A fuzzy DEMATEL approach based on intuitionistic fuzzy information for evaluating knowledge transfer effectiveness in GSD projects

The offshore/onsite teams' effectiveness of knowledge transfer is significantly measured by various kinds of factors. In this paper, we propose a knowledge transfer (KT) assessment framework which integrates four criteria for evaluating the KT effectiveness of GSD teams. These are: knowledge, team, technology, and organisation factors. In this context, we present a fuzzy DEMATEL approach for assessing GSD teams KT effectiveness based on intuitionistic fuzzy numbers (IFNs). In this approach, decision makers provide their subjective judgments on the criteria, characterised on the basis of intuitionistic fuzzy sets. Moreover, intuitionistic fuzzy sets used in the fuzzy DEMATEL approach can effectively assess the KT effectiveness criteria and rank the alternatives. Subsequently, the entire process is illustrated with GSD teams' KT evaluation criteria samples, and the factors are ranked using fuzzy linguistic variables which are mapped to IFNs. Afterwards, the IFNs are converted into their corresponding basic probability assignments (BPAs) and then the Dempster-Shafer theory is used to combine the group decision making process. Besides, illustrative applicability and usefulness of the proposed approach in group decision making process for the evaluation of multiple criteria under fuzzy environment has been tested by software professionals at Inowits Software Organisation in India

An Evidential Fractal Analytic Hierarchy Process Target Recognition Method

Target recognition in uncertain environments is a hot issue, especially in extremely uncertain situation where both the target attribution and the sensor report are not clearly represented. To address this issue, a model which combines fractal theory, Dempster-Shafer evidence theory and analytic hierarchy process (AHP) to classify objects with incomplete information is proposed. The basic probability assignment (BPA), or belief function, can be modelled by conductivity function. The weight of each BPA is determined by AHP. Finally, the collected data are discounted with the weights. The feasibility and validness of proposed model is verified by an evidential classifier case in which sensory data are incomplete and collected from multiple level of granularity. The proposed fusion algorithm takes the advantage of not only efficient modelling of uncertain information, but also efficient combination of uncertain information

A comprehensive review of hybrid game theory techniques and multi-criteria decision-making methods

More studies trend to hybrid the game theory technique with the multi-criteria decision-making (MCDM) method to aid real-life problems. This paper provides a comprehensive review of the hybrid game theory technique and MCDM method. The fundamentals of game theory concepts and models are explained to make game theory principles clear to the readers. Moreover, the definitions and models are elaborated and classified to the static game, dynamic game, cooperative game and evolutionary game. Therefore, the hybrid game theory technique and MCDM method are reviewed and numerous applications studied from the past works of literature are highlighted. The result of the previous studies shows that the fundamental elements for both frameworks were studied in various ways with most of the past studies tend to integrate the static game with AHP and TOPSIS methods. Also, the integration of game theory techniques and MCDM methods was studied in various applications such as politics, economy, supply chain, engineering, water management problem, allocation problem and telecommunication network selection. The main contribution of the recent studies of employment between game theory technique and MCDM method are analyzed and discussed in detail which includes static and dynamic games in the non-cooperative game, cooperative game, both non-cooperative and cooperative games and evolutionary gam

Developing a novel Grey integrated multi-criteria approach for enhancing the supplier selection procedure: A real-world case of Textile Company

upplier selection is one of the most essential activities in purchase management and plays a crucial role in the production phase. Supplier selection as a vital step of supply chain management is a multi-criteria decision-making issue. For any organization, the process of selecting the best supplier holds variable multilayered complications involving quantitative and qualitative criteria. This paper tackles the supplier selection problem in a Turkish Textile Company. The present study carries out a novel grey integrated multi-criteria approach for enhancing the supplier procedure within Textile Company with the help of the grey analytical hierarchy process G-AHP model for weighting the set of criteria, and the grey weighted aggregated sum product assessment WASPAS-G model for prioritizing the suppliers. The study starts with reviewing the previous works of multi-criteria decision-making MCDM methods and the list of existing criteria evaluation in supplier selection. Then, the range of criteria is selected based on the company requirements and the experts’ interview. In the case study, the consistency rate of the models is tested in order to verify the quality of experts’ judgments. The final results affirm that Grey integrated approach could be efficient and far more precise than the existing models for overcoming the supplier selection and evaluation obstacles in the supply chain management

An overview of fuzzy techniques in supply chain management: bibliometrics, methodologies, applications and future directions

