Grey relational decision making model of three-parameter interval grey number based on AHP and DEA

2019 ◽  
Vol 10 (1) ◽  
pp. 25-37
Author(s):  
Bingjun Li ◽  
Xiaoxiao Zhu
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Agriculture Industry ◽  
Parameter Interval ◽  
Grey Number ◽  
Index Weight ◽  
Decision Making Model ◽  
Grey Relational ◽  
Grey Relation

Purpose The purpose of this paper is to put forward the grey relational decision-making model of three-parameter interval grey number based on Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA), based on the previous study of grey relational decision-making model, and it considers the advantages of the decision-making schemes and the subjective preferences of decision makers. Design/methodology/approach First of all, through AHP, the preference of each index is analyzed and the index weight is determined. Second, the DEA model is adopted to obtain the index weight from the perspective of the most beneficial to each scheme and objectively reflect the advantages of different schemes. Then, assign the comprehensive weights to each index of the grey relational decision-making model of three-parameter interval grey number, and calculate the grey relation degree of each scheme to rank the schemes. Findings The effectiveness of the model is proved by an example of carrier aircraft selection. Practical implications The applicability of this model is analyzed by taking carrier aircraft selection as an example. In fact, this model can also be widely used in agriculture, industry, economy, society and other fields. Originality/value In this paper, the combination of AHP and DEA is used to determine the index weight. Based on which, the grey relation degree under the three-parameter interval grey number is calculated. It intended the application space of the grey relational decision-making model.

Grey target decision-making model of interval grey number based on cone volume

2017 ◽  
Vol 7 (2) ◽  
pp. 247-258 ◽  
Author(s):  
Lizhen Wang ◽  
Wuyong Qian
Keyword(s):  
Decision Making ◽  
Entropy Method ◽  
Maximal Entropy ◽  
Information Distortion ◽  
Content Type ◽  
Model Based ◽  
Proposed Model ◽  
Grey Number ◽  
Decision Making Model ◽  
The Impact

Purpose The purpose of this paper is to propose a grey target decision model based on cobweb area in order to overcome the effect and influence from the extreme value of the index on the decision result. However, it does not take into account the impact of the correlation between indicators on the angle of the index, and produce a certain degree decision information distortion as a result of the equal angle between the indicators. In order to solve the above problems, a novel grey decision-making model based on cone volume is proposed. Design/methodology/approach In this paper, the model uses the whitening weight function to whiten the interval grey number, and the Delphi method and the maximal entropy method are exploited to integrate the weight of the index. On the basis of this, the center of the bull’s eye, the weight and the index value are constructed as the center circle, the radius, and the high cone, respectively. The scheme is selected by the volume of the cone, the decision is made according to the order relation, and the example is utilized to prove and analyze the validity of the proposed model. Findings The results show that the proposed model can well improve the traditional grey target decision-making model from the modeling object and modeling method. Practical implications The method exposed in the paper can be used to deal with the grey target decision-making problems which characteristics are multi-indexes, and the attribute values are interval grey numbers. Originality/value The paper succeeds in overcoming the disadvantages of grey target decision making based on the target center distance and the cobweb area.

Multi-attribute grey target decision method with three-parameter interval grey number

2016 ◽  
Vol 6 (2) ◽  
pp. 270-280 ◽  
Author(s):  
Ye Li ◽  
Shanli Zhu ◽  
San-dang Guo
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Ranking Method ◽  
Content Type ◽  
Uncertain Environment ◽  
Decision Method ◽  
Multi Attribute Decision Making ◽  
Parameter Interval ◽  
Grey Number ◽  
Bull's Eye

Purpose – The purpose of this paper is to propose the grey target decision method based on three-parameter interval grey number for dealing with multi-attribute decision-making problems under uncertain environment. Design/methodology/approach – First, the kernel and ranking method of three-parameter interval grey number are defined, which is the basis of determining the positive and negative bull’s-eye. Next, a new distance measure of three-parameter interval grey number is defined in view of the importance of the “center of gravity” point. Furthermore, a new comprehensive bull’s-eye distance is proposed based on the kernel which integrates the distance between different attributes to the positive and negative bull’s-eye. Then attribute weights are obtained by comprehensive bull’s-eye distance minimum and grey entropy maximization. Findings – The paper provides a grey target decision method based on three-parameter interval grey number and example analysis shows that the method proposed in this paper is more reasonable and effective. Research limitations/implications – If we have a better understanding of the distribution characteristics of three-parameter interval grey number, it is possible to have a more reasonable measure of the distance of three-parameter interval grey number. Practical implications – The paper provides a grey target decision method, which can help decision maker deal with multi-attribute decision-making problems under uncertain environment. Originality/value – This paper proposed the kernel and ranking method of three-parameter interval grey number, and defined a new distance measure of three-parameter interval grey number and proposed a new comprehensive bull’s-eye distance, Furthermore, this paper structured a grey target decision method based on three-parameter interval grey number.

