A multiple-attribute decision-making method based on the mean value of grey number weight optimisation and its application in supply-chain management

2017 ◽  
Vol 7 (2) ◽  
pp. 297-307 ◽  
Author(s):  
Chuanmin Mi ◽  
Lin Xiao ◽  
Sifeng Liu ◽  
Xiaoyan Ruan
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Mean Value ◽  
Decision Makers ◽  
Content Type ◽  
Multiple Attribute ◽  
Subjective Preference ◽  
Weight Value ◽  
The Mean ◽  
Grey Number

Purpose With respect to the multiple-attribute decision-making problem with subjective preference for a certain attribute whose weight-value range have been given over other attributes whose weight values are unknown, a method based on the mean value of the grey number is proposed to analyse the decision-making problem. This method is used to choose a supply-chain partner under the condition that the decision makers have a preference for a certain attribute of various alternatives. The paper aims to discuss these issues. Design/methodology/approach First, the middle value of the preferred attribute’s weight-value range is supposed to be its weight value according to the content of the mean value of the grey number. Second, to reflect the decision maker’s subjective preference information, an improved optimisation model that requests the minimum deviation between the actual and expected numerical value of each attribute is constructed to assess the attributes’ weights. Third, the correlated degree and the correlation matrix, which are determined by the weight values of all attributes, are used to rank all the alternatives. Findings This paper provides a method for making a decision when decision makers have a preference for a certain attribute from an array of various alternatives, and the range of the certain attribute’s weight value is given but the weight value of the other attributes is unknown. When applied to supply-chain partner selection, this method proves feasible and effective. Practical implications This method is feasible and effective when applied to supply-chain partner selection, and can be applied to other kinds of decision-making problems. This means it has significant theoretical importance and extensive practical value. Originality/value Based on the mean value of the grey number, an optimisation model is built to determine the importance degree of each attribute, then the correlated degree of each alternative is combined to rank all the alternatives. This method can suit the decision makers’ subjective preference for a certain attribute well.

Appraisement and benchmarking of supply chain performance extent

2015 ◽  
Vol 5 (1) ◽  
pp. 2-30 ◽  
Author(s):  
Santosh Kumar Sahu ◽  
Saurav Datta ◽  
Siba Sankar Mahapatra
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Fuzzy Numbers ◽  
Decision Makers ◽  
Supply Chain Performance ◽  
Triangular Fuzzy Numbers ◽  
Subjective Judgment ◽  
Content Type ◽  
Grey Relation ◽  
Evaluation Information

Purpose – Supply chain performance (SCP) extent can be attributed as a function of multiple criteria/attributes. Most of the criterions/attributes being intangible in nature; SCP appraisement relies on the subjective judgment of the decision makers. Moreover, quantitative appraisement of SCP appears to be very difficult due to involvement of ill-defined (vague) performance measures as well as metrics. The purpose of this paper is to develop an efficient decision support system (DSS) to facilitate SCP appraisement, benchmarking and related decision making. Design/methodology/approach – This study explores the concept of fuzzy logic in order to tackle incomplete and inconsistent subjective judgment of the decision makers’ whilst evaluating supply chain’s overall performance. Grey relational analysis has been adopted in the later stage to derive appropriate ranking of alternative companies/enterprises (in the same industry) in view of ongoing SCP extent. Findings – In this work, a performance appraisement index system has been postulated to gather evaluation information (weights and ratings) in relation to SCP measures and metrics. Combining the concepts of fuzzy set theory, entropy, ideal and grey relation analysis, a fuzzy grey relation method for SCP benchmarking problem has been presented. First, triangular fuzzy numbers and linguistic evaluation information characterized by triangular fuzzy numbers have been used to evaluate the importance weights of all criteria and the superiority of all alternatives vs various criteria above the alternative level. Then, the concept of entropy has been utilized to solve the adjusted integration weight of all objective criteria above the alternative level. Moreover, using the concept of the grey ration grades, various alternatives have been ranked accordingly. Originality/value – Finally, an empirical example of selecting most appropriate company has been used to demonstrate the ease of applicability of the aforesaid approach. The study results showed that this method appears to be an effective means for tackling multi-criteria decision-making problems in uncertain environments. Empirical data have been analysed and results obtained thereof, have been reported to exhibit application potential of the said fuzzy grey relation based DSS in appropriate situation.

