基于本底线和亲景度的秦岭国家植物园客流量预测

FORECAST OF THE TOURIST-GENERATING MARKET OF QINLING NATIONAL BOTANICAL GARDEN BASED ON THE BACKGROUND OF TREND LINE & PREFERENCE SCALE

客源市场分析与预测是景区规划的重要内容。对于拟建或新建景区,目前尚无公认的较为科学的预测方法。本文采用以本底趋势线和游客亲景度相结合的方法对拟建的秦岭国家植物园客流量进行预测。该方法以西安市为客源聚集地,建立国际入境旅游、国内旅游和本地居民游憩3条本底趋势线,再结合游客对目的地的旅游偏好和亲景度,按高低两个方案分别计算出未来5—25年秦岭国家植物园的游客分流量。本研究为拟建景区客流量预测提供了一种新方法。

At present, there is not a widely acceptable market analysis and forecast method for a new-built or a would-be-built tourism attraction. In this paper, a new method based on the theory of background trend line （BTL） and concept of preference scale is applied to conduct the analysis and forecast of tourist-generating market for Qinling National Botanical Garden （QNBG）, a would-be tourism attraction. The relatively accurate forecast of potential tourist flow of Xian in coming 5-25 years is the precondition for the market forecast of QNBG. According to the theory of BTL, Xian＇s tourist flow change can be regarded as a combination of tendency change and periodical change. Using linear equation plus sine equation, the paper establishes 3 BTLs for Xian＇s international, domestic and local tourist markets. And potential tourist flow of the above markets can be calculated for the next 5-25 years. Also, the paper estimates and confirms the preferences scale of the certain tourism attraction for the three markets by the way of market survey, and the tourist flow of the three markets of QNBG can then be calculated. Total tourist flow should be the sum of the three markets. According to what have been forecasted, the expected tourist flow of QNBG would be 530 thousands to 650thousands in the year 201 I, 750 thousands to 930 thousands in 2021 and 930 thousands to 1.15 million in 2029. The structure of tourist-generating market of the forecast is reasonable, with international tourists occupying 5.4 - 6.2%, domestic tourists occupying 57-60% and local tourists 34-38%. To testify the result of the forecast, the paper compares QNBG with similar type of tourism attractions in Shanxi province and other provinces and results reveal that the forecast is feasible and reasonable. The paper provides a new forecast method for a would-be tourism attraction and especially useful for predicting new tourist attractions which are located near central big cities.