Artificial Intelligence-Augmented Decision Making in Supply Chain Monitoring: An Action Design Research Study

European Conference on Information Systems 2023 Research Papers https://aisel.aisnet.org/ecis2023_rp/282/

18 Pages Posted: 1 May 2023 Last revised: 26 May 2023

See all articles by Savindu Herath Pathirannehelage

Savindu Herath Pathirannehelage

ETH Zurich

Johann Gunnar Johannsson

ETH Zurich

Yash Raj Shrestha

University of Lausanne - Faculty of Business and Economics (HEC Lausanne)

Georg von Krogh

ETH Zurich

Date Written: November 17, 2022

Abstract

Organizations are progressively adopting hybrid human-artificial intelligence (AI) systems in decisionmaking processes, with human decisions being augmented by AI insights. Among the promising AI applications in supply chain monitoring (SCMo) are predictive maintenance systems that predict potential device failures and augment maintenance decisions, allowing for timely and efficient interventions. Despite the growing proliferation of such systems, prescriptive knowledge encompassing technical, business, and organizational aspects on how to design, develop, and deploy them in actual operational environments remains limited. To address this shortcoming of evidence-based design principles in practice, our action design research developed a predictive maintenance system that predicts SCMo device failures and augments the maintenance decisions about those devices. By doing so, we outline generalizable design principles to guide prospective predictive maintenance systems in SCMo.

Keywords: AI-augmented decision making, Supply chain monitoring, Design principles, Action design research

Suggested Citation

Herath Pathirannehelage, Savindu and Johannsson, Johann Gunnar and Shrestha, Yash Raj and von Krogh, Georg, Artificial Intelligence-Augmented Decision Making in Supply Chain Monitoring: An Action Design Research Study (November 17, 2022). European Conference on Information Systems 2023 Research Papers https://aisel.aisnet.org/ecis2023_rp/282/, Available at SSRN: https://ssrn.com/abstract=4422594

Savindu Herath Pathirannehelage (Contact Author)

ETH Zurich ( email )

WEV
Weinbergstrasse 56/58
Zurich, Zürich 8092
Switzerland

Johann Gunnar Johannsson

ETH Zurich ( email )

ETH-Zentrum
Zurich, CH-8092
Switzerland

Yash Raj Shrestha

University of Lausanne - Faculty of Business and Economics (HEC Lausanne) ( email )

Switzerland

Georg Von Krogh

ETH Zurich ( email )

D-MTEC, SMI, WEV J 411
Weinbergstrasse 56/58
Zurich, 8092
Switzerland
+41 44 632 88 50 (Phone)

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
244
Abstract Views
815
Rank
245,605
PlumX Metrics