上海迪士尼在建景区客源市场空间结构预测——旅游引力模型的修正及应用
A case study of Shanghai Disneyland on spatial structure forecast for proposed scenic spot market: Modification and its application of gravity model
查看参考文献56篇
|
文摘
|
客源市场预测是旅游科学决策的关键,由于缺乏历史数据,对尚未开业的旅游景区客源市场预测成为研究的难点。上海迪士尼乐园投资巨大、影响深远、广受关注、开园在即,迫切需要学界从理论层面对其客源市场展开研究。遵循“要素选取—系统分析—模型构建—市场预测—模型验证”的研究思路,对已有旅游引力模型进行修正:① 引入出游意愿,用百度指数进行测度,以明确旅游目的地偏好;② 引入出游率,用旅游人口取代总人口,以界定客源规模基数。而且修正模型中解释变量之间没有显著相关。基于2009-2013年香港迪士尼乐园内地客源市场数据、中国各省市区以及重点城市社会经济数据,运用修正引力模型,预测上海迪士尼乐园国内客源市场空间结构。研究表明:① 迪士尼乐园的强大品牌效应,在一定程度上弱化了空间阻尼的影响,进而导致内地游客对迪士尼乐园的旅游需求整体上缺乏弹性;② 上海迪士尼乐园国内客源市场在空间分布格局上,存在明显的近域指向、东部指向和大中城市指向特征;③ 经过交互验证,用修正引力模型推算的理论值与实际值的吻合程度更高,预测效果更好。 |
|
其他语种文摘
|
The market forecast plays a key role in tourism decision-making. However, due to lack of historical data, it remains an unsolved problem for the tourist market forecast of destinations which are not yet open to the public. Shanghai Disneyland has attracted wide attention for its huge investment and profound influence. With its forthcoming development, it is imperative to carry out a theoretical research in this field. The existing tourism gravity model is presented with three main explanatory variables: attractiveness of tourist destination, emissiveness of tourist origin, and spatial damping between the destination and origin. This paper makes modifications on the model as follows: (1) It introduces tourist rate which aims at replacing total population with tourist population to measure the tourist scale and accurately determine its base quota. (2) It introduces the element of tourist willingness, which is measured and estimated by using Baidu Index to clarify the preference for tourism destination. Thus, the scope of applying gravity model is not solely confined within the large and medium-scale tourist destinations (namely, cities, provinces and countries). The modified gravity model can also be applicable to the small- scale tourist destinations (namely, scenic spots). Likewise, it will avoid the interference of intervening opportunity. Furthermore, there is no significant correlation between any two variables in the modified model. Based on statistics of mainland tourists to Hong Kong Disneyland and socioeconomic statistics of China's provinces and municipalities from 2009 to 2013, this paper forecasts the spatial structure of domestic tourist market of Shanghai Disneyland through the modified gravity model. The research shows that: (1) Disneyland's strong brand effect drives tourists to overcome obstacles, so the impact brought about by spatial damping is reduced to some degree; as a whole, tourism demand of mainland tourists for Disneyland is inelastic. (2) The spatial distribution of domestic tourist market of Shanghai Disneyland remains strongly concentrated in neighboring regions accoding to the distance-decay theory. It is also mainly concentrated in eastern region and major cities driven by level of socioeconomic development. Based on the forecast of this paper, the Yangtze River Delta region is expected to account for 71.45% of the domestic market share, and China's eastern region occupies 82.40%, 39 major cities 41.44%.(3) Through verification, the coincident degree between the theoretical value deduced from the modified tourism gravity model and the actual value is better than that between the theoretical value deduced from the existing model and the actual value. Accordingly, the newly modified tourism gravity model proves to be more effective than the existing model. |
|
来源
|
地理学报
,2016,71(2):304-321 【核心库】
|
|
DOI
|
10.11821/dlxb201602010
|
|
关键词
|
迪士尼乐园
;
主题公园
;
引力模型
;
客源市场
;
空间结构
;
预测
|
|
地址
|
1.
