A Thurstonian comparison of the analytic hierarchy process and probabilistic multidimensional scaling through application to the nuclear waste site selection decision

Abstract Monte-Carlo simulation and subjective evaluations are used to compare the Analytic Hierarchy Process (AHP) and probabilistic multidimensional scaling (PROSCAL) in the context of selecting the United States' first high-level nuclear waste repository. The simulation assumes a Thurstonian judgment framework as a means of evaluating the perofrmance of AHP/PROSCAL estimation procedures. Simulated factors include the amount of Thurstonian uncertainty and number of decision-makers. The subjective evaluations of the two methods are given by individuals who make both AHP and PROSCAL judgments in a hypothetical nuclear waste repository decision. Various strengths and weaknesses of the two methods are identified.

[1]  E. Erkut,et al.  Locating obnoxious facilities in the public sector: An application of the analytic hierarchy process to municipal landfill siting decisions , 1991 .

[2]  David B. MacKay,et al.  Probabilistic Multidimensional Analysis of Preference Ratio Judgments , 1989 .

[3]  T. Saaty.  An exposition of the AHP in reply to the paper “remarks on the analytic hierarchy process” , 1990 .

[4]  Eric J. Johnson,et al.  Information displays and preference reversals , 1988 .

[5]  David B. MacKay,et al.  Probabilistic multidimensional scaling: An anisotropic model for distance judgments , 1989 .

[6]  A H Gholamnezhad,et al.  Formulating Energy Strategies and Policies for China: A Systematic Approach , 1984 .

[7]  Ricardo D. Kamenetzky.  THE RELATIONSHIP BETWEEN THE ANALYTIC HIERARCHY PROCESS AND THE ADDITIVE VALUE FUNCTION , 1982 .

[8]  C. C. Waid,et al.  An Experimental Comparison of Different Approaches to Determining Weights in Additive Utility Models , 1982 .

[9]  V. Belton.  A comparison of the analytic hierarchy process and a simple multi-attribute value function , 1986 .

[10]  James Jaccard,et al.  A comparison of six methods for assessing the importance of perceived consequences in behavioral decisions: Applications from attitude research , 1984 .

[11]  Yacov Y. Haimes,et al.  Integration of the surrogate worth trade-off method and the analytic hierarchy process , 1986 .

[12]  L. Thurstone.  A law of comparative judgment. , 1994 .

[13]  R. Shepard.  Ecological constraints on internal representation: resonant kinematics of perceiving, imagining, thinking, and dreaming. , 1984, Psychological review.

[14]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[15]  C. Coombs.  A theory of data. , 1965, Psychology Review.

[16]  Claes Fornell,et al.  The Nature and Methodological Implications of the Cognitive Representation of Products , 1987 .

[17]  Harry Timmermans,et al.  Behavioural Modelling in Geography and Planning , 1988 .

[18]  A. R. Banai-Kashani,et al.  A paradigm for location and multidimensional problems in planning , 1984 .

[19]  Joseph L. Zinnes,et al.  A Probabilistic Model for the Multidimensional Scaling of Proximity and Preference Data , 1986 .

[20]  R. Shepard,et al.  Second-order isomorphism of internal representations: Shapes of states ☆ , 1970 .

[21]  Karl Christoph Klauer,et al.  New developments in psychological choice modeling , 1989 .

[22]  J. Dyer.  Remarks on the analytic hierarchy process , 1990 .

[23]  R. Shepard.  Attention and the metric structure of the stimulus space. , 1964 .

[24]  Thomas L. Saaty,et al.  High-Level Nuclear Waste Management: Analysis of Options , 1982 .

[25]  Elliott N. Weiss,et al.  AHP DESIGN ISSUES FOR LARGE-SCALE SYSTEMS , 1987 .

[26]  N. L. Johnson,et al.  Continuous Univariate Distributions. , 1995 .

[27]  Gregory W. Fischer,et al.  UTILITY MODELS FOR MULTIPLE OBJECTIVE DECISIONS: DO THEY ACCURATELY REPRESENT HUMAN PREFERENCES?* , 1979 .