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Introduction to Multi-attribute Decision Making in Business Analytics

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Advanced Business Analytics

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.

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Acknowledgements

We thank all the reviewers of this and other material used to produce this chapter. These views are the views of the author and not of the Department of Defense, the Department of the Navy, or the Naval Postgraduate School.

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Authors and Affiliations

  1. Naval Postgraduate School, Monterey, CA, USA

    William P. Fox

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  1. William P. Fox
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Correspondence to William P. Fox .

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Editors and Affiliations

  1. ETSI Industriales de Ciudad Real, University of Castilla-La Mancha, Ciudad Real, Spain

    Fausto Pedro García Márquez

  2. Decision Sciences Department, LeBow College of Business, Drexel University, Philadelphia, Pennsylvania, USA

    Benjamin Lev

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Fox, W.P. (2015). Introduction to Multi-attribute Decision Making in Business Analytics. In: García Márquez, F., Lev, B. (eds) Advanced Business Analytics. Springer, Cham. https://doi.org/10.1007/978-3-319-11415-6_4

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