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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.

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.

The purpose of this paper is to develop a decision tool that enables supply chain (SC) architects to design resilient SC networks (SCNs). Two resilience design determinants are considered: SC density and node criticality. The effect of considering these determinants on network structures is highlighted based on the ability to resist disruptions and how SC performance is affected.

A mixed-integer non-linear programming model is proposed as a proactive strategy to develop resilient structures; design determinants are formulated and considered as constraints. An upper limit is set for each determinant, and resistance capacity and performance of the developed structures are evaluated. These upper limits are then changed until SC performance stabilizes in case of no disruption.

Resilient SCN structures are achieved at relatively low design determinants levels on the expense of profit and without experiencing shortage in case of no disruption. This reduction in profit can be minimized on setting counter values for the two determinants; relatively higher SC density with lower node criticality or vice versa. At very low SC density levels, the design model will reduce the number of open facilities largely leading to only one facility open at each echelon; therefore, shortage occurs and vulnerability to disruption increases. On the other hand, at high determinants levels, SC vulnerability also increases as a result of having more geographically clustered structures with higher inbound and outbound flows for each facility.

In this paper, a novel proactive decision tool is adopted to design resilient SCNs. Previous literature used metrics for SC density and node criticality to assess resilience; in this research, determinants are incorporated directly as constraints in the design model. Results give insight to SC architects on how to set determinant values to reach resilient structures with minimum performance loss in case of no disruption.

The purpose of this study is to explore the importance of supplier innovativeness (SI), top management support (TMS) and strategic sourcing (SS) in the development of supply chain (SC) resilience. The study also argues that organization culture (OC) strongly influences SI, TMS and SS in their importance in generating SC resilience.

The study adopted a cross-sectional approach for collecting online-survey-based responses for evaluating the validity of the proposed associations. Respondents were chosen ensuring that they have sufficient exposure in SC operations in their respective designations. With two reminders, around 212 completed responses were received and analyzed using partial least squares in SmartPLS 2.0.M3.

Findings suggested TMS as a positive enabler of SC resilience. However, although SI and SS had positive influences, they were not significant. The study argues that this may be attributed to the presence of OC as a strong precursor for SI, TMS and SS. The findings showed that OC is indeed a strong predictor of SI, TMS and SS.

The study has undersigned empirically the influence of OC in the development of SI, TMS and SS. The study is the foremost to acknowledge the influence of SI, TMS and SS on SC resilience.

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.

Resilience, the ability of start-ups to deal with anticipated instabilities and probable disruptions, is becoming an important success element during coronavirus disease 2019 (Covid-19). To survive in this pandemic situation, resilience is an important concept for start-ups. The present paper aims to “identify”, “analyse” and “categorize” the resilience factors for start-ups during the Covid-19 pandemic using total interpretive structural modelling (TISM).

The resilience elements of start-ups during Covid-19 were identified and shortlisted during the first phase, which included literature analysis and extensive interaction with experts. TISM was used in the second phase to investigate or to determine how the factors interplayed between the resilience factors of start-ups during Covid-19. The Matrice d'impacts Croises Multiplication Appliquee a un Classment (MICMAC) method is used to rank and categorize the factors. Closed-ended questionnaire with the scheduled interview was conducted to collect the data.

The first part of the study found ten resilience elements in total. The TISM digraph was constructed in the second step to show why one resilience component led to another. The MICMAC analysis divided these factors into four groups: autonomous, linkage, dependent and independent. These groups represented resilience variables based on their driving and dependent power, which assist executives and managers in proactively addressing them while using the TISM digraph as a guide.

During the Covid-19 epidemic, this study focused primarily on resilience characteristics for Indian start-ups.

This study will help key stakeholders and scholars to better understand the elements that contribute to start-up's resilience.

The TISM method for start-up's resilience is suggested in this paper, which is a novel attempt in the field of resilience in this industry.

The COVID-19 pandemic has led to major sales strategy and process changes as many interactions migrated from face-to-face to virtual environments. The nature of the interactions changed, and sales firms, the sales function and salespeople created new processes to excel in virtual environments. As sales processes evolve further, this paper aims to focus on understanding the enduring shifts in sales strategy and processes. In addition, this study seeks to understand the characteristics of enduring shifts and how they are distinct from temporary shifts.

This qualitative analysis provides a comprehensive overview of the sales organizations and salespeople over the period from the start of the pandemic to early 2022. The authors interviewed 66 sales professionals from different countries and industries to better understand the temporary and enduring shifts in sales strategy and processes, adopting ad inductive and narrative approach.

There are four major findings. First, four key themes emerged: increased digitalization, resistance to digitalization, sales process changes and sales organization transformation. Second, changes are classified as temporary, permanent and accelerated changes. Third, some proposed changes were not supported. Finally, five findings were found that were not discussed in previous literature.

This paper finds distinctive findings that offer additional valuable insights that connect to and extend existing literature. These include emerging themes, classification shifts, unsupported proposed changes and unique findings.

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.