Modeling of Travel Behavior Processes from Social Media

2016 ◽  
pp. 626-637 ◽  
Author(s):  
Yuki Yamagishi ◽  
Kazumi Saito ◽  
Tetsuo Ikeda
Keyword(s):  
Social Media ◽  
Travel Behavior

scholarly journals Travel-Related Influencer Content on Instagram: How Social Media Fuels Wanderlust and How to Mitigate the Effect

2022 ◽  
Vol 14 (2) ◽  
pp. 855
Author(s):  
Björn Asdecker
Keyword(s):  
Social Media ◽  
Social Identity Theory ◽  
Behavioral Change ◽  
Travel Behavior ◽  
Environmental Attitudes ◽  
Comparison Theory ◽  
Net Zero ◽  
Benign Envy ◽  
The One ◽  
Harmful Effects

Tremendous efforts will be required in the coming decades to limit the harmful effects of climate change. This includes travel behavior, which not only has a significant impact on climate but also affects the perceived justice and trust necessary to manage the transition to net zero successfully. Technologies such as social media can promote behavioral change; unfortunately, also for the negative. Drawing on social comparison theory, social identity theory, and the theory of planned behavior, this study uses a PLS-SEM model to investigate if and under which circumstances exposure to travel-related content posted by professional influencers affects their followers’ travel intentions. It extends previous studies by explicitly focusing on influencers that use Instagram to make a living and considers the effect of pro-environmental attitudes. On the one hand, it shows that influencers are not only responsible for their travel behavior. Their content stimulates their audiences’ wanderlust through benign envy. On the other hand, the study suggests that reinforcing pro-environmental attitudes can help mitigate the negative climate effects of imitating influencer travel behavior.

scholarly journals New Frontiers in Travel Motivation and Social Media: The Case of Longyearbyen, the High Arctic

2020 ◽  
Vol 12 (15) ◽  
pp. 5905 ◽  
Author(s):  
Carolina Aldao ◽  
Tanja A. Mihalic
Keyword(s):  
Social Media ◽  
Travel Behavior ◽  
High Arctic ◽  
Future Research ◽  
Research Directions ◽  
Travel Motivation ◽  
Future Research Directions ◽  
Push And Pull ◽  
The Impact ◽  
The Town

Tourism explores new frontiers by traveling around unknown geographical and technological territories that bring new tourism opportunities and hazards to satisfy visitors’ needs and sustainability and responsibility in destinations. This study introduces a composite model for measuring travel motivation and the impact of social media on travel behavior and applies it to the town of Longyearbyen in the High Arctic. Both aspects were surveyed through qualitative semi-structured visitor interviews. While the motivation to visit Longyearbyen depended on travelers’ needs, their travel experiences, and push and pull motivational factors, respondents gave examples of how social media positively or negatively affected different elements of their motivation and visitation. The study indicates the opportunities and hazards analyzed from social media as well as future research directions needed in the pursuit of a more responsible tourism approach while exploring new technological and geographical frontiers.

scholarly journals Investigating the relation between social media activities and the mobility and activity types of users

2019 ◽  
Author(s):  
Konstantinos Gkiotsalitis
Keyword(s):  
Social Media ◽  
Real World ◽  
Travel Behavior ◽  
Probabilistic Models ◽  
Activity Patterns ◽  
Limited Attention ◽  
Mobility Patterns ◽  
The Real ◽  
Twitter Data ◽  
Activity Types

In the past years, there has been an emerging number of studies on estimating the passenger demand in urban environments based on social media and cellular data. However, the study of the travel behavior at the individual level and the relation between social media activity and the activity/mobility patterns of users has received limited attention. To rectify this, this study examines Twitter data for unveiling the relations between geo-tagged Tweets and Twitter user sentiments, and the respective activity types performed in the real-world. In this work we try to find common patterns between users' Twitter activity and their actual mobility/activity patterns with the aim to provide some generalizations that can help to understand and model the travel behavior of users. This is achieved with the development of educated rules and probabilistic models that can predict the mobility transfers of users between different activities based solely on social media data. The validity of our generalizations is validated with the use of 4-month Twitter data from London. Only active Twitter users have been selected to study in deep the relations between social media activities/sentiments and the activity types performed in the real-world. Although our generalizations are case study-specific, they demonstrate that it is possible to extract the activity and mobility behavior of users with the use of social media and offer a first step in this direction.

scholarly journals Using Logarithmic Fuzzy Preference Programming To Prioritization Social Media Utilization Based On Tourists’ Perspective

