The impact of online shopping on in-store shopping: An investigation of Nanfang Commercial Center in Shanghai

doi:10.3969/j.issn.1004-9479.2020.03.2018554

Abstract

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

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

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.

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.

Figures/Tables 7

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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