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Data on the relationship between traveller perceived value and traveller intention to revisit a destination.

ABSTRACT: Data was collected at the OR Tambo Airport in Johannesburg South Africa from 503 willing international tourists. The survey was self-administered over a two-month period. Due to the absence of a sampling frame, non-probability sampling was adopted in selecting participants. A unique conceptual model was developed to test the causal effect of traveller perceived value on cognitive and affective destination image as well as on traveller intention to revisit. In addition, the direct effect of cognitive and affective destination image on traveller intention to revisit was also measured. Analysis of data involved descriptive statistics and structural equation modeling conducted in the Statistical Package for the Social Sciences (SPSS) 25 and Analysis of Moment Structures (AMOS) 25 respectively. Descriptive statistics produced frequencies on gender, age, travels, purpose of trip and holidays associated with each respondent. Structural equation modeling was conducted following a two-step process. First, confirmatory factor analysis followed by hypothesis testing. Further research could assess the possibility of a link between affective and cognitive destination image.

SUBMITTER: Chuchu T

PROVIDER: S-EPMC6736770 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Data on the relationship between traveller perceived value and traveller intention to revisit a destination.

Chuchu Tinashe T

Data in brief 20190827

Data was collected at the OR Tambo Airport in Johannesburg South Africa from 503 willing international tourists. The survey was self-administered over a two-month period. Due to the absence of a sampling frame, non-probability sampling was adopted in selecting participants. A unique conceptual model was developed to test the causal effect of traveller perceived value on cognitive and affective destination image as well as on traveller intention to revisit. In addition, the direct effect of cogni ...[more]

PMID: 31516956

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Project description:BackgroundConsidering the increasing demand for health services by older people and the ongoing COVID-19 pandemic, digital health is commonly viewed to offer a pathway to provide safe and affordable health services for older adults, thus enabling self-management of their health while health care systems are struggling. However, several factors cause older people to be particularly reluctant to adopt digital health technologies such as mobile health (mHealth) tools. In addition to previously studied technology acceptance factors, those related to perceived risks of mHealth use (eg, leakage of sensitive information or receiving incorrect health recommendations) may further diminish mHealth adoption by older adults.ObjectiveThe aim of this study was to explore the relationship between perceived risks of using mHealth applications and the intention to use these applications among older adults.MethodsWe designed a cross-sectional study wherein a questionnaire was used to collect data from participants aged 65 years and older in the Netherlands. Perceived risk was divided into four constructs: privacy risk, performance risk, legal concern, and trust. Linear regression analyses were performed to determine the associations between these perceived risk constructs and the intention to use mHealth applications.ResultsLinear regression per perceived risk factor showed that each of the four constructs is significantly associated with the intention to use mobile medical applications among older adults (adjusted for age, sex, education, and health status). Performance risk (β=-.266; P=<.001), legal concern (β=-.125; P=.007), and privacy risk (β=-.100; P=.03) were found to be negatively correlated to intention to use mHealth applications, whereas trust (β=.352; P=<.001) was found to be positively correlated to the intention to use mHealth applications.ConclusionsPerformance risk, legal concern, and privacy risk as perceived by older adults may substantially and significantly decrease their intention to use mHealth applications. Trust may significantly and positively affect this intention. Health care professionals, designers of mHealth applications, and policy makers can use these findings to diminish performance risks, and tailor campaigns and applications to address legal and privacy concerns and promote mHealth uptake and health care access for older adults, especially during the COVID-19 pandemic.

Project description:OBJECTIVES:Many countries are driving forward policies to widen the socioeconomic profile of medical students and to train more medical students for certain specialties. However, little is known about how socioeconomic origin relates to specialty choice. Nor is there a good understanding of the relationship between academic performance and specialty choice. To address these gaps, our aim was to identify the relationship between socioeconomic background, academic performance and accepted offers into specialty training. DESIGN:Longitudinal, cohort study using data from the UK Medical Education Database (https://www.ukmed.ac.uk/). PARTICIPANTS:6065 (60% females) UK doctors who accepted offers to a specialty training (residency) post after completing the 2-year generic foundation programme (UK Foundation Programme) between 2012 and 2014. MAIN OUTCOME MEASURES:Χ2 tests were used to examine the relationships between sociodemographic characteristics, academic ability and the dependent variable, specialty choice. Multiple data imputation was used to address the issue of missing data. Multinomial regression was employed to test the independent variables in predicting the likelihood of choosing a given specialty. RESULTS:Participants pursuing careers in more competitive specialties had significantly higher academic scores than colleagues pursuing less competitive ones. After controlling for the presence of multiple factors, trainees who came from families where no parent was educated to a degree level had statistically significant lower odds of choosing careers in medical specialties relative to general practice (OR=0.78, 95% CI, 0.67 to 0.92). Students who entered medical school as school leavers, compared with mature students, had odds 1.2 times higher (95% CI, 1.04 to 1.56) of choosing surgical specialties than general practice. CONCLUSIONS:The data indicate a direct association between trainees' sociodemographic characteristics, academic ability and career choices. The findings can be used by medical school, training boards and workforce planners to inform recruitment and retention strategies.

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Data on the relationship between traveller perceived value and traveller intention to revisit a destination.

Publications

Data on the relationship between traveller perceived value and traveller intention to revisit a destination.

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