Using a support vector machine to determine loyalty in African, European, and North American telecoms

Clene Mohlala; Felix Bankole

doi:10.3389/frma.2022.1025303

Using a support vector machine to determine loyalty in African, European, and North American telecoms

Front Res Metr Anal. 2022 Dec 21:7:1025303. doi: 10.3389/frma.2022.1025303. eCollection 2022.

Authors

Clene Mohlala¹, Felix Bankole¹

Affiliation

¹ School of Computing, University of South Africa, Pretoria, South Africa.

Abstract

Brand loyalty is seen as a repeat purchase and the ability to recommend services or products. Telecommunication service providers require loyal customers to stay in business. The current study examines the impact of brand function and corporate image on customer loyalty in the telecommunication industry. The research employed a total of 971 responses from an anonymous online survey of telecommunication customers in Africa, Europe, and North America. Employing partial least squares, the study examined the relationships between brand function, corporate image, and loyalty. The result showed that brand function and corporate image have a significant positive effect on customer satisfaction. In addition, a machine learning algorithm was used to model the best prediction for consumer recommendations of products and services provided by their telecommunication service provider to friends and family.

Keywords: brand engineering; brand science; computing; data science; loyalty; support vector machine; telecommunications.