibliometric analysis were conducted.FindingsThe paper identifies the impact of novel technologies on the different supply chain processes. Furthermore, the paper develops a roadmap framework for future research and practice.Practical implicationsThe proposed work is useful for both academics and practitioners as it outlines the pillar components for every supply chain transformation. It also proposes a range of research questions that can be used as a base to guide the future research direction of the field.Originality/valueThis paper presents a novel and original literature review-based study on SCM4.0 as no comprehensive review is available where bibliometric analysis, motivations, barriers and technologies' impact on different SC processes have been considered.

Purpose The COVID-19 pandemic showed that preestablished contingency plans and resilience practices were insufficient to cope with long-term and global disruptions. Companies thus struggled to develop capabilities that ensure their survivability during similar crises. Building on the adaptation-based view (ABV) of supply chain resilience, this study aims to offer an in-depth perspective on survivability in supply chains (SCs). Design/methodology/approach The paper empirically tests related relationships between adaptation capabilities and practices that ensure operational continuity. Responses from 252 organisations were collected and analysed using partial least squares structural equation modelling. Findings The results empirically support the ABV’s theoretical propositions and assess the possibilities of intertwining, digitalisation, a circular economy and maturity for the survivability of SCs. Research limitations/implications The derived insights are attractive for managers and researchers to foster supply chain survivability and contribute to the increasing efforts of middle-range theorising in logistics and supply chain management research. Originality/value To the best of the authors’ knowledge, this study is one of the first studies to define factors enhancing the survivability of SCs through the lens of the ABV.

The world is characterized by volatility, uncertainty, complexity, and ambiguity (VUCA). In such an environment, the viability in terms of digitalization, resilience, and sustainability capabilities has gained worldwide attention in supply chain management. Therefore, it is crucial to give special consideration to these paradigms when selecting suppliers. Moreover, the availability of data in digital supply chain systems can aid in supplier selection by using Artificial Intelligence techniques to identify viable suppliers. This approach can streamline the supplier selection process and lead to more efficient and effective manufacturing operations. Thus, it is necessary to have a big data analytics infrastructure in today’s data-driven world. In this context, this paper aims to design a multi-agent system that belongs to the theory of Distributed Artificial Intelligence based on big data analytics to give a strong tool for finding the best viable suppliers based on a thorough and data-driven evaluation. To do so, designing a multi-agent-based big data analytics system model necessitates identifying the multiple criteria needed for selecting viable suppliers in real-time decision-making. To this end, through a literature review, this paper analyzes more than 140 publications and identifies the main criteria needed for viable suppliers’ selection in the VUCA world. Therefore, the proposed system can be used as an intelligent viable supplier selection that improves the quality of the process and controls it while considering different capabilities. It presents a comprehensive model for viable supplier selection, consisting of four main layers: decision-making system, data resources, supplier selection, and big data analytics. The model incorporates six types of agents: Suppliers agent, Resource Agent, Knowledge Management Agent, Pilot Agent, Analyst Agent, and Decision-Making Agent. The integration of these layers and agents enables real-time data-driven decision-making, contributing to the selection of viable suppliers in a volatile and uncertain environment. The proposed model enhances supply chain performance in the digital era, offering a robust tool for both academics and practitioners to improve the quality of supplier selection.

PurposeThe COVID-19 pandemic has caused major disruptions and revealed the fragilities in supply chains. This crisis has re-opened the debate on supply chain resilience and sustainability. This paper aims to investigate distinct impacts of COVID-19 on supply chains. It identifies both short- and medium-to-long-term measures taken to mitigate the different effects of the pandemic and highlights potential transformations and their impacts on supply chain sustainability and resilience.Design/methodology/approachTo address the purpose of the study, a qualitative research approach based on case studies and semi-structured interviews with 15 practitioners from various supply chain types and sectors was conducted. Studied organizations included necessary and non-necessary supply chain sectors, which are differently impacted by the COVID-19 pandemic.FindingsThis study reveals five main challenges facing supply chains during COVID-19, including uncertain demand and supply, suppliers' concentration in specific regions, globalized supply chains, reduced visibility in the supply network, and limited supplier capacity. To help mitigate these challenges and develop both sustainability and resilience, this paper identifies some mitigating actions focusing on the promotion of the health and wellbeing of employees and supply chain stabilization. Further, in the post-COVID era, sustainable and resilient supply chains should consider regionalization of the supply chain, diversification of the supply network, agility, collaboration, visibility, and transparency; and should accelerate the use of smart technologies and circular economy practices as dynamic capabilities to improve supply chain resilience and sustainability.Originality/valueThis study contributes to exploring the sustainability- and resilience-related challenges posed by the COVID-19 pandemic. Its findings can be used by researchers and supply chains decision-makers to limit disruptions and improve responsiveness, resilience, sustainability, and restoration of supply chains. The results support benchmarking through sharing of the best practices and organizations can also integrate the different capabilities discussed in this study into the processes of selection and auditing of their suppliers.

