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This paper aims to assist managers and food supply chain practitioners in efficiently implementing lean and green (LG) practices for sustainability. Examining barriers to LG practices, as well as prioritizing mitigation strategies in the food supply chain, are all part of this work.

Using a combination of literature review and expert team inputs, this paper investigated the LG barriers and their solutions under PESTEL (Political, Economic, Social, Technological, Environmental and Legal) framework. To prioritize them, this work used the fuzzy best worst method (fuzzy BWM) with the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS).

From the fuzzy BWM, the economic barriers were identified as the most significant. From the FTOPSIS approach, top management expertise and commitment to adopting LG practices were identified as the best solution for overcoming the barriers.

This paper discusses the barriers and solutions for successfully implementing LG techniques from the real-time food supply chain. The practitioners and food chain managers welcomed the methodology for its use in prioritizing the barriers to LG practices. Conclusions drawn from this work were found to be realistic.

The original contribution of this study is to present the model framework for barriers and solutions of LG practices in the dairy supply chain using the hybrid MCDM technique.

Improving the medical oxygen supply chain (MOSC) is important to cope with the uneven demand and supply seen in the MOSC when India faced the second wave of COVID-19. This improvisation increases the supply chain (SC) maturity and consequently the efficiency and resiliency to tackle oxygen shortage across the country and to prevent another similar scenario from ever happening. The purpose of this study is to identify and prioritize the solutions to overcome the issues faced by the MOSC during the second wave of COVID-19 cases in India and in turn reduce the extent of casualties in the expected third wave.

This paper uses best worst method (BWM) and fuzzy technique for order performance by similarity to ideal solution to classify the sub-criteria for solutions to solve major SC issues. BWM is used to determine the weights of the sub-criteria and fuzzy technique for order performance by similarity to ideal solution for the final ranking of the solutions to be adopted.

The result of this study shows that the Internet of Things based tagging system is the best solution followed by horizontal and vertical integration of SC in making a resilient and digitized MOSC capable of handling general bottlenecks during a possible third wave.

The research provides insights that can enable the personnel involved in MOSC. Proper understanding will help the practitioners involved in the SC to effectively tailor the operations and to allocate the resources available in an effective and dynamic manner by minimizing or eliminating the pre-existing bottlenecks within the SC.

The proposed framework provides an accurate ranking and decision-making tool for the implementation of the solutions for the maturity of the MOSC.

The COVID-19 pandemic has caused significant disruptions to global supply chains (SCs), affecting the production, distribution, and transportation of goods and services. To mitigate these disruptions, it is essential to identify the barriers that have impeded the seamless operation of SCs. This study identifies these barriers and assesses their impact on supply chain network (SCN).

To determine the relative importance of different barriers and rank the affected industries, a hybrid approach was employed, combining the best-worst method (BWM) and the technique for order preference by similarity to an ideal solution (TOPSIS). To accommodate the inherent uncertainties associated with the pandemic, a triangular fuzzy TOPSIS was used to represent the linguistic variable ratings provided by decision-makers.

The study found that the airlines and hospitality industry was the most affected by the barriers, accounting for 46% of the total, followed by the healthcare industry (23%), the manufacturing industry (19%), and finally the consumer and retail industry (17%).

This study is limited to the four critical industries and nine identified barriers. Other industries and barriers may have different weights and rankings. Nevertheless, the findings offer valuable insights for decision-makers in SC management, aiding them in mitigating the impact of COVID-19 on their operations and enhancing their resilience against future disruptions.

This study enhances understanding of COVID-19’s impact on SCN and provides a framework for assessing disruptions using multi-criteria decision-making processes. The hybrid approach of BWM and TOPSIS in a fuzzy environment is unique and offers potential applicability in various evaluation contexts.

Increased demand for new batteries and strict government protocols have stressed the battery industries to collect and recycle used batteries for economic and environmental benefits. This scenario has forced the battery industries to collect used batteries and establish the formal battery recycling plant (BRP) for effective recycling. The starting of BRP includes several strategic decisions, one of the most critical decisions encountered is to find the best sustainable location for BRP. Hence, this paper aims to address the complexity of the issues faced during the BRP location selection through a hybrid framework.

In this study, the criteria are identified under socio-cultural, technical, environmental, economic and policy and legal (STEEP) dimensions through literature review and experts' opinions. Then, the hybrid methodology integrating fuzzy decision making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and technique for order preference by similarity to an ideal solution (TOPSIS) has been proposed to find the inter-relationship between criteria, the weights of criteria and the best alternative.

