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Journal Ratings and Their Consensus Ranking

In: Operations Research Proceedings 2008

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  • Stefan Theussl

    (Dep. of Statistics and Mathematics)

  • Kurt Hornik

    (Dep. of Statistics and Mathematics)

Abstract

Summary In this paper we explore the possibility of deriving consensus rankings by solving consensus optimization problems, characterizing consensus rankings as suitable complete order relations minimizing the average Kemeny-Snell distance to the individual rankings. This optimization problem can be expressed as a binary programming (BP) problem which can typically be solved reasonably efficiently. The underlying theory is discussed in Sect. 1. Applications of the proposed method given in Sect. 2 include a comparison to other mathematical programming (MP) approaches using the data set of Tse [9] and establishing a consensus ranking of marketing journals identified by domain experts from a subset of the Harzing journal quality list [2]. In Sect. 3 we discuss computational details and present the results of a benchmark experiment comparing the performance of the commercial solver CPLEX to three open source mixed integer linear programming (MILP) solvers

Suggested Citation

  • Stefan Theussl & Kurt Hornik, 2009. "Journal Ratings and Their Consensus Ranking," Springer Books, in: Bernhard Fleischmann & Karl-Heinz Borgwardt & Robert Klein & Axel Tuma (ed.), Operations Research Proceedings 2008, chapter 65, pages 401-406, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-00142-0_65
    DOI: 10.1007/978-3-642-00142-0_65
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