A Machine-Learning Analysis of the Impacts of the COVID-19 Pandemic on Small Business Owners and Implications for Canadian Government Policy Response.

Journal: Canadian public policy. Analyse de politiques

Volume: 48

Issue: 2

Year of Publication: 

Affiliated Institutions:  Sprott School of Business, Carleton University, Ottawa, Ontario, Canada, and Department of Business Management, School of Management, University of Johannesburg, Johannesburg, South Africa. Faculty of Business Administration, University of Regina, Regina, Saskatchewan, Canada. Sprott School of Business, Carleton University, Ottawa, Ontario, Canada.

Abstract summary 

This study applies a machine-learning technique to a dataset of 38,000 textual comments from Canadian small business owners on the impacts of coronavirus disease 2019 (COVID-19). Topic modelling revealed seven topics covering the short- and longer-term impacts of the pandemic, government relief programs and loan eligibility issues, mental health, and other impacts on business owners. The results emphasize the importance of policy response in aiding small business crisis management and offer implications for theory and policy. Moreover, the study provides an example of using a machine-learning-based automated content analysis in the fields of crisis management, small business, and public policy.

Authors & Co-authors:  Isabelle Diane A DA Han Yu Jade YJ Westerlund Mika M

Study Outcome 

Source Link: Visit source

Statistics
Citations :  Asgary, A., Anjum M.I., and Azimi N.. 2012. “Disaster Recovery and Business Continuity after the 2010 Flood in Pakistan: Case of Small Businesses.” International Journal of Disaster Risk Reduction 2:46–56. 10.1016/j.ijdrr.2012.08.001.
Authors :  3
Identifiers
Doi : 10.3138/cpp.2021-018
SSN : 0317-0861
Study Population
Male,Female
Mesh Terms
Other Terms
COVID-19 crisis management;Canada;impacts;small business;topic modelling
Study Design
Cross Sectional Study
Study Approach
Country of Study
Publication Country
Canada