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A Dynamic Simulation Comparing Classical and Emergent-Network Models: Organizational Design Implications

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Abstract

In the last decade, organizations have spent more on the creation, transformation, and communication of information than on the production of physical goods. The information age has been ushered in by the widespread assimilation of information and communication technologies. Many contemporary practitioners and organizational theorists predict the demise of the classical organizational design because of its inability to accommodate the sociological change engendered by the information age.

The current study advances an emergent-network model of organizational design and compares it to the classical approach through a dynamic simulation of prototypical organizational activities. Organizational activities approximating one year were simulated in each of five organizations under constant baseline conditions and over one hundred experimental design conditions. The emergent network model manifested higher levels of goal attainment, resource utilization, and organizational capacity for accommodating change. These findings suggest that organizations will benefit from conformance to the design principals of the emergent-network model.

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Authors and Affiliations

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Correspondence to H. Roland Weistroffer.

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Bernard D. Hill Jr. earned his Ph.D. in Public Policy and Administration from Virginia Commonwealth University. He also holds a Master of Science in Business and a Bachelor of Science in Education. Bernard is currently employed as a Chief Information Officer with the Commonwealth of Virginia. He has held a broad array of technology leadership positions in both the public and private sectors and the academic arena. Bernard was selected as one of Computerworld’s Premier 100 IT Leaders for 2002. As CIO for the Virginia Department of Transportation, he also brokered a public-private partnership that won a nationwide Government Technology Leadership Award. This partnership provides security awareness training for employees in Virginia State government, as well as cities, counties, and localities throughout Virginia.

Heinz Roland Weistroffer is an Associate Professor of Information Systems in the School of Business at Virginia Commonwealth University. Roland holds a Doctor of Science degree from the Free University Berlin, Germany, and a Master of Arts degree from Duke University. Previous appointments include Chief Research Officer at the Council for Scientific and Industrial Research in Pretoria, South Africa, and Senior Lecturer at the University of Natal in Durban, South Africa. Roland’s current research interests include computer assisted decision support, computer simulation modeling, object oriented modeling, and software engineering. He has published in IEEE Transactions on Software Engineering, IEEE Transactions on Systems, Man and Cybernetics, the Journal of Multi-Criteria Decision Analysis, and Socio-Economic Planning Sciences, among other journals.

Peter Aiken is Director of the Institute for Data Research and an Associate Professor of Information Systems at Virginia Commonwealth University. His research has widely explored the area of data engineering and its relationship to systems and business reengineering. He is the author of Data Reverse Engineering and Clive Finkelstein’s co-author of Corporate Information Portals (McGraw-Hill 1996/99). His sixth book is titled XML in Data Management and is co-authored with David Allen. He has held leadership positions with the US Department of Defense and consulted with more than 50 organizations in 14 different counties. His research publications have appeared in the Communications of the ACM, IBM Systems Journal, IEEE Software and many others. He is a member of ACM, and the IEEE (Senior Member). He has been a DAMA International Advisor since 1999 and received their 2001 International Achievement Award. He has lectured internationally on these and related topics.

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Hill, B.D., Weistroffer, H.R. & Aiken, P.H. A Dynamic Simulation Comparing Classical and Emergent-Network Models: Organizational Design Implications. Comput Math Organiz Theor 11, 59–85 (2005). https://doi.org/10.1007/s10588-005-1727-1

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  • DOI: https://doi.org/10.1007/s10588-005-1727-1

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