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Global Malmquist Productivity Index based on preference common-weights

Abbasian-Naghneh Salman (Islamic Azad University, Najafabad Branch, Department of mathematics, Najafabad, Iran)

Data Envelopment Analysis is a linear programming technique for assessing the efficiency and productivity of decision making units (DMUs). Over the last decade, DEA has gained considerable attention as a managerial tool for measuring performance. The flexibility in selecting the weights in standard DEA models deters the comparison among DMUs on a common base. Moreover, these weights are unsuitable to measure the preferences of a decision maker (DM). For dealing with these two difficulties simultaneously; we use preference common weights. This paper uses preference common weights for time-series evaluations to calculate the global Malmquist productivity index (MPI) so that the productivity of changes of all DMUs have a common basis for comparison, and DM’s preference information is incorporated in calculating global MPI. The Malmquist Productivity Index (MPI) suggests a convenient way of measuring the productivity change of a given unit between two consequent time periods.

Keywords: data envelopment analysis, efficiency, global malmquist productivity index, preference common-weights