2015 ◽  
Vol 7 (1) ◽  
pp. 7-18
Author(s):  
Mina Balouchi ◽  
Ehsan Khanmohammadi
Keyword(s):  
Social Media ◽  
Travel Behavior ◽  
Analytic Hierarchy ◽  
Media Usage ◽  
Media Technologies ◽  
Programming Methodology ◽  
Related Information ◽  
Fuzzy Extent Analysis ◽  
Hierarchy Process ◽  
Fuzzy Preference

Abstract The advent of Web 2.0 or social media technologies gives travelers a chance to access quickly and conveniently to a mass of travel-related information. This study investigates the importance of social media in travel process in three different phases (pre-visit, on site, post-visit) from the perspective of Iranian travelers. It is worthwhile to know the level of influence of social media on respondents’ travel behavior. Logarithmic fuzzy preference programming methodology is used in this article to determine the importance of social media usage in each phase of travel process and its subcategories. Fuzzy analytic hierarchy process methodology, based on Chang’s Fuzzy Extent Analysis is also used for the data analysis, then the results of these two methods are presented for comparison and better understanding. The results of this study suggest that the most usage of social media is on pre-visit phase while post-visit has the least usage. This study shows that Iranian travelers use social media mainly to share experiences (post-visit phase), get help in different circumstances and gain travel advice.

scholarly journals The Role of Social Media and User-Generated-Content in Millennials’ Travel Behavior

2013 ◽  
Vol 7 (1) ◽  
pp. 87-104
Author(s):  
Maria-Irina ANA ◽  
◽  
Laura-Gabriela ISTUDOR ◽  
Keyword(s):  
Social Media ◽  
Travel Behavior ◽  
User Generated Content

scholarly journals Innovative Approach to Sustainable Mobility and Transport Through Big Data From ICT – Pilot Study in Cracow, Poland

2021 ◽  
Vol 334 ◽  
pp. 01032
Author(s):  
Lidia Zakowska ◽  
Zofia Bryniarska
Keyword(s):  
Social Media ◽  
Big Data ◽  
Public Transport ◽  
Travel Behavior ◽  
Life Quality ◽  
Urban Transport ◽  
Data Availability ◽  
Urban Mobility ◽  
Sustainable Mobility

New challenges of urban transport are connected to sustainability, the growing urban population globally, life quality and quality of urban environment, reduction of pollution and energy consumption. Sustainable urban mobility is no more dependent only on passenger transport efficiency, but also on transport accessibility of commuting services, acceptable level of comfort, safety and security of urban public transport and many more. Although a huge amount of data are available from modern communication services, the question of how to use those big data efficiently to improve urban mobility is unknown. Positive changes of mobility attitudes and travel behavior of citizens are going slowly, which means that personal motivation do not follow big data availability. This motivation is dependent on quality of public transport offer and services, among which information services are suspected to play a crucial role. Modern ICT methods of transport information delivery are based on Internet and social media, which through commonly used mobile devices are available at every stage of journey. In this article authors try, based on the pilot survey, to check how young Krakow citizens use social media in every day travels and commuting. The overall goal of the author’s study is to answer the question: how to use big data coming from ICT in order to upgrade urban transport sustainability.

Pre - Purchasing and Post - Purchasing Travel Behavior on Social Media: The Case of Kazakhstan

2020 ◽  
Vol 11 (6) ◽  
pp. 1475
Author(s):  
Assem ABDUNUROVA ◽  
Maira USPANOVA ◽  
Rajibul HASAN ◽  
Zinagul SURAPBERGENOVA ◽  
Nuradin KUDAIBERGENOV
Keyword(s):  
Social Media ◽  
Travel Behavior ◽  
Purchase Behavior ◽  
Tourism Product ◽  
Before And After ◽  
The Republic ◽  
Two Stages ◽  
Online Travel ◽  
Post Purchase ◽  
The Impact

Purpose – To identify consumers’ travel behavior on social media (SM) before and after purchasing tourism product in the case of the Republic of Kazakhstan. Methodology – A quantitative survey collected data involving travel purposes from 413 users of SM platforms. Findings – This paper revealed the impact of social-economic characteristics on travel behavior and characterized two stages of purchasing process tourism product on SM: The pre-purchase behavior: the impact on decision-making process such factors as sources of trustworthy content, travel frequency, being a member of travel companies’ SM and feedback from travel companies; The post-purchase behavior: the impact of satisfaction and dissatisfaction on the level of spreading positive and negative reviews; feedback from travel companies on consumers’ satisfaction, frequency usage of SM. The originality – The paper investigated pre-purchasing and post-purchasing travel behavior on SM and lack of researches and online travel behavior statistics in Central Asia makes this paper valuable.

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