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

Authors

Iyiolai E. Olatunj, The Chinese University of Hong KongFollow
Wing Kuen, Eric SEE-TO, Faculty of Business, Lingnan University, Hong KongFollow
Savvas Papagiannidis, Newcastle University Business School, Newcastle University, Newcastle upon Tyne, UK.Follow

Corresponding Author

Iyiola E. Olatunji, The Chinese University of Hong Kong, iyiola@link.cuhk.edu.hk

Document Type

Abstract

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.

Recommended Citation

Olatunj, Iyiolai E.; SEE-TO, Wing Kuen, Eric; and Papagiannidis, Savvas, "Longitudinal Analysis of Economic Clusters: A Novel Methodology and Application of UK Regions" (2019). ICEB 2019 Proceedings (Newcastle Upon Tyne, UK). 64.
https://aisel.aisnet.org/iceb2019/64