Identifying emerging hotel preferences using Emerging Pattern Mining technique

Li, Gang; Law, Rob; Vu, Huy Quan; Rong, Jia; Zhao, Xinyuan

doi:10.1016/j.tourman.2014.06.015

Cited by 146 publications

(81 citation statements)

References 44 publications

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“…A partir dessa breve contextualização, é possível apresentar os enfoques teóricos pertinentes. Para isso, partiu-se da compreensão que para o planejamento de viagens, uma parcela significativa de pessoas tem como prioridade a escolha das acomodações, ou seja, a seleção do meio de hospedagem mais adequado, gastando a maior parte do tempo nesse processo, possuindo expectativas e/ou preferências individuais, conforme seu destino, razão e forma de viagem, além de experiências anteriores com meios de hospedagens (LI et al, 2015). Desse modo, de acordo com a declaração de Herculano de A. Iglesias, presidente da Associação da Indústria de Hotéis (ABIH), em 1999, destacada na obra de Martineli (2001, p. 147), "[...] 'a hotelaria representa a espinha dorsal da indústria do turismo', deixando, portanto, de ser apenas ponto de apoio para ser um grande foco de investimento e renda".…”

Section: Aspectos Considerados Importantes Pelo Hóspede Nos Diferenteunclassified

“…Entretanto, é difícil para os gestores de meios de hospedagem obter a compreensão plena dos requisitos adotados pelos clientes no momento de sua tomada de decisão, abrangendo uma ampla variedade de critérios de seleção (LI et al, 2015). Desses critérios, segundo os levantamentos bibliográficos de Li et al (2015), os que possuem mais destaque estão relacionados com localização, preço, instalações e limpeza; ficando em segundo plano características como o tamanho, tipo de edificação, qualidade de serviço e um ambiente tranquilo (LOCKYER, 2005; ALBALADEJO-PINA; DIAZ-DELFA, 2009;MERLO;DE SOUZA JOÃO, 2001apud LI et al, 2015.…”

Section: Aspectos Considerados Importantes Pelo Hóspede Nos Diferenteunclassified

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Sistema brasileiro de classificação dos meios de hospedagem (SBClass) na perspectiva dos hóspedes

Bastiani¹,

Macedo

2016

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Mestra em Administração. Faculdade de Tecnologia Senac Caçador -Brasil. scheine@sc.senac.br Suzana Rodrigues Macedo -Mestra em Meteorologia. Faculdade de Tecnologia Senac Florianópolis -Brasil. suzana@prof.sc.senac.br RESUMO Este estudo tem como objetivo avaliar a legitimidade do Sistema Brasileiro de Classificação dos Meios de Hospedagem, na perspectiva dos hóspedes. Para tanto, empregamos uma pesquisa qualiquantitativa, dos tipos exploratório, descritivo, bibliográfico, documental e survey, sendo o instrumento de coleta de dados um questionário aplicado aos clientes da SBTur entre setembro e outubro de 2015. Para a análise desses dados utilizamos variados métodos estatísticos, desde frequência relativa, média simples, desvio padrão e distribuição Normal, até o teste de associação qui-quadrado e o coeficiente de correlação de Pearson. Considerando a comparação dos aspectos empíricos levantados com o aporte teórico, destaca-se que, para o sistema de classificação ser legítimo precisa ter como base a perspectiva do cliente, garantindo fidedignidade no processo de classificação, permitindo o uso do Sistema para seu verdadeiro fim, que visa subsidiar o consumidor com informações, mais próximas da realidade possível, conduzindo a uma escolha mais precisa do meio de hospedagem desejado. Palavras-chave: SBClass. Meios de Hospedagem. Hóspedes. Clientes. Legitimidade. Brazilian system of classification of accomodation (SBClass) in the perspective of guests ABSTRACTThis study aims to evaluate the legitimacy of the Brazilian System of Accommodation Rating from the point of view of the guests. For this purpose, we used a qualitative and quantitative research of the exploratory type, descriptive, bibliographical, documentary and survey, and the data collection instrument, a questionnaire applied to SBTur customers between September and October 2015. For the analysis of the data we used varied statistical methods, from relative frequency, simple mean, standard deviation and normal distribution, to the chi-square association test and Pearson's correlation coefficient. And, by comparing the empirical issues raised with the theoretical support, we emphasize that, in order to be legitimate, the classification system needs to be based on the customer's perspective, thus, ensuring reliability in the classification process, allowing the use of the system for its true purpose, which is to subsidize the consumer with information as close to reality as possible, leading to a more precise choice of the desired type of accommodation.

