Information Technology Reference
In-Depth Information
Finally, investments in IT have increased over the years to the point where IT now
represents over half of all capital investments in most companies. Despite increas-
ing evidence that IT investments pay off in aggregate, we still see that IT initiatives
produce dramatically varying outcomes from firm to firm, and even from initiative
to initiative within a given firm. Our model seeks to account for this variation by
using the economic logic of complementarities to analyze why certain clusters of
organizational elements should be observed in conjunction with more successful IT
investment and deployment. Thus, we contribute to the domain of IT and organiza-
tional design by redefining (or, re-conceptualizing) the concept of “fit” between IT
and organization and by providing a precise logic for generating eminently testable
hypotheses that relate IT to other organizational elements.
The remainder of this chapter is organized as follows. In Section 2.2, we dis-
cuss the “disconnect” between the IT innovation investments and the IT business
value literatures, and establish the critical need to develop an integrated theory of
IT investments, IT innovation, and business value, and the promise of the “comple-
mentarities approach” for doing so. In Section 2.3, we review the literature on the
logic of complementarities and its application in the innovation and IT literatures.
Section 2.4 provides an overview of our research model, and in Sections 2.5 and
2.6, we present the micro-level (i.e., PLM or IT initiative-level) and the macro-level
(i.e., firm-level) parts of our model respectively. We conclude the chapter by dis-
cussing the important implications of the model for future research and managerial
practice.
2.2 IT Investments and Business Value of IT: The Missing Link
The streams of research on IT innovation and IT business value have proceeded
largely in parallel. The IT innovation stream has primarily been the province of
behavioral science researchers and has addressed two general questions (Cooper
& Zmud, 1990; Swanson, 1994): (1) Why are some organizations more prone to
exhibit innovative behaviors than others? and (2) Why do some innovations dif-
fuse more widely and rapidly than others? The IT business value stream, on the
other hand, has mainly been the province of economics researchers, who have been
concerned with establishing whether investments in IT produce business value and
under what conditions this value will be greatest (Barua & Mukhopadhyay, 2000;
Brynjolfsson & Hitt, 1996; Kohli & Devaraj, 2003; Melville et al., 2004).
The central goal of the IT innovation research stream has been to identify the
determinants of IT adoption and implementation. This research has been guided by a
number of theoretical perspectives, including the traditional communications-based
diffusion of innovation model (Rogers, 2003), adaptive structuration (DeSanctis &
Poole, 1994), the technology acceptance model and related approaches (Venkatesh,
Morris, Davis, & Davis, 2003), organizational learning (Nambisan & Wang,
2000; Purvis, Sambamurthy, & Zmud, , 2001), network effects (Markus, 1987),
institutions (Teo, Wei, & Benbasat, 2003), power and influence (Hart & Saunders,
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