Dynamic multi-attribute decision-making method with three-parameter interval grey number based on the prospect theory

2018 ◽  
Vol 8 (4) ◽  
pp. 424-435 ◽  
Author(s):  
Ye Li ◽  
Dongxing Zhang
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Value Function ◽  
Reference Points ◽  
Content Type ◽  
Time Points ◽  
Decision Method ◽  
Multi Attribute Decision Making ◽  
Parameter Interval ◽  
Grey Number

Purpose The purpose of this paper is to propose a dynamic multi-attribute decision-making method based on the prospect theory for dealing with the dynamic multi-attribute decision-making problem with three-parameter interval grey number. Design/methodology/approach First, the kernel and comparison rule of three-parameter interval grey numbers are defined, which are the basis of collecting and sorting grey numbers. Next, the prospect value function is determined in view of the decision-making information with different time points as the reference points. Then, an optimal model for solving the attribute weight and time weight is constructed based on the grey entropy principle. Findings The paper provides a dynamic grey interrelation decision method based on the prospect theory with three-parameter interval grey number, and the example analysis shows that the method proposed in this paper has validity and rationality. Research limitations/implications If we have a better understanding of the weights of different reference points, it is possible to receive a more reasonable expression for the comprehensive prospect utility value function. Practical implications The paper provides a grey interrelation decision method based on the prospect theory, which can help the decision maker deal with the dynamic multi-attribute decision-making problems under the uncertain environment. Originality/value The paper proposes the kernel and ranking method of three-parameter interval grey number, and uses different time points as the reference points to define the prospect value function. Furthermore, this paper structures a dynamic grey interrelation decision method with three-parameter interval grey number based on the prospect theory.

Developing an analytic hierarchy process-based decision model for modular construction in urban areas

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Michael Sing ◽  
Joseph Chan ◽  
Henry Liu ◽  
Nancy Hei Ngai
Keyword(s):  
Decision Making ◽  
Urban Area ◽  
Urban Areas ◽  
Modular Construction ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Decision Making Factors ◽  
Decision Making Model ◽  
Hierarchy Process ◽  
Decision Making Tool

Purpose Modular construction is considered a well-established construction method for improving the efficiency of the construction industry worldwide. However, the industry struggles to achieve higher levels of modularisation in urban areas. Previous studies on decision-making for modularisation have, so far, not focussed much on its application in urban areas. As modular construction could bring lots of advantages such as speed of construction, This study aims to develop a decision-making tool that can assist the project planners in deciding whether the modular construction techniques should be applied in their urban area project. Design/methodology/approach Based on the literature review, a total of 35 decision-making factors of modularisation were identified for this study. The decision-making model is then developed to evaluate the significance of each factor using the analytic hierarchy process (AHP) approach. A total number of 72 valid responses were obtained and analysed. The geometric mean of priorities is adopted to obtain the par-wise comparison between the critical factors in which each factor’s weighting in the decision-making model is calculated. Afterwards, the robustness of the decision-making model is demonstrated by the real-life projects in China, Hong Kong and the UK, respectively. Findings A total of 35 decision-making factors allocated in five criteria for modular construction selection in urban areas were identified. The criteria include site attributes, project characteristics, labour consideration, environmental and organisation and project risk. Their impact was calculated using the AHP to indicate the relative importance with respect to the adoption of modularisation in urban areas. Afterwards, a two-level decision-making model was developed that can be used as a decision-making tool for the adoption of modular construction. Practical implications The outcome of this research will be beneficial to industrial practitioners and academics in understanding the critical attributes that affect the adoption of modular construction in an urban area. It further enables the building professionals to assess the feasibility of using modular construction in their projects, especially at the early stage, so as to facilitate its use. Originality/value There is a number of literature on the decision-making model on the adoption of modular construction. However, previous studies did not provide specific concerns related to urban areas, whereas there is an urgent need to have an updated analysis that can be catered to the modular construction in the urban area. In this research study, the 35 decision-making factors were ranked by the experienced project managers and then a pair-wise comparison was conducted. With this information, the robust decision-making model is formulated to offer a kept promised indicator in adopting modularisation in the urban area.

