Impact of distance on the arrivals, behaviours and attitudes of international tourists in Hong Kong: A longitudinal approach

Manosuthi, Noppadol; Lee, Jin Soo; Han, Heesup

doi:10.1016/j.tourman.2019.103963

Cited by 54 publications

(33 citation statements)

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“…Attitude is indubitably a significant factor influencing individuals' intention generation process and behaviors ( Bernerth, 2020 ; Perugini & Bagozzi, 2001 ; Xiong & King, 2019 ). The concept of an attitude refers to one's overall assessment of whether a specific object is either favorably or unfavorably valued ( Ajzen, 2012 ; Ajzen & Kruglanski, 2019 ; Manosuthi et al, 2020 ). In the present research, attitude toward the airline indicates employees' general evaluation concerning whether working for their airline company is positively or negatively valued.…”

Section: Literature Reviewmentioning

confidence: 99%

Are airline workers planning career turnover in a post-COVID-19 world? Assessing the impact of risk perception about virus infection and job instability

Han

Koo

Ariza-Montes

et al. 2021

Journal of Hospitality and Tourism Management

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Airline workers have been suffering risks of job instability and virus infection since the outbreak of COVID-19. This research developed a novel framework explicating airline workers' career turnover decision formation by considering the influence of perceived risks of virus infection and job instability during the COVID-19. A quantitative approach using a survey method was utilized to attain research goals. Our empirical findings revealed that airline image, attitude, and commitment have a significant influence on employee career turnover intention. Both attitude and commitment were identified as essential mediators. In addition, perceived risks of virus infection and job instability significantly moderated the relationships among attitude, commitment, and employee career turnover intention. The effectiveness of the proposed theoretical framework for career turnover intention was demonstrated. Our findings help researchers and entrepreneurs find effectual ways to lower competent workers’ career turnover and raise their approach behaviors in a post-COVID-19 world.

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Section: Literature Reviewmentioning

confidence: 99%

Are airline workers planning career turnover in a post-COVID-19 world? Assessing the impact of risk perception about virus infection and job instability

Han

Koo

Ariza-Montes

et al. 2021

Journal of Hospitality and Tourism Management

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“…By contrast, proxies in composite-based SEM are conceptualized as a weighted linear combination of indicators, called composites. Although factor-based SEM is regularly used in social and behavioral sciences, composite-based SEM has gained considerable attention in various fields, such as marketing (Hair, Sarstedt, Ringle, & Mena, 2012), strategic management (Hair, Sarstedt, Pieper, & Ringle, 2012), international management (Sinkovics et al, 2016), and tourism and hospitality (Ali et al, 2018; Manosuthi et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

An Innovative Application of Composite-Based Structural Equation Modeling in Hospitality Research With Empirical Example

Manosuthi

Lee

Han

2020

Cornell Hospitality Quarterly

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Partial least squares path modeling (PLS-PM) and generalized structured component analysis (GSCA) are two key estimators derived from a full-fledged composite-based structural equation modeling (SEM). The analyses of PLS-PM and GSCA have been recently extended to mimic factor-based SEM, and the extended approaches are called PLSC and GSCAM, respectively. Simulation studies have confirmed that the relative performance of PLS-PM is comparable with that of GSCA. Similarly, GSCAM, PLSC, and the traditional factor-based SEM perform equally well in parameter recovery. Although composite-based SEM perfectly fits into the current research landscape that focuses on a prediction-oriented approach, empirical research in the hospitality context that uses PLS-PM, GSCA, PLSC, and GSCAM estimators is extremely rare. To encourage hospitality researchers to adopt these methodologies, we demonstrate an illustrative example using PLS-PM, GSCA, PLSC, and GSCAM based on the confirmatory composite analysis (CCA) procedure. Measurement and structural invariances, applications of model fit, PLSpredict, and importance-performance map analysis are incorporated into our example. Finally, practical management in the hospitality field based on this methodology is discussed.

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“…The desired outcomes (or variables of interest) can be the annual performance of the hospitality company, the number of service failure incidents in each year, and any periodical information that describes the firms’ performance. Other possible examples of longitudinal analysis in hospitality and tourism fields would be identifying how the hospitality firms’ revenue eventually changes after launching a new advertisement, the relationship between consumers’ levels of satisfaction and repeated purchases, how emotional labor employees manage stress after completing an emotional intelligence training program, or how tourists use social media differently before, during, and after travel [ 52 , 53 ]. By employing the GMM approach to the longitudinal data, researchers can identify the dominant patterns of changes in the variable of interest among samples and the possible influencing factors from the research findings.…”

Section: Discussionmentioning

confidence: 99%

Sustainable Growth of Social Tourism: A Growth Mixture Modeling Approach Using Heterogeneous Travel Frequency Trajectories

Lee

Baek

2021

IJERPH

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As travel activity has gained attention as one of the essential ways of understanding the sustainable growth of social tourism, a growing number of research projects have been conducted to elucidate the relationship between residents’ travel quantity (frequency) and quality (experience) in both macro and micro perspectives. Yet, very little research has highlighted that travel opportunities are not equally available to residents, especially a longitudinal perspective. The current study classified domestic travelers into four distinct classes using four years of longitudinal data from 5054 Korean residents. Latent growth curve modeling (LGCM) and growth mixture modeling (GMM) were employed to find out (1) the optimal number of classes, (2) the longitudinal travel frequency trajectory of each class, and (3) the distinctive demographic and travel characteristics of the four classes. This study provides some practical implications for policymakers when optimizing available resources for sustainable travel opportunities to relevant target sub-populations. Furthermore, detailed step-by-step analytic tutorials are also introduced for the extended application of longitudinal latent variable analysis in the tourism and hospitality fields, providing additional insights for relevant stakeholders.

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Impact of distance on the arrivals, behaviours and attitudes of international tourists in Hong Kong: A longitudinal approach

Cited by 54 publications

References 100 publications

Are airline workers planning career turnover in a post-COVID-19 world? Assessing the impact of risk perception about virus infection and job instability

Are airline workers planning career turnover in a post-COVID-19 world? Assessing the impact of risk perception about virus infection and job instability

An Innovative Application of Composite-Based Structural Equation Modeling in Hospitality Research With Empirical Example

Sustainable Growth of Social Tourism: A Growth Mixture Modeling Approach Using Heterogeneous Travel Frequency Trajectories

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