The Confluence of Transactional and Behavioural Data in a Knowledge-Driven Business in West Africa

This study examines how transactional and behavioural data shape knowledge-driven business capabilities in West African small and medium enterprises. Using a quantitative design, data were collected via structured e-surveys from 350 firms across manufacturing, trade and agriculture. Transactional data were operationalised as data accuracy and data timeliness, while behavioural data captured customer loyalty and social relationships. Structural equation modelling with IBM SPSS AMOS 23 was used to test the hypotheses. Data timeliness exerts the strongest positive effect on knowledge-driven business (β = 0.40, p < 0.001), followed by data accuracy (β = 0.27, p = 0.001) and customer loyalty (β = 0.21, p = 0.002), whereas social relationships show a non-significant direct effect (β = 0.07, p = 0.343). The models demonstrate satisfactory reliability, validity and fit. The study concludes that high-quality transactional and behavioural data are critical for building knowledge capabilities and securing competitive advantage in emerging markets. It recommends that managers prioritise real-time, accurate data capture, strengthen consumer engagement and invest in analytics infrastructure to support knowledge-driven development.