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This research aims to model the social dimension of sustainability in construction projects. A new hybrid system dynamic (SD)–fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is proposed to analyze the various factors affecting social aspect of sustainability taking into account their complex interactions.

The various factors affecting the social dimension of sustainable development are identified based on the opinions of 12 experts with an extensive experience in highway construction projects and a thorough knowledge and/or professional experience in the sustainability area. The qualitative model of social sustainability is constructed using SD approach and the complex inter-related structure of the various influencing factors are modeled using cause and effect feedback loops. Fuzzy set theory is applied to model the uncertainty of human judgments. The importance of various influencing factors is then determined quantitatively taking account of their complex interactions using the proposed SD-fuzzy DEMATEL method. The most significant influencing factors are finally determined.

To evaluate the performance of the proposed method, it is implemented on a real highway project and the importance of various factors affecting the social sustainability is determined. A set of complex interrelated factors affecting social sustainability are divided into cause and effect groups, and the root causes affecting the social sustainability performance of the project are determined. Therefore, the required managerial actions can be taken to improve the social sustainability.

Well-qualified experts with a well-developed mental model of social sustainability are necessary to provide required input data for modeling social sustainability using the proposed approach. The absence of such experts could be a limitation for the implementation of the proposed model on a new project.

The proposed Hybrid SD-fuzzy DEMATEL method provides a practical and robust tool to analyze the various factors affecting social sustainability taking into account their complex interactions.

The proposed method offers a more precise and accurate analysis of various factors affecting social sustainability of construction projects since the complex inter-related structure of influencing factors as well as the vague and imprecise nature of experts' judgment is taken into account efficiently.

The purpose of this article is to identify the critical success factors (CSFs) of knowledge management (KM) adoption in the supply chain (SC) using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method through an empirical case study.

The paper examines the influencing factors of KM adoption in SC which have been identified through the literature survey and expert opinion. The fuzzy DEMATEL method has been used to evaluate identified influencing factors. Considering the interdependence among factors, the fuzzy DEMATEL method forms a structural model and then visualizes the causal relationships among factors through a cause–effect relationship diagram. On the basis of the cause–effect relationship diagram, CSFs that are extraordinarily essential for KM adoption in SC are identified. Empirical case study of an Indian automobile organization presented to illustrate the fuzzy DEMATEL method and demonstrates its usefulness.

The results gathered from the implementation of the fuzzy DEMATEL method to identify CSFs of KM adoption in SC to the chosen case illustrate that factors such as top management support, employee training and education, integration of knowledge and information flow, communication among the SC members and trustworthy teamwork to exchange knowledge within SC need to be highlighted as critical factors for successful adoption of KM in SC.

The finding not only offers a meaningful base to deepen the understanding with regard to KM adoption in SC, but also provides a clue to develop an effective adoption of KM in SC in a stepwise manner.

The empirical case study contributes to the literature on KM adoption in SC, suggesting how an organization can identify CSFs of KM adoption in SC and implement them progressively to greatly improve the efficiency of the whole SC performance.

The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.

Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.

The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.

This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.

The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.

The purpose of this paper is threefold: first, to present a structural competency model; second, to remark new criteria for personnel selection in Industry 4.0 environment; and third, to contribute to the operations management literature by focusing on recruitment process in Industry 4.0 environment and supporting human resources activities with Industry 4.0 related criteria and point out a new research field in Industry 4.0.

Fuzzy DEMATEL has been used in the implementation. The study is conducted in a high-tech firm, which has started to modify its processes according to Industry 4.0, and introduces a new specific department that is responsible of this transformation. In total, 11 personnel selection criteria were presented and then assessed by experts through a fuzzy linguistic scale. Both importance order and causal relation between criteria are presented at the end of the study.

According to the results, the most important criteria in the selected firm are the ability of dealing with complexity and problem solving, thinking in overlapping process, and flexibility to adapt new roles and work environments. While cause group includes criteria such as knowledge on IT and production technologies, awareness of IT security and data protection, and ability of fault and error recovery, effect group includes flexibility to adapt new roles and work environments, organizational and processual understanding, and the ability to interact with modern interfaces.

