Richetin, Juliette and Sengupta, Abhijit and Perugini, Marco and Adjali, Iqbal and Hurling, Robert and Greetham, Danica and Spence, Michael (2010) A micro-level simulation for the prediction of intention and behavior. Cognitive Systems Research, 11 (2). pp. 181-193. DOI https://doi.org/10.1016/j.cogsys.2009.08.001
Richetin, Juliette and Sengupta, Abhijit and Perugini, Marco and Adjali, Iqbal and Hurling, Robert and Greetham, Danica and Spence, Michael (2010) A micro-level simulation for the prediction of intention and behavior. Cognitive Systems Research, 11 (2). pp. 181-193. DOI https://doi.org/10.1016/j.cogsys.2009.08.001
Richetin, Juliette and Sengupta, Abhijit and Perugini, Marco and Adjali, Iqbal and Hurling, Robert and Greetham, Danica and Spence, Michael (2010) A micro-level simulation for the prediction of intention and behavior. Cognitive Systems Research, 11 (2). pp. 181-193. DOI https://doi.org/10.1016/j.cogsys.2009.08.001
Abstract
In this contribution we aim at anchoring Agent-Based Modeling (ABM) simulations in actual models of human psychology. More specifically, we apply unidirectional ABM to social psychological models using low level agents (i.e., intra-individual) to examine whether they generate better predictions, in comparison to standard statistical approaches, concerning the intentions of performing a behavior and the behavior. Moreover, this contribution tests to what extent the predictive validity of models of attitude such as the Theory of Planned Behavior (TPB) or Model of Goal-directed Behavior (MGB) depends on the assumption that peoples' decisions and actions are purely rational. Simulations were therefore run by considering different deviations from rationality of the agents with a trembling hand method. Two data sets concerning respectively the consumption of soft drinks and physical activity were used. Three key findings emerged from the simulations. First, compared to standard statistical approach the agent-based simulation generally improves the prediction of behavior from intention. Second, the improvement in prediction is inversely proportional to the complexity of the underlying theoretical model. Finally, the introduction of varying degrees of deviation from rationality in agents' behavior can lead to an improvement in the goodness of fit of the simulations. By demonstrating the potential of ABM as a complementary perspective to evaluating social psychological models, this contribution underlines the necessity of better defining agents in terms of psychological processes before examining higher levels such as the interactions between individuals. © 2009 Elsevier B.V.
Item Type: | Article |
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Uncontrolled Keywords: | ABM; Models of attitude; Prediction of behavior; Rational decision making |
Subjects: | B Philosophy. Psychology. Religion > BF Psychology H Social Sciences > H Social Sciences (General) |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Essex Business School |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 26 Nov 2012 15:22 |
Last Modified: | 16 May 2024 17:26 |
URI: | http://repository.essex.ac.uk/id/eprint/4368 |