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Introduction to Multi-attribute Decision Making in Business Analytics

In: Advanced Business Analytics

Author

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  • William P. Fox

    (Naval Postgraduate School)

Abstract

Multi-attribute decision making (MADM) is commonly used when we are comparing more than two courses of actions or alternatives based upon many selected criteria. In this chapter, we present methodologies to conduct MADM analysis. These methodologies include data envelopment analysis (DEA), simple additive weighting (SAW), analytical hierarchy process (AHP), and the technique of order preference by similarity to ideal solution (TOPSIS). We describe each methodology, provide some strengths and limitations of each, discuss tips for sensitivity analysis, and provide two examples to illustrate each method. Additionally, we provide a carry-through example based upon social network analysis so that we can compare these methods.

Suggested Citation

  • William P. Fox, 2015. "Introduction to Multi-attribute Decision Making in Business Analytics," Springer Books, in: Fausto Pedro García Márquez & Benjamin Lev (ed.), Advanced Business Analytics, edition 127, pages 55-91, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-11415-6_4
    DOI: 10.1007/978-3-319-11415-6_4
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    Cited by:

    1. W. P. Fox & J. Hansberger, 2018. "Methodology for targeting analysis for minimal response," The Journal of Defense Modeling and Simulation, , vol. 15(3), pages 323-336, July.
    2. SHI, Jia & LEE, Ching-Hung & GUO, Xuesong & ZHU, Zhengwei, 2020. "Constructing an integrated stakeholder-based participatory policy evaluation model for urban traffic restriction," Technological Forecasting and Social Change, Elsevier, vol. 151(C).

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