John E. Taylor, Raymond Levitt and Andrei Villarroel recently won the Best Paper Award at the North American Association for Computational Social and Organizational Sciences (NAACSOS) Annual Conference held at Notre Dame University on 22-23 June 2006.

The authors developed a computational simulation model to extend and enhance current theoretical understandings for learning in interorganizational networks.

The paper title, authors and abstract are as follows:

"Simulating Learning in Interorganizational Networks: The Insidious Role of Task Interdependence and Relational Instability on System-level Learning"

Author: John E. Taylor; HEC Lausanne.
Author: Raymond Levitt; Stanford University.
Author: Andrei Villarroel; HEC Lausanne & EPFL.

Abstract :

In this paper we develop a multi-agent simulation model to explore the issue of learning in interorganizational networks. Though interorganizational network researchers generally agree that when firms form into networks they will gain access to new knowledge, the question of learning beyond the firm at the boundaries between firms or at the level of the network itself remain less explored. We simulate the impact of task interdependence and relational instability on learning in interorganizational networks comprised of multiple disparate specialist firms. We find that relational instability in networks slows learning and that task interdependence moderates the impact of increasing relational instability on network productivity rates. The findings have significant implications for interorganizational network theory. Furthermore, the simulation results provide insights into appropriate firm and network strategies for change.

Keywords: Interorganizational Networks, Interorganizational Learning, Simulation, Task Interdependence, Relational Instability, Innovation, Organizational Change

Read full paper here.

Posted by rjorr at June 26, 2006 9:57 AM