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• W1495804514 abstract "Data Envelopment Analysis (DEA) is a linear programming technique for measuring therelative efficiencies of a set of Decision Making Units (DMUs). Each DMU uses the sameset of inputs in differing amounts to produce the same set of outputs in differing quantities.Weights are freely allocated in order to allow these multiple incommensurate inputs andoutputs to be reduced to a single measure of input and a single measure of output. Arelative efficiency score of a DMU under Constant Returns to Scale is given by maximisingthe sum of its weighted outputs to the sum of its weighted inputs, such that this ratio cannot exceed I for any DMU; with the weights derived from the model being taken torepresent the value attributed to the inputs and outputs of the assessment.It is well known in DEA that this free allocation of weights can lead to several problems inthe analysis. Firstly inputs and outputs can be virtually ignored in the assessment; secondlyany relative relationships between the inputs or outputs can be ignored, and thirdly anyrelationships between the inputs and outputs can be violated. To avoid/overcome theseproblems, the Decision Maker's (DM) value judgments are incorporated into theassessment. At present there is one main avenue for the inclusion of values, that of weightsrestrictions, whereby the size of the weights are explicitly restricted. Thus to include therelative value of the inputs or outputs, the relative value of the weights for these relatedinputs or outputs are restricted. The popularity of this approach is mainly due to itssimplicity and ease of use.The aim of this thesis is, therefore, firstly, to demonstrate that, although the weightsrestrictions approach is appropriate for many DMs, for a variety of reasons some DMs,may prefer an alternative form for the expression of their values, e.g. so that they caninclude local values in the assessment. With this in mind, the second aim of this thesis is topresent a possible alternative approach for the DMs to incorporate their values in a DEAassessment and, thirdly, it aims to utilise this alternative approach to improve envelopment.This alternative approach was derived by considering the basic concept of DEA, which isthat it relies solely on observed data to form the Production Possibility Set (PPS), and thenuses the frontier of this PPS to derive a relative efficiency score for each DMU. It could beperceived, therefore, that the reason for DMUs receiving inappropriate relative efficiencyscores is due to the lack of suitable DEA-efficient comparator DMIUs. Thus, the proposedapproach attempts to estimate suitable input output levels for these missing DEA-efficientcomparator DMUs, i.e. Unobserved DMUs. These Unobserved DMUs are based on themanipulation of observed input output levels of specific DEA-efficient DMUs.The aim of the use of these Unobserved DMUs is to improve envelopment, and the specificDEA-efficient DMTJs that are selected as a basis for the Unobserved DMILTs are those thatdelineate the DEA-efficient frontier from the DEA-inefficient frontier. So, the proposedapproach attempts to extend the observed PPS, while assuming that the values of theobserved DEA-efficient DMIJs are in line with the perceived views of the DM.The approach was successfully applied to a set of UK bank branches. To illustrate that noapproach is all-purpose, and that each has its strengths and weaknesses and, therefore, itsown areas of application, a brief comparison is made between the approach of weightsrestrictions and the approach proposed in this thesis.This thesis is divided into three sections: A - Overview of the research area;B - An alternative perspective for incorporating values in DEA; C - The use of UDMUsto express the DM's values to improve envelopment" @default.
• W1495804514 created "2016-06-24" @default.
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• W1495804514 date "1997-04-01" @default.
• W1495804514 modified "2023-09-24" @default.
• W1495804514 title "Incorporating value judgments in data envelopment analysis" @default.
• W1495804514 hasPublicationYear "1997" @default.
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