Fuzzy Delphi Research Articles

Development of Design Optimization for Smart Grid (DOfSG) Framework for Residential Energy Efficiency via Fuzzy Delphi Method (FDM) Approach

The smart grid revolution has benefited many sectors but the potential for design optimization among residential units has yet to be explored. Despite some researchers having negative perception of house design's association with the smart grid system, there is in fact potential for investigating design attribute optimisation aligned with the smart grid system. As electricity becomes a necessity of the 21st century society, residential dwellers are becoming more dependent on this indispensable source of energy. As such, this paper explains the development of a framework focusing on design optimization for residential units aligned to the smart grid system using the Fuzzy Delphi Method approach. It focuses on the significant smart grid components linked to the residential sector incorporating key design attributes for energy optimization purposes. The proposed framework denoted two main components of residential design optimization, depicted as indoor and outdoor parameters with its subsequent attributes further categorised into main and detailed components. Twelve design parameters were found to be substantial for the DOfSG development, intended to provide useful guide for aligning residential design towards the smart grid system in Malaysia.

Sustainable entrepreneurship practices of Indian SMEs: A strategic approach using fuzzy Delphi and best worst method

AbstractSmall and medium‐sized enterprises (SMEs) make up a sizable portion of the business sector in most countries. These businesses are also becoming more concerned about sustainability and how to strategically incorporate it into their operations. However, SMEs have shied away from sustainability investments due to a lack of a comprehensive viewpoint on the matter, an overemphasis on an economic perspective, and the resulting devaluation of environmental and social viewpoints. Though the importance of social and environmental practices for assessing sustainable entrepreneurship (SE) has increased, very little research has been done on SE, particularly those linked to the competitiveness of SMEs. The novelty lies in the identification of social and environmental practices for SE and analyzing it using the best worst method. The two main objectives are to calculate the relative weights of these practices and to identify the most crucial elements for judging SMEs' propensity for SE. The findings of this study have significant consequences not only for the businesses themselves but also for decision‐makers in charge of putting policies in place that make it easier to take actions that are consistent with SE.

Retracted: “Best of Both World”: The Amalgamation of Fuzzy Delphi Method with Nominal Group Technique for Dengue Risk Prioritisation Decision-Making

Retracted: “Best of Both World”: The Amalgamation of Fuzzy Delphi Method with Nominal Group Technique for Dengue Risk Prioritisation Decision-Making

Energy security challenges and opportunities in the carbon neutrality context: A hierarchical model through systematic data-driven analysis

This study contributes to fundamental knowledge about energy security strategy for carbon neutrality by identifying important tendencies in terms of future challenges and opportunities from the state-of-the-art literature and by evaluating regional position gaps and global energy strategy for carbon neutrality. Addressing carbon emissions plays an undeniable role in energy security improvement since most countries have advanced to responding to climate change. However, whether these responses achieve actual good outcomes remains questionable. Since there are plenty of related studies and indicators, this study conducts data-driven analysis to generate an energy security and carbon neutrality model and indicates the challenges and opportunities for future assessments. A hybrid method incorporating content analysis, the fuzzy Delphi method, interpretive structural modeling, the fuzzy decision-making trial and evaluation laboratory, and the entropy weight method is implemented to understand the complex system of energy security and carbon neutrality and its inner interrelationships as well as regional perspectives. There are 19 valid indicators clustered into 5 aspects that form a strategic hierarchical model. Overall, sustainable energy strategies, renewable energy conversion, and carbon mitigation approaches are found to be causal aspects. The top critical indicators are cobenefits, the energy transition, a low-carbon society, renewable energy policy, renewable energy sources, energy resilience, and low-carbon technology. Regional assessment is taken as an approach; despite the imbalance in the information provided by regions, the outputs still leave much room for development.

Extracting Evaluation Factors of Social Resilience in Water Resource Protection Areas Using the Fuzzy Delphi Method

Development in water resource protection areas frequently grapples with balancing environmental sustainability and local economic growth. Consequently, a nuanced assessment of social resilience becomes imperative. This research presented a case study of the Water Resource Protection Area in Taipei, gauging its social resilience across five dimensions: “social support function”, “inclusive governance”, “economic allocation”, “built environment”, and “resources for sustainability”. From these, 49 influential factors that could impact the social resilience of the water resource protection area were discerned. Through the engagement of 21 experts via questionnaires and subsequent analysis using the Fuzzy Delphi method, this study identified 23 core factors. Notably, influential factors pertaining to the “social support function” significantly impacted the water resource protection area. The findings aim to streamline the evaluation of social resilience in water resource protection areas, potentially guiding future research utilizing the multi-criteria decision-making (MCDM) method and steering industrial developments in these areas.