Every practice in supply chain management (SCM) requires decision making. However, due to the complexity of evaluated objects and the cognitive limitations of individuals, the decision information given by experts is often fuzzy, which may make it difficult to make decisions. In this regard, many scholars applied fuzzy techniques to solve decision making problems in SCM. Although there were review papers about either fuzzy methods or SCM, most of them did not use bibliometrics methods or did not consider fuzzy sets theory-based techniques comprehensively in SCM. In this paper, for the purpose of analyzing the advances of fuzzy techniques in SCM, we review 301 relevant papers from 1998 to 2020. By the analyses in terms of bibliometrics, methodologies and applications, publication trends, popular methods such as fuzzy MCDM methods, and hot applications such as supplier selection, are found. Finally, we propose future directions regarding fuzzy techniques in SCM. It is hoped that this paper would be helpful for scholars and practitioners in the field of fuzzy decision making and SCM

DCM: D Number Extended Cognitive Map. Application on Location Selection in SCM

Offshore outsourcing is a widely used management technique for performing business functions with the aim of reducing labor and transportation costs. The selection of locations has a significant influence on the supply chain’s resilience and qualities, but the influence of multiple external factors on the supply chain’s performance in local places in a complex and uncertain environment has not been examined. In this study, we investigated the influence of external factors in a highly uncertain and complicated situation in which relationships between external factors and supply chain resilience are complicated. Furthermore, we proposed a novel model to select locations from a comprehensive perspective. Specifically, the fuzzy cognitive map (FCM) is utilized to simulate the dynamic influence process where the adjacency is aggregated by D numbers. The weights of different resilience capabilities are considered from the perspective of maximizing benefits by using the decision-making trial and evaluation laboratory-analytic network processes (DEMATEL-ANP) model. By comparing the distance to the ideal solutions, we selected the best alternative location. Our results differ from the general case, which reveals that the weights of different capabilities influence selections

STUDY TOWARDS THE TIME-BASED MCDA RANKING ANALYSIS – A SUPPLIER SELECTION CASE STUDY

Decision-making processes increasingly use models based on various methods to ensure professional analysis and evaluation of the considered alternatives. However, the abundance of these methods makes it difficult to choose the proper method to solve a given problem. Also, it is worth noting whether different results can be obtained using different methods within a single decision problem. In this paper, we used three selected Multi-Criteria Decision Analysis (MCDA) methods called COMET, TOPSIS, and SPOTIS in order to examine how the obtained rankings vary. The selection of material suppliers was taken into consideration. The equal weights, entropy and standard deviation methods were used to determine the weights for criteria. Final preferences values were then compared with the WS similarity coefficient and weighted Spearman correlation coefficient to check the similarity of the received rankings. It was noticed that in the given problem, all of the methods provide highly correlated results, and the obtained positional rankings are not significantly different. However, practical conclusions indicate the need to look for improved solutions in the correct and accurate assessment of suppliers in a given period

Performer selection in Human Reliability analysis: D numbers approach

Dependence assessment among human errors in human reliability analysis (HRA) is an significant issue. Many previous works discussed the factors influencing the dependence level but failed to discuss how these factors like "similarity of performers" determine the final result. In this paper, the influence of performers on HRA is focused, in addition, a new way of D numbers which is usually used to handle with the multiple criteria decision making (MCDM) problems is introduced as well to determine the optimal performer. Experimental result demonstrates the validity of proposed methods in choosing the best performers with lowest the conditional human error probability (CHEP) under the same circumstance

Modeling and analysing the barriers to the acceptance of energy-efficient appliances using an ISM-DEMATEL approach

Electricity savings from energy-efficient appliances (EEAs) may have a significant impact on reducing global warming. There are several barriers confronted by EEAs, which have lowered their acceptance rate. The current study identifies and highlights key barriers to strengthening domestic sector adoption of EEAs in developing countries. In the current study, thirteen barriers were discovered by an indepth literature review and the judgement of experts as well. Further, integrated “Interpretive Structural Modeling” (ISM) and “Decision Making Trial and Evaluation Laboratory” (DEMATEL) approaches are utilized to evaluate barriers. The ISM technique is implemented to categorize barriers into distinct hierarchy levels, and “Cross-Impact Matrix Multiplication Applied to Classification” (MICMAC) analysis to divide barriers among four clusters “independent, linkage, dependent, and autonomous”. Moreover, the DEMATEL methodology is applied to classify the barriers among cause and effect clusters. The integrated ISM and DEMATEL approach suggests that the topmost influencing barriers to the acceptance of EEAs are the lack of Government policies and initiatives, lack of attractive loan financing, and subsidized energy prices. This study would help researchers, regulators, producers, policymakers, and consumers to comprehend the need for additional developments and understand that the adoption of EEAs is a current need. Overall, the results of this study expedite stakeholders with the key barriers that may assist to enhance the acceptance of EEAs within the domestic sector. An extensive literature survey showed a dearth of studies for the identification, modeling, and analysis of barriers collectively. Therefore, the current work utilized the ISM and DEMATEL approaches to fill the gap and to provide more comprehensive knowledge on barriers related to the acceptance of EEA