The identified five main criteria and 26 sub-criteria have been analyzed through fuzzy DEMATEL, and found that the policy and legal criteria have more inter-relationship with other criteria. Then from BWM results, it is found that the support from government bodies has attained the maximum weightage. Finally, the second alternative has been identified as a more suitable location for establishing BRP using TOPSIS. Further, it is found from the results that the support from government bodies, the impact of emissions, availability of basic facilities and community health are the essential criteria under STEEP dimensions for establishing BRP.

In addition to the various existing sustainable criteria, this study has also considered a set of policy and legal criteria for the evaluation of locations for BRP. Further, the hybrid MCDM method has been proposed in this study for selecting the best alternative. Thus, this study has yielded more insights to the decision-makers in choosing a sustainable location for BRP.

The purpose of this paper is to persuade a hybrid framework, which can be used to assess the performance of various supply chains and can be further used to segregate supply chains concerning critical KPMs. The KPMs have been selected in the COVID-19 pandemic condition.

A real case of e-commerce is presented to illustrate the working of the proposed framework comprising a hybrid methodology of BWM and Fuzzy TOPSIS to measure the performance of the e-commerce supply chains by identifying the critical key performance metrics (KPMs) and measuring the performance of the considered supply chains against these.

The proposed framework is illustrated using real-time data from experts, collected through interviews and discussions. It is found that rate of return on investment (SCPM 27), flexibility of service systems to meet particular customer needs (SCPM 23) and supplier lead time against industry norm (SCPM 33) are significantly weighed in assessing performance of the selected supply chains, with weights 0.07764, 0.06863 and 0.0547, respectively. Amazon and Flipkart are seen to stand out among the other supply chains taken for the present study with closeness coefficients as 0.945 and 0.516, respectively.

The contemporary world has seen the drastic attack of COVID-19 on many firms worldwide, and hence measuring the performance of the supply chains has become necessary so as to understand the critical factors affecting performance, their relative importance and the firm's relative standings. There have been studies in the recent past where researchers worked on similar motives to generate a framework to measure performance of supply chains, but it is seen that the methodologies lack flexibility with respect to effectively handling large data, uncertainty in human emotions, consistency, etc. This is where the current study stands out in effectively measuring the performance of supply chains so as to aid many firms affected by the pandemic.

This paper proposes a multi-layer hybrid decision-making approach to evaluate the capability alternatives for developing a collaborative network to operate in the international market.

The present study is contextualised in the Iranian pistachio export industry. An extensive review of the state-of-the-art literature on supplier collaboration was conducted to identify key capabilities that are essential to establish a collaborative network. The set of defined capabilities were then optimised through interviews with 14 experts from the relevant industry, academics and export authorities. A combination of the fuzzy Delphi method and the best–worst method (BWM) approach was, respectively, used to reduce the number of capability alternatives and assign priority weights to these alternatives. Subsequently, a weighted aggregated sum product assessment method (WASPAS) was employed to rank and evaluate the ability to creating a collaborative network for the export of pistachio.

From the extant literature review, 18 capabilities for the formation of coordination networks in the international markets were identified. Then, the prominent indicators in forming a global network were extracted. After ranking the top pistachio export countries/regions to formalise an efficient collaborative network, it was revealed that although Iran exports approximately 30% of the global market, it falls behind the USA and European Union. The competitors have scored higher in critical criteria, including “trust and commitment”, “strategy and management”, “managerial control and standardization” and “financial resources”.

The proposed hybrid approach encompassing fuzzy Delphi–BWM–WASPAS offers to solve the capability evaluation and selection as well as ranking the possible alternative to formalise a collaborative network in an integrated fashion. This combination of methods is capable to first identify the most important factors, then measuring their importance and eventually rank the possible alternatives. The suggested framework provides an approach to deal with the uncertainty of global collaborative network formation.

Recognizing the factors affecting employees’ job motivation is one of the necessities that can improve people’s performance and increase their effectiveness. This study aims to determine the factors affecting job motivation and to examine effective strategies to increase motivation through identifying internal and external factors.

In this descriptive study, the statistical population was the employees of the largest petrochemical company in Iran. The questionnaire was randomly distributed to the organization’s employees and managers based on Herzberg’s motivation-hygiene theory. To analyze the obtained data, first, the best and the worst factors were identified using SPSS software and then were ranked using best–worst method (BWM).

The results demonstrated that the highest rank among the motivational factors of employees is related to working environment conditions and the lowest rank is related to career advancement and development indicator. In the second stage, the best strategies for motivational factors were determined using the fuzzy goal programming method. The findings showed that 12 out of the 17 proposed solutions have the highest motivation among employees, the implementation of which can increase employee productivity in the petrochemical company under study.