The role of blockchain in reducing the impact of barriers to humanitarian supply chain management

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ali Ihsan Ozdemir ◽  
Ismail Erol ◽  
Ilker Murat Ar ◽  
Iskender Peker ◽  
Ali Asgary ◽  
...  
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Decision Aid ◽  
Decision Makers ◽  
Chain Management ◽  
Content Type ◽  
Humanitarian Supply Chain ◽  
The Impact

PurposeThe objective of this study is to investigate the role of blockchain in reducing the impact of barriers to humanitarian supply chain management (HSCM) using a list of blockchain benefits.Design/methodology/approachA decision aid was used to explore the suitability of blockchain in humanitarian supply chains. To achieve that, first, a list of barriers to HSCM was identified. Then, the intuitionistic fuzzy decision-making trial and evaluation laboratory (IF–DEMATEL) method was utilized to determine the relationships and the level of interdependencies among the criteria. Finally, the intuitionistic fuzzyanalytic network process (IF–ANP) technique was employed, as it successfully handles dependencies among the criteria.FindingsThe findings of this study suggest that interorganizational barriers are the most suitable ones, the impacts of which blockchain may alleviate. This study further suggests that trust turned out to be the most significant benefit criterion for the analysis.Research limitations/implicationsThe readers should construe the findings of this study with caution since it was carried out using the data collected from the experts of a particular country. Moreover, the proposed decision aid contemplates a limited set of criteria to assess a possible role of blockchain in overcoming the barriers to HSCM.Practical implicationsThe findings of this study can assist humanitarian supply chain managers to make more judicious assessments on whether they implement the blockchain in humanitarian supply chain operations. Specifically, this research may help decision makers to identify the certain barriers, the impact of which may be reduced by using the blockchain. The findings of this research will also help various decision makers make more rational decisions and allocate their resources more effectively.Originality/valueTo the best of authors’ knowledge, no single study exists to investigate the role of blockchain in reducing the impact of barriers to HSCM using an intuitionistic fuzzy multi-criteria decision-making approach.

Evaluation of risks in foodgrains supply chain using failure mode effect analysis and fuzzy VIKOR

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rishabh Rathore ◽  
J. J. Thakkar ◽  
J. K. Jha
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Supply Chain ◽  
Failure Mode ◽  
Risk Mitigation ◽  
Supply Chain System ◽  
Effect Analysis ◽  
Content Type ◽  
Fuzzy Vikor ◽  
Multiple Attribute

PurposeThis paper investigates the risks involved in the Indian foodgrain supply chain (FSC) and proposes risk mitigation taxonomy to enable decision making.Design/methodology/approachThis paper used failure mode and effect analysis (FMEA) for risk estimation. In the traditional FMEA, risk priority number (RPN) is evaluated by multiplying the probability of occurrence, severity and detection. Because of some drawbacks of the traditional FMEA, instead of calculating RPN, this paper prioritizes the FSC risk factors using fuzzy VIKOR. VIKOR is a multiple attribute decision-making technique which aims to rank FSC risk factors with respect to criteria.FindingsThe findings indicate that “technological risk” has a higher impact on the FSC, followed by natural disaster, communication failure, non-availability of procurement centers, malfunctioning in PDS and inadequate storage facility. Sensitivity analysis is performed to check the robustness of the results.Practical implicationsThe outcomes of the study can help in deriving detailed risk mitigation strategy and risk mitigation taxonomy for the improved resilience of FSC.Originality/valueSpecifically, this research investigates the risks for foodgrains supply chain system for a developing country such as India, an area which has received limited attention in the present literature.

