000 04353nam a22005055i 4500
001 vtls000543308
003 RU-ToGU
005 20210922082707.0
007 cr nn 008mamaa
008 160915s2014 gw | s |||| 0|eng d
020 _a9783319066479
_9978-3-319-06647-9
024 7 _a10.1007/978-3-319-06647-9
_2doi
035 _ato000543308
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aHD30.23
072 7 _aKJT
_2bicssc
072 7 _aKJMD
_2bicssc
072 7 _aBUS049000
_2bisacsh
082 0 4 _a658.40301
_223
100 1 _aZhu, Joe.
_eauthor.
_9303806
245 1 0 _aQuantitative Models for Performance Evaluation and Benchmarking
_helectronic resource
_bData Envelopment Analysis with Spreadsheets /
_cby Joe Zhu.
250 _a3.
260 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXVIII, 414 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v213
505 0 _aChapter 1: Data Envelopment Analysis -- Chapter 2: Envelopment DEA Models -- Chapter 3: Multiplier DEA Model -- Chapter 4: DEA Cross Efficiency -- Chapter 5: Slack-Based DEA Models -- Chapter 6: Measure-Specific DEA Models.- Chapter 7: Non-radical DEA Models and DEA with Preference -- Chapter 8: Modeling Undesirable Measures -- Chapter 9: Context-dependent Data Envelopment Analysis -- Chapter 10: Super Efficiency -- Chapter 11: Sensitivity Analysis -- Chapter 12: Benchmarking Models -- Chapter 13: Returns-to-Scale -- Chapter 14: DEA Models for Two-Stage Network Processes -- Chapter 15: Models for Evaluating Supply Chains and Network Structures -- Chapter 16: Congestion.- Chapter 17: Identifying Critical Measures in DEA.- Chapter 18: Interval and Ordinal Data in DEA.- Chapter 19: DEAFrontier Software.
520 _aBased upon the author’s years of research and teaching experiences, this 3rd Edition introduces Data Envelopment Analysis (DEA) as a data analysis tool for multiple-measure performance evaluation and benchmarking. The focus of performance evaluation and benchmarking is shifted from characterizing performance in terms of single measures to evaluating performance as a multidimensional systems perspective. Conventional and new DEA approaches are presented and discussed using Excel spreadsheets — one of the most effective ways to analyze and evaluate decision alternatives. The user can easily develop and customize new DEA models based upon these spreadsheets. DEA models and approaches are presented to deal with performance evaluation problems in a variety of contexts. For example, a context-dependent DEA measures the relative attractiveness of similar operations/processes/products. Sensitivity analysis techniques can be easily applied, and used to identify critical performance measures. Two-stage network efficiency models can be utilized to study performance of supply chain. DEA benchmarking models extend DEA’s ability in performance evaluation. Various cross efficiency approaches are presented to provide peer evaluation scores. This book also provides an easy-to-use DEA software — DEAFrontier. This DEAFrontier is an Add-In for Microsoft® Excel and provides a custom menu of DEA approaches. This version of DEAFrontier is for use with Excel 97-2013 under Windows and can solve up to 50 DMUs, subject to the capacity of Excel Solver.
650 0 _aEconomics.
_9135154
650 0 _aIndustrial engineering.
_9303056
650 0 _aOperations research.
_9303058
650 1 4 _aEconomics/Management Science.
_9247365
650 2 4 _aOperation Research/Decision Theory.
_9411428
650 2 4 _aOperations Research, Management Science.
_9353130
650 2 4 _aIndustrial and Production Engineering.
_9303059
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
830 0 _aInternational Series in Operations Research & Management Science,
_9303329
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-06647-9
912 _aZDB-2-SBE
999 _c401188