Longitudinal Analysis of Economic Clusters: A Novel Methodology and Application of UK Regions

Lyiola E. OLATUNJI*, Wing Kuen Eric SEE-TO, Savvas PAPAGIANNIDIS

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)

Abstract

Standard Industrial Classification (SIC) classify organizations based on their business activities. However, choosing appropriate SIC code that represents an organization’s business activities in a challenging task. In the UK, there are almost 100 categories each having several subcategories of predefined business activities designed by experts. However, such scheme cannot cater for emerging business needs while some organizations cannot be easily defined by a single SIC code, due to the complexity of their business nature. Similarly, if a company expands or changes its operation during the year, a new SIC code needs to be assigned. This results in organizations having difficulties picking representative SIC code to use in defining their business activities. In this paper, we propose a dynamic framework that can automatically group organizations based on their business activities. Our framework leverages techniques from topic modelling. Result shows that our proposed framework can automatically adapt to changing business needs and cluster organizations effectively.

Original languageEnglish
Title of host publicationProceedings of the 19th International Conference on Electronic Business : ICEB, Newcastle upon Tyne, U.K., December 8-12
EditorsEldon Y. LI, Honglei LI
PublisherAssociation for Information Systems
Pages570-572
Number of pages3
Volume2019-December
Publication statusPublished - Dec 2019
Event19th International Conference on Electronic Business, ICEB 2019 - Newcastle upon Tyne, United Kingdom
Duration: 8 Dec 201912 Dec 2019

Publication series

NameProceedings of International Conference on Electronic Business (ICEB)
Volume2019
ISSN (Print)1683-0040

Conference

Conference19th International Conference on Electronic Business, ICEB 2019
CountryUnited Kingdom
CityNewcastle upon Tyne
Period8/12/1912/12/19

Keywords

  • Big data analytics
  • Longitudinal analysis
  • Standard industrial classification
  • Topic modelling

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    OLATUNJI, L. E., SEE-TO, W. K. E., & PAPAGIANNIDIS, S. (2019). Longitudinal Analysis of Economic Clusters: A Novel Methodology and Application of UK Regions. In E. Y. LI, & H. LI (Eds.), Proceedings of the 19th International Conference on Electronic Business : ICEB, Newcastle upon Tyne, U.K., December 8-12 (Vol. 2019-December, pp. 570-572). (Proceedings of International Conference on Electronic Business (ICEB); Vol. 2019). Association for Information Systems. https://aisel.aisnet.org/iceb2019/64