From the Special Issue Editors: Multi-agent Simulation as a Novel Decision Support Tool for Innovation and Technology Management

Organizations and markets can both be seen as complex systems whose aggregate dynamics cannot often be inferred from their micro building blocks [Faggini and Lux (2008)]. Different traditional modeling methods exist to support researchers to understand and predict the behavior of such complex systems. However, most of these models are developed under the assumption of a state of stability, equilibrium and linearity, whereas real world organizations and markets are dynamic, non-linear and complex. Furthermore, such traditional models are usually input-output models and therefore do not give insight into the process of getting to a state of equilibrium. Agent-Based Modeling and Simulation (ABM/S), with its intrinsic multidisciplinary approach, is gaining increasing attention as a problem-solving tool in the social sciences (particularly in economics, business, finance, and politics) [Wilkinson et al. (2003)] as well as in Operations Research [Siebers et al. (2010)]. It is a bottom-up modeling approach where aggregate dynamics emerge from the interactions of constituent components and between components and the environment [Gilbert and Terna (2000)]. It provides a powerful tool to study the dynamics of equilibrium and non-equilibrium systems over time and its outputs offer the potential to be used for explanatory, exploratory and predictive purposes [Twomey and Cadman (2000)]. The development of ABM/S technology has been rapid in recent years; however real world ABM/S applications found in innovation and technology management are rare (as indicated by the long time it took to put together this special issue). This is despite the recognition of the usefulness of simulation as a decision support tool for business analysts and managers [Garcia and Jager (2011)]. We believe that the transfer of knowledge, concepts, frameworks, and technologies between disciplines (i.e. between theoretical and applied sciences) represents the main barriers for ABM/S. This special issue aims to fill the gap that exists in the literature for describing how newly developed formal approaches can be utilized by practitioners from different fields.