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Modeling Supply-Side Dynamics of IT Components, Products, and Infrastructure: An Empirical Analysis Using Vector Autoregression

Gediminas Adomavicius (), Jesse Bockstedt () and Alok Gupta ()
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Gediminas Adomavicius: Department of Information and Decision Sciences, Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455
Jesse Bockstedt: Information Systems and Operations Management, School of Management, George Mason University, Fairfax, Virginia 22030
Alok Gupta: Department of Information and Decision Sciences, Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455

Information Systems Research, 2012, vol. 23, issue 2, 397-417

Abstract: Prior IS research on technological change has focused primarily on organizational information systems and technology innovation; however, there is a growing need to understand the dynamics of supply-side forces in the introduction of new technologies. In this paper we investigate how the interdependencies among information technology components, products, and infrastructure affect the release of new technologies. Going beyond the ad hoc heuristic approaches applied in previous studies, we empirically validate the existence of several patterns of supply-side technology relationships in the context of wireless networking. We use vector autoregression (VAR) to model the comovements of new component, product, and infrastructure introductions and provide evidence of strong Granger-causal interdependencies. We also demonstrate that substantial improvements in forecasting can be gained by incorporating these cross-level effects into models of technological change. This paper provides some of the first research that empirically demonstrates these cross-level effects and also provides an exposition of VAR methodology for both analysis and forecasting in IS research.

Keywords: information systems and technology trends; supply-side forces; technological change; technology ecosystems; technology forecasting; time series analysis; vector autoregression (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (8)

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