安徽师范大学国土资源与旅游学院旅游发展与规划研究中心, 芜湖, 241002
2.
上海对外经贸大学会展与旅游学院, 上海, 201620
|
|
语种
|
中文 |
|
文献类型
|
研究性论文 |
|
ISSN
|
0375-5444 |
|
基金
|
国家自然科学基金重点项目
|
|
文献收藏号
|
CSCD:5634570
|
参考文献 共
56
共3页
|
|
1.
张捷. 自然观光旅游地客源市场的空间结构研究：以九寨沟及比较风景区为例.
地理学报,1999,54(4):357-364
|
被引
72
次
|
|
|
|
|
2.
南开大学旅游学系(译).
旅游决策与分析方法,1991:131-132
|
被引
1
次
|
|
|
|
|
3.
任来玲. 旅游需求预测方法文献述评.
旅游学刊,2006,21(8):90-92
|
被引
5
次
|
|
|
|
|
4.
陶伟. 中西方旅游需求预测对比研究: 理论基础与模型.
旅游学刊,2010,25(8):12-17
|
被引
7
次
|
|
|
|
|
5.
Yeong W Y. A Delphi forecast for the Singapore tourism industry: Future scenario and marketing implications.
European Journal of Marketing,1989,23(11):15-26
|
被引
1
次
|
|
|
|
|
6.
Martino J P.
Technological Forecasting for Decision Making,1993
|
被引
1
次
|
|
|
|
|
7.
赵西萍. 旅游目的地国国际旅游需求预测方法综述.
旅游学刊,1996(6):28-32
|
被引
4
次
|
|
|
|
|
8.
Chu F L. Forecasting tourism demand in Asian-Pacific countries.
Annals of Tourism Research,1998,25(3):597-615
|
被引
3
次
|
|
|
|
|
9.
Kulendran N. Cointegration versus least squares regression.
Annals of Tourism Research,2001,28(2):291-311
|
被引
3
次
|
|
|
|
|
10.
Goh C. Modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention.
Tourism Management,2002,23(5):499-510
|
被引
8
次
|
|
|
|
|
11.
Du Preez J. Univariate versus multivariate time series forecasting: An application to international tourism demand.
International Journal of Forecasting,2003,19(3):435-451
|
被引
4
次
|
|
|
|
|
12.
Lim C. Time series forecasts of international travel demand for Australia.
Tourism Management,2002,23:389-396
|
被引
5
次
|
|
|
|
|
13.
Gonzalez P. Analysis of tourism trends in Spain.
Annals of Tourism Research,1996,23(4):739-754
|
被引
2
次
|
|
|
|
|
14.
Cho V. A comparison of three different approaches to tourist arrival forecasting.
Tourism Management,2003,24:323-330
|
被引
4
次
|
|
|
|
|
15.
Law R. A neural network model to forecast Japanese demand for travel to Hong Kong.
Tourism Management,1999,20:89-97
|
被引
9
次
|
|
|
|
|
16.
Law R. Back- propagation learning in improving the accuracy of neural network- based tourism demand forecasting.
Tourism Management,2000,21(4):331-340
|
被引
6
次
|
|
|
|
|
17.
Goh C. Incorporating the rough sets theory into travel demand analysis.
Tourism Management,2003,24(5):511-517
|
被引
3
次
|
|
|
|
|
18.
Wang C H. Predicting tourism demand using fuzzy time series and hybrid grey theory.
Tourism Management,2004,25(3):367-374
|
被引
4
次
|
|
|
|
|
19.
Frechtling D C. Practical Tourism Forecasting.
Oxford: Butterworth-Heinemann,1996,10:133-139
|
被引
1
次
|
|
|
|
|
20.
Qu H. A travel demand model for Mainland Chinese tourists to Hong Kong.
Tourism Management,1997,18(8):593-597
|
被引
3
次
|
|
|
|
|
了解气象卫星更多信息，请访问