Fuzzy multi-attribute group decision making to identify the order of establishing temporary logistics hubs during disaster response

2019 ◽  
Vol 9 (1) ◽  
pp. 2-21 ◽  
Author(s):  
Rajali Maharjan ◽  
Shinya Hanaoka
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Disaster Response ◽  
Group Decision ◽  
Decision Makers ◽  
Numerical Illustration ◽  
Content Type ◽  
Using Data ◽  
The Impact ◽  
Post Disaster

Purpose The purpose of this paper is to reveal the importance of the order of establishment of temporary logistics hubs (TLHs) when resources (mobile storage units used as TLHs) are limited and to present the development and implementation of a methodology that determines the order of establishment of TLHs to support post-disaster decision making. Design/methodology/approach It employed a decision support system that considers multiple decision makers and subjective attributes, while also addressing the impreciseness inherent in post-disaster decision making for ordering the establishment of TLHs. To do so, an optimization model was combined with a fuzzy multi-attribute group decision making approach. A numerical illustration was performed using data from the April 2015 Nepal Earthquake. Findings The results showed the location and order of establishment of TLHs, and demonstrated the impact of decision makers’ opinions on the overall ordering. Research limitations/implications The study does not discuss the uncertain nature of the location problem and the potential need for relocation of TLHs. Practical implications This methodology offers managerial insights for post-disaster decision making when resources are limited and their effective utilization is vital. The results highlight the importance of considering the opinions of multiple actors/decision makers to enable coordination and avoid complication between the growing numbers of humanitarian responders during disaster response. Originality/value This study introduces the concept of the order of establishment of TLHs and demonstrates its importance when resources are limited. It develops and implements a methodology determining the order of establishment of TLHs to support post-disaster decision making.

Decision rules, escalation of commitment and sensitivity to framing in group decision-making

2016 ◽  
Vol 54 (7) ◽  
pp. 1649-1668 ◽  
Author(s):  
Petru Lucian Curseu ◽  
Sandra G. L. Schruijer ◽  
Oana Catalina Fodor
Keyword(s):  
Decision Making ◽  
Decision Rule ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Rules ◽  
Escalation Of Commitment ◽  
Group Level ◽  
Content Type ◽  
The Impact ◽  
Collaborative Decision

Purpose – The purpose of this paper is to test the influence of collaborative and consultative decision rules on groups’ sensitivity to framing effect (FE) and escalation of commitment (EOC). Design/methodology/approach – In an experimental study (using a sample of 233 professionals with project management experience), the authors test the effects of collaborative and consultative decision rules on groups’ sensitivity to EOC and FE. The authors use four group decision-making tasks to evaluate decision consistency across gain/loss framed decision situations and six decision tasks to evaluate EOC for money as well as time as resources previously invested in the initial decisions. Findings – The results show that the collaborative decision rule increases sensitivity to EOC when financial resources are involved and decreases sensitivity to EOC when time is of essence. Moreover, the authors show that the collaborative decision rule decreases sensitivity to FE in group decision making. Research limitations/implications – The results have important implications for group rationality as an emergent group level competence by extending the insights concerning the impact of decision rules on emergent group level cognitive competencies. Due to the experimental nature of the design, the authors can probe the causal relations between the investigated variables, yet the authors cannot generalize the results to other settings. Practical implications – Managers can use the insights of this study in order to optimize the functioning of decision-making groups and to reduce their sensitivity to FEs and EOC. Originality/value – The study extends the research on group rationality and it is one of the few experimental attempts used to understand the role of decision rules on emergent group level rationality.

Visualization of preference aggregation based on Weber point in social network group decision-making problem

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhiqin Yang ◽  
Wuyong Qian ◽  
Jue Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Weighted Average ◽  
Decision Makers ◽  
Preference Aggregation ◽  
Group Preference ◽  
Content Type ◽  
Trust Propagation ◽  
Decision Making Problem

PurposeThis study aims to construct a Weber point-based model to complete the visualization of preference aggregation in group decision-making problem, in which decision-makers are associated with trust relationship.Design/methodology/approachThis study mainly comprises four parts: trust propagation, preference aggregation, opinion adjustment and alternative selection. Firstly, the incomplete trust between decision-makers is completed with trust transfer operators and propagation probability in trust propagation process. Secondly, a preference aggregation model based on Weber point is proposed to aggregate the group preference visually. Thirdly, opinions are adjusted to reach a consensus. Finally, the ranking of alternatives is determined by the correlation coefficient with the group preference as a reference.FindingsThe Weber point-based model proposed in this study can minimize the gap in the preference of alternatives between the group and all decision-makers, and realize the visualization of aggregation result. A case of plan selection is introduced to illustrate the feasibility and effectiveness of the proposed model.Originality/valueBy comparing the result with the weighted average-based preference aggregation method, the Weber point-based model proposed in this study can show the result of preference aggregation intuitively and improve group consensus.

