An Integrated Approach of Fuzzy-AHP-TOPSIS for E-commerce Evaluation

2021 ◽  
Vol 20 (2) ◽  
pp. 82-95
Author(s):  
Tran Thi Tham ◽  
Hong-Phuc Nguyen
Keyword(s):  
Fuzzy Ahp ◽  
Integrated Approach

An integrated supplier selection approach incorporating decision maker’s risk attitude using ANN, AHP and TOPSIS methods

Kybernetes ◽  
2019 ◽  
Vol 49 (9) ◽  
pp. 2263-2284 ◽  
Author(s):  
Chunxia Yu ◽  
Zhiqin Zou ◽  
Yifan Shao ◽  
Fengli Zhang
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Ahp ◽  
Evaluation Criteria ◽  
Risk Attitude ◽  
Integrated Approach ◽  
Fuzzy Topsis ◽  
Ann Model ◽  
Content Type ◽  
Selection Approach

Purpose The purpose of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the artificial neural network (ANN), analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods. Design/methodology/approach In the proposed approach, the ANN model is used to classify decision maker’s risk attitude; the fuzzy AHP method is used to determine the relative weights of evaluation criteria; and the fuzzy TOPSIS method is used to evaluate ratings of suppliers. Finally, experiments are conducted to verify the feasibility and efficiency of the proposed integrated approach. Findings Experiments results show that the proposed integrated approach is effective and efficient to help decision makers to select suitable suppliers according to their risk attitudes. Originality/value The aim of this paper is to develop a novel integrated supplier selection approach incorporating decision maker’s risk attitude using the ANN, AHP and TOPSIS methods. The decision maker’s risk attitude toward procurement transaction is originally considered in supplier selection process.

A fuzzy AHP and TOPSIS methodology to evaluate 3PL in a supply chain

2012 ◽  
Vol 7 (3) ◽  
pp. 287-303 ◽  
Author(s):  
Pravin Kumar ◽  
Rajesh K. Singh
Keyword(s):  
Supply Chain ◽  
Service Providers ◽  
Fuzzy Ahp ◽  
Integrated Approach ◽  
Third Party ◽  
Preference Ranking ◽  
Relative Importance ◽  
Content Type ◽  
Logistics Service Providers ◽  
Hierarchy Process

PurposeThe purpose of this paper is to provide an insight into the use of an integrated approach of fuzzy analytical hierarchy process (fuzzy AHP) and TOPSIS in evaluating the performance of global third party logistics service providers for effective supply chain management.Design/methodology/approachIn this study, the integration of fuzzy AHP with TOPSIS is proposed in determining the relative importance (weight) of criteria and then ranking of 3PLs.FindingsFindings show that the logistics cost and service quality are two most important criteria for performance rating of 3PLs. Deciding the relative importance of various criteria for 3PLs evaluation is a complex task. The superiority of one criterion over the other varies from person to person and firm to firm. Therefore, to capture the variability in decision fuzzy extended AHP is very useful tool. Finally, the preference raking of alternatives are found using TOPSIS.Research limitations/implicationsFuzzy AHP is a complex methodology and requires more numerical calculations than the traditional AHP and hence it increases the effort. But in this paper single stage fuzzy AHP is used to simplify the process. Fuzzy AHP is integrated with TOPSIS for preference ranking of 3PL, which provides a good methodology to rank 3PLs.Originality/valueThere is a lack of research in the literature to deal directly with the uncertainty of human decisions in evaluating the relative importance of multiple criteria. Therefore, fuzzy AHP is an appropriate methodology to find the relative importance of the criteria to rank the 3PLs using TOPSIS.

An integrated fuzzy-AHP and TOPSIS approach for maintenance policy selection

2019 ◽  
Vol 37 (9/10) ◽  
pp. 1275-1299 ◽  
Author(s):  
Narges Hemmati ◽  
Masoud Rahiminezhad Galankashi ◽  
D.M. Imani ◽  
Farimah Mokhatab Rafiei
Keyword(s):  
Heat Exchanger ◽  
Fuzzy Ahp ◽  
Integrated Approach ◽  
Added Value ◽  
Risk Level ◽  
Maintenance Policy ◽  
Content Type ◽  
Policy Selection ◽  
Different Types ◽  
Molten Sulfur

Purpose The purpose of this paper is to select the best maintenance policy for different types of equipment of a manufacturer integrating the fuzzy analytic hierarchy process (FAHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) models. Design/methodology/approach The decision hierarchy of this research includes three levels. The first level aims to choose the best maintenance policy for different types of equipment of an acid manufacturer. These equipment pieces include molten sulfur ponds, boiler, absorption tower, cooling towers, converter, heat exchanger and sulfur fuel furnace. The second level includes decision criteria of added-value, risk level and the cost. Lastly, the third level comprises time-based maintenance (TBM), corrective maintenance (CM), shutdown maintenance and condition-based maintenance (CBM) as four maintenance policies. Findings The best maintenance policy for different types of equipment of a manufacturer is the main finding of this research. Based on the obtained results, CBM policy is suggested for absorption tower, boiler, cooling tower and molten sulfur ponds, TBM policy is suggested for converters and heat exchanger and CM policy is suggested for a sulfur fuel furnace. Originality/value This research develops a novel model by integrating FAHP and an interval TOPSIS with concurrent consideration of added-value, risk level and cost to select the best maintenance policy. According to the highlights of the previous studies conducted on maintenance policy selection and related tools and techniques, an operative integrated approach to combine risk, added-value and cost with integrated fuzzy models is not developed yet. The majority of the previous studies have considered classic fuzzy approaches such as FAHP, FANP, Fuzzy TOPSIS, etc., which are not completely capable to reflect the decision makers’ viewpoints.

