Handbook of Research Methods on Trust
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Handbook of Research Methods on Trust

Second Edition

Edited by Fergus Lyon, Guido Möllering and Mark N.K. Saunders

With the growing interest in trust in the social sciences, this second edition of the Handbook of Research Methods on Trust provides a fully updated and extended account of quantitative, qualitative and mixed methods for empirical research. While many researchers have already drawn inspiration and insight from the previous edition, the dynamic development of trust research calls for further and deeper engagement with methodological issues, particular methods, practical research experience, and current challenges and innovations as offered by this new edition.
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Chapter 5: Agent-based simulation of trust

Bart Nooteboom


Agent-based simulation is useful for exploring possible worlds, seeing what might happen under what conditions as a result of complex interaction between agents, as in the building and breaking of trust. A survey of some attempts is given, and a specific case is summarized. Shortcomings and problems are also indicated. With a variety of associates I had done a number of statistical/econometric studies of trust (Noorderhaven et al., 1998; Nooteboom et al., 1997, 2000) but when you find statistical associations between antecedents and outcomes of trust this does not tell you how trust processes work. So with other associates I turned to case studies (Klein Woolthuis et al., 2005), studying the development of trust over time, but this still does not trace how interactions produce the trust outcomes you find. Therefore with yet other associates I turned to agent-based simulation. Trust is an interactive phenomenon. People adjust their trust or distrust in others on the basis of observed actions and their interpretation. This becomes especially complex when there are multiple agents. In such complex interaction there may arise virtuous cycles of trust-building and vicious cycles of collapse. A natural method for investigating this is that of agent-based simulation, in which interaction is explicitly modelled. With this method one can study emergent properties that would be hard or impossible to tackle analytically.

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