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A case study of public transport preference in Cape Town using the best-worst scaling method
Commuter preference and service satisfaction influences transport mode choice and even when there is no choice (captive travellers) there is dignity in providing minimal quality. It has been proven that a shift from private transport towards public transport is rare. It is therefore easier to improv...
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| Format: | Thesis |
| Language: | English English |
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Department of Civil Engineering
2025
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| _version_ | 1867613195772887040 |
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| access_status_str | Open Access |
| author | Thanjekwayo, Maxine Nokuthula |
| author2 | Zuidgeest, Marcus |
| author_browse | Thanjekwayo, Maxine Nokuthula Zuidgeest, Marcus |
| author_facet | Zuidgeest, Marcus Thanjekwayo, Maxine Nokuthula |
| author_sort | Thanjekwayo, Maxine Nokuthula |
| collection | Thesis |
| description | Commuter preference and service satisfaction influences transport mode choice and even when there is no choice (captive travellers) there is dignity in providing minimal quality. It has been proven that a shift from private transport towards public transport is rare. It is therefore easier to improve satisfaction or perceptions of captive public transport users than to move car users to public transport. Except in Greece where well-timed transport improvement during an economic downturn resulted in an increase in public transport use. The national fiscus has competing priorities it supports infrastructure, health, education, public transport and many other government services. Justification for funding public transport in lieu of other government priorities is linked to commuter demand. Commuter demand is measured by the number of passengers per mode or trip. The goal for public transport modes is full occupancy of vehicles. Higher occupancy rates justify the trip and by implication the fiscal investment on the trip and or mode. Commuters choose transport modes based on a number of attributes such as: cost, travel time, access time, frequency of service, comfort, safety etc. Therefore, improving public transport users preference capture may lead to better informed public transport improvement investments decisions. Case 2 best worst scaling is a survey method that compares varying attributes to one another by soliciting a ranking of one best and one worst. The method allows for at least three attributes per domain of investigation. Each attribute's attribute level is compared, in a choice set, to other attributes' attribute level. Commuters seek a transport service from origin to destination that is safe, economical and comfortable. Commuter studies show that needs and levels of satisfaction vary from person to person and mode choices are usually restricted by affordability. However, as soon as there is affordability for better options, commuters always choose the most responsive mode. In urban areas this choice is evidenced by higher percentage of low-occupancy private car commute. The aim of this research was to determine the applicability of case 2 best worst scaling; and commuter preferred service attribute levels for travel, safety and comfort for Bus, Minibus Taxi, MyCiTi and Train commuters in Cape Town. The study used attributes and dissatisfaction data from the National Household Travel Survey to identify key attributes and attribute levels for investigation. Case 2 best worst scaling surveys were designed as follows: three domains – travel, safety and comfort; three to four attributes per domain; and each attribute tiered into attribute three levels. The field work was intercept surveys to Cape Town commuters. Data were analysed using R and yielded the following key findings: Case 2 best worst scaling is applicable for preference studies in South Africa and beyond; paying more, experiencing sudden braking and overcrowding were least preferred (disutility); there were nuanced variations for other attribute levels based on mode and demographic groups. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/41951 |
| institution | University of Cape Town (South Africa) |
| language | English eng |
| last_indexed | 2026-06-10T12:32:17.361Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Department of Civil Engineering |
| publisherStr | Department of Civil Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/41951 A case study of public transport preference in Cape Town using the best-worst scaling method Thanjekwayo, Maxine Nokuthula Zuidgeest, Marcus Behrens, Roger Public transport Cape Town Commuter preference and service satisfaction influences transport mode choice and even when there is no choice (captive travellers) there is dignity in providing minimal quality. It has been proven that a shift from private transport towards public transport is rare. It is therefore easier to improve satisfaction or perceptions of captive public transport users than to move car users to public transport. Except in Greece where well-timed transport improvement during an economic downturn resulted in an increase in public transport use. The national fiscus has competing priorities it supports infrastructure, health, education, public transport and many other government services. Justification for funding public transport in lieu of other government priorities is linked to commuter demand. Commuter demand is measured by the number of passengers per mode or trip. The goal for public transport modes is full occupancy of vehicles. Higher occupancy rates justify the trip and by implication the fiscal investment on the trip and or mode. Commuters choose transport modes based on a number of attributes such as: cost, travel time, access time, frequency of service, comfort, safety etc. Therefore, improving public transport users preference capture may lead to better informed public transport improvement investments decisions. Case 2 best worst scaling is a survey method that compares varying attributes to one another by soliciting a ranking of one best and one worst. The method allows for at least three attributes per domain of investigation. Each attribute's attribute level is compared, in a choice set, to other attributes' attribute level. Commuters seek a transport service from origin to destination that is safe, economical and comfortable. Commuter studies show that needs and levels of satisfaction vary from person to person and mode choices are usually restricted by affordability. However, as soon as there is affordability for better options, commuters always choose the most responsive mode. In urban areas this choice is evidenced by higher percentage of low-occupancy private car commute. The aim of this research was to determine the applicability of case 2 best worst scaling; and commuter preferred service attribute levels for travel, safety and comfort for Bus, Minibus Taxi, MyCiTi and Train commuters in Cape Town. The study used attributes and dissatisfaction data from the National Household Travel Survey to identify key attributes and attribute levels for investigation. Case 2 best worst scaling surveys were designed as follows: three domains – travel, safety and comfort; three to four attributes per domain; and each attribute tiered into attribute three levels. The field work was intercept surveys to Cape Town commuters. Data were analysed using R and yielded the following key findings: Case 2 best worst scaling is applicable for preference studies in South Africa and beyond; paying more, experiencing sudden braking and overcrowding were least preferred (disutility); there were nuanced variations for other attribute levels based on mode and demographic groups. 2025-10-01T12:33:53Z 2025-10-01T12:33:53Z 2025 2025-09-30T13:12:17Z Thesis / Dissertation Masters MSc (Eng) http://hdl.handle.net/11427/41951 en eng application/pdf Department of Civil Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Public transport Cape Town Thanjekwayo, Maxine Nokuthula A case study of public transport preference in Cape Town using the best-worst scaling method |
| thesis_degree_str | Master's |
| title | A case study of public transport preference in Cape Town using the best-worst scaling method |
| title_full | A case study of public transport preference in Cape Town using the best-worst scaling method |
| title_fullStr | A case study of public transport preference in Cape Town using the best-worst scaling method |
| title_full_unstemmed | A case study of public transport preference in Cape Town using the best-worst scaling method |
| title_short | A case study of public transport preference in Cape Town using the best-worst scaling method |
| title_sort | case study of public transport preference in cape town using the best worst scaling method |
| topic | Public transport Cape Town |
| url | http://hdl.handle.net/11427/41951 |
| work_keys_str_mv | AT thanjekwayomaxinenokuthula acasestudyofpublictransportpreferenceincapetownusingthebestworstscalingmethod AT thanjekwayomaxinenokuthula casestudyofpublictransportpreferenceincapetownusingthebestworstscalingmethod |