旅游地客源市场出游力时空格局演化及其影响因素
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摘要
出游力对旅游地可持续发展及客源市场开发具有重要作用。通过出游力理论内涵分析,基于"推-阻-拉"理论修正了出游力测评模型,对厦门客源市场出游力进行测评,并运用季节性强度指数、空间自相关分析了出游力的时空格局。研究发现:1)厦门客源市场出游力主要分布于夏春两季,旺季短、平(淡)季长;各月出游力呈现"倒海鸥"形变化规律。2)出游力逐年增长,且高峰值集中于第三季度,呈现出厦门周边地区出游力强且季节性差异大,西北和东北出游力弱且季节性差异小的特点。3)出游力呈现空间集聚格局,但集聚程度呈下降态势。冷热点呈现"东南-西北"方位递减的空间分布趋势,符合距离衰减规律,热点区域分布于省内及周边地区。4)厦门客源市场可分为强出游力区、较强出游力区、一般出游力区和弱出游力区4个等级。5)经济发展水平、空间邻近效应、气候舒适度、旅游资源差异、交通成本和休假制度是厦门客源市场出游力的主要影响因素。
Emissiveness is an important way to assess the latent emissiveness of domestic tourist market,which contributes to the sustainable development of tourism destination and the development of tourist market.Based on the theoretical analysis of emissiveness,the emissiveness evaluation model is revised through push-resistance-pull theory.Further,the emissiveness of Xiamen tourist market is evaluated.And seasonal intensity index and spatial autocorrelation are adopted to analyze the spatial-temporal pattern of emissiveness.It is found as follows.First,the emissiveness of Xiamen tourist market is mainly distributed in the summer and spring.Specifically,peak-season is short,and the off-season and shoulder season are long.Moreover,the monthly emissiveness shows the change law of "inverted seagull" shape.Second,the emissiveness increases year by year with peak values of emissiveness concentrated in the third quarter.There is such a feature that the emissiveness in surrounding areas of Xiamen is relatively high with a distinct seasonal differences,while the emissiveness of Northwest and Northeast China is rather low with a minor seasonal differences.Third,there is a spatial agglomeration pattern shown in terms of emissiveness,but the agglomeration development trend is declining.Further,the cold-hot spots present a spatial distribution trend of decreasing along "southeast-northwest" orientation,which is consistent with distance decay.Fourth,the Xiamen tourist market can be divided into 4 levels,including strong emissiveness areas,relatively strong emissiveness areas,general emissiveness areas and weak emissiveness areas.Finally,economic development level,spatial proximity effect,comfort index of climate,tourism resource difference,transportation cost and vacation system are the main influencing factors of Xiamen tourist market.
Emissiveness is an important way to assess the latent emissiveness of domestic tourist market,which contributes to the sustainable development of tourism destination and the development of tourist market.Based on the theoretical analysis of emissiveness,the emissiveness evaluation model is revised through push-resistance-pull theory.Further,the emissiveness of Xiamen tourist market is evaluated.And seasonal intensity index and spatial autocorrelation are adopted to analyze the spatial-temporal pattern of emissiveness.It is found as follows.First,the emissiveness of Xiamen tourist market is mainly distributed in the summer and spring.Specifically,peak-season is short,and the off-season and shoulder season are long.Moreover,the monthly emissiveness shows the change law of "inverted seagull" shape.Second,the emissiveness increases year by year with peak values of emissiveness concentrated in the third quarter.There is such a feature that the emissiveness in surrounding areas of Xiamen is relatively high with a distinct seasonal differences,while the emissiveness of Northwest and Northeast China is rather low with a minor seasonal differences.Third,there is a spatial agglomeration pattern shown in terms of emissiveness,but the agglomeration development trend is declining.Further,the cold-hot spots present a spatial distribution trend of decreasing along "southeast-northwest" orientation,which is consistent with distance decay.Fourth,the Xiamen tourist market can be divided into 4 levels,including strong emissiveness areas,relatively strong emissiveness areas,general emissiveness areas and weak emissiveness areas.Finally,economic development level,spatial proximity effect,comfort index of climate,tourism resource difference,transportation cost and vacation system are the main influencing factors of Xiamen tourist market.
引文
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(1)数据来源:中国互联网络发展状况统计调查。
[2] 赖思振,邹永广.旅游区的客源地出游力测评研究——以福建省古田旅游区为例[J].经济地理,2016,36(3):194-200.
[3] 吴丽霞,赵现红.基于出游力的我国主要国际客源市场分类研究[J].地域研究与开发,2012,31(2):112-116.
[4] 范红艳.中原经济区居民国内出游力综合评价及时空演变[J].经济地理,2015,35(1):195-201.
[5] 陈超,谢红彬.福建省居民潜在国内出游力的地区差异综合评判[J].经济地理,2006,26(5):884-887.
[6] 郑海燕,保继刚.广东省居民潜在国内出游力的地区差异分析[J].地域研究与开发,2001,20(3):70-74.
[7] 郭伟,王颖,刘国玺.河北省农民潜在出游力地区差异的综合评判[J].统计与决策,2010(2):95-97.
[8] 冯学钢,黄和平,万田户.我国省际出游市场潜力时空差异与反季开发策略研究[J].旅游科学,2015,29(3):1-14.
[9] 赵英丽.新时期居民国内出游力影响因素研究[J].地域研究与开发,2006,25(2):52-56.
