Tourist Behaviour Analysis Based on Digital Pattern of Life—An Approach and Case Study

Mikhailov, Sergey; Kashevnik, Alexey

doi:10.3390/fi12100165

Cited by 7 publications

(14 citation statements)

References 44 publications

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“…Information about tourist, region and the POI forms the digital pattern of life [23]. The digital pattern of life represents the tourist and the world around them in the virtual world at the concept level.…”

Section: Reference Modelmentioning

confidence: 99%

Car Tourist Trajectory Prediction Based on Bidirectional LSTM Neural Network

Mikhailov

Kashevnik

2021

Electronics

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COVID-19 has greatly affected the tourist industry and ways of travel. According to the UNTWO predictions, the number of international tourist arrivals will be slowly growing by the end of 2021. One of the ways to keep tourists safe during travel is to use a personal car or car-sharing service. The sensor-based information collected from the tourist’s smartphone during the trip allows his/her behaviour analysis. For this purpose, we propose to use the Internet of Things with ambient intelligence technologies, which allows information processing using the surrounding devices. The paper describes a solution to the car tourist trajectory prediction, which has been the demanding subject of different research studies in recent years. We present an approach based on the usage of the bidirectional LSTM neural network model. We show the reference model of the tourist support system for car-based attraction-visiting trips. The sensor data acquisition process and the bidirectional LSTM model construction, training and evaluation are demonstrated. We propose a system architecture that uses the tourist’s smartphone for data acquisition as well as more powerful surrounding devices for information processing. The obtained results can be used for tourist trip behaviour analysis.

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Section: Reference Modelmentioning

confidence: 99%

Car Tourist Trajectory Prediction Based on Bidirectional LSTM Neural Network

Mikhailov

Kashevnik

2021

Electronics

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“…LR is a supervised machine-learning method that applies the sigmoid function through binary variables [6,7]. Meanwhile, the ANN describes functional relationships among the model's features and investigates human behavior in different contexts [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Super Typhoon Rai’s Impacts on Siargao Tourism: Deciphering Tourists’ Revisit Intentions through Machine-Learning Algorithms

2023

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Super Typhoon Rai damaged Siargao’s tourism industry. Despite the reconstruction projects, there was still evidence of limited resources, destructed infrastructures, and destroyed natural resources. Therefore, this study aimed to examine the significant factors influencing tourists’ intentions to revisit Siargao after Super Typhoon Rai using feature selection, logistic regression (LR), and an artificial neural network (ANN). It employed three feature-selection techniques, namely, the filter method’s permutation importance (PI), the wrapper method’s Recursive Feature Elimination (RFE), and the embedded method’s Least Absolute Shrinkage and Selection Operator (LASSO). Each feature-selection technique was integrated into LR and the ANN. LASSO-ANN, with a 97.8146% model accuracy, was found to be the best machine-learning algorithm. The LASSO model performed at its best with a 0.0007 LASSO alpha value, resulting in 35 subfeatures and 8 primary features. LASSO subsets underwent the ANN model procedure, and the optimal parameter combination was 70% training size, 30% testing size, 30 hidden-layer nodes, tanh hidden-layer activation, sigmoid output-layer activation, and Adam optimization. All eight features were found to be significant. Among them, hedonic motivation and awareness of Typhoon Rai’s impact were considered the top-tier post-typhoon tourism factors, as they maintained at least 97% prediction accuracy. The findings could be elaborated by combining feature-selection techniques, utilizing demographic characteristics, assessing Siargao’s tourism before the typhoon, and expanding the context and participant selection. Nevertheless, none of the existing studies explored the combination of feature selection, LR, and ANNs in a post-typhoon tourism context. These unique methods and significant findings represent the study’s novelty. Furthermore, practical contributions were provided through economic resolutions focusing on tourism activities and communication revamping by the government, media outlets, and transportation companies.

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“…In 2019, it is estimated that there were around 1.5 billion international tourist arrivals worldwide. Before the 2020 pandemic, international travel is expected to increase by more than three percent per year [14]. The tourism and hospitality industry can develop rapidly based on the pattern of visits and the efforts made by decision makers to attract visitors to support the development of this sector.…”

Section: Introductionmentioning

confidence: 99%

Readiness of Tourism Digitalization in Alas Sumur Bondowoso Tourism Village

Ramadhany¹,

Saifudin²,

Huzain³

2022

Advances in Social Science, Education and Humanities Research

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The COVID-19 pandemic that is still happening today has had various impacts in various sectors, one of which is the tourism sector. The government has taken various ways to minimize the impact of the pandemic in the tourism sector, such as the use of health protocols, and limiting the number of visitors at tourist attractions. However, the policy is considered still not effective in minimizing the impact of the pandemic in the tourism sector, forcing the government to temporarily close various tourist attractions in Indonesia. As an alternative to tourism, the government suggests that tourism managers can develop digital tourism. For this reason, this research was carried out with the aim of knowing how the readiness of digitizing tourism in Sumur Alas Village, Pujer District, Bondowoso Regency is to be prepared. Sumur Alas Village is a tourist village which was inaugurated in 2017. This village has the main tourism potential in the form of a lake, as well as other natural beauty such as caves, rivers, and agriculture. This research is a qualitative research in which the researcher conducts in-depth interviews with the perpetrators of the Alas Sumur tourism village tourism. This study shows that the community is still not ready to face the role of digitizing tourism in the tourist village of Alas Sumur. This is because the majority of the people lack knowledge related to technology and lack of personnel as managers who are able and master the field of information technology, as well as lack of network access.

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Tourist Behaviour Analysis Based on Digital Pattern of Life—An Approach and Case Study

Cited by 7 publications

References 44 publications

Car Tourist Trajectory Prediction Based on Bidirectional LSTM Neural Network

Car Tourist Trajectory Prediction Based on Bidirectional LSTM Neural Network

Super Typhoon Rai’s Impacts on Siargao Tourism: Deciphering Tourists’ Revisit Intentions through Machine-Learning Algorithms

Readiness of Tourism Digitalization in Alas Sumur Bondowoso Tourism Village

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