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中国文化和旅游融合发展效率时空动态演化及其驱动机制

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提高文旅融合发展效率是关乎效率变革和质量变革背景下文化和旅游深度融合及高质量发展的重要科学问题,有效把握其动态演化特征及驱动机制对推动区域文化产业与旅游产业转型升级和提质增效及其深度融合高质量发展具有重要的理论价值和现实意义.文章构建文化和旅游融合发展效率分析框架,运用耦合协调模型、基于松弛变量的超效率测度模型、空间马尔科夫链和面板空间杜宾模型等方法,剖析中国2011-2019年文化和旅游融合发展效率的时空动态特征及其驱动机制.研究发现:1)中国文化和旅游融合发展效率在9年间仅提升3.4%,距离最佳生产前沿面还存在至少17.3%的潜力空间,4大区域呈东部>中部>西部>东北格局,并且仅天津、上海、广东与云南4个省份常年达到最佳生产前沿面,其他省份还存在至少6.7%~33.9%的潜力空间;2)中国文化和旅游融合发展效率大致呈现"东南沿海高值集聚,西北内陆低值集聚"空间格局,存在显著的路径依赖与马太效应现象,短期内难以实现跨越式增长,但当与高效率的省份为邻时,本地省份文化和旅游融合发展效率向上转移概率有所提升;3)产业结构与交通水平是提高本地省份文化和旅游融合发展效率的主要因素,但对邻近省份产生了负向溢出效应,科技创新、消费需求和政府调控促进了邻近省份文化与旅游融合发展效率,但对本地省份的推动作用尚不显著,服务队伍抑制了本地省份文化与旅游融合发展效率,但对邻近省份的溢出效应并不显著.
Spatiotemporal Dynamic Evolution of the Cultural Tourism Integration Development Efficiency and Its Driving Mechanism in China
Promoting the cultural tourism integration development efficiency is an important issue associated with both culture and tourism integration and its development in terms of changes in efficiency and quality.Thus,effectively grasping its dynamic evolution characteristics and driving mechanism is of great theoretical and practical significance in promoting the transformation and upgrading of the regional cultural industry and tourism industry,as well as improving quality and efficiency,and its deep integration and high-quality development.A framework for analyzing the cultural tourism integration development efficiency was constructed and various models,including the coupled coordination,super efficiency slacks-based measure,spatial Markov chain,and spatial panel Durbin models,were used to explore the spatiotemporal dynamic characteristics and driving factors of the efficiency of integration development of culture and tourism between 2011 and 2019 in China.We made the following findings.(1)The cultural tourism integration development efficiency increased by only 3.4%in 9 years in China,with at least 17.3%potential room for expansion to the best production frontier;the four major regions of the country were ranked as east>central>west>northeast,and only four provinces,Tianjin,Shanghai,Guangdong,and Yunnan,have consistently reached the best production frontier.Other provinces still had at least 6.7%to 33.9%potential space.(2)The cultural tourism integration development efficiency conformed roughly to the spatial pattern of"high-value agglomeration along the southeastern coastal regions and low-value agglomeration in the northwestern inland regions".There were significant instances of path dependence and the Matthew effect,indicating the difficulties associated with achieving great-leap-forward development within a short time.However,when adjacent to efficient provinces,the probability of the cultural tourism integration development efficiency in local provinces transferring upwards increases.(3)The industrial structure and traffic level were the main factors that promoted the cultural tourism integration development efficiency in local provinces,but had a negative spillover effect on the cultural tourism integration development efficiency in neighboring provinces.In addition,although technological innovation,consumer demand,and government regulation have boosted the cultural tourism integration development efficiency in neighboring provinces,the driving effect on local provinces was not yet significant;The service team has suppressed the efficiency of integration development of cultural and tourism in local provinces,but the spillover effect on neighboring provinces was not significant.This study sheds new insights into the research on the cultural tourism integration development efficiency in the context of quality change from the perspective of an efficiency perspective.Moreover,it helps to provide a reference and basis for the deep integration and high-quality development of culture and tourism in China.

cultural industrytourism industryintegration of culture and tourismefficiencyspatial Markov chainspatial panel Durbin model

王兆峰、谢佳亮

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湖南师范大学旅游学院,湖南长沙 410081

文化产业 旅游产业 文旅融合 效率 空间马尔科夫链 面板空间杜宾模型

国家自然科学基金面上项目&&

4177116241771162/41971188

2024

旅游学刊
北京联合大学旅游学院

旅游学刊

CSTPCDCSSCICHSSCD北大核心
影响因子:2.013
ISSN:1002-5006
年,卷(期):2024.39(1)
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