On multiplicative priority rating methods for the AHP

Stam, Antonie; Silva, A. Pedro Duarte

doi:10.1016/s0377-2217(02)00228-x

Cited by 66 publications

(31 citation statements)

References 17 publications

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“…A more fundamental solution to avoid rank reversals has been proposed by Lootsma. He suggested the use of a multiplicative value function instead of the additive value function in the multiplicative AHP [32,33].…”

Section: Calculating the Priorities For The Alternativesmentioning

confidence: 99%

Group Decision Making with the Analytic Hierarchy Process in Benefit-Risk Assessment: A Tutorial

Hummel

Bridges

IJzerman

2014

Patient

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The analytic hierarchy process (AHP) has been increasingly applied as a technique for multi-criteria decision analysis in healthcare. The AHP can aid decision makers in selecting the most valuable technology for patients, while taking into account multiple, and even conflicting, decision criteria. This tutorial illustrates the procedural steps of the AHP in supporting group decision making about new healthcare technology, including (1) identifying the decision goal, decision criteria, and alternative healthcare technologies to compare, (2) structuring the decision criteria, (3) judging the value of the alternative technologies on each decision criterion, (4) judging the importance of the decision criteria, (5) calculating group judgments, (6) analyzing the inconsistency in judgments, (7) calculating the overall value of the technologies, and (8) conducting sensitivity analyses. The AHP is illustrated via a hypothetical example, adapted from an empirical AHP analysis on the benefits and risks of tissue regeneration to repair small cartilage lesions in the knee. Key Points for Decision MakersIn a step-by-step approach, it is illustrated how the analytic hierarchy process (AHP) can support groups making healthcare decisions.The AHP facilitates the decision makers in discussing and valuing the multiple outcomes of alternative healthcare technologies.The AHP can prioritize the healthcare technology to help decision makers in selecting the most valuable technology for patients.

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Section: Calculating the Priorities For The Alternativesmentioning

confidence: 99%

Group Decision Making with the Analytic Hierarchy Process in Benefit-Risk Assessment: A Tutorial

Hummel

Bridges

IJzerman

2014

Patient

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“…The multiplicative adherents [2,22] criticize the ambiguous criteria weights used in AHP. Yet, they themselves do not pay attention to the wording necessary for the criteria weights in the multiplicative model.…”

Section: Discussionmentioning

confidence: 99%

“…There is also disagreement on the validity of rank preservation of alternatives after some alternative is added or deleted [3,21]. Another disagreement is whether additive or multiplicative aggregation is the better way to aggregate [22]. In the remainder of this paper, we compare the fundamental properties of the additive and multiplicative aggregation rules for ratio scales MCDM.…”

Section: Literature Reviewmentioning

confidence: 99%

Comparing Fundamentals of Additive and Multiplicative Aggregation in Ratio Scale Multi-Criteria Decision Making

Choo¹,

Wedley²

2008

TOORJ

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Additive and multiplicative aggregations of ratio scale preferences are frequently used in multi-criteria decision making models. In this paper, we compare the advantages and limitations of these two aggregation rules by exploring only their fundamental properties after ratio scaled local priorities and criteria weights have been successfully generated from the decision maker. The comparisons of these properties are therefore independent of ancillary procedures such as interactive elicitations from decision makers, pairwise comparisons and calculations of local priorities and criteria weights. We compare six fundamental properties of the two aggregation rules. The criteria weights used in the multiplicative aggregation have complicated meanings which are not well understood and often mixed up in the ambiguous notion of "criteria importance". As the scaling factors of the local preference values do not appear explicitly in the computations of the relative ratios of the overall preferences in the multiplicative aggregation model, the relative ratios remain unchanged when the scaling factors are changed or an alternative is added or deleted. Furthermore, the relative ratios in the multiplicative aggregation do not depend on similar local preference values which cancel each other out mathematically. It is quite evident that the additive aggregation model is superior and easier for decision makers to use and understand. We recommend the additive aggregation rule over the multiplicative aggregation rule.

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“…Due to its rank reversal preservation and its non-linear properties (Triantaphyllou and Baig, 2005), the multiplicative AHP (MAHP) seems to receive a growing attention. In particular Stam and Duarte Silva (2003) notice that the additive AHP tends to overweight extreme alternatives, which seems not to be the case for the MAHP. He suggests that further research should be done to confirm these observations.…”

Section: Aggregationmentioning

confidence: 94%

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

Ishizaka

Balkenborg

Kaplan

2011

Journal of the Operational Research Society

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Analytic Hierarchy Process (AHP) is one of the most popular multi-attribute decision aid methods. However, within AHP, there are several competing preference measurement scales and aggregation techniques. In this paper, we compare these possibilities using a decision problem with an inherent trade-off between two criteria. A decision-maker has to choose among three alternatives: two extremes and one compromise. Six different measurement scales described previously in the literature and the new proposed logarithmic scale are considered for applying the additive and the multiplicative aggregation techniques. The results are compared with the standard consumer choice theory. We find that with the geometric and power scales a compromise is never selected when aggregation is additive and rarely when aggregation is multiplicative, while the logarithmic scale used with the multiplicative aggregation most often selects the compromise that is desirable by consumer choice theory.

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On multiplicative priority rating methods for the AHP

Cited by 66 publications

References 17 publications

Group Decision Making with the Analytic Hierarchy Process in Benefit-Risk Assessment: A Tutorial

Group Decision Making with the Analytic Hierarchy Process in Benefit-Risk Assessment: A Tutorial

Comparing Fundamentals of Additive and Multiplicative Aggregation in Ratio Scale Multi-Criteria Decision Making

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

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