scholarly journals Business intelligence evaluation model in enterprise systems using fuzzy PROMETHEE

2016 ◽  
Vol 6 (3) ◽  
Author(s):  
Mansoureh Maadi ◽  
Mohammad Javidnia ◽  
Malihe Khatami
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Fuzzy Theory ◽  
Evaluation Model ◽  
Enterprise Systems ◽  
Practical Method ◽  
Multi Criteria Decision Making ◽  
Proposed Model ◽  
Fuzzy Promethee

In this paper, a new model to evaluate business intelligence (BI) for enterprisesystems is presented. Evaluation of BI before making decisions about buying and deploymentcan be an important decision support system for managers in organizations. In this paper, asimple and practical method is presented that evaluates BI for enterprise systems. In this way,after reviewing different papers in the literature, 34 criteria for BI specifications aredetermined, and then by applying fuzzy PROMETHEE, different enterprise systems areranked. To continue to assess the proposed model and as a case study, five enterprise systemswere selected and ranked using the proposed model. The advantages of PROMETHEE overother multi-criteria decision making methods and the use of fuzzy theory to deal withuncertainty in decision making is assessed and it is found that the proposed model can be auseful and applied method to help managers make decisions in organizations.

scholarly journals An Evaluation Model of Quantitative and Qualitative Fuzzy Multi-Criteria Decision-Making Approach for Location Selection of Transshipment Ports

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Ji-Feng Ding ◽  
Chien-Chang Chou
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Evaluation Model ◽  
Multi Criteria Decision Making ◽  
Location Selection ◽  
Container Logistics ◽  
Proposed Model ◽  
Fuzzy Mcdm ◽  
Selection Of

The role of container logistics centre as home bases for merchandise transportation has become increasingly important. The container carriers need to select a suitable centre location of transshipment port to meet the requirements of container shipping logistics. In the light of this, the main purpose of this paper is to develop a fuzzy multi-criteria decision-making (MCDM) model to evaluate the best selection of transshipment ports for container carriers. At first, some concepts and methods used to develop the proposed model are briefly introduced. The performance values of quantitative and qualitative subcriteria are discussed to evaluate the fuzzy ratings. Then, the ideal and anti-ideal concepts and the modified distance measure method are used in the proposed model. Finally, a step-by-step example is illustrated to study the computational process of the quantitative and qualitative fuzzy MCDM model. The proposed approach has successfully accomplished our goal. In addition, the proposed fuzzy MCDM model can be empirically employed to select the best location of transshipment port for container carriers in the future study.

scholarly journals A Novel Dynamic Multi-Criteria Decision Making Method Based on Generalized Dynamic Interval-Valued Neutrosophic Set

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 618 ◽  
Author(s):  
Nguyen Tho Thong ◽  
Florentin Smarandache ◽  
Nguyen Dinh Hoa ◽  
Le Hoang Son ◽  
Luong Thi Hong Lan ◽  
...  
Keyword(s):  
Decision Making ◽  
Evaluation Model ◽  
Real Life ◽  
Decision Makers ◽  
Neutrosophic Set ◽  
Multi Criteria Decision Making ◽  
Neutrosophic Sets ◽  
Proposed Model ◽  
Interval Valued ◽  
Knowledge Evaluation

Dynamic multi-criteria decision-making (DMCDM) models have many meaningful applications in real life in which solving indeterminacy of information in DMCDMs strengthens the potential application of DMCDM. This study introduces an extension of dynamic internal-valued neutrosophic sets namely generalized dynamic internal-valued neutrosophic sets. Based on this extension, we develop some operators and a TOPSIS method to deal with the change of both criteria, alternatives, and decision-makers by time. In addition, this study also applies the proposal model to a real application that facilitates ranking students according to attitude-skill-knowledge evaluation model. This application not only illustrates the correctness of the proposed model but also introduces its high potential appliance in the education domain.

Strategic Decision Making for Outsourcing Information Systems with a Fuzzy Multi-criteria Decision-Making Approach

2018 ◽  
Vol 6 (8) ◽  
pp. 6
Author(s):  
Mahmoud Modiri ◽  
Mohammad Dashti
Keyword(s):  
Decision Making ◽  
Analytic Network Process ◽  
Decision Makers ◽  
Strategic Decision ◽  
Multi Criteria Decision Making ◽  
Service Support ◽  
Proposed Model ◽  
Network Process ◽  
Selection Of

Today, IS supplier selection is one of the most critical steps in the outsourcing process; the success of outsourcing is highly dependent on the selection of IS suppliers. This paper proposes a new hybrid fuzzy multi-criteria decision-making (MCDM) model, which uses decision-making trial and evaluation laboratory (DEMATEL) technique, analytic network process (ANP), and Vlse Kriterijumska Optimizacija I Kompromisno Resenje(VIKOR) to evaluate four potential suppliers using seven factors and five decision makers using a realistic case study. the results showed that Service support is importance for outsourcing. The proposed model can help practitioners improve their decision making process.

scholarly journals Multi-Criteria Decision-Making Model Evaluating the Performance of Vietnamese Commercial Banks

2017 ◽  
Vol 9 (1) ◽  
pp. 132 ◽  
Author(s):  
Dinh Xuan Cuong ◽  
Hoang Thi Hien ◽  
Tran Long
Keyword(s):  
Decision Making ◽  
Analytical Hierarchy Process ◽  
Commercial Banks ◽  
Decision Model ◽  
Evaluation Model ◽  
Multi Criteria Decision Making ◽  
Proposed Model ◽  
Decision Making Model ◽  
Hierarchy Process ◽  
Research Show

The commercial banks (CBs) performance evaluating has been a necessary problem in currently integration trend and usually implemented by a committee of experts under criteria selected. Therefore, it is considered as a Multi - Criteria Decision - Making model (MCDM). Nowadays, there have been many researches proposing various standards and models to evaluate and rank CBs. But in Vietnam, the number of studies related to the Vietnamese banking evaluation model have still been limited. As a result, this study develops a multi-criteria decision model integrating Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy the Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). The proposed model has evaluated and ranked five Vietnamese commercial banks including CTG, VCB, BIDV, TCB and MB. The paper revealed their ranks. Besides, the results of the research show that the Analytical Hierarchy Process (AHP) model is suitable for applying it to the process evaluating bank performance.

