People Travel Research Articles

User-generated videos and tourists’ intention to visit

ABSTRACT In pursuit of better travel decisions, potential tourists are not only exposed to online destination marketing content but are also exposed to user-generated content (UGC) which are based on the subjective evaluation of people's travel experiences. These user-generated contents have been observed to significantly influence tourist travel intentions, vlogs in particular. This paper aims to further our understanding of how tourists perceive user-generated videos and their influence on their travel intentions. A survey was conducted among tourists (n = 274) in Cape Coast Castle, Ghana and analysed using a Partial Least Squares Structural Equation Modelling (PLS-SEM) technique. Results suggest that tourist's perception of user-generated videos in relation to their perceived credibility and perceived fairness influenced their travel intentions.

Simulating the impacts of interregional mobility restriction on the spatial spread of COVID-19 in Japan

A spatial susceptible–exposed–infectious–recovered (SEIR) model is developed to analyze the effects of restricting interregional mobility on the spatial spread of the coronavirus disease 2019 (COVID-19) infection in Japan. National and local governments have requested that residents refrain from traveling between prefectures during the state of emergency. However, the extent to which restricting interregional mobility prevents infection expansion is unclear. The spatial SEIR model describes the spatial spread pattern of COVID-19 infection when people commute or travel to a prefecture in the daytime and return to their residential prefecture at night. It is assumed that people are exposed to an infection risk during their daytime activities. The spatial spread of COVID-19 infection is simulated by integrating interregional mobility data. According to the simulation results, interregional mobility restrictions can prevent the geographical expansion of the infection. On the other hand, in urban prefectures with many infectious individuals, residents are exposed to higher infection risk when their interregional mobility is restricted. The simulation results also show that interregional mobility restrictions play a limited role in reducing the total number of infected individuals in Japan, suggesting that other non-pharmaceutical interventions should be implemented to reduce the epidemic size.

Stated Preference Analysis of Automated Vehicles among California Residents Using Probabilistic Inferences

As technology advances, improvements in the way people travel also occur. In 2017, the National Renewable Energy Laboratory (NREL) conducted a travel survey in California to understand residents’ perception of several aspects of mobility. This study used the data collected by NREL to understand various factors associated with safety perceptions and acquisition of automated vehicles among California residents. Bayesian networks (BNs) were used to learn the probabilistic interrelationships between aspects of automated vehicles. The predicted probabilities for safety concerns about vehicles with full driving automation (FAVs), purchase of vehicles with auto-drive assistance, and purchase of FAVs were determined after learning the BN structure and parameters from the data. The study found a strong relationship between the acquisition of automated vehicles and vehicles with auto-drive assistance. The BN model predicted that residents who are interested in purchasing vehicles with auto-drive assistance also have about 95% likelihood of purchasing FAVs. Moreover, ridesharing, number of vehicles in the household, housing type, and plug-in electric vehicle (PEV) ownership are among other factors playing a great role in the acquisition and safety perception of automated vehicles. Residents who are currently participating in ridesharing and living in apartments are more likely to purchase vehicles with auto-drive assistance. Residents who either own a PEV or have three or more vehicles are more likely to have safety concerns about FAVs. Additionally, residents who do not have safety concerns about FAVs have about a 45% likelihood of purchasing them. These results could provide valuable user opinion information for vehicle developers and other stakeholders.

The Optimization of Transportation Costs in Logistics Enterprises during the Covid-19 Pandemic

The Covid-19 pandemic has had a significant impact on every industry globally, especially the transportation industry being severely disrupted. With people's travel demand at an all-time low, maintaining the country's transportation infrastructure is crucial to ensure the movement of essential goods. However, the Vietnamese government’s decision to apply social distancing measures to limit and prevent the spread of the disease has generated extreme challenges in the freight transport industry, which have harmed the Vietnamese economy by restricting levels of business activity, causing the movement and distribution of essential commodities to be halted. Based on the practical needs of transportation enterprises, this study proposes a low-cost freight allocation strategy using mix-integer linear programming approaches to ensure an efficient operation for businesses in order to resume normal operations in the context of the Covid-19 epidemic's complex development. The research focuses on developing a mathematical model with an objective function that minimizes total cost and associated constraints. The findings of the study point to the development of a solution that solves businesses problems in determining the optimal transportation plan and assist in making decisions on allocating goods to suitable locations, ensuring the quantity of serving the needs of each district in Ho Chi Minh City, minimizing transportation time while still saving costs. Furthermore, the article aids a decision-making process for other transportation industries.

