Factors affecting regional electronic cargo tracking system performance at the port of Mombasa

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dc.contributor.authorKemboi, Emmanuel K.
dc.date.accessioned2021-05-10T11:39:26Z
dc.date.accessioned2022-06-07T06:47:12Z
dc.date.available2021-05-10T11:39:26Z
dc.date.available2022-06-07T06:47:12Z
dc.date.issued2019
dc.descriptionPROJ 380.5 KEMen_US
dc.description.abstractAdvancement in trade across the globe has necessitated mechanism to be put in place to regulate, promote and ensure secure supply chain. Accession to WTO, which facilitates fair trade, requires trading nations to conform to the required laws and regulations facilitating free flow of transit commodities. The application of modern technologies in the sector like RFID and GPS are essential for monitoring movement of transit goods and revenue collection. In East African region before the introduction of digital monitoring system is attributed to diminishing transit and cargo management which have resulted in a decline of paperwork administration which is quiet. As such, the KRA has frequently reported smuggling of goods to the local market, diversion of goods meant for transit, theft on goods on transit among other cases. As a result, more questions have been raised to challenge the effectiveness of the KRA measures aimed to counter illegal activities at the Mombasa Port. The research main objective is to determine the factors affecting Regional Electronic Cargo Tracking System performance at the port of Mombasa. It sought to give answer to the following questions; what is the effect of operational infrastructure, staffing and information sharing on the performance of Electronic Cargo Tracking System team at the port of Mombasa. To further look on these factors, resource-based theory, human resource theory and the hype cycle theory was reviewed. The study adopted a descriptive design which requires the exploration of qualitative and quantitative data. Descriptive research design was considered appropriate for this study with the intention of investigating various challenges RECTS team faces in the port. The target population constituted 54 respondents and a sample size of 48 was arrived at using Slovin’s formula. Primary data was collected using close-ended questionnaires regarding the topic purposely to gather the primary data. Data analysis was done using the SPSS version 25.0. and a linear regression model to show the correlation between the independent and dependent variables of the study. Out of the targeted 48 respondents, 41 fully responded to the issued questionnaires translating to 85.4%response rate. Karl Pearson analysis indicated that operational infrastructure strongly with a positive correlation affects RECTS team performance at the Port of Mombasa by 75.3% Staffing being the second influence RECTS team performance by 64.1% and lastly, Information Sharing indicated to be having a moderate correlation relationship with RECTS team performance at the port of Mombasa being supported 46.5% effect on RECTS team performance at the port of Mombasa. Regression model findings statistically indicates that operational infrastructure by 19.3%, Staffing at 17.7% and information sharing by 39.3% affected the dependent variable. The study concludes by opining that increasing RECTS operational infrastructure so as to improve regional tracking and monitoring cargo which will result in increase of the number of transit cargo being monitored by RECTS, and thus increasing compliance of the sector players resulting to increase in revenue collected and on the other hand being in a position to curb most of the malpractices relating to transit Cargo while enhancing faster clearance.en_US
dc.identifier.urihttps://ikesra.kra.go.ke/handle/123456789/1434
dc.language.isoenen_US
dc.publisherKESRA/JKUAT - Unpublished research projecten_US
dc.subjectOperational Infrastructureen_US
dc.subjectStaffingen_US
dc.subjectRECTSen_US
dc.subjectInformation sharingen_US
dc.titleFactors affecting regional electronic cargo tracking system performance at the port of Mombasaen_US
dc.typeProjectsen_US

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