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A micro-level simulation for the prediction of intention and behavior

Richetin, J., Sengupta, A., Perugini, M., Adjali, I., Hurling, R., Greetham, D., Spence, M. (2010) A micro-level simulation for the prediction of intention and behavior. Cognitive Systems Research, 11 (2). pp. 181-193. ISSN 1389-0417. (doi:10.1016/j.cogsys.2009.08.001) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:71503)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
https://dx.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.

Item Type: Article
DOI/Identification number: 10.1016/j.cogsys.2009.08.001
Uncontrolled keywords: Agent based simulation; Agent-based modeling; Data sets; Goal-directed behavior; Goodness of fit; Human psychology; Low level; Physical activity; Psychological model; Psychological process; Rational decision making; Soft drinks; Statistical approach; Theoretical models; Theory of planned behavior, Beverages; Decision making; Forecasting; Multi agent systems, Computer simulation, adult; agent based modelling; article; behavior control; cognition; controlled study; decision making; drinking behavior; female; human; human experiment; inhibition (psychology); intermethod comparison; male; mathematical model; physical activity; prediction; priority journal; reproducibility; social behavior; social psychology; theory validation
Subjects: H Social Sciences
H Social Sciences > H Social Sciences (General)
Divisions: Divisions > Kent Business School - Division > Kent Business School (do not use)
Depositing User: Abhijit Sengupta
Date Deposited: 03 Jan 2019 12:02 UTC
Last Modified: 16 Nov 2021 10:25 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/71503 (The current URI for this page, for reference purposes)

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