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The purpose of this research is to determinate the criteria weight in a fashion design scheme evaluation system.

The first stage is to use the fuzzy Delphi method (FDM) by fashion design experts of academia and industries for fashion design evaluation criteria. The second stage is based on the use of a fuzzy analytic hierarchy process (FAHP) to find the criteria weight. Finally, an empirical example is used to illustrate the procedure of obtaining the criteria weights for the evaluation of a fashion design scheme.

The result shows that there are eight evaluation criteria to be obtained for fashion design scheme selection. The evaluation characteristic weights of theme and innovation score almost 90 percent (88.93 percent), the criteria weights of the first five, fashion forecast theme story, best‐seller modification, new idea and product position, score almost 80 percent (79.96 percent) and the criteria weights of the first two, fashion forecast and theme story, score almost 40 percent (39.93 percent) when selecting a design scheme in the fashion design process.

This paper proposes the vital characteristic and criteria for the selection of the fashion design scheme. In selecting fashion design scheme, this study uncovers that the marketing is less important than theme and innovation characteristics. Additionally, the results of this study, indicate the important five criteria, offered designer a set of useful indicators in preparing fashion design scheme and improving the quality of fashion design decision.

This research work has developed an integrated fuzzy Delphi and neutrosophic best–worst framework for selecting the sustailient (sustainable and resilient) supplier for an additive manufacturing (AM)-enabled industry.

An integrated fuzzy Delphi method (FDM) and neutrosophic best–worst method (N-BWM) approach is developed. 34 supplier evaluation criteria falling under 4 groups, that is, traditional, sustainable, resilient, and AM specific, are identified and validated using the FDM. Afterward, the weights of each criterion are measured by N-BWM. Later on, the performance evaluation is carried out to determine the best-suited supplier. Finally, sensitivity analysis is performed to know the stability and robustness of the proposed framework.

The outcome indicates the high performance of the suggested decision-making framework. The analysis reveals that supplier 4 (S4) is selected as the most appropriate for a given firm based on the FDM and N-BWM method.

The applicability of this framework is demonstrated through an industrial case of a 3D-printed trinket manufacturer. The proposed research helps AM decision-makers better understand resiliency, sustainability, and AM-related attributes. With this, the practitioners working in AM business can prioritize the supplier selection criteria.

This is the primitive study to undertake the most critical aspect of supplier selection for AM-enabled firms. Apart from this, an integrated FDM-N-BWM framework is a novel contribution to the literature on supplier selection.

The purpose of this study is to evaluate maintenance strategies based on fuzzy decision-making trial evaluation and laboratory (DEMATEL) and fuzzy analytic network process (ANP) in the petrochemical industry.

This study proposes a hybrid-structured multi-criteria decision-making (MCDM) method based on fuzzy Delphi, fuzzy DEMATEL and fuzzy ANP as a structured methodology to assist decision makers in strategic maintenance. The fuzzy Delphi method (FDM) is applied to refine the effective criteria, fuzzy DEMATEL is applied for defining the direction and relationships between criteria and Fuzzy ANP is used for the selection of optimized maintenance strategy.

The results identify “strategic management complexity” as the top criterion. The predictive maintenance (PdM) with the highest priority is the best strategy. It is followed by reliability-centered (RCM), condition-based (CBM), total productive (TPM), predictive (PM) and corrective maintenance (CM).

Today, companies act in an atmosphere that is known with the features of uncertainty. In this atmosphere, only those companies can survive that have a strategy based on presenting the quality services and products to their customers. Similarly, maintenance as a system plays a vital role in availability and the quality of products, which creates value for customers. The selection of maintenance strategy is a kind of MCDM problem, which includes consideration of different factors. This article considers a broad category of alternates, including CM, PM, TPM, CBM, RCM and PdM.

Assessing a measure of sustainable supply chain management (SSCM) performance is currently a key challenge. The literature on SSCM is very limited and performance measures need to have a systematic framework. The recently developed balanced scorecard (BSC) is a measurement system that requires a balanced set of financial and non-financial measures. The purpose of this paper is to evaluate the SSCM performance based on four aspects i.e. sustainability, internal operations, learning and growth, and stakeholder.

