Abstract:A wide variety of mathematical and empirical models have been implemented as practical tools for land-use planning, and multilayer perceptron (MLP), logistic regression or LR (mathematical model) and multi-criteria evaluation or MCE (empirical) are among widely applied models. One of the main drawbacks of the mathematical models is that they require dependent data and the process of data collection can be so costly and time-consuming for large areas. As such, we investigated the possibility of providing depend… Show more
“…Advanced text-mining techniques could complement traditional methods [63]. In other words, adopting user-generated-content approaches has some benefits compared with traditional methods for data collection and data analysis [64]. This implies that this study might contribute to filling the absence of utility among tourism destinations and user-generated content.…”
Although the tourism industry has increasingly used social media, there has been little empirical research in terms of the attributes of tourist satisfaction and dissatisfaction with user-generated contents. The purpose of this study is to explore the attributes of tourist satisfaction and dissatisfaction through user-generated contents. We collected data from online review platforms. Our data include historical online reviews, names of reviewers, ratings, location, helpful votes, date of visits, and contributions. In terms of results, the study found 30 key topics related to tourist satisfaction and dissatisfaction. Additionally, we found three clusters (i.e., holiday experience, attractions and facilities, and food experience). Lastly, we that suggested rating levels are different based on the type of tourists (i.e., domestic and international). This study provides discussions and implications for tourism research and industry practices.
“…Advanced text-mining techniques could complement traditional methods [63]. In other words, adopting user-generated-content approaches has some benefits compared with traditional methods for data collection and data analysis [64]. This implies that this study might contribute to filling the absence of utility among tourism destinations and user-generated content.…”
Although the tourism industry has increasingly used social media, there has been little empirical research in terms of the attributes of tourist satisfaction and dissatisfaction with user-generated contents. The purpose of this study is to explore the attributes of tourist satisfaction and dissatisfaction through user-generated contents. We collected data from online review platforms. Our data include historical online reviews, names of reviewers, ratings, location, helpful votes, date of visits, and contributions. In terms of results, the study found 30 key topics related to tourist satisfaction and dissatisfaction. Additionally, we found three clusters (i.e., holiday experience, attractions and facilities, and food experience). Lastly, we that suggested rating levels are different based on the type of tourists (i.e., domestic and international). This study provides discussions and implications for tourism research and industry practices.
“…Adopting a data mining approach has several advantages when compared to other data analysis procedures. Specifically, data mining encompasses a set of modeling techniques grounded on machine learning and artificial intelligence which enable to apprehend complex (non-linear) relations between the variables, as opposed to traditional modeling techniques such as a logistic regression, which are more restrictive (Siroosi et al , 2019; Bloom, 2004). Furthermore, the difference in the predictive performance between a neural network model such as the one adopted in this study and a technique such as a logistic regression is amplified for larger data sets containing thousands of instances and several features, with a clear advantage in using a neural network (Eftekhar et al , 2005).…”
Purpose
This paper aims to propose a data mining approach to evaluate a conceptual model in tourism, encompassing a large data set characterized by dimensions grounded on existing literature.
Design/methodology/approach
The approach is tested using a guest satisfaction model encompassing nine dimensions. A large data set of 84 k online reviews and 31 features was collected from TripAdvisor. The review score granted was considered a proxy of guest satisfaction and was defined as the target feature to model. A sequence of data understanding and preparation tasks led to a tuned set of 60k reviews and 29 input features which were used for training the data mining model. Finally, the data-based sensitivity analysis was adopted to understand which dimensions most influence guest satisfaction.
Findings
Previous user’s experience with the online platform, individual preferences, and hotel prestige were the most relevant dimensions concerning guests’ satisfaction. On the opposite, homogeneous characteristics among the Las Vegas hotels such as the hotel size were found of little relevance to satisfaction.
Originality/value
This study intends to set a baseline for an easier adoption of data mining to evaluate conceptual models through a scalable approach, helping to bridge between theory and practice, especially relevant when dealing with Big Data sources such as the social media. Thus, the steps undertaken during the study are detailed to facilitate replication to other models.
“…), a computing method made up of processing units called “neurons” that function similarly to the human brain in terms of learning and storing knowledge. ANN has been successfully applied in studies of tourism (Fernández-Gámez et al , 2016; Siroosi et al , 2020) and consumer behaviour (Sakar et al , 2019), in which this technique outperformed traditional statistical techniques in terms of precision (Chong, 2013).…”
PurposeThis study aimed to assess whether sociodemographic variables explain significant differences in attitudes towards transforming academic conferences into more sustainable events.Design/methodology/approachAn analytical model of participants' attitudes towards sustainable conferences based on literature review as well as the theories of reasoned action and planned behaviour was developed and applied to a sample of 532 surveyed individuals from 68 countries who regularly attended academic conferences in the last five years prior to 2020. The results were refined using statistical and computational techniques to achieve more empirically robust conclusions.FindingsResults reveal that sociodemographic variables such as attendees' gender and age explain differences in attitudes. Women and older adults have stronger pro-environmental attitudes regarding event sustainability. On the other hand, attitudes towards more sustainable academic conferences are quite strong and positive overall. More sustainable events' venues, catering, conference materials and accommodations strongly influence attendees' attitudes towards more sustainable conferences. The strength of attitudes was weaker towards transportation.Research limitations/implicationsFirst, the analyses focused on only aspects related to the attendees' attitudes. Assessing their real behaviour would complete this research. The geographical areas defined by the U.N. and used in this study have the limitation of combining highly developed countries and developing countries in the same geographical area, for example, the Americas and Asia and the Pacific.Practical implicationsSpecific socio-demographic variables' effects on attitudes towards sustainable academic conferences can indicate how organisers can best promote these events according to attendees' characteristics and develop differentiated marketing campaigns. For women and older adults, event sustainability should be emphasised as a competitive strategy to promote events and attract these audiences. Marketing strategies for younger attendees (under 30 years old) could focus on technology, networking or attractive social programmes. Sustainable venues, catering, conference materials and accommodations are easier to promote. Event organisers should encourage participants to make more environmentally friendly decisions regarding more sustainable event transport.Social implicationsA strategy based on promoting the event as contributing to sustainable development could educate attendees and put them on the path to developing stronger positive attitudes regarding sustainability and more sustainable behaviours. Sustainable academic conferences can educate students, organisers, service providers and delegates through their involvement in sustainable practices.Originality/valueTo our best knowledge, this research is the first to assess whether sociodemographic variables explain significant differences in attitudes towards the sustainable transformation of academic conferences.
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