Information Technology Reference
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1997), and mindfulness (Swanson & Ramiller, 2004) to name a few of the more
prominent ones. This research has identified scores of different variables that
influence organizational innovation with IT - variables pertaining to characteris-
tics of the technologies themselves (e.g., compatibility), characteristics of leaders
(e.g., degree of top management support), organizational structural characteristics
(e.g., size), characteristics of the workforce (e.g., level of technical knowledge),
environmental influences (e.g., competitive pressures), and implementation pro-
cesses and tactics (e.g., innovation champions) (Fichman, 2000).
While the IT innovation stream has been concerned with whether organizations
thoroughly deploy the innovations they have adopted, the ultimate organizational
impacts that flow from deployment have been viewed as generally falling outside
the scope of this stream, possibly because innovation behaviors are viewed as of
intrinsic interest regardless of their specific impacts, or because their impacts are
presumed to be generally beneficial (the so-called pro innovation bias), or because
of the difficulty of examining both IT deployment and IT impacts within the confines
of a single study. Whatever the reason, the absence of work that relates business
value to innovation antecedents and behaviors leaves some important questions
unanswered, such as how does the extent of deployment relate to business value?
Besides the extent of deployment, what conditions at (a) the IT initiative-level and
(b) the firm-level affect business value? How can we specify and measure these
conditions so as to lead to actionable insights?
One might expect that the natural place to look for answers to the above ques-
tions would be the research on the business value of IT. However, with some notable
exceptions to be discussed shortly, this research is generally conducted at a level of
abstraction and aggregation that precludes answering these specific sorts of ques-
tions. Business value research tends to view IT as monolithic: Studies will often
link firm-level IT spending or accumulated IT capital stock to firm-level business
value (e.g., multi-factor productivity or accounting measures of profits and costs).
Such measures of IT investment represent only a partial view of what has actually
been spent on IT, and more to the point, do not capture what specific kinds of IT
were invested in, when and how the investments occurred, or to what extent such
investments can even be viewed as being “innovative.”
So, unlike IT innovation research, IT business value research tends not to be
contextualized to particular kinds of IT or organizational adopters, and this research
does not usually link IT investment and business value to specific innovative behav-
iors, such as investment timing or extent of deployment. Despite this general stance,
there are some notable exceptions. Dos Santos and Peffers (1995) showed that banks
that had adopted ATM networks earlier gained a competitive advantage, thus linking
an innovation concept (i.e., adoption timing) to business value (i.e., profitability).
Hitt, Wu, and Zhou (2001) showed that greater operational improvements occurred
for firms that had implemented ERP earlier and more thoroughly. Devaraj and Kohli
(2003) linked the extent of IT use in a hospital setting to operational performance
improvements. Karimi, Somers, and Bhattacherjee (2007) studied the impact of the
extent of ERP implementation (functional scope, geographic scope, organizational
scope, etc. of the solution) on business process outcomes (such as process flexibility,
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