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引文資料
題名:
基於效率的組織多屬性決策及實證研究:DEA-TOPSIS組合方法
書刊名:
中國管理科學
作者:
杜濤
/
冉倫
/
李金林
/
曹雪麗
出版日期:
2017
卷期:
2017(7)
頁次:
153-162
主題關鍵詞:
數據包絡分析
;
逼近理想解的排序方法
;
相對效率
;
多屬性決策
;
鬆弛改進量
;
DEA
;
TOPSIS
;
Data envelopment analysis
;
Technique for order preference by similarity to ideal solution
;
Relative efficiency
;
Multicriteria decisionmaking
;
Slack improvements
原始連結:
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相關次數:
被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
排除自我引用:0
共同引用:0
點閱:1
在日益激烈的競爭中,決策和效率已成為組織獲得競爭力的關鍵因素,但在管理實踐中往往會出現以犧牲效率來達到決策優化的目的。為了在保證效率甚至提高效率的基礎上優化組織的決策,本文首次從基于效率進行多屬性決策的角度,將DEA方法和TOPSIS方法進行組合。DEA方法不僅可以對具有多種投入多種產出指標的組織的相對效率進行測算,還可求得決策單元(Decision Making Unit,DMU)各指標的松弛改進量,這使得DEA方法與TOPSIS方法進行組合在理論上是可行的。以首都醫科大學為例,假設組織為了提高整體的效率競爭力,希望在2013年效率的基礎上使有效DMU的個數增加,并在實現過程中使各指標松弛改進總量盡可能小(即使改變盡可能"容易")。將首都醫科大學附屬的10所三甲綜合醫院作為DMUs,并運用DEA-TOPSIS組合方法,從提高技術效率的角度進行了研究。研究結果表明,DEA-TOPSIS組合方法不僅可以有效地對基于效率的決策備選方案進行排序,還可以通過選擇不同的模型和指標處理方法以盡可能地反映實際情況,具有很強的實踐價值。
以文找文
In an increasingly competitive environment,decision making and efficiency have become to be the key factors.But in practice,managers usually appear to achieve the purpose of optimizing decision-making with the sacrifice efficiency.This practice is very easy to make managers in the dilemma of care for this and lose that.Therefore,ensuringor even improving efficiency is crucial during the process of optimization of decision making.However,no scholars have combined the data envelopment analysis(DEA)method with the decision method in existing researches,which is in order to solve the problem of optimizing the decision based on the current relative efficiency.From the perspective of multi criteria decision making,based on the current efficiency,the DEA method is firstly combined with technique for order preference by similarity to an ideal solution(TOPSIS)method.The DEA-TOPSIS integrated method can deal with the issue of multi criteria decision making on the base of efficiency assurance.DEA is a non-parametric method that measures therelative efficiencies of organizations,which is with multi inputs and outputs.This method also can calculate the inputs and outputs’ slack improvements of ineffective decision making units(DMUs).These slack improvements provide a clear direction and goal for further decision making optimization based on the efficiency.TOPSIS method is widely used in multi criteriadecision making problems.As DEA method,TOPSIS method’sbasic idea is to sort alternatives according to the evaluation of ideal and negative ideal distance between the targets.So it is feasible in theory to integrate the DEA method and TOPSIS method.DEA-TOPSIS integrated method consists of two stages:the first stage is to measure theDMUs’ relative efficiencyby DEA,and determine the decision alternatives set according to the efficiency values and decision goals.The second stage is to constructthe decision matrix according to the projections of inefficiency DMUs,then rank the alternatives using TOPSIS method.Taking Capital Medical University for example,the organization is assumed,in order to improve its efficiency,intend to increase the numbers of DEA efficient DMUs.Meanwhile the organization’objective is to minimize the slack improvements(i.e.let the revolution easier)during the efficiency improvement.The 10 class1,Grade 3 general affiliation hospitals as the DMUs,we study the technical efficiency by using the DEA-TOPSIS integrated method.2008~2013 is taken as the observation period,and 3 inputs-including the number of employees(person),the purchase of medical equipment gross this year(million yuan)and the number of beds(zhang)-and 1 output-outpatients(person)are selected.The data are derived from the Beijing health Yearbook 2009~2014.The results show that DEA-TOPSIS method can not only rank the alternatives effectively,but also reflect the actual situation by choosing different models or index disposal methods.This research can provide some management ideas and references for similar organizations,such as administrations of hospital,education departments,group corporations,etc.
以文找文
期刊論文
1.
McDonald, J.(2009)。Using least squares and Tobit in second stage DEA efficiency analyses。European Journal of Operational Research,197(2),792-798。
2.
