Relative Industry Concentration and Customer-Driven IT Spillovers

Zhuo (June) Cheng () and Barrie R. Nault ()
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Zhuo (June) Cheng: School of Accounting and Finance, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Barrie R. Nault: Haskayne School of Business, University of Calgary, Calgary, Alberta T2N 1N4, Canada

Information Systems Research, 2012, vol. 23, issue 2, 340-355

Abstract: We examine how one industry's productivity is affected by the IT capital of its customers and how this effect depends on industries' relative concentration. These customer-driven IT spillovers result from customers' IT investments in various information systems that reduce transaction costs through information sharing and coordination and lead to more efficient production and logistics upstream. The magnitude of IT spillovers depends on relative industry concentration because customers in more concentrated industries relative to those of their suppliers are better able to retain the benefits from their IT investments. We model customer-driven effects based on production theory and empirically test the model using two industry-level data sets covering different and overlapping time periods (1987--1999 and 1998--2005), different scopes of the economy (manufacturing only versus all industries), and different levels of industry aggregation. We find that, given an increase in a downstream industry's IT capital, there is a significant increase in downstream industry output as well as significant increases in upstream industry output. Moreover, the magnitude of IT spillovers is related to relative industry concentration: A 1% decrease in a customer's relative industry concentration increases spillovers by roughly 1%. Thus, further increases in IT capital can be justified along the supply chain, and an industry's relative concentration---which can reflect market power---in part determines the distribution of productivity benefits.

Keywords: business value of IT; IT-enabled supply chains; economics of IS; spillovers; production function framework; input-output tables; industry concentration (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (14)

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