Multi-stage group risk decision making with grey numbers based on grey target and prospect theory

2016 ◽  
Vol 6 (1) ◽  
pp. 64-79 ◽  
Author(s):  
Shuli Yan ◽  
Sifeng Liu
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Group Decision ◽  
Expected Utility Theory ◽  
Decision Makers ◽  
Content Type ◽  
Multi Stage ◽  
Zero Reference ◽  
Grey Number ◽  
Risk Decision

Purpose – With respect to multi-stage group risk decision-making problems in which all the attribute values take the form of grey number, and the weights of stages and decision makers are unknown, the purpose of this paper is to propose a new decision-making method based on grey target and prospect theory. Design/methodology/approach – First, the sequencing and distance between two grey numbers are introduced. Then, a linear operator with the features of the “rewarding good and punishing bad” is presented based on the grey target given by decision maker, and the prospect value function of each attribute based on the zero reference point is defined. Next, weight models of stages and decision makers are suggested, which are based on restriction of stage fluctuation, the maximum differences of alternatives and the maximum entropy theory. Furthermore, the information of alternatives is aggregated by WA operator, the alternatives are selected by their prospect values. Findings – The comprehensive cumulative prospect values are finally aggregated by WA operator, alternatives are selected or not are judged by the sign of the comprehensive prospect theory, if the prospect value of alternative is negative, the corresponding alternative misses the group decision makers’ grey target, on the contrary, if the prospect value of alternative is positive, the corresponding alternative is dropped into the group decision makers’ grey target, the alternative with positive prospect value whose value is the maximum is selected. Originality/value – Compared with the traditional decision-making methods using expected utility theory which suppose the decision makers are all completely rational, the proposed method is based on irrational which is more in line with the decision maker’s psychology. And this method considers the decision maker’s psychological expectation values about every attribute, different satisfactory grey target about attributes will directly affect decision-making result.

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.

Interval grey numbers based multi-attribute decision making method for supplier selection

Kybernetes ◽  
2014 ◽  
Vol 43 (7) ◽  
pp. 1064-1078 ◽  
Author(s):  
Naiming Xie ◽  
Jianghui Xin
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Decision Makers ◽  
Selection Problem ◽  
Content Type ◽  
Numerical Example ◽  
Possibility Degree ◽  
Multi Attribute Decision Making ◽  
Grey Number ◽  
Supplier Selection Problem

Purpose – The purpose of this paper is to study a novel grey possibility degree approach, which is combined with multi-attribute decision making (MADM) and applied MADM model for solving supplier selection problem under uncertainty information. Design/methodology/approach – The supplier selection problem is a typical MADM problem, in which information of a series of indexes should be aggregated. However, it is relatively easy for decision makers to define information in uncertainty, sometimes as a grey number, rather than a precise number. By transforming linguistic scale of rating supplier selection attributes into interval grey numbers, a novel grey MADM method is developed. Steps of proposed model were provided, and a novel grey possibility degree approach was proposed. Finally, a numerical example of supplier selection is utilized to demonstrate the proposed approach. Findings – The results show that the proposed approach could solve the uncertainty decision-making problem. A numerical example of supplier selection is utilized to demonstrate the proposed approach. The results show that the proposed method is useful to aggregate decision makers’ information so as to select the potential supplier. Practical implications – The approach constructed in the paper can be used to solving uncertainty decision-making problems that the certain value of the decision information could not collect while the interval value set could be defined. Obviously it can be utilized for other MADM problem. Originality/value – The paper succeeded in redefining interval grey number, constructing a novel interval grey number based MADM approach and providing the solution of the proposed approach. It is very useful to solving system forecasting problem and it contributed undoubtedly to improve grey decision-making models.

