School of Economics and Management, Yanshan University, Qinhuangdao 066004, China.
Int J Environ Res Public Health. 2021 Feb 8;18(4):1601. doi: 10.3390/ijerph18041601.
To discuss the coupling coordination relationship among tourism carbon emissions, economic development and regional innovation it is not only necessary to realize the green development of tourism economy, but also great significance for the tourism industry to take a low-carbon path. Taking the 30 provinces of China for example, this paper calculated the tourism carbon emission efficiency based on the super-efficiency Slacks based measure and Data envelope analyse (SBM-DEA) model from 2007 to 2017, and on this basis, defined a compound system that consists of tourism carbon emissions, tourism economic development and tourism regional innovation. Further, the coupling coordination degree model and dynamic degree model were used to explore its spatiotemporal evolution characteristics of balanced development, and this paper distinguished the core influencing factors by Geodetector model. The results showed that (1) during the study period, the tourism carbon emission efficiency showed a reciprocating trend of first rising and then falling, mainly due to the change of pure technical efficiency. (2) The coupling coordination degree developed towards a good trend, while there were significant differences among provinces, showing a gradient distribution pattern of decreasing from east to west. Additionally, (3) the core driving factors varied over time, however, in general, the influence from high to low were as follows: technological innovation, economic development, urbanization, environmental pollution control, and industrial structure. Finally, some policy recommendations were put forward to further promote the coupling coordination degree.
为了探讨旅游碳排放、经济发展和区域创新之间的耦合协调关系,不仅需要实现旅游经济的绿色发展,而且对于旅游业走低碳道路也具有重要意义。本文以中国 30 个省份为例,基于超效率 Slacks 基于测度和数据包络分析(SBM-DEA)模型,计算了 2007-2017 年的旅游碳排放效率,并在此基础上构建了一个由旅游碳排放、旅游经济发展和旅游区域创新构成的复合系统。进一步运用耦合协调度模型和动态度模型,探讨了其时空演变特征及其协调发展水平,利用地理探测器模型区分了核心影响因素。结果表明:(1)研究期间,旅游碳排放效率呈现先升后降的波动趋势,主要受纯技术效率变化的影响。(2)耦合协调度呈向好发展态势,但各省份之间存在显著差异,呈东向西递减的梯度分布格局。(3)核心驱动因素随时间变化而变化,但总体上,影响程度由高到低依次为:技术创新、经济发展、城市化、环境污染控制和产业结构。最后,提出了一些政策建议,以进一步促进耦合协调度的提升。