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FuzzEA: A fuzzy logic approach to efficiency analysis

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Abstract

We apply fuzzy logic to measure the efficiency of a unit that consumes multiple inputs to produce multiple outputs. We demonstrate how the fuzzy inference process produces an efficiency profile of a producing unit, which can serve as the output of the analysis or which can be "defuzzified" to produce a specific efficiency score. The approach, which we call FuzzEA for Fuzzy Efficiency Analysis, allows the analyst to measure the efficiency of an individual unit without collecting detailed data for all comparable units. The approach allows the analyst, in conjunction with the context expert, to incorporate industry-specific experiential knowledge concerning relevant ratios of inputs and outputs, information often known as benchmarks, or "rules of thumb." Therefore, the analyst may prefer the FuzzEA approach when detailed data on all producing units are either unavailable or cumbersome to collect, or when the analyst requires efficiency results for only one or a small number of units. Finally, context experts may find the results more acceptable because the methodology explicitly incorporates expert experience. We demonstrate the FuzzEA methodology in the context of Major League Baseball teams.

Original languageEnglish
Pages (from-to)182-192
Number of pages11
JournalINFOR
Volume49
Issue number3
DOIs
StatePublished - Aug 1 2011

Keywords

  • efficiency analysis
  • expert systems
  • Fuzzy inference systems
  • Major League Baseball
  • productivity

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