Data science and big data analytics: a systematic review of methodologies used in the supply chain and logistics research

H Jahani, R Jain, D Ivanov - Annals of Operations Research, 2023‏ - Springer
Data science and big data analytics (DS &BDA) methodologies and tools are used
extensively in supply chains and logistics (SC &L). However, the existing insights are …

Outcome-oriented predictive process monitoring: Review and benchmark

I Teinemaa, M Dumas, ML Rosa… - ACM Transactions on …, 2019‏ - dl.acm.org
Predictive business process monitoring refers to the act of making predictions about the
future state of ongoing cases of a business process, based on their incomplete execution …

Predictive business process monitoring with LSTM neural networks

N Tax, I Verenich, M La Rosa, M Dumas - Advanced Information Systems …, 2017‏ - Springer
Predictive business process monitoring methods exploit logs of completed cases of a
process in order to make predictions about running cases thereof. Existing methods in this …

[HTML][HTML] Utilizing machine learning on freight transportation and logistics applications: A review

K Tsolaki, T Vafeiadis, A Nizamis, D Ioannidis… - ICT Express, 2023‏ - Elsevier
This review article explores and locates the current state-of-the-art related to application
areas from freight transportation, supply chain and logistics that focuses on arrival time …

Predictive monitoring of business processes: a survey

AE Márquez-Chamorro, M Resinas… - IEEE Transactions on …, 2017‏ - ieeexplore.ieee.org
Nowadays, process mining is becoming a growing area of interest in business process
management (BPM). Process mining consists in the extraction of information from the event …

Machine learning in business process monitoring: a comparison of deep learning and classical approaches used for outcome prediction

W Kratsch, J Manderscheid, M Röglinger… - Business & Information …, 2021‏ - Springer
Predictive process monitoring aims at forecasting the behavior, performance, and outcomes
of business processes at runtime. It helps identify problems before they occur and re …

Predictive process monitoring methods: Which one suits me best?

C Di Francescomarino, C Ghidini, FM Maggi… - … conference on business …, 2018‏ - Springer
Predictive process monitoring has recently gained traction in academia and is maturing also
in companies. However, with the growing body of research, it might be daunting for data …

Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring

I Verenich, M Dumas, ML Rosa, FM Maggi… - ACM Transactions on …, 2019‏ - dl.acm.org
Predictive business process monitoring methods exploit historical process execution logs to
generate predictions about running instances (called cases) of a business process, such as …

Impact of big data on supply chain management

S Raman, N Patwa, I Niranjan, U Ranjan… - … Journal of Logistics …, 2018‏ - Taylor & Francis
This study focuses on big data, which offer new opportunities, added value and operational
excellence for existing supply chain practices. A survey was conducted among employees of …

Clustering-based predictive process monitoring

C Di Francescomarino, M Dumas… - IEEE transactions on …, 2016‏ - ieeexplore.ieee.org
The enactment of business processes is generally supported by information systems that
record data about each process execution (aka case). This data can be analyzed via a …