Digital Transformation of Supply Chain Management - Challenges and Strategies for Successfully Implementing Data Analytics in Practice
Author:
Affiliation:
1. Logistikum, University of Applied Sciences Upper Austria, Austria
Funder
Christian Doppler Forschungsgesellschaft
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3675585.3675592
Reference42 articles.
1. Brandtner P. Predictive Analytics and Intelligent Decision Support Systems in Supply Chain Risk Management—Research Directions for Future Studies. In: Yang X-S, Sherratt S, Dey N, Joshi A, editors. Proceedings of Seventh International Congress on Information and Communication Technology, vol. 464. Singapore: Springer Nature Singapore; 2023. pp. 549–558.
2. Saravanan N Olivares-Aguila J Vital-Soto A. Bibliometric and Text Analytics Approaches to Review COVID-19 Impacts on Supply Chains. Sustainability. 2022; https://doi.org/10.3390/su142315943
3. Proposals for Addressing Research Gaps at the Intersection of Data Analytics and Supply Chain Management
4. Applications of Big Data Analytics in Supply Chain Management: Findings from Expert Interviews
5. Al. RME, Gilkey J. The challenges and realities of retailing in a COVID-19 world: Identifying trending and Vital During Crisis keywords during Covid-19 using Machine Learning (Austria as a case study): arXiv; 2021.
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