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The authors analysed the operations of two synchronised channels by focusing on “buy online and return in store” (BORS) strategies in fast-fashion retail by investigating internal and external factors affecting this omnichannel strategy.

The authors apply a combination of techniques to identify the BORS factors. Firstly, a strengths, weaknesses, opportunities and threats (SWOT) analysis was used to define the operational factors of BORS adoption. The authors then apply analytic hierarchy process (AHP) to evaluate the factors under four SWOT categories for kids, male and female consumer groups. The factors of BORS were then ranked using the fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (fuzzy VIKOR) approach.

Combining the SWOT, AHP and fuzzy VIKOR techniques, the authors identified 21 factors in this study. The opportunity that BORS provides for trying in the fitting room for a better convenient shopping experience was ranked as the most important factor, followed by the opportunity to create a loyal customer profile with an easy and well-organised return process. Furthermore, the results reveal that the child consumer group is the most critical of the stated operations factors, followed by male and female consumers.

The authors described the operational factors and supported the decision-making system of BORS for each consumer group with a priority ranking to realise effective managerial management for fast-fashion retailers and practitioners.

The study contributes to the growing literature on the BORS omnichannel strategy, specifically for fast-fashion retail based on consumer needs.

Amid the outbreak of coronavirus disease 2019 (COVID-19), supply chains have faltered. This has influenced operational and financial performance and lead to uncertainty in supply and distribution. Therefore, systems measuring supply chain risk and disruption management performance have gained interest. This study explores barriers to supply chain performance measurement during disruptions such as COVID-19.

Based on a survey and literature review, the authors formalise the barriers and rank them using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) fuzzy Višekriterijumsko kompromisno rangiranje (VIKOR) methodology. A total of 14 experts in 11 countries were surveyed. Performance measurement is based on a balanced scorecard.

Fifteen barriers are identified. Based on DEMATEL analysis, the cause–effect relationships among the four scorecard aspects are explored. The customer axis is revealed as the cause, while the financial, internal business and learning/development are identified as the effect of the supply chain performance measurement. Fuzzy VIKOR calculations show that uncertainty of investment, disrupted cash flows and the bullwhip effect are the most critical barriers to measure supply chain performance during outbreaks such as the COVID-19 pandemic.

The study identifies and ranks general barriers; additional research is required to differentiate barriers in specific industrial sectors.

The findings may help develop proactive, resilient supply chain performance strategies to overcome disruptions.

Policy-makers and decision-makers in industrial and service firms can explore these findings to inform strategies for robust supply chains that can resist disruption in risky environments.

This research addresses a knowledge gap in barriers to measure supply chain performance in post-pandemic areas. It is unclear how far firms will measure supply chain performance in terms of learning from disruption patterns, managing financial and customer demand processes in light of COVID-19. This study contributes by explaining the influences among the barriers and exploring them, offering insights from multiple stakeholders.

This study aims to analyse the resilience of customer demand management post-coronavirus disease 2019, using fast fashion as an example. The paper provides insights for potential applications to micro-, small and medium enterprises (MSMEs).

Based on the qualitative analysis and an integrated Plan-Do-Check-Act (PDCA)-decision making trial and evaluation laboratory (DEMATEL)-fuzzy technique for order of preference by similarity to the ideal solution (TOPSIS) methodology of fuzzy multi-criteria decision-making, we explored and prioritised the enablers of resilience management for fast-fashion MSMEs.

The results reveal that the highest priority enabler is maintaining customer loyalty. Other enablers are associated with e-commerce endorsement, a customer-focussed assortment of items and flexible store operations.

The study findings will enable fast-fashion MSMEs to develop effective actions and priorities in operations efforts to promote post-pandemic recovery.

Despite the importance of the resilience project and the changing fast-fashion customer patterns, only a handful of studies have explored how resilience can be managed in this field. Thus, the findings can contribute to closing this gap in the context of operations resilience research as well as MSME operations.

The purpose of the study is to propose a framework for fleet management and make suitable distribution solution choices in the food industry.

This study reviews the literature to examine food distribution criteria. These criteria are used in the analytic hierarchy process (AHP) assessment and combined with discrete events simulation in a structured framework, which is validated through an empirical study.

The empirical case results demonstrate that both the AHP and discrete events simulation converge toward the same solution in most cases.

This study contributes to the literature on distribution management and develops a framework that can both guide future research and aid logistics practitioners in analysing distribution decision-making systems in dynamic environments.

Focussing on issues that have impacted textiles, clothing and fast fashion following the COVID-19 outbreak, this study aims to identify agility factors pertinent to retail maturity management, mainly on resilience. These factors were then assessed based on priority.

The authors conducted a strengths, weaknesses, opportunities and threats (SWOT) analysis to identify the main factors. This analysis was integrated with the analytic hierarchy process to rank the internal and external factors. Then, the authors used fuzzy technique for order of preference by similarity to the ideal solution to evaluate the significant strategies from the SWOT analysis based on adaptability and flexibility. Thus, the authors produced a prioritised list of relevant factors and guidelines useful in practical settings.

The authors identified and ranked 14 agility and resilience SWOT factors for maturity management and proposed and prioritised six relevant strategies. These highlighted changes and adaptations must be undertaken by various actors, ranging from the supply/manufacturing side to global retail locations.

The sampling study of experts is limited, and the application is focussed on one area. Future research might investigate other fields, for retail and industry.

The output of this study enables a better understanding of the internal and external factors of maturity management for fast-fashion retailers. Hence, it will further help them go through resilience and agility challenges following the pandemic.

This study significantly contributes to the literature because the results can guide retailers in developing effective decision-making systems for mature business operations following the pandemic outbreak. Here, the authors incorporate internal, external, agility and resilience aspects into one decision-making support system while enhancing existing knowledge on fuzzy multi-criteria decision-making applications. Further, this study discusses critical issues that have affected several aspects of the fashion and textile industry and will likely persist for some time.

Circular economy (CE) has evolved as a result of the growing environmental awareness, environmental legislation and the need for social responsibility. However, awareness levels of CE are not as high as expected and practices are further behind than they should be, with a significant lack of research around the subject in the literature. Therefore, the purpose of this paper is to examine the current state of awareness levels and the practices around CE in manufacturing firms. Moreover, the study aims to empirically validate one of the earlier proposed CE models.

The study adopts a quantitative survey questionnaire based approach. More than 500 people from various manufacturing organisations were contacted directly over a 40-day long sampling process through the FAME database, personal contacts and LinkedIn. The survey resulted in 103 completed responses. Given the exploratory nature of the study, the data were mainly analysed using descriptive statistics. To validate the CE model, a correlation analysis was also conducted.

The research findings show that with the growing emphasis on CE across the globe by governing bodies, firms are becoming more aware of CE practices. The analysis also shows some useful insights on the state of each of the pillars (economic benefits, environmental impact and resource scarcity) of CE. The findings also indicate that the environmental impact pillar of CE is at a more developed state than the other two pillars which are, mostly, in a research state.

The study provides manufacturing firms with a thorough understanding of the state of CE practices and importance of its successful implementation. The findings of the study advocates consideration of all three pillars of CE by managers as a guide to plan for an efficient strategy around CE implementation. Moreover, our study adds to existing efforts by the academic community to raise the awareness towards CE practice among all relevant stakeholders. The findings of this study are based on the responses from a limited 103 survey responses from manufacturing firms.

This study adds to the very limited empirical literature on CE awareness and practices in manufacturing firms. This is also one of the first studies attempting to empirically validate an existing CE model.