网购时代广州市居民购买食品行为特征

doi:10.13284/j.cnki.rddl.003171

Abstract

Abstract:

Information and communication technology reshapes resident behavior and urban spaces. Emerging online shopping has changed residents’ shopping preferences and processes, which inevitably affects the physical business space. However, there are some differences in shopping behaviors of different types of goods. Current research focuses on online shopping behavior for books, clothes, and other commodities, but seldom explores online food shopping behavior from the spatial perspective. Based on 1406 questionnaires on the food shopping behavior of residents in Guangzhou, we compared the behaviors of food purchasers whether to buy online, who buy food online in different locations and with different frequencies. General and spatial characteristics of food shopping behaviors of Guangzhou residents under the influence of online shopping were investigated in this study using cross frequency, chi-square test, and corresponding analyses. Spatial characteristics included shopping locations, retail formats, residence locations, and shopping travel time. The results of this study are as follows: 1) Acceptance of online shopping food is generally low, and the traditional shopping model still dominates; however, online food shopping has a certain substitution effect on traditional food purchases based on purchase frequency and single cost. This is consistent with Suel et al. (2015) who investigated the relationship between online and physical grocery shopping in the United Kingdom. 2) The influence of online shopping on food sales spaces varies in different locations and formats. Online food shopping has a greater negative effect on shops around residential areas but little on those in the business district. Supermarkets and department stores will be negatively affected relative to leisure snacks and local specialty food sales, whereas fresh food stores will be less affected. In the context of the decline in physical business owing to online shopping, Guangzhou’s fresh supermarkets are booming, which also confirms that online shopping has less impact on fresh food stores. 3) The role of spatial factors still exists in the information age. Resident online shopping behaviors show similar frequency in different locations but are dissimilar in cost, time, and reasons for online shopping. However, residents with poor physical shopping conditions are more inclined to buy food online, verifying the “efficiency hypothesis”. Spatial factors are an important reason why Guangzhou residents buy food online. Residents with poor physical shopping conditions are more affected by this factor, supporting the “efficiency hypothesis” from another angle. 4) The purpose and time of physical shopping trips of online food shoppers have changed. Online food shoppers have more leisure shopping purposes and more weekend shopping trips. Additionally, residents with high online food shopping frequency have shorter travel times. The results of this study will help develop targeted business development strategies and commercial space planning in the future. This study helps understand the impact of online shopping on different types of goods and different physical business locations to guide the future layout and development of online and offline retail enterprises and provide a basis for city governments to conduct business facilities network planning.

Key words: online shopping, food shopping behavior, spatial characteristics, location, Guangzhou

CLC Number:

K901

Deng Qinghua, Xue Desheng, Gong Jianzhou. Behavior Characteristics of Food Shopping of Guangzhou Residents in the Age of Online Shopping[J].Tropical Geography, 2019, 39(5): 780-789.

