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| 旅游资源非优区的园区化建设探讨——以吕梁山苍儿会旅游经济园区为例 | |
| 引用本文： | 李跃军,孙虎,胡默言.旅游资源非优区的园区化建设探讨——以吕梁山苍儿会旅游经济园区为例[J].地域研究与开发,2007,26(3):71-74. |
| 作者姓名： | 李跃军 孙虎 胡默言 |
| 作者单位： | 1. 陕西师范大学,旅游与环境学院,西安,710062;台州学院,浙江,临海,317000 2. 陕西师范大学,旅游与环境学院,西安,710062 3. 河南省科学院,地理研究所,郑州,450052 |
| 摘 要： | 旅游资源非优区主要是在资源质量及其开发条件等方面表现出"非优性"的特征.在区域发展中如果仍然沿用传统的旅游资源开发思路和方法,必然使区域旅游业处于市场竞争中的劣势.因此,对于该类型区域有必要探索出新的经济发展思路.从区域比较优势角度,旅游资源非优区的发展应以资源禀赋特征为基础,以旅游经济园区发展为主体,走产业多样化的道路.以吕梁山苍儿会生态旅游经济区为例,提出加快园区化建设的步伐,促进旅游经济与区域产业经济的良性互动,是避免片面强调旅游经济而抑制其它产业发展,以及促进区域可持续发展的根本战略选择. |
| 关 键 词： | 旅游资源非优区 园区化建设 苍儿会旅游经济园区 吕梁山区 |
| 文章编号： | 1003-2363（2007）03-0071-04 |
| 修稿时间： | 2006-12-152007-02-25 |
Research on Regionalization Construction in Non-optimal Tourism Areas——A Case Study of Cangerhui Tourism Economic Zone in Luliang Mountain |
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| LI Yue-jun,SUN Hu,HU Mo-yan.Research on Regionalization Construction in Non-optimal Tourism Areas——A Case Study of Cangerhui Tourism Economic Zone in Luliang Mountain[J].Areal Research and Development,2007,26(3):71-74. | |
| Authors: | LI Yue-jun SUN Hu HU Mo-yan |
| Abstract: | Non-optimal tourism areas show that the obvious characteristic is "being not excellent" in the respect of tourism resources and its exploitation condition etc.Indeed,it is in inferior positions for non-optimal tourism areas in the regional development under market competition.So non-optimal tourism areas must be tried to probe into the new way to develop regional economy according to its resources condition.The authors put out that the pattern of regionalization construction is the best way to develop economy in non-optimal tourism areas,and non-optimal tourism areas should take a way of multiple economy and promote the relationship between the tourism industry and regional economic development.Finally,the developing strategies of eco-tourism economic zone were analysed based on case study of Chongerhui tourism economic zone in Luliang Mountain. |
| Keywords: | non-optimal tourism areas regionalization construction Chongerhui tourism economic zone Luliang Mountain |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |