The Role of Psychological Factors in Travel Constraints Effect on Leisure Travel Participation of People with Disabilities

ABSTRACTThere is literature detailing the effects of travel motivation, risks perceptions, and travel constraints on the destination image and travel behaviour of individuals. However, literature explaining these factors in the context of prospective young women travellers is scarce. This study empirically tests a comprehensive model of prospective young women’s travel behaviour, based on cognitive and affective perceptions about destination, travel motivations, perceived risks, and travel constraints. A quantitative study was performed on 370 young university women in Malaysia. The results revealed that the travel motivation of young women has positive effects on the cognitive and affective image, whereas the dimensions of perceived travel risks and travel constraints have negative effects on cognitive and affective destination images. The results also found that cognitive and affective images positively influence the visit intention of prospective young women travellers.

Discovering patterns and detecting anomalies in individual travel behavior is a crucial problem in both research and practice. In this paper, we address this problem by building a probabilistic framework to model individual spatiotemporal travel behavior data (e.g., trip records and trajectory data). We develop a two-dimensional latent Dirichlet allocation (LDA) model to characterize the generative mechanism of spatiotemporal trip records of each traveler. This model introduces two separate factor matrices for the spatial dimension and the temporal dimension, respectively, and use a two-dimensional core structure at the individual level to effectively model the joint interactions and complex dependencies. This model can efficiently summarize travel behavior patterns on both spatial and temporal dimensions from very sparse trip sequences in an unsupervised way. In this way, complex travel behavior can be modeled as a mixture of representative and interpretable spatiotemporal patterns. By applying the trained model on future/unseen spatiotemporal records of a traveler, we can detect her behavior anomalies by scoring those observations using perplexity. We demonstrate the effectiveness of the proposed modeling framework on a real-world license plate recognition (LPR) data set. The results confirm the advantage of statistical learning methods in modeling sparse individual travel behavior data. This type of pattern discovery and anomaly detection applications can provide useful insights for traffic monitoring, law enforcement, and individual travel behavior profiling.

Learned helplessness often arises when an individual feels that a challenging situation is inescapable. Childhood trauma can lead to feelings of learned helplessness in youth and adulthood. Resiliency theory suggests that positive experiences in childhood and adulthood may counteract traumatic experiences in childhood and reduce learned helplessness and promote learned optimism, the antithesis of learned helplessness. The purpose of this study was to examine the relationship of adverse childhood experiences (ACEs) with learned helplessness and optimism in adulthood and whether positive childhood and adult experiences (PCEs and PAEs) can lessen learned helplessness even in the presence of ACEs and promote greater learned optimism. The sample consisted of 435 adults who were recruited to participate in the study through Amazon Mechanical Turk (MTurk), a crowdsourcing recruitment service. Participants lived in the United States and were 18-56 years at the time of the study. Each participant completed a survey about their childhood and adulthood experiences and learned helplessness and optimism as an adult. Data were analyzed using structural equation modeling (SEM) in Mplus Version 7. The learned helplessness scale had two factors which we termed learned helplessness and learned optimism. ACEs were associated with higher self-report of learned helplessness and lower learned optimism. When PCEs were added to the model, ACEs retained their relationship with learned helplessness but were no longer associated with learned optimism. PCEs were positively associated with learned optimism but were not associated with learned helplessness. PAEs were negatively correlated with learned helplessness and positively correlated with learned optimism. Learned optimism and learned helplessness in adults were inversely correlated. Potentially traumatic experiences in childhood, as measured by ACEs, may lead to more learned helplessness throughout life. However, positive experiences in both childhood and adulthood can increase learned optimism, which was correlated with lower learned helplessness, even when childhood trauma was experienced.