Identification of User Preference for Multi-Criteria Reporting in Business Intelligence

2018 ◽  
pp. 16-47
Author(s):  
Martin Aruldoss ◽  
Miranda Lakshmi Travis ◽  
Prasanna Venkatesan Venkatasamy
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
User Preference ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Order Preference ◽  
Banking Business ◽  
Different Levels ◽  
Support Decision Making

Business intelligence (BI) is an integrated set of tools used to support the transformation of data into information in order to support decision making. Among different functionalities, reporting plays a significant role that provides information to its readers to make better decisions. BI lacks user-specific reporting to the different levels of users of an organization. Different users require different kinds of reporting with respect to different requirement (criteria) in an organization. A multi-criteria reporting (MCR) finds the suitable information to suitable user based on the multiple conflicting preferences of a user. Technique for order preference by similarity to ideal solution (TOPSIS) is the most popularly applied multi-criteria decision-making (MCDM) technique selected to identify different levels of user preference for MCR. Banking business is considered as a case study to identify user preference for MCR. This research also designs evaluation metrics for TOPSIS.

scholarly journals LOGISTICS FREIGHT CENTER LOCATIONS DECISION BY USING FUZZY-PROMETHEE

Transport ◽  
2014 ◽  
Vol 29 (4) ◽  
pp. 412-418 ◽  
Author(s):  
Birol Elevli
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Preference Ranking ◽  
Multi Criteria Decision Making ◽  
Uncertain Information ◽  
Logistics Center ◽  
Promethee Method ◽  
Fuzzy Promethee ◽  
Fuzzy Preference

Fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (F-PROMETHEE) was applied for choosing among potential logistics center locations. The method combines the concept of fuzzy sets to represent uncertain information with the PROMETHEE, a subgroup of Multi-Criteria Decision-Making (MCDM) methods. Criteria are identified based on review of scientific and trade literature and inputs received from experts. The suitability of areas have been evaluated on the basis of these criteria. There are substantial uncertainties and subjectivity about site information. Therefore F-PROMETHEE method is preferred. The case study shows that this application provides reasonable results.

Multi-Criteria Decision Making for Vulnerability Mapping of Flood Hazard: A Case Study of Pune City

2019 ◽  
Vol 2 (1) ◽  
pp. 41-52
Author(s):  
Nitin Mundhe
Keyword(s):  
Decision Making ◽  
Flood Hazard ◽  
Geographical Information ◽  
Multi Criteria Decision Making ◽  
Flood Hazards ◽  
Very High Frequency ◽  
Flood Vulnerability ◽  
Natural Risk ◽  
The Town

Floods are natural risk with a very high frequency, which causes to environmental, social, economic and human losses. The floods in the town happen mainly due to human made activities about the blockage of natural drainage, haphazard construction of roads, building, and high rainfall intensity. Detailed maps showing flood vulnerability areas are helpful in management of flood hazards. Therefore, present research focused on identifying flood vulnerability zones in the Pune City using multi-criteria decision-making approach in Geographical Information System (GIS) and inputs from remotely sensed imageries. Other input data considered for preparing base maps are census details, City maps, and fieldworks. The Pune City classified in to four flood vulnerability classes essential for flood risk management. About 5 per cent area shows high vulnerability for floods in localities namely Wakdewadi, some part of the Shivajinagar, Sangamwadi, Aundh, and Baner with high risk.

scholarly journals Coupling Fuzzy Multi-Criteria Decision-Making and Clustering Algorithm for MSW Landfill Site Selection (Case Study: Lanzhou, China)

2021 ◽  
Vol 10 (6) ◽  
pp. 403
Author(s):  
Jiamin Liu ◽  
Yueshi Li ◽  
Bin Xiao ◽  
Jizong Jiao
Keyword(s):  
Decision Making ◽  
Clustering Algorithm ◽  
Fuzzy Membership Function ◽  
Multi Criteria Decision Making ◽  
Landfill Site Selection ◽  
Spatial Distribution Characteristics ◽  
Criteria Weights ◽  
Spatial Decision Making ◽  
Complex Decision

The siting of Municipal Solid Waste (MSW) landfills is a complex decision process. Existing siting methods utilize expert scores to determine criteria weights, however, they ignore the uncertainty of data and criterion weights and the efficacy of results. In this study, a coupled fuzzy Multi-Criteria Decision-Making (MCDM) approach was employed to site landfills in Lanzhou, a semi-arid valley basin city in China, to enhance the spatial decision-making process. Primarily, 21 criteria were identified in five groups through the Delphi method at 30 m resolution, then criteria weights were obtained by DEMATEL and ANP, and the optimal fuzzy membership function was determined for each evaluation criterion. Combined with GIS spatial analysis and the clustering algorithm, candidate sites that satisfied the landfill conditions were identified, and the spatial distribution characteristics were analyzed. These sites were subsequently ranked utilizing the MOORA, WASPAS, COPRAS, and TOPSIS methods to verify the reliability of the results by conducting sensitivity analysis. This study is different from the previous research that applied the MCDM approach in that fuzzy MCDM for weighting criteria is more reliable compared to the other common methods.

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