A university in a small city: Discovering which sectors benefit

Abstract

Orientation: A university, and equally so a university campus, has the ability to influence the economy through its sectoral links. This raises the question as to what sectors benefit as a result of expenditure made by a university campus that is situated within a small city in South Africa.Research purpose: This paper identified the university-sector links by applying a bill-of-goods approach to identify which sectors benefit as a result of an operational university campus.Motivation for the study: The findings of this study will be used in refining provincial or local social accounting matrix (SAM) models to improve the measurement of an economic impact assessment for the university campus, especially as SAM models are not readily available on such a micro-level within South Africa.Research design, approach and method: The bill-of-goods is a detailed representation of the purchases of goods and services for the campus. The goods and services are grouped into the corresponding sector according to the Standard Industrial Classification to identify and quantify university-sector linkages.Main findings: The results indicated a significant benefit for tertiary sectors of the economy, which receive approximately 85% of university expenditure. On a sectoral level, there is an increased benefit to the utility, retail and personal services sectors, whereas manufacturing and construction turn out to be less significant. Growth prospects for sectors within the tertiary sectors are higher compared to sectors in the primary and secondary sectors.Practical and managerial implications: Understanding this link enables strategic spatial planning on the part of local government and will enable proactive land-use planning, based on the strength and growth prospects of each individual sector that benefits from university expenditure.Contribution or value-add: This approach provided exceptional value in identifying the sectors that benefit and provide important trend analyses that will be combined with input–output models to improve the accuracy of measuring university impact assessment on a local level.

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