Exploring Opportunities and Challenges of Artificial Intelligence and Machine Learning in Higher Education Institutions

The way people travel, organise their time, and acquire information has changed due to information technologies. Artificial intelligence (AI) and machine learning (ML) are mechanisms that evolved from data management and developing processes. Incorporating these mechanisms into business is a trend many different industries, including education, have identified as game-changers. As a result, education platforms and applications are more closely aligned with learners’ needs and knowledge, making the educational process more efficient. Therefore, AI and ML have great potential in e-learning and higher education institutions (HEI). Thus, the article aims to determine its potential and use areas in higher education based on secondary research and document analysis (literature review), content analysis, and primary research (survey). As referent points for this research, multiple academic, scientific, and commercial sources were used to obtain a broader picture of the research subject. Furthermore, the survey was implemented among students in the Republic of Serbia, with 103 respondents to generate data and information on how much knowledge of AI and ML is held by the student population, mainly to understand both opportunities and challenges involved in AI and ML in HEI. The study addresses critical issues, like common knowledge and stance of research bases regarding AI and ML in HEI; best practices regarding usage of AI and ML in HEI; students’ knowledge of AI and ML; and students’ attitudes regarding AI and ML opportunities and challenges in HEI. In statistical considerations, aiming to evaluate if the indicators were considered reflexive and, in this case, belong to the same theoretical dimension, the Correlation Matrix was presented, followed by the Composite Reliability. Finally, the results were evaluated by regression analysis. The results indicated that AI and ML are essential technologies that enhance learning, primarily through students’ skills, collaborative learning in HEI, and an accessible research environment.

Application of the health belief model to explain public perceptions, travel intentions and actions during COVID-19: a sequential transformative design

PurposeThis paper uses a supplemented health belief model (HBM) to explain the risk perception of COVID-19 coronavirus infection by potential and actual domestic and international travelers (from primarily European countries) in the early pre-vaccine phase of the pandemic and its influence on their travel intentions, decisions, and actions. With a health crisis of this magnitude, it is vital to understand the effect of COVID-19-associated containment measures and safety industry strategies in abating public fear and apprehension associated with non-essential travel.Design/methodology/approachThe authors used a sequential transformative design consisting of a (QUAN + Qual) survey to explore the HBM dimensions. The questions in the quantitative part of the survey were disseminated online examine perceptions of the severity and susceptibility of the disease, travel risks and willingness to travel. The questions in the qualitative face-to-face survey examined, how international/cross-border travelers (from Spain and Germany) perceive the benefits and barriers of personal protective behavior and the potential influence of cues to action.FindingsResults suggest that despite potential fear arousal and confusion associated with this infectious disease, people were willing to travel during periodic on-and-off travel restrictions and perceive the benefits of such travel as outweighing barriers like wearing masks, social distancing and other containment measures.Research limitations/implicationsThe conceptual model enabled the capture of real-time traveler's feelings about the benefits of traveling in the presence of the coronavirus and their perceptions of COVID-19 safety strategies used at destinations. This study adds to the lack of existing knowledge about potential psychological factors influencing travel decisions and behavior, including self-protective behavior. As borders reopen and we progress towards tourism and hospitality recovery, the results of this study can assist organizations, including health officials and governments, by reminding them of the likelihood of residual public fear when planning their COVID-19 safety strategies.Originality/valueGiven the scarcity of COVID-19 research on people's travel intentions and behavior following periods of social isolation due to lockdowns and border closures, this study captures sample public perceptions at two stages early in the pandemic. It is the first to apply all of the HBM dimensions with the addition of travel risk as a construct to investigate people's travel intentions and behaviors without vaccinations or treatments and to include cues to action in the investigation.

Impact of Social Media on Travel Behaviors during the COVID-19 Pandemic: Evidence from New York City.