Further to the best of the authors’ knowledge, job motivation factors in the petrochemical industry have never been examined and ranked by using the BWM method so far. Also, the goal programming approach has never been applied to determine strategies for increasing job motivation and ultimately productivity.

The food industry is directly related to the health of humans and society and also that little attention has been paid to the assessment of sustainable supply chain risk management in this area, this will be qualified as an important research area. This study aims to develop a framework for assessing the sustainable supply chain risk management in the realm of the food industry (confectionery and chocolate) with a case study of three generic companies denotes as A1–A3. The proposed risk management was evaluated in three aforementioned manufacturing companies, and these three companies were ranked by the Fuzzy-Weighted Aggregated Sum Product Assessment (F-WASPAS) method in EXCEL.

The evaluation was carried out using integrated multi-criteria decision-making methods Best-Worst method (BWM)-WASPAS. Via an extensive literature review in the area of sustainable supply chain, sustainable food supply chain and risks in this, 9 risk criteria and 59 sub-criteria of risk were identified. Using expert opinion in the food industry, 8 risk criteria and 39 risk sub-criteria were identified for final evaluation. The final weight of the main and sub-criteria was obtained using the F-BWM method via LINGO software. Risk management in the sustainable supply chain has the role of identifying, analyzing and providing solutions to control risks.

The following criteria in each group gained more weight: loss of credibility and brand, dangerous and unhealthy working environment, unproductive use of energy, human error, supplier quality, quality risk, product perishability and security. Among the criteria, the economic risks have the highest weight and among the alternatives, A3 has obtained first ranking.

Modeling of risk for the food supply chain is the unique contribution of this work.

The global resolution of embracing dynamic and intertwined production systems has made it necessary to adopt viable systems like circular economy (CE) to ensure excellency in the business. However, in emerging countries, it is challenging to implement the CE practices due to the existing problems in the supply chain network, as well as due to the vulnerable financial condition of the business after the deadly hit of COVID-19. The main aim of this research is to determine the barriers to implementing CE considering the recent pandemic and suggest strategies to organizations to ensure CE for a cleaner environment and greener economy.

After an extensive literature review and validation from experts, 24 sub-barriers under the class of 6 main barriers are finalized by Pareto analysis, which is further analyzed via the best-worst method to determine the weight and rank of the barriers Further, fuzzy-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to rank the proposed startegies to overcome the analysed barriers.

The results identified “unavailability of initial funding capital”, “need long time investment”, “lack of integrating production system using advance technology” and “lack of strategic planning” as the most acute sub-barriers to CE implementation. Further, fuzzy TOPSIS method is used to suggest the best strategy to mitigate the ranked barriers. The results indicated “integrated design facility to CE”, “ensuring large scale funding for CE facility” as the best strategy.

This study will motivate managers to implement CE practices to enjoy proper utilization of the resources, sustainable benefits in business, and gain competitive advantage.

Periodically, a lot of work is done on CE practices but none of them highlighted the issues in the domain of the leather products industry (LPI) and COVID-19 toward achieving sustainability in production and consumption. Thus, some significant barriers and strategies to implement CE for achieving sustainability in LPI are highlighted in this study, which is a unique contribution to the literature.

The purpose of this study is to identify the risks that exist in halal meat supply chain activities and to carry out a risk assessment using the fuzzy best-worst method (FBWM) along with mitigating risks using the risk mitigation number (RMN).

The method used is to collect several literature reviews related to the halal meat supply chain, which has information relevant to the risks of the meat industry in Indonesia. Then, a focus group discussion was held with several experts who play a role in the meat industry in Indonesia, and 33 identified risks were identified in halal meat supply chain activities. The proposed methodology uses FBWM and RMN in conducting risk assessment and mitigation in the meat industry in Indonesia.

The analysis reveals that priority risk is obtained by using the global weight value on the FBWM, and then risk mitigation is carried out with RMN. Priority mitigation strategies can mitigate some of the risks to the meat industry in Indonesia. The proposed mitigation strategy is designed to be more effective and efficient in preventing risks that can interfere with product halalness in halal meat supply chain activities in the Indonesian meat industry.

The implications of this study highlight the need for collaboration among stakeholders, improved risk assessment methodologies and the expansion of research into other halal supply chains. By addressing these implications, the halal industry can enhance its integrity, consumer confidence and overall contribution to the global market.

This research provides an integrated approach to identifying, analyzing, assessing and mitigating risks to the meat industry in Indonesia.