Effects of customs automated systems on trade facilitation in Kenya.

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dc.contributor.authorOuso, Elijah Gogah
dc.date.accessioned2020-03-02T06:56:25Z
dc.date.accessioned2022-06-07T06:48:02Z
dc.date.available2020-03-02T06:56:25Z
dc.date.available2022-06-07T06:48:02Z
dc.date.issued2019
dc.descriptionPROJ 340 OUSen_US
dc.description.abstractTrade facilitation is simplifying, harmonizing, standardizing and modernizing trade processes. It aims to reduce the cost of trade transactions at the business-government interface and is an agenda item for many customs-related operations. Customs administrations carry out large, significant tasks that enable the flow of products and services across global boundaries. Customs have traditionally played a rather limited role, focusing mainly on collecting duties and taxes on imported products. For instance, income gathered by the (KRA) in Kenya in the department of customs is a major source of revenue. The purpose of this study was to investigate the effects of customs systems on trade facilitation in Kenya. The study was guided by three objectives which include; examining the effects of Simba 2005 System, determining the effects of single window systems and establishing the effects of electronic cargo trucking system on trade facilitation in Kenya. The study based on four theories which include: Technology change, constraints and operational measures, Mobility intergenerational, trade facilitation. The research evaluated and examined various systems that influence custom administration operations which may affect trade facilitation in Kenya. It also aimed at addressing how customs administration implemented various systems which include; Simba 2005 System, single window system and electronic cargo trucking system in their operations and the need to adopt a robust and more efficient system built on the latest technology with capability of seamlessly internal and external systems. The target population of this study is heterogeneous and it targeted 30% of 525 Customs officers who work in the customs departments in at Times Towers main office. The targeted population was 525 customs officers working in various departments of customs at times towers. Primary and secondary data were the main data source for this study. Questionnaire was the major tool for obtaining primary data from respondents while secondary data were obtained from existing study-related empirical literature. Using a descriptive survey design, the study used an exploratory approach. The questionnaire was conceived using the type of Likert scale. For a sample target of 157 participants, a stratified sampling method was used and out of 157 questionnaires issued, 125 (79.62%) were dully field. Data were coded and entered into SPSS from which correlation analysis was used to evaluate the collected information. Both quantitative analysis and regression analysis were used as a data analysis technique. The information gathered have been executed through different models to obviously highlight the factors that determine the impacts of customs schemes on trade facilitation. The investigator also used a multivariate regression analysis to determine the relationship between the independent variables and the variable dependent. The study established that the adoption of various systems on customs departments had a major effect on traders and clearing and forwarding companies because custom systems reduce the average lodging time and clearance time of goods. From these findings, there was quick movement of products as a result of the implementation of various customs systems. Thus, the implementation of various customs systems has a major impact on facilitating trade in Kenya.en_US
dc.identifier.urihttps://ikesra.kra.go.ke/handle/123456789/644
dc.language.isoenen_US
dc.publisherKESRA/JKUAT - Unpublished research projecten_US
dc.subjectTrade Facilitationen_US
dc.subjectCustoms Systemsen_US
dc.subjectOperational Measuresen_US
dc.subjectCustoms Administrationen_US
dc.titleEffects of customs automated systems on trade facilitation in Kenya.en_US
dc.typeProjectsen_US

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