忠诚
营销
业务
消费者满意度
旅游
目的地
广告
经济地理学
地理
考古
作者
Y. Andrew Hao,Mohd Fabian Hasna,Faziawati Abdul Aziz
出处
期刊:Tourism Review
[Emerald Publishing Limited]
日期:2025-04-12
标识
DOI:10.1108/tr-08-2024-0750
摘要
Purpose As landscape is a prerequisite for tourism destinations with rich aesthetic connotations, destination aesthetics research is becoming increasingly indispensable in tourism dynamics. However, previous landscape aesthetics literature has mostly focused on a single attribute, type and region, lacking a comprehensive assessment of its impact on tourists’ behavioral decisions. Therefore, this study aims to reveal the universality and specificity of the impact of landscape aesthetic attributes on tourists’ satisfaction and loyalty through meta-analysis. Design/methodology/approach In this study, a random model of the meta-analysis was used to test the effects of landscape aesthetic attributes (uniqueness, novelty, conditionality, harmony and authenticity) on tourist satisfaction and loyalty. Moderating variables (gender, previous visit, place of origin and landscape type) were tested by subgroup and meta-regression analyses. Findings The results showed that all aesthetic attributes can positively influence satisfaction and loyalty, except for novelty-satisfaction was not significant. Landscape uniqueness was important for satisfaction and loyalty, while harmony and condition were relatively unimportant. The analysis of moderating variables of gender, prior visit, geographic origin of the study and landscape type further revealed potential reasons for the divergence of previous research findings. Social implications Destination planners and related managers can formulate scientific and reasonable policies and actionable programs for tourism landscape development based on the results of this study, which promotes the effective combination of theory and practice. Originality/value The findings enrich the theoretical study of destination aesthetics and are valuable for understanding tourist attitudes and behaviors, filling the current research gap in meta-analysis.
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