Critical factors influencing the adoption of digital marketing devices by service-oriented micro-businesses in Nigeria: A thematic analysis approach

The study investigates which factors critically influence the adoption of digital marketing devices (DMD) among service-oriented micro-businesses in Nigeria, addressing the need for context-specific understanding beyond traditional, quantitatively driven technology adoption models. The authors note that DMDs enable personalisation, secure transactions, and continuous interaction with target customers, yet SMEs in developing countries, including Nigeria, show relatively low adoption rates compared to developed countries. Prior research often extrapolates findings from developed contexts and applies theories not tailored to SMEs’ unique characteristics. Given Nigeria’s service-oriented economy and the slow penetration of digital technologies, the research aims to explore the critical success factors for DMD adoption using a broader, robust framework (TOE) and to develop an integrated framework that can guide micro-businesses and academics. The focus is on micro-businesses in Owerri West, Imo State, where adoption rates are low despite a large number of such firms, making the study both timely and significant for economic development and SME competitiveness.

The literature highlights SMEs as key drivers of industrial growth and competitiveness, with DMDs facilitating efficient communication, customer engagement, and marketing automation. Despite these benefits, Nigerian studies often mirror developed-country perspectives, overlooking local cultural and infrastructural realities. DMDs support awareness creation, interaction, and trust-building, but SMEs frequently fail to leverage them to influence loyalty and purchase decisions. The study adopts the Technology-Organisation-Environment (TOE) framework (Tornatzky & Fleischer, 1990) because it captures technological capabilities, organisational resources, and environmental pressures, providing both constraints and opportunities for innovation adoption. TOE is considered more robust than single-theory approaches (e.g., IDT) for explaining intra-firm innovation in SMEs. The authors justify TOE by its inclusion of environmental factors, its empirical resilience in prior SME adoption research, and its analytical breadth. They also note the scarcity of Nigeria-specific research on DMD adoption in remote areas and the lagging adoption rates in developing countries compared to the West, underscoring the need for a localized, comprehensive framework.

The study employed a qualitative research design to explore critical factors influencing DMD adoption by micro-businesses in Owerri West, Imo State, Nigeria. Purposive sampling targeted managers of service-oriented micro-businesses (defined as employing 1–10 workers) that had used some form of DMD in the past three years. The research was conducted from February to December 2019. Data collection occurred in two stages: (1) preliminary unstructured interviews with 4 participants (M1–M4) to explore the phenomenon, align initial theoretical codes from the TOE framework to raw data, and develop semi-structured interview questions; (2) semi-structured interviews with 22 participants (M5–M26). Interviews lasted approximately 1 hour 30 minutes each. The study area (Owerri) was selected due to a high number of micro-businesses and low DMD adoption rates. Data analysis used a theory-driven thematic approach, combining TOE-based a priori codes with empirically derived codes. The multi-stage analysis included data gathering, transcription, code generation, application of post-defined codes, verification, and presentation of findings. NVivo software supported data management and coding. Inter-coder reliability was assessed with two judges using quotes and categories; agreement was 87% (first judge) and 82% (second judge), exceeding the 70% benchmark. A coding guide defined the contexts: Technology, Organisation, Environment, and an emergent Impact Expectancy. Although other factors (e.g., accessibility, technical know-how, efficiency-driven, owner’s support) surfaced, they were excluded due to limited support and failure to pass reliability thresholds.

Thematic analysis identified 14 critical success factors influencing DMD adoption, organized into four contexts: 1) Technology: - Functional capability (operational efficiency, performance, low complexity). - Adaptive capacity (compatibility and ease of integration with existing processes/technologies). - Expandability (scalability and ability to evolve with business processes). 2) Organisation: - Collective understanding (shared understanding via open interaction in decision-making). - Degree of partnership (collaboration with internal/external partners despite competitive concerns). - Diversity of information (leveraging internal and external knowledge to inform adoption). 3) Environment: - Level of training (feasibility and time required for effective training; lengthy learning curves deter adoption). - Quality of service delivery (speed, reliability, improved processes, and customer-facing information quality). - Customer fulfilment (ability of DMD to satisfy customer needs and support buying processes). - Intense competition (competitive pressures motivating adoption to avoid being left behind). 4) Impact Expectancy (emergent, extending TOE): - Budget (cost-effectiveness and affordability). - Business expansion (contribution to growth, customer acquisition, market share). - Diversity (differentiation and niche creation through unique features). - Return on investment (profitability and measurable financial returns). Reported coverage of cases per context included Technology cumulative 16/26 (61%); Organisation cumulative 16/26 (61%); Environment cumulative 21/26 (80%); Impact Expectancy cumulative 15/25 (58%). The analysis indicates environmental pressures and impact expectancy considerations weigh heavily in adoption decisions. Inter-coder reliability support was 87% and 82%.

The findings address the research question by revealing that DMD adoption in Nigerian micro-businesses is multi-dimensionally shaped by technological fit, organisational processes, environmental pressures, and expected business impacts. Beyond the traditional TOE framework, the emergent Impact Expectancy context highlights that micro-businesses prioritize demonstrable, near-term benefits—cost reduction, growth, differentiation, and ROI—due to constrained resources and risk aversion. This extension enriches the explanatory power of TOE for SME contexts. The results underscore that high-performing, compatible, and scalable DMDs, accompanied by organisational learning and collaboration, can improve service quality and customer satisfaction, thereby enhancing competitiveness. The framework suggests that facilitating training, promoting knowledge sharing, and building partnerships can reduce perceived complexity and uncertainty. Practically, the study provides a structured lens for managers to evaluate DMD options, ensuring alignment with operational needs, market dynamics, and financial imperatives.

The study identifies 14 critical success factors influencing DMD adoption among service-oriented micro-businesses in Nigeria and proposes an integrated framework that extends the TOE model with an Impact Expectancy dimension (budget, business expansion, diversity, ROI). This extension offers a more comprehensive explanation of intra-firm innovation adoption in resource-constrained SME contexts. The research contributes locally grounded insights for Nigeria, addressing the paucity of context-specific studies and countering reliance on developed-country extrapolations. Practically, the framework can guide micro-business managers in strategy formulation for DMD adoption, emphasizing technological fit, organisational readiness, environmental pressures, and expected business impacts. Future research should validate and refine the framework using mixed-methods and confirmatory statistical techniques across larger and more diverse samples, sectors, and developing-country contexts, and explore additional factors that showed preliminary signals (e.g., accessibility, owner support).

Limitations include the qualitative design’s susceptibility to researcher/respondent bias, challenges in managing and analysing large volumes of qualitative data, and a relatively small sample (26 participants) limiting generalisability. The context-specific nature (Owerri West, Imo State, Nigeria) may reduce applicability to other regions or developing countries with different cultural, social, economic, and technological conditions. Some potential factors (e.g., accessibility, technical know-how, efficiency-driven, owner’s support) were excluded due to limited support and reliability. The authors recommend mixed-methods, case studies, and confirmatory statistical techniques to validate the framework across broader populations and sectors.