During the outbreak of COVID-19, people's reliance on social media for pandemic-related information exchange, daily communications, and online professional interactions increased because of self-isolation and lockdown implementation. Most of the published research addresses the performance of nonpharmaceutical interventions (NPIs) and measures on the issues impacted by COVID-19, such as health, education, and public safety; however, not much is known about the interplay between social media use and travel behaviors. This study aims to determine the effect of social media on human mobility before and after the COVID-19 outbreak, and its impact on personal vehicle and public transit use in New York City (NYC). Apple mobility trends and Twitter data are used as two data sources. The results indicate that Twitter volume and mobility trend correlations are negative for both driving and transit categories in general, especially at the beginning of the COVID-19 outbreak in NYC. A significant time lag (13 days) between the online communication rise and mobility drop can be observed, thereby providing evidence of social networks taking quicker reactions to the pandemic than the transportation system. In addition, social media and government policies had different impacts on vehicular traffic and public transit ridership during the pandemic with varied performance. This study provides insights on the complex influence of both anti-pandemic measures and user-generated content, namely social media, on people's travel decisions during pandemics. The empirical evidence can help decision-makers formulate timely emergency responses, prepare targeted traffic intervention policies, and conduct risk management in similar outbreaks in the future.

Risk perception before travelling: solutions for consumers with vulnerabilities

PurposeThe purpose of this paper is to contribute to the understanding of the tourism service experience of consumers with vulnerabilities. Moreover, this research analyses the pre-core service encounter in the tourism services sector, which is one of the most important phases in the service experience. The objective is to understand how vulnerability might influence risk perceptions when people travel. To this end, this study focusses on individuals with coeliac disease (CD) and non-coeliac gluten sensitivity (NCGS) as a specific group to test the hypotheses. For the millions of individuals with CD or NCGS, food is one of the most critical elements of a trip and the reason for vulnerability perception. The research also proposes measures suggested by survey respondents to improve the information search process of vulnerable travellers before a trip.Design/methodology/approachA mixed-method was used based on a survey of 813 responses from people diagnosed with CD and NCGS. The individuals were placed in three groups according to their perception of how strongly their disease impacts their trips: low impact, medium impact and high impact.FindingsThe results confirm that people with a high-risk perception due to their vulnerability spend more time searching for information prior to the trip than people without this perception. In this sense, individuals that feel more vulnerable, tend to use more personal information sources and also make greater use of online information sources. The participants affected by CD and NCGS proposed measures to reduce their perceived vulnerability. These proposals are based on information about the disease, specific information from the tourist industry at the destination and various online, as well as offline information channels.Originality/valueThe novelty of this research is mainly found in the study in the study of how consumers with vulnerabilities behave during the information process before travelling. From a holistic approach and based on both, marketing service theory and the risk perception perspectives, this research is focussed on vulnerable individuals affected by CD and NCGS to find answers to the problems they face during the pre-core service encounter.

Infrastructure of life: public address, listening and crowds in the Delhi metro and Kumbh

Through an ethnographic study of the Delhi metro and Kumbh fair, this article explores the public address system as an infrastructure of life in urban India. Amplified sound is the singular means to address crowds during emergencies which makes it significant for understanding mass mediation and public safety. Since millions of people travel in the Delhi metro every day, and the Kumbh fair is the largest human gathering in the world, human density and scale as a predominant Southern reality is the premise of this research. It offers an intersubjective understanding of crowds through empathy and care, and reveals the life-saving potentiality of infrastructures when the masses are at risk.

Combining Residual and LSTM Recurrent Networks for Transportation Mode Detection Using Multimodal Sensors Integrated in Smartphones

In recent years, with the rapid development of public transportation, the ways people travel has become more diversified and complicated. Transportation mode detection, as a significant branch of human activity recognition (HAR), is of great importance in analyzing human travel patterns, traffic prediction and planning. Though many works have been devoted to transportation mode detection, there remains challenge for accurate and robust transportation pattern identification. In this paper, we propose a residual and LSTM recurrent networks-based transportation mode detection algorithm using multiple light-weight sensors integrated in commodity smartphones. Feature representation learning is adopted separately on multiple preprocessed sensor data using deep residual and LSTM network, which can enhance the identification accuracy and support one or more sensors. Residual units are introduced to accelerate the learning speed and enhance the accuracy of transportation mode detection. Furthermore, we also leverage the attention model to learn the significance of different features and different timesteps to enhance the recognition accuracy. Extensive experimental results on three datasets indicate that using our proposed model can achieve the best recognition accuracy for eight transportation modes including being stationary, walking, running, cycling, taking a car, taking a bus, taking a subway and taking a train, which outperforms other benchmark algorithms.

