Methodological Demonstration of a Text Analytics Approach to Country Logistics System Assessments

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Abstract

The purpose of this study is to develop and demonstrate a semi-automated text analytics approach for the identification and categorization of information that can be used for country logistics assessments. In this paper, we develop the methodology on a set of documents for 21 countries using machine learning techniques while controlling both for 4 different time periods in the world FDI trends, and the different geographic and economic country affiliations. We report illustrative findings followed by a presentation of the separation of concerns/division of labor between the domain expert and the text analyst. Implications are discussed and future work is outlined.
Original languageEnglish
Title of host publicationDynamics in Logistics : Proceedings of the 5th International Conference LDIC, 2016 Bremen, Germany
EditorsMichael Freitag, Herbert Kotzab, Jürgen Pannek
Place of PublicationCham
PublisherSpringer
Publication date2017
Pages119-129
Chapter11
ISBN (Print)9783319451169
ISBN (Electronic)9783319451176
DOIs
Publication statusPublished - 2017
EventThe 5th International Conference on Dynamics in Logistics. LDIC 2016 - Bremen, Germany
Duration: 22 Feb 201625 Feb 2016
Conference number: 5
http://www.ldic-conference.org/

Conference

ConferenceThe 5th International Conference on Dynamics in Logistics. LDIC 2016
Number5
CountryGermany
CityBremen
Period22/02/201625/02/2016
Internet address
SeriesLecture Notes in Logistics
ISSN2194-8917

Keywords

  • Logistics
  • Transport system evaluation
  • Big data analytics
  • Data mining
  • Text mining
  • Machine learning

Cite this

Kinra, A., Mukkamala, R. R., & Vatrapu, R. (2017). Methodological Demonstration of a Text Analytics Approach to Country Logistics System Assessments. In M. Freitag, H. Kotzab, & J. Pannek (Eds.), Dynamics in Logistics: Proceedings of the 5th International Conference LDIC, 2016 Bremen, Germany (pp. 119-129). Springer. Lecture Notes in Logistics https://doi.org/10.1007/978-3-319-45117-6_11