Understanding the acceptance of carbon offset programs among hospitality consumers: an application of the extended parallel process model

The tourism and hospitality (T&H) industry can significantly impact the environment by using natural resources and waste generation. Measuring and improving firms’ emission performance in this industry is becoming increasingly important. However, the prediction of financial indicators and governance scores on firms’ emission performance is still poorly established. Drawing on the agency and stakeholders’ theory, our research explores whether financial indicators and governance scores predict firms’ emission performance in the T&H industry. Data on all companies that are publicly traded was acquired from Thomson Reuters Eikon using 485 publicly traded tourism firms as of the end of the fiscal year 2021. Our findings suggest that governance pillar score (GP), management score (MS), board size (BS), and market capitalization (MC) are the best four predictors of carbon emission reduction scores in T&H companies. Theoretical and practical implications are presented, and directions for further research are provided.

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Study on the Strength of Rural Tourism Operators’ Willingness to Carbon Offset and Its Influencing Mechanisms

Song,

Wang,

et al. 2024

Sustainability

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Tourism operators generate carbon emissions during their operations, and their environmental responsibility behaviors, such as carbon offsetting, significantly impact the ecological environment of tourist sites. Understanding the operators’ willingness to engage in carbon offsetting and the factors influencing this willingness is crucial for achieving the “dual carbon” goals and promoting sustainable growth in China’s tourism sector. This study collected 746 offline questionnaires from operators at rural tourism sites across 100 counties and districts in Jiangxi Province. It empirically analyzed their willingness to participate in carbon offsetting, comparing various factors such as the strength of willingness, spatial differences, and distinctions between all-for-one tourism counties and non-all-for-one tourism counties, as well as suburban, outer suburban, and remote tourism sites. Using the value–belief–norm theory and the theory of planned behavior, a structural equation model was developed to comprehensively examine the operators’ willingness and its influencing mechanisms. The structural statistical analysis revealed that the integrated model effectively predicted rural tourism operators’ willingness to participate in carbon offsetting. The results showed that, except for Hypothesis 6, all suggested correlations between the variables were significant. Value perception had a significantly positive effect on participants’ desire to engage in carbon offsetting. This research provides various theoretical and practical implications for local authorities regarding rural tourism operators, advancing the incentive for carbon offsetting and sustainable tourism development.

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Understanding the acceptance of carbon offset programs among hospitality consumers: an application of the extended parallel process model

Cited by 3 publications

References 64 publications

Who is sharing green eWOM? Big data evidence from the travel and tourism industry

Who is sharing green eWOM? Big data evidence from the travel and tourism industry

The predictive roles of financial indicators and governance scores on firms’ emission performance in the tourism and hospitality industry

Study on the Strength of Rural Tourism Operators’ Willingness to Carbon Offset and Its Influencing Mechanisms

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