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低碳视角下乡村旅游决策行为实证研究——基于北京市300位游客的调查数据
引用本文:罗红,陈晓,何忠伟. 低碳视角下乡村旅游决策行为实证研究——基于北京市300位游客的调查数据[J]. 中国农学通报, 2014, 30(34): 294-302. DOI: 10.11924/j.issn.1000-6850.2014-1617
作者姓名:罗红  陈晓  何忠伟
作者单位:(北京农学院经管学院,北京 102206)
基金项目:基金项目:2013年北京社科基金项目“低碳经济背景下北京乡村旅游转型升级研究”(13JGB118);北京农学院优势科技团队项目“北京农业产业安全理论与政策研究”(5095237001/028)。
摘    要:全球低碳经济背景下,乡村旅游低碳化发展是必然趋势。而旅游者决策行为直接决定其出行的选择,因而对乡村旅游者低碳旅游决策行为的研究,将对乡村旅游接待地和旅游企业的经营发展提供重要的参考依据。笔者以推拉模型为基础,将游客低碳乡村旅游决策行为影响因素归为推和拉2类,依据对北京市300位游客的调查,构建二元Logistic模型对其影响因素进行实证分析。实证结果表明:除了游客学历、收入等客观因素外,还受到游客的出游经验、所持低碳乡村旅游态度、低碳乡村旅游感知价值、乡村旅游目的地特色等方面的显著影响,并提出了低碳经济背景下推动乡村旅游转型升级的相关政策建议。

关 键 词:组织培养  组织培养  
收稿时间:2014-06-07
修稿时间:2014-12-04

Empirical Study on Rural-tourism Decision-making Behavior in the Perspective of Low-carbon:Based on the Survey of 300 Tourists in Beijing
Affiliation:(College of Economics and Management, Beijing University of Agricultural, Beijing 102206)
Abstract:Under the background of global low-carbon economy, rural-tourism developing with low-carbon is an inevitable trend. As tourists’travelling choices are determined by their decision-making behavior, the study of tourists’decision-making behaviors of low-carbon tourism would provide important reference for rural-tourism development. The push-pull model was constructed to classify the factors that affected low- carbon rural-tourism in this paper. And using binary logistic model, the influencing factors were analyzed, based on the research data of tourists from 10 suburban counties of Beijing. Empirical results showed that, in addition to individual objective factors such as education and income, significant factors of tourists’low- carbon rural-tourism decision-making included travel experiences, attitude toward low-carbon rural-tourism, perceived value of low-carbon rural-tourism and destination features of rural-tourism. Further, suggestions were put forward to promote the transformation and upgrading of rural-tourism under the background of low-carbon economy.
Keywords:low-carbon tourism   rural-tourism tourists   decision-making behavior   factors   binary Logistic model
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