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with Data Envelopment Analysis

01 Jan 2012-
TL;DR: Data Envelopment Analysis (DEA) is an increasingly popular management tool and is commonly used to evaluate the efficiency of a number of producers.
Abstract: Data Envelopment Analysis (DEA) is an increasingly popular management tool. DEA is commonly used to evaluate the efficiency of a number of producers. A typical statistical approach is characterized as a central tendency approach and it evaluates producers relative to an average producer. In contrast, DEA compares each producer with only the "best" producers. By the way, in the DEA literature, a producer is usually referred to as a decision making unit or DMU. DEA is not always the right tool for a problem but is appropriate in certain cases.
Citations
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Journal ArticleDOI
TL;DR: This paper attempts to examine and reflect on the experiences of being a beginning social worker and beginning teacher, and describes the similarities between the two processes.
Abstract: This paper attempts to examine and reflect on my experiences of being a beginning social worker and beginning teacher. I describe the similarities between the two processes. In many respects they were painful experiences, fraught with disappointments, frustrations, and, at times, loss, sadness, and anger. Yet, out of these painful experiences, there are many humorous events and many different, diverse, and interesting opportunities. All these experiences enriched my learning, and produce a worker and teacher who is able to draw on all these experiences for the benefit of his clients and students.

147 citations

01 Jan 1997
TL;DR: The strengths and weaknesses for estimating environmental efficiency of the methods applied are revealed; namely Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA).
Abstract: The objective of this paper is to estimate comprehensive environmental efficiency measures for Dutch dairy farms. The environmental efficiency scores are based on the nitrogen surplus, phosphate surplus and the total (direct and indirect) energy use of an unbalanced panel of dairy farms. We define environmental efficiency as the ratio of minimum feasible to observed use of multiple environmentally detrimental inputs, conditional on observed levels of output and the conventional inputs. We compare two methods for the calculation of efficiency; namely Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). This paper reveals the strengths and weaknesses for estimating environmental efficiency of the methods applied. Both SFA and DEA can estimate environmental efficiency scores. The mean technical efficiency scores (output-oriented, SFA 89%, DEA 78%) and the mean comprehensive environmental efficiency scores (SFA 80%, DEA 52%) differ between the two methods. SFA allows hypothesis testing, and the monotonicity hypothesis is rejected for the specification including phosphate surplus. DEA can calculate environmental efficiency scores for all specifications, because regularity is imposed in this method.

101 citations

Book ChapterDOI
01 Jan 1980
TL;DR: Efficiency and productivity in research and development must not be confused as being the same as efficiency in production or ordinary service activities as discussed by the authors, and the greatest output and its highest quality in scientific terms comes from the time and energy of the scientifically productive research workers.
Abstract: Efficiency and productivity in research and development must not be confused as being the same as efficiency in production or ordinary service activities. The greatest output and its highest quality in scientific terms comes from the time and energy of the scientifically productive research workers, and the organiser of a laboratory who has efficiency in mind would have constantly under review ways in which this time and energy can be conserved and the research quality enhanced.

62 citations

Journal Article
TL;DR: In this paper, the authors present an approach to estimate lower bounds for the value efficiency scores, which reflect the decision-maker's (DM's) preferences in data envelopment analysis.

34 citations

Posted Content
TL;DR: In this paper, the authors show how a conventional performance evaluation methodology has evolved into a novel performance enhancement methodology, which is the result of cooperations among individual credit union managements, movement officials and the authors.
Abstract: In the United States credit unions are not-for-profit cooperative financial institutions, owned by and operated for the benefit of their members. Being part of a cooperative movement enhances the likelihood that credit unions will share performance-enhancing ideas, for the benefit of weak credit unions and the movement as a whole. In this paper we show how a conventional performance evaluation methodology has evolved into a novel performance enhancement methodology. The evolution of the methodology is the result of cooperations among individual credit union managements, movement officials and the authors. The evolution is illustrated with 1990 data on nearly 9,000 credit unions.

27 citations

References
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Journal ArticleDOI
TL;DR: A nonlinear (nonconvex) programming model provides a new definition of efficiency for use in evaluating activities of not-for-profit entities participating in public programs and methods for objectively determining weights by reference to the observational data for the multiple outputs and multiple inputs that characterize such programs.

