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«Multiway data analysis» and the general problem of journals’ ranking

Author

Listed:
  • Rubinstein, Alexander

    (Institute of Economics of the RAS, Moscow, Russian Federation)

  • Slutskin, Lev

    (Institute of Economics of the RAS, Moscow, Russian Federation)

Abstract

The paper presents a principally new ranking algorithm (on the example of economic journals) which applies methods of multiway data analysis to a sociological survey of representatives of the economic community. The algorithm provides determination of the weight function for aggregation of private ratings, taking into consideration both statistically discovered differences between the respondents and the journals weights. It also reflects latent relationships between all the components of measurement process of journals characteristics. The algorithm central element is an iterative procedure of determination of the journals core and extracting on its basis a subset of experts, whose estimates allow determining the journals aggregated ratings with subsequent clustering. The research practical result is methodological and instrumental justification of Russian economic journals ranking and selection on its basis the five categories of periodical publications.

Suggested Citation

  • Rubinstein, Alexander & Slutskin, Lev, 2018. "«Multiway data analysis» and the general problem of journals’ ranking," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 50, pages 90-113.
    • Handle: RePEc:ris:apltrx:0345
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    References listed on IDEAS

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    1. Rubinshtein, A., 2014. "On the Journal of the New Economic Association and other Economic Journals: Results of a Readers' Survey," Journal of the New Economic Association, New Economic Association, vol. 23(3), pages 175-187.
    2. J. Carroll & Jih-Jie Chang, 1970. "Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition," Psychometrika, Springer;The Psychometric Society, vol. 35(3), pages 283-319, September.
    3. E. Balatsky & N. Ekimova., 2015. "The Experience of Ranking Russian Economic Journals," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 8.
    4. Gangan Prathap, 2010. "The 100 most prolific economists using the p-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(1), pages 167-172, July.
    5. Volkova, O., 2016. "Do Visual Culture Revolutions Affect Accounting Practices?," Journal of the New Economic Association, New Economic Association, vol. 29(1), pages 54-82.
    6. Aleskerov, F. & Badgaeva, D. & Pislyakov, V. & Sterligov, I. & Shvydun, S., 2016. "An Importance of Russian and International Economic Journals: a Network Approach," Journal of the New Economic Association, New Economic Association, vol. 30(2), pages 193-205.
    7. Muravyev, Alexander A., 2011. "Economic science in Russia through the lens of publications of Russian economists in national and international journals over 2000-2009," Working Papers 828, Graduate School of Management, St. Petersburg State University.
    8. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    9. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    10. 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.
    11. Rubinstein, A., 2016. "Ranking of Russian Economic Journals: The Scientific Method or "Numbers Game"," Journal of the New Economic Association, New Economic Association, vol. 30(2), pages 162-175.
    12. Balatsky, E. & Yurevich, M., 2016. "The Misalignment of Russian Economists' Scientometric Indicators in RISC," Journal of the New Economic Association, New Economic Association, vol. 30(2), pages 176-180.
    13. Ledyard Tucker, 1966. "Some mathematical notes on three-mode factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 31(3), pages 279-311, September.
    14. A. Muravyev., 2013. "On Scientific Value of Russian Journals in Economics and Related Fields," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 4.
    15. Leibovici, Didier G., 2010. "Spatio-Temporal Multiway Data Decomposition Using Principal Tensor Analysis on k-Modes: The R Package PTAk," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 34(i10).
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    Cited by:

    1. Rubinstein, A. & Burakov, N., 2021. "Economic journals in the optics of scientometrics," Journal of the New Economic Association, New Economic Association, vol. 50(2), pages 205-215.
    2. Rubinstein, A., 2019. "Man shall not live by RSCI alone..," Journal of the New Economic Association, New Economic Association, vol. 44(4), pages 245-259.
    3. Nikita Alexandrovich Burakov & Alexander Yakovlevich Rubinstein, 2020. "Theoretical and Applied Aspects of Measuring the Economic Growth Potential of Russian Regions," Spatial Economics=Prostranstvennaya Ekonomika, Economic Research Institute, Far Eastern Branch, Russian Academy of Sciences (Khabarovsk, Russia), issue 1, pages 24-50.

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    More about this item

    Keywords

    ranking; rating; weights of indicators; aggregation of weights; principal component analysis; Tucker decomposition; multiway data analysis;
    All these keywords.

    JEL classification:

    • A11 - General Economics and Teaching - - General Economics - - - Role of Economics; Role of Economists
    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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