Predictive models of hotel booking cancellation: a semi-automated analysis of the literature
This study sought to combine data science tools and capabilities with human judgement and interpretation in order to demonstrate how semiautomatic analysis of the literature can contribute to identifying and synthesising research findings and topics about booking cancellation forecasting. The st...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Algarve, ESGHT/CINTURS
2019-01-01
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| Series: | Tourism & Management Studies |
| Subjects: | |
| Online Access: | https://www.tmstudies.net/index.php/ectms/article/view/1107/pdf_117 |
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| _version_ | 1832568677623398400 |
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| author | Nuno António Ana de Almeida Luís Nunes |
| author_facet | Nuno António Ana de Almeida Luís Nunes |
| author_sort | Nuno António |
| collection | DOAJ |
| description | This study sought to combine data science tools and capabilities
with human judgement and interpretation in order to demonstrate
how semiautomatic analysis of the literature can contribute to
identifying and synthesising research findings and topics about
booking cancellation forecasting. The study also focused on
recording in detail the analysis’s full experimental procedure to
encourage other researchers to conduct automated literature
reviews in order to understand more fully the current tendencies in
their field of study. The data were obtained through a keyword
search in Scopus and Web of Science databases. The methodology
presented not only diminishes human bias but also enhances data
visualisation and text mining techniques’ ability to facilitate
abstraction, expedite analysis and improve literature reviews. The
results show that, despite the importance of forecasting booking
cancellations to understanding net demand and improving
cancellation and overbooking policies, further research on this
subject is needed. |
| format | Article |
| id | doaj-art-ec87c189487f4853a934cc9f2a01fe0c |
| institution | Kabale University |
| issn | 2182-8466 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | University of Algarve, ESGHT/CINTURS |
| record_format | Article |
| series | Tourism & Management Studies |
| spelling | doaj-art-ec87c189487f4853a934cc9f2a01fe0c2025-02-03T00:57:36ZengUniversity of Algarve, ESGHT/CINTURSTourism & Management Studies2182-84662019-01-0115172110.18089/tms.2019.15011Predictive models of hotel booking cancellation: a semi-automated analysis of the literatureNuno António0Ana de Almeida1Luís Nunes2ISCTE-IUL and Instituto de Telecomunicações, Av. das Forças Armadas, 1649-026 Lisboa, PortugalISCTE-IUL, CISUC and ISTAR, 1649-026 Lisboa, PortugalISCTE-IUL, Instituto de Telecomunicações and ISTAR, 1649-026 LisboaThis study sought to combine data science tools and capabilities with human judgement and interpretation in order to demonstrate how semiautomatic analysis of the literature can contribute to identifying and synthesising research findings and topics about booking cancellation forecasting. The study also focused on recording in detail the analysis’s full experimental procedure to encourage other researchers to conduct automated literature reviews in order to understand more fully the current tendencies in their field of study. The data were obtained through a keyword search in Scopus and Web of Science databases. The methodology presented not only diminishes human bias but also enhances data visualisation and text mining techniques’ ability to facilitate abstraction, expedite analysis and improve literature reviews. The results show that, despite the importance of forecasting booking cancellations to understanding net demand and improving cancellation and overbooking policies, further research on this subject is needed.https://www.tmstudies.net/index.php/ectms/article/view/1107/pdf_117data scienceforecastliterature reviewpredictionrevenue management |
| spellingShingle | Nuno António Ana de Almeida Luís Nunes Predictive models of hotel booking cancellation: a semi-automated analysis of the literature Tourism & Management Studies data science forecast literature review prediction revenue management |
| title | Predictive models of hotel booking cancellation: a semi-automated analysis of the literature |
| title_full | Predictive models of hotel booking cancellation: a semi-automated analysis of the literature |
| title_fullStr | Predictive models of hotel booking cancellation: a semi-automated analysis of the literature |
| title_full_unstemmed | Predictive models of hotel booking cancellation: a semi-automated analysis of the literature |
| title_short | Predictive models of hotel booking cancellation: a semi-automated analysis of the literature |
| title_sort | predictive models of hotel booking cancellation a semi automated analysis of the literature |
| topic | data science forecast literature review prediction revenue management |
| url | https://www.tmstudies.net/index.php/ectms/article/view/1107/pdf_117 |
| work_keys_str_mv | AT nunoantonio predictivemodelsofhotelbookingcancellationasemiautomatedanalysisoftheliterature AT anadealmeida predictivemodelsofhotelbookingcancellationasemiautomatedanalysisoftheliterature AT luisnunes predictivemodelsofhotelbookingcancellationasemiautomatedanalysisoftheliterature |