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Productivity and quality benchmarking in operations management using data envelopment analysis

Posted on:2001-11-24Degree:Ph.DType:Dissertation
University:The University of Texas at ArlingtonCandidate:Prabhakar, Rao SaiFull Text:PDF
GTID:1469390014954355Subject:Business Administration
Abstract/Summary:
The role of operations management has changed from functional to strategic dimension, due to the paradigm shifts caused by the overall evolution from Industrial to Post-industrial Era. For example, the focus has changed from mass production to lean production, from technology as exogenous to technology as endogenous, from law of diminishing returns to law of increasing returns, and from single-criterion to multi-criteria decision making.; This dissertation investigates the constructs that can be developed, through Multi-criteria Decision Making (MCDM), using Data Envelopment Analysis (DEA), that may help the operations manager to make optimum decisions in a globally tough and competitive business environment. The advantages of DEA are that it can handle multiple outputs and inputs, and it does not require any explicit assumptions for the functional form. The fundamental limitations inherent in the nonparametric approach to DEA modeling are overcome by current extensions to DEA modeling that enhance its discerning power in the classification of the Decision Making Units (DMUs).; The scenario researched is from a firm that deals with several products, which, in turn, consume multiple inputs to result in multiple outputs. The operations decisions made by the managers have become complicated due to rapid advances in technology, global competition, and customers' demanding and varied expectations. The author brings out the importance of the strategic role of the operations manager, and develops MCDM philosophy and methodology. MCDM will aid in comparing the actual productivity and quality metrics with those of the benchmarks established by DEA, so that the manager can make better decisions, based on the critical nature of the product/process.; This research fills the existing gap in the use of DEA at the shop level. The emphasis is on the new treatment of DEA extensions as a control tool in establishing the benchmark set matrix, as against the normal use of DEA as an ex post facto evaluation of the relative efficiency of management achievements.
Keywords/Search Tags:Management, DEA, Operations
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