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People with autism and their families struggle with travel because of its complexity. This study aims to promote travel participation by exploring the travel needs and patterns of people with autism and their families.

A total of 28 participants were interviewed. Data were analyzed via constructivist grounded theory.

People with autism and their families displayed five travel patterns: mutual support, relatives’ visitation, independent travel, expanded socialization and package tours. These patterns were adopted in a stepwise fashion as the autistic individuals’ abilities improved. The travel challenges and support needs of Chinese autistic people and their families were identified.

The findings can inform accessibility tourism, promote an understanding of autistic people’s tourism activities among the public and industry marketers and offer strategic guidance about family travel for this population.

This effort responds to a call to investigate disability-related issues. The study evaluated the travel behavior of people with autism and their families, from a developmental perspective, presenting a new angle in research on accessibility tourism.

This study aims to explore what may have contributed to risk-taking travel behavior during the COVID-19 pandemic and what may be the drivers of satisfaction and intention to travel again. The study compares travelers based on their travel purposes (business, pleasure and visiting friends and relatives [VFR]) and explore the influence of subjective well-being received from their travel activities.

Data from a structured survey of 323 US residents who traveled during the COVID-19 pandemic were collected on MTurk. Respondents were asked travel behavior questions related to their favorite trips and to rate several multi-item scales measuring the benefits expected and received from their trip, the trip’s contribution to their positive mental and subjective psychological well-being, as well as their satisfaction with the trip and intention to travel in the future. In addition, personality measures focused on risk-taking, thrill-seeking and self-confidence, as well as additional risk-related concepts of optimism bias, probability neglect and proximity to self.

Data analysis revealed some differences among respondents who traveled for business, pleasure and VFR purposes. Business travelers were more risk takers and thrill seekers; pleasure travelers achieved more well-being benefits from their favorite trips during the pandemic; however, VFR travelers’ satisfaction and intention to go on similar trips were explained more by the benefits they received from their favorite trips.

Although several studies addressed consumers’ travel motivation during the COVID-19 pandemic, there is a lack of empirical research comparing the characteristics of travelers based on their travel purposes, as well as their sociodemographics, personality traits and the expected and perceived well-being benefits from traveling.

Purpose: This study links SDG goal 9 of industry, innovation strategies and another infrastructural environment to branding relating to destination and interactive marketing. Digital marketing tools with various applications aim to offer hi-tech services to customers in interactive marketing services, namely multiple goods and services, data and innovative techniques in the tourism and travel sector. Exploring the study would add to the existing literature supporting interactive marketing procedures and destination branding. Branding relating to destinations fosters tourists around the globe facilitating economic growth and development and supporting the local economies.

Need for the Study: It is observed from the literature that very few studies have been identified across the globe from various researchers on the interactive marketing and destination branding that ensures brand loyalty and reassesses the intent of the tourists just before the epidemic pandemic in the form of COVID-19. Artificial Intelligence, as part of information technology, offers various interactive marketing services in the form of different social media marketing strategies, attractive websites for tourists and travel providers and image building on destination branding. This study would help fill the marketing gap, which results in branding relating to destination, brand loyalty and reassessing the intent of various tours and travel plans just before the pandemic.

Methodology: The study focused on the literature, demonstrating the stimulus organism methodology and examining the impact of potential marketing strategy, which is interactive focusing on the destination branding, loyalty relating to the brand and also procedures to revert with the intent that would motivate and facilitate the customer’s confidence showering the loyalty relating to the brand in the travel and tourism sector.

Findings and their Practical Implications: The study revealed that the marketing relating to interactive methodologies in the hi-tech digital approaches ought to be carried out to create opportunities for prospective tourists willing to get information about various tourists destinations with the help of various marketing techniques such as different social media applications, easy access of websites for accessing the tourist destinations and relevant information, accessing images pertinent to the tourism destinations with the ease of chat box and providing suitable audios and video sources to the potential customers.

As the current Coronavirus 2019 pandemic eases, international tourism, which was greatly affected by the outbreak, is gradually recovering. The attraction of countries to overseas tourists is related to their overall performance in the pandemic. This research integrates the data of vaccination of different countries, border control policy and holidays to explore their differential impacts on the overseas tourists’ intention during the pandemic. This is crucial for destinations to built their tourism resilience. It will also help countries and industry organizations to promote their own destinations to foreign tourism enterprises.

