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  4. Managing Supplier Delivery Reliability Risk under Limited Information: Foundations for a Human-in-the-Loop DSS
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Managing Supplier Delivery Reliability Risk under Limited Information: Foundations for a Human-in-the-Loop DSS

Journal
Decision Support Systems
ISSN
0167-9236
ISSN-Digital
1873-5797
Type
journal article
Date Issued
2013-01-01
Author(s)
Pinto, Roberto
;
Mettler, Tobias  
;
Taisch, Marco
DOI
10.1016/j.dss.2012.10.033
Research Team
IWI1
Abstract
The potential impact of suppliers' delivery reliability issues in many industries requires a proper decision support system (DSS) that allows decision makers to analyze and reduce the delays detrimental effects. Despite the relevance of the topic, companies are often confronted with the lack of historical, quantitative data and knowledge about a suppliers performance (i.e., when selecting a new supplier). In this paper, we address the problem of the scarcity of quantitative data by considering and extending the human-in-the-loop DSS concept, which accounts for an experts knowledge and experience. In our concept, a human expert is involved in making and revising data provided by a computational model, with the aim of supporting companies in making decisions when dealing with unreliable suppliers, in order to minimize the costs related to external discontinuities. To deal with scant quantitative data, we developed a distribution-free model. Our findings positively support the distribution-free approach as an effective tool to be used when only a limited and perhaps unstructured base of data is available. The presented computational model aims at creating a solid foundation for developing a comprehensive human-in-the-loop decision support system.
Funding(s)
Health Network Engineering  
Language
English
HSG Classification
not classified
Refereed
Yes
Publisher
Elsevier
Publisher place
Amsterdam
Volume
54
Number
2
Start page
1076
End page
1084
Pages
9
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/89767
Subject(s)

information managemen...

Division(s)

IWI - Institute of In...

Eprints ID
218964
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