Interrelationships between tourist involvement, tourist experience, and environmentally responsible behavior: a case study of Nansha Wetland Park, China

Xu, Songjun; Kim, Hyun Jeong; Mao, Liang; Ryu, Kisang

doi:10.1080/10548408.2018.1439429

Cited by 99 publications

(64 citation statements)

References 58 publications

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“…Regarding its controversy, this study could contribute to the literature by demonstrating significant impact of ease of use in the coffee shop customer research domain. Furthermore, this work clarifies the link between environmental responsibility in prior studies [81] and purchase intention in the café business. Even though the results appeared to be non-significant, elucidation considering the effect of environmental responsibility on purchase intention appeared in the café business domain.…”

Section: Theoretical Implicationssupporting

confidence: 61%

Antecedents of Purchase Intention at Starbucks in the Context of Covid-19 Pandemic

et al. 2021

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The purpose of this research is to examine the determinants of coffee shop purchase intention. The research domain is Starbucks, which is the brand ranked first in the coffee shop market. This study selects healthiness, hygiene, quarantine, ease of app use, and environmental responsibility as candidates for the antecedents of purchase intention. For hypothesis testing, this research used a survey and recruited survey participants using Amazon Mechanical Turk, and carried out multiple linear regressions to test research hypotheses. The number of valid observations for the data analysis is 474. It was found that purchase intention is positively influenced by healthiness, hygiene, quarantine, and ease of app use. However, environmental responsibility was identified as a nonsignificant attribute to account for purchase intention. Practical implications are presented for coffee shop management. The outcomes contribute to the literature by scrutinizing café customers’ purchase intention with various attributes.

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Section: Theoretical Implicationssupporting

confidence: 61%

Antecedents of Purchase Intention at Starbucks in the Context of Covid-19 Pandemic

et al. 2021

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“…The survey questionnaire included the description of the study, the questions for research variables, and the questions regarding personal characteristics. To evaluate research variables, the measures were employed from the exiting studies (Gascon et al, ; Han & Hyun, ; Hennig‐Thurau, ; Lee et al, ; Moon et al, ; Oliver, ; Pietilä et al, ; Vujcic et al, ; Xu et al, ). Multiple items and 7‐point Likert scales were used.…”

Section: Methodsmentioning

confidence: 99%

Impact of airport green atmospherics on mental health value, image, and loyalty among visitors and workers

et al. 2020

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Nature‐based solutions (NBS) are becoming increasingly crucial as NBS brings diverse health‐related benefits to travelers and workers in the tourism business sector. This research explored the influence of green atmospherics as NBS on airport occupants' mental health value, image, and loyalty generation processes. A quantitative approach with a field survey method was employed. A structural equation modeling and metric invariance test were used as data analysis technique. Our empirical result revealed that green atmospherics as NBS significantly improve the occupants' mental health value and image of the airport, and these variables contribute to their loyalty enhancement for the airport. The effect of green spaces and natural surroundings on loyalty was maximized through mental health value and image. In addition, the linkages from natural surroundings to mental health value and image were stronger in the visitor group whereas the mental health value—loyalty relation was stronger in the worker group.

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“…Hwang et al, 2019; J. Hwang & Lee, 2019; Jeaheng et al, 2019; Xu et al, 2018). SEM has two major types: factor-based and composite-based SEM.…”

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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Interrelationships between tourist involvement, tourist experience, and environmentally responsible behavior: a case study of Nansha Wetland Park, China

Cited by 99 publications

References 58 publications

Antecedents of Purchase Intention at Starbucks in the Context of Covid-19 Pandemic

Antecedents of Purchase Intention at Starbucks in the Context of Covid-19 Pandemic

Impact of airport green atmospherics on mental health value, image, and loyalty among visitors and workers

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

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