This study proposes an analysis based on panel data for ten countries over 1,388 days. The coefficient of variation is used to measure monthly differences of Chinese tourists’ intention to visit overseas country destinations.

Results show that, for tourist intention of going abroad: border control of the destination country has a significant negative impact; daily new cases in the destination country have a significant negative impact; domestic daily new cases have a significant positive impact; holidays have significant negative impact; daily vaccination of the destination countries has significant positive impact; and domestic daily vaccination have negative significant impact.

First, there is a large uncertainty in studying consumers’ willingness to travel abroad in this particular period because of unnecessary travel abroad caused by the control of the epidemic. Second, there are limitations in studying only Chinese tourists, and future research should be geared toward a broader range of research pairs.

First, from the government perspective, a humane response can earn the respect and trust of tourists. Second, for tourism industry, to encourage the public take vaccine would be beneficial for both the tourism destination and foreign tourism companies. The same effect can be achieved by helping tourists who are troubled by border control.

First, this research provides suggestions for the government and the tourism industry to deal with such a crisis in the future. Second, this study found that vaccination has a direct impact on tourism. This provides a basis for improving people’s willingness to vaccinate. Thirdly, this study proves suggestion for the destinations to build tourism resilience.

This study analyzes the unique control measures and vaccination in different countries during the pandemic, then provides suggestions for the tourism industry to prepare for the upcoming postpandemic tourism recovery. This study is valuable for improving the economic resilience of tourism destinations. Additionally, it helps to analyze the advantages and disadvantages of different restrain policies around the world.

COVID-19 pandemic led to changes in the mental processes of tourists towards online travel agents. Therefore, the study aims to determine the factors affecting experiential loyalty intention of travellers during pre- and post-COVID times.

Empirical data analysis using structural equation modelling was performed in the study.

Results indicate that there is a change in the mental process of tourists. Travel companies need to understand that post-COVID, travel has transformed into a completely new world and it is essential to change behaviour accordingly. Traveller’s satisfaction would still be the key to driving loyalty of travellers towards a company.

The study implies that managers must put more effort into creating confidence among travellers because many people are still scared to travel due to the prevalence of the COVID-19 virus. Motivation to travel has declined significantly, which can only be regenerated if managers develop great strategies to drive demand from people.

This study will help in filling the gap that exists in extant literature of tourism by developing a robust model for analysing the factors enhancing experiential loyalty intention of travellers towards online travel agents in the pre- and post-COVID scenarios.

Background: The annual average daily traffic (AADT) data from road segments are critical for roadway projects, especially with the decision-making processes about operations, travel demand, safety-performance evaluation, and maintenance. Regular updates help to determine traffic patterns for decision-making. Unfortunately, the luxury of having permanent recorders on all road segments, especially low-volume roads, is virtually impossible. Consequently, insufficient AADT information is acquired for planning and new developments. A growing number of statistical, mathematical, and machine-learning algorithms have helped estimate AADT data values accurately, to some extent, at both sampled and unsampled locations on low-volume roadways. In some cases, roads with no representative AADT data are resolved with information from roadways with similar traffic patterns.

Methods: This study adopted an integrative approach with a combined systematic literature review (SLR) and meta-analysis (MA) to identify and to evaluate the performance, the sources of error, and possible advantages and disadvantages of the techniques utilized most for estimating AADT data. As a result, an SLR of various peer-reviewed articles and reports was completed to answer four research questions.

Results: The study showed that the most frequent techniques utilized to estimate AADT data on low-volume roadways were regression, artificial neural-network techniques, travel-demand models, the traditional factor approach, and spatial interpolation techniques. These AADT data-estimating methods' performance was subjected to meta-analysis. Three studies were completed: R squared, root means square error, and mean absolute percentage error. The meta-analysis results indicated a mixed summary effect: 1. all studies were equal; 2. all studies were not comparable. However, the integrated qualitative and quantitative approach indicated that spatial-interpolation (Kriging) methods outperformed the others.

Conclusions: Spatial-interpolation methods may be selected over others to generate accurate AADT data by practitioners at all levels for decision making. Besides, the resulting cross-validation statistics give statistics like the other methods' performance measures.

This paper examines the post-COVID-19 travel intentions to Kenya among Hong Kong outbound travelers using the theory of planned behavior (TPB) over three different time horizons of 1, 5, and 10 years.