25,433 citations

Journal ArticleDOI
TL;DR: The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs as mentioned in this paper.
Abstract: In management contexts, mathematical programming is usually used to evaluate a collection of possible alternative courses of action en route to selecting one which is best. In this capacity, mathematical programming serves as a planning aid to management. Data Envelopment Analysis reverses this role and employs mathematical programming to obtain ex post facto evaluations of the relative efficiency of management accomplishments, however they may have been planned or executed. Mathematical programming is thereby extended for use as a tool for control and evaluation of past accomplishments as well as a tool to aid in planning future activities. The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs. A separation into technical and scale efficiencies is accomplished by the methods developed in this paper without altering the latter conditions for use of DEA directly on observational data. Technical inefficiencies are identified with failures to achieve best possible output levels and/or usage of excessive amounts of inputs. Methods for identifying and correcting the magnitudes of these inefficiencies, as supplied in prior work, are illustrated. In the present paper, a new separate variable is introduced which makes it possible to determine whether operations were conducted in regions of increasing, constant or decreasing returns to scale in multiple input and multiple output situations. The results are discussed and related not only to classical single output economics but also to more modern versions of economics which are identified with "contestable market theories."

14,941 citations


Additional excerpts

  • ...delphic hierarchy process (DHP) [2845] [2851] deregulation [1435] design and performance of materials kitting systems [516] deterministic frontier [2073] deterministic frontier analysis [1848] deterministic frontiers [1461] [2403] development indexes [2287] differential effectiveness [2871] [2872] dimensionality [1638] directional distance function [693] disaster damage assessment model [845] discrete representation [2743] discriminant analysis [2333] [2335] [2338] [2692] [2792] [2795] discriminant function [1262] discriminating power [1790] discrimination [772] [774] discrimination functions [752] disjunctive programming [1699] disposability [189] [1058] distance function [1826] [1830] [1831] distance functions [213] [522] [1209] [1331] [1350] distributed computing [2799] distribution [2383] distribution of efficiency [2564] Domesday book [1926] dominance [196] dominance cone [1502] dual linear programming [1822] dual linear programs [278] duality [496] [813] [1042] [1383] dualization [43] dynamic adjustment [1450] dynamic DEA [1535] dynamic efficiency [2559] [2572] [2857] East Asia [2956] ecological efficiency [908] econometric models [643] econometrics [2087] [2966] economic development [530] economic efficiency measurement [1692] economic evaluation [40] economic reforms [62] [2313] economics [403] [1299] [2468] economics of information technology [2593] economies of diversification [2275] economies of jointness [2067] economies of scale [1701] [1715] [3000] economies of scale and data envelopment analysis [201] economies of scope [1715] [2067] economies of specialization [1701] education [354] [487] [1661] [1891] [1957] [2245] [2406] [2456] [2861] [2871] [2872] education systems - operations [2591] education systems - planning [402] educational - systems [404] educational costs [2404] educational performance measurement [1919] effectiveness [200] [206] [1587] effectiveness analysis [1274] effectiveness/performance [1264] [1580] [3166] efficiency [78] [93] [107] [130] [183] [205] [206] [257] [269] [293] [296] [297] [304] [317] [354] [355] [414] [464] [466] [468] [469] [476] [487] [496] [522] [539] [552] [562] [595] [610] [611] [612] [638] [643] [715] [748] [767] [772] [773] [784] [787] [801] [809] [817] [946] [979] [1015] [1058] [1233] [1250] [1292] [1303] [1305] [1328] [1355] [1363] [1423] [1451] [1525] [1572] [1573] [1583] [1585] [1587] [1598] [1671] [1893] [1925] [1926] [1967] [2053] [2082] [2087] [2110] [2202] [2230] [2232] [2236] [2239] [2240] [2249] [2267] [2325] [2346] [2354] [2391] [2394] [2398] [2400] [2402] [2421] [2434] [2467] [2497] [2498] [2500] [2628] [2669] [2671] [2699] [2708] [2723] [2727] [2820] [2833] [2855] [2961] [2978] [2983] [3162] [3183] [3185] [3186] [3189] [3192] efficiency analysis [62] [276] [1385] [1394] [1396] [1398] [1400] [1401] [1403] [1404] [1567] [1579] [1656] [1657] [1695] [1698] [2088] efficiency and performance audits [63] efficiency change [114] [213] [241] [1257] efficiency comparisons [502] efficiency depth [688] efficiency enhancement [111] efficiency estimation [111] [315] [847] efficiency evaluation [307] [566] [569] efficiency evaluations [503] efficiency frontiers [296] [636] [798] [1064] [1126] efficiency gains [2483] efficiency index [426] [1486] efficiency indices [498] efficiency measure [1039] [1168] [1821] efficiency measurement [63] [72] [365] [411] [983] [1289] [1468] [1483] [1494] [1663] [1719] [1838] [1848] [1904] [1946] [2009] [2058] [2073] [2136] [2316] [2405] [2433] [2494] [2887] [3115] [3150] efficiency measures [797] [2169] [2742] efficiency ranking [712] efficiency sensitivity [2923] efficiency, industrial [1078]...

