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A Balance Model for Evaluating Subsets of Multiattributed Items

Author

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  • Peter H. Farquhar

    (Northwestern University)

  • Vithala R. Rao

    (Cornell University)

Abstract

There are numerous situations in management and elsewhere in which an individual decision maker chooses subsets of multiattributed items. The specification of a measure of goodness for selecting subsets may differ from one situation to the next. In this paper, a model is developed for evaluating subsets where the choice criterion is one of balance among the attributes of items in the subset chosen. A method for determining the parameters of the model from a small number of judgments on subsets using linear programming is discussed. The model is applied to the problem of evaluating subsets of television shows and of choosing the most balanced subset of shows. Several extensions of the model and potential applications are also given.

Suggested Citation

  • Peter H. Farquhar & Vithala R. Rao, 1976. "A Balance Model for Evaluating Subsets of Multiattributed Items," Management Science, INFORMS, vol. 22(5), pages 528-539, January.
    • Handle: RePEc:inm:ormnsc:v:22:y:1976:i:5:p:528-539
    DOI: 10.1287/mnsc.22.5.528
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    Cited by:

    1. Tetyana Kosyakova & Thomas Otter & Sanjog Misra & Christian Neuerburg, 2020. "Exact MCMC for Choices from Menus—Measuring Substitution and Complementarity Among Menu Items," Marketing Science, INFORMS, vol. 39(2), pages 427-447, March.
    2. Fishburn, Peter C. & LaValle, Irving H., 1996. "Binary interactions and subset choice," European Journal of Operational Research, Elsevier, vol. 92(1), pages 182-192, July.
    3. Koschmann, Anthony & Bowman, Douglas, 2018. "Evaluating marketplace synergies of ingredient brand alliances," International Journal of Research in Marketing, Elsevier, vol. 35(4), pages 575-590.
    4. Michaela Draganska & Dipak C. Jain, 2005. "Product‐Line Length as a Competitive Tool," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 14(1), pages 1-28, March.
    5. Peter C. Fishbur, 1992. "A general axiomatization of additive measurement with applications," Naval Research Logistics (NRL), John Wiley & Sons, vol. 39(6), pages 741-755, October.
    6. Kwak, Kyuseop & Duvvuri, Sri Devi & Russell, Gary J., 2015. "An Analysis of Assortment Choice in Grocery Retailing," Journal of Retailing, Elsevier, vol. 91(1), pages 19-33.
    7. Do-Hyung Park, 2019. "Virtuality Changes Consumer Preference: The Effect of Transaction Virtuality as Psychological Distance on Consumer Purchase Behavior," Sustainability, MDPI, vol. 11(23), pages 1-16, November.
    8. Lee, Jacob C. & Kim, Jungkeun & Kwak, Kyuseop, 2018. "A multi-attribute examination of consumer conformity in group-level ordering," Australasian marketing journal, Elsevier, vol. 26(1), pages 41-48.
    9. Karsu, Özlem & Morton, Alec, 2014. "Incorporating balance concerns in resource allocation decisions: A bi-criteria modelling approach," Omega, Elsevier, vol. 44(C), pages 70-82.
    10. Erica van Herpen & Rik Pieters, 2002. "The Variety of an Assortment: An Extension to the Attribute-Based Approach," Marketing Science, INFORMS, vol. 21(3), pages 331-341, June.
    11. P. K. Kannan & Barbara Kline Pope & Sanjay Jain, 2009. "—Pricing Digital Content Product Lines: A Model and Application for the National Academies Press," Marketing Science, INFORMS, vol. 28(4), pages 620-636, 07-08.
    12. Vithala R. Rao & Gary J. Russell & Hemant Bhargava & Alan Cooke & Tim Derdenger & Hwang Kim & Nanda Kumar & Irwin Levin & Yu Ma & Nitin Mehta & John Pracejus & R. Venkatesh, 2018. "Emerging Trends in Product Bundling: Investigating Consumer Choice and Firm Behavior," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 107-120, March.
    13. A. Ye(scedilla)im Orhun, 2009. "Optimal Product Line Design When Consumers Exhibit Choice Set-Dependent Preferences," Marketing Science, INFORMS, vol. 28(5), pages 868-886, 09-10.

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