Skip to main content
SpringerLink
Log in
Book cover

Data, Expert Knowledge and Decisions pp 279–290Cite as

Asymmetric Multidimensional Scaling of Car Switching Data

  • Conference paper

Summary

Car switching data among 16 car segments was analyzed by an asymmetric multidimensional scaling. The car switching data was formed by rescaling a 16 × 16 car switching matrix whose (j, k) element represents the frequency with which any car in car segment j was traded-in for any car in car segment k. The asymmetric multidimensional scaling utilized in the present study represents each car segment as a point and a circle (shpere, hypershpere) centered at the point representing the car segment in a multidimensional Euclidean space. The resulting three-dimensional solution revealed size or price dimension, imports-captive imports-domestic dimension, and specialty dimension. It seems that radii of shperes might represent the relative dominance or attractiveness of car segments.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Bishop YMM, Fienberg SE, Holland PW (eds.) (1975). Discrete Multivariate Analysis: Theory and Practice. The MIT Press

    Google Scholar 

  • Blau PM, Duncan OD (1967) The American Occupational Structure. Wiley, New York

    Google Scholar 

  • Carroll JD, Arabie P (1980) Multidimensional Scaling. Annual Review of Psychology 31: 607–649

    Article  Google Scholar 

  • Chino N (1978) A Graphical Technique for Representing the Asymmetric Relationships between N Objects. Behaviormetrika 5: 23–40

    Article  Google Scholar 

  • Cliff N (1968) Orthogonal Rotation to Congruence. Psychometrika 31: 33–42

    Article  Google Scholar 

  • Constantine AG, Gower JC (1978) Graphical Representation of Asymmetric Matrices. Applied Statistics 27: 297–304

    Article  Google Scholar 

  • Coombs CH (1964) A Theory of Data. Wiley, New York

    Google Scholar 

  • Coxon APM (1982) The User’s Guide to Multidimensional Scaling. Heinemann Educational Books, Exeter

    Google Scholar 

  • Cunningham JP (1978) Free Trees and Bidirectional Trees as Representations of Psychological Distance. Journal of Mathematical Psychology 17: 165–188

    Article  Google Scholar 

  • Gower JC (1977) The Analysis of Asymmetry and Orthogonality, in: Barra JR, Brodeau F, Romier G, van Cutsem B (eds.) Recent Developments in Statistics. North Holland, Amsterdam, pp 109–123

    Google Scholar 

  • Green PE, Wind Y, Jain AK (1973) Analyzing Free-Response Data in Marketing Research. Journal of Marketing Research 10: 45–52

    Article  Google Scholar 

  • Harshman, RA (1978) Models for Analysis of Asymmetrical Relationships Among N Objects or Stimuli. Paper presented at the First Joint Meeting of the Psychometric Society and the Society for Mathematical Psychology at McMaster University, Hamilton, Ontario

    Google Scholar 

  • Harshman RA (1981) DEDICOM Multidimensional Analysis of Skew-Symmetrical Data. Technical Memorandum, Bell Telephone Laboratories

    Google Scholar 

  • Harshman RA, Green PE, Wind Y, Lundy ME (1982) A Model for the Analysis of Asymmetric Data in Marketing Research. Marketing Science 1: 205–242

    Article  Google Scholar 

  • Harshman RA, Lundy ME (1984) The PARAFAC Model for Three-Way Factor Analysis and Multidimensional Scaling, in: Law LG, Snyder CW, Hattie JA, McDonald RP (eds.) Research Methods for Multimode Data Analysis. Praeger, New York, pp 122–215

    Google Scholar 

  • Holman EW (1979) Monotonic Models for Asymmetric Proximities. Journal of Mathematical Psychology 20: 1–15

    Article  Google Scholar 

  • Holman EW (1979) Johnson SC Hierarchical Clustering Schemes. Psychometrika 32: 241–255

    Google Scholar 

  • Krumhansl CL (1978). Concerning the Applicability of Geometric Models to Similarity Data: The Interrelationship between Similarity and Spatial Density. Psychological Review 85: 445–463

    Article  Google Scholar 

  • Kruskal JB (1964a) Multidimensional Scaling by Optimizing Goodness of Fit to a Nonmetric Hypothesis. Psychometrika 29: 1–27