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  • ...Charnes, Abraham (1,10,0,51,0,6,1) [57] [58] [59] [60] [293] [294] [295] [296] [297] [298] [398] [483] [503] [609] [610] [611] [612] [613] [614] [615] [616] [617] [618] [619] [620] [621] [622] [623] [624] [625] [626] [627] [628] [629] [630] [631] [632] [633] [634] [635] [636] [637] [638] [639] [640] [641] [642] [643] [644] [645] [646] [647] [648] [649] [650] [651] [652] [653] [654] [655] [656] [657] [658] [659] [660] [661] [662] [663] [664]...

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  • ...edu) [57] [58] [59] [60] [63] [145] [167] [168] [169] [293] [294] [295] [296] [297] [298] [302] [303] [304] [306] [321] [322] [323] [324] [390] [391] [398] [483] [503] [505] [506] [507] [518] [590] [617] [618] [619] [620] [621] [622] [624] [628] [630] [631] [632] [633] [634] [635] [636] [637] [638] [639] [640] [641] [642] [643] [644] [645] [646] [647] [648] [649] [650] [651] [652] [653] [654] [655] [656] [657] [658] [659] [660] [661] [662] [744] [776] [777] [778] [779] [780] [781] [782] [783] [784] [785] [786] [787] [788] [789] [790] [791] [792] [793] [794] [795] [796] [797] [798] [799] [800] [801] [802] [803] [804] [805] [806] [807] [808] [809] [810] [811] [812] [813] [814] [815] [816] [817] [818] [819] [820] [1708] [1783] [2504] [3193] [3194]...

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  • ...linear programming [111] [130] [257] [293] [297] [476] [496] [538] [560] [562] [566] [610] [611] [612] [627] [638] [733] [948] [966] [970] [974] [975] [1039] [1331] [1584] [1585] [1852] [1877] [1946] [1967] [2009] [2169] [2228] [2330] [2335] [2338] [2391] [2394] [2434] [2472] [2522] [2769] [2771] [2782] [2788] [2789] [3014] [3042] [3192] linear reverse convex program [2817] linked-cone (LC) profit ratio [2911] literature review [1468] livability assessment [1431] local authorities [200] local government [454] [983] location [2238] [2913] location analysis [3029] log efficiency [656] logistics [3029] loglinear estimation [1248] long-term care [414] Loo metric [2847] [2849] macroecomic performance [1852] macroeconomic performance [495] macro-economic productivity indices [504] maintained hypotheses [2058] Malmquist [1222] [1902] Malmquist index [216] [592] [1087] [1209] [1255] [1328] [1904] [2218] [2953] [3195] Malmquist index and shadow prices [1700] Malmquist indices [213] [2053] [2667] Malmquist productivity index [159] [1168] [1331] [1821] [1826] [1828] Malmquist productivity indices [2217] Malmquist total factor-productivity index [1951] management [1292] [2922] management consulting [2009] management information systems [1028] management of computing and information systems [280] [299] [2035] management productivity [1735] managerial efficiency [636] managerial skill [1624] manufactures [1525] manufacturing [517] manufacturing industries [2956] marginal rates [2370] marginal rates of substitution [798] marginal resource levels [2870] market concentration [856] market efficiency [187] [188] marketability [2500] [3189] marketing [1875] Markov chain model [2797] Markov chain Monte Carlo [1363] mathematical programming [87] [293] [329] [431] [539] [806] [1248] [1925] [2082] [2433] mathematical programming - applications [402] maximin [2238] maximum convex output possible set [604] maximum likelihood estimation [1360] [2997] MBA programs [737] MCDA/M [1104] MCDM [43] [466] [468] [469] [2451] mean-variance analysis [2252] [2256] measurement [315] measures of inefficiency [778] measuring economic rents [1350] measuring gains from regional development [530] measuring potential gains from reform [1350] mergers [1417] methodology [992] methods [1468] metric [2346] Mexico [317] [3000] micro firms [1450] military [2238] military application [476] minimal extrapolation [431] minimax approach [603] minimax solutions [2553] minimum convex input requirement set [604] minimum of Leontif aggregator [2997] mining [538] misspecification [304] mix deviation [681] mix inefficiency [806] mixed-binary linear program [758] model misspecification [2058] [2715] model properties [785] model relation [2742] model relations [797] model specification [2703] model uses [785] modelling [900]...

