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Supply chain uncertainties linked to information systems: a case study approach.

Authors :
Ruel, Salomée
Ouabouch, Lhoussaine
Shaaban, Sabry
Source :
Industrial Management & Data Systems; 2017, Vol. 117 Issue 6, p1093-1108, 16p
Publication Year :
2017

Abstract

Purpose The purpose of this paper is to study the following research question: how can information systems (ISs) be the real sources of uncertainty for supply chain management (SCM), despite their positive roles in the effectiveness of modern supply chain (SC) organization?Design/methodology/approach A typology of the uncertainties linked to ISs and their usage is developed. Then, five explanatory case studies conducted in diverse industries allow to characterize this typology.Findings The case studies allow to identify the most frequently recurring uncertainties, namely, “limited IS capacity” and “data unreliability.” In addition, “company size” does not seem to be a relevant dimension for assessing the vulnerability of a SC to uncertainties linked to ISs. On the other hand, the “business sector,” with its implied power influences, was found to be a relevant dimension.Research limitations/implications This research does not allow to rank uncertainties according to their level of criticality.Practical implications This paper enables SC and information systems managers, as well as ISs/SC project managers to be aware of the need to consider ISs not only as the vectors for performance, but also as the factors for uncertainty in SCs.Originality/value ISs are generally considered to be a vector of performance. Nevertheless, their use remains problematic in many companies. This paper falls within both the ISs and SCM research areas. In the latter field, typologies of the uncertainties are common, but often ignore the uncertainties linked to ISs and their usage. The authors suggest envisaging ISs as the potential factors for uncertainty in the context of SCM. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02635577
Volume :
117
Issue :
6
Database :
Complementary Index
Journal :
Industrial Management & Data Systems
Publication Type :
Academic Journal
Accession number :
123941512
Full Text :
https://doi.org/10.1108/IMDS-07-2016-0264