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SENGUPTA, JATI K. 2000. Dynamic and Stochastic Efficiency Analysis: Economics of Data Envelopment Analysis. World Scientific Publishing, River Edge, NJ. 226 pp. $78.00.
Originally introduced by Charnes et al. (1978), data envelopment analysis (DEA), sometimes called frontier analysis, is a technique based on linear programming for evaluating the relative efficiencies of decision-making units (DMUs). DEA is usually used to analyze a snapshot view of the performance data associated with the entities or organizations being evaluated, and the results do not fully capture the dynamics or uncertainties that these organizations are dealing with. The results from DEA analyses are often criticized as not being wholesome and robust. Sengupta tries to alleviate these concerns by detailing extensions that incorporate dynamics (in competition, learning, flexibility, quality, and so forth) and uncertainties (in costs, inputs and outputs, demands, and so forth) into DEA.
Sengupta starts (Chapter 1) with a brief introduction of DEA and its extensions to dynamic and stochastic efficiency, market demands, and noise in the data. Chapter 2 contains models that capture the dynamics associated with firm independence, production flexibility, and learning. The author accommodates the independence of a firm by using a two-stage model that initially lets the firm decide its profit-maximizing...