Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/4508
Title: Revenue Forecasting in Local Government: A Case of City of Mutare
Authors: Useya, Tsitsi
Keywords: revenue forecasting
service delivery
local authority
Issue Date: 2024
Publisher: Africa University
Citation: Useya, T. (2024). Revenue forecasting in local government: A case of City of Mutare (Master’s thesis). Africa University, Mutare, Zimbabwe.
Abstract: The main objective of the study was to analyse the revenue forecasting techniques at Mutare City Council. The study adopted an explanatory research design where data was collected using questionnaires and interviews from staff at Mutare City Council. Data was analysed through descriptive statistics and content analysis. The results showed that the trend analysis method is the most used forecasting method, followed by the consensus method. The least used methods were the moving average and the time series method. The study found out that inaccurate revenue forecasting resulted in insufficient funds to allow for operations such as procurement of water chemicals, procurement of equipment and machinery used by MCC, in provision of street lighting, road maintenance and sewer maintenance. The study also found out that revenue forecasting was affected by information availability, political interference, lack of expertise, macro-economic factors, failure to predict time horizons and nature of revenue streams. The study concluded that Mutare City Council relied only on a few forecasting techniques, which may affect its revenue processes. The study also concluded that that poor revenue forecasting resulted in budgetary constraints which negatively impacted on service delivery at Mutare City Council. The study recommended that Mutare City Council should adopt other revenue forecasting techniques and not rely on a few techniques. Adopting various techniques simplifies the forecasting process and provide much better analysis which takes into account different changing variables.
URI: http://localhost:8080/xmlui/handle/123456789/4508
Appears in Collections:Department of Business Sciences

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