PurposeThe present study examines the antecedents of learned helplessness, i.e. intrinsic and environmental constraints and consequences, i.e. intention to travel and expectation in the context of people with disability (PwD) tourism context by applying the “Theory of Learned Helplessness”.Design/methodology/approachThe survey method was used to gather data from 209 physically disabled people who had visited/traveled to any tourist destination in the past twelve months. Structural equation modeling technique was used to analyze data.FindingsThe findings reveal that intrinsic and environmental constraints positively influence learned helplessness. Consequently, learned helplessness negatively effects intention to travel and positively affects expectation of PWD tourist' toward a travel destination. Furthermore, learned helplessness contributed as a mediator between intrinsic constraints and intention to travel toward a tourist destination.Originality/valueEven though the body of literature on associations studied pertaining the conceptual lens of learned helplessness is widely recognized, there is dearth of literature investigating the connections between travel constraints, learned helplessness, PwDs intention and their expectation in travel destination context.

Travel constraints in contemporary Nigeria have affected all sectors of the economy. This trend had impacted on small traders in terms of higher cost of doing business, and individual travel behavior over time. Insecurity and travel time constraints had affected the growth of the entrepreneurial environment in most cities in Nigeria. In some regions trade and commerce have experienced very low performance. In most of the Northern Eastern states and big commercial centers in Kano, markets and commercial activities have remained closed due to high security alerts. Aims: To highlight various travel constraints affecting mobility as a result of the growing insecurity on Nigerian roads. Study Design: This study examines some literature on discrete choice and travel-based models. Place and Duration of Study: Contemporary travel constraints in Nigeria from 2000‐ 2012, and the growing ethno-religious crisis in different parts of the country. Methodology: Review of literature. Results/observations: The working of these models is effective where the choice set is not constrained, and the independent irrelevant alternatives (IIA) may not include options/alternatives with a “lesser evil” definitions. This is because it is restrictive for behavioural choice, (utility may be ranked). In advanced market economies, infrastructure has been a springboard for creating and enhancing trade hubs that promotes trade and commerce. A high Infrastructure gap exists in less developed countries as a result of fiscal policy problems, high population and the process of prioritizing development Review Article

Residential relocation and changes in travel behavior: what is the role of social context change?

BackgroundSocial support, which is a crucial external resource for cancer patients, was demonstrated to be a positive predictor of learned helplessness (LH). But it is far from clear whether and how social support decreases the LH in cancer patients. The purpose of present study is to detect the association between social support and LH and the role of individual resilience and self-efficacy in mediating this relationship.MethodsThe convenience sampling method was utilized. From August 2022 to February 2024, a total of 537 lung cancer patients (Mage = 60.25 years, SDage = 9.85 years) from five tertiary hospitals in one municipalities (Chongqing), and two provinces (Sichuan and Yunnan) were recruited, among which 389 were males and 148 were females. LH, social support, individual resilience, and self-efficacy were assessed by using standard scales. A structural equation model was constructed employing AMOS 23.0 to examine the interrelationships among social support, individual resilience, self-efficacy, and LH of lung cancer patients.ResultsA total of 537 lung cancer patients were finally included. Social support, individual resilience, and self-efficacy were positively related to LH (r = −0.299 to −0.451, p < 0.01). The mediation model revealed that the direct effect of social support on LH was significant (β = −0.407, p < 0.001). Besides, social support could also affect LH through three pathways: (1) the mediating effect of individual resilience (β = −0.075, p < 0.001); (2) the mediating effect of self-efficacy (β = −0.060, p < 0.05); (3) the chain mediating effect of individual resilience and self-efficacy (β = −0.011, p < 0.05).ConclusionThe results indicate that social support alleviates lung cancer patients’ LH, and that individual resilience and self-efficacy mediate the correlation between social support and LH. Besides providing adequate social support, intervention strategies built on individual resilience and self-efficacy should be applied to reduce LH in lung cancer patients.

