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2018 | 28 | nr 3 | 63--76
Tytuł artykułu

Efficiency Measurement in Dynamic Two-Stage Network Structures with Flexible Intermediate Materials

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Data envelopment analysis (DEA) is a nonparametric method for evaluating the relative efficiency of decision making units (DMUs) described by multiple inputs and multiple outputs. Since DEA was introduced in the 1970s, it has been widely applied to measure the efficiency of a wide variety of production and operation systems, including two-stage production systems with a series or parallel structure. The outputs from the first stage to the next stage are called intermediate factors (or measures). In some real applications, an intermediate material or some part of it can become the final output or input to the second stage of production. Previously existing models cannot be employed directly to measure the efficiency of such systems. The authors introduce a dynamic DEA model that identifies the structure of flexible intermediate factors to maximise the measure of overall system efficiency. (original abstract)
Rocznik
Tom
28
Numer
Strony
63--76
Opis fizyczny
Twórcy
  • Islamic Azad University, Lahidjan, Iran
  • Islamic Azad University, Lahidjan, Iran
  • Islamic Azad University, Tehran, Iran
  • Islamic Azad University, Rasht, Iran
Bibliografia
  • [1] AMIRTEIMOORI A., EMROUZNEJAD A., Flexible measures in production process. A DEA-based approach, RAIRO Oper. Res., 2011, 45, 63-74.
  • [2] AMIRTEIMOORI A., EMROUZNEJAD A., KHOSHANDAM L., Classifying flexible measures in data envelopment analysis. A slack-based measure, Measurement, 2013, 46, 4100-4107.
  • [3] CHARNES A., COOPER W.W., RHODES E., Measuring the efficiency of decision making units, Eur. J. Oper. Res., 1978, 2, 429-444.
  • [4] CHEN Y., COOK W.D., LI N., ZHU J., Additive efficiency decomposition in two-stage DEA, Eur. J. Oper. Res., 2009, 196, 1170-1176.
  • [5] CHEN Y., COOK W.D., ZHU J., Deriving the DEA frontier for two-stage DEA processes, Eur. J. Oper. Res., 2010, 202, 138-142.
  • [6] CHEN Y., LIANG L., ZHU J., Equivalence in two-stage DEA approaches, Eur. J. Oper. Res., 2009, 193 (2), 600-604.
  • [7] CHEN Y., ZHU J., Measuring information technology's indirect impact on firm performance, Inform. Technol. Manage., 2004, 5 (1-2), 9-22.
  • [8] COOK W.D., BALA K., Performance measurement with classification information. An enhanced additive DEA model, Omega, 2003, 31 (6), 439-450.
  • [9] COOK W.D., ZHU J., Classifying inputs and outputs in data envelopment analysis, Eur. J. Oper. Res., 2007, 180, 692-699.
  • [10] EBRAHIMNEJAD A., TAVANA M., HOSSEINZADEH LOTFI F., SHAHVERDI R., YOUSEFPOUR M., A three-stage data envelopment analysis model with application to banking industry, Measurement, 2014, 14, 308-319.
  • [11] FARRELL M.J., The measurement of productive efficiency, J. Royal Stat. Soc., 1957, 120, 253-290.
  • [12] KAO C., HWANG S.N., Efficiency decomposition in two-stage data envelopment analysis. An application to non-life insurance companies in Taiwan, Eur. J. Oper. Res., 2008, 185, 418-429.
  • [13] KORDROSTAMI S., JAHANI SAYYAD NOVEIRI M., Evaluating the efficiency of decision making units in the presence of flexible and negative data, Indian J. Sci. Technol., 2012, 5 (12), 3776-3782.
  • [14] MA J., A two-stage DEA model considering shared inputs and free intermediate measures, Expert Syst. Appl., 2015, 42 (9), 4339-4347.
  • [15] SEIFORD L.M., ZHU J., Profitability and marketability of the Top 55 US commercial banks, Manage. Sci., 1999, 45 (9), 1270-1288.
  • [16] TOLOO M., On classifying inputs and outputs in DEA. A revised model, Eur. J. Oper. Res., 2009, 198, 358-360.
  • [17] ZHU J., Quantitative models for performance evaluation and benchmarking. Data envelopment analysis with spreadsheets, Kluwer Academic Publishers, Boston 2003.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171532250

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