Evaluating and ranking hotels offering e-service by integrated approach of Webqual and fuzzy AHP

2014 ◽  
Vol 15 (1) ◽  
pp. 84 ◽  
Author(s):  
Arash Shahin ◽  
Javad Khazaei Pool ◽  
Mehdi Poormostafa
Keyword(s):  
Fuzzy Ahp ◽  
Integrated Approach

scholarly journals Comparative analysis of airline financial and operational performances: A fuzzy AHP and TOPSIS integrated approach

2021 ◽  
Vol 10 (3) ◽  
pp. 361-374
Author(s):  
Ki-Hwan Gabriel Bae ◽  
Aman Gupta ◽  
Ronald Mau
Keyword(s):  
Hybrid Method ◽  
Airline Industry ◽  
Evaluation System ◽  
Performance Metrics ◽  
Fuzzy Ahp ◽  
Multiple Criteria Decision Making ◽  
Integrated Approach ◽  
Performance Criteria ◽  
Modeling Framework ◽  
Airline Performance

Already faced with tight competition and low profit margins, the airline industry is going through major changes in the wake of the current pandemic resulting in travel restrictions and slump demands, prompting airlines to curtail services and investments in every aspect of business. To that end, developing a comprehensive method of improving airline performance measures is crucial. However, this type of problem is complex to solve due to a large number of factors, requiring a systematic approach. It entails taking into account a multitude of conflicting, or sometimes interrelated criteria, hence becoming an inherently multiple criteria decision making problem. This study is aimed to assess the competitiveness of airlines and evaluate their financial and operational performances in relation to such criteria. We test FAHP, TOPSIS, and a hybrid method of combining FAHP and TOPSIS methods. In particular, regarding the hybrid method, FAHP is employed to determine the influential weights of criteria that are utilized in TOPSIS for preference values among alternatives. We demonstrate the applicability of the proposed methods to solving a MCDM problem of airline performance assessments using real data sets. Further, this study focuses on examining the relationship between financial and operational performance criteria, as well as gleaning insights for airlines to build an evaluation system that would aid in understanding their strength and weakness in the performance metrics. The computational experiment results of our hybrid FAHP-TOPSIS model support the efficacy of incorporating fuzzy values concerning influential weight criteria. By judiciously distributing criteria weights that are specific to the airline industry, our proposed model captures preference scores reflective of industry-related and concurrent measures. This modeling framework can help airlines better evaluate the systematic influential relation structure among criteria in critical financial and operational dimensions.

The role of 3S in big data quality: a perspective on operational performance indicators using an integrated approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pratima Verma ◽  
Vimal Kumar ◽  
Ankesh Mittal ◽  
Bhawana Rathore ◽  
Ajay Jha ◽  
...  
Keyword(s):  
Big Data ◽  
Data Quality ◽  
Data Science ◽  
Fuzzy Ahp ◽  
Integrated Approach ◽  
Preference Ranking ◽  
Content Type ◽  
Quality Dimensions ◽  
Data Quality Dimensions

PurposeThis study aims to provide insight into the operational factors of big data. The operational indicators/factors are categorized into three functional parts, namely synthesis, speed and significance. Based on these factors, the organization enhances its big data analytics (BDA) performance followed by the selection of data quality dimensions to any organization's success.Design/methodology/approachA fuzzy analytic hierarchy process (AHP) based research methodology has been proposed and utilized to assign the criterion weights and to prioritize the identified speed, synthesis and significance (3S) indicators. Further, the PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations) technique has been used to measure the data quality dimensions considering 3S as criteria.FindingsThe effective indicators are identified from the past literature and the model confirmed with industry experts to measure these indicators. The results of this fuzzy AHP model show that the synthesis is recognized as the top positioned and most significant indicator followed by speed and significance are developed as the next level. These operational indicators contribute toward BDA and explore with their sub-categories' priority.Research limitations/implicationsThe outcomes of this study will facilitate the businesses that are contemplating this technology as a breakthrough, but it is both a challenge and opportunity for developers and experts. Big data has many risks and challenges related to economic, social, operational and political performance. The understanding of data quality dimensions provides insightful guidance to forecast accurate demand, solve a complex problem and make collaboration in supply chain management performance.Originality/valueBig data is one of the most popular technology concepts in the market today. People live in a world where every facet of life increasingly depends on big data and data science. This study creates awareness about the role of 3S encountered during big data quality by prioritizing using fuzzy AHP and PROMETHEE.

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