旅游供应链视角下的旅游需求预测
发布时间：2019-01-01 09:25
【摘要】：旅游产业作为第三产业的重头产业，对经济起到了重要促进作用。需求预测是旅游业管理运行工作的开始，所以旅游需求预测精度对旅游企业具有十分重要的意义。同时，旅游业是由旅游目的地的兴起而发展起来。每一个旅游目的地都有独特的旅游资源和特征，这就决定了游客因目的地的不同而有着不同的旅游需求。而对于目的地旅游产业的参与者，精确的旅游需求预测结果能够指导产品开发和运营计划等生产运营活动。 由于旅游业涉及企业众多，所以必须系统地分析旅游行业和旅游目的地的自身特点，找出影响因素，才能够建立有效的需求预测模型。本文在传统旅游需求预测的基础上，引进了旅游供应链概念。从供应链视角出发，梳理了旅游供应链的运行流程，挖掘旅游供应链上成员对旅游需求的影响，找寻旅游供应链的影响因素，从而建立旅游目的地需求预测模型。 本文提出一种基于旅游供应链的目的地旅游需求预测模型。首先，，提出假设的旅游供应链影响因素。然后，使用灰色关联分析验证假设因素是否确实与目的地旅游需求存在相关性。最后，将灰色关联分析筛选出的因素建立预测模型。并用此建模方法构建美国-香港的入境旅游人数预测模型，以验证方法的可行性和有效性。
[Abstract]:Tourism industry, as the important industry of the tertiary industry, has played an important role in promoting the economy. Demand forecasting is the beginning of tourism management, so the precision of tourism demand prediction is of great significance to tourism enterprises. At the same time, tourism is developed by the rise of tourist destinations. Each tourist destination has its unique tourism resources and characteristics, which determines that tourists have different tourism needs because of their different destinations. For the participants in the destination tourism industry, the accurate forecast results of tourism demand can guide the production and operation activities such as product development and business plan. Since there are many enterprises involved in tourism, we must systematically analyze the characteristics of tourism industry and tourism destination and find out the influencing factors in order to establish an effective demand forecasting model. Based on the traditional tourism demand forecasting, this paper introduces the concept of tourism supply chain. From the perspective of supply chain, this paper combs the running process of tourism supply chain, excavates the influence of tourism supply chain members on tourism demand, finds out the influencing factors of tourism supply chain, and establishes the forecasting model of tourism destination demand. This paper presents a tourism demand forecasting model based on tourism supply chain. Firstly, the hypothetical factors affecting tourism supply chain are put forward. Then, the grey correlation analysis is used to verify whether the hypothetical factors are related to the destination tourism demand. Finally, the prediction model is established by using the factors selected by grey correlation analysis. The model is used to build the prediction model of the number of inbound tourists in the United States and Hong Kong to verify the feasibility and effectiveness of the method.
【学位授予单位】：暨南大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F591
本文编号：2397347
[Abstract]:Tourism industry, as the important industry of the tertiary industry, has played an important role in promoting the economy. Demand forecasting is the beginning of tourism management, so the precision of tourism demand prediction is of great significance to tourism enterprises. At the same time, tourism is developed by the rise of tourist destinations. Each tourist destination has its unique tourism resources and characteristics, which determines that tourists have different tourism needs because of their different destinations. For the participants in the destination tourism industry, the accurate forecast results of tourism demand can guide the production and operation activities such as product development and business plan. Since there are many enterprises involved in tourism, we must systematically analyze the characteristics of tourism industry and tourism destination and find out the influencing factors in order to establish an effective demand forecasting model. Based on the traditional tourism demand forecasting, this paper introduces the concept of tourism supply chain. From the perspective of supply chain, this paper combs the running process of tourism supply chain, excavates the influence of tourism supply chain members on tourism demand, finds out the influencing factors of tourism supply chain, and establishes the forecasting model of tourism destination demand. This paper presents a tourism demand forecasting model based on tourism supply chain. Firstly, the hypothetical factors affecting tourism supply chain are put forward. Then, the grey correlation analysis is used to verify whether the hypothetical factors are related to the destination tourism demand. Finally, the prediction model is established by using the factors selected by grey correlation analysis. The model is used to build the prediction model of the number of inbound tourists in the United States and Hong Kong to verify the feasibility and effectiveness of the method.
【学位授予单位】：暨南大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F591
【参考文献】
相关期刊论文 前10条
1 鲍青青;唐善茂;刘胜峰;陆琳;;基于粗神经网络的旅游需求预测研究[J];安徽农业科学;2006年17期
2 黄丹霞;张俐俐;;构建以旅行社为核心的绿色旅游供应链初探[J];安徽农业科学;2009年05期
3 袁国宏;刘人怀;;旅游供应系统与求学供应系统的类比研究[J];商业研究;2008年01期
4 翁钢民;郑竹叶;刘洋;;我国入境旅游预测:基于ARFIMA模型的研究[J];商业研究;2009年06期
5 张晓明;张辉;毛接炳;;旅游服务供应链中若干环节的协调[J];城市发展研究;2008年05期
6 张侨;蔡道成;;基于灰色系统模型的海南中部国际旅游需求预测[J];科技和产业;2010年03期
7 张郴;张捷;;中国入境旅游需求预测的神经网络集成模型研究[J];地理科学;2011年10期
8 薛巨泉;;论新时期旅游供应链优化的措施和方法[J];大众文艺(理论);2009年22期
9 黄银珠;陈雅丽;;基于多种模型的福建省国内旅游需求预测[J];福建师大福清分校学报;2010年01期
10 李万立;李平;;转型时期我国旅游供应链优化机制研究[J];桂林旅游高等专科学校学报;2007年04期
相关硕士学位论文 前1条
1 刘恒飞;旅游业供应链管理模式研究[D];华中师范大学;2009年
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