"两山"视阈下汕尾文旅融合发展的路径研究
Research on the Path of Integrated Development of Culture and Tourism in Shanwei from the Perspective of"Two Mountains"
吕莎丽1
作者信息
- 1. 汕尾职业技术学院 经贸学院,广东 汕尾 516600
- 折叠
摘要
"两山论"是习近平生态文明思想的核心内容,深刻揭示了生态保护与经济发展辩证统一的关系.旅游业是践行"两山理论"的绿色产业.汕尾文旅深度融合、生态发展是区域高质量发展的时代要求.汕尾作为粤东后花园,拥有良好的生态环境、悠长的文化底蕴和丰富的文化旅游资源,为文旅融合发展奠定了良好基础.汕尾文旅融合有着广阔前景并取得一定成效,但仍存在着文旅产品不够丰富、文化资源的保护传承和开发利用不足、文旅产业创新性发展效果不理想、文旅产业延伸不足等问题.针对存在的问题,本文提出了发展路径:按照"生态优先、绿色发展"理念,践行"两山论",完善居游品质,深入挖掘汕尾的文化资源,基于体验需求创新赋能旅游产品,构建数字战略新格局,深度融合文化和旅游,以推动汕尾文旅融合的智慧化、生态化发展.
Abstract
The"Two Mountains Theory",being the core of Xijinping Thought on Ecological Civilization thought,profoundly reveals the dialectical unity between ecological protection and economic development.Tourism is a green industry that practices this theory.The integration of Shanwei's culture and tourism and ecological development are the requirements for regional high-quality development in the new era.As the backyard of eastern Guangdong,Shanwei has a good ecological environment,a long cultural heritage and rich cultural tourism resources,which has laid a good foundation for the integrated development of culture and tourism.Such an integration in Shanwei has broad prospects and has achieved certain results,but there are still problems such as insufficient relevant products,insufficient protection,transmission and exploita-tion of cultural resources,unsatisfactory innovative development and insufficient extension of of the in-dustry.To achieve the integrated development in an intelligent and ecological way,it's proposed to prac-tice the"Two Mountains Theory"following the concept of"ecology first and green development",improve the quality of residence and tourism,fully explore Shanwei's cultural resources,innovate and empower tourism products based on experience needs,and build a new digital strategy for comprehensive integration.
关键词
"两山论"/生态文明/文旅融合发展/数字战略Key words
"Two Mountains Theory"/Ecological Civilization/Integrated Development of Culture and Tour-ism/Digital Strategy引用本文复制引用
出版年
2024
NETL
NSTL
万方数据