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Computational Analysis of Firms' Organization and Strategic Behaviour
Contributor(s): Mollona, Edoardo (Author)
ISBN: 1138879479     ISBN-13: 9781138879478
Publisher: Routledge
OUR PRICE:   $65.50  
Product Type: Paperback - Other Formats
Published: April 2015
Qty:
Additional Information
BISAC Categories:
- Business & Economics | Organizational Behavior
- Business & Economics | Negotiating
- Business & Economics | Strategic Planning
Dewey: 302.350
Series: Routledge Research in Strategic Management
Physical Information: 0.72" H x 5.98" W x 9.02" (1.03 lbs) 328 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

This book addresses possible applications of computer simulation to theory building in management and organizational theory. The key hypothesis is that modelling and computer simulation provide an environment to develop, test and articulate theoretical propositions. In general, computer simulation provides an experimental environment where researchers are able to play with symbolic representations of phenomena by modifying the model's structure and activating or deactivating model's parameters. This environment allows to both generating hypotheses to ex post explain observed phenomena or to ex ante generate distributions of unrealized events thereby envisioning areas for further empirical investigations.

Under a methodological perspective, the volume investigates logics and techniques to design a research strategy grounded on computer simulation. In particular, the articles in the book concentrate on two different techniques, and philosophies, to set up a simulation study: System Dynamics, which is grounded on differential equations and feedback theory, and agent-based modeling. The book describes how computer simulation helps to look into research issues typical to strategic management and organizational theory. In this respect, such themes as firms' diversification strategies, competitive strategy, rivalry and the impact of role dynamics on organizational performances are explored through the lenses of computer simulation models.