Moderating Effect of Tax Morale on the Relationship Between Electronic Cargo Tracking Systems (ECTS) and Trade Facilitation in Kenya

Abstract

The Port of Mombasa faces several trade facilitation challenges, including congestion, capacity limitations, and inefficient processes. At Mombasa port 15% of cargo delays are directly linked to seal tampering and unauthorized access, costing traders an estimated $50 million annually in demurrage and storage fees. These inefficiencies not only inflate trade costs but also erode Kenya’s competitiveness as a regional logistics hub under the African Continental Free Trade Area (AfCFTA), where seamless cargo movement is critical for intra-African trade growth. The study sought to determine the moderating effect of tax morale on the relationship between Electronic Cargo Tracking Systems (ECTS) and trade facilitation in Kenya. The research was guided by two specific objectives: to assess the effect of ECTS on trade facilitation and to determine the moderating effect of tax morale on the relationship between electronic cargo tracking systems (ECTS) and trade facilitation in Kenya. The theoretical foundation was the Unified Theory of Acceptance and Use of Technology (UTAUT). A quantitative research design was employed, utilizing structured questionnaires to collect data from 116 clearing agents selected through simple random sampling to ensure representativeness. Data analysis involves descriptive statistics (means, frequencies) and inferential statistics (multiple regression analysis) to test two null hypotheses. The results revealed that electronic cargo tracking systems had a positive and significant effect on trade facilitation (β=0.209, p=0.006). The study findings showed that tax morale has a significant moderating effect on the relationship between the electronic cargo tracking systems and trade facilitation in Kenya. The study concluded that Electronic Cargo Tracking Systems significantly enhance trade facilitation by improving cargo security, reducing transit times, and minimizing revenue losses. Governments should prioritize the development and deployment of automated risk management systems within customs and border control agencies. In addition, policymakers should encourage the use of data analytics and machine learning to identify potential risks before they materialize, allowing for targeted interventions and smoother trade flows.