Goal and objectives of the dissertationGoalNorth America is the biggest long haul tourist market to Europe, but the number of tourists has been decreasing over the last years and most of these trips are to cities. In spite of the relevance of this market to Europe it has been understudied by researchers. Therefore, the purpose of this study is to examine the role of travel constraints, nostalgia and travel experience in shaping North American tourists' intentions to revisit rural European destinations.ObjectivesFor to achieve the purpose the work the following research questions were addressed:RQ1. What is the definition and scope of nostalgia, and how can this construct be operationalized in the context of North American tourists returning to rural Europe?Addressing RQ1 required following standard scale development steps as outlined by DeVellis (2003). To address RQ 1 the following hypotheses were tested:* H1: Nostalgia evoked by tourism has four dimensions, namely, personal, intrapersonal, cultural and virtual.* H2: Past positive time perception is positively related to nostalgia.RQ2. To what extent do travel constraints, nostalgia and travel experience influence North American tourists' intentions to revisit rural destinations in Europe?To address RQ2 the following hypotheses were tested:* H3: Nostalgia has a positive direct effect on the intentions to return rural Europe.* H4: Travel constraints have a negative direct effect on intentions to return to rural Europe* H5: Travel constraints have a positive direct effect on nostalgia.* H6: Nostalgia positively mediates the negative relationship between travel constraints and intentions to return to Europe.* H7: Constraints have a positive direct effect on negotiation.* H8: Negotiation has a positive direct effect on intentions to return to Europe.* H9: Experience in travel has a positive direct effect on intentions to return to rural Europe.MethodologyTo achieve the objectives of the thesis the methodology used was based on the application of a questionnaire-based survey. The research was done following several steps starting with an exploratory revision of literature. In the beginning the main theme of the thesis was to analyse multi-destination travel patterns of the North American market to Europe. First, the literature review showed that an analysis of the travel patterns of this market to Europe could be difficult, since it is a large territory, and eventually could not give clues to what could make this market to return and make rural holidays. The second step was based in an exploratory study undertake for three months in a region of USA based on a qualitative technique, namely, participant observation and semi-structured interviews. From this study resulted the constructs that were the theoretical basis for the construction of the research framework. After a review of literature and the development of the proposed model the program SPSS (version 19) was used for the univariate analysis, Exploratory Factor Analysis, t-tests and the program AMOS (version 19) to develop Confirmatory Factor Analysis and Structural Equation Modelling analysis.ResultsFirst, the hypothesis regarding the composition of the nostalgia scale was validated and then its mediating effect on the relationship between travel constraints to travel and intention to revisit rural Europe, then the remaining hypotheses were analyzed through their inclusion within the structural equation model. The confirmed hypotheses are H1, H2, H3, H4, H5, H8. The rejected hypothesis is H7. Partially accepted hypotheses are:* H6: Was rejected in its separate test, but accepted within the overall model.* H9: This hypothesis is partially accepted, because expertise does not affect travel experience.Theoretical conclusionsIn summary, travel experience, nostalgia and negotiation have a positive relation with the intentions to revisit rural areas in Europe. …

In December 2019, a novel and contagious coronavirus also known as Covid-19 outbroke in Wuhan, China. In response to the virus, many countries implemented strict travel restrictions and lockdowns to hold back the spread of the Covid-19. The measures to contain it have brought dramatic changes in individual lifestyles, daily activities and travel behavior. This study focuses on the impacts on individual travel behavior including work/education, shopping and out-of-home physical activities in the state of Qatar. In addition, the study also presents individuals’ expectations and preferences regarding future travel activities. The Qatar Transportation and Traffic Safety Center, QTTSC conducted a questionnaire survey investigate the impacts of Covid-19 on individuals’ travel behavior. The questionnaire survey included questions regarding individuals’ travel activities for work/education, shopping, out-of-home workouts, before and during Covid-19 and the individual preferences and expectation for changes in their daily travel-activity in the future. After removal of the incomplete entries and outliers, the analyses were done including 404 respondents residing in Qatar for whom 63% were males while 36% were females. The results showed that there were drastic drops for all the activity types. Around 73% of the respondents started work-from-home or online education. The results also revealed that more than 20% of the respondents who were traveling in a group before the Covid-19 pandemic chose to travel alone during the Covid-19 crisis. Most of them were traveling with family before the Covid-19 outbreak. The results for individual expectations and preference revealed that highly educated respondents will prefer to continue work-from-home or bulk shopping. Young and/or Western people prefer to rely more on online shopping. The findings from this study could be very useful for policymakers and other relevant authorities to construct flexible work/education/business policies. This could help them to effectively respond to any future outbreaks and to smartly utilize the available resources of the transport system during post-pandemic and new-normal times.

