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Longitudinal analysis of economic clusters: A novel methodology and application of UK regions

Lookup NU author(s): Dr Eric See-To, Professor Savvas PapagiannidisORCiD


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© 2019 International Consortium for Electronic Business. All rights reserved.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.

Publication metadata

Author(s): Olatunji IE, See-To EWK, Papagiannidis S

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of the International Conference on Electronic Business (ICEB)

Year of Conference: 2019

Pages: 570-572

Online publication date: 08/12/2019

Acceptance date: 02/04/2016

ISSN: 1683-0040

Publisher: International Consortium for Electronic Business