星巴克在中国大陆的空间扩散特征与影响因素研究
作者简介:曾国军(1977- ),男,湖南华容人,教授,博士生导师,研究方向为酒店管理和饮食地理。E-mail: zenggj@mail.sysu.edu.cn
收稿日期: 2016-08-03
要求修回日期: 2016-11-24
网络出版日期: 2017-01-20
基金资助
国家自然科学基金项目(41571129,41301140)
Spatial expansion mode and its influencing factors ofStarbucks in mainland of China
Received date: 2016-08-03
Request revised date: 2016-11-24
Online published: 2017-01-20
Copyright
以在中国大陆的1446家星巴克门店为研究对象,借助空间分析和计量回归方法探讨星巴克的空间分布特征、空间选择的文化制度和经济影响因素以及空间扩张模式。研究发现:第一,星巴克空间分布表现出非均衡的凝聚分布特征,其扩张路径主要是从以沿海经济发达地区为重点布局区域逐步向内陆省份延伸,表现出对零售业对外政策实施的高度响应,即政策制度显著影响星巴克的空间扩散。第二,市场需求、购买力水平等8个影响因素均显著正向地影响星巴克门店的空间选择。第三,星巴克空间扩张表现出等级扩散与接触扩散相混合的特征,其空间扩张模式分别经历了等级扩散为主、等级扩散与接触扩散并存、接触扩散为主的三个阶段。研究不仅对目前跨国零售企业的空间扩张研究进行了实证补充,而且为企业空间扩张理论提供了一个实践验证。同时,研究给服务企业的传统空间增长理论提出新的挑战。
曾国军 , 陆汝瑞 . 星巴克在中国大陆的空间扩散特征与影响因素研究[J]. 地理研究, 2017 , 36(1) : 188 -202 . DOI: 10.11821/dlyj201701015
In the process of globalized consumption, multinational corporations have accelerated overseas expansion. Retail industry is the most typical case. With production turned from Fordism to post-Fordism, multinational corporations in retail industry are more inclined to lie in the consumer sites. They sell standardized product to the rest of the world through foreign direct investment as well as foreign trade, and gradually formed a unified global production and sales network. At the same time, the embedded consumption patterns and lifestyles in the consumer product have a direct impact on consumer preferences and choices around the world. With the gradual implementation of the opening-up policy in China's retail industry, the multinational retail corporations distributed quickly to strengthen their localization process in China. From the perspectives of expansion scale and strategy, KFC, McDonald's, Haagen-Dazs, Starbucks and other multinational corporations are most typical in F&B industry. In their expansion to China, these multinational corporations in F&B industry need to consider not only the economic and cultural advantages among cities, but also the differences among commercial locations within the city. However, few reports in the literature relates to the overseas location choice of the multinational corporations in F&B industry. This paper discusses the spatial distribution, influencing factors and expansion mode based on the sample of 1446 Starbucks subsidiaries in the mainland of China with the methods of spatial analysis and regression. The results show that: (1) Starbucks exhibits a non-equilibrium and aggregated distribution mode. Its expansion path gradually extends from the coastal well-developed areas to inland provinces, which echoes to the implementation of the opening-up policy in retail industry. At the same time, it shows that the cultural system and economic factors greatly influence the expansion mode. (2) Under the dimensions of economy, space, information and humanities, indicators of market demand, purchasing power, price level, retail market conditions, transportation accessibility, commerce prosperity, the level of development of communication facilities, information networks and regional economic openness are closely related to the location choice of Starbuck stores. (3) The expansion mode of Starbucks is not the typical contagious diffusion model in service enterprises, but shows the hierarchical diffusion and contagious diffusion mixed mode. The study finds that the expansion of Starbucks has undergone three stages: hierarchical diffusion, mixed mode, and contagious diffusion.
