The Performance-Variability Paradox: Optimizing

  • Stephen J. Guastello
  • Katherine Reiter
  • Anton Shircel
  • Paul Timm
  • Matthew Malon
  • Megan Fabisch
Part of the Evolutionary Economics and Social Complexity Science book series (EESCS, volume 13)


The study presented in this chapter examined the relationship between performance variability and actual performance of financial decision makers who were working under experimental conditions of increasing workload and fatigue. The rescaled range statistic, also known as the Hurst exponent (H) was used as an index of variability. Although H is defined as having a range between 0 and 1, 45 % of the 172 time series generated by undergraduates were negative. Participants in the study chose the optimum investment out of sets of 3–5 options that were presented a series of 350 displays. The sets of options varied in both the complexity of the options and number of options under simultaneous consideration. Depending on experimental condition, participants to make their choices within 15 s or 7.5 s. Results showed that (a) negative H was possible and not a result of psychometric error; (b) negative H was associated with negative autocorrelations in a time series. (c) H was the best predictor of performance of the variables studied; (d) three other significant predictors were scores on an anagrams test and ratings of physical demands and performance demands; (e) persistence as evidenced by the autocorrelations was associated with ratings of greater time pressure. Furthermore, persistence and overall performance were correlated, “healthy” variability only exists within a limited range, and other individual differences related to ability and resistance to stress or fatigue are also involved in the prediction of performance.


Task Switching Hurst Exponent Divergent Thinking Performance Variability Economic Time Series 
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 Japan 2016

Authors and Affiliations

  • Stephen J. Guastello
    • 1
  • Katherine Reiter
    • 1
  • Anton Shircel
    • 2
  • Paul Timm
    • 3
  • Matthew Malon
    • 4
  • Megan Fabisch
    • 5
  1. 1.Marquette UniversityMilwaukeeUSA
  2. 2.Kohler CorporationSheboyganUSA
  3. 3.Mayo ClinicRochesterUSA
  4. 4.Mount Mary UniversityMilwaukeeUSA
  5. 5.Illinois College of OptometryChicagoUSA

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