scholarly journals Contribution of fishery and aquaculture products to Turkish foreign trade: An evaluation by a hybrid multi-criteria decision-making method

2021 ◽  
Vol 38 (3) ◽  
pp. 275-282
Author(s):  
Bilgen Akmermer ◽  
Pelin Çelik
Keyword(s):  
Decision Making ◽  
Foreign Trade ◽  
Sea Bass ◽  
Sea Bream ◽  
Multi Criteria Decision Making ◽  
High Return ◽  
Aquaculture Industry ◽  
Criteria Weights ◽  
Aquaculture Products ◽  
Market Strategies

Fisheries and aquaculture industry, which provides a continuous and high-return market advantage to potential countries, is also one of the priority industries for Turkey. Although Turkey has important advantages with its geographic position and bio-diversity, the industry's contribution to foreign trade is not at an acceptable level. Accordingly, it is important to evaluate the capture fishery and aquaculture products, which provide the best contribution to the foreign trade of Turkey. Thus, the present paper aims to provide foreign trade executives with an intuition about the most appropriate products to invest in and contributing products to Turkish foreign trade within the scope of market strategies. Entropy-WASPAS, which is a hybrid multi-criteria decision-making method, is used for evaluating the contribution of fishery and aquaculture products to Turkish foreign trade. This model includes both criteria (production, import quantity, import value, export quantity, export value) and alternatives (trout, sea bream, sea bass, sprat, atlantic bonito, anchovy, horse mackerel, pilchard, sea snail, prawn, cuttle fish, mussel). Entropy is used to determine the criteria weights, and WASPAS is applied for ranking the fishery and aquaculture products. According to the results, export value is the most important criteria while Sea Bream is found as the most significant product for Turkey’s foreign trade.

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.

scholarly journals Establishing a Sustainable Sports Tourism Evaluation Framework with a Hybrid Multi-Criteria Decision-Making Model to Explore Potential Sports Tourism Attractions in Taiwan

2020 ◽  
Vol 12 (4) ◽  
pp. 1673 ◽  
Author(s):  
Jen-Jen Yang ◽  
Huai-Wei Lo ◽  
Chen-Shen Chao ◽  
Chih-Chien Shen ◽  
Chin-Cheng Yang
Keyword(s):  
Decision Making ◽  
Evaluation Framework ◽  
Government Support ◽  
Multi Criteria Decision Making ◽  
Practical Applications ◽  
Proposed Model ◽  
Sports Tourism ◽  
Criteria Weights ◽  
Tourism Attractions ◽  
Multiple Experts

In recent years, the awareness of sustainable tourism has risen around the world. Many tourism industries combine sports to attract more customers to facilitate the development of the economy and the promotion of local culture. However, it is an important task to establish a comprehensive tourism evaluation framework for sustainable sports tourism. This study proposes a Multi-Criteria Decision-Making (MCDM) model to discuss the above issues, using the Bayesian Best Worst Method (Bayesian BWM) to integrate multiple experts’ judgments to generate the group optimal criteria weights. Next, the modified Visekriterijumska Optimizacija i Kompromisno Resenje (VIKOR) technique is combined with the concept of aspiration level to determine the performance of sports attractions and their priority ranks. In addition, this study adds a perspective of institutional sustainability to emphasize the importance of government support and local marketing. The effectiveness and robustness of the proposed model is demonstrated through potential sports tourism attractions in Taiwan. A sensitivity analysis and models comparison were also performed in this study. The results show that the proposed model is feasible for practical applications and that it effectively provides some management implications to support decision-makers in formulating improvement strategies.

scholarly journals Multi-criteria decision-making for flood risk management: a survey of the current state of the art

2016 ◽  
Vol 16 (4) ◽  
pp. 1019-1033 ◽  
Author(s):  
Mariana Madruga de Brito ◽  
Mariele Evers
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Flood Risk ◽  
Flood Risk Management ◽  
Decision Making Process ◽  
Multi Criteria Decision Making ◽  
Wide Range ◽  
Order Preference ◽  
Criteria Weights ◽  
Simple Additive Weighting

Abstract. This paper provides a review of multi-criteria decision-making  (MCDM) applications to flood risk management, seeking to highlight trends and identify research gaps. A total of 128 peer-reviewed papers published from 1995 to June 2015 were systematically analysed. Results showed that the number of flood MCDM publications has exponentially grown during this period, with over 82 % of all papers published since 2009. A wide range of applications were identified, with most papers focusing on ranking alternatives for flood mitigation, followed by risk, hazard, and vulnerability assessment. The analytical hierarchy process (AHP) was the most popular method, followed by Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and Simple Additive Weighting (SAW). Although there is greater interest in MCDM, uncertainty analysis remains an issue and was seldom applied in flood-related studies. In addition, participation of multiple stakeholders has been generally fragmented, focusing on particular stages of the decision-making process, especially on the definition of criteria weights. Therefore, addressing the uncertainties around stakeholders' judgments and endorsing an active participation in all steps of the decision-making process should be explored in future applications. This could help to increase the quality of decisions and the implementation of chosen measures.