    Article  Google Scholar 

  • Kruskal JB (1964b) Nonmetric Multidimensional Scaling: A Numerical Method. Psychometrika 29: 115–129

    Article  Google Scholar 

  • Kruskal JB (1964a) Multidimensional Scaling by Optimizing Goodness of Fit to a Nonmetric Hypothesis. Psychometrika 29: 1–27

    Article  Google Scholar 

  • Lorr M (1983) Cluster Analysis for Social Scientists. Jossey-Bass., San Francisco

    Google Scholar 

  • Laumann EO, Guttman L (1966) The Relative Associational Contigiuty of Occupations in an Urban Setting. American Sociological Review 31: 169–178

    Article  Google Scholar 

  • McDonald KI (1972) MDSCAL and Distances between Socio-Economic Groups, in: Hope K (ed.) The Analysis of Social Mobility. Charendon Press, Oxford, pp 211–234

    Google Scholar 

  • Okada A (1986) Asymmetric Multidimensional Scaling of Intergenerational Occupational Mobility, in: Proceedings of the Second Japan China Symposium on Statistics. Kyushu University, Fukuoka, Japan, pp 197–200

    Google Scholar 

  • Okada A, Imaizumi T (1984) Geometric Models for Asymmetric Similarity Data. Research Report, Rikkyo (St.Paul’s) University

    Google Scholar 

  • Okada A, Imaizumi T (1987) Nonmetric Multidimensional Scaling of Asymmetric Proximities. Behaviormetrika 21: 81–96

    Article  Google Scholar 

  • Okada A, Imaizumi T (in press) How to Use Nonmetric Asymmetric Multidimensional Scaling Program (NAMS Version 1. 1f). Journal of Applied Sociology

    Google Scholar 

  • Rips LJ, Shoben EJ, Smith EE (1973) Semantic Distance and the Verification of Semantic Relations. Journal of Verbal Learning and Verbal Behavior 12: 1–20

    Article  Google Scholar 

  • Rosch E (1975) Cognitive Reference Points. Cognitive Psychology 7: 532–547

    Article  Google Scholar 

  • Shepard RN (1963) Analysis of Proximities as a Technique for the Study of Information Processing in Man. Human Factors 5: 33–48

    Google Scholar 

  • Smith EE, Medin DL (1981). Categories and Concepts. Harvard University Press, Cambridge

    Google Scholar 

  • Tobler W (1977) Spatial Interaction Patterns. Journal of Environmental Systems 6: 271–301

    Article  Google Scholar 

  • Tobler WR (1979) Estimation of Attractivities from Interactions. Environment and Planning A 11: 121–127

    Article  Google Scholar 

  • Tversky A (1977) Features of Similarity. Psychological Review 84: 327–352

    Article  Google Scholar 

  • Urban GL, Hauser JR (1980) Design and Marketing of New Products. Prentice Hall, Englewood Cliffs

    Google Scholar 

  • Weeks DG, Bentler PM (1982) Restricted Multidimensional Scaling Models for Asymmetric Proximities. Psychometrika 47: 201–208

    Article  Google Scholar 

  • Young FW (1975) An Asymmetric Euclidean Model for Multi-Process Asymmetric Data, in: Proceedings of the US Japan Seminar on the Theory, Methods and Applications of Multidimensional Scaling and Related Techniques at the University of California San Diego, La Jolla, California

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Relations, School of Social Relations, Rikkyo (St. Paul’s) University, 3 Nishi Ikebukuro, Toshima-ku, Tokyo 171, Japan

    A. Okada

Authors
  1. A. Okada
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institut für Entscheidungstheorie und Unternehmensforschung, Universität Karlsruhe (TH), Kollegiengebäude am Schloß, Bau III, 7500, Karlsruhe 1, Germany

    Wolfgang Gaul

  2. Institut für Informatik, Universität der Bundeswehr, Holstenhofweg 85, 2000, Hamburg 70, Germany

    Martin Schader

Rights and permissions

Reprints and permissions

Copyright information

© 1988 Springer-Verlag Berlin · Heidelberg

About this paper

Cite this paper

Okada, A. (1988). Asymmetric Multidimensional Scaling of Car Switching Data. In: Gaul, W., Schader, M. (eds) Data, Expert Knowledge and Decisions. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-73489-2_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-73489-2_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-73491-5

  • Online ISBN: 978-3-642-73489-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation