国外气候变化对旅游业影响的定量研究进展与启示
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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。
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.
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.
引文
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[23] BROUDER P, LUNDMARK L. Climate change in Northern Sweden:Intra-regional perceptions of vulnerability among winter-oriented tourism businesses. Journal of Sustainable Tourism, 2011, 19(8):919-933.
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[33] MCEVOY D, CAVAN G, HANDLEY J, et al. Changes to climate and visitor behaviour:Implications for vulnerable landscapes in the northwest region of England. Journal of Sustainable Tourism, 2008, 16(1):101-121.
[34] RIXEN C, TEICH M, LARDELLI C, et al. Winter tourism and climate change in the Alps:An assessment of resource consumption, snow reliability, and future snowmaking potential. Mountain Research and Development, 2011, 31(3):229-236.
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[36] TSAI H T, TSENG C J, TZENG S Y, et al. The impacts of natural hazards on Taiwan's tourism industry. Natural Hazards, 2012, 62(1):83-91.
[37] RICHARDSON R B, LOOMIS J B. Adaptive recreation planning and climate change:A contingent visitation approach.Ecological Economics, 2004, 50(1):83-99.
[38] CROUCH G I. The study of international tourism demand:A survey of practice. Journal of Travel research, 1994, 32(4):41-55.
[39] TAYLOR T, ORTIZ R A. Impacts of climate change on domestic tourism in the UK:A panel data estimation. Tourism Economics, 2009, 15(4):803-812.
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[41] KULENDRAN N, DWYER L. Modeling seasonal variation in tourism flows with climate variables. Tourism Analysis,2012, 17(2):121-137.
[42] OTERO-GIRáLDEZ M S,áLVAREZ-DíAZ M, GONZáLEZ-GóMEZ M. Estimating the long-run effects of socioeconomic and meteorological factors on the domestic tourism demand for Galicia(Spain). Tourism Management, 2012, 33(6):1301-1308.
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[2]丁一汇,任国玉,石广玉,等.气候变化国家评估报告(Ⅰ):中国气候变化的历史和未来趋势.气候变化研究进展,2006, 2(1):3-8.[DING Y H, REN G Y, SHI G Y, et al. National assessment report of climate change(Ⅰ):Climate change in China and its future trend. Advances in Climate Change Research, 2006, 2(1):3-8.]
[3]《第二次气候变化国家评估报告》编写委员会.气候变化国家评估报告.北京:科学出版社, 2007.[The Committees of The Second National Assessment Report of Climate Change. National Assessment Report of Climate Change. Beijing:Science Press, 2007.]
[4] WTM(World Travel Market). Why the ministers'summit 2007 is crucial to the industry. The UNWTO Ministers Summit on Tourism and Climate Change, 2007.
[5] DUBOIS G, CERON J P. Tourism and climate change:Proposals for a research agenda. Journal of Sustainable Tourism,2006, 14(4):399-415.
[6] ROSSELLó-NADALJ.Howtoevaluatetheeffectsofclimatechangeontourism.TourismManagement,2014,42:334-340.
[7]侯国林,黄震方,台运红,等.旅游与气候变化研究进展.生态学报, 2015, 35(9):2837-2847.[HOU G L, HUANG Z F,TAI Y H, et al. Progress and implications in tourism and climate change research. Acta Ecologica Sinica, 2015, 35(9):2837-2847.]
[8]孙根年,马丽君.西安旅游气候舒适度与客流量年内变化相关性分析.旅游学刊, 2007, 22(7):34-39.[SUN G N, MA L J. An analysis of tourist climate comfortable degree and yearly variation of tourist traffic in Xi'an. Tourism Tribune,2007, 22(7):34-39.]
[9]席建超,赵美风,葛全胜.全球气候变化对中国南方五省区域旅游流的可能影响评估.旅游学刊, 2011, 26(11):78-83.[XI J C, ZHAO M F, GE Q S. An assessment of the possible impact of global climate changes on regional tourist flows in five provinces of southern China. Tourism Tribune, 2011, 26(1):78-83.]
[10]邢彩盈,张京红,刘少军,等.基于气候指标评估气候变化对海南旅游的影响.自然资源学报, 2015, 30(5):846-857.[XING C Y, ZHANG J H, LIU S J, et al. Assessing the impact of climate change on Hainan tourism based on a climateresolving index. Journal of Natural Resources, 2015, 30(5):846-857.]
[11] WALL G, HARRISON R, KINNAIRD V, et al. The implications of climatic change for camping in Ontario. Recreation Research Review, 1986, 13(1):50-60.
[12] SCOTT D, HALL C M, G?SSLING S. A review of the IPCC Fifth Assessment and implications for tourism sector climate resilience and decarbonization. Journal of Sustainable Tourism, 2016, 24(1):8-30.
[13] KOENIG U, ABEGG B. Impacts of climate change on winter tourism in the Swiss Alps. Journal of Sustainable Tourism, 1997, 5(1):46-58.
[14] SPARKS T H. Local-scale adaptation to climate change:The village flower festival. Climate Research, 2014, 60(1):87-89.