scholarly journals Resolving a location selection problem by means of an integrated AHP-RAFSI approach

2021 ◽  
Vol 2 (1) ◽  
pp. 135-142
Author(s):  
Abdulaziz Alossta ◽  
◽  
Omar Elmansouri ◽  
Ibrahim Badi ◽  
◽  
...  
Keyword(s):  
Decision Making ◽  
Service Providers ◽  
Multi Criteria Decision Making ◽  
User Characteristics ◽  
Efficient Manner ◽  
Location Selection ◽  
Location Allocation ◽  
Criteria Weights ◽  
Cost Efficient ◽  
Site Network

The optimal Site selection operation is one of the most important challenges facing planners. Many location-allocation models have been developed based on multi-criteria decision making process. Recent methods take into account site, network, and user characteristics to determine the appropriate location. The development of optimum system has been a growing focus for most authorities across the world. It is generally thought that utlities allocation is the ultimate goal for service providers, which has been attributed to giving assistance in a time- and cost-efficient manner. In this paper, a multi-criteria decision making approach was implemented in two steps. Analytical hierarchy process (AHP) was adopted in the first step to determine the criteria weights. Results of AHP showed that response time had the highest weight among other criteria. Ranking of different alternatives was conducted in the second step using RAFSI model to choose the optimal location. Model ranking clearly indicated road-network as the best alternative to locate EMS centers.

scholarly journals GIS-SUPPORTED MAPPING OF SUITABLE PARKING AREAS USING AHP METHOD: THE CASE OF KONYA

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 51-56
Author(s):  
T. Alkan ◽  
S. S. Durduran
Keyword(s):  
Decision Making ◽  
Information System ◽  
Analytical Hierarchy Process ◽  
Site Selection ◽  
Multi Criteria Decision Making ◽  
Situation Analysis ◽  
Ahp Method ◽  
Criteria Weights ◽  
Suitable Site ◽  
Hierarchy Process

Abstract. The increase in the number of vehicles with the increasing population has caused the problem of parking insufficiency. This problem necessitate situation analysis of existing parking areas and site selection analyses for new parking areas. It is possible to make suitable site selections with spatial analysis supported by Geographic Information System (GIS). In this study, available parking areas in Selçuklu district of Konya province were evaluated and suitable parking areas were determined in line with the needs. The criteria affecting the parking areas site selection were determined and the importance levels of the criteria were detected by using the Analytical Hierarchy Process (AHP) which is one of the Multi-Criteria Decision Making (MCDM) methods. Density analyses were carried out with GIS and suitable parking areas map was produced considering the criteria weights obtained.

scholarly journals Review Article: Multi-criteria decision making for flood risk management: a survey of the current state-of-the-art

2015 ◽  
Vol 3 (11) ◽  
pp. 6689-6726 ◽  
Author(s):  
M. M. de Brito ◽  
M. Evers
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Flood Risk ◽  
Flood Control ◽  
Flood Risk Management ◽  
Multi Criteria Decision Making ◽  
Coping Capacity ◽  
Order Preference ◽  
Criteria Weights ◽  
Simple Additive Weighting

Abstract. This paper provides a review of Multi-Criteria Decision Making (MCDM) applications to flood risk management, seeking to highlight trends and identify research gaps. Totally, 128 peer-reviewed papers published from 1995 to June 2015 were systematically analysed and classified into the following application areas: (1) ranking of alternatives for flood mitigation, (2) reservoir flood control, (3) susceptibility, (4) hazard, (5) vulnerability, (6) risk, (7) coping capacity, and (8) emergency management. Additionally, the articles were categorized based on the publication year, MCDM method, whether they were or were not carried out in a participatory process, and if uncertainty and sensitivity analysis were performed. Results showed that the number of flood MCDM publications has exponentially grown during this period, with over 82 % of all papers published since 2009. The Analytical Hierarchy Process (AHP) was the most popular technique, followed by Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and Simple Additive Weighting (SAW). Although there is greater interest on MCDM, uncertainty analysis remains an issue and is seldom applied in flood-related studies. In addition, participation of multiple stakeholders has been generally fragmented, focusing on particular stages of the decision-making process, especially on the definition of criteria weights. Based on the survey, some suggestions for further investigation are provided.

