An evaluative framework for research on the performance effects of information technology investment
ICIS '89 Proceedings of the tenth international conference on Information Systems
Post implementation evaluation of computer-based information systems: current practices
Communications of the ACM
Journal of Management Information Systems
Recent applications of economic theory in Information Technology research
Decision Support Systems
The productivity paradox of information technology
Communications of the ACM
Investment in information systems and the financial performance of the firm
Information and Management
Technology investment and business performance
Communications of the ACM
Beyond the productivity paradox
Communications of the ACM
Information and Management
Information Systems Research
Measuring Information Technology's Indirect Impact on Firm Performance
Information Technology and Management
A unified model for detecting efficient and inefficient outliers in data envelopment analysis
Computers and Operations Research
Hi-index | 0.01 |
The increasing use of information technology (IT) has resulted in a need for evaluating the productivity impacts of IT. The contemporary IT evaluation approach has focused on return on investment and return on management. IT investment has impacts on different stages of business operations. For example, in the banking industry, IT plays a key role in effectively generating (i) funds from the customer in the forms of deposits and then (ii) profits by using deposits as investment funds. Existing approaches based upon data envelopment analysis (DEA) only measure the IT efficiency or impact on one specific stage when a multi-stage business process is present. A detailed model is needed to characterize the impact of IT on each stage of the business operation. The current paper develops a DEA non-linear programming model to evaluate the impact of IT on multiple stages along with information on how to distribute the IT-related resources so that the efficiency is maximized. It is shown that this non-linear program can be treated as a parametric linear program. It is also shown that if there is only one intermediate measure, then the non-linear DEA model becomes a linear program. Our approach is illustrated with an example taken from previous studies.