Destination Emotions, Loneliness, and Reasons to Travel: Predictors and Moderators of Tourism Well-being

This study aims to determine predictors and moderators of tourism well-being among destination emotions (DES) (total, joy, love, and positive surprise), loneliness (UCLA) (total, affinities, and isolation) and reasons to travel. Regression and moderation analyses were carried out; factor analysis (exploratory and confirmatory) to validate the emotions destination scale were performed. Marital status, family as a reason to travel, love (DES), positive surprise (DES), and affinities (UCLA) explain tourism well-being variance. Of the motivations for traveling, only family and work proved to moderate the relationship between DES and its subscales and tourism well-being. Traveling in Portugal or abroad was a moderator in the relationship between DES and its subscales and tourism well-being. The relationship between destination emotions and tourism well-being is stronger when people do not travel for family or work; this relationship is also stronger when people travel within Portugal than when traveling outside Portugal.

Luggage Tracking System Using IoT

Abstract: The luggage tracking system is designed to track the luggage and bags which gets lost or theft from public and other areas. When people travel, there is always the chance of their luggage and bags being stolen, which is where the proposed system comes in. The luggage tracking system is based on an alert system that uses an Arduino Nano board and a GPS module. The alarm is also activated if the bag is stolen and moves outside of a certain range. Furthermore, a map is constructed via which we can monitor the location of the bag as it moves by dropping markers, which in turn informs us the location of the bag as it moves away from the owner. In this, the IOT components are being used like Arduino Board and a GPS Module in order to track the bag and to keep track of things, a frontend or mobile app is constructed. Keywords: IOT components, Arduino board, GPS, GSM model, Battery booster, Buzzer, Bluetooth model.

Gaps between International Tourists’ Attitudes and Behaviours towards Japanese Heritage Tourism and Government Policymakers’ Views - Opportunities for Tourism Innovation Post COVID-19

Around the world, people travel to explore natural beauty, different cultures and social traditions. Much of this involves heritage tourism and this has become an important motivation for international travelers and contributes huge economic benefits to many countries. Besides, it can also bring positive impacts to the society, culture, and environment conservation of the country involved. The Japan Tourism National Promotion Basic Law (2006) states that culture and heritage are “the most important components of Japan tourism” and that Japan will emphasize its abilities to attract more international travelers and support conservation of cultural heritage [1]. However, as a result of the COVID-19 pandemic, Japanese tourism has been damaged significantly and is forecasted to take a long time to recover. The local government shows its concerns about how to reduce the pandemic impacts on the society and economy and encourage international visitors to return. The “new normal” situation requires an insight of the changes in international tourists’ attitudes, traveling behavior and motivations. The experience of Japan could provide a model which other countries in the Asia and Pacific area might study. The research was conducted through in-depth interviews with Japanese government tourism policymakers and a quantitative survey of 211 responses from 43 countries and territories which was conducted from July 2019 to June 2020. From the findings, some recommendations for Japanese tourism innovation are proposed.