This paper developed a BSC hierarchical network for SSCM in a close-loop hierarchical structure. A generalized quantitative evaluation model based on the Fuzzy Delphi Method (FDM) and Analytical Network Process (ANP) were then used to consider both the interdependence among measures and the fuzziness of subjective measures in SSCM.

The results of this study indicate that the top-ranking aspect to consider is that of stakeholders, and the top five criteria are green design, corporate sustainability, strategic planning for environmental management, supplier cost-saving initiatives and market share.

The main contributions of this study are twofold. First, this paper provides valuable support for supply chain stakeholders regarding the nature of network hierarchical relations with qualitative and quantitative scales. Second, this paper improves practical performance and enhances management effectiveness for SSCM.

In the contemporary global market, supplier selection represents a crucial process for enhancing firms’ competitiveness. This is a multi-criteria decision-making problem that involves consideration of multiple criteria. Therefore this requires reliable methods to select the best suppliers. The purpose of this paper is to examine and propose appropriate method for selecting suppliers.

ANFIS and fuzzy analytic hierarchy process-fuzzy goal programming (FAHP-FGP) are new methods for evaluating and selecting the best suppliers. These methods are used in this study for evaluating suppliers of dairy industries and the results obtained from methods are compared by performance measures such as Mean Squared Error, Root Mean Squared Error, Normalized Root Men Squared Error, Mean Absolute Error, Normalized Root Men Squared Error, Minimum Absolute Error and R2.

The results indicate that the ANFIS method provides better performance compared to the FAHP-FGP method in terms of the selected suppliers scoring higher in all the performance measures.

The proposed method could help companies select the best supplier, by avoiding the influence of personal judgment.

This study uses the well-structured method of the fuzzy Delphi in order to determine the supplier evaluation criteria as well as the most recent ANFIS and FAHP-FGP methods for supplier selection. In addition, unlike most other studies, it performs the selection process among all available suppliers.

The purpose of this paper is to analyze issues pertaining to maintenance performance and to develop a framework that addresses challenges of maintenance management of an international lube blending plant in Malaysia. This study capitalizes on the contribution of selected maintenance department stakeholders from within the plant to develop “tailor-made” intervention strategies for maintenance performance improvement.

The study employed two focus group workshops to ascertain issues facing the maintenance department and identify intervention strategies. The final phase of the study employed fuzzy Delphi method (FDM) to prioritize and rank the intervention strategies for performance improvement.

The first focus group workshop identified 106 issues which could be classified under aspects of spare parts (n=8), equipment (n=14), communication (n=12), non-technical resource (n=8), health, safety and environment (n=4), technical skills and recruitment (n=27), and handling and procedures (n=33). Based on these findings, the second focus group revealed 28 significant performance initiatives to improve the issues identified for maintenance performance improvement. Through the FDM, 18 performance initiatives were ranked and prioritized. Performance improvement through leadership category leads the overall initiatives followed by equipment maintenance management, talent management, work environment and vendor management.

Interesting implications for maintenance management theory would be realized if future research were able to demonstrate that certain aspects or dimensions were related to high performing plant maintenance, and not with low performing ones. Apparently, the present study is not able to provide this clue because it is merely a case study of a single company.

As ILBP attempts to implement maintenance performance improvement, it is pertinent for the management to understand the relevant performance issues and concerns. The appropriate enablers have been identified and must be initiated to chart the strategic role of their maintenance organization.

This study contributes toward further understanding of the maintenance performance management. It has demonstrated the need of organizations to make infrastructural investments such as quality leadership, employee training and empowerment, to name a few, to strategically enhance their maintenance capabilities.

This study uses the FDM for the decision-making process of improving plant maintenance performance. It adds value to the body of knowledge of plant operation management.

This paper aims to contribute significantly to the empirical investigations on adopting Industry 4.0–circular economy in the Malaysian palm oil industry. The paper also aims to theorise and empirically assess a comprehensive model incorporating three aspects and 51 criteria.

A two-stage methodology is proposed using the fuzzy Delphi method and the fuzzy-based analytical network process. Twenty-seven criteria on adoptability of industry 4.0–circular economy were selected for the first-stage methodology, followed by identifying each criteria's intersection with the overall objectives.

The findings indicate that financial constraints, the lack of a collaborative I4.0–CE model, laws and policy, low management support and the training of dedicated employers in I4.0–CE-application are the top five criteria requiring critical attention from the POI.

The overall sustainability advantages of the POI are identified and discussed in depth to establish criteria for industry 4.0–circular economy applications.

This study fills the previous research gap by theoretically explaining POI's industry 4.0 adoption–circular economy from the perspective of two underpinning theories. Due to the pressure towards sustainability, the industry must be ready to adopt industry 4.0–circular economy applications, and resources must be managed appropriately and effectively by sharing and integrating. Advanced industry 4.0 technologies and pragmatic practices such as a circular economy are needed to achieve optimal sustainable development while retaining commercial success.

The purpose of this study is to identify and prioritize the critical success factors (CSFs) of knowledge management (KM) implementation through a novel hybrid model, namely, Fuzzy Delphi method (FDM), interpretive structural modeling (ISM) and revised Simos, which is one of group decision-making (GDM) approaches.

The CSFs of KM implementation were identified through a systematic literature review. FDM was adopted to determine the CSFs in the Iranian oil industry. Then, a novel hybrid model consisting of ISM and revised Simos techniques were used to classify and prioritize the CSFs.

The obtained results suggest that there are 13 CSFs of KM implementation. The result of ISM shows that the CSFs of KM implementation were classified into five levels. The result of revised Simos reveals that the “human resources management” obtained the highest priority and “leadership commitment and support” and “intellectual capital” ranked second and third, respectively.

As this research was performed in the Iranian oil industry, caution should be taken regarding the generalizability of the obtained results.

The top managers of the surveyed companies could get acquainted with CSFs of KM implementation in their organization and use a GDM technique that has various advantages to solve the relevant problems.

This paper provides a twofold contribution to expand KM and GDM literature and to the best knowledge of the authors, it is a novel hybrid GDM model of its kind.

The lack of suitable indicators tailored to manufacturing industries’ needs, particularly to small and medium enterprises (SMEs), has been the major challenge to measure and manage industrial sustainability performance. This paper aims to empirically analyze and select the useful and applicable indicators to measure sustainability performance in the context of SMEs.

A systematic review was carried out to identify potential sustainability indicators from the literature. A questionnaire was designed based on the identified indicators and then pretested with the selected industrial experts, scholars, and researchers to further refine the indicators before data collection from the Italian footwear SMEs. Fuzzy Delphi method with consistency aggregation method was applied to analyze and select the final indicators.

The study’s findings show that the selected indicators emphasized measuring progress toward achieving industrial sustainability goals in terms of increasing financial benefits, reducing costs, improving market competitiveness, improving the effectiveness of resources utilization, and promoting the well-being of employees, customers and the community. In doing so, Italian footwear SMEs can contribute to achieving the Sustainable Development Goals (SDGs) by promoting health and well-being, promoting sustainable economic growth, providing productive employment and decent work, and ensuring responsible consumption and production.

The results of this study have significant social implications in terms of promoting the well-being of employees, customers, and the community.

By providing empirically supported indicators tailored to measure and manage sustainability performance in the context of SMEs, this paper contributes to the existing knowledge in the field of industrial sustainability performance measurement. Furthermore, it links the selected indicators to their respective SDGs to provide policy implications.

Due to the high use of mobile devices, the market share of mobile advertisements (Ads) is significantly growing. Although mobile Ads can contact potential customers at any time and in any location depending on their unique demands, one of the biggest problems for advertisers is how to improve customer repurchases with their Ads. The development and empirical support of customer repurchase through mobile Ads context have not been addressed. Therefore, the purpose of this paper is to define and identify the key attributes of customer repurchase in a mobile Ads context.

In this research, the set of attributes was derived from a systematic literature review and finalized by applying the Fuzzy Delphi method. To develop a hierarchical model and classify the cause/effect groups among identified key attributes, the Fuzzy mixed approach uses a combination of Fuzzy interpretive structural modeling-decision-making trial and evaluation laboratory.

The findings suggest that language, type of website and social media are classified to as essential attributes for improving customer repurchase through mobile Ads.

The focus of the current research is limited to identify and develop the hierarchical interrelationships between customer repurchase attributes that are unique to the mobile Ads business context. Additional research may be conducted for various media contexts and other products/services categories.

This study illustrated how multicriteria decision-making techniques could be used effectively using Fuzzy theory to explore the research area of customer repurchase in mobile Ads concept.