Efficiency analysis of engineering colleges in India: Decomposition into parallel sub-processes systems.

Analyzing engineering colleges in India with Data Envelopment Analysis (DEA) is the focus of this study. Engineering colleges pioneer in teaching and research, creating two sub-processes within engineering education. Thus, our study considers each engineering college to comprise two parallel non-homogenous sub-processes, such as teaching and researching. Unlike the conventional DEA models, where the system is treated as a black box, this work attempts to independently assess the impact of each parallel sub-process so that it is possible to identify specific changes in the respective processes to improve the overall efficiency. In particular, our study analyzed the efficiency of engineering colleges based on the National Institute Ranking Framework (NIRF) data. Further, the comparison of the efficiency scores from teaching and research indicates that, on average, the institutes are more efficient in teaching than researching. The current study helps policymakers set priorities and course corrections for performance improvement programs of engineering colleges in India. • We consider parallel non-homogeneous sub-processes in Data Envelopment Analysis (DEA) model. • We proposed the variable return to scale model for parallel non-homogeneous sub-processes in DEA. • We applied the above methodology to engineering colleges in India, with teaching and research being sub-processes. • We found that engineering colleges are more efficient in teaching than research. • With a ranking system like the NIRF, colleges have improved their efficiency. [ABSTRACT FROM AUTHOR]