Rigorous time-domain analysis of statistically oriented graphene sheet fluctuations

2017 ◽  
Vol 36 (5) ◽  
pp. 1351-1363 ◽  
Author(s):  
Athanasios N. Papadimopoulos ◽  
Stamatios A. Amanatiadis ◽  
Nikolaos V. Kantartzis ◽  
Theodoros T. Zygiridis ◽  
Theodoros D. Tsiboukis
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Finite Difference ◽  
Surface Waves ◽  
Time Domain ◽  
Finite Difference Time Domain ◽  
Mean Value ◽  
Content Type ◽  
The Mean ◽  
Difference Time

Purpose Important statistical variations are likely to appear in the propagation of surface plasmon polariton waves atop the surface of graphene sheets, degrading the expected performance of real-life THz applications. This paper aims to introduce an efficient numerical algorithm that is able to accurately and rapidly predict the influence of material-based uncertainties for diverse graphene configurations. Design/methodology/approach Initially, the surface conductivity of graphene is described at the far infrared spectrum and the uncertainties of its main parameters, namely, the chemical potential and the relaxation time, on the propagation properties of the surface waves are investigated, unveiling a considerable impact. Furthermore, the demanding two-dimensional material is numerically modeled as a surface boundary through a frequency-dependent finite-difference time-domain scheme, while a robust stochastic realization is accordingly developed. Findings The mean value and standard deviation of the propagating surface waves are extracted through a single-pass simulation in contrast to the laborious Monte Carlo technique, proving the accomplished high efficiency. Moreover, numerical results, including graphene’s surface current density and electric field distribution, indicate the notable precision, stability and convergence of the new graphene-based stochastic time-domain method in terms of the mean value and the order of magnitude of the standard deviation. Originality/value The combined uncertainties of the main parameters in graphene layers are modeled through a high-performance stochastic numerical algorithm, based on the finite-difference time-domain method. The significant accuracy of the numerical results, compared to the cumbersome Monte Carlo analysis, renders the featured technique a flexible computational tool that is able to enhance the design of graphene THz devices due to the uncertainty prediction.

CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection

2021 ◽  
pp. 1-11
Author(s):  
Huiyuan Zhang ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Comparison Method ◽  
Entropy Method ◽  
Decision Makers ◽  
Green Supplier Selection ◽  
Multiple Attribute ◽  
Psychological Perceptions

The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified.

The hidden power of language

2020 ◽  
Vol 11 (1) ◽  
pp. 187-206
Author(s):  
Philipp Hummel ◽  
Jacob Hörisch
Keyword(s):  
Decision Making ◽  
Value Creation ◽  
Cost Reduction ◽  
Social Consequences ◽  
Decision Makers ◽  
Social Aspects ◽  
Social Aspect ◽  
Content Type ◽  
Current Accounting ◽  
Cost Reductions

Purpose Stakeholder theory research identifies changes in language as one possible mechanism to overcome the deficiencies of current accounting practices with regard to social aspects. This study aims to examine the effects of the terms used for specific accounts on company internal decision-making, drawing on the example of “value creation accounting”. Design/methodology/approach The study uses a survey based-experiment to analyze the effects of terms used for specific accounts on decision-making, with a focus on social aspects (in particular expenditures for staff) in cost reduction and expenditure decisions. Findings The findings indicate that wordings, which more closely relate to value creation than to costs, decrease cost reductions and increase the priority ascribed to the social aspect of reducing staff costs in times of financial shortage. The effects of terms used on cost reductions are stronger among female decision makers. Practical implications The analysis suggests that conventional accounting language best suits organizations that aim at incentivizing decision makers to primarily cut costs. By contrast, if an organization follows an approach that puts importance on social aspects in times of financial shortage and on not doing too sharp cost reductions, value creation-oriented language is the more effective approach. Social implications The study suggests that the specific terminology used for accounts should be chosen more carefully and with awareness for the possible effects on cost reduction decisions as well as on social consequences. Originality/value This study contributes to a better understanding of the relevance of language in accounting. It suggests that the terms used for accounts should be chosen purposefully because of their far-reaching potential consequences for stakeholders as well as for the organization.

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