地理研究 ›› 2015, Vol. 34 ›› Issue (10): 1957-1970.doi: 10.11821/dlyj201510013

• 研究论文 • 上一篇    下一篇

基于碳排放的代表性省份旅游产业效率测算与比较分析

韩元军1(), 吴普1(), 林坦2   

  1. 1. 中国旅游研究院,北京 100005
    2. 交通运输部规划研究院,北京 100028
  • 收稿日期:2015-03-11 修回日期:2015-07-16 出版日期:2015-10-15 发布日期:2015-10-15
  • 作者简介:

    作者简介:韩元军(1981- ),男,山东潍坊人,助理研究员,研究方向为旅游政策与产业效率。E-mail: yjhan@cnta.gov.cn

  • 基金资助:
    国家社会科学基金青年项目(14CGL022);国家自然科学基金项目(41101044)

Regional tourism industry' efficiency measurement and comparative analysis based on carbon emissions

Yuanjun HAN1(), Pu WU1(), Tan LIN2   

  1. 1. China Tourism Academy, Beijing 100005, China
    2. Transport Planning and Research Institute of Ministry of Transport, Beijing 100028, China
  • Received:2015-03-11 Revised:2015-07-16 Online:2015-10-15 Published:2015-10-15

摘要:

借鉴“旅游消费剥离系数”概念对中国五省份旅游业碳排放量进行了测度,然后利用传统DEA模型和非期望产出DEA模型,结合碳排放指标,评价了五省份旅游产业效率,并进行了比较分析。研究发现:2009-2011年海南省旅游业碳排放总量始终最低,湖北增长幅度最大,而北京是唯一的总量逐年下降地区,2009-2011年海南旅游业人均碳排放量是最高的,北京、海南人均总量逐年下降;不考虑碳排放下,2009-2011年中国五省份综合效率及其分解效率总体水平较高,符合地区将旅游业作为支柱产业予以高度重视的实际;与不考虑碳排放相比,考虑碳排放的五省份旅游产业效率发生了不同程度的变动,特别是,旅游综合技术效率从2009年的下降或不变状态向2010-2011年的复杂不规律状态转变,这是由纯技术效率和规模效率联合效应决定的。未来各地区需要协调好旅游节能减排与资源优化配置工作,基于地方技术、市场势力适时提升旅游产业效率。

关键词: 旅游碳排放, 旅游消费剥离系数, 产业效率, 非期望产出DEA模型

Abstract:

This paper firstly calculates the carbon emissions of tourism industry of five provinces based on the concept of "tourist consuming minus coefficient". Then it evaluates the tourism industry efficiencies and conducts a comparative analysis with the traditional DEA model and the undesirable output DEA model. The results are shown as follows. The rank of Hainan's carbon emissions of the tourism industry is always the lowest. The growth rate of Hubei' carbon emissions is the largest, and Beijing is the only declining area from 2009 to 2011. For per capita carbon emissions, Hainan tourism industry ranks first while Beijing and Hainan show a declining trend year by year. The overall level of the comprehensive and decomposition efficiencies in five provinces is high without considering carbon emissions, and it is in line with the fact that regional tourism as a pillar industry is attached great importance. The tourism industry efficiencies in the five provinces change irregularly while carbon emissions are considered. Tourism comprehensive technical efficiencies change from the regular status of decline or steadiness in 2009 to the irregular status in 2010-2011, which are determined by the combined effects between pure technical efficiency and scale efficiency. In the future, China should strengthen coordination between tourism energy conservation and optimal allocation of tourism resources, and improve the tourism industry efficiencies according to the level of local technology and market power advantages.

Key words: tourism carbon emissions, tourist consuming minus coefficient, industry efficiency, the undesirable output DEA model