Benchmarking knowledge management practices in small and medium enterprises

2017 ◽  
Vol 24 (5) ◽  
pp. 1215-1233 ◽  
Author(s):  
Santoso Wibowo ◽  
Srimannarayana Grandhi
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Small And Medium Enterprises ◽  
Evaluation Criteria ◽  
Evaluation Process ◽  
Decision Makers ◽  
Content Type ◽  
Multicriteria Group Decision Making ◽  
Medium Enterprises

Purpose The purpose of this paper is to formulate the process of measuring and benchmarking the performance of knowledge management (KM) practices as a multicriteria group decision-making problem and present a new multicriteria group decision-making approach for effectively evaluating the performance of KM practices to meet the interests of various stakeholders in small and medium enterprises (SMEs). Design/methodology/approach A new multicriteria group decision-making approach is developed for evaluating the performance of KM practices of individual SMEs. Intuitionistic fuzzy numbers are used for representing the subjective assessments of decision makers in evaluating the relative importance of the evaluation criteria and the performance of individual KM practices with respect to specific evaluation criteria. A fuzzy multicriteria group decision-making algorithm is developed for measuring and benchmarking the performance of alternative KM practices. Findings The proposed multicriteria group decision-making approach is capable of effectively evaluating the performance of KM practices through adequately considering the presence of multiple decision makers, the multi-dimensional nature of the evaluation problem, and appropriately modeling the subjectiveness and imprecision of the evaluation process. The presentation of an example shows that the proposed fuzzy multicriteria group decision-making algorithm is simple to use and efficient in computation. Research limitations/implications The outcome of the multicriteria group decision-making approach is highly dependent on the inputs provided by the decision maker. Practical implications The novelty from this research lies in the utilization of a multicriteria group decision-making approach for evaluating the performance of KM practices in an organization. The outcome from the performance evaluation process allows the enterprise to adopt appropriate KM practices for achieving competitive advantages. Social implications The proposed multicriteria group decision-making approach has a significant social implication as it can be used as a decision-making tool for providing various decision makers in SMEs with useful and strategic information concerning the performance of KM practices in a given situation. Originality/value The originality of this paper lies in the development of the multicriteria group decision-making approach for effectively measuring and benchmarking the performance of KM practices of individual SMEs.

An e-Delphi experiment of quality of equity predictions in online groups

2015 ◽  
Vol 7 (2) ◽  
pp. 136-158
Author(s):  
Tobias Endress
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Stock Price ◽  
Group Decision ◽  
Influence Factors ◽  
Research Process ◽  
Decision Making Process ◽  
Content Type ◽  
Stock Price Prediction ◽  
The Impact

Purpose – This paper aims to present the results of experiments with groups making online group stock price predictions and include the research process and a summary of the preliminary results. The overall objectives of the study are to assess the effect of individual and remote group decision-making approaches to stock price predictions, to assess whether a learning effect exists through the feedback loop of an e-Delphi process and to identify the underlying key mechanisms of the individual and of the group that influence the decision-making process. Design/methodology/approach – The experiments consist of a pilot and a main run. The main run was performed with three lay groups (totaling 49 participants) and two expert groups (totaling ten financial analysts and other stock market professionals). The groups were benchmarked with actual market prices as well as with each other, over ten e-Delphi cycles (ten weeks). Each participant in the experiment was asked to provide an estimation of the movement (up or down) for one-week, one-month and three-month future periods for each share, as well as to enter a stock price prediction for a three-month period. Findings – Although the pilot run has provided some indications that in certain situations and with careful group design, stock price predictions can be superior to the predictions of experts, the main experiment indicated a more differentiated picture and provided some information about the underlying decision-making process. Originality/value – The paper presents influence factors and measures the impact of the group decision-making process of Internet communities focusing on stock trading, based on predicting share prices.

CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection

2021 ◽  
pp. 1-11
Author(s):  
Huiyuan Zhang ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Comparison Method ◽  
Entropy Method ◽  
Decision Makers ◽  
Green Supplier Selection ◽  
Multiple Attribute ◽  
Psychological Perceptions

The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified.

