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A framework for optimising real-estate development incentivisation in priority areas
Thesis (MEng)--Stellenbosch University, 2021.
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| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2021
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| _version_ | 1867613802357325824 |
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| access_status_str | Open Access |
| author | Loots, Martinus |
| author2 | Van Vuuren, Jan Harm |
| author_browse | Loots, Martinus Van Vuuren, Jan Harm |
| author_facet | Van Vuuren, Jan Harm Loots, Martinus |
| author_sort | Loots, Martinus |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MEng)--Stellenbosch University, 2021. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/109829 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:41:56.100Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/109829 A framework for optimising real-estate development incentivisation in priority areas Loots, Martinus Van Vuuren, Jan Harm Van Heerden, Quintin Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering. Metaheuristics Spatial optimisation Real estate development -- Incentives Industrial priorities Industrial policy UCTD Thesis (MEng)--Stellenbosch University, 2021. ENGLISH ABSTRACT: South African cities are experiencing rapid growth as the country becomes more urbanised and people search for a better quality of life. This rapid population growth has exacerbated the urban spatial contrasts that South Africa has been grappling with for centuries. The historical spatial separation experienced in South Africa has been reinforced due to the most marginalised in society settling on the peripheries of cities where the delivery of municipal services and quality of life is a stark contrast to those of more central locations in these cities. These problems have prompted the South African government to create an urban vision of pursuing more inclusive,integrated and compact cities in the future. For the modern South African city to align with this vision, spatial transformation of the urban environment must take place. Urban spatial transformation may be encouraged by enacting municipal plans and frameworks.A strategy for encouraging spatial transformation involves the incentivisation of real-estate development in certain strategically located land areas within the boundaries of a city. Such development allows for densification of the population in specific areas where municipal services may be more efficiently employed, allowing for more sustainable growth of cities. Municipalities often employ tailored urban policies which encourage densification in strategic areas by making available subsidies and grants for this purpose. A novel generic framework is proposed in this thesis for optimising the implementation of urban policies aimed at incentivising the development of residential real-estate in strategically prioritised areas. The framework comprises of two generic components which facilitate the iterative optimisation of potential urban policy implementation. The components of the framework employ statistical methods to predict possible future urban compositions and employ a meta-heuristic approach to optimise the anticipated future consequences of strategically implementing these urban policies. The framework is intended as a decision support tool for policy makersand city planners in aid of developing incentivisation urban densification policies.The framework is instantiated on a computer and implemented virtually as a proof of concept ina real-world case study. This case study is based on data for the City of Ekurhuleni, located in the South African province of Gauteng. It is demonstrated in the case study how the frameworkis capable of achieving significantly more efficient urban densification policies than would occurnaturally. AFRIKAANSE OPSOMMING: Raadpleeg teks vir opsomming Masters 2021-02-11T11:31:06Z 2021-04-21T14:27:59Z 2021-02-11T11:31:06Z 2021-04-21T14:27:59Z 2021-03 Thesis http://hdl.handle.net/10019.1/109829 en_ZA Stellenbosch University 120 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Metaheuristics Spatial optimisation Real estate development -- Incentives Industrial priorities Industrial policy UCTD Loots, Martinus A framework for optimising real-estate development incentivisation in priority areas |
| title | A framework for optimising real-estate development incentivisation in priority areas |
| title_full | A framework for optimising real-estate development incentivisation in priority areas |
| title_fullStr | A framework for optimising real-estate development incentivisation in priority areas |
| title_full_unstemmed | A framework for optimising real-estate development incentivisation in priority areas |
| title_short | A framework for optimising real-estate development incentivisation in priority areas |
| title_sort | framework for optimising real estate development incentivisation in priority areas |
| topic | Metaheuristics Spatial optimisation Real estate development -- Incentives Industrial priorities Industrial policy UCTD |
| url | http://hdl.handle.net/10019.1/109829 |
| work_keys_str_mv | AT lootsmartinus aframeworkforoptimisingrealestatedevelopmentincentivisationinpriorityareas AT lootsmartinus frameworkforoptimisingrealestatedevelopmentincentivisationinpriorityareas |