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This paper aims to uncover the key enablers of an agile supply chain in the manufacturing sector amidst disruptions such as pandemics, trade wars and cross-border challenges. The study aims to assess the applicability of existing literature to manufacturing and identify additional industry-specific enablers contributing to the field of supply chain management.

The research methodology is comprehensively described, detailing the utilization of extent literature and semistructured interviews with mid- and top-level executives in a supply chain. The authors ensure the robustness of the data collection process and results interpretation.

The study identifies six essential dimensions of an agile supply chain: information availability, design robustness, external resource planning, quickness and speed, public policy influencing skills and cash flow management. The study provides valuable insights for industry professionals to develop agile supply chains capable of responding to disruptions in a rapidly changing world.

This study is limited by its focus on the manufacturing sector, and future research may explore the applicability of these findings to other industries. By focusing on these essential dimensions identified in the study, managers can develop strategies to improve the agility and responsiveness of their supply chains. In addition, further research may investigate how these enablers may vary in different regions or contexts.

The COVID-19 pandemic has forced executives to reconsider their sourcing strategies and reduce dependence on suppliers from specific geographies. To ensure business continuity, companies should assess the risk associated with their suppliers and develop a business continuity plan that includes multisourcing their strategic materials. Digital transformation will revolutionize the supply chain industry, allowing for end-to-end visibility, real time insights and seamless integration of business and processes. Companies should also focus on creating a collaborative workforce ecosystem that prioritizes worker health and well-being. Maintaining trust with stakeholders is crucial, and firms must revisit their relationship management strategies. Finally, to maintain business leadership and competitiveness during volatile periods, the product portfolio needs to be diversified and marketing and sales teams must work in tandem with product teams to position new products accordingly.

This work contributes substantially to the literature on supply chain agility (SCA) by adding several new factors. The findings result in a more efficient and cost-effective supply chain during a stable situation and high service levels in a volatile situation. A less complex methodology for understanding SCA provides factors with a more straightforward method for identifying well-springs of related drivers. First, the study contributes to reestablish the factors such as quickness, responsiveness, competency, flexibility, proactiveness, collaboration and partnership, customer focus, velocity and speed, visibility, robustness, cost-effectiveness, alertness accessibility to information and decisiveness as applicable factors for SCA. Second, the study suggests a few more factors, such as liquidity management, Vendors’ economic assessment and economic diversity, that are the study’s unique contributions in extending the enablers of SCA. Finally, public policy influencing skills, local administration connects and maintaining capable vendors are the areas that were never considered essential for SCA. These factors have emerged as a vital operational factor during the lockdown, and academicians may consider these factors in the future to assess their applicability.

This study provides new insights for decision-makers looking to enhance the resilience and agility of their supply chains. The identification of unique enablers specific to the manufacturing industry contributes to the existing body of literature on agile supply chains in the face of disruptions.

This paper aims to evaluate the construction supply chain (CSC) by examining its relationships with various key areas and its development, identifying gaps and outlining potential future research directions that affect the implementation of CSC standards during the timeframe of the United Nations’ “Decade of Action” plans in the past two decades.

This paper reports on a systematic literature review with bibliometric analysis that investigates publications from around the world on various aspects of CSC. These aspects include research methodology/data collection technique, inquiry mode, country-specific research, focused areas of study, the research aims and publication periods.

The findings of the study reveal that information technology, information sharing, collaboration, performance measurement and CSC configuration have received considerable attention and analysis. However, financial management, supply chain resilience, logistics, vendor managed inventory and rural CSC have been identified as significant areas that require further investigation since limited attention has been given to them in the existing literature.

CSC is a very dominant topic in the current study, but there are some limitations to it. Scopus and Web of Science databases were used to conduct the study. A future study can therefore consider papers related to other databases. As the focus was specifically dedicated to construction material SC only, the papers associated with SCs of labours and equipment have been eradicated.

To the best of the authors’ knowledge, this is the first structured and systematic literature review that identifies the issues related to the CSC during the timeframe of the United Nations’ “Decade of Action” plans and proposes future research directions to enhance the effectiveness and efficiency of CSC.

