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In an attempt to promote the implementation of lean in small and medium sized enterprises (SMEs), the purpose of this paper is to determine and to evaluate success factors critical to the implementation of lean in SMEs. This will help SMEs to redirect and stepwise strategies for implementing lean and overcome the financial and technical limitations that are hindering smaller companies to address a large set of factors at the same time.

This research proposes the use of a two-phase research methodology. First, 28 critical success factors (CSFs) were identified and grouped into five categories: policy, leadership and management, funding, technic and process, culture, humans and competencies, market, customers and suppliers and understanding, methodology and implementation. Second, a structural model based on the analytical hierarchy process (AHP) was proposed to prioritize the identified CSFs. A practical case study is conducted in a small automotive supplier to validate the proposed model, take inputs and solve the problem under study.

The results show that CSFs related to “Policy, leadership and management” are found to be the most significant for SMEs to successfully implement lean production. This is followed closely by CSFs from the category of “Understanding, methodology and implementation”. CSFs of “Culture, humans and competencies” and “Funding, technique and process” are the third and fourth prominent categories. At the end of the priority list come CSFs of “Market, customers and suppliers”.

The present study has a twofold contribution that complete the existing literature. First, the study is focused on small companies which have not received sufficient attention. Second, it provides a more accurate, effective and systematic decision support tool for selecting the most prominent CSFs to redirect lean efforts in SMEs in a stepwise manner.

The agricultural supply chain is susceptible to disruptive geopolitical events. Therefore, agri-food firms must devise robust resilience strategies to hasten recovery and mitigate global food security effects. Hence, the central aim of this paper is to investigate how supply chains could leverage digital technologies to design resilience strategies to manage uncertainty stemming from the external environment disrupted by a geopolitical event. The context of the study is the African agri-food supply chain during the Russian invasion of Ukraine.

The authors employ strategic contingency and dynamic capabilities theory arguments to explore the scenario and conditions under which African agri-food firms could leverage digital technologies to formulate contingency strategies and devise mitigation countermeasures. Then, the authors used a multi-case-study analysis of 14 African firms of different sizes and tiers within three main agri-food sectors (i.e. livestock farming, food-crop and fisheries-aquaculture) to explore, interpret and present data and their findings.

Downstream firms (wholesalers and retailers) of the African agri-food supply chain are found to extensively use digital seizing and transforming capabilities to formulate worst-case assumptions amid geopolitical disruption, followed by proactive mitigation actions. These capabilities are mainly supported by advanced technologies such as blockchain and additive manufacturing. On the other hand, smaller upstream partners (SMEs, cooperatives and smallholders) are found to leverage less advanced technologies, such as mobile apps and cloud-based data analytics, to develop sensing capabilities necessary to formulate a “wait-and-see” strategy, allowing them to reduce perceptions of heightened supply chain uncertainty and take mainly reactive mitigation strategies. Finally, the authors integrate their findings into a conceptual framework that advances the research agenda on managing supply chain uncertainty in vulnerable areas.

This study is the first that sought to understand the contextual conditions (supply chain characteristics and firm characteristics) under which companies in the African agri-food supply chain could leverage digital technologies to manage uncertainty. The study advances contingency and dynamic capability theories by providing a new way of interacting in one specific context. In practice, this study assists managers in developing suitable strategies to manage uncertainty during geopolitical disruptions.

Despite the growing awareness of supply chains on industry 4.0 (I4.0) capabilities as the enabler of sustainable performance, little is known about what accelerates this interaction. Prior studies have focused on the ambidexterity dilemma and the need to adopt sustainable inter-organizational governance to drive I4.0 capabilities while achieving sustainable performance. To address these issues, this paper aims to explore the distinct and combined effects of several approaches such as digital business transformation (DBT), organizational ambidexterity (OA) and circular business models (CBMs) on the relationship between I4.0 capabilities and sustainable performance.

Drawing upon a hybrid methodology including structural equation modeling and fuzzy set qualitative comparative analysis, this paper develops and tests a hypothetical model using data collected from 306 organizations in Europe, Asia and Africa.

The study findings lead to several important implications concerning the potential paths linking I4.0 and sustainable performance. Notably, the DBT was found to mediate this relationship by integrating circular principles to devise business models. Moreover, OA was found to substitute the CBMs in developing new sustainable business models and reconcile sustainability.

The study is among the first to analyze the combined effects of OA, DBT and CBMs on the relationship between I4.0 capabilities and sustainable performance at the supply chain level. Moreover, the findings propose several solutions to resolve the sustainability dilemma through I4.0 capabilities, DBT, OA and CBMs.

The 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.

To 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.

This 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.

This 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.

The implementation of lean production in small manufacturing enterprises (SMEs) harbors a great deal of barriers on practical, theoretical, financial and organizational sides. In view of this, the purpose of this paper is to explore and prioritize the solutions to overcome these barriers and pitfalls in order to identify a list of the most feasible and efficient solutions on which SMEs must focus to success their lean journey.