Analyzing drivers of sustainable project‐driven supply chains: A fuzzy Delphi methodology–grey relational analysis approach

AbstractA sustainable project‐driven supply chain (SPDSC) refers to integrating sustainability into project management to improve the sustainability performance of projects. Integrating sustainability and supply chain management is any project‐based organization's most significant performance‐related challenge. Therefore, the present study explores the drivers that can effectively tackle supply chain issues in managing projects undertaken in construction contracting firms for long‐term sustainability. Sixteen critical drivers were considered through a rigorous literature review and fuzzy Delphi method (FDM) for construction contracting firms. Then, selected drivers were used to analyze established construction contracting firms using a grey relational analysis (GRA) technique. The results highlight that construction contracting firms (CCFs) considered the drivers of sustainable use of resources, energy and eco‐efficiency, and environmental impact assessment; stakeholder engagement and social impact; and supply chain collaboration dimensions need to be improved for enhancing the sustainability of PDSCs. This study's contribution is twofold: It quantifies the identified set of critical drivers relevant to SPDSCs; it offers the CCFs a practical toolkit for sustainable project deliverables.

Framework for critical information infrastructure protection in smart government: a case study in Indonesia

PurposeThis paper aims to develop a framework for critical information infrastructure (CII) protection in smart government, an alternative measure for common cybersecurity frameworks such as NIST Cybersecurity Framework and ISO 27001. Smart government is defined as the government administration sector of CII due to its similarity as a core of smart technology.Design/methodology/approachTo ensure the validity of the data, the research methodology used in this paper follows the predicting malfunctions in socio-technical systems (PreMiSTS) approach, a variation of the socio-technical system (STS) approach specifically designed to predict potential issues in the STS. In this study, PreMiSTS was enriched with observation and systematic literature review as its main data collection method, thematic analysis and validation by experts using fuzzy Delphi method (FDM).FindingsThe proposed CII protection framework comprises several dimensions: objectives, interdependency, functions, risk management, resources and governance. For all those dimensions, there are 20 elements and 41 variables.Practical implicationsThis framework can be an alternative guideline for CII protection in smart government, particularly in government administration services.Originality/valueThe author uses PreMiSTS, a socio-technical approach combined with thematic analysis and FDM, to design a security framework for CII protection. This combination was designed as a mixed-method approach to improve the likelihood of success in an IT project.

Expert Agreement towards the Orang Asli Community Learning Center Model Based On the Local Environment: Analysis of the Fuzzy Delphi Method

The purpose of this study is to obtain the agreement and opinion of experts towards the framework of the Orang Asli Community Learning Center model based on the local environment. This study has used Fuzzy Delphi method as well as using a 7 Likert-scale to collect feedback from 11 experts in various fields of education at public universities in Malaysia. A total of 5 main elements and sub-item elements of the questionnaire were given to experts for evaluation. Data was analyzed using triangular fuzzy number and position (ranking) with each element of the model is determined using defuzzification process. The results of the analysis of expert agreement and consensus have been shows that the agreement value is at a good level. This shows the elements of The Community Learning Center model has received good expert approval. The elements are arranged according to the priority (ranking) that has been agreed by experts.

Development of Antecedent Factors for Malaysian Women’s Entrepreneurial Resilience Framework: A Fuzzy Delphi Method

This study assesses the antecedent factors of entrepreneurial resilience and the underlying criteria to develop a Malaysian women’s entrepreneurial framework based on the expert linguistic consensus to identify potential strategies to empower women entrepreneurship sector in Malaysia. The Delphi Fuzzy (FDM) method is used to obtain expert consensus on the important factors that stimulate and encourage entrepreneurial resilience based on a review of previous literature. The judgment sampling technique was used to develop a survey and distributed it to 20 experts. The linguistic consensus of experts is analyzed using Fuzzy Set Theory and Triangular Fuzzy Numbers (TFN). This study confirms the strategic factors that can foster the development of resilient women entrepreneurs and identifies key resilience criteria that play a vital role in boosting the business longevity of women-owned SMEs. Importantly, religion and psychological capital are key to developing entrepreneurial resilience among women entrepreneurs. In addition, technology skills should be leveraged to deal with an increasingly complex market environment and create opportunities in a crisis. This study focuses on the context of Malaysian women entrepreneurs, who may not represent other countries. This study highlights the importance of entrepreneurial psychological traits (i.e., cognitive, and behavioural) for theoretical and managerial implications in fostering the ability of women entrepreneurs to adjust to new circumstances and thereby contribute to the long-term sustainability of their businesses. Upcoming studies are recommended to test the resilience factor of these entrepreneurs on a sample of the female entrepreneur population through exploratory studies using questionnaire instruments.

