Attribute weighting methods and decision quality in the presence of response error: a simulation study

Jia, Jianmin; Fischer, Gregory W.; Dyer, James S.

doi:10.1002/(sici)1099-0771(199806)11:2<85::aid-bdm282>3.0.co;2-k

Cited by 172 publications

(96 citation statements)

References 25 publications

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“…Ratio weight procedures maintain ratio scale properties of the decisionmaker's judgments during the elicitation. Accurate determinations of attribute weights by using ratio weight procedures are tricky to acquire in practice as assessed weights are always subject to response error [14]. Consequently, suggestions on how to use imprecise weights have been proposed instead.…”

Section: Methods For Eliciting Weights In Mcdamentioning

confidence: 99%

“…Jia et al [14] state that due to the relative robustness of linear decision models regarding weight changes, the use of approximate weights often yields satisfactory decision quality, but that the assumption of knowing the ranking with certainty is strong. Instead, they believe that there can be uncertainty regarding both the magnitudes and ordering of weights and that people can be quite confident that some differences in importance are greater than others.…”

Section: Cardinal Rank Ordering Of Criteriamentioning

confidence: 99%

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Employing Cardinal Rank Ordering of Criteria in Multi-Criteria Decision Analysis

Riabacke¹,

Danielson²,

Larsson³

et al. 2012

Uncertainty Modeling in Knowledge Engineering and Decision Making

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The elicitation of preference information in multi-criteria decision analysis (MCDA) processes and the lack of practical means supporting it is a significant problem in real-life applications of MCDA. The issues at hand are problematical in a multitude of ways, but some of these issues may be remedied by accepting weaker input statements from decision-makers than what is most commonly needed, yet being able to utilize these statements for decision evaluation. In this paper, we propose a fast and practically useful weight elicitation method, which builds on the ideas of rank-order methods, but in addition take imprecise cardinal information into account.

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Section: Methods For Eliciting Weights In Mcdamentioning

confidence: 99%

Section: Cardinal Rank Ordering Of Criteriamentioning

confidence: 99%

Employing Cardinal Rank Ordering of Criteria in Multi-Criteria Decision Analysis

Riabacke¹,

Danielson²,

Larsson³

et al. 2012

Uncertainty Modeling in Knowledge Engineering and Decision Making

View full text Add to dashboard Cite

show abstract

“…This procedure requires very little knowledge on decisional priorities and can be used for many multicriteria decision tools. Dawes and Corrigan suggested that the equal-weighting method frequently produces results that are at least as good as precise numerical weights [31,32]. However, this method has been criticized because each criterion has different information and meanings and it is very hard to accept the idea that all the criteria can have the same weights [33].…”

Section: Shannon's Entropy For Objective Weightingmentioning

confidence: 99%

“…However, this method has been criticized because each criterion has different information and meanings and it is very hard to accept the idea that all the criteria can have the same weights [33]. As suggested by Jia Fischer & Dyer (1998) [32], several other authors have argued the superiority of the rank-order weighting method, which uses quantitative information concerning the relative importance of criteria [34][35][36][37].…”

Section: Shannon's Entropy For Objective Weightingmentioning

confidence: 99%

Evaluation of Combined Heat and Power (CHP) Systems Using Fuzzy Shannon Entropy and Fuzzy TOPSIS

2016

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Combined heat and power (CHP) or cogeneration can play a strategic role in addressing environmental issues and climate change. CHP systems require less fuel than separate heat and power systems in order to produce the same amount of energy saving primary energy, improving the security of the supply. Because less fuel is combusted, greenhouse gas emissions and other air pollutants are reduced. If we are to consider the CHP system as "sustainable", we must include in its assessment not only energetic performance but also environmental and economic aspects, presenting a multicriteria issue. The purpose of the paper is to apply a fuzzy multicriteria methodology to the assessment of five CHP commercial technologies. Specifically, the combination of the fuzzy Shannon's entropy and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach will be tested for this purpose. Shannon's entropy concept, using interval data such as the α-cut, is a particularly suitable technique for assigning weights to criteria-it does not require a decision-making (DM) to assign a weight to the criteria. To rank the proposed alternatives, a fuzzy TOPSIS method has been applied. It is based on the principle that the chosen alternative should be as close as possible to the positive ideal solution and be as far as possible from the negative ideal solution. The proposed approach provides a useful technical-scientific decision-making tool that can effectively support, in a consistent and transparent way, the assessment of various CHP technologies from a sustainable point of view.

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“…For example, the equal weight function can be applied. This technique simplifies the choice process by ignoring information about the relative importance of each attribute (Jia et al 1998;Bettman et al 2006, p. 329). In doing so the method assumes that all attributes have equal weight.…”

Section: Step 5: Perform Sensitivity Analyses and Make Recommendationsmentioning

confidence: 99%

The Measurement and Analysis of Housing Preference and Choice

Jansen¹,

Coolen²,

Goetgeluk³

2011

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Attribute weighting methods and decision quality in the presence of response error: a simulation study

Cited by 172 publications

References 25 publications

Employing Cardinal Rank Ordering of Criteria in Multi-Criteria Decision Analysis

Employing Cardinal Rank Ordering of Criteria in Multi-Criteria Decision Analysis

Evaluation of Combined Heat and Power (CHP) Systems Using Fuzzy Shannon Entropy and Fuzzy TOPSIS

The Measurement and Analysis of Housing Preference and Choice

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