TY - GEN
T1 - Predictive Analytics and Intelligent Decision Support Systems in Supply Chain Risk Management—Research Directions for Future Studies
AU - Brandtner, Patrick
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - Today’s supply chains (SC) are immersed in extremely dynamic environments, and supply chain management (SCM) has to deal with a multitude of risks. The domain of supply chain risk management (SCRM) has emerged, providing approaches on how to cope with risks in SC. However, due to increased complexity, volatility, and uncertainty, the number of risks in global SC has increased significantly. Harnessing the power of predictive analytics (PA), implemented in intelligent decision support systems (IDSS), offers huge potential in SCRM. However, research at the intersection of the domains of SCRM, PA, and IDSS is still in its infancy, and several research gaps have yet to be addressed. The paper elaborates on these research gaps by means of a systematic literature review. The results include a set of seven research questions and proposed research directions for future studies. Future research is presented with a plethora of starting points, which originate from the business perspective (i.e., the SCRM domain), the data-driven (i.e., the PA domain) as well as an IT-system perspective (i.e., the IDSS domain).
AB - Today’s supply chains (SC) are immersed in extremely dynamic environments, and supply chain management (SCM) has to deal with a multitude of risks. The domain of supply chain risk management (SCRM) has emerged, providing approaches on how to cope with risks in SC. However, due to increased complexity, volatility, and uncertainty, the number of risks in global SC has increased significantly. Harnessing the power of predictive analytics (PA), implemented in intelligent decision support systems (IDSS), offers huge potential in SCRM. However, research at the intersection of the domains of SCRM, PA, and IDSS is still in its infancy, and several research gaps have yet to be addressed. The paper elaborates on these research gaps by means of a systematic literature review. The results include a set of seven research questions and proposed research directions for future studies. Future research is presented with a plethora of starting points, which originate from the business perspective (i.e., the SCRM domain), the data-driven (i.e., the PA domain) as well as an IT-system perspective (i.e., the IDSS domain).
KW - Decision support
KW - Predictive analytics
KW - Supply chain management
KW - Supply chain risk management
UR - http://www.scopus.com/inward/record.url?scp=85135057707&partnerID=8YFLogxK
U2 - 10.1007/978-981-19-2394-4_50
DO - 10.1007/978-981-19-2394-4_50
M3 - Conference contribution
AN - SCOPUS:85135057707
SN - 9789811923937
T3 - Lecture Notes in Networks and Systems
SP - 549
EP - 558
BT - Proceedings of 7th International Congress on Information and Communication Technology, ICICT 2022
A2 - Yang, Xin-She
A2 - Sherratt, Simon
A2 - Dey, Nilanjan
A2 - Joshi, Amit
PB - Springer
T2 - 7th International Congress on Information and Communication Technology, ICICT 2022
Y2 - 21 February 2022 through 24 February 2022
ER -