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This study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.

Based on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.

The results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.

This study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.

This paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.

To develop a fuzzy causal model of enterprise flexibility dimensions in a case study of Indian pharmaceutical industry.

The eight dimensions of enterprise flexibility were identified based on literature review. Fermatean fuzzy decision-making trail and evaluation laboratory (FF-DEMATEL) technique is applied to develop the cause-and-effect interrelationship model among various enterprise flexibility dimensions.

The information technology flexibility, supply chain flexibility, technical flexibility and marketing flexibility are found to be causing/influencing other flexibilities and contributing to overall enterprise flexibilities. Therefore, more attention needs to be paid to develop and sustain them for competitive advantage.

Fermatean fuzzy sets offer more flexibility and more accurate handling complex uncertain group decision making. FF-DEMATEL is a more accurate method to develop inter-dependencies and causal model than ISM, TISM. Ratings from the limited number of decision experts (DEs) from few pharmaceutical firms were done. Future study should take bigger sample of firms and more number of DEs to generalize the findings.

The model will help managers in pharmaceutical industry to prioritize the dimensions of enterprise flexibility to achieve agility, responsiveness, resilience and competitive advantage.

To the best knowledge of the authors, causal modeling enterprise flexibility dimensions using FF-DEMATEL has been studied for the first time in a developing economy context.

Today, with the increasing involvement of the environment and human beings business units, paying attention to fulfilling social responsibility obligations while making a profit has become increasingly necessary for achieving sustainable development goals. Attention to profit by organizations should not be without regard to their social and environmental performance. Social responsibility accounting (SRA) is an approach that can pay more attention to the social and environmental performance of companies, but it has many barriers. Therefore, the purpose of this study is to identify barriers to SRA implementation and provide strategies to overcome these barriers.

In this study, the authors identify barriers to social responsibility accounting implementation and provide strategies to overcome these barriers. By literature review, 12 barriers and seven strategies were identified and approved using the opinions of six academic experts. Interpretive structural modeling (ISM) has been used to identify significant barriers and find textual relationships between them. The fuzzy technique for order performance by similarity to ideal solution (TOPSIS) method has been used to identify and rank strategies for overcoming these barriers. This study was undertaken in Iran (an emerging market). The data has been gathered from 18 experts selected using purposive sampling and included CEOs of the organization, senior accountants and active researchers well familiar with the field of social responsibility accounting.

Based on the results of this study, the cultural differences barrier was introduced as the primary and underlying barrier of the social responsibility accounting barriers model. At the next level, barriers such as “lack of public awareness of the importance of social responsibility accounting, lack of social responsibility accounting implementation regulations and organization size” are significant barriers to social responsibility accounting implementation. Removing these barriers will help remove other barriers in this direction. In addition, the results of the TOPSIS method showed that “mandatory regulations, the introduction of guidelines and social responsibility accounting standards,” “regulatory developments and government incentive schemes to implement social responsibility accounting,” as well as “increasing public awareness of the benefits of social responsibility accounting” are some of the essential social responsibility accounting implementation strategies.

The findings of the study have implications for both professional accounting bodies for developing the necessary standards and for policymakers for adopting policies that facilitate the implementation of social responsibility accounting to achieve sustainability.

This paper creates a new perspective on the practical implementation of social responsibility accounting, closely related to improving environmental performance and increasing social welfare through improving sustainability.

Experts believe that the strategies mentioned above will be very effective and helpful in removing the barriers of the lower level of the model. To the best of the authors’ knowledge, for the first time, this study develops a model of social responsibility accounting barriers and ranks the most critical implementation strategies.

Amid rapid technological progress, the construction industry is embracing Construction 4.0, redefining work practices through emerging technologies. However, the implications of Construction 4.0 technologies to enhancing well-being are still poorly understood. Particularly, the challenge lies in selecting technologies that critically contribute to well-being enhancement. Therefore, this study aims to evaluate the implications of Construction 4.0 technologies to enhancing well-being.