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  • ...edu) [261] [262] [263] [264] [265] [266] [267] [268] [269] [270] [271] [272] [273] [274] [275] [276] [277] [278] [279] [280] [281] [282] [283] [284] [285] [286] [287] [288] [289] [290] [291] [292] [293] [294] [295] [296] [297] [298] [299] [300] [301] [302] [303] [304] [305] [306] [307] [308] [309] [310] [311] [312] [313] [314] [315] [593] [596] [1643] [1740] [1915]...

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Journal ArticleDOI
01 May 1957

14,922 citations

Book
30 Nov 1999
TL;DR: In this article, the basic CCR model and DEA models with restricted multipliers are discussed. But they do not consider the effect of non-discretionary and categorical variables.
Abstract: List of Tables. List of Figures. Preface. 1. General Discussion. 2. The Basic CCR Model. 3. The CCR Model and Production Correspondence. 4. Alternative DEA Models. 5. Returns to Scale. 6. Models with Restricted Multipliers. 7. Discretionary, Non-Discretionary and Categorical Variables. 8. Allocation Models. 9. Data Variations. Appendices. Index.

4,395 citations


Additional excerpts

  • ...edu) [57] [58] [59] [60] [63] [145] [167] [168] [169] [293] [294] [295] [296] [297] [298] [302] [303] [304] [306] [321] [322] [323] [324] [390] [391] [398] [483] [503] [505] [506] [507] [518] [590] [617] [618] [619] [620] [621] [622] [624] [628] [630] [631] [632] [633] [634] [635] [636] [637] [638] [639] [640] [641] [642] [643] [644] [645] [646] [647] [648] [649] [650] [651] [652] [653] [654] [655] [656] [657] [658] [659] [660] [661] [662] [744] [776] [777] [778] [779] [780] [781] [782] [783] [784] [785] [786] [787] [788] [789] [790] [791] [792] [793] [794] [795] [796] [797] [798] [799] [800] [801] [802] [803] [804] [805] [806] [807] [808] [809] [810] [811] [812] [813] [814] [815] [816] [817] [818] [819] [820] [1708] [1783] [2504] [3193] [3194]...

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  • ...edu) [54] [55] [77] [78] [79] [80] [93] [95] [164] [193] [211] [325] [326] [332] [333] [334] [335] [645] [646] [649] [650] [651] [655] [656] [678] [740] [743] [747] [765] [772] [773] [774] [783] [800] [801] [802] [808] [809] [978] [1152] [1457] [1759] [1760] [1761] [1762] [1979] [2137] [2313] [2488] [2489] [2490] [2491] [2492] [2493] [2494] [2495] [2496] [2497] [2498] [2499] [2500] [2501] [2502] [2503] [2504] [2505] [2506] [2507] [2508] [2509] [2510] [2511] [2512] [2513] [2514] [2515] [2516] [2517] [2518] [2519] [2520] [2653] [2752] [3175] [3176] [3177] [3178] [3179] [3180] [3193] [3194]...

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  • ...jp) [778] [788] [789] [790] [791] [802] [808] [809] [811] [812] [2815] [2967] [2968] [2969] [2970] [2971] [2972] [2973] [2974] [2975] [2976] [2977] [2978] [2979] [2980]...

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  • ...[802] Cooper, William Wager, Lawrence M....

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