Beyond carbon footprints: the ‘Greta Thunberg Effect’ and tourist hotel preferences

Srivastava, Praveen; Mishra, Niraj; Singh, Nripendra; Ramkissoon, Haywantee

doi:10.1080/10548408.2023.2293017

Cited by 7 publications

(1 citation statement)

References 83 publications

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“…When choosing a tourist hotel, tourists consider various factors, such as the environment [9], price [10], transportation [11], services and facilities provided by the hotel [12], and service attitude [13]. A more comfortable environment could put visitors in a better mood, affecting the subjective feelings of the hotel occupants and their evaluation of the environmental experience [14,15].…”

Section: Introductionmentioning

confidence: 99%

Construction of the tourist sentiment dictionary for hotels to mining tourist demands: Based on Macao’s hotel reviews from Agoda

Wang,

Zhu,

Zhang

et al. 2024

Smart. Tour.

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<p><span lang="AZ-LATIN">Tourist hotels (or tourist accommodations) are located near tourist attractions, primarily serving tourists. In recent years, with the gradual improvement of people’s living standards around the globe, tourists’ demands and standards for tourist hotel construction have been rising accordingly. In the context of technologization and informatization, various hotel booking platforms (Agoda, Booking, Trip, etc.) cover a large amount of review data in evaluating systems to reflect tourists’ demands. Meanwhile, identifying demand-oriented reviews and extracting core consumer demands from them is crucial for optimizing hotel services and enhancing tourist satisfaction. Therefore, this study explores the demands of tourists in tourist hotels from the perspective of text sentiment analysis and takes Macao, a famous tourist destination, as an example, based on reviews of tourist hotels on the Agoda site platform. Specifics are as follows: (1) Based on pointwise mutual information (PMI) and information entropy (IE), it realizes the identification of sentiment words in the field of tourist hotels and constructs a sentiment dictionary to address the problem of poor relevance between word segmentation results; (2) It summarizes the five types of reviews containing tourist demands (positive, negative, suggestion, demand, and comparison) and their characteristics to solve the ambiguity of texts and further accurately reveal the main demands of tourists; (3) It classifies tourist demands and group similar tourist demands into the same categories to address the problem of multiple expressions for the same demand. The present study provides empirical experiences from Macao’s hotels and contributes to the literature on text sentiment analysis in tourist hotels. Furthermore, the study results could enhance the mining accuracy and provide a detailed summarization of consumer demands and directions for the sustainable optimization improvement of tourist services.</span></p>

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Section: Introductionmentioning

confidence: 99%

Construction of the tourist sentiment dictionary for hotels to mining tourist demands: Based on Macao’s hotel reviews from Agoda

Wang,

Zhu,

Zhang

et al. 2024

Smart. Tour.

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Spatio-temporal evolution and prediction of carbon balance in the Yellow River Basin and zoning for low-carbon economic development

Dong

2024

Sci Rep

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Studying the carbon effect of land use in watersheds is important for mitigating global warming, promoting coordinated emission reduction in different regions within the watersheds, and realizing high-quality development of the watersheds. Although a number of scholars have carried out relevant studies in the past, they mainly focused on carbon emissions, rarely involved the carbon balance formed by carbon sources and sinks, and lacked relevant studies on the development of low-carbon economy sub-region. Based on this, this study takes the Yellow River Basin as an example, explores the spatial and temporal evolution of carbon emissions from land use in counties in the Yellow River Basin from 1980 to 2020, and predicts the spatial pattern of carbon income and expenditure from land use under natural conditions in 2030 and 2060 using the PLUS model; and then superimposes on the main functional area planning, divides 735 counties in the Yellow River Basin into six low-carbon economic development subregions, and analyzes their economic development The model of their economic development is analyzed. The results show that: (1) the spatial and temporal differentiation of land use carbon balance in the Yellow River Basin has changed greatly over the past 40 years, (2) the spatial distribution pattern of land use carbon balance in the natural context in 2030 and 2060 is more similar to that in 1990, (3) the carbon emission reduction potentials and pattern optimization of the different low-carbon economic development subregions differ greatly, and they have different low-carbon economic development patterns. The results of this study provide a theoretical basis for scientifically and rationally formulating economic policies for low-carbon development in the counties of the Yellow River Basin, and also provide an important reference for related studies in other similar basins or regions in the world.

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Special issue: Green Marketing: Consumption and Development of Sustainable Tourism and Hospitality

Han,

Chua,

Fakfare

2024

Journal of Travel & Tourism Marketing

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Beyond carbon footprints: the ‘Greta Thunberg Effect’ and tourist hotel preferences

Cited by 7 publications

References 83 publications

Construction of the tourist sentiment dictionary for hotels to mining tourist demands: Based on Macao’s hotel reviews from Agoda

Construction of the tourist sentiment dictionary for hotels to mining tourist demands: Based on Macao’s hotel reviews from Agoda

Spatio-temporal evolution and prediction of carbon balance in the Yellow River Basin and zoning for low-carbon economic development

Special issue: Green Marketing: Consumption and Development of Sustainable Tourism and Hospitality

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