网上购物对实体零售的影响

doi:10.3969/j.issn.1004-9479.2020.03.2018554

摘要/Abstract

摘要：

在互联网时代，商业中心受到新兴信息技术的冲击日益显著，成为新经济对城市空间影响效应的集中体现。本文以上海南方商城商业中心为例，通过消费者问卷调查与实地商家访谈探讨了网上购物对实体零售的影响效应。总体而言，网购频率对实体购物的影响呈正态分布的形式，高频和低频网购者产生高频实体购物的可能性较低，而中频网购人群具有更高的实体购物频率。从消费者内在决策过程分析，网购一方面降低了消费者对实体零售空间的满意度，但另一方面也刺激了消费者需求的增长，催生出更多的休闲娱乐消费行为。因此，网购对实体零售业及其消费者所带来的影响是复杂的，决策过程中不同方面受到的影响不尽相同。最后对商业中心的应对策略进行了分析讨论。

关键词: 网上购物, 实体零售, 个人出行, 智慧商圈

Abstract:

In the Internet era, the impact of new information technologies on commercial centers is becoming more obvious, which has become the concentrated embodiment of the spatial effects of new economy in the urban areas. Taking Nanfang commercial center as a case, this paper explores the impact of online shopping on in-store shopping via consumer questionnaires and semi-structured interviews. Overall, the influence of online shopping frequency on in-store shopping is in the form of normal distribution. High-frequency and low-frequency online shoppers are less likely to carry out high-frequency in-store shopping, while medium-frequency online shoppers have higher in-store shopping frequency. Through the analysis of consumers' internal decision process, we can see that online shopping decreased the satisfaction of shopping mall, but stimulated the demand of consumers so that brought more entertainment consumption. Therefore, the impact of online shopping on in-store shopping is complex. In the process of shopping decision-making, online shopping has different impacts in different aspects. Finally, the article also discusses the countermeasures of commercial centers.

Key words: online shopping, in-store shopping, personal travel, smart commercial area

林玥希, 汪明峰, 马同翠. 网上购物对实体零售的影响[J]. 世界地理研究, 2020, 29(3): 568-578.

Yuexi LIN, Mingfeng WANG, Tongcui MA. The impact of online shopping on in-store shopping: An investigation of Nanfang Commercial Center in Shanghai[J]. World Regional Studies, 2020, 29(3): 568-578.

