scholarly journals Habit drives sustainable tourist behaviour

2022 ◽  
Vol 92 ◽  
pp. 103329
Author(s):  
Sarah MacInnes ◽  
Bettina Grün ◽  
Sara Dolnicar
Keyword(s):  
2017 ◽  
pp. 101-126 ◽  
Author(s):  
Marcello Risitano ◽  
Rosaria Romano ◽  
Annarita Sorrentino ◽  
Michele Quintano

2020 ◽  
Vol 5 ◽  
pp. 78-83
Author(s):  
S.A. Mikhailov ◽  

The tourism industry has grown rapidly in recent years, and IT technology is also having a big impact on tourists. Tourism services, information generated by tourists and other sources can be used to build models of tourist behavior. These models can improve the travel experience in various ways. The author presents the system for analyzing tourist behavior based on the concept of a digital pattern of life. The system determines the tourist, possible data sources, ways of storing and presenting data, as well as tools for analyzing behavior. The author used artifi cial neural networks to analyze behavior from a dataset of tourist travels made with cars. One scenario of tourist behavior using artifi cial neural networks is presented. The collected results will be used for improving tourist services.


2021 ◽  
Vol 63 (1) ◽  
pp. 109-127
Author(s):  
Kinga Zsuzsanna Nagy ◽  
Kata Tóth ◽  
Noémi Gyömbér ◽  
László Tóth ◽  
Miklós Bánhidi

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gianluca Solazzo ◽  
Ylenia Maruccia ◽  
Gianluca Lorenzo ◽  
Valentina Ndou ◽  
Pasquale Del Vecchio ◽  
...  

Purpose This paper aims to highlight how big social data (BSD) and analytics exploitation may help destination management organisations (DMOs) to understand tourist behaviours and destination experiences and images. Gathering data from two different sources, Flickr and Twitter, textual and visual contents are used to perform different analytics tasks to generate insights on tourist behaviour and the affective aspects of the destination image. Design/methodology/approach This work adopts a method based on a multimodal approach on BSD and analytics, considering multiple BSD sources, different analytics techniques on heterogeneous data types, to obtain complementary results on the Salento region (Italy) case study. Findings Results show that the generated insights allow DMOs to acquire new knowledge about discovery of unknown clusters of points of interest, identify trends and seasonal patterns of tourist demand, monitor topic and sentiment and identify attractive places. DMOs can exploit insights to address its needs in terms of decision support for the management and development of the destination, the enhancement of destination attractiveness, the shaping of new marketing and communication strategies and the planning of tourist demand within the destination. Originality/value The originality of this work is in the use of BSD and analytics techniques for giving DMOs specific insights on a destination in a deep and wide fashion. Collected data are used with a multimodal analytic approach to build tourist characteristics, images, attitudes and preferred destination attributes, which represent for DMOs a unique mean for problem-solving, decision-making, innovation and prediction.


2018 ◽  
Vol 13 (1) ◽  
pp. 19-28
Author(s):  
Bivek Dutta ◽  
Sajnani M

A review of literature pertaining to online travel behaviour shows that most travel purchases in India are done online. In India, 68% of the population book flight tickets directly. India has an urban adult population of 240 million out of which 27% or 65 million go on holidays. India has 205 million internet users and 110 million Smartphone users. Online Travel bookings are expected to grow rapidly as India’s online travel penetration is expected to increase It is not only restricted to online product purchases. This paper is an attempt to discuss online tourist behaviour in the burgeoning Tourism Industry. The paper also looks into some key aspects such as the performance of the service sector, E-commerce and development of internet which are majorly responsible for developing customer expectation. It also throws light on online tourist behaviour and means of delivering a good experience to the tourists through an array of online services.


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