A Simulation-Based Approach to Understanding the Wisdom of Crowds Phenomenon in Aggregating Expert Judgment

Patrick Afflerbach (), Christopher Dun (), Henner Gimpel (), Dominik Parak () and Johannes Seyfried ()
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Patrick Afflerbach: University of Augsburg
Christopher Dun: University of Bayreuth
Henner Gimpel: University of Augsburg
Dominik Parak: University of Augsburg
Johannes Seyfried: University of Augsburg

Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, 2021, vol. 63, issue 4, No 2, 329-348

Abstract: Abstract Research has shown that aggregation of independent expert judgments significantly improves the quality of forecasts as compared to individual expert forecasts. This “wisdom of crowds” (WOC) has sparked substantial interest. However, previous studies on strengths and weaknesses of aggregation algorithms have been restricted by limited empirical data and analytical complexity. Based on a comprehensive analysis of existing knowledge on WOC and aggregation algorithms, this paper describes the design and implementation of a static stochastic simulation model to emulate WOC scenarios with a wide range of parameters. The model has been thoroughly evaluated: the assumptions are validated against propositions derived from literature, and the model has a computational representation. The applicability of the model is demonstrated by investigating aggregation algorithm behavior on a detailed level, by assessing aggregation algorithm performance, and by exploring previously undiscovered suppositions on WOC. The simulation model helps expand the understanding of WOC, where previous research was restricted. Additionally, it gives directions for developing aggregation algorithms and contributes to a general understanding of the WOC phenomenon.

Keywords: Simulation; Forecasting; Expert judgment; Expert aggregation; Wisdom of crowds (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s12599-020-00664-x

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