图/表 7

参考文献 31

1	汪明峰. 技术、产业和地方：互联网的经济地理学. 人文地理, 2005, 20(5): 90-94.
	Wang M. Technology, industry and place: the economic geography of Internet. Human Geography, 2005, 20(5): 90-94.
2	李飞, 任莹, 衡量. 零售革命形成的动因——基于技术革命的视角. 技术经济, 2018, 37(9): 25-35.
	Li F, Ren Y, Heng L. Motivation of formation in retail revolution: Based on perspective of technology revolution. Technology Economics, 2018, 37(9): 25-35.
3	商务部流通发展司.《2017-2018中国零售行业发展报告》. . [Department of Circulation Industry Development, Ministry of Commerce, 2017-2018 China Retail Industry Development Report. ]
4	申悦, 柴彦威, 王冬根. ICT对居民时空行为影响研究进展. 地理科学进展, 2011, 30(6): 643-651.
	Shen Y, Chai Y, Wang D. Reviews on impacts of information and communication technologies on human spatial-temporal behavior. Progress in Geography, 2011, 30(6): 643-651.
5	Mokhtarian P L. A conceptual analysis of the transportation impacts of B2C e-commerce. Transportation, 2004, 31(3): 257-284.
6	Farag S, Weltevreden J, van Rietbergen T, et al. E-shopping in the Netherlands：Does geography matter? Environment and Planning B：Planning and Design, 2006, 33(1): 59-74.
7	刘学, 甄峰, 张敏, 等. 网上购物对个人出行与城市零售空间影响的研究进展及启示. 地理科学进展, 2015, 34(1): 48-54.
	Liu X, Zhen F, Zhang M. Research review of online shopping impact on personal travel and urban retail space and implications. Progress in Geography, 2015, 34(1): 48-54.
8	Dixon T, Marston A. UK retail real estate and the effects of online shopping. Journal of Urban Technology, 2002, 9(3): 19-47.
9	Bhat C R, Sivakumar A, Axhausen K W. An analysis of the impact of information and communication technologies on non-maintenance shopping activities. Transportation Research Part B: Methodological, 2003, 37(10): 857-881.
10	刘红, 真虹. 信息技术发展对城市交通客流量替代作用的定量研究. 系统工程理论与实践, 2000, 20(9): 78-82.
	Liu H, Zhen H. A quantitative study on substitute effect of information technology for the development of urban passengers traffic. Systems Engineering-Theory & Practice, 2000, 20(9): 78-82.
11	甄峰, 魏宗财, 杨山, 等.信息技术对城市居民出行特征的影响——以南京为例.地理研究, 2009, 28(5): 1307-1317.
	Zhen F, Wei Z, Yang S, et al. The impact of information technology on the characteristics of urban resident travel: Case of Nanjing. Geographical Research, 2009, 28(5): 1307-1317.
12	Farag S, Schwanen T, Dijst M, et al. Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping. Transportation Research Part A, 2007, 41(2): 125-141．
13	Lee R J, Sener I N, Mokhtarian P L, et al. Relationships between the online and in-store shopping frequency of Davis, California residents. Transportation Research Part A: Policy & Practice, 2017, 100: 40-52.
14	汪明峰, 卢姗, 邱娟. 网上购物对城市零售业空间的影响: 以书店为例. 经济地理, 2010, 30(11): 1835-1840.
	Wang M, Lu S, Qiu J. The impact of online shopping on urban retail space: A case study of book store. Economic Geography, 2010, 30(11): 1835-1840.
15	Calderwood E, Freathy P. Consumer mobility in the Scottish isles: The impact of internet adoption upon retail travel patterns. Transportation Research Part A: Policy & Practice, 2014, 59(1):192-203.
16	汪明峰, 卢姗. 替代抑或补充: 网上购物与传统购物出行的关系研究. 人文地理, 2012, 27(3): 44-49.
	Wang M, Lu S. Substitution or complementarity: Online shopping and its relationship with traditional shopping behavior. Human Geography, 2012, 27(3): 44-49.
17	张永明,甄峰.城市居民网络与实体购物互动模式及空间分异——以南京为例. 经济地理, 2017, 37(1): 15-22.
	Zhang Y, Zhen F. The interaction mode between online shopping and store shopping of urban resident and spatial differentiation—A case study of Nanjing. Economic Geography, 2017, 37(1): 15-22.
18	席广亮, 甄峰, 汪侠, 等. 南京市居民网络消费的影响因素及空间特征. 地理研究, 2014, 33(2): 284-295.
	Xi G, Zhen F, Wang X. Study on the influencing factors and spatial characteristics of residents' online consumption in Nanjing. Geographical Research, 2014, 33(2): 284-295.
19	朱玮, 陈懿慧, 王德. 基于多代理人模拟的上海市域零售业中心体系研究. 上海城市规划, 2014, (1): 109-115.
	Zhu W, Chen Y, Wang D. Research on the Retail center system of shanghai using multi-agent simulation. Shanghai Urban Planning Review, 2014, (1): 109-115.
20	路紫, 王文婷, 张秋娈, 等.体验性网络团购对城市商业空间组织的影响. 人文地理, 2013, 28(5): 101-104.
	Lu Z, Wang W, Zhang Q, et al. The impact of experiential online group-buying on the urban commercial spatial organization. Human Geography, 2013, 28(5): 101-104.
21	Weltevreden J W J, Rietbergen T V. E-shopping versus city center shopping: The role of perceived city center attractiveness. Tijdschrift voor Economische En Sociale Geografie, 2007, 98(1): 68-85.
22	Singleton A D, Dolega L, Riddlesden D, et al. Measuring the spatial vulnerability of retail centers to online consumption through a framework of e-resilience. Geoforum, 2016, (69):5-18．
23	曾思敏, 陈忠暖. 国外网上零售商业空间及其影响效应研究综述. 人文地理, 2013, 28(1): 36-42.
	Zeng S, Chen Z. A review on spatial organization of E-retail and its impact abroad. Human Geography, 2013, 28(1): 36-42.
24	丁亮, 钮心毅, 宋小冬. 上海中心城区商业中心空间特征研究. 城市规划学刊, 2017, (1): 63-70.
	Ding L, Niu X, Song X. A study on spatial characteristics of commercial centers in the Shanghai central city. Urban Planning Forum, 2017, (1): 63-70.
25	张文忠, 李业锦. 北京城市居民消费区位偏好与决策行为分析——以西城区和海淀中心地区为例. 地理学报, 2006, 61(10): 1037-1045.
	Zhang W, Li Y. Study on residents' shopping location preference and shopping location choice: A case on Xicheng and Haidian Districts of Beijing. Acta Geographica Sinica, 2006, 61(10): 1037-1045.
26	Hawkins S A, Hoch S J. Low-involvement learning: memory without evaluation. Journal of Consumer Research, 1992, 19(2): 212-225.
27	柴彦威, 林涛, 龚华. 深圳居民购物行为空间决策因素分析. 人文地理, 2004, 19(6): 85-88.
	Chai Y, Lin T, Gong H. Spatial decision making process of shopping behavior of Shenzhen residents. Human Geography, 2004, 19(6): 85-88.
28	唐得昊, 林岚. 民营超市购物选择行为影响因素的模型构建与实证研究——以福州市为例. 人文地理, 2013, 28(4): 64-70.
	Tang D, Lin L. Model construction on shopping choice behavior influence factors in private supermarket: A case study of Fuzhou. Human Geography, 2013, 28(4): 64-70.
29	Cardozo R N. An experimental study of customer effort, expectation, and satisfaction. Journal of Marketing Research, 1965, 2(3): 244-249.
30	Cubukcu K M. Factors affecting shopping trip generation rates in metropolitan areas. Studies in Regional & Urban Planning, 2001, 9: 51-67.
31	Sim L L, Koi S M. Singapore's Internet shoppers and their impact on traditional shopping patterns. Journal of Retailing and Consumer Services, 2002, 9(2): 115-124.

