EXPLORING THE BUSINESS MINDSET OF SERVICE SME OWNERS TOWARDS DIGITAL CONTENT MARKETING ADOPTION IN SOUTHWEST NIGERIA

The adoption of digital content marketing (DCM) has become vital for the growth and competitiveness of small and medium enterprises (SMEs) globally. Amid intense competition, SMEs are increasingly leveraging digital content marketing to implement sustainable strategies(Ijomah et al., 2024). However, in Nigeria, the service SME sector demonstrates varying levels of engagement with DCM, influenced by the owners’ mindset, and readiness for digital adoption. This study explores the mindsets of service SME owners in south-west Nigeria towards adopting DCM using a qualitative approach. Through semi-structured interviews with a diverse group of 29 SME owners across different service industries, the research delves into their attitudes, perceived benefits, challenges, and barriers to DCM adoption. The findings reveal that while SME owners recognize the potential of DCM in expanding market reach and enhancing customer engagement, they are often constrained by limited digital literacy, resource allocation concerns, and scepticism about returns on investment. Consequently, creating a mindset gap that inhibits the lack of localized digital strategies, hence contributing to the slow adoption rates. By analyzing these insights, the study offers practical recommendations for SMEs in Nigeria, policymakers, digital marketing educators, and technology providers to address the barriers and foster a supportive ecosystem for DCM adoption among Nigerian service SMEs. This research also contributes to the broader discourse on digital marketing adoption in emerging economies and underscores the importance of aligning digital strategies with the unique contexts of SMEs in the service sector.

Name dc:type.qualificationname

PhD

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

De Montfort University

Year dc:date.issued

2024

Author dc:creator

• Nnabuife, Izuchukwu

Licence

• https://dora.dmu.ac.uk/bitstreams/659a23a7-5f66-456a-9d66-a4054cf51570/download