Supply chain challenges and recommendations for international development agriculture projects: an application of the FGD-fuzzy Delphi approach

International development (ID) agriculture projects play a crucial role in ensuring the long-term viability of agriculture-based economies in developing countries. While, unlike other development projects, these projects face unique supply chain challenges that agriculture development projects focus primarily on increasing crop production to ensure food security in a country, which is affected not only by social or national context issues but also by natural environments. Since no previous research has investigated the supply chain issues of ID agriculture projects, this study makes a significant contribution to the literature by identifying the key supply chain challenges of ID agriculture projects in a developing country context and proposing specific solutions to these challenges. Initially, the study conducted a literature review to generate a primary list of project supply chain challenges. To identify more significant and relevant challenges, the study conducted focus group discussions and consulted with an expert panel; it identified seventeen critical challenges and provided specific recommendations to address each challenge. The recommendations were then ranked using the fuzzy Delphi method based on their importance. Certain critical challenges, such as political influence, are exacerbated by the unique project and context environments. While others are the result of donors’ incompatible strategies and influences (e.g., donor-incompatible regulations). Some of them are created by both the host nation and the donors (delayed project launch, for example). Moreover, the projects face specific challenges posed by natural environments (such as natural disasters). To ensure value for money within the project’s scope, it is recommended that the professionals adopt the most important strategies to address the challenges. Not only are the findings impressive for industry professionals, but also policymakers, development partners, academics, and future researchers.

A circular waste bioeconomy development model in the Ecuadorian fishery industry: the impact of government strategy on supply chain integration and smart operations.

This study develops a set of measures to address the interrelationship among circular waste-based bioeconomy (CWBE) attributes, including those of government strategy, digital collaboration, supply chain integration, smart operations, and a green supply chain, to build a circular bioeconomy that feeds fish waste back into the economy. CWBE development is a potential solution to the problem of waste reuse in the fish supply chain; however, this potential remains untapped, and prior studies have failed to provide the criteria to guide its practices. Such an analytical framework requires qualitative assessment, which is subject to uncertainty due to the linguistic preferences of decision makers. Hence, this study adopts the fuzzy Delphi method to obtain a valid set of attributes. A fuzzy decision-making trial and evaluation was applied to address the attribute relationships and determine the driving criteria of CWBE development. The results showed that government strategies play a causal role in CWBE development and drive digital collaboration, smart operations, and supply chain integration. The findings also indicated that smart manufacturing technology, organizational policies, market enhancement, supply chain analytics, and operational innovation are drivers of waste integration from fisheries into the circular economy through waste-based bioeconomy processes.

Determinants of prioritised influencing factors on coal spontaneous combustion propensity – A Fuzzy-Delphi-geometric mean analytic hierarchy process

One of the most common hazards in coal mines is spontaneous combustion, a significant cause of coal loss in underground mines. Specifying a suitable approach for the determinants of prioritized influencing factors on coal spontaneous combustion propensity is challenging. There needs to be more research that directly addresses the uncertainty of human judgement in assessing the factors influencing coal propensity to self-combustion. This is the first attempt to address the aforesaid problem by ranking the factors influencing spontaneous coal combustion. The ranking was performed using the Fuzzy Delphi Analytic Hierarchy Process (FDAHP) with two variants of the Geometric Mean Method (GMM), which enabled the analysis of both quantitative and qualitative data related to the rating of each factor influencing spontaneous combustion risk and the relative importance of each factor related to coal seam characteristics, geological aspects, mining practices, and environmental aspects. The results show that ‘GMM as a whole’ is a comparatively best-aggregating approach to the AHP process. The presented case study of using this methodology in underground mine conditions confirms its efficacy in assessing susceptibility to coal spontaneous combustion. This mainly concerns the pace and reliability of the obtained results and the determination of risk evaluation system based on intrinsic and extrinsic factors influencing susceptibility to spontaneous combustion of coal. Finally, this systematic technique was validated in the research area by utilizing spontaneous combustion incident that occurred in Jharia and Raniganj coalfields, which revealed rather excellent concordance in Jharia and Raniganj coalfields. The study can be used in mine planning to develop engineering data to select the operational parameter and prevent the initiation of spontaneous heating by identifying intrinsic factors and optimizing extrinsic factors.

