Determinants of mobile marketing adoption among SMEs in South Africa

Abstract: SMEs are widely regarded as important building blocks for economic prosperity and broader social well-being for both developed and developing nations. However, SMEs face a number of challenges that impede their ability to fully provide the much-needed boost to the socio-economic development of countries. Besides financial constraints, the lack of marketing skills and capability is often cited as one of the key challenges of most SMEs. Mobile technology innovation has become the cutting edge for socio-economic development for most developing economies. Significant competitive advantage is exploited when businesses use mobile technology to streamline their operations and to initiate interactive communication with their target market through the use of mobile marketing. Thus, it is widely believed that mobile marketing applications hold a great deal of business value, particularly for SMEs that have limited financial resources to invest in costly traditional marketing practices to overcome their marketing challenges. However, SMEs have been slow to adjust and rebalance their marketing media mix to reflect the unprecedented mobile-centric world of consumers. It is therefore important to investigate the factors that influence the adoption of mobile marketing among SMEs. It is against this background that this study uses an integrated conceptual model that combines theories used to understand innovation adoption at the individual level of adoption (theory of planned behaviour) and the organisational level of adoption (Technology Organisation Environment framework). Considering that models of innovation adoption at the individual and organisational levels have been tested with samples drawn from large firms and in developed countries, this study tested the integrated conceptual model with SMEs in South Africa. This was important, because SMEs have peculiar characteristics that distinguish from large firms. More so, findings from developed countries cannot be generalised to a cultural, socio-economically diverse and developing country, such as South Africa. Following a quantitative approach, data were sourced randomly from 511 SMEs in the manufacturing, tourism, and wholesale/retail sectors of the South African economy. Structural equation modelling was the main statistical technique employed to analyse the data and test the hypotheses.D.Phil. (Marketing Management