Nuno António

  • Monday, 26 October 2020 10:14

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Identification

Nuno Miguel da Conceição António, PhD degree in Computer Science by ISCTE-IUL

Contacts

E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Biography

Nuno António holds a PhD degree in Computer Science by ISCTE-IUL, a Masters in Hotel Administration and Management by the School of Management, Hospitality and Tourism of the University of the Algarve, and a degree in Software Engineering by ISMAT. His research interests are related to the application of Data Science, Machine Learning, Text Mining, Data Mining, and Big Data in hospitality and tourism, retail, health, and other domains. His work has been published in major scientific journals and conferences, including International Journal of Contemporary Hospitality Management, Cornell Hospitality Quarterly, Journal of Travel Research, Information Technology & Tourism, Data Science Journal, IEEE ICMLA, among others. He is actually Chief Technology Officer at Itbase/WareGuest, a company specialized in the development of software and decision support systems for the hospitality and retail industries. Additionally, he is an invited Assistant Professor at Nova IMS. Nuno is certified in Business Intelligence, specialization of Business Analytics by TDWI – The Data-Warehousing Institute. He is certified as ScrumMaster and member of the Scrum Alliance and, he is also certified as Project Management Associate by IPMA - International Project Management Association.

Publications

Journal article

  • António, N., Almeida, A. de, & Nunes, L. (2019). Predictive models for hotel booking cancellation: a semi-automated analysis of the literature. Tourism & Management Studies, 15(1), 7-21. https://dx.doi.org/10.18089/tms.2019.15011
  • Antonio, N., de Almeida, A., & Nunes, L. (2019). An Automated Machine Learning Based Decision Support System to Predict Hotel Booking Cancellations. Data Science Journal, 18(1), 32. DOI: http://doi.org/10.5334/dsj-2019-032
  • Antonio, N., de Almeida, A., & Nunes, L. (2019). Big Data in Hotel Revenue Management: Exploring Cancellation Drivers to Gain Insights Into Booking Cancellation Behavior. Cornell Hospitality Quarterly, 60(4), 298–319. https://doi.org/10.1177/1938965519851466
  • Antonio, N.; Almeida,A. M. de & Nunes, L. (2018). Hotel booking demand datasets. Data in Brief, 22(february), 41-49. DOI:10.1016/j.dib.2018.11.126
  • Phillips, P., Antonio, N., de Almeida, A., & Nunes, L. (2019). The Influence of Geographic and Psychic Distance on Online Hotel Ratings. Journal of Travel Research. https://doi.org/10.1177/0047287519858400
  • Antonio, N.& Serra, F. (2018). Software as a Service: an effective platform to deliver holistic Hotel Performance Management SystemsSoftware como um Serviço: uma plataforma eficaz para oferta de sistemas holísticos de gestão da performance hoteleira. Tourism & Management Studies, 14(Especial), 25-35. https://dx.doi.org/10.18089/tms.2018.14SI103
  • Antonio, N., de Almeida, A., Nunes, L. et al. (2018). Hotel online reviews: different languages, different opinions. Information Technology & Tourism 18, pp. 157–185. https://doi.org/10.1007/s40558-018-0107-x
  • Antonio, N., de Almeida, A., Nunes, L., Batista, F. and Ribeiro, R. (2018). Hotel online reviews: creating a multi-source aggregated index. International Journal of Contemporary Hospitality Management, 30(12), 3574-3591. https://doi.org/10.1108/IJCHM-05-2017-0302
  • Antonio, N.; Almeida, A. de & Nunes, L. (2017). Predicting Hotel Booking Cancellation to Decrease Uncertainty and Increase Revenue, 3(2):25-39.DOI:10.18089/tms.2017.13203
  • António, N. & Serra, F. (2015). The use of design science research in the development of a performance management system for hospitality. Dos Algarves: A Multidisciplinary e-Journal, 26(2): 23-46. DOI: 10.18089/DAMeJ.2015.26.2.2.

Book Section

  • Antonio,N.; Almeida, A. M. de & Nunes, L. M. M. (2017). Using Data Science to Predict Hotel Booking Cancellations. In P. Vasant & Kalaivanthan M. (Eds.), Handbook of Research on Holistic Optimization Techniques in the Hospitality, Tourism, and Travel Industry,pp. 140-166. IGI-Global.ISBN: 9781522510543. DOI:10.4018/978-1-5225-1054-3.ch006
  • Antonio,N.; Serra,F.; Afonso, C. M. & Ribeiro, C. (2013). Aplicação de um modelo de gestão de receitas: estudo de caso numa unidade hoteleira no Algarve. In C. Henriques, I. Monteiro, F. Serra, J. Santos & P. Águas (Eds.), Inovação e qualidade na hotelaria, pp. 173-191. (TMs Conferences Studies, 2013). Universidade do Algarve. ISBN: 978-989-8472-37-3

Conference Proceeding

  • Borralho, C. M., António, N., Serra, M. & Afonso, C. M. (2019). Produtores de vinho do Algarve no Facebook: oportunidades e desafios. In Pedro de Alcântara Bittencourt César Cláudia Henriques (Ed.), Anais da Conferência Internacional Turismo e História. (pp. 134-135). Faro: U. Algarve, UCS.
  • Ribeiro, F. P., Correia, M. B. & António, N. (2019). Uma abordagem metodológica para a análise comparativa de comentários de viagens online de duas cidades património UNESCO. In Pedro de Alcântara Bittencourt César Cláudia Henriques (Ed.), Anais da III Conferência Internacional Turismo e História. (pp. 55-56). Faro: U. Algarve, UCS.
  • Ribeiro, F. P., Correia, M. B. & António, N. (2019). Uma abordagem metodológica para a análise comparativa de comentários de viagens online de duas cidades património UNESCO. In Pedro de Alcântara Bittencourt César Cláudia Henriques (Ed.), Anais da III Conferência Internacional Turismo e História. (pp. 55-56). Faro: U. Algarve, UCS.
  • António, N., de Almeida, A. & Nunes, L. (2018). Predictive models for hotel booking cancellation: a semiautomated analysis of the literature. In José António C. Santos, Margarida C. Santos, Marisol B. Correia, Célia Ramos (Ed.), Tourism and Management Studies International Conference, TMS Algarve 2018. Olhão: Escola Superior de gestão, Hotelaria e Turismo, Universidade do Algarve.
  • Antonio, N.; Almeida, A. de & Nunes, L. (2017). Predicting Hotel Bookings Cancellation with a Machine Learning Classification Model. 16th IEEE International Conference on Machine Learning and Applications (ICMLA), Cancun, 2017, pp. 1049-1054. doi: 10.1109/ICMLA.2017.00-11
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