Social Media marketing

Article Authors: Cliff R. Kikawa, Charity Kiconco, Moses Agaba, Dimas Ntirampeba, Amos Ssematimba and Billy M. Kalema


Thanks to the ongoing expansion of internet access and, most recently, the movement restrictions that were put in place globally to stop COVID-19 spread, many small and medium enterprises (SMEs) are prepared to use social media platforms to market their products as a way to improve their business performance in emerging economies. Businesses at all levels that use social media marketing (SMM) see a considerable increase in their output. This study’s objective is to identify the factors that significantly help Ugandan SMEs implement SMM techniques to enhance their commercial performance. Here, statistical models are utilized to analyze how the age and gender of SMEs owners as moderating variables affect the adoption and performance of SMEs in Uganda. A theoretical model that is based on the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT) theories has been put out as part of a specific conceptual framework. The following indicators are used to evaluate the performance of SMEs: sales, customer engagement, awareness of customers’ needs, low operation costs, and brand modification by staff. Empirical model validation has been performed using 152 business units (observation units) corresponding to the number of respondents (units of analysis), and the ensuing analyses have been done using structural equation modelling (SEM). The results indicate that compatibility and perceived ease of use have a positive impact on SMEs to adopt SMM, while perceived usefulness has a negative impact on SMEs to adopt SMM. Age and gender as moderating variables all have a positive moderating effect. With limited studies available on the subject, this research contributes to already existing literature by combining two components of the TAM model and one component of the IDT to explain the impact of SMM on SMEs when moderated by both age and gender in a developing economy

Bibliographical metadata

Related Faculties/Schools

Department of Economics and Statistics, Kabale University, Kabale P.O. Box 317, Uganda
2 Department of Business Studies, Kabale University, Kabale P.O. Box 317, Uganda
3 Department of Mathematics and Statistics, Namibia University of Science and Technology, 13 Jackson Kaujeua
Street, Windhoek 10005, Namibia
4 Department of Mathematics, Gulu University, Gulu P.O. Box 166, Uganda
5 School of Computing and Mathematical Sciences, University of Mpumalanga, Mpumalanga, Cnr R40 and
D725 Roads, Mbombela 1200, South Africa
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