國立虎尾科技大學 |

Product development projects = dynamics and emergent complexity /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Product development projects/ by Christopher Schlick, Bruno Demissie.
Reminder of title:	dynamics and emergent complexity /
Author:	Schlick, Christopher.
other author:	Demissie, Bruno.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	viii, 365 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	New products. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-21717-8
ISBN:	9783319217178

Product development projects = dynamics and emergent complexity /
Schlick, Christopher.

Product development projectsdynamics and emergent complexity /[electronic resource] :by Christopher Schlick, Bruno Demissie. - Cham :Springer International Publishing :2016. - viii, 365 p. :ill., digital ;24 cm. - Understanding complex systems,1860-0832. - Understanding complex systems..

Introduction -- 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.

This 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.

ISBN: 9783319217178

Standard No.: 10.1007/978-3-319-21717-8doiSubjects--Topical Terms:

569440
New products.

LC Class. No.: QA76.9.M35

Dewey Class. No.: 620

Product development projects = dynamics and emergent complexity /
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520 $a This 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.
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