RT Journal Article
T1 Computational Intelligence in the hospitality industry: 												A systematic literature review and a prospect of challenges
A1 Guerra-Montenegro, Juan
A1 Sanchez-Medina, Javier
A1 Laña, Ibai
A1 Sanchez-Rodriguez, David
A1 Alonso-Gonzalez, Itziar
A1 Del Ser, Javier
AB This research work presents a detailed survey about Computational Intelligence (CI) applied to various Hotel and Travel Industry areas. Currently, the hospitality industry's interest in data science is growing exponentially because of their expected margin of profit growth. In order to provide precise state of the art content, this survey analyzes more than 160 research works from which a detailed categorization and taxonomy have been produced. We have studied the different approaches on the various forecasting methods and subareas where CI is currently being used. This research work also shows an actual distribution of these research efforts in order to enhance the understanding of the reader about this topic and to highlight unexploited research niches. A set of guidelines and recommendations for future research areas and promising applications are also presented in a final section.
SN 1568-4946
YR 2021
FD 2021-04
LK https://hdl.handle.net/11556/3387
UL https://hdl.handle.net/11556/3387
LA eng
NO Guerra-Montenegro , J , Sanchez-Medina , J , Laña , I , Sanchez-Rodriguez , D , Alonso-Gonzalez , I & Del Ser , J 2021 , ' Computational Intelligence in the hospitality industry : A systematic literature review and a prospect of challenges ' , Applied Soft Computing Journal , vol. 102 , 107082 . https://doi.org/10.1016/j.asoc.2021.107082
NO Publisher Copyright: © 2021 Elsevier B.V.
NO Research work co-funded by Agencia Canaria de Investigación, Innovación y Sociedad de la Información (ACIISI) de la Consejería de Economía, Industria, Comercio y Conocimiento, Spain and by Fondo Social Europeo (FSE) Programa Operativo Integrado de Canarias 2014–2020, Spain, Eje 3 Tema Prioritario 74 (85%). This paper was developed under project “Sistema de vigilancia meteorológica para el seguimiento de riesgos medioambientales”, VIMetRi-MAC (ref. MAC/3.5b/065), funded by Programa de Cooperación Territorial INTERREG V A Spain–Portugal, MAC 2014–2020, Spain. Ibai Laña and Javier Del Ser also acknowledge funding support from the Basque Government, Spain through the EMAITEK and ELKARTEK funding programs, Basque Government, Spain. Javier Del Ser receives funding support from the Consolidated Research Group MATHMODE, Spain (IT1294-19) granted by the Department of Education of the Basque Government. Research work co-funded by Agencia Canaria de Investigación, Innovación y Sociedad de la Información (ACIISI) de la Consejería de Economía, Industria, Comercio y Conocimiento, Spain and by Fondo Social Europeo (FSE) Programa Operativo Integrado de Canarias 2014–2020, Spain , Eje 3 Tema Prioritario 74 (85%). This paper was developed under project “Sistema de vigilancia meteorológica para el seguimiento de riesgos medioambientales”, VIMetRi-MAC (ref. MAC/3.5b/065), funded by Programa de Cooperación Territorial INTERREG V A Spain–Portugal, MAC 2014–2020, Spain . Ibai Laña and Javier Del Ser also acknowledge funding support from the Basque Government, Spain through the EMAITEK and ELKARTEK funding programs, Basque Government, Spain . Javier Del Ser receives funding support from the Consolidated Research Group MATHMODE, Spain ( IT1294-19 ) granted by the Department of Education of the Basque Government.
DS TECNALIA Publications
RD 31 jul 2024