Effective inventory management is crucial for SMEs due to limited resources and higher risks like cash flow, storage space, and stockouts. Hence, the aim is to explore how technology and know-how can be integrated with inventory practices and impact operational performance.

The basis of the analysis was collecting papers from a wide range of databases, which included Scopus, Web of Science, and Google Scholar. In the first phase of the process, a search string with as many as nine related keywords was used to obtain 175 papers. It further filtered them based on their titles and abstracts to retain 95 papers that were included for thorough analysis.

The study introduced innovative methods of measuring inventory practices by exploring the impact of know-how. It is the first of its kind to identify and demonstrate how technical, technological, and behavioral know-how can influence inventory management practices and ultimately impact the performance of emerging SMEs. This study stands out for its comprehensive approach, which covers traditional and modern inventory management technologies in a single study.

The study provides valuable insights into the interplay between technical, technological, and behavioral know-how in inventory management practices and their effects on the performance of emerging SMEs in Industry 5.0 in the light of RBV theory.

The RBV theory and the Industry 5.0 paradigm are used in this study to explore how developing SMEs' inventory management practices influence their performance. This study investigates the effects of traditional and modern inventory management systems on business performance. Incorporating RBV theory with the Industry 5.0 framework investigates firm-specific resources and technological advances in the current industrial revolution. This unique technique advances the literature on inventory management and has industry implications.

Design Science (DS) is a relatively new paradigm for addressing complex real-world problems through the design and evaluation of artifacts. Its constituent methodologies are currently being discussed and established in numerous related research fields, such as information systems and management (Hevner et al., 2004). However, a DS methodology that describes the “how to” is largely lacking, not only in the field of OM but in general. The Theory of Constraints (TOC) and its underlying thinking processes (TP) have produced several novel artifacts for addressing ill-structured real-world operations problems (Dettmer, 1997; Goldratt, 1994), but they have not been analyzed from a DS research standpoint. The purpose of this research is to demonstrate how TOC’s thinking process methodology can be used for conducting exploratory DS research in Operations and Supply Chain Management (OSCM).

A case study of spare parts replenishment illustrates the use of TOC’s thinking processes in DS to structure an initially unstructured problem context and to facilitate the design of a novel solution.

TOC’s thinking processes are an effective methodology for problem-solving DS research, enabling the development of novel solutions in initially unstructured and wicked problem situations. Combined with structured CIMO design logic TOC’s thinking process offers a systematic method for exploring wicked problems, designing novel solutions, and demonstrating theoretical contributions.

The implication for research is that TOC’s thinking process methodology can provide important elements of the lacking “how to” methodology for DS research, not only for the field of OM but in general for the field of management.

The practical outcome of the research is a novel design for dynamic buffer-based replenishment that extends beyond organizational boundaries.

This work shows how the thinking processes can be used in DS research to develop rigorous design propositions for ill-structured problems.

We introduce decision support tools aimed at optimizing perishable food supply chain management, effectively balancing conflicting objectives such as the exporter’s product collection cost and the importer’s profit. This involves considering factors like perishability, selling price, discount rate, and order quantity to achieve optimal outcomes.

This study considered a three-echelon supply chain comprising farmers, a single exporter, and a single importer providing a single, random-lifetime, perishable product under deterministic customer demand. The proposed mathematical model derived the optimal order quantity, selling price, and discount rate for the entire supply chain. This integrated optimization model treats both demand and supply sides as a multi-objective problem, employing a nonlinear program and a two-stage capacitated vehicle routing problem formulation. Numerical examples and a case study focusing on Thailand durian supply chain were conducted to illustrate the approach of the proposed model.

Taking into account both the importer’s profit and the exporter’s product collection cost, the proposed integrated supply chain model and tools maximize profitability, minimizes waste, and meets demand by optimizing perishable product collection costs and proposing a discount system for selling prices.

Limited to a single perishable product in a three-echelon international food supply chain. Future research can explore different products and supply chain contexts.