Stochastic interval-grey number VIKOR method based on prospect theory

2015 ◽  
Vol 5 (1) ◽  
pp. 105-116 ◽  
Author(s):  
Qingsheng LI ◽  
Ni Zhao
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Expected Utility Theory ◽  
Decision Makers ◽  
Vikor Method ◽  
Content Type ◽  
Multi Attribute Decision Making ◽  
Grey Number ◽  
Index Weight ◽  
Attribute Value

Purpose – The purpose of this paper is to deal with interval grey-stochastic multi-attribute decision-making problems. It proposes a VIKOR method based on prospect theory in which probabilities and the attribute value are both grey numbers. Design/methodology/approach – In the prospect theory the results values and probability weight are used while the utility and probability values in the expected utility theory, which the more realistically reflect and describe the decision makers on the optimal process. VIKOR method makes the decision acceptable superiority and decision process stability. At the same time, a new interval grey number entropy is put forward, which is used to calculate the index weight of unknown. Findings – The paper provides a VIKOR method based on prospect theory in which probabilities and the attribute value are both grey numbers. And the validity and feasibility of the method are illustrated by an example. Research limitations/implications – Although VIKOR is much closer to PIS than TOPSIS, at the same time VIKOR method can get the compromise solution with priority, researchers are encouraged to carry on comparative study further. Practical implications – The paper includes interval grey-stochastic multi-attribute decision-making method and implications. The validity and feasibility of the method are illustrated by a case. Originality/value – This paper proposes a VIKOR method based on prospect theory in which probabilities and the attribute value are both interval grey numbers. At the same time, a new interval grey number entropy is put forward, which is used to calculate the index weight of unknown.

Measuring the supply chain competitiveness of e-commerce industry in Indonesia

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ade Febransyah ◽  
Joklan Imelda Camelia Goni
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Future Research ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Content Type ◽  
The Future ◽  
Business To Consumer ◽  
Software And Hardware ◽  
Decision Making Model

Purpose The purpose of this study is to measure the supply chain competitiveness of the e-commerce industry in Indonesia. Design/methodology/approach The study used a multi-criteria decision-making model based on the analytic hierarchy process. Four main criteria are used to measure the supply chain competitiveness, i.e. cost, differentiation, sustainability and infrastructure. Findings The findings of this study show that cost is the most important criterion with a degree of importance of 33.19%, followed by infrastructure of 29.40%, differentiation of 27.96% and sustainability of 9.45%. It shows that the internally controlled strategy contributes about 70% of supply chain competitiveness. The internal infrastructure criterion that consists of software and hardware contributes 65.92% to the whole infrastructure criterion. The internal infrastructure then contributes 19.38% to supply chain competitiveness. Therefore, the internally controlled strategies and internal infrastructure contribute up to 90.08% to the supply chain competitiveness of e-commerce in Indonesia. This result implies that to attain the supply chain competitiveness, the company must carry out strategies focusing on the performance such as cost, differentiation, sustainability as well as on the internal infrastructure such as software and hardware. Research limitations/implications In this paper, the authors limited their study to the business to business (B2B) and business to consumer (B2C) players because these two platforms have been experiencing a very rapid growth. While e-commerce business can take many platforms besides B2B and B2C, the future research should include other platform such as consumer to consumer as well. Because the focus in this study is more the information and material flows, it will be of great interest if the future research covers the platform of mobile payment as well that guarantee the ease of cashflows within supply chains. Also, with the occurrence of the Covid-19 pandemic when this paper was written, in the near future, it is then of great interest to incorporate the pandemic context into the proposed model used in this study. The further study should analyze long-term changes happened as the result of pandemic such as behavioral changes of online shopping from customer side or shift in e-commerce supply chain infrastructure and inventory practice. Practical implications With this study, it is expected that it can be determined which criteria contribute the most to the supply chain competitiveness of the e-commerce industry in Indonesia that will be useful for industry player. Originality/value E-commerce development in Indonesia is still facing serious challenges. The multi-criteria decision making approach used in this research lays a foundation of how supply chain competitiveness is determined based on the judgment of experts coming from major companies within the supply chain.

A GIS-based DANP-VIKOR approach to evaluate R&D performance of Turkish cities

Kybernetes ◽  
2019 ◽  
Vol 48 (10) ◽  
pp. 2266-2306 ◽  
Author(s):  
Bariş Özkan ◽  
Eren Özceylan ◽  
I.brahim Halil Korkmaz ◽  
Cihan Çetinkaya
Keyword(s):  
Decision Making ◽  
Real Life ◽  
Three Dimensions ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Solution Approach ◽  
Related Data ◽  
Effective Strategies ◽  
Pros And Cons ◽  
Decision Making Model

