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E-commerce localisation to African markets : Canadian multinational enterprise perspectives
Journal of Cultural Marketing Strategy,
7
(2),
134-145
(2023)
Abstract
The main objective of this study is to examine and analyse the extent to which African cultural values are depicted on local business-to-consumer (B2C) websites in Africa compared with local websites in Canada during and after the COVID-19 era. By exploring the cross-cultural variations between African B2C websites and Canadian B2C websites, we attempt to provide recommendations to global marketers and diverse stakeholders on how best to localise their websites when catering to e-commerce internet users in African and Canadian regional economies. Therefore, this research extends the boundary of e-commerce marketing strategy and international marketing research to encompass the perspectives of Canadian multinational enterprises seeking to market to African regions.
Keywords: e-commerce; localisation; websites; cultural values; Canadian multinational enterprises; Africa; COVID-19
The full article is available to subscribers to the journal.
Author's Biography
Wootae Chun is an Associate Professor of Marketing at the University of Northern British Columbia. His research interests include, among other things, international business, international marketing, e-commerce, cross-cultural marketing, and social media marketing. He holds a PhD in international business and marketing from Saint Louis University, an MBA from the University of Texas–Pan American, and a BS in business administration from the Ohio State University.
Emmanuel Ogwal is the Economic Development & Natural Resources Coordinator at Lheidli T’enneh Nation. He holds a Master of Arts Degree in Economic Development from the University of Northern British Columbia. He also holds Professional Data Science Certification from the University of Waterloo and the University of Toronto. He has previously worked as a deemed employee for Statistics Canada and has access to the Canadian Research Data Centre Network Data. His research interests include econometrics, marketing, machine learning and predictive modelling.