Granularity Approach for Multi-Criteria Decision Making About Hybrid Evaluation Information

2018 ◽  
Vol 32 (11) ◽  
pp. 1859020 ◽  
Author(s):  
Shihu Liu ◽  
Fusheng Yu ◽  
Patrick S. P. Wang
Keyword(s):  
Decision Making ◽  
Convex Combination ◽  
Data Representation ◽  
Multi Criteria Decision Making ◽  
Ideal Solutions ◽  
Criteria Weights ◽  
Totally Ordered Set ◽  
Knowledge Granularity ◽  
Interval Valued ◽  
Evaluation Information

In this study, a new version of TOPSIS method is reconstructed to deal with the problem of multi-criteria decision making. Here, the data representation of all alternatives is varied according to different criteria, such as real number, interval-valued number, set-valued number and intuitionistic fuzzy-valued number, etc. Because the distinguishing ability of each criterion can be reflected by its knowledge granularity, naturally, a knowledge granularity method is constructed to measure the criteria weights. Besides, the approach of how to select the ideal solution is redefined, especially for the case that the content of criterion according to all alternatives is not a totally ordered set anymore. What is more, the decision maker’s personal preference is considered, and the concrete indicator value can be calculated by the convex combination of the distance from possible alternatives to ideal solutions. Finally, the validity of the proposed decision-making algorithm is illustrated by a synthetic example.

scholarly journals Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA – Fuzzy MABAC model

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246857
Author(s):  
Miroslav Nedeljković ◽  
Adis Puška ◽  
Suzana Doljanica ◽  
Saša Virijević Jovanović ◽  
Pavle Brzaković ◽  
...  
Keyword(s):  
Decision Making ◽  
Comparison Method ◽  
Assessment Method ◽  
Multi Criteria Decision Making ◽  
Vegetable Crops ◽  
Criteria Weights ◽  
Fuzzy Mcdm ◽  
Criteria Importance ◽  
Novi Sad ◽  
Importance Assessment

Decision making is constantly present in agriculture. Choosing the wrong variety carries the risk that the investment in terms of sowing does not pay off at all. Therefore, it is necessary to choose the variety that gives the best results. In order to achieve this, it is necessary to apply multi-criteria decision-making of available varieties, which is, in this paper, done on the example of hybrid varieties of rapeseed that were created by selection at the Institute of Field and Vegetable Crops in Novi Sad. By applying fuzzy logic, a novel integrated Multi-Criteria Decision-Making (MCDM) model is developed and rapeseed varieties were evaluated. For determining four main and 20 subcriteria, fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method has been applied based on fuzzy Bonferroni operator, while for ranking alternatives fuzzy MABAC (Multi-Attributive Border Approximation area Comparison) method has been used. The results obtained using the novel integrated fuzzy MCDM model showed that the variety A2 – Zorica has the best results, followed by A1 - NS Ras, while the worst results were seen by the variety A5 - Zlatna. These results were confirmed using other five fuzzy MCDM methods. Sensitivity analysis—changing criteria weights showed the worst results in the variety A6 - Jovana, which took last place in the application of 18 scenarios. The presented model and the results of this research will help farmers to solve this decision problem.

scholarly journals INNOVATION IN EASTERN EUROPE & CENTRAL ASIA: A MULTI-CRITERIA DECISION-MAKING APPROACH

2019 ◽  
Vol 7 (3) ◽  
pp. 98-121
Author(s):  
Özgür KABADURMUŞ ◽  
Fatma Nur Karaman KABADURMUŞ
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Eastern European ◽  
Competitive Advantages ◽  
Firm Level ◽  
Data Set ◽  
Process Innovations ◽  
Central Asian ◽  
Level Data ◽  
Criteria Weights

In today’s intense competition environment, innovation levels of countries determine their competitive advantages. This study compares the innovation levels of Eastern European and Central Asian (EECA) countries using multi-criteria decision-making methods. The firm-level data set of the World Bank on innovation (BEEPS data) is used to evaluate innovation levels and capabilities of the countries in the region. In our proposed TOPSIS based methodology, countries are compared in terms of four different innovation types (New Product, New Organization, New Marketing, and New Process Innovations). Also, we provide an extensive sensitivity analysis to show the changes in the innovation rankings of the countries wıth different criteria weights.

Simulation-Based Evaluation of Criteria Rank-Weighting Methods in Multi-Criteria Decision-Making

2016 ◽  
Vol 15 (01) ◽  
pp. 43-61 ◽  
Author(s):  
Hesham K. Alfares ◽  
Salih O. Duffuaa
Keyword(s):  
Decision Making ◽  
Rank Order ◽  
Probability Distributions ◽  
Decision Makers ◽  
Estimation Accuracy ◽  
Multi Criteria Decision Making ◽  
Simulation Based ◽  
Criteria Weights ◽  
Single Method ◽  
Preference Structures

This paper presents a simulation study to assess the performance of the five known methods for converting ranks of several criteria into weights in multi-criteria decision-making. The five methods assessed for converting criteria ranks into weights are: rank- sum (RS) weights, rank reciprocal (RR) weights, rank order centroid (ROC) weights, geometric weights (GW), and variable-slope linear (VSL) weights. The methods are compared in terms of weight estimation accuracy considering different numbers of criteria and decision makers’ (MS) preference structures. Alternative preference structures are represented by different probability distributions of randomly generated criteria weights, namely the uniform, normal, and exponential distributions. Results of the simulation experiments indicate that no single method is consistently superior to all others. On average, RS is best for uniform weights, VSL is best for normal weights, and ROC is best for exponential weights. However, for any multi-criteria decision-making (MCDM) problem, the best method for converting criteria ranks into weights depends on both the number of criteria and the weight distribution.

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