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Performance Impacts of Information Technology: Is Actual Usage the Missing Link?

Performance Impacts of Information Technology: Is Actual Usage the Missing Link?. Sarv Devaraj and Rajiv Kohli Management Science (2003) Gun- woong Lee. Research Motivation and Objective. Need for a new approach measuring IT productivity Mixed results of IT productivity

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Performance Impacts of Information Technology: Is Actual Usage the Missing Link?

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  1. Performance Impacts of Information Technology:Is Actual Usage the Missing Link? SarvDevaraj and Rajiv Kohli Management Science (2003) Gun-woong Lee

  2. Research Motivation and Objective • Need for a new approach measuring IT productivity • Mixed results of IT productivity • Is it neutral, negative, positive, or insignificant effect? • Black Box of IT usage • How to detect and measure IT impacts where they occur? • Missing link between IT investment and Its impact • How to identify the impact of individual technologies on firm performance? • Research Questions • What are previous studies’ limitations in measuring IT productivity? • What are the key variables in evaluating the impact of IT on performance? • Is actual usage of the IT effectively measure the organizational performance?

  3. Mixed results and Limitations of IT Payoff Studies

  4. Proposition: The actual usageof strategic information technology by an organization will be associated with higher performance, after controlling for the effect of external variables.

  5. Findings • Significant Link between Actual Usage and Firm Performance • The greater the actual usage of IT, the better finical and quality performance • (There was two periods lag effects

  6. Strengthens • Data • Small sample data to Large sample data • Cross-sectional to Longitudinal data set • Mandatory of data usage to Voluntary data usage (self-reported data) • Methodology • Use of a set of control variables • Specification Tests • Causality tests, omitted variable tests, and diagnostic checks on residuals • Contribution • Academic: New measurement approach for IT Productivity • Encourage IS researcher to conduct further related studies • Practice: Evidence for the monetary and quality improvements • Allow IT managers to justify investments in IT

  7. Weaknesses and Extensions • Multi-collinearity • High correlation among the control variables (p. 283) • CASEMAX & FTE (.53*), OUTPATNT & MEDICAID (.65*), Medicaid & FTE (.70*) • Require multicollinearitytest and model re-specification • Model Fit Improvements • Compare the estimates w/o control variables with those w/ them. • Provide model fit indexes • Measure for Organizational Performance • Only ‘Revenue’ does not indicate the financial benefits from IT • Mention how to handle different cost structures

  8. Weaknesses and Extensions • Lag Effects • Due to the billing cycle, it takes 60 days period to reflect the benefit from it?? • Consider other factors (e.g. execution time and putting several requests into action) • Provide Criteria for lag selection (e.g., AIC & SIC) • Generalizability • Small observation size (8 hospitals) and short period of observation time (3 years) • How to generalize the findings to other industries or other period of time? • Include other industrial groups over long period of time and utilize a hierarchical data analysis approach

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