This paper presents a novel method for mining the individual travel behavior regularity of different public transport passengers through constructing travel behavior graph based model. The individual travel behavior graph is developed to represent spatial positions, time distributions, and travel routes and further forecasts the public transport passenger’s behavior choice. The proposed travel behavior graph is composed of macronodes, arcs, and transfer probability. Each macronode corresponds to a travel association map and represents a travel behavior. A travel association map also contains its own nodes. The nodes of a travel association map are created when the processed travel chain data shows significant change. Thus, each node of three layers represents a significant change of spatial travel positions, travel time, and routes, respectively. Since a travel association map represents a travel behavior, the graph can be considered a sequence of travel behaviors. Through integrating travel association map and calculating the probabilities of the arcs, it is possible to construct a unique travel behavior graph for each passenger. The data used in this study are multimode data matched by certain rules based on the data of public transport smart card transactions and network features. The case study results show that graph based method to model the individual travel behavior of public transport passengers is effective and feasible. Travel behavior graphs support customized public transport travel characteristics analysis and demand prediction.

The purposes of this research were to examine the most important travel motivations for Omani tourists to attend sporting events, and to identify travel constraints which impeded them from travelling to attend sporting events. Questionnaires were used to collect data from 166 Omani tourists attended sporting events. Research findings showed that enjoy stadium atmosphere; support my team; spend my time without worrying about my study/work; spend time with my friends and family; and escape from the ordinary or routine environment at home were the most important travel motivations for Omani tourists to attend sporting events. The study also revealed that financial challenges (a lack of money); lack of time and opportunities to travel; and work and study commitments were the main travel constraints that inhibit Omani tourists from travelling to attend sporting events. Finally, other useful statistical findings regarding participants’ travel behaviour are reported.

transfer, create conditions for the establishment of farmers' behavioral psychological contracts in the process of agricultural land transfers, and guide farmers to establish relationship psychological contracts. The second is to improve the market system, properly cultivate and develop agricultural land transfer intermediaries, reduce transaction costs, and reduce the probability of farmers' psychological contracts being broken. The third is to guide farmers to establish a positive agricultural land transfer psychology based on their resource endowments such as labor force quality and cultural quality, and encourage farmers to make agricultural land transfer decisions such as subcontracting, leasing, reselling, and interchanging.

Modeling and analyzing of family intention for the customized student routes: A case study in China

In this study, we investigated the mediating effects of classroom silence and academic self-efficacy on the relationship between English classroom climate and learned helplessness among vocational college students. A total of 501 students from 5 postsecondary vocational colleges in Fujian Province, China, were assessed using the Classroom Climate Scale, Classroom Silence Scale, Learning Self-Efficacy Scale, and English Learned Helplessness Scale. Structural equation modelling was used to evaluate the mediating effects of classroom silence and academic self-efficacy on the relationship between classroom climate and learned helplessness. We found that perceived classroom climate negatively affected students’ learned helplessness. In addition, classroom silence and academic self-efficacy fully mediated the relationship between perceived classroom climate and learned helplessness. This study provides relevant recommendations for educational administrators, English teachers, and students.

Exploring the changes of individuals’ travel behavior in response to COVID-19 and their influencing factors based on mobile phone data