Agent-based modeling of consumer decision making process based on power distance and personality Omid Roozmand a,⇑ , Nasser Ghasem-Aghaee a,e , Gert Jan Hofstede b,c,1 , Mohammad Ali Nematbakhsh a , Ahmad Baraani a , Tim Verwaart d,2 a Department of Computer Engineering, Faculty of Engineering, University of Isfahan, Iran b Wageningen University, Hollandseweg 1, 6706 KN Wageningen, Netherlands c Delft University of Technology, Mekelweg 4, 2628 CD Delft, Netherlands d LEI Wageningen UR, Postbus 29703, 2502 LS Den Haag, Netherlands e Department of computer Engineering, Sheikh-Bahaei University, Isfahan, Iran article info Article history: Received 31 January 2011 Received in revised form 29 April 2011 Accepted 2 May 2011 Available online 6 May 2011 Keywords: Agent-based simulation Consumer behavior Culture and personality modeling Human needs Cognitive modeling abstract Simulating consumer decision making processes involves different disciplines such as: sociology, social psychology, marketing, and computer science. In this paper, we propose an agent-based conceptual and computational model of consumer decision-making based on culture, personality and human needs. It serves as a model for individual behavior in models that investigate system-level resulting behavior. Theoretical concepts operationalized in the model are the Power Distance dimension of Hofstede’s model of national culture; Extroversion, Agreeableness and Openness of Costa and McCrae’s five-factor model of personality, and social status and social responsibility needs. These factors are used to formulate the util- ity function, process and update the agent state, need recognition and action estimation modules of the consumer decision process. The model was validated against data on culture, personality, wealth and car purchasing from eleven European countries. It produces believable results for the differences of consumer purchasing across eleven European countries. Ó 2011 Elsevier B.V. All rights reserved. 1. Introduction Agent-based modeling is a new analytical and computational method envisaged as important in many fields of study that have multi-level system properties, since it gives a better understanding of micro processes and their emergent consequences at macro le- vel [18,49]. This applied method must create a simplified represen- tation of what occurs in reality so that each agent plays the role of an individual as if it is happening in social reality. Agent-based modeling is a new way of analyzing of dynamic complex systems [18]. Hence, it is used in consumer behavior modeling to give a bet- ter understanding of, as well as predicting, the consumer decision making processes [18,97]. The consumers are represented as autonomous agents with individual characteristics as well as an independent internal decision making process [18], and sellers as agents who enter their products with different characteristics into the market. Consumer decision making involves research in the fields of sociology, psychology, consumer behavior and marketing, com- puter science and artificial intelligence which is related to the re- search of the computational modeling of complex social systems [97]. Modeling this behavior in an agent-based simulation requires a pragmatic integration of findings from all these fields. What is of prime importance for the scientists today is the presentation of a computational agent-based model for the consumers’ decision making processes which is the closest to the real consumer’s deci- sion. Hence, what can be of help to researchers is taking human factors influencing consumer behaviors into account. Consumer behavior includes five important stages: need recog- nition, information search, evaluation of alternatives, purchase, and post purchase behaviors [7,9,18,47,62,75,83]. The consumer decision making process starts with the recognition of a need. The main factor here is ‘need’. According the nature of the present study, we use the definition given by Max-Neef [55] who defines a need as an ‘underlying internal forces that drive our actions’. Other important concepts in this stage include actual state, desired state and tolerance threshold of each need for the consumer. Actual state refers to the extent of the consumer’s present satisfaction with the product he (or she, but for simplicity’s sake we shall use ‘he’) pos- sesses. The desired state is the consumer’s desired satisfaction. A need is felt by a consumer only when the discrepancy between 0950-7051/$ - see front matter Ó 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.knosys.2011.05.001 ⇑ Corresponding author. Tel.: +98 9133295459. E-mail addresses: roozmand@eng.ui.ac.ir (O. Roozmand), aghaee@eng.ui.ac.ir (N. Ghasem-Aghaee), gertjan.hofstede@wur.nl (G.J. Hofstede), nematbakhsh@eng. ui.ac.ir (M.A. Nematbakhsh), ahmadb@eng.ui.ac.ir (A. Baraani), tim.verwaart @wur.nl (T. Verwaart). 1 Tel.: +31 317484630. 2 Tel.: +31 703358114. Knowledge-Based Systems 24 (2011) 1075–1095 Contents lists available at ScienceDirect Knowledge-Based Systems journal homepage: www.elsevier.com/locate/knosys