How did micro-mobility change in response to COVID-19 pandemic? A case study based on spatial-temporal-semantic analytics

Cities worldwide adopted lockdown policies in response to the outbreak of coronavirus disease 2019 (COVID-19), significantly influencing people's travel behavior. In particular, micro-mobility, an emerging mode of urban transport, is profoundly shaped by this crisis. However, there is limited research devoted to understanding the rapidly evolving trip patterns of micro-mobility in response to COVID-19. To fill this gap, we analyze the changes in micro-mobility usage before and during the lockdown period exploiting high-resolution micro-mobility trip data collected in Zurich, Switzerland. Specifically, docked bike, docked e-bike, and dockless e-bike are evaluated and compared from the perspective of space, time and semantics. First, the spatial and temporal analysis results uncover that the number of trips decreased remarkably during the lockdown period. The striking difference between the normal and lockdown period is the decline in the peak hours of workdays. Second, the origin-destination flows are used to construct spatially embedded networks. The results suggest that the origin-destination pairs remain similar during the lockdown period, while the numbers of trips between each origin-destination pair is reduced due to COVID-19 pandemic. Finally, the semantic analysis is conducted to uncover the changes in trip purpose. It is revealed that the proportions of Home, Park, and Grocery activities increase, while the proportions of Leisure and Shopping activities decrease during the lockdown period. The above results can help planners and policymakers better make evidence-based policies regarding micro-mobility in the post-pandemic society.

English

The outbreak of an infectious disease and its spread beyond geographic boundaries which leads to a high mortality is declared as pandemic. The factors responsible for pandemic are globalization and travel of people across the world for education, employment, business etc. On March 11, 2020 the corona virus outbreak was declared as pandemic by the World Health Organization. Nevertheless, India was one of the countries affected by the coronavirus outbreak. This article describes the epidemics and pandemics in India since 20th century. But, India was a sufferer of few serious pandemics even before that which are mentioned in brief in this article. Every pandemic has some similar and some dissimilar set of characteristics. All the possible precautionary measures should be taken to avoid transmission within the country and to other countries. In this article, the sincere efforts have been put into compilation of all these natural disasters to alert the dental and medical professionals about the mistakes they might have committed in dealing with an outbreak in the past or how they would overcome or face the current issues. Fortunately India has fought against all these calamites bravely and successfully. Nevertheless during COVID-19 also, India is maintaining better control over the disease spread irrespective of its limited resources and dense population. Though overall incidence of new cases is reducing day by day, COVID-19 still exists in India and all over the world. A widespread occurrence of an infectious disease in a community at a particular time is termed as “endemic’. However, if the outbreak of a disease occurs due to its high infectious potential it can lead to a high mortality rate, and so is declared as a pandemic. The globalization and travel of people across the world is usually responsible for pandemic. India has handled many epidemics and pandemics as revealed by history. The World Health Organization declared the coronavirus outbreak as pandemic on March 11, 2020. Basically the disease originated in China, as the first case of COVID-19 infection was diagnosed in Wuhan city of China. Large number of cases were detected to be suffering from the same disease in China as it was a highly contagious disease. Presently, the disease has spread all over the world like a storm, affecting most of the countries, with the highest number of infected cases in U.S., Italy and Spain. India is also one of the victim countries. Taking into account the rapid spread of disease COVID 19 is the topic of great worry in India due to its high population density. This article describes the epidemics and pandemics since 20th century. But, India was a sufferer of few serious pandemics even before that such as Cholera Pandemic in 5 phases, Bombay Plague Epidemic and VIth Cholera Pandemic in 19thcentury.

A window of opportunity: systems thinking for prevention of haemolytic disease of the fetus and newborn with transfusion policy.

A window of opportunity: systems thinking for prevention of haemolytic disease of the fetus and newborn with transfusion policy.

PERSEPSI DAN SIKAP WISATAWAN MILENIAL TERHADAP PARIWISATA DI ERA COVID 19

The tourism sector has been predicted to be the second largest source of foreign exchange contribution in Indonesia, but the Covid 19 pandemic has made this sector sluggish. The Government of the Republic of Indonesia has made various efforts so that this sector can return to normal. Starting from restricting people traveling, using masks when going out and always washing hands. At the time of tourism in the Covid 19 era, it is believed that millennial generation tourists will continue to carry out their activities. The millennial generation is relatively bolder when traveling on tour when compared to previous generations. With the opening of tourism in the Covid 19 era, the millennial generation will immediately carry out tourism travel activities. Perception is the process of an individual selecting, organizing, and interpreting information inputs to create a meaningful picture of the world. Millennial generation tourists' perceptions focus on risks when traveling. Contracting the covid 19 virus is the biggest risk. Attitude is an evacuation of trust for positive feelings or negative feelings from someone if they have to do behavior that will determine. Attitude is a characteristic that is owned by a person in forming a character, this character is a principle that is owned and is static or difficult to change. The number of respondents in this study were 100 tourists. The results of this study are the perceptions of millennial tourists towards tourism in the new normal era prioritizing the quality of health protocols both in hotels, restaurants, transportation, and in tourist objects. Similarly, the attitude of millennial tourists towards tourism in the new normal era is more concerned about health and hygiene when traveling.

