Chinese Geographical Science

, Volume 28, Issue 2, pp 261–273 | Cite as

Impact of Shipping Distance on Online Retailers’ Sales: A Case Study of Maiyang on Tmall

  • Chunshan Zhou
  • Wanfu Jin
  • Guojun Zhang


Many studies have qualitatively explained that information and communication technology (ICT) has loosened the restrictions of distance and space on retailers’ sales. Few empirical studies, however, have explored the impact of shipping distance on online retailers’ sales. This study examined the Maiyang (M-Y) store on Tmall in China as a case study to investigate the relationship between shipping distance and sales. The results showed that sales volume in 2014 at the county level did not strictly obey the distance decay law. The shipped distance of high-priced commodities may not be much longer than that of low-priced commodities. Within the scope of investigation, the relationships between income, cost, and net profit curves do not follow central place theory. Goods have neither thresholds nor ranges. The key factor in the spatial discrepancy of sales is the size of market. The impact of shipping distance on sales is not as strong as that of traditional retailers in Information Era.


online retailers shipping distance central place theory 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



We would like to thank M-Y for its data support, and we acknowledge the reviews of anonymous referees.


  1. Anderson W P, Chatterjee L, Lakshmanan T R, 2003. E- commerce, transportation, and economic geography. Growth and Change, 34(4): 415–432. doi: 10.1046/j.0017-4815.2003.00228.xCrossRefGoogle Scholar
  2. Anderson W P, 2012. Economic Geography. New York: Routledge.Google Scholar
  3. Aoyama Y, 2003. Sociospatial dimensions of technology adoption: recent M-commerce and E-commerce developments. Environment and Planning A, 35(7): 1201–1221. doi: 10.1068/a35104CrossRefGoogle Scholar
  4. Cao X J, Douma F, Cleaveland F, 2010. Influence of e-shopping on shopping travel: evidence from Minnesota’s twin cities. Transportation Research Record: Journal of the Transportation Research Board, 2157: 147–154. doi: 10.3141/2157-18CrossRefGoogle Scholar
  5. Cao X J, Chen Q, Choo S, 2013. Geographic distribution of e-shopping: application of structural equation models in the Twin Cities of Minnesota. Transportation Research Record: Journal of the Transportation Research Board, 2383: 18–26. doi: 10.3141/2383-03CrossRefGoogle Scholar
  6. Crewe L, 2013. When virtual and material worlds collide: democratic fashion in the digital age. Environment and Planning A, 45(4): 760–780. doi: 10.1068/a4546CrossRefGoogle Scholar
  7. Ettlinger N, 2008. The predicament of firms in the new and old economies: a critical inquiry into traditional binaries in the study of the space-economy. Progress in Human Geography, 32(1): 45–69. doi: 10.1177/0309132507083506CrossRefGoogle Scholar
  8. Farag S, Weltevreden J, van Rietbergen T et al., 2006. E-shopping in the Netherlands: does geography matter? Environment and Planning B: Planning and Design, 33(1): 59–74. doi: 10.1068/b31083CrossRefGoogle Scholar
  9. Farag S, Schwanen T, Dijst M et al., 2007. Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping. Transportation Research Part A: Policy and Practice, 41(2): 125–141. doi: 10.1016/j.tra.2006.02.003Google Scholar
  10. Galliano D, Roux P, Soulié N, 2011. ICT intensity of use and the geography of firms. Environment and Planning A, 43(1): 67–86. doi: 10.1068/a43167CrossRefGoogle Scholar
  11. Ghezzi A, Mangiaracina R, Perego A, 2012. Shaping the e- commerce logistics strategy: a decision framework. International Journal of Engineering Business Management, 4(1): 1–13. doi: 10.5772/51647Google Scholar
  12. Hsiao M H, 2009. Shopping mode choice: physical store shopping versus e-shopping. Transportation Research Part E: Logistics and Transportation Review, 45(1): 86–95. doi: 10.1016/j.tre.2008.06.002CrossRefGoogle Scholar
  13. Huang Xiujuan, Huang Fucai, 2007. Analysis on influence factors of tourism international competitiveness with PCR. Economic Geography, 27(5): 847–851. (in Chinese)Google Scholar
  14. Huang Jinchuan, Chen Shouqiang, 2015. Classification of China’s urban agglomerations. Progress in Geography, 34(3): 290–301. (in Chinese)Google Scholar
  15. Javalgi R, Ramsey R, 2001. Strategic issues of e-commerce as an alternative global distribution system. International Marketing Review, 18(4): 376–391. doi: 10.1108/02651330110398387CrossRefGoogle Scholar
  16. Kaplan D, Wheeler J O, Holloway S, 2009. Urban Geography. 2nd ed. New York: Wiley.Google Scholar
  17. Kolars J, Nystuen J D, 1974. Geography: the Study of Location, Culture and Environment. New York: McGraw-Hill.Google Scholar
  18. Krizek K, Li Y, Handy S, 2005. Spatial attributes and patterns of use in household-related information and communications technology activity. Transportation Research Record: Journal of the Transportation Research Board, 1926: 252–259. doi: 10.3141/1926-29CrossRefGoogle Scholar
  19. Liu W D, Dicken P, Yeung H W C, 2004. New information and communication technologies and local clustering of firms: a case study of the Xingwang industrial park in Beijing. Urban Geography, 25(4): 390–407. doi: 10.2747/0272-3638.25.4.390CrossRefGoogle Scholar
  20. Martin R N, 2008. Globalized freight transport: intermodality, e-commerce, logistics and sustainability. The Professional Geographer, 60(4): 586–588. doi: 10.1080/00330120802239936CrossRefGoogle Scholar
  21. Michalak W, Calder L, 2003. Integration of e-commerce as a retail channel: impact of youth: on e-commerce trends in Canada. Progress in Planning, 60(1): 111–126. doi: 10.1016/S0305-9006(02)00094-6CrossRefGoogle Scholar
  22. Morgan K, 2001. The exaggerated death of geography: localised learning, innovation and uneven development. Technology, 89(1): 32–49.Google Scholar
  23. Morgan K, 2004. The exaggerated death of geography. Geography, 89(1): 32–49.Google Scholar
  24. Morganti E, Dablanc L, Fortin F, 2014. Final deliveries for online shopping: the deployment of pickup point networks in urban and suburban areas. Research in Transportation Business & Management, 11: 23–31. doi: 10.1016/j.rtbm.2014.03.002CrossRefGoogle Scholar
  25. National Bureau of Statistics of China, 2015. China Statistical Yearbook 2015. Beijing: China Statistics Press. (in Chinese)Google Scholar
  26. Nemoto T, Visser J, Yoshimoto R, 2001. Impacts of information and communication technology on urban logistics system. In: Joint OECD/ECMT Seminar on the Impacts of E-Commerce on Transport. Paris: OECD/ECMT.Google Scholar
  27. Park S O, 2004. The impact of business-to-business electronic commerce on the dynamics of metropolitan spaces. Urban Geography, 25(4): 289–314. doi: 10.2747/0272-3638.25.4.289CrossRefGoogle Scholar
  28. Park SO, Taylor M, 2004. E-commerce, e-business, and the dynamics of metropolitan economies. Urban Geography, 25(4): 285–288. doi: 10.2747/0272-3638.25.4.285CrossRefGoogle Scholar
  29. Pyle R, 1996. Electronic commerce and the internet. Communications of the ACM, 39(6): 22–23. doi: 10.1145/228503.228507CrossRefGoogle Scholar
