Alignment prediction in collaborative networks

• Type: Article in International Scientific Journal
• Date: 2012

Authors

Da Piedade Francisco, R (Author) Other; Azevedo, A (Author) FEUP; Almeida, A (Author) Other

Journal

Title: Journal of Manufacturing Technology Management

Vol. 23

Pages: 1038-1056

ISSN: 1741-038X

Publisher: Emerald

Indexing

ISI Proceedings

ISI Web of Knowledge

Scopus - 16 Citations

Other information

Authenticus ID: P-008-7XV

DOI: 10.1108/17410381211276862

Abstract (EN): Purpose - The purpose of this paper is to study the alignment measurement in collaborative networks, using the fit concept and predictive performance measurement as its main enablers. A performance prediction approach is used in order to control a collaborative business network based not only in present and past performance measurements of each partner, but also taking into account the future behaviour of the intra- and inter-organisational processes performance. Design/methodology/approach - An exploratory case study was applied to a Brazilian collaborative network and mathematical approaches normally used in control theory were adopted to support alignment measurement. Findings - The use of predictive measurements to manage the alignment between the results of inter-organisational processes and performance targets set by the collaborative network. Research limitations/implications - This approach was applied in a specific supply chain network, based on three industrial companies. For other network typologies it will be necessary to evaluate the alignment that can be achieved. Practical implications - This predictive approach makes it possible to manage performance pro-actively using feedforward and feedback control. Therefore, tools that consider performance estimation are used based on a data fusion approach, with a proper combination of leading and lagging measurements, which make it possible to use forecasting methods and tools to achieve good predictions. Originality/value - The paper introduces an approach to alignment measurement leveraged by the new paradigm of performance prediction and presents an alignment metric for collaborative networks. © Emerald Group Publishing Limited.

Language: English

Type (Professor's evaluation): Scientific