摘要
在“双碳”目标下提升旅游业碳排放效率愈发紧迫,而数字经济的兴起为提高旅游业碳排放效率带来了新的机遇。基于2005—2019年云南省16个州市的数据,采用非期望SBM模型、熵权法分别测度旅游碳排放效率和数字经济发展水平并进行空间可视化分析,随后利用核密度估计分析旅游业碳排放效率空间效应,最后运用动态QCA分析数字经济对旅游业碳排放效率的组态路径。研究发现:(1)研究期内云南省旅游业碳排放效率呈现先下降后上升的“V”型发展趋势,数字经济发展水平呈现波动上升趋势;(2)旅游业碳排放效率和数字经济发展水平呈现明显的空间差异,旅游业碳排放高效率聚集地区由滇西地区逐渐转移至滇中地区,数字经济发展高水平地区主要分布在滇中;(3)各州市旅游业碳排放效率的分布状态变化较小,滇南、滇西南等存在高-低聚集的负向空间相关性;(4)通过动态QCA分析发现数字经济有3种组态能实现高旅游业碳排放效率,进一步提炼为数字基础推动型和数字人才驱动型,部分州市受组态影响较小。
Improving carbon emission efficiency in the tourism industry has become increasingly urgent under the"dual carbon"goal,and the rise of the digital economy offers new opportunities for enhancement.This paper examined data from 16 cities in Yunnan Province from 2005 to 2019,applying the unexpected-SBM model and entropy weight method to evaluate tourism carbon emission efficiency and the level of digital economy development,along with spatial visualization analysis.Kernel density estimation revealed the spatial effects of tourism carbon emission efficiency.Dynamic QCA analysis explored the configuration effects of the digital economy on tourism carbon emission efficiency.The findings included that:①The tourism industry's carbon emission efficiency in Yunnan followed a"V"-shaped trend,initially declining and then increasing,while digital economy development exhibited a fluctuating upward trend.②Significant spatial differences existed between tourism carbon emission efficiency and digital economy development.Areas with high carbon emission efficiency had shifted from northwest to central Yunnan,whereas regions with advanced digital economy levels were mainly concentrated in central Yunnan.③The distribution of tourism carbon emission efficiency across states and cities remained relatively stable,with high-low clustering negatively correlated in southwestern and southern Yunnan.④Dynamic QCA analysis identified three configurations of the digital economy conducive to high tourism carbon emission efficiency,refined into digital-driven and digital-talent-driven models,though their influence varies across regions.
作者
王峰
和增辉
全山鑫
WANG Feng;HE Zenghui;QUAN Shanxin(Lancang-Mekong International Cooperation Research Institute,Yunnan Minzu University,Kunming 650500,China)
出处
《资源开发与市场》
2025年第8期1240-1251,共12页
Resource Development & Market
基金
国家社会科学基金项目(编号:20BMZ112)
云南省“兴滇英才支持计划”青年人才专项项目阶段成果。
关键词
数字经济
旅游业
碳排放效率
核密度估计
动态QCA
digital economy
tourism industry
carbon emission efficiency
Kernel density estimation
dynamic QCA
