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中国科学院大学学报 ›› 2017, Vol. 34 ›› Issue (6): 701-711.DOI: 10.7523/j.issn.2095-6134.2017.06.007

• 环境科学与地理学 • 上一篇    下一篇

广东省城市旅游竞争力评价与发展对策

陈沛然1,2, 张落成1   

  1. 1. 中国科学院南京地理与湖泊研究所, 南京 210008;
    2. 中国科学院大学, 北京 100049
  • 收稿日期:2016-06-29 修回日期:2017-03-06 发布日期:2017-11-15
  • 通讯作者: 张落成
  • 基金资助:
    中国科学院南京地理与湖泊研究所"135"重点项目(NIGLAS2012135006)资助

Evaluation and strategy for urban tourism competitiveness of Guangdong Province

CHEN Peiran1,2, ZHANG Luocheng1   

  1. 1. Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2016-06-29 Revised:2017-03-06 Published:2017-11-15

摘要: 选取经济竞争优势、竞争潜力、基础支撑3个方面19个指标,采用基于熵权的灰色关联分析方法评价广东省各城市的旅游竞争力。结果表明广州和深圳旅游竞争力的综合评价系数远远高于其他城市;东莞、佛山、珠海、惠州等综合排序都处于前列,排序靠后的城市主要是位置较为偏远的揭阳、潮州、汕尾、阳江等。对城市规模与城市竞争力排序的关系进行研究。归纳广东省旅游竞争力的区域格局,即广东省的旅游业呈现出中心突出、四周下陷、环绕珠三角展开的核心-边缘结构。利用同样基于熵权的TOPSIS方法与原分析结果进行对比,确定分辨系数的可靠性和数据不稳定性的来源。最后从城市和区域2个尺度给出广东省提升旅游竞争力、发展区域旅游的建议和对策。

关键词: 旅游竞争力, 熵权, 关联系数, 区域旅游, 广东省

Abstract: In this work, 19 indicators selected in three aspects, including economic competitive advantage, competitive potential, and basic support, were used to evaluate the tourism competitiveness of cities in Guangdong Province. By using the method of grey relational analysis based on entropy weight, the tourism competitiveness of every city in Guangdong was evaluated, and the results show that the comprehensive evaluation indexes of tourism competitiveness in Guangzhou and Shenzhen are much higher than in the other cities. In the comprehensive ranking, the first part includes Dongguan, Foshan, Zhuhai, Huizhou, and so on, and the last part includes Jieyang, Chaozhou, Shanwei, Yangjiang, and so on. Furthermore a preliminary study on the relationship between urban size and urban tourism competitiveness was made. The regional pattern of tourism in Guangdong shows a core-edge structure surrounding the Pearl River Delta region. Our method was compared with TOPSIS method, and we analyzed the reliability of distinguishing coefficients and the origin of data volatility. In this work the advice and strategy were proposed for improving tourism competitiveness of Guangdong Province at urban scale and regional scale.

Key words: tourism competitiveness, entropy weight, correlation coefficient, regional tourism, Guangdong Province

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