自然资源学报 ›› 2019, Vol. 34 ›› Issue (1): 205-220.doi: 10.31497/zrzyxb.20190117

• • 上一篇    

国外气候变化对旅游业影响的定量研究进展与启示

曾瑜皙1,2(), 钟林生1,2(), 刘汉初1,2, 虞虎1   

  1. 1. 中国科学院地理科学与资源研究所,北京 100101
    2. 中国科学院大学,北京 100049
  • 收稿日期:2018-06-01 修回日期:2018-10-09 出版日期:2019-01-20 发布日期:2019-01-20
  • 作者简介:

    作者简介:曾瑜皙(1990- ),女,湖南怀化人,博士研究生,研究方向为生态旅游与旅游地理。E-mail: zengyux007@sina.com

  • 基金资助:
    国家自然科学基金项目(41671527);国家重点研发计划课题(2017YFC0506401)

Implications of overseas quantitative studies of climate change impact on tourism for domestic research

Yu-xi ZENG1,2(), Lin-sheng ZHONG1,2(), Han-chu LIU1,2, Hu YU1   

  1. 1. Institute of Geographical Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2018-06-01 Revised:2018-10-09 Online:2019-01-20 Published:2019-01-20

摘要:

加强气候变化对旅游业影响的定量研究,有助于旅游业在气候变化背景下实现可持续发展。基于SCI/SSCI文献数据库,梳理分析国外气候变化对旅游业影响的定量研究进展。结果显示,30余年来国外主要采用指标方法、需求模型与选择分析方法开展相关研究。20世纪80年代末出现的指标方法是运用最早、最广泛的方法,主要用于旅游资源环境变化等研究,呈现由单项指标转向综合指标的应用趋势;20世纪90年代末兴起的需求模型主要用于天气状况对旅游需求的影响等研究,呈现由时间序列模型转向累计需求模型的应用趋势;21世纪兴起的选择分析主要用于气候变化背景下的行为意愿等研究,呈现由描述统计转向离散选择模型的应用趋势。这些给我国研究的启示是:在研究方法与研究领域上,重点加强累计需求模型在旅游流相关研究中的运用,加强离散选择模型在旅游市场结构相关研究中的运用,加强系统科学方法与大数据技术在相关研究中的运用;在研究对象上,丰富中国境内气候敏感型旅游活动的相关研究,加强“一带一路”沿线国家、地区及青藏高原的相关研究。

关键词: 气候变化, 旅游业, 影响, 定量研究, 国外

Abstract:

The quantitative study on the impact of climate change on tourism in China is relatively weak, so it is urgent to learn from foreign experience. Therefore, based on the SCI/SSCI literature database, this article reviews the related research progress abroad from 1986 to 2017. The study finds that for more than 30 years, quantitative research on the impact of climate change on tourism in foreign countries has mainly used index methods, tourism demand models and selection analysis methods. Among them, the index method includes the single index method and the comprehensive index method. The tourism demand model includes the time series model and the cumulative demand model. The selection analysis includes the descriptive statistics and the discrete selection model. The indicator method is mainly used to study the environmental effects of tourism resources and environmental changes, changes in tourism climate conditions, changes in comprehensive factors, and the climate change response behavior of the main body of tourism. Due to the existence of offsetting effects of climate change, the comprehensive index method is more advantageous than the single index method. Although the comprehensive index method has difficulties such as computational complexity, it can comprehensively examine the impact of climate change on the comprehensive factors of tourism destinations, and is an important direction of development of indicators and methods. The indicator approach focuses on the changes in tourism destinations, and climate change responses need to understand the changes in tourism demand. Therefore, the use of tourism demand model has gradually increased. Among them, the time series method is mainly used to study the impact of weather conditions on tourism demand. The cumulative demand model is mainly used to study the structural impact of climate change on tourism demand and the impact of climate policy on tourism demand. With the development of computer technology and artificial intelligence, there is a great potential for future applications. The tourism demand model focuses on changes in the macro-tourism flow and ignores the heterogeneity of the tourism market. With the diversification and diversity of the tourism market becoming more apparent, the use of micro-individual-based selection analysis methods has increased. In related studies of selective analysis, descriptive statistics are often used to study the effects of climate change based on preference, behavioral willingness and climate change perception in the context of climate change. Discrete choice models are often used to study the influence of climate change based on preference and help to analyze the changes in the market structure of tourist destinations in the context of climate change. As more and more studies show that the impact of climate change on the tourism market is more reflected in the change in market structure, the application demand for discrete selection models has further increased. However, the basic theoretical assumptions of the discrete selection model still need to be studied in the correction of tourism scenarios. Combining the latest progress in the quantitative research on the impact of climate change on tourism in foreign countries, and linking with China's reality, future research needs to strengthen the application of cumulative demand models in tourism flow related research, the application of discrete selection models in tourism market structure research, and the use of systematic scientific methods and big data technologies in related research. In the future, we should enhance research on climate-sensitive tourism activities in China, and as relevant studies on "Belt and Road" countries and regions, as well as the Tibetan Plateau.

Key words: climate change, tourism, impacts, quantitative studies, overseas