Figures/Tables 12

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References 51

1	Ahmed S A and Aguilar S . 2013. Comparison of Canadian and Mexican Students’ Online Shopping Behavior. Latin American Business Review, 14(1):79-106.
2	Anderson W P, Chatterjee L and Lakshmanan T R . 2003. E-commerce, Transportation, and Economic Geography. Growth and Change, 34(4):415-432.
3	Bryła P . 2018. Organic Food Online Shopping in Poland. British Food Journal, 120(5):1015-1027.
4	Corbett J J . 2001. Is Online Grocery Shopping Increasing in Strength?. Journal of Food Distribution Research, 32(1):37-40.
5	Dennis C, Hansen T and Jensen J M . 2009. Shopping Orientation and Online Clothing Purchases: The Role of Gender and Purchase Situation. European Journal of Marketing, 43(9/10):1154-1170.
6	Daim T, Basoglu N, Gunay D, Yildiz C and Gomez F . 2013. Exploring Technology Acceptance for Online Food Services. International Journal of Business Information Systems, 12(4):383-403.
7	杜晓娟, 甄峰 , Cao Jason. 2017. 南京市居民购物行为的影响因素和空间效应——基于四种商品的对比研究. 地理研究, 36(5):957-971.
	[ Du Xiaojuan, Zhen Feng and Cao Jason . 2017. Influential Factors and Spatial Effects of Individuals’ Shopping Behavior in Nanjing: A Comparative Study on Four Types of Goods. Geographical Research, 36(5):957-971. ]
8	Edrisi A and Ganjipour H . 2017. The Interaction between E-Shopping and Shopping Trip, Tehra. Proceedings of the Institution of Civil Engineers - Municipal Engineer, 170(4):239-246.
9	Farag S, Weltevreden J W J, Rietbergen T V, Dijst M J and Oort F G V . 2006. E-shopping in the Netherlands: Does Geography Matter? Environment and Planning B: Planning and Design, 33(1):59-74.
10	傅辰昊, 周素红, 闫小培, 柳林 . 2018. 广州市零售商业中心消费活动时变模式及其影响因素. 地理科学, 38(1):20-30.
	[ Fu Chenhao, Zhou Suhong, Yan Xiaopei and Liu Lin . 2018. Temporal Variation Patterns and Influencing Factors of Consuming Activity in Retailing Centers: A Case Study of Guangzhou, China. Scientia Geographica Sinica, 38(1):20-30. ]
11	Ganapathi R . 2015. A Study on Factors Affecting Online Shopping Behavior of Consumers in Chennai. Journal of Management Research and Analysis, 2(2):123-126.
12	Girard T, Korgaonkar P and Silverblatt R . 2003. Relationship of Type of Product, Shopping Orientations, and Demographics with Preference for Shopping on the Internet. Journal of Business & Psychology, 18(1):101-120.
13	国家统计局广州调查队城镇住户处. 2018. 网购消费需求与供给应对分析.(2018-08-28)[2018-12-05]. .
	[ Urban Households’ Office of Guangzhou Survey Team, National Bureau of Statistics. 2018. Analysis on the Demand and Supply of Online Purchase.(2018-08-28)[2018-12-05]. ]
14	Hasanov J and Khalid H . 2015. The Impact of Website Quality on Online Purchase Intention of Organic Food in Malaysia: A Web Qual Model Approach. Procedia Computer Science, 72:382-389.
15	Hiser J, Nayga R M J and Capps O J . 1999. An Exploratory Analysis of Familiarity and Willingness to Use Online Food Shopping Services in a Local Area of Texas. Journal of Food Distribution Research, 30(1):78-90.
16	冯其予 . 2019. 去年全国网上零售额超九万亿元农村电商迅猛发展.(2019-02-22)[2019-03-20]. 经济日报, .
	[ Feng Qiyu. 2019. The National Online Retail Sales Exceeded 9 Trillion Yuan, and Rural E-commerce Developed Rapidly Last Year. (2019-02-22) [2019-03-20]. Economic Daily, ]
17	Kapoor N, Kumar Maurya M and Kamalvanshi V . 2017. Consumer’s Perception Towards Online Shopping of Food Products: An Empirical Research. Social Science Electronic Publishing, 5(12):25-30.
18	Lennon S J, Ha Y, Johnson K K P, Jasper C R, Damhorst M L and Lyons N . 2009. Rural Consumers’ Online Shopping for Food and Fiber Products as a Form of Outshopping. Clothing and Textiles Research Journal, 27(1):3-30.
19	Li Dekui and Zhou Fan . 2017. Study on Food Online Shopping Behavior of Citizen Based on Food-Related Lifestyle Theory. Qingdao: 3 ^rd International Conference on Social Science and Development.
20	Liang A R and Lim W M . 2011. Exploring the Online Buying Behavior of Specialty Food Shoppers. International Journal of Hospitality Management, 30(4):855-865. doi: 10.1016/j.ijhm.2011.01.006
21	Morganosky M A and Cude B J . 2000. Consumer Response to Online Grocery Shopping. International Journal of Retail & Distribution Management, 28(1):17-26.
22	Morganosky M A and Cude B J . 2001. Consumer Responses to Online Food Retailing. Journal of Food Distribution Research, 32(1):5-17.
23	Mokhtarian P L . 2004. A Conceptual Analysis of The Transportation Impacts of B2C E-Commerce. Transportation, 31(3):257-284. doi: 10.1023/B:PORT.0000025428.64128.d3
24	Muruganantham G and Bhakat R S . 2013. An Empirical Study of Impulse Buying Behavior in Online Bookstores. International Journal of Online Marketing, 3(3):1-17.
25	Nelson P J . 1970. Information and Consumer Behavior. Journal of Political Economy, 78(2):311-329.
26	欧玫姗 . 2009. 澎湖地区居民之生活型态与网络购物行为研究. 澎湖:国立澎湖科技大学.
	[ Ou Meishan . 2009. The Study on The Lifestyles and the Internet Shopping Behaviors of the Inhabitants in Penghu Area. Penghu: National Penghu University. ]
27	Pauzi S, Thoo A C, Tan L C, Muharam F M and Talib N A . 2017. Factors Influencing Consumers Intention for Online Grocery Shopping-A Proposed Framework. IOP Conference Series: Materials Science and Engineering, 215:1-12.
28	Ren F and Kwan M . 2009. The Impact of Geographic Context on E-Shopping Behavior. Environment and Planning B: Planning and Design, 36(2):262-278.
29	Robertson G, Murphy J and Purchase S . 2005. Distance to Market: Propinquity across In-store and Online Food Retailing. Electronic Markets, 15(3):235-245.
30	Shin J and Lee S . 2019. A Study on the Effect of Online Activation Business Transaction Factors of Fresh Food Shopping Mall on E-Customer Relationship Quality and E-Customer Loyalty. The East Asian Journal of Business Management, 7(1):1-16.
31	Suel E, Le Vine S and Polak J . 2015. Empirical Application of Expenditure Diary Instrument to Quantify Relationships between In-Store and Online Grocery Shopping. Transportation Research Record: Journal of the Transportation Research Board, 2496:45-54.
32	孙智群, 柴彦威, 王冬根 . 2009. 深圳市民网上购物行为的空间特征. 城市发展研究, 16(6):106-112.
	[ Sun Zhiqun, Chai Yanwei and Wang Donggen . 2009. The Spatial Characteristics of E-shopping Behavior of Shenzhen Residents. Urban Studies, 16(6):106-112. ]
33	Tang W and Mokhtarian P L . 2009. Impact of Product Type and Other Variables on Store and Internet Purchase Intentions: Clothing Versus Books. Washington D C: Transportation Research Board 88 ^th Annual Meeting.
34	汪明峰, 卢姗, 邱娟 . 2010. 网上购物对城市零售业空间的影响:以书店为例. 经济地理, 30(11):1835-1840.
	[ Wang Mingfeng, Lu Shan and Qiu Juan . 2010. The Impact of Online Shopping on Urban Retail Space: A Case Study of Book Store. Economic Geography, 30(11):1835-1840. ]
35	汪明峰, 卢姗 . 2012. 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, 27(3):44-49.
	[ Wang Mingfeng and Lu Shan . 2012. Substitution or Complementarity: Online Shopping and Its Relationship with Traditional Shopping Behavior. Human Geography, 27(3):44-49. ]
36	汪明峰, 卢姗, 袁贺 . 2013. 网上购物对不同区位消费者行为的影响——市区和郊区的比较. 城市规划, 37(11):84-88,95.
	[ Wang Mingfeng, Lu Shan and Yuan He . 2013. Influences of Online Shopping on Consumer Behaviors at Different Shopping Locations: A Comparative Study on City Center and Suburb. City Planning Review, 37(11):84-88, 95. ]
37	翁艺丹, 千庆兰, 陈颖彪, 韩富状 . 2015. 广州人口空间均衡特征与经济关联研究初探. 广州大学学报(自然科学版), 14(6):84-91.
	[ Weng Yidan, Qian Qinglan, Chen Yinbiao and Han Fuzhuang . 2015. A Preliminary Study on the Spatial Equilibrium of Guangzhou’s Population and Its Relationship with Economy. Journal of Guangzhou University (Natural Science Edition), 14(6):84-91. ]
38	Weltevreden J W J and Rietbergen T V . 2007. E-shopping versus City Centre Shopping: The Role of Perceived City Centre Attractiveness. Tijdschrift voor Economische en Sociale Geografie, 98(1):68-85.
39	White G K . 2001. Online Specialty Food Consumers in 2000: Who They Are and What They Buy. Journal of Food Distribution Research, 32(2):39-52.
40	席广亮, 甄峰, 汪侠, 秦萧 . 2014. 南京市居民网络消费的影响因素及空间特征. 地理研究, 33(2):284-295.
	[ Xi Guangliang, Zhen Feng, Wang Xia and Qin Xiao . 2014. Study on the Influencing Factors and Spatial Characteristics of Residents’ Online Consumption in Nanjing. Geographical Research, 33(2):284-295. ]
41	杨浩雄, 王浩 . 2018. 生鲜食品网络购买决策的关键因素研究. 管理现代化, 38(4):64-66.
	[ Yang Haoxiong and Wang Hao . 2018. Study on Key Factors of Fresh Food Online Purchasing Decision. Modernization of Management, 38(4):64-66. ]
42	杨进广 . 2013. 网上购物感知风险研究——以网购食品为例. 成都:西南交通大学.
	[ Yang Jinguang . 2013. Online Shopping Perceived Risk Research: As the Net to Food. Chengdu: Southwest Jiaotong University. ]
43	易智康 . 2015. B2C电子商务对广州天河IT商业空间的影响研究. 广州:华南理工大学.
	[ Yi Zhikang . 2015. The Impact of E-business on IT Commercial District in Guangzhou Tianhe. Guangzhou: South China University of Technology. ]
44	余安琦, 刘杨晨, 缪琪琪 . 2018. 基于描述性统计分析的网络食品购买行为与风险感知. 中国商论,( 22):60-62.
	[ Yu Anqi, Liu Yangchen and Mu Qiqi . 2018. Internet Food Purchase Behavior and Risk Perception Based on Descriptive Statistical Analysis. Chinese Commerce, ( 22):60-62. ]
45	张小英, 巫细波 . 2016. 广州购物中心时空演变及对城市商业空间结构的影响研究. 地理科学, 36(2):231-238.
	[ Zhang Xiaoying and Wu Xibo . 2016. Spatial-Temporal Evolution of Malls in Guangzhou City and Its Impact on Urban Commercial Spatial Structure. Scientia Geographica Sinica, 36(2):231-238. ]
46	张永明, 甄峰 . 2017 a.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, 37(1):15-22.
	[ Zhang Yongming and Zhen Feng . 2017 a. The Interaction Mode between Online Shopping and Store Shopping of Urban Resident and Spatial Differentiation:A Case Study of Nanjing. Economic Geography, 37(1):15-22. ]
47	张永明, 甄峰, 曹新宇, 翟青, 章雨晴 . 2017b. 基于区位和商品类型的居民购物过程分解比较——以南京为例. 人文地理, 32(1):109-115.
	[ Zhang Yongming, Zhen Feng, Jason Cao, Zhai Qing and Zhang Yuqing . 2017b. A Comparative Study on Residents’ Shopping Process by Differentiating Location and Types of Goods: A Case Study of Nanjing City. Human Geography, 32(1):109-115. ]
48	张红霞, 杨渊 . 2017. 消费者网购食品安全信心及其影响因素分析. 调研世界,( 10):17-22.
	[ Zhang Hongxia and Yang Yuan . 2017. Consumer’s Confidence in Online Food Safety and Its Influencing Factors. The World of Survey and Research, ( 10):17-22. ]
49	章雨晴, 甄峰, 张永明 . 2016. 南京市居民网络购物行为特征——以书籍和衣服为例. 地理科学进展, 35(4):476-486.
	[ Zhang Yuqing, Zhen Feng and Zhang Yongming . 2016. Characteristics of E-Shopping Behavior of Nanjing Residents: A Case of Books and Clothes. Progress in Geography, 35(4):476-486. ]
50	中国互联网络信息中心. 2019. 第43次《中国互联网络发展状况统计报告》.(2019-02-28)[2019-04-06].http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201902/t20190228_70645.htm .
	[ China Internet Network Information Center. 2019. The 43rd Statistical Report on the Development of Internet in China (2019-02-28)[ 2019-04-06]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201902/t20190228_70645.htm. ]
51	中国商务部电子商务和信息化司. 2017. 中国电子商务报告(2016).(2017-06-14)[2019-02-15].http://dzsws.mofcom.gov.cn/article/dzsw/tjjc/201706/20170602591881.shtml .
	[ Department of Electronic Commerce and Informatization, Ministry of Commerce of the People’s Republic of China. 2017. China E-commerce Report(2016). (2017-06-14)[2019-02-15]. http://dzsws.mofcom.gov.cn/article/dzsw/tjjc/201706/20170602591881.shtml .]

