Effect of Customs Modernization Initiatives on Customs Performance at Key one Stop Border Posts in Kenya

Abstract

In light of modernization initiatives that have been implemented by the Kenya Revenue Authority (KRA), the current study sought to find out the effect of these initiatives on customs performance at key One Stop Border Posts (OSBP’s) i.e. Malaba, Busia, Namanga and Lungalunga. Specifically, the study looked at how Customs Modernization initiatives such as, Co-ordinated Border Management, System Automation and Human Resource Development have affected customs performance at the border posts. The study was guided by the Technology Acceptance Theory and the Resource Based View Theory. The study adopted a descriptive survey design with primary data being used in the analysis. Primary data was collected through a structured self-administered questionnaire targeting customs officers and clearing agents who formed the target population of the study. The key OSBP’s formed the sampling frame of the study from where a sample of the clearing agents and customs officers, was drawn for purposes of administering the questionnaire. The population was 163 customs officers and clearing agents, while the sample size was 116. A pilot study was conducted in Malaba OSBP to test the reliability of research instruments that were used for the study. A Cronbach alpha reliability co-efficient of 0.7 was used as the threshold for accepting reliability of the questionnaire. The questionnaire was found to be reliable with a Chronbach alpha score of 0.869. The collected data was analysed using SPSS. Multivariate Regression Analysis was carried out to specify the estimation model and determine the type of relationship that exists between the independent variables and the dependent variable. The study findings indicated that systems automation (β 2 = 0.358, p = 0.000<0.05); and human resource development (β 3 = 0.179, p =0.022<0.05) had a positive and significant effect on customs performance. However, coordinated border management did not have a significant effect on customs performance (β 1 = 0.051, p =0.579>0.05), and as such, the null hypothesis was not rejected. To test the overall statistical significance of the model, analysis of variance (ANOVA) was used. The ANOVA results, showed that the model was statistically significant. This was supported by a reported p value less than the predetermined alpha value (p=0.000<0.05) and an F Statistic which was greater than the F Critical value (F = 17.36>2.71) at (3, 84) degrees of freedom. The results confirmed that Systems automation and Human Resource Development were statistically significant in explaining customs performance at the OSBP’s. The R 2 of the regression model was established to be 0.383 (R 2 = 0.389). The study concluded that systems automation and human resource development contribute significantly towards customs performance. Based on the findings, the study recommended that KRA should explore the technology field of Artificial Intelligence (AI) as there are many potential benefits associated with this area of systems automation. The study also recommended establishment of a reward and motivation system to boost the morale of customs staff as well as enhancing the staff establishment at the border posts, as part of further strengthening human resource development at the border posts and enhancing service delivery.