Suchergebnisse

Purpose: In this age of knowledge economy, universities play an important role in the development of a country. As government subsidies to universities have been decreasing, more efficient use of resources becomes important for university administrators. This study evaluates the relative technical efficiencies of academic departments at the Islamic University in Gaza (IUG) during the years 2004-2006. Design/methodology/approach: This study applies Data Envelopment Analysis (DEA) to assess the relative technical efficiency of the academic departments. The inputs are operating expenses, credit hours and training resources, while the outputs are number of graduates, promotions and public service activities. The potential improvements and super efficiency are computed for inefficient and efficient departments respectively. Further, multiple linear -regression is used to develop a relationship between super efficiency and input and output variables. Findings: Results show that the average efficiency score is 68.5% and that there are 10 efficient departments out of the 30 studied. It is noted that departments in the faculty of science, engineering and information technology have to greatly reduce their laboratory expenses. The department of economics and finance was found to have the highest super efficiency score among the efficient departments. Finally, it was found that promotions have the greatest contribution to the super efficiency scores while public services activities come next.Research limitations/implications: The paper focuses only on academic departments at a single university. Further, DEA is deterministic in nature. Practical implications: The findings offer insights on the inputs and outputs that significantly contribute to efficiencies so that inefficient departments can focus on these factors. Originality/value: Prior studies have used only one type of DEA (BCC) and they did not explicitly answer the question posed by the inefficient departments "Which of the resources should be given priority so that these inefficient DMUs become efficient?". This study uses both (BCC) and (CCR) in addition to relating efficiencies to input and output variables.