基于网络文本分析的乡村旅游者绿色消费行为现状及促进对策——以湖南省为例
Current Situation and Promotion Strategies of Rural Tourists'Green Consumption Behavior Based on Network Text Analysis:A Case Study of Hunan Province
佘白连1
作者信息
- 1. 湖南商务职业技术学院,湖南长沙 410205
- 折叠
摘要
"双碳"目标对乡村的发展提出了要求,实施乡村全面振兴战略,推进农业农村现代化建设,始终肩负着实现"双碳"目标的责任和使命.本文选取11个文旅部公布的位于湖南省的乡村旅游重点村,采集携程、马蜂窝网站的相关点评数据505条,对其进行文本分析,构筑乡村旅游者绿色消费行为的5原则6要素N表现模型,即"5R6FNs"模型,并深入剖析乡村旅游者的绿色消费行为现状和问题.数据显示,绿色"游"表现是乡村绿色消费行为的首要内涵,乡村的大自然环境是吸引旅游者的重要因素,绿色"住""娱""食""购"是重要表现方面,绿色"行"仍有较大提升空间;并提出了保留原始生态环境,完善基础设施建设,引导绿色经营转型,加大绿色营销宣传等建议,以期助力乡村旅游可持续发展.
Abstract
The carbon peaking and carbon neutrality goals puts forward requirements for rural development,implements a comprehensive rural revitalization strategy,promotes the modernization of agriculture and rural areas,and always shoulders the goals.This paper selected 11 Key Rural Tour-ism Villages in Hunan Province announced by the Ministry of Culture and Tourism,505 relevant re-view data from Ctrip and Mafengwo websites for text analysis,established the so-called 5-principle and 6-element N performance model of rural tourists'green consumption behavior,that is,the'5R6FNs'model,and analyzed the current situation and problems of rural tourists'green consumption behavior.The data showed that green'traveling'was the primary connotation of rural green consump-tion behavior,the natural environment of the countryside was an important factor to attract tourists,and green'housing',green'entertainment',green'food'and green'shopping'were important aspects.There still was a lot of room for improvement in the green'transport'.Based on this,several sugges-tions were put forward,such as preserving the native ecological environment,improving infrastruc-ture construction,guiding the transformation of green business,and increasing green marketing and publicity,in order to promote the substantial development of rural tourism.
关键词
乡村旅游/绿色消费行为/网络文本分析/乡村振兴Key words
Rural tourism/green consumption behavior/web text analytics/rural revitalization引用本文复制引用
基金项目
2022年度湖南省教育厅科学研究项目(22C1040)
出版年
2024
国家科技期刊平台
NSTL
万方数据