样本属性		网购食品者		不网购食品者		合计
样本属性		样本数/个	比例/%	样本数/个	比例/%	样本数/个	比例^*/%
性别	男	313	45.3	378	54.7	691	49.1
性别	女	384	53.7	331	46.3	715	50.9
年龄/岁	15~24	290	60.4	190	39.6	480	34.1
	25~34	244	66.8	121	33.2	365	26.0
	35~44	114	46.9	129	53.1	243	17.3
	45~59	45	20.1	179	79.9	224	15.9
	≥60	4	4.3	90	95.7	94	6.7
学历	初中及以下	25	12.3	179	87.7	204	14.5
	高中或高职	129	41.2	184	58.8	313	22.3
	大专或本科	511	61.1	326	38.9	837	59.5
	研究生	32	61.5	20	38.5	52	3.7
月收入 /万元	<0.3	319	53.3	279	46.7	598	42.5
	0.3~0.6	180	46.9	204	53.1	384	27.3
	0.6~1	139	51.5	131	48.5	270	19.2
	1~1.5	49	46.7	56	53.3	105	7.5
	>1.5	10	20.4	39	79.6	49	3.5
职业	机关/事业单位人员	58	45.0	71	55.0	129	9.2
	企业员工	194	56.4	150	43.6	344	24.5
	私营业者	73	40.3	108	59.7	181	12.9
	在校学生	281	61.4	177	38.6	458	32.5
	自由职业者	50	47.6	55	52.4	105	7.5
	农民	3	9.7	28	90.3	31	2.2
	退休人员	7	8.9	72	91.1	79	5.6
	其他	31	39.2	48	60.8	79	5.6
居住区位	中心区	241	48.7	254	51.3	495	35.2
	近郊区	257	49.4	263	50.6	520	37.0
	远郊区	199	50.8	192	49.2	391	27.8
	合计	697	49.6	709	50.4	1 406	100