The tools enhance decision-making for supply chain managers, improving efficiency, reducing costs, and enhancing customer satisfaction in the perishable food industry.

The proposed model aids in local workforce management by forecasting required manpower for upcoming seasons. By factoring in product quality and pricing, it ensures customers receive fresh products at fair prices. Furthermore, the near-zero waste concept enhances storage conditions at importers' facilities, contributing to improved environmental hygiene.

The integrated model and decision support tools offer a novel approach to address complexities and conflicting objectives in perishable food supply chains, providing practical insights for researchers and practitioners.

The pharmaceutical industry is facing significant pressure to tackle antimicrobial resistance (AMR). Other ecological, societal and regulatory pressures are also driving the industry to “go green”. While such a (green) transition could be possible through appropriate green practices’ implementation, the present understanding about it is superficial and vague. A key reason is the lack of green practices’-related studies on pharmaceuticals, which are also insufficiently comprehensive. This knowledge gap is sought to be addressed.

A systematic literature review (SLR) was conducted with 73 carefully selected articles, then subjected to thematic content analyses for synthesising the relevant themes and sub-themes.

Around 76 operational-level green practices covering all key stakeholders across the drug lifecycle were identified. It was revealed that designing drugs having accelerated environmental degradability is important to combat AMR. Also, redesigning existing drugs is environmentally more resource-intensive than developing new ones with significant cost-saving potential in solvent recycling and flexible manufacturing, both of which are not common at present. With regards to green-related barriers, stringent quality requirements on drugs (and therefore risks in making relevant green-oriented modifications) and time-consuming and costly regulatory approvals were found to be the key ones.

The operational green practices’ framework developed for individual pharmaceutical supply chain stakeholders could help practitioners in benchmarking, modifying and ultimately, adopting green practices. The findings could also assist policymakers in reframing existing regulations, such as Good Manufacturing Practices or GMP-related, to promote greener drug development.

This work is the first systematic attempt to identify and categorise operational-level green supply chain practices across stakeholders in the pharmaceutical sector.

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  Biodegradability of drugs is more important than environmental degradability.

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  Flexible manufacturing process design (or quality by design) reduces resource wastage.

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  Ecopharmacovigilance is effective in combating PIE and AMR-related issues.

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  Upstream and downstream coordination is key to greening pharma operations.

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  Costly and time-consuming regulatory approval is a key barrier to greening pharma processes.

Biodegradability of drugs is more important than environmental degradability.

Flexible manufacturing process design (or quality by design) reduces resource wastage.

Ecopharmacovigilance is effective in combating PIE and AMR-related issues.

Upstream and downstream coordination is key to greening pharma operations.

Costly and time-consuming regulatory approval is a key barrier to greening pharma processes.

The purpose of the study is to analyze and measure the impact of disruption in demand which causes the bullwhip effect. The bullwhip effect impacts the performance of firm. Just like everything else, covid has had an impact on the disruption of supply chain too leading to the need of measuring the bullwhip effect of select Indian sectors. The comparison on bullwhip effect is drawn in pre- and during covid era in major sectors. The study helps to understand, analyze and measure the impact of covid and its challenges to supply chain.

The empirical study is carried out on five major select Indian sectors which have the largest market capitalization in Indian economy, namely, FMCG (fast-moving consumer goods), automobile, utility, consumer durable and IT (information technology). The disruption in the supply chain is measured in terms of bullwhip effect. The novel metric ratio of bullwhip effect is computed which is based on demand–supply mismatch and analyzed based on 10 years of observations. The data is analyzed twice, first from 2011 to 2019 (pre-covid era) and second from 2019 to 2021 (during covid era). Each time, Bombay Stock Exchange (BSE) sectoral indices are used to compute the bullwhip ratio, and empirical data is collected using Prowess. The firms listed in BSE represent most of the sector. Such panel data helps us to analyze inter- and intraindustry bullwhip effect. The changes in the bullwhip effect for various BSE listed firms are analyzed pre- and during covid era. These changes are specifically studied at the manufacturer end of the supply chain. Later regression analysis is performed to study the changes required in production based on the demand. The various strategies that cause or mitigate the impact of covid in intraindustry can be derived from the study. The disruption in production is analyzed based on the disruption in demand and profit before interest and tax (PBIT).