An extension was made by including two new constructs of perceived destination image and travel constraints. A cross-sectional sample of Hongkongers was surveyed. Data were collected using a self-administrated bilingual (English and Chinese) online survey. Exploratory factor analysis, linear regression and mediation analysis were conducted to test the research model.

The findings from 216 Hongkongers reveal that different combinations of the four constructs, namely, perceived behavioral control, attitude, subjective norms, and destination image, share a positive effect on individuals' travel intention to Kenya over the three different time horizons. Travel constraints act as a significant negative mediator on the four constructs in predicting travel intention to Kenya among Hongkongers.

The results provide useful insight to Kenya's destination marketing organization (DMO) and Hong Kong outbound travel agencies to integrate prominent elements into marketing strategies to arouse travel intention and expand their business prospects, which will also accelerate tourism recovery in the post-pandemic era.

By integrating two extended variables into the TPB model, this study makes a contribution by overcoming the deficiency of the original theory.

The COVID-19 pandemic and the onset of the conflict in Ukraine led to a sustained downturn in tourist arrivals (TA) in Russia. This paper aims to explore the influence of geopolitical risk (GPR) and other indices on TA over 1995–2023.

We employ a nonlinear autoregressive distributed lag (NARDL) model to analyze the effects, capturing both the positive and negative shocks of these variables on TA.

Our research demonstrates that the NARDL model is more effective in elucidating the complex dynamics between macroeconomic factors and TA. Both an increase and a decrease in GPR lead to an increase in TA. A 1% negative shock in GPR leads to an increase in TA by 1.68%, whereas a 1% positive shock in GPR also leads to an increase in TA by 0.5%. In other words, despite the increase in GPR, the number of tourists coming to Russia increases by 0.5% for every 1% increase in that risk. Several explanations could account for this phenomenon: (1) risk-tolerant tourists: some tourists might be less sensitive to GPR or they might find the associated risks acceptable; (2) economic incentives: increased risk might lead to a depreciation in the local currency and lower costs, making travel to Russia more affordable for international tourists; (3) niche tourism: some tourists might be attracted to destinations experiencing turmoil, either for the thrill or to gain firsthand experience of the situation; (4) lagged effects: there might be a time lag between the increase in risk and the actual impact on tourist behavior, meaning the effects might be observed differently over a longer period.

Our study, employing the NARDL model and utilizing a dataset spanning from 1995 to 2023, investigates the impact of GPR, gross domestic product (GDP), real effective exchange rate (REER) and economic policy uncertainty (EPU) on TA in Russia. This research is unique because the dataset was compiled by the authors. The results show a complex relationship between GPR and TA, indicating that factors influencing TA can be multifaceted and not always intuitive.

This study aims to explore the challenges faced by the tourism and hospitality industry following the COVID-19 pandemic and to propose effective strategies for recovery and resilience of this sector.

The study analysed the challenges encountered by the tourism and hospitality industry post-pandemic and identified key strategies for overcoming these challenges. The study utilised the modified Delphi method to finalise the challenges and employed the Best-Worst Method (BWM) to rank these challenges. Additionally, solution strategies are ranked using the Criteria Importance Through Intercriteria Correlation (CRITIC) method.

The study identified significant challenges faced by the tourism and hospitality industry, highlighting the lack of health and hygiene facilities as the foremost concern, followed by increased operational costs. Moreover, it revealed that attracting millennial travellers emerged as the top priority strategy to mitigate the impact of COVID-19 on this industry.

This research contributes to understanding the challenges faced by the tourism and hospitality industry in the wake of the COVID-19 pandemic. It offers valuable insights into practical strategies for recovery. The findings provide beneficial recommendations for policymakers aiming to revive and support these industries.

This study aims to investigate the effectiveness of two types of social media videos used for destination image development: induced/commercial-oriented content and organic content (where content is made without commercial interest, such as vlogs classified as user-generated content).

Experimental research using “Emotive EEG” (electroencephalogram) in a controlled environment was conducted with 30 participants (20 males, 10 females), age range 18 to 26. Emotive EEG recording was performed while the participants watched both types of video clips. Test results for both groups indicate that induced content is preferred over organic content.

This study opens up future research avenues where neuromarketing’s “Marketer Friendly” EEG equipment can be applied to the customer selection process.

Marketing analysts can gauge the interest and response of customers on different types of social media video content for destination marketing based on the findings of this study.