An Empirically Derived Taxonomy of Information Technology Structure and Its Relationship to Organizational Structure

Abstract:

This study empirically develops a taxonomy that has implications for matching information technology (IT) and organizational structures. The taxonomy of IT structure is based on the degree of centralization of computer processing, capability to support communications, and the ability to share resources. By using a multistep cluster analysis, both the membership and number of groups are derived from the responses of 313 firms. Four IT structures are identified: centralized (centralized processing, low communication, low sharing), decentralized (decentralized processing, low communication, low sharing), centralized cooperative (centralized processing, high communication, high sharing), and distributed cooperative computing (decentralized processing, high communication, high sharing). Centralized computing is related to functional organizational forms with low integration and centralized decision making. Decentralized computing is related to product organizational forms with decentralized decision making. Centralized cooperative computing is related to functional organizational forms with high integration. Distributed cooperative computing is related to both matrix and product organizational forms with high integration. The ability to identify and understand the implications of IT structure is of critical importance to both academic and management practitioners.

Key Words and Phrases:

• information technology structure
• organizational decision-making structure
• organizational integration
• organizational structure
• taxonomy

Additional information

Notes on contributors

Kirk Dean Fiedler

Kirk Dean Fiedler is an Assistant Professor of MIS at the University of South Carolina, School of Business Administration. He received a B. A. from Wittenberg University and an M.B.A. and an M.S. in information systems and systems science from the University of Louisville, before completing his Ph.D. in MIS at the University of Pittsburgh. His work experience includes several years at Arthur Young & Company, and he has earned CPA certification. Currently, his research interests involve the investigation of technology assimilation and business process redesign. He has published this research in various journals, including MIS Quarterly, IEEE Transactions in Engineering Management, California Management Review, Long Range Planning, Journal of Information Technology, Omega, and European Journal of Information Systems. Dr. Fiedler was a finalist in the Decision Sciences Institute’s Instructional Innovation Award Competition. He is a member of the Academy of Management, AICPA, DSI, and AIS.

Varun Grover

Varun Grover is currently an Associate Professor of MIS in the Management Science Department at the University of South Carolina. He holds a B.Tech. in electrical engineering from the Indian Institute of Technology, an M.B.A. from Southern Illinois University, and a Ph.D. in MIS from the University of Pittsburgh. Dr. Grover has over sixty refereed papers published or forthcoming on organizational impacts of IT, reengineering, strategic information systems, and telecommunications, in journals such as Journal of Management Information Systems, MIS Quarterly, Decision Sciences, IEEE Transactions on Engineering Management, Data Base, Information and Management, Journal of Systems Management, California Management Review, Communications of the ACM, Long Range Planning, Journal of Information Systems, and Omega. Dr. Grover is the recipient of an Outstanding Achievement Award from the Decision Sciences Institute. He is also the recipient of the 1992 Alfred G. Smith Award for excellence in teaching. He is currently on the Editorial Boards of four journals and an active referee for twelve more. He recently coedited a book called Business Process Change: Reengineering Concepts, Methods and Technologies. He is a member of DSI, AIS, and TIMS.

James T.C. Teng

James T.C. Teng is Associate Professor at the College of Business Administration, University of South Carolina. He earned his M.S. in mathematics from the University of Illinois at Urbana-Champagne, and his Ph.D. in MIS from the University of Minnesota. Dr. Teng’s research and consulting interests are in the areas of information management, decision support systems, and management of process and organizational change. He has published over forty articles in journals such as Journal of Management Information Systems, Decision Sciences, Information and Management, California Management Review, INFOR, Data Base, European Journal of Information Systems, Information Systems Journal, and IEEE Transactions in Engineering Management. In 1992 he won the Outstanding Achievement Award from the Decision Sciences Institute.