Changes in Passengers’ Travel Behavior Due to COVID-19

The COVID-19 outbreak in 2020 has changed the way people travel due to its highly contagious nature. In this study, changes in the travel behavior of passengers due to COVID-19 in the first half of 2020 were examined. To determine whether COVID-19 has affected the use of transportation by passengers, paired t-tests were conducted between the passenger volume of private vehicles in Seoul prior to and after the pandemic. Additionally, the passenger occupancy rate of different modes of transportation during the similar time periods were compared and analyzed to identify the changes in monthly usage rate for each mode. In the case of private vehicles and public bicycles, the usage rates have recovered or increased when compared to those of before the pandemic. Conversely, bus and rail passenger service rates have decreased from the previous year before the pandemic. Furthermore, it is found that existing bus and rail users have switched to the private auto mode due to COVID-19. Based on the results, traffic patterns of travelers after the outbreak and implications responding to the pandemic are discussed.

Is travel behaviour an equity issue? Using GPS location data to assess the effects of income and supermarket availability on travel reduction during the COVID-19 pandemic

ABSTRACT With recent research identifying mobility restrictions for alleviating the spread of COVID-19, governments have implemented stay-at-home measures, which in turn produced significant changes in people's travel behaviours. Despite these orders, however, people still have to make trips for work or to acquire essential goods. To better understand how these necessary trips influenced changes in individual mobility due to the pandemic, this study focused on the relationship between trip frequency and distance to median incomes, as well as between trip frequency and distance to supermarket density. We made use of the University of Maryland COVID-19 Impact Analysis Platform as our primary source for GPS travel data to study mobility changes at the county-level across the U.S.A. Results showed that trip frequency and distance were significantly different before the outbreak of COVID-19 and during three peak periods of COVID-19 infection. Specifically, we found the reduction of both frequency and distance of trips is negatively correlated to both median income and supermarket density. Thus we conclude that individual choice in adherence to staying-at-home is less dependent on the lockdown measures and more influenced by financial capacity and access to necessary goods and services. These findings could help inform policy development and programmatic responses to help people reduce their mobility. For example, government authorities might consider monthly stimulus or other financial support programs that would allow people greater access to delivery services. In the future, urban planners and policymakers should address the root causes that lead to such economic disparities and food insecurities, in order to build resilience in the face of possible future pandemics.

Contribution of travel participation to social integration and life satisfaction after spinal cord injury

BackgroundResearch has found that participation in travel declines for people after spinal cord injury (SCI) because the traumatic injury usually results in impaired physical mobility and sensation, and barriers in the environment make travel more challenging. While travel participation can offer numerous physical, psychological, and emotional benefits, empirical evidence on positive outcomes of travel for people after SCI is scarce in the literature. ObjectiveTo empirically examine the effects of travel participation on social integration and life satisfaction for people with SCI, along with other personal characteristics including income, self-perceived health status, levels of physical independence, occupational activities, and travel barriers. MethodsCross sectional data are collected from 250 patients enrolled in a SCI Model System. Hierarchical regression analyses, followed by mediation analyses, are conducted to assess the effects of travel participation on social integration and life satisfaction. ResultsTravel participation along with occupational activities is shown to significantly impact social integration, with participation in occupational activities partially mediating the relation from travel participation to social integration. The significant effect of travel participation on life satisfaction is fully mediated by social integration. Income and self-perceived health status both significantly contribute to social integration and life satisfaction. ConclusionsTravel participation should be considered as an independent domain that directly impacts the social integration of people with SCI, which in turn enhances their life satisfaction. Systematic interventions with standard protocols for travel-related skill training and assessments procedures are needed for people after SCI.