Analytical thinking and system approach are the key topics for new supporting personnel selection criteria, which lead to the need for the skills and qualifications in decision making and process management. Results of the cause group criteria also indicate the importance of technical abilities such as coding, IT security and human-machine interfaces. On the other hand, effect group of the study emphasizes on the flexibility and interdisciplinary working structure that suggests the suitability of matrix organization in the companies which follow the Industry 4.0 trends. Moreover, team work comes forward as another key concept for organizations transforming to Industry 4.0.

The originality of this study appears on modeling of a competency structural model for Workforce 4.0 which is proposed as a road map, including the suggested set of related criteria and the fuzzy MCDM-based methodology for companies which alter their organizations according to Industry 4.0.

This paper aims to develop a lean manufacturing road map for industrial firms by selecting the appropriate lean tools relying on the predefined strategic objectives and the firm constraints. It also illustrates how to prioritize these tools considering their interrelationship.

Relying on the predefined strategic objectives, operational objectives can be set by using the balanced scorecard (BSC). Afterwards, the theory of constraints (TOC) is introduced to investigate the manufacturing system and to determine its constraints. For these constraints, the principle of fault tree analysis (FTA) is used to determine their root causes. Consequently, lean manufacturing tools/initiatives can be proposed. Finally, the fuzzy-decision making trial and evaluation laboratory (fuzzy-DEMATEL) method is implemented to prioritize these initiatives and to construct a suitable lean road map by managing experts’ knowledge.

The practical results indicate that diagnosing the manufacturing system and managing experts’ knowledge to select the appropriate lean initiatives, and prioritizing these initiatives relying on the understanding of their interrelationship could support achieving the strategic targets without consuming extra time or resources.

The study is limited to manufacturing firms. Besides, it reinforces the need for investigating the effectiveness of the proposed approach on service sectors.

The study provides a methodology with a real application, to manage experts’ knowledge for developing an effective lean improvement road map. The methodology could be adopted by any manufacturing firm.

The study supports decision makers of a firm to select the improvement initiatives by an original structural approach, which integrates BSC, TOC, FTA and fuzzy-DEMATEL. Besides, the interrelationships among the selected lean initiatives are considered, and results show the importance of analysing these interrelationships during the construction of the lean improvement plan. Moreover, its effectiveness and applicability are validated via a practical case study.

The aim of this paper is to predict and minimize the risks of oil, gas and petrochemical projects. Besides, reducing the likelihood of occurrence and minimizing risks impact on the projects to reduce the probable costs and improve the economic situation is another purpose of this paper.

This paper provides a fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) – a technique that assist to solve decision-making problems – and IP (Impact & Probability) table methods to identify and analyze critical risks in energy projects, and then fuzzy Binary Logistic Regression (BLR) in order to predict the probability of each level of risk for more efficient risk management in projects. Furthermore, in this paper, the fuzzy BLR (FBLR) is optimized such that the probability of a high level of risk for the implementation of the project has been minimized using meta-heuristic algorithm.

The results from the point of view of experts show that combination of fuzzy DEMATEL with FBLR approach as well as using SA algorithm, in order to optimize the high level of risks, can provide a smart approach to managing risks with more success.

The application of the proposed method is illustrated via a real data set from energy projects.

We propose combined fuzzy DEMATEL and FBLR methods to predict and optimize the risks of the energy projects, which is the innovation of this paper.

From last few decades, logistics management (LM) constitutes a global concern among organization’s supply chain (SC) to improve their business effectiveness. The purpose of this paper is to uncover and analyze the critical factors (CFs) related to the implementation of effective LM concept and benchmark the SC performance.

The most common (16) CFs were identified and selected through literature and use of the Delphi method. Subsequently, the selected most common CFs were analyzed to distinguish their causal relations using the fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) technique under unclear surroundings. A case example of Indian Logistics Company is also discussed to reveal the practical applicability of the research.

Provision of the effective information communication and technological developments in the system and Management dedication, support and involvement CFs are found to have the top most influences in the effective implementation of LM. This paper also groups the CFs into cause and effect relationship which provides valuable insights for analyzing the factors in successful implementation of LM.