Given the growing global emphasis on sustainable transportation systems, this research presents a comprehensive approach to achieving economic, social, and environmental efficiency in transport within the waste management sector. To address the different challenges of sustainable transportation issues, this paper presents a hybrid multi-criteria decision-making (MCDM) approach that incorporates the analytic hierarchy process (AHP) along with data envelopment analysis (DEA) for sustainable route selection. By leveraging the strengths of both methods, this approach reconciles conflicting requirements and diverse perspectives, facilitating effective decision making. This paper involves identifying relevant criteria for route evaluation, engaging waste management company experts and stakeholders in pairwise comparisons using AHP. Furthermore, DEA is used to calculate route efficiency based on the inputs and outputs of the system. These evaluations enable the identification of the most effective and sustainable routes. This proposed methodology empowers decision makers and transportation policymakers to develop an effective decision-making tool for addressing waste transportation challenges in developing countries. The study contributes to the growing body of research on sustainable waste management practices and provides insights for waste management companies and decision makers on how to optimize waste transportation routes while reducing economic, social, and environmental impacts.

PurposeBlockchain technology (BT) is creating a new standard for all business operations. It can assist businesses in handling the complexity of circular digital supply chain (DCM) management. Despite this optimistic view, several barriers hinder its implementation. In this regard, this study contributes to Industry 4.0, circular economy (CE), the viability with a critical emphasis on its potential ramifications and influence on the future agenda while using BT technology in the supply chain (SC). In addition, the research reduces the knowledge gap by investigating and ranking the key barriers to the deployment of BT in viable circular digital supply chains (VCDSCs) and studies their interdependencies and causal relationships. The purpose of this paper is to address these issues.Design/methodology/approachThe barriers to BT adoption in the VCDSC are identified through a thorough literature review and considering viability performance. These barriers are then classified using the analytical hierarchy process (AHP) method. Decision-making trial and evaluation laboratory (DEMATEL) is then employed to examine the cause/effect, correlation, and connection among the 14 barriers selected barriers from the AHP classification to estimate each barrier's overall degree of impact over the others.FindingsThis paper identifies and analyzes the BT adoption barriers in the VCDSC as well as examines how the key barriers interact. As a result, according to the AHP/DEMATEL method, the most prominent influencing barriers to the BT implementation in the VCDSC are “Data transparency,” “Market competition,” “Missing infrastructure,” “Lack of standardization,” “Complex protocol,” “Lack of industry involvement,” “Financial constraints,” “Missing infrastructure,” “Data transparency” and “Interoperability.” The outcomes offer a potential path for identifying important barriers as well as insight into the implementation of BT in the SC while integrating different capabilities such as viability, sustainability and CE principles.Practical implicationsManagers and researchers will benefit from this research by gaining an understanding of the challenges that must be prioritized and examined for BT to be implemented successfully in the VCDSC.Originality/valueThe use and implementation of blockchain-enabled VCDSC continue to face challenges despite an increase in relevant practice and research. Despite the benefits of BT, managers struggle to apply such technology in the context of their company. In this respect, this paper uses an integrated AHP–DEMATEL for categorizing the BT barriers as well as the interrelationship between them. In this respect, this paper presents the BT barriers studied are those related to the use of BT in the SC while integrating different paradigms such as viability, digitalization and CE. While many studies look at the barriers to BT adoption; none of them has ever included the viable capability, which means the ability to “react agilely to positive changes, be resilient to absorb negative events and re-cover after disruptions and survive at long-term periods.” The study concludes with insightful comments based on the findings and suggestions for eradicating those obstacles and their associated effects.