A list of Construction 4.0 technologies was identified from a national strategic plan on Construction 4.0, using Malaysia as a case study. Fourteen construction industry experts were selected to evaluate the implications of Construction 4.0 technologies on well-being using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The expert judgment was measured using linguistic variables that were transformed into fuzzy values. Then, the collected data was analyzed using the following analyses: fuzzy TOPSIS, Pareto, normalization, sensitivity, ranking performance and correlation.

Six Construction 4.0 technologies are critical to enhancing well-being: cloud & real-time collaboration, big data & predictive analytics, Internet of Things, building information modeling, autonomous construction and augmented reality & virtualization. In addition, artificial intelligence and advanced building materials are recommended to be implemented simultaneously as a very strong correlation exists between them.

The novelty of this study lies in a comprehensive understanding of the implications of Construction 4.0 technologies to enhancing well-being. The findings can assist researchers, industry practitioners and policymakers in making well-informed decisions to select Construction 4.0 technologies when targeting the enhancement of the overall well-being of the local construction industry.

This study aims to explore how subsidiary capabilities collectively configure for performance. Additionally, it seeks to examine whether these configurations of capabilities can provide equifinal solutions through developing a comprehensive research framework that focuses on subsidiaries in China.

With a data set collected through a questionnaire from 172 Korean multinational enterprises (MNEs) in China, this study used a fuzzy-set qualitative comparative analysis to detect the capability conditions and configurations. These configurations represent combinations of various subsidiary capabilities linked to high performance.

This study identified several complex pathways with distinct configurations for high subsidiary performance. The findings demonstrate the importance of configurations over individual conditions. Thus, the results highlight that the effectiveness of diverse capabilities, which are widely believed to singularly contribute to the high performance of MNE subsidiaries, depends on how each combines with other capabilities. Overall, the findings provide a richer and fine-grained understanding of the role and relative importance of various forms of MNE subsidiary capabilities and how the joint effect of these subsidiaries contributes to high performance.

This study suggests that MNE managers should comprehensively understand how subsidiary capabilities are configured to produce subsidiary performance outcomes. This specifically illustrates the importance of understanding the mutually conflicting yet collectively exhaustive results of multi-selective solutions and aims to align with China’s industrial and regional heterogeneity.

By examining the role of MNE subsidiary capability configurations, which may collectively influence the subsidiary’s performance, this study contributes to the literature. It elucidates how MNE subsidiaries may achieve superior performance by developing and possessing various capabilities tailored to the local context.

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.

Because family businesses are highly complex enterprises, researchers need appropriate theoretical and methodological tools to study them. The neoconfigurational perspective and its accompanying method, qualitative comparative analysis, are particularly well suited to phenomena characterized by complex causality, but their uptake in family business research has been slow and fragmented. To remedy this, the authors highlight their unique ability to address research questions for which other approaches are not well suited and discuss how they might be applied to family business phenomena.

The authors introduce the core tenets of the neoconfigurational perspective and how its set-theoretic epistemology differs from traditional approaches to theorizing and analysis. The authors then use a dataset of family firms to present a primer on conducting qualitative comparative analysis and interpreting the results.

The authors find that family firm resources can be combined in multiple ways to affect business survival, suggesting that resources are substitutable and complementary. The authors discuss how the unique features of the neoconfigurational approach, namely equifinality, conjunctural causation and causal asymmetry, can be fruitfully applied to break new ground in scholarly understanding of family businesses.

This article allows family business researchers to apply the neoconfigurational approach without first having to consult multiple and disparate sources often written for other disciplines. This article explicates how to leverage the theoretical and empirical advantages of the neoconfigurational approach in the context of family businesses, supporting a more widespread adoption of the neoconfigurational perspective in family business research.