The impact of family group decision-making on preventing removals

2017 ◽  
Vol 78 ◽  
pp. 89-92 ◽  
Author(s):  
Matthew C. Lambert ◽  
Leah E. Johnson ◽  
Eugene W. Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Family Group ◽  
The Impact

Method for Selecting Storage Enterprises Based on IFHA

2015 ◽  
Vol 713-715 ◽  
pp. 1769-1772
Author(s):  
Jie Wu ◽  
Lei Na Zheng ◽  
Tie Jun Pan
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Decision Problems ◽  
Decision Making Process ◽  
Final Decision ◽  
Multiple Decision Makers ◽  
Intuitionistic Fuzzy ◽  
Averaging Operator

In order to reflect the decision-making more scientific and democratic, modern decision problems often require the participation of multiple decision makers. In group decision making process,require the use of intuitionistic fuzzy hybrid averaging operator (IFHA) to get the final decision result.

scholarly journals Some q-Rung Dual Hesitant Fuzzy Heronian Mean Operators with Their Application to Multiple Attribute Group Decision-Making

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 472 ◽  
Author(s):  
Yuan Xu ◽  
Xiaopu Shang ◽  
Jun Wang ◽  
Wen Wu ◽  
Huiqun Huang
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Hesitant Fuzzy Sets ◽  
Multiple Attribute ◽  
A New Technique ◽  
Supplier Selection Problem ◽  
Heronian Mean

The q-rung orthopair fuzzy sets (q-ROFSs), originated by Yager, are good tools to describe fuzziness in human cognitive processes. The basic elements of q-ROFSs are q-rung orthopair fuzzy numbers (q-ROFNs), which are constructed by membership and nonmembership degrees. As realistic decision-making is very complicated, decision makers (DMs) may be hesitant among several values when determining membership and nonmembership degrees. By incorporating dual hesitant fuzzy sets (DHFSs) into q-ROFSs, we propose a new technique to deal with uncertainty, called q-rung dual hesitant fuzzy sets (q-RDHFSs). Subsequently, we propose a family of q-rung dual hesitant fuzzy Heronian mean operators for q-RDHFSs. Further, the newly developed aggregation operators are utilized in multiple attribute group decision-making (MAGDM). We used the proposed method to solve a most suitable supplier selection problem to demonstrate its effectiveness and usefulness. The merits and advantages of the proposed method are highlighted via comparison with existing MAGDM methods. The main contribution of this paper is that a new method for MAGDM is proposed.

scholarly journals Hybrid Multiattribute Group Decision Making Based on Intuitionistic Fuzzy Information and GRA Method

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Jian Guo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Ideal Solution ◽  
Decision Matrix ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Intuitionistic Fuzzy Entropy ◽  
Fuzzy Group Decision Making

Hybrid multiple attribute group decision making involves ranking and selecting competing courses of action available using attributes to evaluate the alternatives. The decision makers assessment information can be expressed in the form of real number, interval-valued number, linguistic variable, and the intuitionistic fuzzy number. All these evaluation information can be transformed to the form of intuitionistic fuzzy numbers. A combined GRA with intuitionistic fuzzy group decision-making approach is proposed. Firstly, the hybrid decision matrix is standardized and then transformed into an intuitionistic fuzzy decision matrix. Then, intuitionistic fuzzy averaging operator is utilized to aggregate opinions of decision makers. Intuitionistic fuzzy entropy is utilized to obtain the entropy weights of the criteria, respectively. After intuitionistic fuzzy positive ideal solution and intuitionistic fuzzy negative ideal solution are calculated, the grey relative relational degree of alternatives is obtained and alternatives are ranked. In the end, a numerical example illustrates the validity and applicability of the proposed method.

Multi-Attribute Group Decision Making Method for Preference Conflicting with Heterogeneous Information

2018 ◽  
Vol 7 (4) ◽  
pp. 1-14 ◽  
Author(s):  
Kai-Rong Liang
Keyword(s):  
Decision Making ◽  
Objective Function ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Heterogeneous Information ◽  
Multi Objective ◽  
Attribute Weights ◽  
Relative Closeness ◽  
Decision Making Model

The aim of this article is to propose a multi-objective decision-making method for researching and solving multi-attribute heterogeneous group decision-making problems. This is in the case that the characters of the decision information and decision makers' preferences are heterogeneous, and the weight information is incomplete. In this method, the multi-objective decision-making model, which considers the alternatives decision relative closeness and the preference of heterogeneous degree of decision makers in the objective function, is put forward. In addition, this article uses the minimax method to derive the multi-objective decision-making model and obtain the attribute weights and decision makers weights, and then the optimal scheme is established. Finally, an illustrative example shows the effectiveness of the proposed method.

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