This work attempts to understand the different CFs, their relative position and the importance rating in the system, due to which, managers can differentiate the factor which greatly affects the concepts of implementing LM, and thus, improvements can be made accordingly.

First, this work offers 16 CFs to LM implementation from a SC scenario. Second, in the context of contributing to the theory, the combined Delphi and fuzzy DEMATEL-based model is provided that helps in managing the logistic related issues effectively.

The purpose of this paper is to develop the strategy map (SM) of an Iranian automotive industry and the causal and effects relations of the SM’s variables though fourth generation of balanced scorecard (BSC) and fuzzy DEMATEL (decision-making trial and evaluation laboratory) technique.

This research has employed a fuzzy DEMATEL approach in order to find cause and effect relations. At first step, CSFs in Company A’s SM were determined. Then four experts’ views of Company A’s strategic planning department were gathered and calculated by fuzzy set theory.

Results showed the important role of customer perspective in supporting and achieving the organization’s vision which ultimately will lead to fulfillment of the financial objective of the company through satisfied customers. In other words, the dominant approach to logic of SM design in Company A and the obtained results from this research indicate, Company A can achieve strategic result with a more prominent role of customer and financial perspective, through employing the enabler perspective, i.e. learning and growth perspective.

Current study is limited to Iranian automotive industry. So, the strategic planning managers and future researchers shall consider their own company’s strategic structures for developing their SM.

To the best of knowledge of the authors, it is the first attempt, particularly in the context of Iran, aimed at using fourth generation of BSC and fuzzy DEMATEL technique in an automotive industry which led to the confirmation that these two approaches can jointly be employed for the identifying cause and effect relations in SM and clarification and easy understanding of it. This proposed research structure can be a suitable base for the development of SM in other companies.

The objective of this study is to investigate the barriers hindering the integration of lean manufacturing (LM) practices within the furniture industry of Bangladesh. The traditional operational paradigms in this sector have posed substantial challenges to the effective implementation of LM. In this study, the barriers of implementing LM in the furniture business are examined, aiming to provide a systematic understanding of the barriers that must be addressed for a successful transition.

The research reveals that “Fragmented Industry Structure,” “Resistance to Lean Practices” and “Inadequate Plant Layout and Maintenance”, emerged as the foremost barriers to LM implementation in the furniture industry. Additionally, “Insufficient Expert Management,” “Limited Technical Resources” and “Lack of Capital Investment” play significant roles.

The outcomes of this study provide valuable insights into the furniture industry, enabling the development of strategies for effective LM implementation. One notable challenge in lean implementation is the tendency to revert to established practices when confronted with barriers. Therefore, this transition necessitates informed guidance and leadership. In addition to addressing these internal challenges, the scope of lean implementation should be broadened.

This study represents one of the initial efforts to systematically identify and assess the barriers to LM implementation within the furniture industry of Bangladesh, contributing to the emerging body of knowledge in this area.

Blockchain has the potential to facilitate a paradigm shift in the construction industry toward effectiveness, transparency and collaboration. However, there is currently a paucity of empirical evidence from real-world construction projects. This study aims to systematically review blockchain adoption barriers, investigate critical ones and propose corresponding solutions.

An integrated method was adopted in this research based on the technology–organization–environment (TOE) theory and fuzzy decision-making trial and evaluation laboratory (DEMATEL) approach. Blockchain adoption barriers were first presented using the TOE framework. Then, key barriers were identified based on the importance and causality analysis in the fuzzy DEMATEL. Several suggestions were proposed to facilitate blockchain diffusion from the standpoints of the government, the industry and construction organizations.

The results highlighted seven key barriers. Specifically, the construction industry is more concerned with environmental barriers, such as policy uncertainties (E2) and technology maturity (E3), while most technical barriers are causal factors, such as “interoperability (T4)” and “smart contracts' security (T2)”.

This study contributes to a better understanding of the problem associated with blockchain implementation and provides policymakers with recommendations.

Identified TOE barriers lay the groundwork for theoretical observations to comprehend the blockchain adoption problem. This research also applied the fuzzy method to blockchain adoption barrier analysis, which can reduce the uncertainty and subjectivity in expert evaluations with a small sample.