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Evolution of the fuzzy Delphi analysis template (FDMv2.0) development for impact studies
... The fuzzy Delphi analysis template (FDMv2. 0) proposed by Ridhuan et al. (2024) was employed in the progress of achieving consensus. The evolution of innovation on the development of Fuzzy Delphi Analysis Template or known as FDMv2.0 which has been developed since 2013 as well as through the process of innovation in ensuring the generation of data findings for FDM methods can be implemented well and effectively. ...
The main purpose of this study was to evaluate an interdisciplinary teaching module (IHTM) that had been developed, and this evaluation determined the usability of the module and its instructional objectives in strengthening the higher-order thinking skills of Chinese university students. The evaluation process involved a total of 37 teachers in interdisciplinary fields; these participants included 27 young teachers and 10 expert teachers. Descriptive analyses, comparative analyses, and Fuzzy Delphi (FDM)-based expert consensus were used to derive results in terms of the module's usability. Findings indicated the module's usability and usefulness in strengthening higher-order thinking skills, and the 10-member expert panel reached a consensus on the evaluation of the module's usability.
Facebook can increase interaction between teachers and students in web-based communication. Many research studies related to the use of Facebook by students and impact on their academic achievement but none of the research focused on futures study related to Facebook in education. The objective of this study was to get consensus on the benefits of the use of Facebook as a tool for teaching and learning in the future, student participation in teaching and learning process, suitability of subject in teaching and learning process via Facebook in the future, the impact of the use of Facebook in skills of students and the impact of the use of Facebook in terms of students’ character in the future. In this study, Fuzzy Delphi Method using a seven-point Linguistic scale was used to get consensus of 20 experts consisting of 10 specialist teachers, five IT specialists and five lecturers in the Faculty of Education. This study can be beneficial not only to teachers and students, but also as a reference to the education system in Malaysia to transform education through collaboration with social networking technology in the future. All the domains and subdomains in this study obtained consensus from the experts.
A new fuzzy Delphi method is proposed. The method employs the fuzzy statistics and technique of the conjugate gradient search to fit membership functions. Membership functions besides triangles may be derived for the fuzzy forecasts. A procedure termed as stabilization rather than convergence of the iterative interval-valued surveys is utilized, in which the α-level set of the fuzzy forecasts is used. The testing of stability of the process is conducted on the fuzzy forecasts between two consecutive iterations instead of within each iteration. An application of this method to the problem of managerial talent assessment for a company located in Taiwan and the obtained results are provided.
This article describes the Delphi method, how it is used, its underlying assumptions, its strengths and limitations, its potential benefits to higher education research, and some key considerations in its use. The authors illustrate the Delphi method by discussing a recent national study to develop a set of management audit assessment criteria. Their focus is on often overlooked and unique aspects of this versatile qualitative research methodology.
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Author Address: Murray, Tj Syracuse Univ,Sch Business Adm,Syracuse,Ny 13210, USA Syracuse Univ,Sch Business Adm,Syracuse,Ny 13210, USA Babson Coll,Babson Pk,Ma 02157 Calif State Univ Sacramento,Sch Business & Publ Adm,Sacramento,Ca 95819
ID - 23
The purpose of this research is to establish an evaluation model for selecting the most appropriate technology for development in Taiwan, based on 14 evaluation criteria. Due to the inherent uncertainty and imprecision associated with the mapping of decision makers’ perception to crisp values, linguistic variables are used to assess the weights of the criteria and the ratings of each technology with respect to each criterion. The criteria weights and technology ratings are collected through a seven-point linguistic scale using a Delphi questionnaire. The linguistic scores are then converted into fuzzy numbers, and a consensus of the decision makers’ opinions on weights and ratings is mathematically derived using fuzzy Delphi methodology. We have used the model to evaluate seven different hydrogen production technologies. The results indicate that hydrogen production via electrolysis by wind power and that via electrolysis by photovoltaic electricity are the two technologies that should be chosen for further development.
This study aims to construct ranking indicators from the perspective inside of the university and shift the ranking target
from overall university quality to undergraduate education quality. In dealing with the complexity of the concept of undergraduate
education quality, two-stage questionnaire survey was conducted to gain comprehensive opinions from 20 higher education evaluation
experts. The Fuzzy Delphi Method then was introduced to perform data analysis and help final indicator selection as well as
the distribution of weights. The results compared with ranking systems conducted by US NEWS and Guardian showed weighting
differences and greater comprehensiveness in terms of the types of measures, sources of data and different perspectives from
the students, employers and the academics. Most important of all, this study provided a more transparent ranking system and
detailed ranking methodology that are crucial for users’ understanding and use of the ranking system.
KeywordsUniversity ranking-Quality of undergraduate education-Fuzzy Delphi Method (FDM)
Knowledge acquisition has been a critical bottleneck in building knowledge-based systems. In past decades, several methods and systems have been proposed to cope with this problem. Most of these methods and systems were proposed to deal with the acquisition of domain knowledge from single expert. However, as multiple experts may have different experiences and knowledge on the same application domain, it is necessary to elicit and integrate knowledge from multiple experts in building an effective expert system. Moreover, the recent literature has depicted that “time” is an important parameter that might significantly affect the accuracy of inference results of an expert system; therefore, while discussing the elicitation of domain expertise from multiple experts, it becomes an challenging and important issue to take the “time” factor into consideration. To cope with these problems, in this study, we propose a Delphi-based approach to eliciting knowledge from multiple experts. An application on the diagnosis of Severe Acute Respiratory Syndrome has depicted the superiority of the novel approach.
To face the reality of practical multiple criteria problems usually possessing characters of fuzziness, and to consider group decision making with various subjective–objective backgrounds usually participating in decision-making process. In this paper, the experts' opinions are described by linguistic terms which can be expressed in trapezoidal (or triangular) fuzzy numbers. To make the consensus of the experts consistent, we utilize fuzzy Delphi method to adjust the fuzzy rating of every expert to achieve the consensus condition. For the aggregate of many experts' opinions, we take the operation of fuzzy numbers to get the mean of fuzzy rating, and the mean of weight, . In multi-alternatives and multi-attributes cases, the fuzzy decision matrix is constructed by the mean of the fuzzy rating, . Then, we can derive the aggregate fuzzy numbers by multiplying the fuzzy decision matrix with the corresponding fuzzy attribute weights. The final results become a problem of ranking fuzzy numbers. We also propose an easy procedure of using fuzzy numbers to rank aggregate fuzzy numbers . In this way, we can obtain the best selection for evaluating system. For practical application, we propose an algorithm for evaluating the best main battle tank by fuzzy decision theory and compare it with other method.
The aim of this paper is to extend the TOPSIS to the fuzzy environment. Owing to vague concepts frequently represented in decision data, the crisp value are inadequate to model real-life situations. In this paper, the rating of each alternative and the weight of each criterion are described by linguistic terms which can be expressed in triangular fuzzy numbers. Then, a vertex method is proposed to calculate the distance between two triangular fuzzy numbers. According to the concept of the TOPSIS, a closeness coefficient is defined to determine the ranking order of all alternatives by calculating the distances to both the fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS) simultaneously. Finally, an example is shown to highlight the procedure of the proposed method at the end of this paper.
Three median alpha-levels of a fuzzy number A are introduced. Two of them are based on the vertical and horizontal dimensions of A, one on the cardinality of A. Approximation of fuzzy numbers by alpha-cuts associated with the median alpha-levels is discussed. Percentile characterizations of alpha-cuts with respect to the selected properties of fuzzy numbers are proposed.
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