First, a review of the published articles along with the interview of some lean experts have allowed to identify 20 barriers grouped into five categories along with 17 solutions proposed to overcome these barriers. Afterwards, an integrated fuzzy Analytic Hierarchy Process-Technique for Order Preference by Similarity to Ideal Solution (AHP-TOPSIS) was proposed to evaluate and rank the solutions of lean implementation in SMEs and overcome its barriers. The AHP is used to determine weights of the barriers as criteria, and the fuzzy TOPSIS method is used to determine the final ranking of the solutions of lean adoption in SMEs.

The top five barriers of lean implementation in SMEs were found to be: lack of management involvement, lack of adapted methodology of lean implementation, short-term vision, fear and resistance to change and lack of understanding of lean. Moreover, the top five solutions to overcome the barriers of lean adoption in SMEs are as follows: commitment and participation of management, adoption of simple measurement and KPIs, development of organizational learning culture, early deployment of lean culture through training and allocation of sufficient time and resources for change.

The findings of this study can provide a basis for researchers and practitioners in order to understand the real reasons of lean failure in SMEs and develop improvement plans to increase its success rate. Moreover, it proposes a more reliable, robust and systematic decision support tool for stepwise implementation of the solutions of lean adoption in SMEs since they lack sufficient resources to address all the solutions simultaneously.

The digital warehouse management system is an emergence that forms a critical part of the transformation of economic structure in Industry 4.0. In the present business scenario, the warehouse management system encounters a messy layout, poor damage control, unsatisfactory order management, lack of visibility and lack of technological interventions. Digital twin (DT) based warehouse system shows the ontology and knowledge graphs for competitive advantage by consolidating and transferring goods directly from an inbound supplier to an outbound customer on short notice and with no or limited storage. There remains a lack of clarity on how the DT can be implemented successfully in warehouse management.

The current literature remains largely unstructured and scattered due to a lack of a systematic approach to integrating the research implications and analysis. This paper probes the conceptualization of the DT with the help of theoretical analysis using the systematic literature analysis method.

The study explores essential concepts such as interoperability and integrability in implementing DT. Further, it analyzes the role of a supply chain control tower (SCCT) in modern supply chain management. A research framework is proposed for practitioners and academicians by incorporating the opportunities and challenges associated with DT implementation. The research findings are mainly threefold: Conceptualization of DT, Featuring SCCT and Exploration of cross-computer platform interfaces, scalability and maintenance strategies.

This study is among the first to analyze and review DT applications in warehouse management. Moreover, the study proposes a theoretical toolbox for the practitioners to successfully implement the DT in warehouse DT-based warehouse management system: A theoretical toolbox for future research and applications.

As e-commerce has expanded rapidly, online shopping platforms have become widespread in India and throughout the world. Product return, which has a negative effect on the E-Commerce Industry's economic and ecological sustainability, is one of the E-Commerce Industry's greatest challenges in light of the substantial increase in online transactions. The authors have analyzed the purchasing patterns of the customers to better comprehend their product purchase and return patterns.

The authors utilized digital transformation techniques-based recency, frequency and monetary models to better understand and segment potential customers in order to address personalized strategies to increase sales, and the authors performed seller clustering using k-means and hierarchical clustering to determine why some sellers have the most sales and what products they offer that entice customers to purchase.

The authors discovered, through the application of digital transformation models to customer segmentation, that over 61.15% of consumers are likely to purchase, loyal customers and utilize firm service, whereas approximately 35% of customers have either stopped purchasing or have relatively low spending. To retain these consumer segments, special consideration and an enticing offer are required. As the authors dug deeper into the seller clustering, we discovered that the maximum number of clusters is six, while certain clusters indicate that prompt delivery of the goods plays a crucial role in customer feedback and high sales volume.

This is one of the rare study that develops a seller segmentation strategy by utilizing digital transformation-based methods in order to achieve seller group division.

COVID-19 pandemic has heavily affected worldwide. One of the major industrial sectors impacted by COVID-19 virus is the travel and hospitality, and it has resulted in extreme level of unemployment in travel and tourism industries especially hotels, restaurant chains, street food caterers and bars. Cancellations of events, conferences, conventions and sports leagues are instantaneously causing severe impact on the travel and tourism and hospitality industry. The unemployed workforce is facing numerous mental health challenges in the form of depression, anxiety, hopelessness, lack of confidence and loss of interest in life which are leading them to maladaptive coping mechanisms like suicide, alcohol and substance abuse. This chapter discusses the following topics:

This study aims to explore supply chain resilience (SCR) and provides a unique resilience index. The work measures the resilience status of 37 organizations across 22 industries and provides insight into accessing the supply chain (SC) vulnerability in an uncertain environment.

This study involves measuring the resilience status of 37 organizations across 22 industries based on a subjective decision-making approach using fuzzy logic. Experts from industries rated the importance and level of implementation of 33 attributes of SCR, which are used to develop a fuzzy index of implementation that explains the resilience status of organizations.

A novel coexistent resilience index is computed based on mutualism to exhibit the proportion of contribution or learning of each attribute of an organization in an industry. The research will enhance the response plans and formation of strategic alliances for mutual coexistence by industry.

Evidence-based interpretations and suggestions are provided for each industry to enhance resilience through coexistence.

The work uniquely contributes to academic literature and SC strategy. The novel coexistent resilience index is computed based on mutualism, facilitating researchers to access SC resiliency.