长江经济带旅游业绿色生产率测算与时空演变分析
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摘要
旅游业绿色生产率是将能源消耗与环境代价纳入旅游业全要素生产率框架,表征旅游业绿色发展能力和水平,关系着区域旅游业可持续发展和生态文明建设。本文在借用"自下而上"法对长江经济带旅游业能源消耗与碳排放评估的基础上,采用基于方向性距离函数的非参数DEA法及ML指数对长江经济带11年间的旅游业绿色生产率进行测度与分解,并运用引力模型对该区域旅游业绿色生产率空间格局演变进行研究。结果表明:①长江经济带旅游业能源消耗与碳排放仍处于增长态势,区域内省份旅游经济与两者(能源消耗与碳排放)正向关联显著,且长江经济带旅游业发展与两者(能源消耗与碳排放)并未实现脱钩。②长江经济带旅游业绿色发展绩效有所提升,但因粗放型发展模式致使其绿色生产率增长迟缓,技术进步已成为该区域旅游业绿色生产率增长的主要源泉,而技术效率驱动作用薄弱。③长江经济带11省市旅游业绿色生产率可分为发展进步型、发展停滞型和发展衰退型,不同类型省份应基于技术进步和技术效率的此消彼长采取适当措施促进旅游业绿色生产率实现俱乐部趋同。④长江经济带旅游业绿色生产率势能值从下游到上游呈"L"型,长三角成为该区域核心增长极,长江中游实现中部隆起而长江上游出现塌陷状态,江西、安徽两省成为长三角和长江中游旅游业绿色生产率联系的重要枢纽,而长江上游旅游业绿色生产率尚未与长三角、长江中游形成相互联系的网络结构。
The green productivity of tourism integrates energy consumption and environmental cost into the measurement framework of tourism total factor productivity. Indicating the green development capacity and level of tourism,it is closely related to the green sustainable development of regional tourism and ecological civilization construction. Based on the ‘bottom-up'method,this paper estimates tourism energy consumption and carbon emissions in the Yangtze River Economic Belt( YREB). Then it measures and decomposes the tourism green productivity of the YREB in 11 years,adopting the non-parametric DEA method based on directional distance function and the ML index. Finally,this paper examines the spatial pattern evolution of tourism green productivity in this region by means of the gravity model. The results show that: ①The energy consumption and carbon emissions of tourism in the YREB are still increasing. The tourism economy of these provinces is significantly positively related with energy consumption and carbon emissions,and what is more,the tourism development in the YREB has not decoupled with them( energy consumption and carbon emissions). ② The green development performance of tourism industry in the YREB has improved,but the growth of its green productivity remains sluggish due to its extensive development mode. In the meantime,technological progress has become the main source of tourism green productivity growth in the region,while the driving effect of technological efficiency remains weak. ③The green productivity of tourism in 11 provinces and cities in the YREB can be divided into three types: progressive,stagnant and declining.Provinces of different types should take appropriate measures to promote tourism green productivity to achieve club convergence according to the variation of technological progress and technical efficiency. ④The potential energy value of tourism green productivity in the YREB presents an‘L'shape from downstream to upstream,the Yangtze River Delta being the core growth pole,with the middle reaches uplifted while the upper reaches collapsed. Jiangxi and Anhui provinces become important hubs to connect the green productivity of tourism in the Yangtze River Delta and the middle reaches,however,the green productivity in the upper reaches have not yet formed a network structure with these two areas.
The green productivity of tourism integrates energy consumption and environmental cost into the measurement framework of tourism total factor productivity. Indicating the green development capacity and level of tourism,it is closely related to the green sustainable development of regional tourism and ecological civilization construction. Based on the ‘bottom-up'method,this paper estimates tourism energy consumption and carbon emissions in the Yangtze River Economic Belt( YREB). Then it measures and decomposes the tourism green productivity of the YREB in 11 years,adopting the non-parametric DEA method based on directional distance function and the ML index. Finally,this paper examines the spatial pattern evolution of tourism green productivity in this region by means of the gravity model. The results show that: ①The energy consumption and carbon emissions of tourism in the YREB are still increasing. The tourism economy of these provinces is significantly positively related with energy consumption and carbon emissions,and what is more,the tourism development in the YREB has not decoupled with them( energy consumption and carbon emissions). ② The green development performance of tourism industry in the YREB has improved,but the growth of its green productivity remains sluggish due to its extensive development mode. In the meantime,technological progress has become the main source of tourism green productivity growth in the region,while the driving effect of technological efficiency remains weak. ③The green productivity of tourism in 11 provinces and cities in the YREB can be divided into three types: progressive,stagnant and declining.Provinces of different types should take appropriate measures to promote tourism green productivity to achieve club convergence according to the variation of technological progress and technical efficiency. ④The potential energy value of tourism green productivity in the YREB presents an‘L'shape from downstream to upstream,the Yangtze River Delta being the core growth pole,with the middle reaches uplifted while the upper reaches collapsed. Jiangxi and Anhui provinces become important hubs to connect the green productivity of tourism in the Yangtze River Delta and the middle reaches,however,the green productivity in the upper reaches have not yet formed a network structure with these two areas.
引文
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[4]王勇,李海英,俞海.中国省域绿色发展的空间格局及其演变特征[J].中国人口·资源与环境,2018,28(10):96-104.