The study aims to propose a decision-support system to determine the location of a regional disaster logistics warehouse. Emphasizing the importance of disaster logistics, it considers the criteria to be evaluated for warehouse location selection. It is aimed to determine a warehouse location that will serve the disaster victims most efficiently in case of a disaster by making an application for the province of Izmir, where a massive earthquake hit in 2020.

The paper proposes a fuzzy best–worst method to evaluate the alternative locations for the warehouse. The method considers the linguistic evaluations of the decision-makers and provides an advantage in terms of comparison consistency. The alternatives were identified through interviews and discussions with a group of experts in the fields of humanitarian aid and disaster relief operations. The group consists of academics and a vice-governor, who had worked in Izmir. The results of a previously conducted questionnaire were also used in determining these locations.

It is shown how the method will be applied to this problem, and the most effective location for the disaster logistics warehouse in Izmir has been determined.

This study contributes to disaster preparedness and brings a solution to the organization of the logistics services in Izmir.

The apparel industry of Bangladesh is rethinking lean manufacturing (LM) deployment because of the challenges imposed by the COVID-19 pandemic. Due to COVID-19, LM implementation in the apparel industry has become more difficult. Thus, the purpose of this study is to explore the barriers to implementing LM practices in the apparel industry of Bangladesh in the context of COVID-19 pandemic.

For evaluating the barriers, an integrated framework that combines the Delphi method and fuzzy total interpretive structural modeling (TISM) has been designed. The application of fuzzy TISM has resulted in a structured hierarchical relationship model of the barriers with driving and driven power.

The findings reveal that “lack of synchronization of lean planning with strategic planning”, “lack of proper understanding of lean concept” and “low priority from the top management” are the three top most important barriers of LM implementation in apparel industry.

These findings will help the apparel industry to formulate strategy for implementing the LM practices successfully. The proposed model is expected to contribute to the sustainable development goals (SDGs) such as Responsible Consumption and Production (SDG 12); Decent Work and Economic Growth (SDG 8); Industry, Innovation and Infrastructure (SDG 9) via resilient strategies.

This study is one of few initial efforts to investigate LM implementation barriers during the COVID-19 epidemic in a real-world setting.

Given the complexity of building information modeling (BIM) adoption decisions in small- and medium-sized enterprises (SMEs) in the Architecture, Engineering and Construction (AEC) industry, understanding BIM adoption decision-making through the net effect of a single factor on BIM adoption decisions alone is limited. Therefore, this paper analyzed the co-movement effect of managers' psychological factors on the BIM adoption decisions from the perspective of managers' perceptions. The purpose is to let managers have a deep understanding of their BIM adoption decisions, and put forward targeted suggestions for the AEC industry to promote the adoption of BIM by SMEs.

Data from 192 managers in SMEs collected by the questionnaire were used in a fuzzy set qualitative comparative analysis (fsQCA). Due to the limitations of fsQCA in making the best use of the data used, as a complement to fsQCA, necessary conditions analysis (NCA) was used to analyze the extent to which necessary conditions influenced the outcome.

(1) NCA analysis shows that high perceived resource availability (PRA) and high performance expectancy (PE) are necessary conditions for high BIM adoption intention (AI). (2) fsQCA analysis shows that high PE is the single core condition for high AI. fsQCA analysis identifies three configurations of managers' psychological factors, reflecting three types of managers' decision preferences, namely benefit preference, loss aversion and risk avoidance, respectively. Different decision preferences may lead to different BIM adoption strategies, such as full in-house use, partial in-house/outsourcing and full outsourcing of BIM processes. (3) High perceived risk (PR) and low perceived business value of BIM (PBV) are the core conditions for low AI.

This paper expands on the application of fsQCA to context of BIM adoption decisions. Based on the results of fsQCA analysis, this paper also establishes the relationship between managers' decision-making psychology and BIM adoption strategy choice and analyzes the impact of different decision biases on BIM adoption strategy choice. It concludes with suggestions for encouraging managers to adopt BIM and for avoiding decision-making bias.