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01.07.2005

Chain Quality Information Management – development of a reference model for quality information requirements in pork chains

As in many food chains, pork production is carried out in heterogeneous chain scenarios with diverse organisational arrangements. Inter-organisational information management systems are not yet established in pork production even though they provide a chance to improve chain wide cooperation and quality management.

This article presents the concept and first results of a sub-project in an ongoing Dutch-German collaborative research and development project of the public-private network “GIQS e.V.” that develops tools for improved quality and health management in pork chains. Here, a chain quality information system is designed, implemented and validated in three pilot chains in Germany and the Netherlands. Major result will be a comprehensive implementation guideline for chains that want to improve their use of chain quality information in their quality and health management.

Aim of this study is to identify the main aspects of chain actors’ information requirements taking into account the existing organisational heterogeneity in the pork industry. The theoretical framework of this paper integrates the netchain model with the process approach of ISO 9000:2000. Focus lies in describing a general structure of a chain wide information system. The concept of inter-enterprise data warehousing is adopted for quality management in food chains. Based on this concept, a “natural language” reference model for information requirements in pork netchains is generated. The adaptation of the reference model will be exemplified in one specific pilot implementation with the special focus on improving animal health management and supporting a risk based meat inspection with chain wide information management.

Schulze Althoff, G., Ellebrecht, A. & B. Petersen (2005)

Chain Quality Information Management – development of a reference model for quality information requirements in pork chains, Journal of Chain and Network Science (5) 2005 S. 27 - 38

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