居民及购物渠道		月均购物频率/次					单次花费/元					时间
居民及购物渠道		0	1~4	5~10	≥11	合计	<20	20~50	50~100	>100	合计	工作日	周末	两者差不多	合计
不网购食品者	实体占比/%	2.6	47.8	29.4	20.2	100	15.5	38.1	32	14.4	100	6.2	32	61.8	100
网购食品者	实体占比/%	1	58.6	23.5	16.9	100	15.4	39.5	32	13.1	100	4.5	43.5	52	100
网购食品者	网络占比/%	0	89.1	9.8	1.1	100	13	40	35.4	11.6	100	5.2	21.9	72.9	100

常网购食品类型	频数/次	比例^*/%
休闲零食	577	83.6
生鲜食品	44	6.4
粮油调味	53	7.7
饮料冲饮	217	31.4
保健品类	66	9.6
烟酒	21	3
地方特产	115	16.7
进口食品	279	40.4
其他	2	0.3

购买地点	不网购食品者	网购食品者	合计
购物网站	0	25.2	13.8
居住地周边商店	96.7	70.5	82.4
商业区	3.3	4.3	3.8

区域类型	月均网购频率/次				单次花费/元					时间
区域类型	1~4	5~10	≥11	合计	<20	20~50	50~100	>100	合计	工作日	周末	两者差不多	合计
中心区	88.0	11.2	0.8	100	11.0	33.7	40.1	15.2	100	5.5	19.9	74.6	100
近郊区	89.1	10.1	0.8	100	10.5	49.3	32.4	7.8	100	6.3	17.7	76.0	100
远郊区	90.5	7.5	2.0	100	18.8	35.5	33.5	12.2	100	3.6	29.6	66.8	100

Behavior Characteristics of Food Shopping of Guangzhou Residents in the Age of Online Shopping

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