Key words: Starbucks; location choice; diffusion; space expansion; food
Tab. 1 Summary of the research methods and data sources表1 研究方法与数据来源汇总 |
| 研究方法 | 研究目的 | 主要数据来源 |
|---|---|---|
| 最邻近距离指数 | 描述星巴克的空间分布特征 | 百度地图API以及星巴克官网 |
| 基尼系数与洛伦兹曲线 | 补充描述星巴克在不同城市的分布情况 | 百度地图API以及星巴克官网 |
| Pearson相关分析 | 探究星巴克空间选择的影响因素 | 中国城市地价动态监测网、中国经济与社会发展统计数据库 |
| 空间状态模型 | 探究星巴克的空间扩张模式 | 中国城市统计年鉴 |
Tab. 2 Expansion trajectory of the Starbucks in China表2 星巴克在中国的扩张之路 |
| 首次进入时间 | 城市布局 |
|---|---|
| 1999年 | 北京 |
| 2000年 | 上海 |
| 2002年 | 深圳 |
| 2003年 | 广州、南京、宁波 |
| 2004年 | 苏州、无锡、常州 |
| 2005年 | 青岛、大连、成都、沈阳、东莞 |
| 2006年 | 重庆(第19座城市)、西安 |
| 2007年 | 佛山 |
| 2008年 | 武汉(第26座城市) |
| 2010年 | 珠海、长沙、福州、济南 |
| 2011年 | 厦门、昆明、合肥、石家庄、郑州、哈尔滨等省会城市 |
| 2012年 | 烟台、保定、南昌、南宁、泉州、 淮安、三亚(门店总数超过700家) |
注:数据来源于星巴克官网及相关新闻资料,作者整理数据绘制了表2。 |
Fig. 1 Spatial distribution of Starbuck stores图1 星巴克门店的空间分布图 |
Tab. 3 Results of the nearest neighbor ratio表3 最邻近距离分析结果 |
| 实际观测平均距离(m) | 4274.049463 |
|---|---|
| 理想分布平均距离(m) | 39770.122867 |
| 最邻近距离指数 | 0.107469 |
| Z值 | -64.928955 |
| P值 | 0.000000 |
Tab. 4 Proportions of Starbuck stores in provinces (autonomous regions, municipalities) respectively (%)表4 各省份/直辖市的星巴克门店数量占比(%) |
| 上海 | 广东 | 北京 | 江苏 | 浙江 | 四川 | 湖北 | 山东 | 福建 |
|---|---|---|---|---|---|---|---|---|
| 18.81 | 15.01 | 12.24 | 11.69 | 7.68 | 4.50 | 3.87 | 3.87 | 3.11 |
| 天津 | 辽宁 | 重庆 | 陕西 | 湖南 | 安徽 | 河南 | 河北 | 黑龙江 |
| 2.70 | 2.63 | 1.87 | 1.66 | 1.52 | 1.18 | 1.11 | 1.04 | 0.97 |
| 吉林 | 广西 | 云南 | 海南 | 山西 | 江西 | 内蒙古 | 贵州 | 甘肃 |
| 0.83 | 0.76 | 0.76 | 0.54 | 0.48 | 0.41 | 0.41 | 0.21 | 0.14 |
Fig. 2 The Space Lorenz Curve of the Starbuck stores图2 星巴克门店的空间洛伦兹曲线 |
Tab. 5 Number of Starbuck stores in 32 cities表5 32个城市的星巴克门店数量(家) |
| 北京 | 上海 | 天津 | 重庆 | 广州 | 深圳 | 东莞 | 珠海 |
|---|---|---|---|---|---|---|---|
| 174 | 273 | 39 | 27 | 76 | 74 | 16 | 11 |
| 佛山 | 合肥 | 厦门 | 福州 | 郑州 | 哈尔滨 | 武汉 | 长沙 |
| 22 | 13 | 22 | 13 | 13 | 11 | 53 | 20 |
| 南京 | 苏州 | 无锡 | 常州 | 南通 | 长春 | 沈阳 | 大连 |
| 35 | 48 | 34 | 12 | 10 | 11 | 25 | 11 |
| 青岛 | 济南 | 烟台 | 西安 | 成都 | 昆明 | 杭州 | 宁波 |
| 23 | 11 | 11 | 23 | 62 | 11 | 46 | 28 |
Tab. 6 Pearson correlation coefficient of each variable with the number of the Starbuck stores表6 各变量与星巴克门店数量的皮尔逊相关系数② |
| 变量名 | Pearson Correlation | 变量名 | Pearson Correlation |
|---|---|---|---|
| 人口密度(人/km2) | 0.478** | 人均道路拥有面积(m2) | 0.506** |
| 人均可支配收入(元) | 0.459** | 商业营用房销售面积(万m2) | 0.397* |
| 商服地价水平(元) | 0.754** | 国际互联网用户数(万户) | 0.520** |
| 社会消费品零售(亿元) | 0.867** | 外贸依存度 | 0.438* |
注:*和**分别表示在0.05和0.01水平(双侧)上显著相关。 |
Tab. 7 NLS source of the nlinfit based on the MATLAB 7.0表7 基于Matlab 7.0的nlinfit非线性最小二乘法源程序 |
| load SJ |
|---|
| x=A(:,1:2); |
| y=A(:,1); |
| beta0=[-1 2.214 -0.089]; %初始值 |
| f=@(beta,x)(beta(1)*x(:,1)+beta(1)*(x(:,1).^2))./(x(:,2).^beta(3)); |
| [beta,resid,J,Sigma]= nlinfit(x,y,f,beta0); |
| beta %回归系数 |
| ci = nlparci(beta,resid,'covar',Sigma) |
| ci %回归系数的置信区间 |
| [ypred, delta] = nlpredci(f,x,beta,resid,'Covar',Sigma); |
| ypred %预测值 |
| R2=1-sum((y-ypred).^2)/sum((y-mean(y)).^2) % R2判决系数 |
| plot([1:32],y,[1:32],ypred) |
Tab. 8 Spatial diffusion model of the Starbucks in China表8 星巴克在中国大陆的空间扩散类型 |
| 系数 | 回归系数 | 置信区间 | |
|---|---|---|---|
| 0.009742** | (0.001693, 0.017791) | 0.76 | |
| 0.000003* | (0.000003, 0.000003) | ||
| 0.127327*** | (0.001715, 0.252939) |
注:*、**和***分别表示在0.05、0.01和0.001水平下显著。 |
The authors have declared that no competing interests exist.
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