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Authors: Lingzhe Liu 1 ; Hennie Daniels 2 and Ron Triepels 3

Affiliations: 1 Erasmus University, Netherlands ; 2 Erasmus University and Tilburg University, Netherlands ; 3 Tilburg University, Netherlands

Keyword(s): Data Reliablity, Data-level Auditing, Business Intelligence.

Abstract: Data reliability closely relates to the risk management in international logistics. Unreliable data negatively affect the business in various ways. Due to the competence specialization and cooperation among the business partners in a logistics chain, the business in a focal company is inevitably dependent on external data sources from its partner, which is impractical to control. In this paper, we present a research-in-progress on an analysis method with Bayesian networks. The goal is to support auditor’s assessment on the reliability of the external data. A case study is provided to illustrate the merits of Bayesian networks when dealing with the data reliability problem.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Liu, L. ; Daniels, H. and Triepels, R. (2014). Auditing Data Reliability in International Logistics - An Application of Bayesian Networks. In Proceedings of the 16th International Conference on Enterprise Information Systems (ICEIS 2014) - Volume 1: ISS; ISBN 978-989-758-028-4; ISSN 2184-4992, SciTePress, pages 707-712. DOI: 10.5220/0004987507070712

@conference{iss14,
author={Lingzhe Liu and Hennie Daniels and Ron Triepels},
title={Auditing Data Reliability in International Logistics - An Application of Bayesian Networks},
booktitle={Proceedings of the 16th International Conference on Enterprise Information Systems (ICEIS 2014) - Volume 1: ISS},
year={2014},
pages={707-712},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004987507070712},
isbn={978-989-758-028-4},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Enterprise Information Systems (ICEIS 2014) - Volume 1: ISS
TI - Auditing Data Reliability in International Logistics - An Application of Bayesian Networks
SN - 978-989-758-028-4
IS - 2184-4992
AU - Liu, L.
AU - Daniels, H.
AU - Triepels, R.
PY - 2014
SP - 707
EP - 712
DO - 10.5220/0004987507070712
PB - SciTePress

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