Utilize Fuzzy Delphi Method to Design and Develop T2IG Application for Primary Schools

Education has encountered multiple transformations in tandem with the globalisation of society. Technology is an essential tool for conducting teaching and learning activities. COVID-19 pre- and post-education also emphasize the importance of technology in accessing education. This study aims to develop a Text to Infographic (T2IG) application. T2IG is an application that developed on two platforms, namely in the form of a website and a smartphone application. Users (students) upload text, and the Google Cloud Platform Artificial Intelligence components will translate it into a graphical form containing information. In addition, Google Cloud Platform Artificial Intelligence will quote actual contents from the entire text uploaded by the user. In this study, the process of gathering experts' consensus to identify the application's elements and components that should be used as the application's primary function. The Fuzzy Delphi Method was used to identify the consensus of the experts through a questionnaire. Using the Fuzzy Delphi technique is to get concessions from experts on the development of instructional materials. This method involves the use of fuzzy set theory which has been integrated with the classic Delphi method. The use of this technique helps in determining the requirements of the elements that are important in the development of instructional materials in detail. A total of 12 experts were identified using the expert sampling method. These 12 experts are among lecturers and officials from the fields of education, technology and language who are currently working at the University, Teaching Institutions and the Department of Education. The study identified seven key components and 25 sub-constructs that should be used in the development of the T2IG application. The findings highlight the importance of using technology to enhance teaching and learning activities and the significance of experts' opinions in the development of instructional materials. Twelve study experts accepted a total of six components. The findings of this study have implications for the development of instructional applications that will be developed. This study's findings also emphasise the appropriate components for developing T2IG applications as proposed.

An interpretive structural modeling—analytic network process approach for analysing green entrepreneurship barriers

AbstractEntrepreneurship is one of the issues that plays a key role in the economic growth and development of countries. This economic development and technological advancement have caused environmental damage, which has led entrepreneurs to move towards sustainable production and green entrepreneurship. There are, however, challenges and barriers in front of green entrepreneurs. Hence, this article aims to identify the barriers and challenges of green entrepreneurship in Iran and explore their Interactions and prioritization. To achieve this goal, two quantitative and qualitative approaches were used. In the qualitative approach, using the Fuzzy Delphi method and using expert opinions in this field, 16 factors were identified. In the quantitative phase, the ISM-ANP combination approach was used. First, Interpretive Structural Modeling (ISM) was used to analyze the Interactions between these factors. Finally, using the ISM output, the analytic network process (ANP) method was used to prioritize these barriers. The results showed that the factor of reducing budget allocations and investing in green entrepreneurship in the first priority and the factor of high investment costs in the last priority. Given that so far few studies have been conducted in Iran on the barriers to green entrepreneurship, this paper provides a basis for understanding the various factors that prevent the implementation of green entrepreneurship. Also the analysis of these barriers by using the ISM-ANP approach is a new attempt and important in the field green entrepreneurship.

The factors obstructing the blockchain adoption in supply chain finance: a hybrid fuzzy DELPHI-AHP-DEMATEL approach

PurposeSupply chain finance (SCF) is an advanced financing solution for medium and small organizations. However, due to its nascent stage, SCF is still struggling with its application in the supply chain. The blockchain application in SCF can bring lots of opportunities and smart techniques to deal with financing to organizations. However, some factors restrict the proper adoption of blockchain in SCF. Therefore, this study aims to identify and analyze the factors obstructing blockchain adoption in SCF.Design/methodology/approachThe present study applied a hybrid fuzzy DELPHI-AHP-DEMATEL to validate and analyze the factors. The fuzzy Delphi techniques were adopted to validate the identified factors. Thereafter, the analytic hierarchy process (AHP) has been used to prioritize the validated factors. Further, the decision-making trial and evaluation laboratory (DEMATEL) method has opted to classify the factors into cause-and-effect groups.FindingsThe result of the study revealed that lack of technological competence and confidentiality leaking are the most prioritized factors and act as the prime factors for the obstacles in the blockchain application in the SCF. The application of the DEMATEL method revealed that the highest causing factor is authenticity, and the highest effecting factor is high cost.Practical implicationsThe current study enhances the knowledge and information of managers and policymakers about the challenges associated with the blockchain application in SCF as well as provides better insight to deal with various factors obstructing blockchain adoption in SCF.Originality/valueThe current study is the first of its kind, where factors obstructing blockchain adoption in SCF are identified and validated with the help of experts and practitioners by incorporating the fuzzy Delphi method. Thereafter, the validated factors are prioritized by using fuzzy AHP and fuzzy DEMATEL techniques helps to identify the cause-and-effect group, which opens the door for future research work.

