Touristic Stakeholders’ Perceptions about the Smart Tourism Destination Concept in Puerto Vallarta, Jalisco, Mexico

Jóia

et al. 2021

BAR, Braz. Adm. Rev.

Several tourism destinations around the world have started to implement smart city projects with the aim of improving the standard of living of their citizens, as well as the sustainability of their urban and touristic areas, which motivated the emergence of the concept of smart tourism destination. However, the extant literature on this subject is still incipient. Thus, this article aims to investigate, via an exploratory case study, whether the implementation of a smart city initiative in a touristic destination has helped it be transformed into a smart tourism destination. For that, a smart tourism destination development model is presented and applied as the theoretical lens adopted in this research. The results showed a clear misalignment between the smart city initiative and the touristic destination analyzed, as despite the opportunities arising from the technological infrastructure provided by the smart city project, the touristic sector of the city under analysis was not able to take advantage of the opportunities enabled by the smart city project. Lastly, one concluded that political discontinuity, missing local government tourism strategy and governance, lack of engagement of the citizens, and disregard for the local context were the main reasons for that misalignment.

Section: Discussion Of the Casementioning

confidence: 99%

Smart Tourism Destinations: (Mis)Aligning Touristic Destinations and Smart City Initiatives

Jóia

et al. 2021

BAR, Braz. Adm. Rev.

“…Currently, the real-life impact of areas such as artificial intelligence, soft computing, computational intelligence, and neural networks, with special emphasis on deep learning, is undeniable [28][29][30][31][32][33]. Recently, computational intelligence techniques are being used to determine the tourists' attitudes towards technology [34], to develop intelligent facilities [35][36][37], to search for hot destinations [38,39], to analyze the impact of smart destinations in tourism [40][41][42], and for customer segmentation [43].…”

Section: Related Workmentioning

confidence: 99%

Improvement of Tourists Satisfaction According to Their Non-Verbal Preferences Using Computational Intelligence

et al. 2021

In the tourism industry it is common that the information obtained from customers can be varied, dispersed, and with high volumes of data. In this context, the automatic analysis of information has been proposed through electronic customer relationship management, which refers to marketing activities, tools and techniques, delivered with the use of electronic channels for the specific purpose of locating, building and improving long- term relationships with customers, to enhance their individual potential. In this paper, we refer to the analysis of information in three aspects: customer satisfaction, the study of customer behavior and the forecast of tourist demand. Specifically, we have created a novel dataset comprising the non-verbal preference assessment of tourists who are clients of the Sol Cayo Guillermo hotel belonging to the Melia hotel chain, in Jardines del Rey, Cuba. Then, by applying Computational Intelligence algorithms to this dataset, we achieve segment customers according to their non-verbal preferences, in order to increase their satisfaction, and therefore the client profitability. In order to achieve a good performance in the realization of this task, we have proposed two modifications of the Naïve Associative Classifier, whose results are compared with the most relevant computational algorithms of the state of the art. The experimentally obtained values of balanced accuracy and averaged F1 measure show that, by clearly improving the results of the state-of-the-art algorithms, our proposal is adequate to successfully use electronic customer relationship management in the tourist services provided by hotel chains.

“…Urban tourism generally takes a single city as the main research area, focusing on the analysis of the relationship between the tourism system and the various subsystems of the city, with the aim to realize sustainable tourism and smart tourism development [63]. It does not only emphasize the balance between economic value and environmental impact at the macro-level [5], but also underlines the importance of balancing the interests of all stakeholders at the micro-level [64]. At the same time, through advanced technologies such as information technology, GIS, GPS, social media, and big data, spatial-temporal analysis (STA) has been conducted to solve the problems of overtourism and sustainable tourism planning in urban tourism, and thereby foster urban smart tourism development [65,66] Urban agglomeration tourism stresses the importance of interconnectivity and integration.…”

Section: Urban Tourism and Urban Agglomeration Tourismmentioning

confidence: 99%

Tourism Network in Urban Agglomerated Destinations: Implications for Sustainable Tourism Destination Development through a Critical Literature Review

Hua

Wondirad

2020

Sustainability

This study analyzes tourism network in urban agglomerated destinations and puts forth implications for future sustainable development through a critical and extensive review of related literature. First of all, with a bibliometric analysis of 2670 selected articles from three research fields of urban tourism, urban agglomeration tourism and tourism destination network, we analyzed their respective research themes and classified them accordingly. Then, the study further investigates the role of tourism network in urban agglomerated destinations by identifying the differences and connections between urban agglomeration tourism and urban tourism. Finally, a basic architecture is established for the study of tourism networks in urban agglomerated destinations context. Study findings highlight that urban agglomeration tourism emphasizes the interconnectivity and social network relationships. However, research on the destination network of urban agglomerations is limited, especially from the tourism development perspectives. Therefore, the evolution process, structural effects, determinants and dynamic mechanisms of the tourism network in urban agglomerated destination are among the opportunities for future research. Moreover, the research architecture shows that the network relationship emerges as a new direction for the study of urban agglomeration system to better integrate and harness destinations’ resources and thereby promote sustainable development in urban agglomerated areas.