A highly connected world opens plenty of new possibilities. One rising phenomena is the “wisdom of the crowds” that can be efficiently used, since the web lowered cost of information collecting and the reaching of large groups. An application of this potential is for example group forecasting. Group forecasting can happen from relatively small numbers as in Delphi Studies to an extensive set of participants as in polls. However there exist a number of other methods, which advantages and disadvantages each. Methods as Prediction Markets generates sometimes impressively accurate results, but also recently perform only average or below. So it is to assume that not only the method, but also the context of the question, the presentation of the question and the question itself have influence on the outcome.
Aim of this thesis is to investigate which biases can affect the performance of group decision methods. Based on relevant literature a list of biases is to create and should be argued regarding their relevance for different group forecasting methods. The five most relevant biases should be in addition considered from a cognitive load perspective.
Language: English or German