Agent-Based Simulation of Effectual and Causal Behaviors of Entrepreneurs

The IMP Boost project "Overcoming Barriers in the Innovation Process" investigates a new approach to explain the success or failure of entrepreneurs. At the centre of interest is the notion of "effectuation" (http://www.effectuation.org) [1, 2]. This denotes a fundamentally different way to act in comparison to traditional approaches in economics, now denoted by "causation".
A "causal" entrepreneur starts by carrying out comprehensive (and rather expensive) market studies to clearly identify a dedicated market opportunity. This is then settled as a goal and the entrepreneur only decides between different alternatives in regard to their utility to achieve the settled goal.
In contrast to this an "effectual" entrepreneur is not committed to a particular product or goal, but only to the desire to run an enterprise. Instead of carrying out expensive market studies (s)he choose between alternatives in regard to the resulting opportunities and under consideration of the "affordable loss", this is how much money (s)he can loose without harming her/his capacity to act. A major means of an "effectual" actor is to utilize her/his knowledge and network to find cooperation partners. These can be potential customers as well as money donators. Very much in contrast to the "causal" approach these strategic partners can have a great influence on the actual product or goal to be achieved. This is the "effectual" entrepreneur simply adapts the goal to the partner's needs, including the chance to build a completely different product. The reward to this flexibility is a definite commitment of the partner to become a part of the new venture. Thus, the two approaches differ considerably in regard to how they address uncertainty. While the "causation" approach employs prediction to reduce uncertainty, "effectuation" controls the unknown future by taking decisions, this is explicitly deciding which way to go.
The aim of the IMP Boost project is to compare these two approaches by running simulations. Based on theoretical research neither of these two approaches is to be favored in general. Accordingly, we need to identify the settings, conditions, and constraints that put either of these approaches in front. From first modeling experiences and basic considerations, agent-based approaches [3] towards simulation seem to be well suited. The topic of this thesis is thus to investigate various agent-based simulation environments in regard to their suitability for the problem and afterwards to set up a framework that allows to run such simulations. Furthermore, simulation analysis means need to be researched as well. Due to the high importance of networking, approaches from social network analysis [4] as well as actor-network theory [5] are likely to be connected to the simulation environment. The work requires a tight collaboration with our partners from the economics since the models to characterize "effectual" and "causal" behavior are set up in parallel.

Literature

1. Sarasvathy, S. D. (2001): Causation and effectuation: Toward a theoretical shift from economic inevitability to entrepreneurial contingency, in: Academy of Management Review, 26 (2), 243-264
2. Saras D. Sarasvathy, Nicholas Dew (2005): New market creation through transformation. Journal of Evolutionary Economics. Heidelberg: Nov 2005. Vol. 15, Iss. 5; p. 533
3. G. Weiss (2000): Multiagent Systems. MIT Press.
4. U. Brandes, T. Erlebach (2005): Network Analysis. Methodological Foundations. Springer, LNCS 3418.
5. Law, J. (1992): Notes on the theory of actor-network: Ordering, strategy and heterogeneity, in: Systems Practice, 5 (4), 379 - 393.