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Preference-neutral attribute weights in the journal-ranking problem

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  • I Horowitz

    (University of Florida)

Abstract

A linear programming model is proposed for assigning linear attribute weights in the journal-ranking problem. The constraints in the model are derived solely from any quasi-dominance relations that can be established between the journals. The objective function of the model minimizes the maximum difference between the implied valuations for the pair of journals that define a constraint. In the sense that personal inputs are not introduced, the derived weights are preference neutral. The feasibility of the procedure is demonstrated for two sets of data. By considering various random samples of journals from the larger data set, it is shown that large differences can emerge in the attribute weights and in the journal rankings from different samples of journals, even when the sample sizes are large relative to the population size.

Suggested Citation

  • I Horowitz, 2003. "Preference-neutral attribute weights in the journal-ranking problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(5), pages 452-457, May.
    • Handle: RePEc:pal:jorsoc:v:54:y:2003:i:5:d:10.1057_palgrave.jors.2601531
    DOI: 10.1057/palgrave.jors.2601531
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    References listed on IDEAS

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    1. Minghe Sun & Antonie Stam & Ralph E. Steuer, 1996. "Solving Multiple Objective Programming Problems Using Feed-Forward Artificial Neural Networks: The Interactive FFANN Procedure," Management Science, INFORMS, vol. 42(6), pages 835-849, June.
    2. Murat Koksalan, M. & Taner, Orhan V., 1992. "An approach for finding the most preferred alternative in the presence of multiple criteria," European Journal of Operational Research, Elsevier, vol. 60(1), pages 52-60, July.
    3. A C B Tse, 2001. "Using mathematical programming to solve large ranking problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(10), pages 1144-1150, October.
    4. Caporaletti, L. E. & Dulá, J. H. & Womer, N. K., 1999. "Performance evaluation based on multiple attributes with nonparametric frontiers," Omega, Elsevier, vol. 27(6), pages 637-645, December.
    5. F. Hutton Barron & Bruce E. Barrett, 1996. "Decision Quality Using Ranked Attribute Weights," Management Science, INFORMS, vol. 42(11), pages 1515-1523, November.
    6. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
    7. Donohue, Joan M. & Fox, Jeremy B., 2000. "A multi-method evaluation of journals in the decision and management sciences by US academics," Omega, Elsevier, vol. 28(1), pages 17-36, February.
    8. Fischer, Ilan & Harvey, Nigel, 1999. "Combining forecasts: What information do judges need to outperform the simple average?," International Journal of Forecasting, Elsevier, vol. 15(3), pages 227-246, July.
    9. L C Dias & J N Clímaco, 2000. "Additive aggregation with variable interdependent parameters: the VIP analysis software," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(9), pages 1070-1082, September.
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    Cited by:

    1. Chiang Kao & Hsiou-Wei Lin & San-Lin Chung & Wei-Chi Tsai & Jyh-Shen Chiou & Yen-Liang Chen & Liang-Hsuan Chen & Shih-Chieh Fang & Hwei-Lan Pao, 2008. "Ranking Taiwanese management journals: A case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(1), pages 95-115, July.
    2. Domingo Docampo & Vicente Safón, 2021. "Journal ratings: a paper affiliation methodology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 8063-8090, September.
    3. Bruce A. Reinig & Ira Horowitz, 2018. "Using Mathematical Programming to Select and Seed Teams for the NCAA Tournament," Interfaces, INFORMS, vol. 48(3), pages 181-188, June.
    4. Ira Horowitz, 2004. "Aggregating Expert Ratings Using Preference-Neutral Weights: The Case of the College Football Polls," Interfaces, INFORMS, vol. 34(4), pages 314-320, August.

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