[10] 钟士恩,张捷,任黎秀,等.基于社会经济属性的中国省际出游力研究——兼对中国与世界已研究国家案例比较[J].经济地理,2009,29(1):153-159.
[11] LEIPER N.The framework of tourism:Towards a definition of tourism,tourist,and the tourist industry[J].Annals of Tourism Research,1979,6(4):390-407.
[12] 闾平贵,汪德根,魏向东.“时空压缩”与客源市场空间结构演变——以江苏国际旅游客源市场为例[J].经济地理,2009,29(3):504-509.
[13] 林海英,孟娜娜,李文龙.“一带一路”战略下内蒙古入境旅游客源市场时空演化[J].地域研究与开发,2016,35(2):101-107.
[14] 保继刚,郑海燕,戴光全.桂林国内客源市场的空间结构演变[J].地理学报,2002,57(1):96-106.
[15] 张高军,吴晋峰,曹晓仪,等.基于等时/费线的旅游客源市场空间分异研究[J].旅游学刊,2015,30(10):89-98.
[16] 靳诚,陆玉麒,范黎丽.江苏国内旅游客源市场空间结构研究[J].经济地理,2010,30(12):2104-2108.
[17] 吴必虎.上海城市游憩者流动行为研究[J].地理学报,1994,49(2):117-127.
[18] 南宇,史婧,赵利敏.西北五省区国内旅游客源市场演化结构分析研究[J].地域研究与开发,2012,31(3):103-107.
[19] 吴必虎,徐斌,邱扶东.中国国内旅游客源市场系统研究[M].上海:华东师范大学出版社,1999.
[20] 崔琰,席建超.基于出游潜力模型的省级出境旅游市场分类研究[J].资源科学,2015,37(11):2120-2128.
[21] 于静,郝金连,殷永昌.山西省居民潜在出游力研究[J].经济问题,2017(4):116-119.
[22] 栾福明,熊黑钢.新疆各地州市居民国内潜在出游力地区差异分析[J].生态经济,2009(12):74-77.
[23] 钟士恩,任黎秀,蒋志欣,等.客源地出游力的社会经济现象假说——基于中国国内旅游出游力研究[J].旅游学刊,2008,23(6):18-23.
[24] CESARIO F J.Alternative models for spatial choice[J].Economic Geography,1976,52(4):363-373.
[25] 吴必虎,方芳,殷文娣,等.上海市民近程出游力与目的地选择评价研究[J].人文地理,1997,12(1):21-27.
[26] DANN G M S.Tourist motivation an appraisal[J].Annals of Tourism Research,1981,8(2):187-219.
[27] FAKEYE P C,CROMPTON J L.Image differences between prospective,first-time,and repeat visitors to the lower Rio Grande Valley[J].Journal of Travel Research,1991,30(2):10-16.
[28] HU Y Z,RITCHIE J R B.Measuring destination attractiveness:A contextual approach[J].Journal of Travel Research,2016,32(2):25-34.
[29] 张佑印,马耀峰,王春,等.入境旅游流西向扩散特征及机理——以中国典型旅游区为例[J].社会科学家,2008(11):88-92.
[30] 高军,吴必虎,马耀峰.旅华英国游客O→D旅游客流动力机制研究[J].旅游学刊,2011,26(2):35-40.
[31] 马丽君,郭留留.基于网络关注度的北京市居民对5A级景区旅游需求时空特征分析[J].干旱区资源与环境,2017,31(10):203-208.
[32] 刘慧悦.旅游者网络信息需求与景区游客量的关联性研究——以四川九寨沟为例[J].情报科学,2017,35(7):39-43.
[33] 林志慧,马耀峰,刘宪锋,等.旅游景区网络关注度时空分布特征分析[J].资源科学,2012,34(12):2427-2433.
[34] 李山,邱荣旭,陈玲.基于百度指数的旅游景区络空间关注度:时间分布及其前兆效应[J].地理与地理信息科学,2008,24(6):102-107.
[35] 汪秋菊,黄明,刘宇.城市旅游客流量—网络关注度空间分布特征与耦合分析[J].地理与地理信息科学,2015,31(5):102-106.
[36] 杨兴柱,顾朝林,王群.旅游流驱动力系统分析[J].地理研究,2011,30(1):23-36.
[37] 刘少湃,田纪鹏,陆林.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[J].地理学报,2016,71(2):304-321.
[38] 阮文奇,李勇泉.自然灾害型危机事件对客源地旅游需求的影响及空间差异——九寨沟地震后的时空异质性分析[J].经济地理,2018,38(8):214-223.
[39] 冯娜,李君轶,张高军.基于因特网的重大事件旅游客流前兆效应研究——以西安世园会为例[J].河南科学,2013,31(2):244-249.
[40] 龙茂兴,孙根年,马丽君,等.区域旅游网络关注度与客流量时空动态比较分析——以四川为例[J].地域研究与开发,2011,30(3):93-97.
[41] 马丽君,孙根年,黄芸玛,等.城市国内客流量与游客网络关注度时空相关分析[J].经济地理,2011,31(4):680-685.
[42] 张舒宁,李勇泉.厦门客源市场旅游需求的时空格局演化[J].资源开发与市场,2018,7(34):1011-1020.
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(1)数据来源:中国互联网络发展状况统计调查。