Moderating effect of technology staff competence on the relationship between scanning technological attributes and custom revenue performance: a case study of Jomo Kenyatta International Airport

Abstract

Customs plays a crucial role in the enforcement of indirect tax regimes at the border. However, statistics has shown that customs revenue performance has been declining in the recent past. Numerous variables have conspired to arrange this, including the absence of scanners, which might facilitate evasion. Although there have been attempts to understand this situation, not much has been done on whether scanning technological attributes factors improves customs revenue performance; and not much has been done on technological staff competence as a potential moderator. The study therefore examined the moderating effect of technology staff competence on the relationship between scanning technological attributes and custom revenue performance at Jomo Kenyatta International Airport. The specific objectives were to determine the effect of baggage scanning accuracy, cargo scanning efficiency, customs declaration scanning and scanning technology integration on custom revenue performance. The study also tested the moderating effect of technology staff competence on the relationship between scanning technological attributes and custom revenue performance. The study was anchored on the Technological Determinism Theory, Human capital theory and Task Technology Fit theory. The study made use of an explanatory research design. The target population for this study was the customs officers working at the KRA customs department at Jomo Kenyatta International Airport who totaled 538. Simple random sampling was used in the study to choose the customs officials. The sample size of 229 was determined using the Yamane (1973) formula. A semi-structured questionnaire was used as the study's data gathering tool. The data was analyzed using both inferential and descriptive statistics, including regression and correlation, as well as mean and percentage calculations. Utilizing hierarchical regression analysis, the moderating impact of technological competency was examined. Conclusions and suggestions were developed based on the study's findings. The correlation analysis revealed a positive and significant correlation between independent variables and dependent variable. The study found that Baggage scanning accuracy has a positive and significant effect on custom revenue performance β=0.138 p-value =0.010, cargo scanning efficiency has a positive and significant effect on custom revenue performance β=0.041 p-value =0.048, customs declaration scanning has a positive and significant effect on custom revenue performance β=0.111 p-value =0.010, scanning technology integration has a positive and significant effect on custom revenue performance β=0.033 p-value =0.022. The study also found that technology staff competence moderates the relationship between baggage scanning accuracy, cargo scanning efficiency, customs declaration scanning, scanning technology integration and custom revenue performance β=0.057 p-value =0.000, β=0.010 p-value =0.003, β=0.135 p-value =0.002, β=0.031 p-value =0.013). Recommendations were made that the management of JKIA should ensure that the baggage scanning technology maintains accuracy, cargo scanning technology is efficient and that the customs declaration scanning runs efficiently and effectively. The study also suggested that the management should ensure the problems are attended to with urgency and that all staff dealing with scanning technology should be properly trained. The policy makers were also advised to make policies that will guide the management of JKIA customs department to effectively and efficiently use scanning technology in the scanning process.