5 Jan-Mar 1999 Jan-Mar 1999 Jan-Mar 1999 Jan-Mar 1999 Jan-Mar 1999 Information Resources Management Journal Information Resources Management Journal Information Resources Management Journal Information Resources Management Journal Information Resources Management Journal Vol. 12, No. 1 Manuscript originally submitted September 9, 1996; Revised January 9, 1997; Accepted February 26, 1997 for publication. Copyright ©1999, Idea Group Publishing. IT benefits are often objectively difficult to quantify, since they affect aspects of performance, such as responsive- ness and flexibility, which cannot be assessed in terms of direct measures such as cost reductions or productivity im- provements. These objective difficulties in assessing the benefits of IT investments have been addressed in a number of different ways. For example, to support individual invest- ment decisions, cost-benefit analysis has attempted to de- emphasize quantitative criteria in favor of qualitative ones (cf. Parker et al., 1988; Willcocks, 1992). A qualitative approach to investment justification has been proposed not only on the basis of the intangible nature of IT benefits, but also on the interdependencies among different investments. The returns of an investment can be either made contingent on, or possibly amplified by, the successful realization of other investments and are thus difficult to quantify in isola- tion. On the other hand, these interdependencies also suggest that benefits may be apparent at an aggregate level. Some authors have noted that, although individually intangible, benefits from different investments are captured by firm- level economic indicators which are influenced by overall IT expenditures (cf., Roach, 1989; Roach, 1991; Strassmann, 1990). This research takes this last perspective and researches aggregate measures of IT returns. Much of the research taking this perspective has relied on analyses that tie IT investments to firm economic perfor- mance through indicators such as financial ratios (Loveman, 1988; Roach 1989; Roach, 1991; Weill, 1992; Bryjolffson and Hitt, 1993; Venkatraman and Zaheer, 1990). As recently surveyed by different authors (Smith and McKeen, 1993; Brynjolfsson, 1993; Blyth, 1995), empirical research using these indicators has failed to provide conclusive evidence suggesting increased business performance related to higher IT investments. Some authors have found a weak or negative correlation between investments and performance (Loveman, 1988; Strasmann, 1990; Cron and Sobol, 1983; Weill, 1992; Measuring the Financial Measuring the Financial Measuring the Financial Measuring the Financial Measuring the Financial Benefits of IT Investments Benefits of IT Investments Benefits of IT Investments Benefits of IT Investments Benefits of IT Investments on Coordination on Coordination on Coordination on Coordination on Coordination CHIARA FRANCALANCI CHIARA FRANCALANCI CHIARA FRANCALANCI CHIARA FRANCALANCI CHIARA FRANCALANCI Politecnico di Milano, Italy Politecnico di Milano, Italy Politecnico di Milano, Italy Politecnico di Milano, Italy Politecnico di Milano, Italy P. MAGGIOLINI P. MAGGIOLINI P. MAGGIOLINI P. MAGGIOLINI P. MAGGIOLINI Politecnico di Milano, Italy Politecnico di Milano, Italy Politecnico di Milano, Italy Politecnico di Milano, Italy Politecnico di Milano, Italy We know from the information processing perspective within the theory of organizations that IT can reduce coordination costs by increasing an organization’s information processing capacity. Purpose of this paper is to empirically examine the relationship between greater investments in information technology and lower coordina- tion costs on firm-level data. Two high-level measures of coordination costs are defined based on the information processing perspective within the theory of organizations. Our hypothesis that greater IT investments should be correlated with lower coordination costs is tested with both measures on longitudinal data from a cross-sectional sample of 18 large Italian companies over an 8-year period between 1988 and 1995. Results on this sample seem to support our hypothesis by showing a significant and negative correlation both aggregately and on sub-samples of data clustered by industry.