Influence of aggregation and measurement scale on ranking a compromise alternative in AHP

Ishizaka, Alessio; Balkenborg, Dieter; Kaplan, Todd R.

doi:10.1057/jors.2010.23

Cited by 93 publications

(18 citation statements)

References 47 publications

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“…It is also a common tool for ranking independent factors having impact on a complex phenomenon [103][104][105]. In order to ensure robustness of the results, we chose an AHP method with three different scales, representing three main scale groups, i.e., from first category, we chose inverse linear scale [106], logarithmic [107] and a power scale [108] from the second and the third categories. Once the Eigenvectors using all the three scales were computed, the next step was the normalization of the obtained results.…”

Section: Analytic Hierarchy Process Methodsmentioning

confidence: 99%

Assessment of Factors Causing Bias in Marketing- Related Publications

et al. 2020

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The present paper aims at revealing and ranking the factors that most frequently cause bias in marketing-related publications. In order to rank the factors causing bias, the authors employed the Analytic Hierarchy Process method with three different scales representing all scale groups. The data for the study were obtained through expert survey, which involved nine experts both from the academia and scientific publishing community. The findings of the study confirm that factors that most frequently cause bias in marketing related publications are sampling and sample frame errors, failure to specify the inclusion and exclusion criteria for researched subjects and non-responsiveness.

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Section: Analytic Hierarchy Process Methodsmentioning

confidence: 99%

Assessment of Factors Causing Bias in Marketing- Related Publications

et al. 2020

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“…where: i=line j=column n=criteria (5) = criteria After obtaining priority, the main criteria in determining prospective debtors then is to determine the priority of the sub-criteria of each of the main criteria using equations . Various other forms of scale have been proposed with different preference strength intervals, such as Power Scale [17], Geometric Scale [18], and Logarithmic Scale [19]. The examples presented from our approach use a scale of 1-9, but any limited numerical scale can be used in this approach.…”

Section: Methodsmentioning

confidence: 99%

Decision Analysis of Giving Credit Using Pairwise Comparisons and Scoring Methods (Case Study: Bank XYZ)

Priangga

Suryani

2019

JTS

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Usaha Rakyat (KUR) is a type of credit given by Bank for segment business Micro, Small and Medium Enterprises (UMKMK). Along with the high interest of the community in applying for credit to the Bank, it raises its problems, namely determining the feasibility of customers. Determining this feasibility is important, considering that KUR is one of the Government's programs in empowering the UMKMK industry sector so that the risk of non-performing loans is expected to be minimized. The method used in this study is the Pairwise Comparisons and Scoring, based on the consideration that Pairwise Comparisons and Scoring are aids in priority of criteria, the priority of sub-criteria and giving scoring to determine lending decisions. Pairwise Comparisons are the basic concepts of the Analytical Hierarchy Process, which have been proven to solve decision problems which involve many complex criteria. The results obtained in this study are the priority of criteria, the priority of, and scoring of debtors for the determination of debtors who are eligible or not eligible for receive credit-30 debtors who were sampled in this study. There were 17 debtors eligible to receive credit and 13 debtors were not eligible to receive credit.

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“…The authors Kumar et al [147], for example, applied AHP to consider, at stratified levels, many criteria, and opinions of the multiple stakeholders involved in sustainable micro-grid design scenarios. The three principles (decomposition, comparative judgments, and priority synthesis) can be accomplished by the following steps: modeling or structuring of the decision problem, valuation and aggregation of weight, and sensitivity analysis [186]. Expert comparative judgments weight the criteria of the hierarchical structure and permit a check of consistency by a proportion scale [187].…”

Section: Ahpmentioning

confidence: 99%

“…The alternative prioritization vector is calculated by assigning values that describe the degree to which a given alternative meets the criteria. Additive aggregation with the normalization of the sum of local priorities determines the overall option priorities at the last level of the hierarchical structure [186]. Hence, the AHP method permits divided the problem into its smaller parts, helping decision-makers organize the critical aspects of a problem [28,171].…”

Section: Ahpmentioning

confidence: 99%

Renewable Energy Problems: Exploring the Methods to Support the Decision-Making Process

et al. 2020

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In the current scenario of increasing energy demand and encouraging sustainable development in countries, the energy sector’s planning has become more complex, involving multiple factors, such as technical, economic, environmental, social, and political. The decision process plays a vital role in structuring and evaluating complex decision situations related to the sector, considering various criteria and objectives, encouraging adopting policies to promote energy efficiency actions by increasing research on renewable energy sources and strategic energy decisions. The high number of multi-criteria decision support methods (MCDM) available and their efficiency in solving highly complex problems results in an impasse with their selection and application in specific decision situations. Thus, the scientific community requires methodological approaches that help the decision-maker select the method consistent with his problem. Accordingly, this paper conducts a Systematic Literature Review (SLR) of renewable energy problems associated with MCDM methods based on a final set of 163 articles. We identified five categories of problems solved by MCDM techniques: Source selection, location, sustainability, project performance, and technological performance. We separate the MCDM process into five evaluation steps (alternative selection, criteria selection, criteria weighting, evaluation of alternatives, and post-assessment analyzes), and we extract the methods used in each MCDM step from papers. This paper’s main contribution is identifying the most common MCDM methods in the renewable energy area and the energy problem they solve. Accordingly, this manuscript helps energy decision-makers, entrepreneurs, investors, and policy-makers to improve their ability to choose the proper MCDM methods to solve energy problems.

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Influence of aggregation and measurement scale on ranking a compromise alternative in AHP

Cited by 93 publications

References 47 publications

Assessment of Factors Causing Bias in Marketing- Related Publications

Assessment of Factors Causing Bias in Marketing- Related Publications

Decision Analysis of Giving Credit Using Pairwise Comparisons and Scoring Methods (Case Study: Bank XYZ)

Renewable Energy Problems: Exploring the Methods to Support the Decision-Making Process

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