![]() ( 2000) concluded that putting a column (a pillar) just before an emergency exit, slightly asymmetrically, about one meter away from the exit, helps to reduce the harmful consequences of irrational herding behavior in collective panic (e.g., when a fire breaks out in a crowded building). The effects of interactions occasionally make the observed emergent phenomena in complex systems difficult to understand and might lead to counterintuitive findings. The outcome of these systems emerges through the large number of interactions among a system’s entities and of these entities with their environment, forming loops of recirculating signals and feedback (Holland 1998, 2014 Miller and 9). 2013 a great source of material on complexity science is the Santa Fe Institute 2020). Thus, a consumer market is a prime example of a complex system for which both micro-level analysis (i.e., a consumer’s adoption of an innovation) and macro-level analysis (i.e., the overall pattern of innovation diffusion) are of interest.Ĭomplex systems are inherently intricate, typically involve stochastic elements, may show chaotic behavior, and are predisposed to unexpected and emergent outcomes (Foote 2007 for a discussion on the characterization of complex systems, see Ladyman et al. While the first two abovementioned issues (i.e., cost and single opportunity) “merely” increase the pressure on decision-makers, the main difficulty lies in appropriately predicting market behavior arising from the heterogeneity of stakeholders in the market (with respect to their individual characteristics, attitudes toward a product’s attributes, needs, objectives, etc.) and their interactions with each other. ![]() Therefore, a better understanding of market behavior is a major concern for innovation management. Third, it is difficult to predict the course of launching a new product into a consumer market because market stakeholders-such as consumers, distributors, and competitors-are not homogenous but rather diverse, and their behavior is influenced by the actions and reactions of others. Second, there is only a single opportunity to “get it right” in the important initial phase of market penetration, in which a successful takeoff can set up a wave of contagious consumption in consumer markets, this takeoff often determines whether the innovation survives in the market (Delre et al. First, market introduction of innovations is usually costly and failure can result in forfeiture of extensive investments in the development of the new product. In doing so, managers face several challenges. It aims to encourage researchers in the field of innovation management, as well as practitioners, to consider agent-based modeling and simulation as a method for gaining deeper insights into market behavior and making better-informed decisions.īringing new products to market on a regular basis is a necessity for the long-term survival of a company. This paper provides an overview of the strengths and criticisms of such tools. ![]() Agent-based modeling, a relatively novel approach to understanding complex systems, is well equipped to deal with this complexity and, therefore, may serve as a valuable tool for both researchers studying particular market effects and practitioners seeking decision support for determining features of products under development or the appropriate combination of measures to accelerate product diffusion in a market. Thus, a typical consumer market constitutes a complex system whose behavior is difficult to foresee because stochastic impulses may give rise to complex emergent patterns of system reactions over time. ![]() These actors may also interact with others in various ways (e.g., through word of mouth or social influence). Market diffusion of new products is driven by the actions and reactions of consumers, distributors, competitors, and other stakeholders, all of whom can be heterogeneous in their individual characteristics, attitudes, needs, and objectives.
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