Evaluating the Efficiency of Lean Management Projects Using Data Envelopment Analysis

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dc.contributor.authorPelloneová Nataliecs
dc.contributor.authorŠtichhauerová Evacs
dc.date.accessioned2018-09-25T12:14:10Z
dc.date.available2018-09-25T12:14:10Z
dc.date.issued2018cs
dc.description.abstractThis paper describes approach to evaluate and compare efficiency of lean management projects, using a set of techniques known as Data Envelopment Analysis. DEA is a non-parametric linear programming method used to the efficiency evaluation of decision making units. Lean methods have been widely used as a tool for improving operational performance and also have been successfully implemented in many manufacturing and non-manufacturing organizations. This paper aims to develop a mathematical model to evaluate the efficiency of lean management projects. Paper provides the identi?cation of important inputs and outputs for projects that are then analysed using DEA. Working with planned indicators values, this model helps to identify one or more projects that result in the maximum bene?t to the organization. Using the real indicators values after implementation of a project, it can help to determine how the project was successful as compared with similar implemented projects.en
dc.format.extent8cs
dc.identifier.doi10.17973/MMSJ.2018_03_2017112
dc.identifier.issn1805-0476cs
dc.identifier.urihttps://dspace.tul.cz/handle/15240/31215
dc.identifier.urihttp://www.mmscience.eu/2017112
dc.language.isoengcs
dc.publisher.cityPrahacs
dc.relation.ispartofseries0cs
dc.relation.urihttp://www.mmscience.eu/2017112cs
dc.rights.otherMM Science Journal http://www.mmscience.eu/en/submissions
dc.subjectproject successcs
dc.subjecttechnical efficiencyen
dc.subjectproject successen
dc.subjectproject efficiencyen
dc.subjectlean management projecten
dc.subjectdata envelopment analysisen
dc.titleEvaluating the Efficiency of Lean Management Projects Using Data Envelopment Analysisen
dc.titleEvaluating the Efficiency of Lean Management Projects Using Data Envelopment Analysiscs
local.identifier.publikace4676
local.relation.issue1cs
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