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Evaluating ERP projects using DEA and regression analysis

Author

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  • S. Parthasarathy
  • N. Anbazhagan

Abstract

Enterprise Resource Planning (ERP) projects appear to be a dream come true. This study evaluates ten ERP projects based on their productivity using Data Envelopment Analysis (DEA). The results of the DEA for preeminent ERP projects are uploaded into a project database. Regression analysis is then applied to the data in the project database to predict the efforts required for new ERP projects to acquire high productivity. Extensive literature survey shows that the DEA is the preeminent slant to evaluate ERP projects. The upshots of the study are: (1) Function Points (FP) and project efforts are the performance indicators of the ERP projects from the viewpoint of software engineering; (2) Lines of Code (LOC) have considerable influence over the efficiency of ERP projects; and (3) DEA, in combination with regression analysis, produces fruitful results for the ERP projects. Future directions in the performance enhancement of ERP projects are also indicated.

Suggested Citation

  • S. Parthasarathy & N. Anbazhagan, 2008. "Evaluating ERP projects using DEA and regression analysis," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 3(2), pages 140-157.
  • Handle: RePEc:ids:ijbisy:v:3:y:2008:i:2:p:140-157
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    Cited by:

    1. Samoilenko, Sergey & Osei-Bryson, Kweku-Muata, 2013. "Using Data Envelopment Analysis (DEA) for monitoring efficiency-based performance of productivity-driven organizations: Design and implementation of a decision support system," Omega, Elsevier, vol. 41(1), pages 131-142.

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