000 04002nam a22005895i 4500
001 978-3-319-21717-8
003 DE-He213
005 20160615101108.0
007 cr nn 008mamaa
008 151012s2016 gw | s |||| 0|eng d
020 _a9783319217178
_9978-3-319-21717-8
024 7 _a10.1007/978-3-319-21717-8
_2doi
049 _aAlfaisal Main Library
050 4 _aQA76.9.M35
072 7 _aGPFC
_2bicssc
072 7 _aTEC000000
_2bisacsh
082 0 4 _a620
_223
100 1 _aSchlick, Christopher.
_eauthor.
245 1 0 _aProduct Development Projects
_h[electronic resource] :
_bDynamics and Emergent Complexity /
_cby Christopher Schlick, Bruno Demissie.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aVIII, 365 p. 56 illus., 50 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aUnderstanding Complex Systems,
_x1860-0832
505 0 _aIntroduction -- Mathematical Models of Cooperative Work in Product Development Projects -- Evaluation of Complexity in product development -- model-driven Evaluation of the Emergent Complexity of Cooperative Work based on Effective Measure Complexity -- Validity Analysis of Selected Closed-Form Solutions for Effective Measure Complexity -- Conclusions and Outlook.
520 _aThis book primarily explores two topics: the representation of simultaneous, cooperative work processes in product development projects with the help of statistical models, and the assessment of their emergent complexity using a metric from theoretical physics (Effective Measure Complexity, EMC). It is intended to promote more effective management of development projects by shifting the focus from the structural complexity of the product being developed to the dynamic complexity of the development processes involved. The book is divided into four main parts, the first of which provides an introduction to vector autoregression models, periodic vector autoregression models and linear dynamical systems for modeling cooperative work in product development projects. The second part presents theoretical approaches for assessing complexity in the product development environment, while the third highlights and explains closed-form solutions for the complexity metric EMC for vector autoregression models and linear dynamical systems. Lastly, part four validates the models and methods using a case study from the industry, together with several Monte Carlo experiments. Presenting a truly unique, integrated treatment of statistical approaches for modeling simultaneous, cooperative work processes in product development projects and assessing their complexity, the book offers a valuable resource for researchers in Industrial Engineering, Engineering Management and Project Management, as well as Project Managers seeking to model and evaluate their own development projects.
650 0 _aEngineering.
650 0 _aOperations research.
650 0 _aManagement science.
650 0 _aComplexity, Computational.
650 0 _aEngineering design.
650 0 _aEngineering economics.
650 0 _aEngineering economy.
650 1 4 _aEngineering.
650 2 4 _aComplexity.
650 2 4 _aOperations Research, Management Science.
650 2 4 _aEngineering Design.
650 2 4 _aEngineering Economics, Organization, Logistics, Marketing.
655 7 _aElectronic books.
_2local
700 1 _aDemissie, Bruno.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319217161
830 0 _aUnderstanding Complex Systems,
_x1860-0832
856 4 0 _uhttp://ezproxy.alfaisal.edu/login?url=http://dx.doi.org/10.1007/978-3-319-21717-8
912 _aZDB-2-ENG
942 _2lcc
_cEBOOKS
999 _c257973
_d257973