A Data Envelopment Analysis Approach to Evaluation of the Program Follow through Experiment in U.S. Public School Education.
01 Nov 1978-
TL;DR: Data Envelopment Analysis (DEA) as mentioned in this paper is used to decompose the efficiency of decision making units (DMU's) into two parts: (1) a component resulting from managerial decisions and (2) a part resulting from constraints (called programs) under which management operates.
Abstract: : A method called Data Envelopment Analysis (DEA) is used to decompose the efficiency of Decision Making Units (DMU's) into two parts: (1) a component resulting from managerial decisions and (2) a component resulting from constraints (called programs) under which management operates. The DEA approach accomplishes this by enveloping the input-output observations with extremal relations developed in terms of a specified nonlinear programming model (and/or its linear programming equivalent). Differences between the observations and the progam specific envelopes -- called alpha-envelopes--are imputed to managerial inefficiencies. An inter-program envelope is then constructed from 2 or more such alpha-envelopes and used to identify 'program' inefficiencies, which are the inefficiencies that remain after the previously determined managerial inefficiencies have been eliminated. Numerical illustrations accompanied by suggested tests of a probabilistic/information theoretic character are provided by means of recenty released data from 'Program Follow Through.' Designed as a study of possible ways of reenforcing or extending Program Head Start - an ongoing pre-school program for disadvantaged children -- the Program Follow Through experiment provides data on agreed upon inputs and outputs for both PFT (Program Follow Through) and matched NFT (Not Follow Through) participants in various parts of the U.S.
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TL;DR: A model for measuring the efficiency of Decision Making Units =DMU's is presented, along with related methods of implementation and interpretation, and suggests the additional possibility of new approaches obtained from PFT-NFT combinations which may be superior to either of them alone.
Abstract: A model for measuring the efficiency of Decision Making Units =DMU's is presented, along with related methods of implementation and interpretation. The term DMU is intended to emphasize an orientation toward managed entities in the public and/or not-for-profit sectors. The proposed approach is applicable to the multiple outputs and designated inputs which are common for such DMU's. A priori weights, or imputations of a market-price-value character are not required.
A mathematical programming model applied to observational data provides a new way of obtaining empirical estimates of extrernal relations-such as the production functions and/or efficient production possibility surfaces that are a cornerstone of modern economics. The resulting extremal relations are used to envelop the observations in order to obtain the efficiency measures that form a focus of the present paper.
An illustrative application utilizes data from Program Follow Through =PFT. A large scale social experiment in public school education, it was designed to test the advantages of PFT relative to designated NFT =Non-Follow Through counterparts in various parts of the U.S. It is possible that the resulting observations are contaminated with inefficiencies due to the way DMU's were managed en route to assessing whether PFT as a program is superior to its NFT alternative. A further mathematical programming development is therefore undertaken to distinguish between "management efficiency" and "program efficiency." This is done via procedures referred to as Data Envelopment Analysis =DEA in which one first obtains boundaries or envelopes from the data for PFT and NFT, respectively. These boundaries provide a basis for estimating the relative efficiency of the DMU's operating under these programs. These DMU's are then adjusted up to their program boundaries, after which a new inter-program envelope is obtained for evaluating the PFT and NFT programs with the estimated managerial inefficiencies eliminated.
The claimed superiority of PFT fails to be validated in this illustrative application. Our DEA approach, however, suggests the additional possibility of new approaches obtained from PFT-NFT combinations which may be superior to either of them alone. Validating such possibilities cannot be done only by statistical or other modelings. It requires recourse to field studies, including audits e.g., of a U.S. General Accounting Office variety and therefore ways in which the results of a DEA approach may be used to guide such further studies or audits are also indicated.
1,544 citations
TL;DR: The results show that the proposed approach allows decision makers to perform trade-off analysis among expected costs, quality acceptance levels, and on-time delivery distributions and provides alternative tools to evaluate and improve supplier selection decisions in an uncertain supply chain environment.
315 citations
TL;DR: Data Envelopment Analysis is used for evaluating the technical efficiency of museum institutions to create for each museum a relative efficiency measure, which takes into account both the resources used by museums and the results of their activities.
Abstract: Data Envelopment Analysis is used for evaluating the technical efficiency of museum institutions. This approach enables us to create for each museum a relative efficiency measure, which takes into account both the resources used by museums and the results of their activities. Moreover this technique is able to overcome some of the difficulties found when applying more traditional indicators of productivity in evaluating the technical efficiency of cultural institutions. An empirical analysis carried out on data from Italian municipal museums illustrates this application of the operational research model.
74 citations
TL;DR: A measure of efficiency for not-for-profit entities is explained and illustrated by data from Program Follow Through, a large scale social experiment in U.S. public school education as discussed by the authors.
Abstract: A measure of efficiency for not-for-profit entities - developed by the authors in association with Edward Rhodes - is explained and illustrated by data from Program Follow Through, a large scale social experiment in U.S. public school education. A division into Follow Through and Non-Follow Through participants facilitates a distinction between “program efficiency” and “managerial efficiency” which is also illustrated and examined for its use in evaluating such programs. Relations to comprehensive audits and other possible uses are explored.
54 citations
TL;DR: The results were mixed with no clear positive effects being proven consistently: in the data set of successful projects, mostly negative influences were found; on the contrary, tool adoption showed positive relationships to efficiency in the random data set, stressing the importance of development status as a moderating variable.
Abstract: In this paper we explore possible benefits of communication and coordination tools in open source projects using an efficiency score derived from data envelopment analysis (DEA) as dependent variable. DEA is a general non-parametric method for efficiency comparisons without asking the user to define any relations between different factors or a production function. The method can account for economies or diseconomies of scale, and is able to deal with multi-input, multi-output systems in which the factors have different scales. Using two different data sets, successful and random open source projects, retrieved from SourceForge.net, we analyze impacts on their efficiency from the usage of communication and coordination tools. The results were mixed with no clear positive effects being proven consistently: In the data set of successful projects, mostly negative influences were found. On the contrary, tool adoption showed positive relationships to efficiency in the random data set. This stresses the importance of development status as a moderating variable and might also hint at threshold values for tool benefits. In addition, adoption of tools outside the hosting platform may be more likely for successful projects.
38 citations
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