In pre-covid era, the percentage of demand disruption was low in select sectors but not exactly zero. Covid caused the disruptions in supply chain across the globe which resulted in bullwhip effect in Indian sectors too. Yet some of the sectors were able to cope better with the situation as compared to others. In the present study, same is analyzed statistically, and results are derived for practical significance.

The empirical data is having the observations of past 10 years to analyze the pattern of demand disruption in the firms and hence the sectors. The impact of covid is studied on performance, which is analyzed in terms of PBIT. The impact of other factors (political, social, marketing policies, etc.) that may cause disruption in the supply chain of a firm is not considered in the study.

Study is unique, as it measures disruption and provides a peerless way to study the inter- and intrasectors. To analyze the impact of bullwhip effect on sector performance, it is very much required to first measure the bullwhip; this measure of bullwhip as a ratio of the slopes of demand and supply is a novel approach. The study emphasizes that the impact of covid is not the same among the firms, and hence among the sectors. Also, it is found that the impact of such adversities can be mitigated, and performance of firm can remain intact in turbulent times too.

Nowadays, in many organizations, products are not delivered instantly. So, the customers should wait to receive their needed products, which will form a queueing-inventory model. Waiting a long time in the queue to receive products may cause dissatisfaction and churn of loyal customers, which can be a significant loss for organizations. Although many studies have been done on queueing-inventory models, more practical models in this area are needed, such as considering customer prioritization. Moreover, in many models, minimizing the total cost for the organization has been overlooked.

This paper will compare several machine learning (ML) algorithms to prioritize customers. Moreover, benefiting from the best ML algorithm, customers will be categorized into different classes based on their value and importance. Finally, a mathematical model will be developed to determine the allocation policy of on-hand products to each group of customers through multi-channel service retailing to minimize the organization’s total costs and increase the loyal customers' satisfaction level.

To investigate the application of the proposed method, a real-life case study on vaccine distribution at Imam Khomeini Hospital in Tehran has been addressed to ensure model validation. The proposed model’s accuracy was assessed as excellent based on the results generated by the ML algorithms, problem modeling and case study.

Prioritizing customers based on their value with the help of ML algorithms and optimizing the waiting queues to reduce customers' waiting time based on a mathematical model could lead to an increase in satisfaction levels among loyal customers and prevent their churn. This study’s uniqueness lies in its focus on determining the policy in which customers receive products based on their value in the queue, which is a relatively rare topic of research in queueing management systems. Additionally, the results obtained from the study provide strong validation for the model’s functionality.

This study aims to critically evaluate resource dependence theory’s (RDT) assumptions and explanations about dependence and the dependent firm’s strategic options. The authors argue that RDT’s perception of dependence is problematic because it evaluates dependence as a purely negative situation in which all firms, by definition, seek to develop strategies to change the power structure of such relationships. On the contrary, the authors argue that there are situations in which dependent firms are in agreement with dependence and, therefore, develop strategies that do not aim to change the balance of power in the relationship, but rather to strengthen their position within the relationship.

The research is designed as a theoretical discussion. The authors critically evaluate and discuss current understanding and assumptions about RDT’s dependence explanations. Drawing on insights from the strategic management literature, the authors offer a new perspective on the problematic areas in the dependence explanations of the RDT.

Drawing on insights from the strategic management literature, the authors argue that dependent firms enjoy certain advantages due to the dependence relationship to gain sustainable competitive advantages over their rivals and potential competitors. These advantages include factors such as increasing growth potential, developing capabilities and competencies, building relationships of trust with powerful firms and leveraging their reputations and references that contribute to the sustainable strategic advantages of dependent firms. The authors believe that this study has the potential to spur new research that further challenges the assumptions of the RDT and empirically tests its propositions.

The authors propose a research framework on dependence as a strategic option that has the possibility of expanding RDT’s current dependence explanation.