  30. Rayport J F, Sviokla J J, 1994. Managing in the marketspace. Harvard Business Review, 72(6): 141–150. doi: 10.1016/0024-6301(95)91061-1Google Scholar
  31. Ren F, Kwan M P, 2009. The impact of geographic context on e-shopping behavior. Environment and Planning B: Planning and Design, 36(2): 262–278. doi: 10.1068/b34014tCrossRefGoogle Scholar
  32. Rotem-Mindali O, 2014. E-commerce: implications for travel and the environment. In: Gärling T, Ettema D, and Friman M (eds). Handbook of Sustainable Travel. Dordrecht: Springer, 293–305.CrossRefGoogle Scholar
  33. Schwanen T, Dijst M, Kwan M P, 2006. Introduction–the internet, changing mobilities, and urban dynamics. Urban Geography, 27(7): 585–589. doi: 10.2747/0272-3638.27.7.585CrossRefGoogle Scholar
  34. Song Zhouying, Liu Weidong, Ma Li et al., 2014. Measuring spatial differences of informatization in China. Chinese Geographical Science, 24(6): 717–731. doi: 10.1007/s11769-013-0646-1CrossRefGoogle Scholar
  35. Wang Shijun, Feng Zhangxian, Liu Daping et al., 2012. Basic perspective and preliminary framework for the theoretical innovation and development of central place theory in new times. Progress in Geography, 31(10): 1256–1263. (in Chinese)Google Scholar
  36. Weltevreden J W J, van Rietbergen T, 2007. E-shopping versus city Centre shopping: the role of perceived city Centre attractiveness. Tijdschriftvoor Economischeen Sociale Geografie, 98(1): 68–85. doi: 10.1111/j.1467-9663.2007.00377.xCrossRefGoogle Scholar
  37. Xi Guangliang, Zhen Feng, Gilles P et al., 2017. Spatio-temporal fragmentation of leisure activities in informationera: empirical evidence from Nanjing, China. Chinese Geographical Science, 27(1): 137–150. doi: 10.1007/s11769-017-0851-4CrossRefGoogle Scholar
  38. Xu Xueqiang, Zhu Jianru, 1988. Modern Urban Geography. Beijing: China Architecture & Building Press. (in Chinese)Google Scholar
  39. Yeung G, Ang K L, 2016. Online fashion retailing and retail geography: the blogshop phenomenon in Singapore. Tijdschriftvoor Economischeen Sociale Geografie, 107(1): 81–99. doi: 10.1111/tesg.12129CrossRefGoogle Scholar
  40. Yu Jinyan, Liu Weidong, Wang Liang, 2013. Analysis of virtual trading area of C2C e-commerce based on temporal distance: a case study of 50 cosmetics retail stores on TAOBAO in Beijing. Acta Geographica Sinica, 68(10): 1380–1388. (in Chinese)Google Scholar
  41. Zhang Xin. 2010. Research on Concentration of Web Information Flows Distance Decay. Shijiazhuang: Hebei Normal University. (in Chinese)Google Scholar
  42. Zhang Haixia, Zhou Lingqiang, 2013. Factor components and differences of the park-based recreational happiness for urban residents: a case study of Hangzhou. Scientia Geographica Sinica, 33(9): 1074–1081. (in Chinese)Google Scholar
  43. Zhen F, Wang B, Wei Z, 2014. The rise of the internet city in China: production and consumption of internet information. Urban Studies, 52(13): 2313–2329. doi: 10.1177/0042098014547369CrossRefGoogle Scholar
  44. Zhen Feng, Wei Zongcai, 2008. Influence of information technology on social spatial behaviors of urban residents—case of Nanjing City in China. Chinese Geographical Science, 18(4): 316–322. doi: 10.1007/s11769-008-0316-xCrossRefGoogle Scholar

Copyright information

© Science Press, Northeast Institute of Geography and Agricultural Ecology, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Geography and PlanningSun Yat-sen UniversityGuangzhouChina
  2. 2.School of Public AdministrationGuangdong University of Finance and EconomicsGuangzhouChina

Personalised recommendations