Marketing Applications of Sequencing and Partitioning of Nonsymmetric and/or Two-Mode Matrices

  • P. Arabie
  • S. Schleutermann
  • J. Daws
  • L. Hubert


Although various authors have provided improvements to the bond energy algorithm for seriation originally proposed by McCormick, Schweitzer, and White (1972), most of these approaches have limited the types of data that can be considered (e.g., by assuming only binary input). We return to the original algorithm, free of such restrictions, and demonstrate ways of markedly improving its computational efficiency as well as the solutions it produces. These improvements enable the algorithm to sequence survey data (e.g., respondents by products’ attributes) having several hundred columns and rows. Such runs require only a few hours on a personal computer. Following the successful sequencing of such matrices, it is straightforward to partition the rows and columns. We present a substantive application from marketing.


Soft Drink Brand Loyalty Brand Relationship Column Mode Proximity Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin · Heidelberg 1988

Authors and Affiliations

  • P. Arabie
    • 1
  • S. Schleutermann
    • 2
  • J. Daws
    • 2
  • L. Hubert
    • 2
  1. 1.Department of Computer ScienceUniversity College DublinUSA
  2. 2.Department of PsychologyUniversity of Illinois at ChampaignChampaignUSA

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