How a BI-wise Responsible Integrated Management System May Support Food Traceability
Maria Gianni,
Katerina Gotzamani and
Isabelle Linden
Additional contact information
Maria Gianni: University of Macedonia, Thessaloniki, Greece
Katerina Gotzamani: University of Macedonia, Thessaloniki, Greece
Isabelle Linden: University of Namur, Namur, Belgium
International Journal of Decision Support System Technology (IJDSST), 2016, vol. 8, issue 2, 1-17
Abstract:
Food manufacturers are required to meet certain traceability specifications. This research aims at underscoring the relevant needs and expectations of various stakeholders across the entire food supply chain. In this context, firms' decisions on resource allocation and risk mitigation overlap several domains, such as quality, safety, environment, social responsibility and information. Business Intelligence (BI) platforms are specifically conceived to support analytical decision making by providing a centralised view on multiple distributed data sources. However, BI solutions are usually deployed within a single organization, whilst traceability involves multiple actors with potentially divergent interests and diverse levels of willingness to participate. Along this line of thought, integration of management systems within a company and throughout the overall supply chain is suggested to meet the emerging managerial challenges. After a detailed survey of integrated management systems (IMSs) in food traceability contexts, this research proposes a BI-wise solution using the IMS overarching approach and investigates its success conditions.
Date: 2016
References: Add references at CitEc
Citations:
Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJDSST.2016040101 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:igg:jdsst0:v:8:y:2016:i:2:p:1-17
Access Statistics for this article
International Journal of Decision Support System Technology (IJDSST) is currently edited by Shaofeng Liu
More articles in International Journal of Decision Support System Technology (IJDSST) from IGI Global
Bibliographic data for series maintained by Journal Editor ().