盐城麋鹿生态旅游区游客变化特征及预测

生态旅游区的发展受到诸多确定性因素和随机性因素的共同作用,并反映于旅游区游客观测序列.通过构建游客序列分析框架,提出了游客序列分析的理论模型.并以江苏盐城麋鹿生态旅游区为例,集成多种数学方法,进行了游客序列的分解、调整和综合预测的实证分析.运用Tramo/Seats方法进行季节调整分析可有效提取时间序列各组分,从而获得了不同尺度的作用模式,所获得的去噪序列为预测研究提供了基础资料.基于ARIMA模型、Winter加法模型、Winter乘法模型和Tramo/Seats模型的综合预测表明,麋鹿生态旅游区未来两年年平均新增游客数量在1.95-3.14万人次之间.各方法预测结果间的差异与其建模思路及实现方法有关,因此集成多种方法进行预测,并进行对比分析,有助于获得对游客波动变化更为全面的认识,同时所提供的多种可能预测方案,可为生态旅游区容量控制、旅游环境资源的保护与开发及旅游区的管理决策提供参考依据.

Forecasts of Tourist Flow Features in Eco-tourism Area: A Case Study of Yancheng David's Deer Eco-tourism Area

The number of tourists is one of the key indexes in measuring the development of eco-tourism area. By studying tourist flow and its variation law and by analyzing the flow series to predict its trend, scientific references could be provided for the area's planning, decision-making, protection, exploration and operational management. The development of eco-tourism area is subject to the interactions of a number of certainties and uncertainties, which is reflected via observational tourist flow series. This paper establishes a tourist serial analysis framework and puts forward its theoretic model. Taking Yancheng eco-tourism area for David's deer in Jiangsu Province as a study case, the paper applies various mathematic methods to discompose, readjust and synthetically forecast tourist series. The Tramo/Seats method is used to undertake seasonal regulation analysis for extracting each component of time series, hence obtaining functional models at various scales of long-term trend with seasonal, periodic and irregular variations. Moreover, the internal law of tourist flow fluctuation in eco-tourism area and its correlation between its influenting factors are analyzed, and thus we get the noise elimination series which provides foundation for a forecast study. The synthetic forecast results obtained by applying ARIMA model, Winter addition model, Winter multiplication model and Tramo/Seats model indicate an annual average increase of 19.5-3.14 thousand tourists in the coming two years, coinciding with the former series. The differences in forecast results between each method are relevant to the modeling thoughts and means of realization, this paper collects various methods to render forecasts and analysis in order to gain more comprehensive knowledge about tourist flow fluctuation. Furthermore, the various possible forecasts could offer references for capacity control, protection and exploration of tourism environmental resources and decision-making of tourism management.