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林业科学 ›› 2015, Vol. 51 ›› Issue (2): 137-146.doi: 10.11707/j.1001-7488.20150217

• 研究简报 • 上一篇    下一篇

我国森林公园旅游效率及其影响因素

黄秀娟, 林秀治   

  1. 福建农林大学管理学院 福州 350002
  • 收稿日期:2014-07-27 修回日期:2014-08-28 出版日期:2015-02-25 发布日期:2015-03-11

Tourism Efficiency and Influence Factors of Chinese Forest Parks

Huang Xiujuan, Lin Xiuzhi   

  1. College of Management, Fujian Agriculture and Forestry University Fuzhou 350002
  • Received:2014-07-27 Revised:2014-08-28 Online:2015-02-25 Published:2015-03-11

摘要: 【目的】以我国大陆31个省(区、市)森林公园为对象,研究其旅游效率,为我国森林公园旅游效率的提升提供参考。【方法】首先,基于DEA的效率测算方法,选择旅游收入和旅游人数为产出变量,森林公园面积、当年投入资金和职工人数为投入变量,利用数据包络分析工具DEAP2.0版本软件中投入导向的规模报酬不变的效率测算模型,以国家林业局官方网站公布的我国大陆各省森林公园数据为依据,测算各省森林公园2009—2013年各年不变规模下的旅游效率。然后,基于供给需求理论,选择森林公园所在省级区域的人口密度、城镇化率、人均GDP、高级别旅游资源密度、森林公园密度、高等级公路密度以及森林公园的森林覆盖率、资金投入强度、劳动力投入强度等为自变量,旅游效率为因变量,建立基于面板数据的多元线性回归模型,定量分析影响森林公园旅游效率的因素,其中回归分析模型中的自变量数据来自于中国统计年鉴,因变量数据来自于第一步的测算结果。【结果】 1) 我国森林公园旅游效率从2011年开始逐年提升,但各省区间森林公园的旅游效率存在较大差异,部分省区各年份森林公园的旅游效率存在较大波动。2) 利用Stata 12.0软件对回归分析模型依次进行个体效应检验、时间效应检验、Hausman检验及异方差稳健检验,得出模型存在个体效应和时间效应,且随机效应效果优于固定效应,最终确定采用双向随机效应模型(显著水平为5%)。3) 利用异方差稳健的GLS估计方法对所建立的随机效应模型进行参数估计,得出人口密度和林地森林覆盖率(5%的显著水平)、城镇化率(10%的显著水平)对森林公园的旅游效率有显著的正向影响; 人均GDP和资金投入强度对森林公园的旅游效率有显著的负向影响(5%的显著水平); 高级别旅游资源密度、森林公园密度、高等级公路密度对森林公园旅游效率产生不显著的正向影响(10%的显著水平); 劳动力投入强度对森林公园旅游效率产生不显著的负向影响。【结论】 2009—2013年,中国森林公园资源的旅游利用效率有显著的提升,但各省之间森林公园的效率存在较大的差异,部分省份森林公园效率的年度波动较大; 地区人口密度、城镇化比率、旅游资源水平、森林公园密度、交通发展水平对森林公园的效率起着正向的影响作用,而资金投入密度对森林公园的效率起着显著的负相影响,这一点与人们关于森林公园资本投资作用的认识相悖。本文提出了提升我国森林公园效率的一些建议,指出了需要进一步跟踪研究的问题。

关键词: 森林公园, 旅游效率, 影响因素, 数据包络分析, 面板数据回归模型

Abstract: 【Objective】 In this study, 31 provincial level unit's forest parks in Chinese mainland were taken as research objects, to study tourism efficiencies of forest parks of mainland China, and provide reference for efficiency promotion of Chinese forest parks. 【Method】 Firstly, based on the DEA computing technique, with tourism income and tourists number as output variables, and the forest parks area, the same year fund investment and staff population as input variables, the input-oriented constant scale model in DEAP2.0 edition software was used to survey the tourism efficiencies of various provinces forest parks of each year from 2009 to 2013. All data came from the Chinese National Forestry Bureau official website announcement. Secondly, based on the supply-demand theory, the population density, the urbanization rate, GDP per capita, the high rank tourism resources density, the forest park density, and the ClassⅠ-Ⅳ highway density of the province, as well as the Woodland forest coverage rate, the fund Investment intensity and the Labor intensity of the forest parks of the province were chosen as independent variables, and the tourism efficiency was the dependent variable, to establish panel-data multi-dimensional linear regression model, and quantitatively analyze factors of influencing forest park tourism efficiency. In this study, all independent variable data were obtained from the Chinese statistics yearbook, the dependent variable data came from the first step computing results. 【Result】 The results show that: 1) In the whole, the mainland forest park tourism efficiencies increase year by year since 2011, but the forest park tourism efficiencies exist big difference among various provincial capital areas. The forest park tourism efficiencies of some provinces undulate greatly during various years. 2) The stata12.0 software was used sequentially to carry on the individual effect examination, the time effect examination, the hausman examination and the different variance steady examination of the regression analysis model, showing that the model exists individual effect and the time effect, and the effect of the stochastic effects model is better than that of the fixed effect model, thus the bidirectional random effect model was chosen as the final regression model (5% significant level). 3) The robust GLS estimation shows that, the population density and Woodland forest coverage rate (5% significant level), the urbanization rate (10% significant level) have the significant positive influence to the forest park tourism efficiency; GDP per capita and the park investment intensity have the significant negative influence to the forest park tourism efficiency (5% significant level); The tourism resources, the forest park density, ClassⅠ-Ⅳ highway density have the positive but not significant influence to the forest park tourism efficiency (10% significant level); The labor intensity has negative but not significant influence to the forest park tourism efficiency. 【Conclusion】 Finally further studies problems are proposed: during 2009—2013, tourism utilization efficiency of Chinese forest parks had significant improved, but there existed large efficiency differences between some provinces, and the efficiency of forest parks in some provinces fluctuated greatly each year. Population density, urbanization rate, tourism resource level, forest park density, traffic development level have played positive roles on the efficiency of forest parks, and the investment density has played a significantly negative impact on the efficiency of forest parks, which is contrary to people's knowledge about the role of capital investment in forest parks. Paper finally gives some advices on how to promote the efficiency of Chinese forest parks, and points out some problems which need further follow-up research.

Key words: forest park, tourism efficiency, influence factor, data envelop analysis method, panel data regression model

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