Using Data Analytics & Machine Learning to Design Business Interruption Insurance Products for Rail Freight Operators-Reference-Cited by-同舟云学术

Using Data Analytics & Machine Learning to Design Business Interruption Insurance Products for Rail Freight Operators

Published:2021 Issue: Volume:58 Page:393-400
ISSN:2352-1465
Container-title:Transportation Research Procedia
language:en
Short-container-title:Transportation Research Procedia

Author:

Cardona John F.,Castaneda Juliana,Martins Leandro do C.,Gandouz Mariem,Juan Angel A.,Franco Guillermo

Publisher

Elsevier BV

Reference20 articles.

1. Big data in insurance. Beyond experimentation to innovation/M. Breading;BREADING,2014

2. Holt-winters forecasting: some practical issues;CHATFIELD;Journal of the Royal Statistical Society: Series D (The Statistician),1988

3. Managing disruption risk: The interplay between operations and insurance;DONG;Management Science,2012

4. Analytics of insurance markets;FREES;Annual Review of Financial Economics,2015

5. GAGATSI, E; GIANNOPOULOS, G; and AIFANDOPOULOU, G. (2014). Supporting policy making in maritime transport by means of MultiActors multi-criteria analysis: A methodology developed for the Greek maritime transport system. Proceedings of the 5th transport research arena (TRA), April, 14–17.

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