碳排放影响下中国省域旅游效率损失度研究

旅游效率损失度反映了碳排放对旅游效率的影响程度。采用超越对数生产函数测算2001—2014年中国30个省(区、市)的旅游效率及损失度,并运用面板回归模型分析效率损失的驱动力。结果表明:(1)碳排放对中国各省(区、市),尤其是中部省份的旅游效率造成了损失。研究期内,中国总体旅游效率损失度呈现上升趋势,东部地区年均增幅最大;(2)中国旅游效率与损失度总体上处于中等水平,但损失度年均增长率远高于旅游效率增长率,中部地区因为排放问题造成了较大的效率损失;(3)根据不同省域旅游效率及其损失度,可划分为"高效低损、高效高损、低效低损、低效高损"4种类型区;(4)基础设施、旅游接待能力、旅游吸引力、旅游产业规模、旅游产业结构、能源技术对不同类型区的影响存在差异,应根据外力驱动大小和作用方向调整旅游效率优化策略。

Evaluation of the tourism efficiency loss due to the influence of carbon emissions from tourism in China

Tourism efficiency (TE) has received increasing attention in research and policy development. Considering that CO₂-emission is one of the important factors influencing TE at both, international and regional levels, the need to understand its impact on TE is not only a managerial challenge, but also an issue of vital importance. This paper proposes a conceptual framework of tourism efficiency-loss (TEL), and calculates the TE and TEL of 30 Chinese provinces during 2001-2014 by utilizing the transcendental logarithmic production function, followed by the analysis of TEL variables using the panel regression model. Our results show that:(1) TEL can serve as an indicator of the impact of carbon emissions on TE. (2) For the entire study period, the CO₂-emission has resulted in a high TEL value for all provinces, especially in central China. At the provincial level, most of the eastern provinces (e.g., Tianjing, Shandong, Zhejiang, Jiangsu, etc.), small parts of the central provinces (e.g., Henan), and parts of the western provinces (e.g., Qinghai and Inner Mongolia) showed a lower TEL value, while most of the central and western provinces, such as Shanxi, Hunan, Hubei, Gansu, etc., showed a relatively high TEL value.(3) An average increase was observed in the growth rates of both TE and TEL; however, the annual growth rate of TEL was relatively higher than that of TE. The general TEL levels have been experiencing a rising trend over the past 15 years in China, and the eastern region became the fastest region, followed by the western and northeast region. On the contrary, the central provinces experienced a decrease in the rate of TEL. (4) According to their TE and TEL values, the Chinese provinces can be categorized into four types:high-TE and low-TEL, high-TE and high-TEL, low-TE and high-TEL, and low-TE and low-TEL. The "high-TE and low-TEL" regions included Tianjing, Shanghai, Jiangsu, Zhejiang,Shandong,Guangdong, Henan, and Jilin, mostly in eastern China; the "high-TE and high-TEL" regions included Beijing, Hebei, Fujian, Shanxi, Anhui, Hubei, Hunan, Liaoning, and Chongqing, mostly in central China; the "low-TE and high-TEL" regions included Heilongjiang, Inner Mongolia, Sichuan, Yunnan, Shanxi, and Qinghai, mostly in northeast and northwest China; and the "low-TE and low-TEL" regions included Hainan, Jiangxi, Guangzhou, Gansu, Ningxia, and Xinjiang, mostly in central-western China. (5) The impacts of the infrastructure, reception capacity, attraction, industrial scale, industrial structure, and energy technology varied according to the type of region, making the selection of optimization measures different in each region. The "high-TE and low-TEL" regions should further improve the energy technology and optimize the structure of tourism industry. The "high-TE and high-TEL" regions should use energy-saving technology, reduce emissions from tourism transport, and speed up the transformation of the mode of traditional tourism development pattern to a more connotative and intensive growth pattern. The "low-TE and high-TEL" regions should focus on raising tourism scenic marginal benefit, optimizing the tourism industrial structure and improving the level of energy conservation and intensive utilization of resources and tourism management. The "low-TE and low-TEL" regions should adjust the structure of the tourism industry, pay attention to the protection of tourism resources and environment, and reduce the negative impact of transportation on the environment.