[15] AMELUNG B, VINER D. Mediterranean tourism:Exploring the future with the tourism climatic index. Journal of Sustainable Tourism, 2006, 14(4):349-366.
[16] HYMAN T A. Assessing the vulnerability of beach tourism and non-beach tourism to climate change:A case study from Jamaica. Journal of Sustainable Tourism, 2014, 22(8):1197-1215.
[17] COOMBES E G, JONES A P. Assessing the impact of climate change on visitor behaviour and habitat use at the coast:A UK case study. Global Environmental Change, 2010, 20(2):303-313.
[18] WOOSNAM K M, KIM H. Hurricane impacts on southeastern United States coastal national park visitation. Tourism Geographies, 2014, 16(3):364-381.
[19] HAMILTON J M, MADDISON D J, TOL R S J. Effects of climate change on international tourism. Climate Research,2005, 29(3):245-254.
[20] TOL R S J. The impact of a carbon tax on international tourism. Transportation Research Part D:Transport and Environment, 2007, 12(2):129-142.
[21] BUJOSA A, RIERA A, TORRES C M. Valuing tourism demand attributes to guide climate change adaptation measures efficiently:The case of the Spanish domestic travel market. Tourism Management, 2015, 47:233-239.
[22] SCOTT D, JONES B, KONOPEK J. Implications of climate and environmental change for nature-based tourism in the Canadian Rocky Mountains:A case study of Waterton Lakes National Park. Tourism Management, 2007, 28(2):570-579.
[23] BROUDER P, LUNDMARK L. Climate change in Northern Sweden:Intra-regional perceptions of vulnerability among winter-oriented tourism businesses. Journal of Sustainable Tourism, 2011, 19(8):919-933.
[24] WHETTON P H, HAYLOCK M R, GALLOWAY R. Climate change and snow-cover duration in the Australian Alps.Climatic Change, 1996, 32(4):447-479.
[25] SCOTT D, MCBOYLE G, SCHWARTZENTRUBER M. Climate change and the distribution of climatic resources for tourism in North America. Climate Research, 2004, 27(2):105-117.
[26] ENDLER C, OEHLER K, MATZARAKIS A. Vertical gradient of climate change and climate tourism conditions in the Black Forest. International Journal of Biometeorology, 2010, 54(1):45-61.
[27] ABEGG B, ELSASSER H. Klima, wetter und tourismus in denSchweizer Alpen. Geographische Rundschau, 1996, 48(12):737-742.
[28] SCOTT D, MCBOYLE G, MILLS B. Climate change and the skiing industry in southern Ontario(Canada):Exploring the importance of snowmaking as a technical adaptation. Climate Research, 2003, 23(2):171-181.
[29] G?SSLING S, SCOTT D, HALL C M, et al. Consumer behaviour and demand response of tourists to climate change.Annals of Tourism Research, 2012, 39(1):36-58.
[30] YU G M, SCHWARTZ Z, WALSH J E. Effects of climate change on the seasonality of weather for tourism in Alaska.Arctic, 2009, 62(4):443-457.
[31] DE FREITAS C R. Tourism climatology:Evaluating environmental information for decision making and business planning in the recreation and tourism sector. International Journal of Biometeorology, 2003, 48(1):45-54.
[32] DE FREITAS C R, SCOTT D, MCBOYLE G. A second generation climate index for tourism(CIT):Specification and verification. International Journal of Biometeorology, 2008, 52(5):399-407.
[33] MCEVOY D, CAVAN G, HANDLEY J, et al. Changes to climate and visitor behaviour:Implications for vulnerable landscapes in the northwest region of England. Journal of Sustainable Tourism, 2008, 16(1):101-121.
[34] RIXEN C, TEICH M, LARDELLI C, et al. Winter tourism and climate change in the Alps:An assessment of resource consumption, snow reliability, and future snowmaking potential. Mountain Research and Development, 2011, 31(3):229-236.
[35] CSETE M, PáLV?LGYI T, SZENDR?G. Assessment of climate change vulnerability of tourism in Hungary. Regional Environmental Change, 2013, 13(5):1043-1057.
[36] TSAI H T, TSENG C J, TZENG S Y, et al. The impacts of natural hazards on Taiwan's tourism industry. Natural Hazards, 2012, 62(1):83-91.
[37] RICHARDSON R B, LOOMIS J B. Adaptive recreation planning and climate change:A contingent visitation approach.Ecological Economics, 2004, 50(1):83-99.
[38] CROUCH G I. The study of international tourism demand:A survey of practice. Journal of Travel research, 1994, 32(4):41-55.
[39] TAYLOR T, ORTIZ R A. Impacts of climate change on domestic tourism in the UK:A panel data estimation. Tourism Economics, 2009, 15(4):803-812.
[40] FALK M, HAGSTEN E. Importance of early snowfall for Swedish ski resorts:Evidence based on monthly data. Tourism Management, 2016, 53:61-73.
[41] KULENDRAN N, DWYER L. Modeling seasonal variation in tourism flows with climate variables. Tourism Analysis,2012, 17(2):121-137.
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