Integrating Chinese values into the prediction of Chinese visitors’ pro-environmental behaviours in Australia: An extended Theory of Planned Behaviour (TPB) model

Updated: 7 months ago
Location: Mount Lawley, WESTERN AUSTRALIA
Deadline: ;

Project Outline:
China is Australia’s most valuable tourist market and in the coming years the market scale of Chinese tourists to Australia will continue to grow. Australia possesses a valuable ecological system with its national parks, pristine beaches and rare wildlife serving as tourism resources and attractions. Understanding and regulating Chinese tourists’ pro-environmental behaviours in Australia from a cultural perspective is important to the sustainable development of Australian tourism economy. This study proposes and tests a tourist behaviour model integrating the pertinent Chinese cultural values identified by Hsu and Huang (2016) in the tourism context into the framework of theory of planned behaviour (Ajzen, 1991), in predicting Chinese tourists’ pro-environmental behaviour. The study contributes to the application of Chinese values in tourism studies. It also aims to extend the theory of planned behaviour and test the link between values and human behaviour. Targeting environmental behaviour, the study also enhances our understanding of human-environment relationships and interactions in the tourism context. Findings of this study are expected to benefit the tourism-related industries and sectors in Australia and help industry practitioners to develop their cultural understanding and competency toward the Chinese tourist market.

A mixed-method approach will be adopted to guide the implementation of this research. In-depth interviews and focus groups are considered before administering a large scale questionnaire survey. Structural Equation Modelling will be the methodology for the quantitative component of the study.

Desired Skills: Prior research experience and knowledge; good understanding of statistics in social sciences; mastery of quantitative data analysis methods including multiple linear regression, logistic regression, and structural equation modelling.

Project Area: Tourism, marketing, business and management

Supervisor(s): Professor Sam Huang

Project level: PhD

Funding: Applicant should apply for ECUHDR or RTP Scholarship

Start date: 2018

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