The results show that none of the faculties is relatively efficient since its functions were found to be inefficient. The proposed model enables to help the management of university faculties to identify weaknesses of each function and thus to plan for suitable actions on improving the overall performance of the university. | Journal of ICT, 17, No. 4 (October) 2018, pp: 569–585 H . ow to cite this article: Kashim, R., Kasim, M. M., & Rahman, A. R. (2018). Measuring efficiency of a university faculty using a hierarchical network data envelopment analysis model. Journal of Information and Communication Technology, 17(4), 569-585. MEASURING EFFICIENCY OF A UNIVERSITY FACULTY USING A HIERARCHICAL NETWORK DATA ENVELOPMENT ANALYSIS MODEL Rosmaini Kashim, Maznah Mat Kasim & Rosshairy Abd Rahman School of Quantitative Sciences Universiti Utara Malaysia, Malaysia rosmaini@; maznah@; shairy@ ABSTRACT An efficiency measurement model of a university faculty is proposed with additional new sub-functions that produce new output variables, based on the network Data Envelopment Analysis (DEA) model for systems with a hierarchical structure. For production systems composed of hierarchical processes, the system efficiency is well represented as the aggregated performance of the components involved in the system. It is identified that the conventional DEA model ignores internal process activities in a university. Therefore, an improved DEA model based on a network structure that accounts for more activities in a university is proposed to measure its overall efficiency. The impact of major functions of a university are taken into account to represent the output variables in assessing the efficiency. Currently, collaboration activities have been given more attention, so, this variable is suggested as a new output for the hierarchical production system. In order to show the practicality of the model, a hypothetical set of data of 14 faculties has been used as a numerical example. The results show that none of the faculties is relatively efficient since its functions were found to be inefficient. The proposed model enables to help Received: 14 March 2018 Accepted: 13 August 2018 569 Published: 1 October 2018 Journal of ICT, 17, No. 4 (October) 2018, pp: 569–585 the .
