Factors Influencing Flow Of Funding On Maintenance Of Devolved Road Networks In Kapsaret, Uasin Gishu County, Kenya

Abstract

Road networks are an important infrastructure for any country. Road networks that are well maintained and in good condition spurs economic growth and development not to mention the reduced travel time for the road users. With a huge population of Kenyans depending on agriculture, roads need to be in good conditions to enable them to link up to the markets easily and faster because most of this produce is perishable. Well maintained roads linking different centres promotes integration of the residents by easing movement from one place to another. The greatest challenge in maintaining these roads in the expected good condition arises when maintenance is either delayed or inadequately done due to funding for maintenance. This study was done to establish the factors influencing the flow of funding on the maintenance of the road networks in Uasin Gishu County, Kapsaret Sub-County. The study sought to understand the various stages that funds flow through and their influence on this flow. The following objectives were therefore considered; To establish how prioritization, assess how budgeting. To determine how tendering and to identify how payments processes influence flow of funding for the maintenance of road networks in Kapsaret. The study targeted the entire adult population from Kapsaret sub-county based on the last census. A sample that was considered representative of this population was considered proportionately along the networks that have been maintained so far. Staff working in the roads department at Uasin Gishu County were targeted to provide secondary information. This study employed questionnaires as the main data collection instruments. Piloting was undertaken to assist in determining the validity and reliability of the questionnaires and subsequently amend and make corrections on its content. The results from the data collection were then analysed to determine whether indeed there exist a relationship between the variables. Recommendations were then made based on the analysis