Analysis of Consumer Behavior on Technological Products: An Agent-Based Modeling Approach

Consumer purchasing decision making has been of great interest to researchers and practitioners for improving strategic marketing policies and gaining a competitive advantage in the market. Traditional market models do not comprehend the inner psychological process of consumer purchase decision and generally concentrate on single individuals rather than taking social interactions into account. In addition individuals are tied to one another with invisible bonds and the influence an individual receives from another is known to be word-of-mouth (WOM) effect. Some people have larger influence on other individuals and they are assumed to be opinion leaders. A new evolving modeling approach, agent-based modeling is capable of comprehending individual preferences and motivations and it is suitable for imitating social interactions among the consumer network. In this paper we aim to build an agent-based simulation model for a technological product in an artificial market. The model assesses the efficiency and profitability of different targeting strategies comprised of four factors; price, promotion, product quality characteristics and number of opinion leaders to collaborate with. In the presence of WOM, product's quality is found to be the most significant factor for consumers to purchase and to disseminate the positive WOM. The other important factors are; level of promotion, change in price and change in number of opinion leaders to collaborate with.