scholarly journals Applying the Fuzzy Analytic Hierarchy Process to Construct the Product Innovative Service System of Wedding Photography Apparel

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Jui-Che Tu ◽  
Chi-Ling Hu
Keyword(s):  
Analytic Hierarchy Process ◽  
Fuzzy Analytic Hierarchy Process ◽  
Product System ◽  
Analytic Hierarchy ◽  
Information Platform ◽  
Product Service ◽  
Weight Analysis ◽  
Fuzzy Weight ◽  
Hierarchy Process ◽  
Apparel Product

This study aimed to investigate the indicators of the wedding photography apparel product system in order to construct the wedding photography apparel product system indicators and analyze the hieratical weights of the wedding photography apparel product system indicators. By using the Delphi method and the fuzzy analytic hierarchy process, this study constructed the questionnaire for wedding photography apparel product system indicator weights. This study used the mean and standard deviation to learn about the distribution of opinions of the experts and scholars. According to the findings of this study, for the fuzzy weight analysis results of the wedding photography apparel product system indicators, the most important indicators are the product-service indicators. Moreover, for the product-service indicators, the wedding apparel package service is the most important. For the information platform indicator, the wedding apparel style opinion platform is the most important. For the maintenance and recycling indicators, the wedding apparel second-hand auction/donation is the most important. For the sales market indicators, the wedding apparel store sales/rental is the most important. The main purpose of the indicators of the wedding photography apparel product system constructed in this study is to propose detailed items and connotations to provide a substantial reference and basis of business strategic indicators for the wedding photography enterprises.

On Moderate Fuzzy Analytic Hierarchy Process Pairwise Comparison Model With Subcriteria

2016 ◽  
Vol 2 (3) ◽  
pp. 54
Author(s):  
G. Marimuthu ◽  
G. Ramesh
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Fuzzy Ahp ◽  
Pairwise Comparison ◽  
Decision Models ◽  
Fuzzy Analytic Hierarchy Process ◽  
Analysis Method ◽  
Analytic Hierarchy ◽  
Comparison Model ◽  
Hierarchy Process

Decisions usually involve the getting the best solution, selecting the suitable experiments, most appropriate judgments, taking the quality results etc., using some techniques.  Every decision making can be considered as the choice from the set of alternatives based on a set of criteria.  The fuzzy analytic hierarchy process is a multi-criteria decision making and is dealing with decision making problems through pairwise comparisons mode [10].  The weight vectors from this comparison model are obtained by using extent analysis method.  This paper concern with an alternate method of finding the weight vectors from the original fuzzy AHP decision model (moderate fuzzy AHP model), that has the same rank as obtained in original fuzzy AHP and ideal fuzzy AHP decision models.

scholarly journals Research on Knowledge Management Models at Universities Using Fuzzy Analytic Hierarchy Process (FAHP)

2021 ◽  
Vol 13 (2) ◽  
pp. 809
Author(s):  
Ngoc Thach Pham ◽  
Anh Duc Do ◽  
Quang Vinh Nguyen ◽  
Van Loi Ta ◽  
Thi Thanh Binh Dao ◽  
...  
Keyword(s):  
Knowledge Management ◽  
Analytic Hierarchy Process ◽  
Fuzzy Analytic Hierarchy Process ◽  
Data Systems ◽  
Knowledge Use ◽  
Analytic Hierarchy ◽  
Priority Order ◽  
Big Data Systems ◽  
Document Review ◽  
Hierarchy Process

This study aims to investigate and evaluate factors related to the knowledge management model at universities in Hanoi, Vietnam. Based on the system literature review (SLR) approach, the study follows descriptive and inductive approach results of the document review process. Eight factors were synthesized with the fuzzy analytic hierarchy process (FAHP) to evaluate the priority order. Ten experts from seven universities participated in the survey. The results rank as follows: (1) knowledge sharing factor (this also has the highest best nonfuzzy performance (BNP) and average multiplier weight (GM)); (2) knowledge management with big data systems; (3) knowledge creation; (4) knowledge use; (5) knowledge gathering; (6) leadership; (7) knowledge rating; and (8) knowledge storage. Discussions, conclusions, limitations of the study, and suggestions for future studies are also mentioned in this study.

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