Data Integration Digitalisation and Performance of Container Freight Stations in Kenya: An Explanatory Sequential Mixed Methods Approach

This research investigated the influence of data integration digitalization on the performance of Container Freight Stations (CFSs) in Kenya. The motivation for this study arises from the ongoing operational difficulties encountered by Kenyan CFSs, including congestion and elevated operational expenses, despite their essential function in alleviating port congestion. An explanatory sequential mixed methods approach was employed, combining both positivist and interpretivist frameworks. Quantitative data were obtained from 136 operational managers across 34 CFSs through structured questionnaires, while qualitative data were collected via interviews with 38 key stakeholders (CEOs and Facility Operators). The analysis of data utilized Ordinary Least Squares (OLS) regression, correlation analysis, and thematic analysis facilitated by ATLAS.ti. The findings reveal a robust and positive correlation (r = 0.851) between digitalisation of data integration and firm performance. The regression analysis indicated that data integration digitalisation explains 72.4% of the variance in firm performance. Further, the regression coefficient showed that data integration digitalisation significantly explained performance of CFS in Kenya (β= 0.851, t=18.767, p=0.00). Qualitative themes further illustrated that data functions as a strategic asset for profitability, human resource planning, and promoting a culture of continuous improvement. As a result, the null hypothesis was rejected, affirming that integrated digital systems significantly improve operational results. The study concludes that the implementation of data integration, comprising data mining, analytics, and data-driven decision-making is crucial for enhancing the competitiveness and efficiency of CFSs in Kenya. It is recommended that CFS management develop standardized, interoperable data frameworks and that the Kenya Ports Authority (KPA) lead the initiative to create digital integration standards to eliminate data silos and improve real-time information sharing within the logistics ecosystem.