Ebrahimnejad, A.、Tavana, M.、Lotfi, F. H.、Shahverdi, R.、Yousefpour, M.(2014)。A Three-stage Data Envelopment Analysis Model with Application to Banking Industry。Measurement,49,308-319。
3.
Liu, John S.、Lu, Louis Y. Y.、Lu, Wen-Min、Lin, Bruce J. Y.(2013)。A survey of DEA applications。Omega,41(5),893-902。
4.
Zeydan, M.、Çolpan, C.(2009)。A new decision support system for performance measurement using combined fuzzy TOPSIS/DEA approach。International Journal of Production Research,47(15),4327-4349。
5.
王有森、許皓、卞亦文(2016)。工業用水系統效率評價:考慮污染物可處理特性的兩階段DEA。中國管理科學,24(3),169-176。
延伸查詢
6.
Kawaguchi, H.、Tone, K.、Tsutsui, M.(2014)。Estimation of the efficiency of Japanese hospitals using a dynamic and network data envelopment analysis model。Health Care Management Science,17(2),101-112。
7.
曾薇、陳收、周忠寶(2016)。金融監管對商業銀行產品創新影響--基於兩階段DEA模型的研究。中國管理科學,24(5),1-7。
延伸查詢
8.
Haelermans, C.、Ruggiero, J.(2013)。Estimating technical and allocative efficiency in the public sector: A nonparametric analysis of Dutch schools。European Journal of Operational Research,227(1),174-181。
9.
杜娟、霍佳震(2014)。基於數據包絡分析的中國城市創新能力評價。中國管理科學,22(6),85-93。
延伸查詢
10.
陳聚祥、曾培培、陳亞運(2016)。基於DEA的全國中醫類醫療衛生資源配置效率評價。中國衛生統計,33(2),271-273。
延伸查詢
11.
薛輝、鄭中華、謝啓偉(2014)。基於多種DEA模型和Gini準則的效率評價方法--兼對我國高校運營績效的評價。中國管理科學,22(4),98-104。
延伸查詢
12.
Fuentes, R.、Lillo-Banuls, A.(2015)。Smoothed bootstrap Malmquist index based on DEA model to compute productivity of tax offices。Expert Systems with Applications,42(5),2442-2450。
13.
Sueyoshi, T.、Goto, M.(2015)。DEA environmental assessment in time horizon: Radial approach for malmquist index measurement on petroleum companies。Energy Economics,51,329-345。
14.
王曉東(2010)。產業升級和轉移背景下廣東工業行業效率變化實證研究--基於Malmquist指數的分析。預測,2010(4),75-80。
延伸查詢
15.
徐建中、曲小瑜(2015)。裝備製造業環境技術創新效率及其影響因素研究--基於DEA-Malmquist和Tobit的實證分析。運籌與管理,24(1),246-254。
延伸查詢
16.
Samut, P. K.、Cafri, R.(2016)。Analysis of the efficiency determinants of health systems in OECD countries by DEA and panel tobit。Social Indicators Research,129(1),113-132。
17.
Shafii, M.、Hosseini, S. M.、Arab, M.(2016)。Performance analysis of hospital managers using fuzzy AHP and fuzzy TOPSIS: Iranian Experience。Global Journal of Health Science,8(2),137-155。
18.
卞亦文、許皓(2013)。基於虛擬包絡面和TOPSIS的DEA排序方法。系統工程理論與實踐,33(2),482-488。
延伸查詢
19.
朱衛東、吳鵬(2015)。引入TOPSIS法的風險預警模型能提高模型的預警準確度嗎?--來自我國製造業上市公司的經驗證據。中國管理科學,23(11),96-104。
延伸查詢
20.
李美娟、陳國宏、林志炳(2015)。基於理想解法的動態評價方法研究。中國管理科學,23(10),156-161。
延伸查詢
21.
李剛、遲國泰、程硯秋(2011)。基於熵權TOPSIS的人的全面發展評價模型及實證。系統工程學報,26(3),400-407。
延伸查詢
22.
Banker, Rajiv D.、Charnes, Abraham、Cooper, William Wager(1984)。Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis。Management Science,30(9),1078-1092。
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Tone, Kaoru(2001)。A slacks-based measure of efficiency in data envelopment analysis。European Journal of Operational Research,130(3),498-509。
24.
Charnes, Abraham、Cooper, William W.、Rhodes, Edwardo(1978)。Measuring the efficiency of decision making units。European Journal of Operational Research,2(6),429-444。
圖書
1.
魏權齡(2012)。評價相對有效性的數據包絡分析模型:DEA和網絡DEA。北京:中國人民大學出版社。
延伸查詢
2.
Hwang, C. L.、Yoon, K.(1981)。Multiple attribute decision making。New York:Springer Verlag。
3.
岳超源(2003)。決策理論與方法。北京:科學出版社。
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