Spatial and big data analytics of E-market transaction in China

Xinyue Ye, Zeng Lian, Bing She, Sonali Kudva

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


This study uses a big data approach and gravity model to quantify the scope and sources of online transactions in urban China and explore the driving forces, based on data from the Taobao platform for online cellphone transactions from June to December in 2011. Comparison among Jing-Jin-Ji Region, Yangtze River Delta, and Pearl River Delta shows that a higher level of economic development corresponds to the more developed logistics industry and more C2C Taobao shops. The regression results illustrate that distance, GDP, and population density are the three main factors which influence the volume and number of trades in the e-marketplace. The number and reputation of traders by relative value also promote the volume and numbers of trades significantly. Additionally, the big data from the Taobao platform provides evidence that the gravity model is valid in estimating the amounts of online transactions.

Original languageEnglish (US)
Pages (from-to)329-341
Number of pages13
Issue number2
StatePublished - Apr 1 2020

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development


  • Big data
  • China
  • E-market
  • Spatial structure


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