On priority weights and consistency for incomplete hesitant fuzzy preference relations

2018 ◽  
Vol 143 ◽  
pp. 115-126 ◽  
Author(s):  
Zhen Zhang ◽  
Xinyue Kou ◽  
Wenyu Yu ◽  
Chonghui Guo
Keyword(s):  
Preference Relations ◽  
Priority Weights ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

scholarly journals Consensus-Based Multi-Person Decision Making with Incomplete Fuzzy Preference Relations Using Product Transitivity

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 185 ◽  
Author(s):  
Atiq-ur Rehman ◽  
Mustanser Hussain ◽  
Adeel Farooq ◽  
Muhammad Akram
Keyword(s):  
Decision Making ◽  
Preference Relation ◽  
Selection Procedure ◽  
Feedback Mechanism ◽  
Decision Makers ◽  
Consensus Process ◽  
Preference Relations ◽  
Priority Weights ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

In this paper, a consensus-based method for multi-person decision making (MPDM) using product transitivity with incomplete fuzzy preference relations (IFPRs) is proposed. Additionally, an average aggregation operator has been used at the first level to estimate the missing preference values and construct the complete fuzzy preference relation (FPR). Then it is confirmed to be product consistent by using the transitive closure formula. Following this, weights of decision makers (DMs) are evaluated by merging consistency weights and predefined priority weights (if any). The consistency weights for the DMs are estimated through product consistency investigation of the information provided by each DM. The consensus process determines whether the selection procedure should be initiated or not. The hybrid comprises of a quitting process and feedback mechanism, and is used to enhance the consensus level amongst DMs in case of an inadequate state. The quitting process arises when some DMs decided to leave the course, and is common in MPDM while dealing with a large number of alternatives. The feedback mechanism is the main novelty of the proposed technique which helps the DMs to improve their given preferences based on this consistency. At the end, a numerical example is deliberated to measure the efficiency and applicability of the proposed method after the comparison with some existing models under the same assumptions. The results show that proposed method can offer useful comprehension into the MPDM process.

Using Fuzzy Preference Relations to Predict the Success Possibility of Assistive Input Devices for Disabled Implementation

2013 ◽  
Vol 647 ◽  
pp. 905-911 ◽  
Author(s):  
Ching Tien Shih ◽  
Shu Chen Hsu ◽  
Ching Hsiang Shih
Keyword(s):  
Influential Factors ◽  
Decision Makers ◽  
Factors Affecting ◽  
Input Devices ◽  
Preference Relations ◽  
Priority Weights ◽  
Fuzzy Preference Relations ◽  
Remedial Actions ◽  
Fuzzy Preference

This study proposes an analytic hierarchical prediction model based on consistent fuzzy preference relations to help the organizations become aware of the essential factors affecting the implementation Assistive Input Devices (AID). Pairwise comparisons are used to determine the priority weights of influential factors and the ratings of success or failure outcomes amongst decision makers. The subjectivity and vagueness in the prediction procedures are dealt with using linguistic terms quantified in an interval scale [0, 1]. Then predicted success/failure values are obtained to enable organizations to decide whether to initiate knowledge management, inhibit adoption or take remedial actions to increase the possibility of successful AID for disabled. This proposed approach is demonstrated with a real case study involving seven influential factors assessed by eleven evaluators solicited from a special school located in Taiwan.

scholarly journals Priority Weights for Predicting the Success of Hotel Sustainable Business Models

2021 ◽  
Vol 13 (24) ◽  
pp. 14032
Author(s):  
Tien-Chin Wang ◽  
Chin-Ying Huang ◽  
Shu-Li Huang ◽  
Jen-Yao Lee
Keyword(s):  
Business Models ◽  
Hotel Industry ◽  
Sustainable Business ◽  
Important Indicator ◽  
Predictive Values ◽  
Preference Relations ◽  
Priority Weights ◽  
Fuzzy Preference Relations ◽  
Sustainable Business Models ◽  
Fuzzy Preference

This study proposes the use of consistent fuzzy preference relations to evaluate the structure of hotel sustainable business model (HSBM) dimensions and the corresponding hierarchy of evaluation indicators, and predict the overall probability of success. As fuzzy preference relations require, a group of hotel professionals in Taiwan was asked to process pairwise comparisons using linguistic variables to determine the weights of dimensions and indicators. According to the results, finances were found to be the most important dimension, followed by human capital. The number of local cultural events in the hotel was identified as the most important indicator. The predictive values revealed the possibility for successful HSBM implementation, shedding light on the vision of sustainability for the hotel industry. The results of the present study contribute to the literature on sustainability by determining the importance and weights of dimensions and indicators for hotel business models, providing an example of the use of this strategic tool in generating and modifying sustainable business models for the hotel industry.

Using Fuzzy Preference Relations to Predict the Success Possibility of Implementing the Oceanographic & Meteorologic Integration Orchestrator

2011 ◽  
Vol 52-54 ◽  
pp. 1812-1817
Author(s):  
Wen Ting Chen ◽  
Ching Tien Shih ◽  
J.C. Tsai
Keyword(s):  
Influential Factors ◽  
Decision Makers ◽  
Linguistic Terms ◽  
Factors Affecting ◽  
Preference Relations ◽  
Priority Weights ◽  
Fuzzy Preference Relations ◽  
Remedial Actions ◽  
Fuzzy Preference

This study proposes an analytic hierarchical prediction model based on consistent fuzzy preference relations to help the organizations become aware of the essential factors affecting the implementation oceanographic & meteorologic Integration Orchestrator. Pairwise comparisons are used to determine the priority weights of influential factors and the ratings of success or failure outcomes amongst decision makers. The subjectivity and vagueness in the prediction procedures are dealt with using linguistic terms quantified in an interval scale [0,1]. Then predicted success/failure values are obtained to enable organizations to decide whether to initiate knowledge management, inhibit adoption or take remedial actions to increase the possibility of successful oceanographic & meteorologic initiatives. This proposed approach is demonstrated with a real case study involving seven influential factors assessed by eleven evaluators solicited from a semiconductor engineering incorporation located in Taiwan.

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