A data analysis demonstrator for managing customer experience in a partnering venture
| dc.contributor.advisor | Bekker, James F. | en_ZA |
| dc.contributor.author | Roos, Maryke | en_ZA |
| dc.contributor.other | Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering. | en_ZA |
| dc.date.accessioned | 2019-02-19T09:12:30Z | |
| dc.date.accessioned | 2019-04-17T08:30:48Z | |
| dc.date.available | 2019-02-19T09:12:30Z | |
| dc.date.available | 2019-04-17T08:30:48Z | |
| dc.date.issued | 2019-04 | |
| dc.description | Thesis (MEng)--Stellenbosch University, 2019. | en_ZA |
| dc.description.abstract | ENGLISH ABSTRACT: Today's world can be better described as a digital world in which technology is becoming increasingly more dominant. In fact, the technologies of today are changing the biological, digital and physical worlds. This change has a huge impact on industry and how it operates and buzz words that have come forward during these times are Artificial Intelligence, Machine Learning and Big Data Analytics. In light of this the following question arises: `How do we look after our customers by using these changes and technologies to our advantage?'. To investigate this question, a research study is conducted in which data analytics along with business partnering on a cross-functional platform are used to manage and improve a customer's experience. This is achieved by developing a capability demonstrator that will simulate customer activities on a full-scale platform in which data is captured and analysed. The focus is placed on the domain of travel, in which a customer undertakes a journey which is solely planned, booked and managed by the demonstrator. While the customer travels, they engage with various collaborating enterprises and the demonstrator focuses on managing and improving the customer experience at various interaction points. After the implementation of this demonstrator, evaluation has been done to ensure the demonstrator can effectively manage and improve customer experience by the use of data analytics in a partnering venture. Further analysis in the form of Machine Learning was applied on the trips simulated by the demonstrator. The analysis gave valuable insights into customer behaviour in the travel domain. | en_ZA |
| dc.description.abstract | AFRIKAANSE OPSOMMING: Die wêreld van vandag kan beter beskryf word as 'n digitale wêreld waarin tegnologie al hoe meer dominant word. Trouens, die tegnologieë van vandag verander die biologiese, digitale en fisiese wêreld. Hierdie verandering het 'n groot impak op die industrie en hoe die ondernemings funksioneer, en terme wat deesdae gebruik word is Kunsmatige Intelligensie, Masjienleer en Groot Data Analise. In die lig hiervan kan die volgende vraag gestel word: `Hoe sien ons om na ons kliente om sodoende hierdie verandering en tegnologie tot ons voordeel te gebruik?'. Om hierdie vraag te ondersoek, is 'n navorsingstudie gedoen waarin data analise saam met vennootskappe op 'n kruis-funksionele platform gebruik word om 'n klient se ervaring te bestuur en te verbeter. Dit word behaal deur 'n vermoe-demonstreerder te ontwikkel wat kliente se aktiwiteite op 'n volskaalse platform sal simuleer waarin data geskep en ontleed word. Die fokus is op die domein van reis, waarin 'n klient 'n reis neem wat uitsluitlik beplan, bespreek en bestuur word deur die demonstreerder. Terwyl die klient reis, het hulle interaksies met verskeie samewerkende ondernemings en die demonstreerder fokus op die bestuur en verbetering van 'n klient se ervaring op hierdie interaksie-punte. Na die implementering van hierdie demonstreerder is evaluering gedoen om te verseker dat die demonstreerder 'n klient se ervaring effektief kan bestuur en verbeter deur die gebruik van data-analise in 'n vennootskap. Verdere analise in die vorm van masjienleer is toegepas op die reise wat deur die demonstreerder gesimuleer is. Die analise het insig gelewer oor die klient se gedrag in die domein van reis. | af_ZA |
| dc.format.extent | xv, 249 pages ; illustrations | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/10019.1/106142 | |
| dc.language.iso | en_ZA | en_ZA |
| dc.publisher | Stellenbosch : Stellenbosch University | en_ZA |
| dc.rights.holder | Stellenbosch University | en_ZA |
| dc.subject | Quantitative research | en_ZA |
| dc.subject | Customer Experience | en_ZA |
| dc.subject | Consumer satisfaction -- Simulation methods | en_ZA |
| dc.subject | Partnerships | en_ZA |
| dc.subject | Customer relations -- Technological innovations | en_ZA |
| dc.subject | Voyages and travel -- Simulation methods | en_ZA |
| dc.subject | Machine learning | en_ZA |
| dc.subject | UCTD | |
| dc.title | A data analysis demonstrator for managing customer experience in a partnering venture | en_ZA |
| dc.type | Thesis | en_ZA |