参数	样本属性	样本量	比重	参数	样本属性	样本量	比重
性别	男	185	50.82%	月收入	1000元以下	39	10.71%
性别	女	179	49.18%		1001-3000元	48	13.19%
年龄	17岁及以下	14	3.85%		3001-5000元	94	25.82%
	18-34岁	251	68.96%		5001-10000元	100	27.47%
	35-59岁	85	23.35%		10000-19999元	67	18.41%
	60岁及以上	14	3.85%		20000元及以上	16	4.40%
学历	初中及以下	18	4.95%	居住地	梅陇镇	100	27.47%
	高中/中专/职高/技校	56	15.38%		闵行(非梅陇镇)	172	47.25%
	大专/电大/夜校	74	20.33%		上海(非闵行区)	81	22.25%
	本科	178	48.90%		非上海地区	11	3.02%
	研究生及以上	38	10.44%

参数	样本属性	样本量	比重	参数	样本属性	样本量	比重
性别	男	185	50.82%	月收入	1000元以下	39	10.71%
性别	女	179	49.18%		1001-3000元	48	13.19%
年龄	17岁及以下	14	3.85%		3001-5000元	94	25.82%
	18-34岁	251	68.96%		5001-10000元	100	27.47%
	35-59岁	85	23.35%		10000-19999元	67	18.41%
	60岁及以上	14	3.85%		20000元及以上	16	4.40%
学历	初中及以下	18	4.95%	居住地	梅陇镇	100	27.47%
	高中/中专/职高/技校	56	15.38%		闵行(非梅陇镇)	172	47.25%
	大专/电大/夜校	74	20.33%		上海(非闵行区)	81	22.25%
	本科	178	48.90%		非上海地区	11	3.02%
	研究生及以上	38	10.44%

参数	样本属性	样本量	比重	参数	样本属性	样本量	比重
网购频率	不网购	13	3.57%	网购消费	不网购	11	3.02%
	每年至少一次	30	8.24%		1-200元	53	14.56%
	每月至少一次	145	39.84%		200-500元	122	33.52%
	每周至少一次	146	40.11%		500-1000元	101	27.75%
	基本上每天	30	8.24%		1000-2000元	55	15.11%
每月网购支出占总消费比例	10%以下	114	31.32%		2000元以上	22	6.04%
	10%-20%	108	29.67%
	20%-30%	87	23.90%
	30%以上	55	15.11%

参数	样本属性	样本量	比重	参数	样本属性	样本量	比重
网购频率	不网购	13	3.57%	网购消费	不网购	11	3.02%
	每年至少一次	30	8.24%		1-200元	53	14.56%
	每月至少一次	145	39.84%		200-500元	122	33.52%
	每周至少一次	146	40.11%		500-1000元	101	27.75%
	基本上每天	30	8.24%		1000-2000元	55	15.11%
每月网购支出占总消费比例	10%以下	114	31.32%		2000元以上	22	6.04%
	10%-20%	108	29.67%
	20%-30%	87	23.90%
	30%以上	55	15.11%

检验内容		卡方	自由度	显著性
似然比检验		100.443	44	0.000
拟合优度检验	Person	555.710	618	0.965
拟合优度检验	Deviance	518.809	618	0.999
平行线检验		39.357^c	44	0.671