Purpose The purpose of this study is to measure the R&D performance of 81 cities in Turkey by using a scientific approach. Design/methodology/approach A four-step solution approach is developed for this problem. In the first step, a hierarchical structure of 14 indicators (including number of patents, publications, R&D expense, etc.) in three dimensions is constructed. In the second step, explicitly and implicitly spatial indicators such as university location and R&D manpower are mapped by using geographic information system (GIS). In the third step, a hybrid multi-criteria decision making model, namely, DANP that combines decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (ANP) techniques is applied to assign different level of importance to the indicators. In the last step, Višekriterijumska Optimizacijai kompromisno Rešenje (VIKOR) method is used to rank the performance of 81 cities. Obtained results are visualized using GIS to show the pros and cons of each city in terms of R&D performance. Findings Results of the paper show that Istanbul, Ankara and Konya are ordered as contenders of best R&D performances and on the contrary, Igdir, Sirnak and Tunceli are ordered as the worst R&D performances among 81 cities. Research limitations/implications One limitation of the study can be the considered criteria. However, all the criteria are obtained from literature and experts; thus, the paper covers as much criteria as possible. Practical implications The proposed study may allow Ministry of Science, Industry and Technology of Turkey to formulate more effective strategies to improve cities’ R&D performance. In addition, any country can apply the same methodology for measuring the R&D performance of their cities by using their related data. As the worst R&D city performances belong to the eastern part of Turkey, it can be deducted that the socio-cultural structure of the eastern part of the country needs improvement. Originality/value To the best of the author’s knowledge, this is the first study which applies a GIS-based MCDM approach for R&D performance measurement. Thus, the value of this paper belongs to both literature and real life.

scholarly journals Multi-criteria decision-making model for supporting manufacturing settlements location in Africa after COVID-19

2021 ◽  
Vol 13 ◽  
pp. 184797902110233
Author(s):  
Stefania Bait ◽  
Serena Marino Lauria ◽  
Massimiliano M. Schiraldi
Keyword(s):  
Decision Making ◽  
Value Chain ◽  
Multinational Enterprises ◽  
Value Added ◽  
Plant Performance ◽  
Multi Criteria Decision Making ◽  
African Countries ◽  
Analytic Hierarchy ◽  
Location Selection ◽  
Decision Making Model

The COVID-19 emergency is affecting manufacturing industries all over the world. Notably, it has generated several issues in the products’ supply and the global value chain in African countries. Besides this, Africa’s manufacturing value-added rate grew only 1.5 since 2018, and the foreign direct investment (FDI) from multinational enterprises (MNEs) remains very low due to high-risk factors. Most of these factors are linked to a non-optimized location selection that can adversely affect plant performance. For these reasons, supporting decision-makers in selecting the suitable country location in Africa is crucial, both for contributing to countries’ growth and companies’ performance. This research aims at presenting a comprehensive multi-criteria decision-making model (MCDM) to be used by MNEs to evaluate the best countries to develop new manufacturing settlements, highlighting the criteria that COVID-19 has impacted. Thus, it has affected countries’ performance, impacting the plant location selection choices. A combination of the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods have also been used for comparative analysis. The criteria used in the proposed approach have been validated with a panel of MNEs experts.

Grey assessment and prediction of the financial agglomeration degree in central five cities

2014 ◽  
Vol 4 (1) ◽  
pp. 95-103 ◽  
Author(s):  
Li Li ◽  
Guo-hui Hu
Keyword(s):  
Decision Making ◽  
Scientific Development ◽  
Fuzzy Decision Making ◽  
Grey Prediction ◽  
Fuzzy Decision ◽  
Content Type ◽  
Multiple Dimension ◽  
The Government ◽  
Development Tendency ◽  
Decision Making Model

Purpose – At present, financial agglomeration tendency in domestic and foreign countries is increasingly evident. Therefore, from a comparative perspective, this paper aims to assess and predict the financial agglomeration degree in central five cities. Design/methodology/approach – According to the diversity of evaluating indexes and the uncertainty of financial agglomeration, this paper constructs a set of indexes of evaluating the financial agglomeration degree, comprehensively evaluates the financial agglomeration degree of the five cities – Wuhan, Changsha, Zhengzhou, Nanchang and Hefei – in China's middle region from 2001 to 2010 by using the multiple dimension grey fuzzy decision-making model, and predicts their development tendency by using the GM (1, 1, β) model. Findings – The results show that the multiple dimension grey fuzzy decision-making pattern cannot only be used to determine the weights of evaluating indexes, but also get the fuzzy partition and ranking order of the financial agglomeration in central five cities. The grey prediction results can objectively reflect the development tendency of the financial agglomeration in central five cities. Practical implications – From the results, it is necessary for any competitive city to clarify their relative strengths and weaknesses in order for the accurate location and scientific development, and it also provides a reference for the government decision-making. Originality/value – The paper succeeds in using the multiple dimension grey fuzzy decision-making model to measure the financial agglomeration degree of the five central cities and the grey prediction model to predict future trends.

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