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Section: Aspectos Considerados Importantes Pelo Hóspede Nos Diferenteunclassified

Sistema brasileiro de classificação dos meios de hospedagem (SBClass) na perspectiva dos hóspedes

Bastiani¹,

Macedo

2016

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“…In fact, the comprehensibility of these rules is even more important in big data environments, because of the relevance of the understanding of the underlying phenomena in such a complex environment. The EPM task has been successfully applied in several fields such as chemistry [10,11], medicine [12,13], tourism management [14], photovoltaic technology [15], among others [16].…”

Section: Introductionmentioning

confidence: 99%

Study on the use of different quality measures within a multi-objective evolutionary algorithm approach for emerging pattern mining in big data environments

et al. 2019

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Background: Emerging pattern mining is a data mining task that extracts rules describing discriminative relationships amongst variables. These rules should be understandable for the experts. Comprehensibility of a rule is traditionally determined by several objectives, which can be calculated by different measures. In this way, multi-objective evolutionary algorithms are suitable for this task. Currently, the growing amount of data makes traditional data mining tasks unable to process them in a reasonable time. These huge amounts of data make even more interesting the extraction of rules that can easily describe the underlying phenomena of this big data. So far there is only one algorithm for emerging pattern mining developed based on multi-objective evolutionary algorithms for big data, the BD-EFEP algorithm. The influence of the selection of different quality measures as objectives in the search process is analysed in this paper. Results:The results show that the use of the combination based on Jaccard index and false positive rate is the one with the best trade-off for descriptive induction of emerging patterns. Conclusions: It is recommended the use of this combination of quality measure as optimisation objectives in future multi-objective evolutionary algorithm developments for emerging pattern mining focused in big data.

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“…During recent years, some studies have been conducted that extensively explore hotel customers' behavior on social media (e.g., Li et al, 2015;Su et al, 2015;Xiang et al, 2015Xiang et al, , 2017Berezina et al, 2016;He et al, 2017). Hotel customers' comments provide significant information and knowledge for customer relationship management.…”

Section: Introductionmentioning

confidence: 99%

The Global Conference on Business, Hospitality, and Tourism Research: Volume 1

Çobanoğlu¹,

Thanh²,

Çorbacı³

2018

The Global Conference on Business, Hospitality, and Tourism Research

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GLOSEARCH received more than 200 abstracts/papers for the conference from 242 authors from 32 countries. Ninety-five of these presentations are accepted to be presented at GLOSEARCH 2018. GLOSEARCH is a truly an interdisciplinary and global conference as we will host 170+ participants from 23 countries and from different fields of studies. We would like to thank each author for submitting their research papers to GLOSEARCH 2018.As GLOSEARCH 2018 was a peer-reviewed, double blind conference, we would like to thank each and every reviewer who ensured that the paper review process was a high quality and smooth. We also would like to thank the awards committee for their hard work in selecting the recipients of this year's award winners.We would like to thank Hoa Sen University for hosting GLOSEARCH 2018. Without their support, this conference would have not been possible. We would like to thank our Sponsors for making this Conference

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Identifying emerging hotel preferences using Emerging Pattern Mining technique

Cited by 146 publications

References 44 publications

Sistema brasileiro de classificação dos meios de hospedagem (SBClass) na perspectiva dos hóspedes

Sistema brasileiro de classificação dos meios de hospedagem (SBClass) na perspectiva dos hóspedes

Study on the use of different quality measures within a multi-objective evolutionary algorithm approach for emerging pattern mining in big data environments

The Global Conference on Business, Hospitality, and Tourism Research: Volume 1

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