|Table of Contents|

Research on the Coupling Coordinated Development and Dynamic Evolution of Scientific and Technological Innovation and Carbon Emission Efficiency of Tourism Industry(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2023年03期
Page:
50-59
Research Field:
地理学
Publishing date:

Info

Title:
Research on the Coupling Coordinated Development and Dynamic Evolution of Scientific and Technological Innovation and Carbon Emission Efficiency of Tourism Industry
Author(s):
He Jing1; Wang Kai2; Li Zhiyuan1; Zou Nan2
(1.School of Business Administration,East China Normal University,Shanghai 200062,China)
(2.College of Tourism,Hunan Normal University,Changsha 410081,China)
Keywords:
scientific and technological innovation;  carbon emission efficiency of tourism industry;  spatio-temporal coupling;  spatial Markov chain
PACS:
F592.7
DOI:
10.3969/j.issn.1001-4616.2023.03.008
Abstract:
The synergy between scientific and technological innovation and carbon emission efficiency of tourism industry is an important path to drive the high-quality development of tourism industry. Taking 30 provinces in China as the research objects,this paper constructs a coupling coordination model from system thinking to study the spatio-temporal evolution characteristics of the coupling coordinated development of scientific and technological innovation and carbon emission efficiency of tourism industry from 2001 to 2019,and then deeply analyzes the dynamic evolution trend with the help of spatial autocorrelation and spatial Markov chain. The results show that:(1)The coupling coordination degree between scientific and technological innovation and carbon emission efficiency of tourism industry has gradually changed from“basic imbalance”to“basic coordination”,showing a spatial distribution pattern of Eastern Area>Central Area>Northeastern Area>Western Area. The right tailing extension and convergence phenomenon of the kernel density curve is obvious and presents a bimodal evolution pattern. The discrete development and low-level state are gradually improved,and the absolute difference between regions is reduced.(2)The coupling coordination degree between scientific and technological innovation and carbon emission efficiency of tourism industry has significant positive spatial autocorrelation characteristics,and H-H type and L-L type are the main local spatial correlation types.(3)The type state is in a steady-state distribution and there is a phenomenon of “club convergence”,which is difficult to achieve leapfrog improvement. In addition,the type transfer process is affected by the geographical background. The severely maladjusted provinces face low-level solidification risk,while the high-level coordinated provinces lack the driving effect,and the basic maladjusted provinces and the basic coordinated provinces are easily affected by the nearest neighbor effect of the severely maladjusted provinces and the basic maladjusted provinces and their development falls back.

References:

[1]LENZEN M,SUN Y Y,FATURAY F,et al. The carbon footprint of global tourism[J]. Nature climate change,2018,8(6):522-528.
[2]SIMPSON M C,GÖSSLING S,SCOTT D,et al. Climate change adaptation and mitigation in the tourism sector:frameworks,tools and practices[R]. Oxford:University of Oxford,2008.
[3]杨莉莎,朱俊鹏,贾智杰. 中国碳减排实现的影响因素和当前挑战:基于技术进步的视角[J]. 经济研究,2019,54(11):118-132.
[4]卢娜,王为东,王淼,等. 突破性低碳技术创新与碳排放:直接影响与空间溢出[J]. 中国人口·资源与环境,2019,29(5):30-39.
[5]KHAN S A R,PONCE P,YU Z. Technological innovation and environmental taxes toward a carbon-free economy:an empirical study in the context of COP-21[J]. Journal of environmental management,2021,298:113418.
[6]D'AMORE F,ROMANO M C,BEZZO F. Carbon capture and storage from energy and industrial emission sources:a Europe-wide supply chain optimization[J]. Journal of cleaner production,2021,290:125202.
[7]黄凌云,谢会强,刘冬冬. 技术进步路径选择与中国制造业出口隐含碳排放强度[J]. 中国人口·资源与环境,2017,27(10):94-102.
[8]ERDOGAN S. Dynamic nexus between technological innovation and building sector carbon emissions in the BRICS countries[J]. Journal of environmental management,2021,293:112780.
[9]KHAN A,YANG C G,HUSSAIN J,et al. Impact of technological innovation,financial development and foreign direct investment on renewable energy,non-renewable energy and the environment in belt & road initiative countries[J]. Renewable energy,2021,171:479-491.
[10]JIAO Z L,SHARMA R,KAUTISH P,et al. Unveiling the asymmetric impact of exports,oil prices,technological innovations,and income inequality on carbon emissions in India[J]. Resources policy,2021,74:102408.
[11]KHATTAK S I,AHMAD M,KHAN Z U,et al. Exploring the impact of innovation,renewable energy consumption,and income on CO2 emissions:new evidence from the BRICS economies[J]. Environmental science and pollution research,2020,27(12):13866-13881.
[12]BRÄNNLUND R,GHALWASH T,NORDSTRÖM J. Increased energy efficiency and the rebound effect:effects on consumption and emissions[J]. Energy economics,2007,29(1):1-17.
[13]王坤,黄震方,曹芳东. 中国旅游业碳排放效率的空间格局及其影响因素[J]. 生态学报,2015,35(21):7150-7160.
[14]SUN Y Y. Decomposition of tourism greenhouse gas emissions:revealing the dynamics between tourism economic growth,technological efficiency,and carbon emissions[J]. Tourism management,2016,55:326-336.
[15]ZHA J P,HE L M,LIU Y,et al. Evaluation on development efficiency of low-carbon tourism economy:a case study of Hubei Province,China[J]. Socio-economic planning sciences,2019,66:47-57.
[16]王凯,刘依飞,甘畅. 旅游产业集聚对旅游业碳排放效率的空间溢出效应[J]. 生态学报,2022,42(10):3909-3918.
[17]ERDOAGˇU1AN S,GEDIKLI A,CEVIK E I,et al. Eco-friendly technologies,international tourism and carbon emissions:evidence from the most visited countries[J]. Technological forecasting and social change,2022,180:121705.
[18]王凯,夏莉惠,陈勤昌,等. 基于空间聚类分析的中国旅游业碳排放效率[J]. 环境科学研究,2018,31(3):419-427.
[19]邵海琴,王兆峰. 长江经济带旅游业碳排放效率的综合测度与时空分异[J]. 长江流域资源与环境,2020,29(8):1685-1693.
[20]金准. 碳达峰、碳中和与旅游业高质量转型[J]. 旅游学刊,2021,36(9):3-5.
[21]刘俊,王胜宏,余云云. 科技创新:生态旅游发展关键问题的思考[J]. 旅游学刊,2021,36(9):5-7.
[22]宋子千. 科技引领“十四五”旅游业高质量发展[J]. 旅游学刊,2020,35(6):10-12.
[23]韩永楠,葛鹏飞,周伯乐. 中国市域技术创新与绿色发展耦合协调演变分异[J]. 经济地理,2021,41(6):12-19.
[24]马玉林,马运鹏. 中国科技资源配置效率的区域差异及收敛性研究[J]. 数量经济技术经济研究,2021,38(8):83-103.
[25]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.
[26]翁钢民,唐亦博,潘越,等. 京津冀旅游—生态—城镇化耦合协调的时空演进与空间差异[J]. 经济地理,2021,41(12):196-204.
[27]聂长飞,简新华. 中国高质量发展的测度及省际现状的分析比较[J]. 数量经济技术经济研究,2020,37(2):26-47.
[28]高鹏,何丹,宁越敏,等. 长三角地区城市投资联系水平的时空动态及影响因素[J]. 地理研究,2021,40(10):2760-2779.

Memo

Memo:
-
Last Update: 2023-09-15