Service Performance Assessment: A PI Toolset Methodology for VEs View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2014

AUTHORS

Alessandra Carosi , Mohammadreza Heydari , Christian Zanetti , Marco Taisch , Yves Ducq

ABSTRACT

Nowadays service sector is becoming more and more relevant in building successful collaborative economies. In this environment Virtual Enterprises (VEs) are forcing a change in the way traditional manufacturing systems are managed. Therefore measuring service performances plays an important role in turning company strategic goals into reality. Performance Indicators (PIs) consist in a supporting tool to assess service efficiency and effectiveness. Consequently, determining the most significant activities which need to be controlled and measured through proper PIs becomes essential. Within this paper, a PI Toolset is going to be presented and tested through industrial use case. The PI Toolset has been developed to support VEs in selecting significant activities, to manage governance processes and to support the design and implementation of specific PIs related to the precise use case objectives. Finally, a lesson learnt approach has been adopted so to stress strengths and weaknesses of both proposed methodology and tools. More... »

PAGES

691-698

Book

TITLE

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

ISBN

978-3-319-12567-1
978-3-319-12568-8

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-662-44736-9_84

DOI

http://dx.doi.org/10.1007/978-3-662-44736-9_84

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1036248701


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