Hierarchical Variance Analysis: A Quantitative Approach for Relevant Factor Exploration and Confirmation of Perceived Tourism Impacts

• Main Authors: Quang Hai Truong, An Thinh Nguyen, Quoc Anh Trinh, Thi Ngoc Lan Trinh, Luc Hens
• Format: Article
• Language: English
• Published: MDPI AG 2020-04-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: hierarchical variance analysis; residents’ perceptions; socio-demographic variables; ANOVA; linear regression model; perceived tourism impacts
• Online Access: https://www.mdpi.com/1660-4601/17/8/2786

The issue of tourism impacts is one that has plagued the tourism industry. This study develops a quantitative approach using hierarchical variance analysis, which deals with the exploration of the relevant factors and the confirmation of their significant contribution to analyze the residents’ perception of tourism impacts. Hierarchical variance analysis includes three mathematical procedures: Cronbach’s alpha tests, the exploration of relevant factors, and a hierarchical factor confirmation. Data are collected using a structured questionnaire completed by 452 surveyed residents living in Ly Son Island, Vietnam. The significant effects of socio-demographic variables on the overall impact assessment are observed. The bilateral and simultaneous relationships are analyzed using a one-factor ANOVA. A two-factor ANOVA shows the significant contribution of each socio-demographic variable on the economic, socio-cultural, and environmental impacts. Interaction between factors such as “Education level”, “Type of work”, etc. are hierarchically confirmed. The findings allow a better understanding of the residents’ perception of the effects of tourism on society, the economy, and the environment. This provides a scientific basis to help define problems and promote legal regulations for community participation in tourism planning in a small island destination.