IDEAS home Printed from https://ideas.repec.org/a/eee/joepsy/v19y1998i3p321-351.html
   My bibliography  Save this article

Three-mode analysis of perceptions of economic activities in Eastern and Western Europe1

Author

Listed:
  • Veldscholte, Carla M.
  • Kroonenberg, Pieter M.
  • Antonides, Gerrit

Abstract

No abstract is available for this item.

Suggested Citation

  • Veldscholte, Carla M. & Kroonenberg, Pieter M. & Antonides, Gerrit, 1998. "Three-mode analysis of perceptions of economic activities in Eastern and Western Europe1," Journal of Economic Psychology, Elsevier, vol. 19(3), pages 321-351, June.
    • Handle: RePEc:eee:joepsy:v:19:y:1998:i:3:p:321-351
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-4870(98)00010-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tyszka, Tadeusz, 1994. "How do people perceive economic activities?," Journal of Economic Psychology, Elsevier, vol. 15(4), pages 651-668, December.
    2. Thaler, Richard, 1981. "Some empirical evidence on dynamic inconsistency," Economics Letters, Elsevier, vol. 8(3), pages 201-207.
    3. Jos Berge & Jan Leeuw & Pieter Kroonenberg, 1987. "Some additional results on principal components analysis of three-mode data by means of alternating least squares algorithms," Psychometrika, Springer;The Psychometric Society, vol. 52(2), pages 183-191, June.
    4. J. Gower, 1975. "Generalized procrustes analysis," Psychometrika, Springer;The Psychometric Society, vol. 40(1), pages 33-51, March.
    5. Willem Kloot & Pieter Kroonenberg, 1985. "External analysis with three-mode principal component models," Psychometrika, Springer;The Psychometric Society, vol. 50(4), pages 479-494, December.
    6. Pieter Kroonenberg & Jan Leeuw, 1980. "Principal component analysis of three-mode data by means of alternating least squares algorithms," Psychometrika, Springer;The Psychometric Society, vol. 45(1), pages 69-97, March.
    7. Kroonenberg, Pieter M., 1994. "The TUCKALS line : A suite of programs for three-way data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 18(1), pages 73-96, August.
    8. Ledyard Tucker, 1972. "Relations between multidimensional scaling and three-mode factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 37(1), pages 3-27, March.
    9. Ledyard Tucker, 1966. "Some mathematical notes on three-mode factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 31(3), pages 279-311, September.
    10. Harshman, Richard A. & Lundy, Margaret E., 1994. "PARAFAC: Parallel factor analysis," Computational Statistics & Data Analysis, Elsevier, vol. 18(1), pages 39-72, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Richard Harshman & Margaret Lundy, 1996. "Uniqueness proof for a family of models sharing features of Tucker's three-mode factor analysis and PARAFAC/candecomp," Psychometrika, Springer;The Psychometric Society, vol. 61(1), pages 133-154, March.
    2. Dawn Iacobucci & Doug Grisaffe & Wayne DeSarbo, 2017. "Statistical perceptual maps: using confidence region ellipses to enhance the interpretations of brand positions in multidimensional scaling," Journal of Marketing Analytics, Palgrave Macmillan, vol. 5(3), pages 81-98, December.
    3. Mariela González-Narváez & María José Fernández-Gómez & Susana Mendes & José-Luis Molina & Omar Ruiz-Barzola & Purificación Galindo-Villardón, 2021. "Study of Temporal Variations in Species–Environment Association through an Innovative Multivariate Method: MixSTATICO," Sustainability, MDPI, vol. 13(11), pages 1-25, May.
    4. Kiers, Henk A. L., 1998. "Three-way SIMPLIMAX for oblique rotation of the three-mode factor analysis core to simple structure," Computational Statistics & Data Analysis, Elsevier, vol. 28(3), pages 307-324, September.
    5. Henk Kiers, 1991. "Hierarchical relations among three-way methods," Psychometrika, Springer;The Psychometric Society, vol. 56(3), pages 449-470, September.
    6. Willem Kloot & Pieter Kroonenberg, 1985. "External analysis with three-mode principal component models," Psychometrika, Springer;The Psychometric Society, vol. 50(4), pages 479-494, December.
    7. Stegeman, Alwin, 2014. "Finding the limit of diverging components in three-way Candecomp/Parafac—A demonstration of its practical merits," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 203-216.
    8. Hildebrandt, Lutz & Klapper, Daniel, 1997. "Möglichkeiten und Ansätze der Analyse dreimodaler Daten für die Marktforschung," SFB 373 Discussion Papers 1997,90, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    9. Pieter C. Schoonees & Patrick J. F. Groenen & Michel Velden, 2022. "Least-squares bilinear clustering of three-way data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(4), pages 1001-1037, December.
    10. Elisa Frutos-Bernal & Ángel Martín del Rey & Irene Mariñas-Collado & María Teresa Santos-Martín, 2022. "An Analysis of Travel Patterns in Barcelona Metro Using Tucker3 Decomposition," Mathematics, MDPI, vol. 10(7), pages 1-17, March.
    11. Yoshio Takane & Forrest Young & Jan Leeuw, 1977. "Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features," Psychometrika, Springer;The Psychometric Society, vol. 42(1), pages 7-67, March.
    12. Giuseppe Brandi & Ruggero Gramatica & Tiziana Di Matteo, 2019. "Unveil stock correlation via a new tensor-based decomposition method," Papers 1911.06126, arXiv.org, revised Apr 2020.
    13. Dahl, Tobias & Naes, Tormod, 2006. "A bridge between Tucker-1 and Carroll's generalized canonical analysis," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 3086-3098, July.
    14. Shi, Chengchun & Lu, Wenbin & Song, Rui, 2019. "Determining the number of latent factors in statistical multi-relational learning," LSE Research Online Documents on Economics 102110, London School of Economics and Political Science, LSE Library.
    15. Michel Velden & Tammo Bijmolt, 2006. "Generalized canonical correlation analysis of matrices with missing rows: a simulation study," Psychometrika, Springer;The Psychometric Society, vol. 71(2), pages 323-331, June.
    16. Paolo Giordani & Roberto Rocci & Giuseppe Bove, 2020. "Factor Uniqueness of the Structural Parafac Model," Psychometrika, Springer;The Psychometric Society, vol. 85(3), pages 555-574, September.
    17. Alwin Stegeman & Tam Lam, 2014. "Three-Mode Factor Analysis by Means of Candecomp/Parafac," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 426-443, July.
    18. Jean-Pierre Rossi & Maxime Nardin & Martin Godefroid & Manuela Ruiz-Diaz & Anne-Sophie Sergent & Alejandro Martinez-Meier & Luc Pâques & Philippe Rozenberg, 2014. "Dissecting the Space-Time Structure of Tree-Ring Datasets Using the Partial Triadic Analysis," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-13, September.
    19. Caterina Liberati & Paolo Mariani, 2012. "Banking customer satisfaction evaluation: a three-way factor perspective," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(4), pages 323-336, December.
    20. Timmerman, Marieke E. & Kiers, Henk A. L., 2002. "Three-way component analysis with smoothness constraints," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 447-470, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:joepsy:v:19:y:1998:i:3:p:321-351. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joep .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.