Design and consensus content validity of the questionnaire for b-learning education: A 2-Tuple Fuzzy Linguistic Delphi based Decision Support Tool

Classic Delphi and Fuzzy Delphi methods are used to test content validity of data collection tools such as questionnaires. Fuzzy Delphi takes the opinion issued by judges from a linguistic perspective reducing ambiguity in opinions by using fuzzy numbers. We propose an extension named 2-Tuple Fuzzy Linguistic Delphi method to deal with scenarios in which judges show different expertise degrees by using fuzzy multigranular semantics of the linguistic terms and to obtain intermediate and final results expressed by 2-tuple linguistic values. The key idea of our proposal is to validate the full questionnaire by means of the evaluation of its parts, defining the validity of each item as a Decision Making problem. Taking the opinion of experts, we measure the degree of consensus, the degree of consistency, and the linguistic score of each item, in order to detect those items that affect, positively or negatively, the quality of the instrument. Considering the real need to evaluate a b-learning educational experience with a consensual questionnaire, we present a Decision Making model for questionnaire validation that solves it. Additionally, we contribute to this consensus reaching problem by developing an online tool under GPL v3 license. The software visualizes the collective valuations for each iteration and assists to determine which parts of the questionnaire should be modified to reach a consensual solution.

Developing and validating an instrument to assess women’s empowerment in dealing with domestic violence in Iran: a mixed-methods study protocol

IntroductionDespite the emphasis on empowerment in interventions supporting women against domestic violence and ending spousal abuse, there is still no standard and accurate instrument to evaluate women’s empowerment in this...

Research on key influencing factors for site selection of DC microgrid-based hydrogen-electric hybrid refueling stations

In the context of the dual-carbon economy, HRSs play a critical role as an essential intermediary hub for upstream hydrogen production, midstream hydrogen storage and transportation, and downstream vehicle fueling. The use of renewable energy sources for hydrogen production and refueling has become a topic of great interest, and direct current (DC) microgrid-based HRSs are a promising model. However, there is a lack of research on the key influencing factors for the site selection of electric-hydrogen hybrid refueling stations. To address this research gap, this study reviewed the scientific literature on refueling station site selection and identified 34 site selection factors based on the characteristics of DC microgrid-based electric-hydrogen hybrid refueling stations. The importance of these factors was evaluated through a combination of fuzzy Delphi and LBWA models, and an optimized site selection evaluation index system was constructed. The results showed that hydrogen storage technology, wind speed, hydrogen production technology, lighting conditions, spatial safety, profit risk, and leakage risk are the key factors that influence site selection decisions. After eliminating nine non-important indicators, a site selection index system with 1-4-25 layers factors was established. The proposed key factors and index system have important guiding and reference significance for governments and investors in making site selection decisions and managing electric-hydrogen hybrid refueling station projects.

The Usability of Dhikr Psychotherapy Model in Developing Muslim Children with Autism

The number of children born in Malaysia with autism has increased in recent years. According to a 2015 National Health survey interview, 1 in 45 children have shown autistic symptoms. Various therapy approaches have been used to improve the self-development of autistic children. However, most of the methods applied less emphasized religious and spiritual development. This article presents the need to include religious elements in therapy process, as well as the usability of Dhikr Psychotherapy Model in the development of Muslim children with autism. This article collected its data using the literature study method and expert questionnaires using the Fuzzy Delphi Method approach. The study found that the Dhikr Psychotherapy Model has a significant effect in helping the development of Muslim autistic children.

Classifying the Factors Affecting Information Therapy to Support Clinical Decisions on Addiction.

The present study aimed to identify the dimensions and components of developing an information therapy approach for clinical decisions on addiction in addiction treatment centers based on the opinions of thematic specialists in Iran using the fuzzy Delphi technique. This study was a qualitative one conducted using Delphi method on 20 researchers of addiction treatment in the areas of psychiatry, psychology, medicine, etc. The analysis of the data revealed 92 indicators in two dimensions, namely information dimension (health literacy) and treatment dimension (health services), each containing 6 components. The information dimension included acquiring information, identifying information, sharing information, raising awareness, information needs, and health knowledge, and the treatment dimension included patient satisfaction, information-seeking behaviors and skills, treatment methods and costs, participatory care and use of information, educational interventions, and disease prevention. Developing an information therapy approach in addiction treatment, as a cost-effective and low-cost method, is one of the cognitive strategies that can be used by officials to pave the way for health in this regard. This technique aims to improve the quality of medical services and care for addicts and is a suitable solution to meet their needs.