[5]ALDOUS D E,ZHOU W Z,GROENING G,et al. Effects of green tourism on sustainable development[J]. Acta horticulturae,2013,999(23):171-178.
[6]HAILU A,VEEMAN T S. Non-parametric productivity analysis with undesirable outputs:an application to the Canadian pulp and paper industry[J]. American journal of agricultural economics,2001,85(4):1075-1077.
[7]GOLLOP F, SWINAND G. From total factor to total resource productivity:an application to agriculture[J]. American journal of agricultural economics,1998,80(3):577-583.
[8]REINHARD S,LOVELL C A K,THIJSSEN G J. Environmental efficiency with multiple environmentally detrimental variables:estimated with SFA and DEA[J]. European journal of operation research,2000,121(2):287-303.
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[10]FARE R,GROSSKOPF S,JR C A P. Environmental production functions and environmental directional distance functions[J].Energy,2007,32(7):1055-1066.
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[12]MORFDLDT J, SILVEIRA S. Capturing energy efficiency in European iron and steel production:comparing specific energy consumption and Malmquist productivity index[J]. Energy efficiency,2014,7(6):955-972.
[13]王许亮,王恕立.服务业能源生产率变迁及收敛性分析——基于全球40个经济体细分行业数据的经验研究[J].数量经济技术经济研究,2018,35(1):42-59.
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[15]刘战豫,孙夏令.中国物流业绿色全要素生产率的时空演化及动因分析[J].软科学,2018,32(4):77-81,114.
[16]吴英姿,闻岳春.中国工业绿色生产率、减排绩效与减排成本[J].科研管理,2013,34(2):105-111.
[17]LEE J W,BRAHMASRENE T. Investigating the influence of tourism on economic growth and carbon emissions:evidence from panel analysis of the European Union[J]. Tourism management,2013,38(13):69-76.
[18]FERNANDES E,PACHECO R. Efficiency use of airport capacity[J]. Transportation research part A,2006,36(2):225-238.
[19]KOKSAL C,AKSU A. An efficiency evaluation of a-group travel agencies with data envelopment analysis(DEA):a case study in the Antalya region,Turkey[J]. Tourism management,2007,28(3):830-834.
[20]ASHRAFI A,HSINVONN S,LAISOON L,et al. The efficiency of the hotel industry in Singapore[J]. Tourism management,2013,37(3):31-34.
[21]王永刚.中国旅游业全要素生产率增长的实证研究[J].经济问题探索,2012(3):135-139.
[22]吴琳萍.中国旅游业全要素生产率的估算[J].统计与决策,2017(9):135-139.
[23]龚艳,郭峥嵘.江苏旅游业发展效率及对策研究——基于超效率DEA和Malmquist指数分析[J].华东经济管理,2014,28(4):7-12,17.
[24]刘建国,刘宇. 2006—2013年杭州城市旅游全要素生产率格局及影响因素[J].经济地理,2015,35(7):190-197.
[25]刘佳,张俊飞.旅游产业绿色全要素生产率变动及收敛性分析——基于中国沿海地区的实证研究[J].资源开发与市场,2017,33(7):867-872.
[26]岳艺吾.基于CO2排放的中国旅游全要素生产率研究[D].长沙:湖南师范大学,2017:29-35.
[27]BECKEN S,SIMMONS D G. Undefstanding energy consumption patterns of tourist attractions and activities in New Zealand[J].Tourism management,2002,23(4):343-354.
[28]BECKEN S,PATTERSON M. Measuring national carbon dioxide emissions from tourism as a key step towards achieving sustainable tourism[J]. Journal of sustainable tourism,2006,14(4):323-338.
[29]汤姿.旅游业碳排放测算及其与经济增长的脱钩分析[J].统计与决策,2015(2):117-120.
[30]时朋飞,李星明.区域美丽中国建设与旅游业发展耦合关联性测度及前景预测——以长江经济带11省市为例[J].中国软科学,2018(2):86-102.
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[32]KELLY J,WILLIAMS P W. Modelling tourism destination energy consumption and greenhouse gas emissions:Whistler, British Columbia,Canada[J]. Journal of sustainable tourism,2007,15(1):67-90.
[33]袁宇杰.中国旅游间接能源消耗与碳排放的核算[J].旅游学刊,2013,28(10):81-88.
[34]BECKEN S, SIMMONS D G, FRAMPTON C. Energy use associated[J]. Tourism management,2003,24(3):267-277.
[35]HWITT O J A,REVOL V G N,SMITH I J,et al. Carbon emissions from international cruise ship passengers’travel to and from New Zealand[J]. Energy policy,2010,38(5):2552-2560.
[36]沈杨.宁波市旅游业碳排放估算及碳减排对策分析[J].环境保护,2016(18):66-68.
[37]陶玉国,黄震方,吴丽敏,等.江苏省区域旅游业碳排放测度及其因素分解[J].地理学报,2014,69(10):1438-1448.
[38]LIU J,FENG T T,YANG X. The energy requirements and carbon dioxide emissions of tourism industry of western China:a case of Chengdu City[J]. Renewable and sustainable energy reviews,2011,15(6):2887-2894.
[39]王凯,肖燕,李志苗,等.中国旅游业CO2排放因素分解:基于LMDI分解技术[J].旅游科学,2016,30(3):13-27.
[40]石培华,吴普.中国旅游业能源消耗与CO2排放量的初步估算[J].地理学报,2011,66(2):235-243.
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