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Effects of Combined Human Decision-Making Biases on Organizational Performance

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Multi-Agent-Based Simulation XIII (MABS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7838))

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As extensive experimental research has shown individuals suffer from diverse biases in decision-making. In our paper we analyze the effects of decision-making biases of managers in collaborative decision processes on organizational performance. The analysis employs an agent-based simulation model which is based on the NK model. In the simulations, managerial decisions which are based on different levels of organizational complexity and different incentive systems suffer from biases known from descriptive decision theory. The results illustrate how biases in combination with each other and in different organizational contexts affect organizational performance. We find that, contrary to intuition, some combinations of biases significantly improve organizational performance while these biases negatively affect organizational performance when they occur separately. This might evoke considerations whether decision-making should be as rational as possible.

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Berlinger, S., Wall, F. (2013). Effects of Combined Human Decision-Making Biases on Organizational Performance. In: Giardini, F., Amblard, F. (eds) Multi-Agent-Based Simulation XIII. MABS 2012. Lecture Notes in Computer Science(), vol 7838. Springer, Berlin, Heidelberg.

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  • Print ISBN: 978-3-642-38858-3

  • Online ISBN: 978-3-642-38859-0

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