Marques, Jorge

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Jorge Marques
Jorge Humberto Soares Marques, Doutorado em Turismo, Lazer e Cultura pela Faculdade de Letras da Universidade de Coimbra. Professor Auxiliar no Departamento de Turismo, Património e Cultura da Universidade Portucalense (Porto) e investigador do Centro de Estudos de Geografia e Ordenamento do Território (CEGOT, Universidade de Coimbra). Principais áreas de interesse: Lazer, Turismo, Turismo de Negócios, Organizações de Gestão dos Destinos, Hotelaria e Hospitalidade.
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REMIT – Research on Economics, Management and Information Technologies
Centro de investigação que que tem como objetivo principal produzir e disseminar conhecimento teórico e aplicado que possibilite uma maior compreensão das dinâmicas e tendências económicas, empresariais, territoriais e tecnológicas do mundo contemporâneo e dos seus efeitos socioeconómicos. O REMIT adota uma perspetiva multidisciplinar que integra vários domínios científicos: Economia e Gestão; Ciências e Tecnologia; Turismo, Património e Cultura. Founded in 2017, REMIT – Research on Economics, Management and Information Technologies is a research unit of Portucalense University. Based on a multidisciplinary and interdisciplinary perspective it aims at responding to social challenges through a holistic approach involving a wide range of scientific fields such as Economics, Management, Science, Technology, Tourism, Heritage and Culture. Grounded on the production of advanced scientific knowledge, REMIT has a special focus on its application to the resolution of real issues and challenges, having as strategic orientations: - the understanding of local, national and international environment; - the development of activities oriented to professional practice, namely in the business world.

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  • PublicaçãoAcesso Restrito
    Data science in supporting hotel management: Application of predictive models to guest evaluations
    2024-03-15 - Martins, Ana Filipa; Silva, Luís M.; Marques, Jorge
    Data science is a multidisciplinary area that gathers several branches, such as statistics, databases, and computer science and whose importance has become more substantial over the last few years. Using several techniques and algorithms from machine learning allows us to understand how certain variables are related, as well as to visualize data and make predictions. This paper aims to use data science as a strategic instrument for the hospitality industry by proposing a model that can help to predict which characteristics will be more valued by guests. By better understanding which features guests value most when evaluating a stay at a hotel, it will be easier for hotel managers to make informed decisions about which service operations management strategies should be used. It can also be helpful in terms of investment decisions, as it can indicate which aspects will be most important to value in a hotel. In this research, it was possible to conclude that guests’ ratings are related primarily to the commodities available at the hotels, followed by cleanliness, staff, location, price-quality relation, and comfort.
  • PublicaçãoAcesso Restrito
    Perception of risk and identification of security measures when visiting cultural heritage
    2024-03-15 - Marques, Jorge; Silva, Fátima Matos
    The perception of safety is essential during tourist visits to historical monuments, whether they are built architectural heritage, civil, military, vernacular, or archaeological. This perception of security helps to guarantee, on the one hand, the physical integrity of visitors and, on the other hand, the preservation of different types of heritage. Many places visited have unique architectural characteristics, especially in the case of old buildings where architectural barriers and limited accessibility are more evident, with particular emphasis on castles, forts, fortresses, and archaeological heritage. Accidents in these places are relatively frequent, mainly related to falls by visitors. In this context, this article intends to address, in an introductory way, the need to study the perception of risk associated with visiting historic sites, to identify weaknesses and opportunities, and to enable the implementation of coherent strategies and actions to limit the risk of accidents, thus increasing the safety of visitors. A theoretical framework on the risk associated with visiting cultural heritage is presented, and the methodological procedures that will be developed in a more comprehensive research project on the subject are identified.