地理学报 ›› 2018, Vol. 73 ›› Issue (2): 295-317.doi: 10.11821/dlxb201802007

• 交通与旅游地理 • 上一篇    下一篇

旅游季节性测度指标的敏感度研究

刘泽华1(),章锦河2(),彭红松2,张瑜2,汤国荣2   

  1. 1. 南京财经大学工商管理学院,南京 210023
    2. 南京大学地理与海洋科学学院,南京 210023
  • 收稿日期:2017-01-25 出版日期:2018-02-11 发布日期:2018-02-11
  • 基金资助:
    国家自然科学基金项目(41671145);国家旅游局规划项目(15TAAG011);国家旅游局旅游业青年专家培养计划(TYETP201312)

Sensitivity analysis of the measures of tourism seasonality

LIU Zehua1(),ZHANG Jinhe2(),PENG Hongsong2,ZHANG Yu2,TANG Guorong2   

  1. 1. School of Business Administration, Nanjing University of Finance and Economics, Nanjing 210023, China
    2. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
  • Received:2017-01-25 Online:2018-02-11 Published:2018-02-11
  • Supported by:
    National Natural Science Foundation of China, No.41671145;Planning Project of National Tourism Administration, No.15TAAG011;Tourism Young Expert Training Program, No.TYETP201312

摘要:

常用的旅游季节性测度指标有季节性强度指数(Rsd)、基尼系数(G)、泰尔系数(T)、季节性比率(Rsr)、不均匀系数(Rhl)等,国内外学者对其相互关系、客流变动对各项指标的影响程度仍存在争议。构建旅游季节性测度指标的敏感度指标客流量变动效应(si)和客流量相对变动效应(pi),通过蒙特卡洛方法计算不同旅游季节性强弱尺度(Int)下的各项旅游季节性测度指标的相关系数、以及不同旅游季节性强弱尺度(Int)和不同客流量变动大小尺度(Δ)的组合条件下各项旅游季节性测度指标对各个月份的μsi、μ*si和μ*pi,发现:① RsdGT这3项指标相关系数极高,RsrRsdGT 3项指标的相关系数随着Int的增大而增大,RhlRsdGTRsr 4项指标间的相关系数随着Int的增大而减小;② RsrRhl对各月份的si以及RsdGTRsr对不同月份的μsi、μ*si及μ*pi均受Int和Δ的影响,其大小及排序相应产生变动,即在不同的旅游地,其季节性的强弱和客流量变动的大小都会导致各项旅游季节性测度指标对不同月份客流量变动的敏感度及排序存在差异,因此不能简单的认为某项指标对淡旺季客流或平季客流量变动更敏感。

关键词: 旅游季节性, 测度指标, 敏感度分析, 蒙特卡洛

Abstract:

Standard Deviation (Rsd), Gini coefficient (G), Theil index (T), seasonality ratio (Rsr), and ratio of highest to lowest-season demand (Rhl) are popular measures of tourism seasonality; however the relationship between these measures and their influence on changes in tourism flow varies in literatures. Two sensitivity indices were developed to reflect the effect of the changes of tourism flow on the tourism seasonality measures (si) and the relative effect of the changes of tourism flow on the tourism seasonality measures (pi). The correlation coefficient of measures of tourism seasonality in various scales (Int), the μsi, μsi*, and μpi* and changes of tourism flow (Δ) are calculated by the Monte Carlo method. The results show that: (1) All the correlation coefficients between Rsd, G and T are over 0.970. Therefore, the tourism seasonality of some destinations with the three measures is significantly consistent. The correlation coefficients of Rsr and Rsd (or G, T) are between 0.446 to 0.845, and increase with increasing Int. The differences of using Rsr and Rsd (or G, T) are increased with Int. The correlation coefficients of Rhl and Rsd (or G, T, Rsr) are in the range of 0.003-0.772, and smaller with increasing Int. The differences of using Rhl and Rsd (or G, T, Rsr) are decreased with increasing Int. (2) Besides s12 of Rhl, the only coefficient affected by m1, si of Rsr and Rhl to the other months are influenced by Rsr and Rhl, Δ, m? and mi. In addition to s12 >0, the value, even the sign, of si has no correlation to Rsr and Rhl, and cannot consider to be more sensitive to a specific month. (3) The μsi, μsi*, and μpi* of Rsd, G, T and Rsr for each month are varied by Int and Δ. Values and rank order change respectively to Int and Δ. Among them, s12 is always positive, increasing tourism flow increases the value of the measures of tourism seasonality; and to the other months, changing tourism flow may increase, decrease, or no change measures of tourism seasonality. Range of seasonal variation and changes of tourism flow could affect the sensitivity of different measures of tourism seasonality and the rank order in different months. Therefore, no such particular measure is discovered in this research that it is more sensitive than other measures related to the tourism flows, and neither are any measures more sensitive to the changes in the peak season, off-season, or shoulder season.

Key words: tourism seasonality, measure, sensitivity analysis, Monte Carlo