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Processing and Analysing Experimental Data Using a Tensor-Based Method: Evidence from an Ultimatum Game Study

Chapter
Publication Date:
2018
abstract:
This work investigates how newer economic behavioural research can be applied to human group behaviour and how it can be enriched using a relatively novel knowledge discovery approach. Based on an ultimatum game study conducted in the context of an extra-lab experiment, the authors propose a tensorbased method to analyse their experimental results and, therefore, to address a multi-dimensional approach. The authors prove that subjects do not behave as game theory would predict, but rather they basically prefer fair divisions of gains. This evidence confirms significant implications for theories addressing the evolution of, and the mechanisms underpinning, human group behaviour in economics, cognitive, and organizational studies.
Iris type:
2.1 Contributo in volume (Capitolo o Saggio)
Keywords:
Economic behavioural research - Experimental economics - Knowledge discovery in databases - Tensor-based analysis - Fairness preferences
List of contributors:
Bucciarelli, Edgardo; Persico, Tony E.
Authors of the University:
BUCCIARELLI EDGARDO
PERSICO TONY ERNESTO
Handle:
https://ricerca.unich.it/handle/11564/690903
Book title:
Decision Economics - In the Tradition of Herbert A. Simon’s Heritage
  • Overview

Overview

URL

https://link.springer.com/chapter/10.1007/978-3-319-60882-2_15
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