A Model for Fine Collection on Traffic Offenses in Kenya

Transport sector has major influence on any countrys economy. According to the Kenya Vision 2030, infrastructure is among the main foundations for the countrys sustainable development. In particular, road transport is increasingly becoming dynamic with new modes of road transport emerging such as motor bikes and tuk-tuk. Correspondingly as demand keeps increasing, regulatory authorities are adjusting policies to accommodate new modes of transport. Further, development of transport network systems has brought many economic benefits and challenges which cannot be overlooked. Currently, road accidents are ranked 9th as cause of death and disability in developing nations. The county governments and Regulation authority in Kenya (e. g. NTSA) have implemented several technologies to curb the vice such as speedometer and breathers. Despite such measures violations still go unaddressed indicating challenges in the role played by the regulators. This gap could be filled by having surveillance systems in place with capability to track and transfer real-time information through use of effective control systems that ensure full accountability by traffic department who then book the offender for a court hearing. In the view of this, the researchers sought to address this gap through development of a model for traffic information systems. Information systems are potentially a major source of real-time information; automation of manual systems; transformation of business processes and integration of business processes and boundaries that have previously existed. The main purpose of this study was to propose a model on traffic information system for efficient fine collection in Kenya. The study adopted institutional theory and technology acceptance model. Descriptive research design was applied. A purposive sampling technique was adopted to identify the respondents who were to participate in the studys survey. Online survey technique was adopted by the study using structured questionnaire. The study established a positive impact of the model on fine collection and recommends commercialization as well as deeper investigation in a wider scope for feasibility purposes.