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

  • Xinyue Ye
  • Zeng Lian
  • Bing She
  • Sonali Kudva
Article
  • 16 Downloads

Abstract

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.

Keywords

Big data Spatial structure E-market China 

Notes

Funding

This study was partially supported by the National Science Foundation (Grant Number 1416509).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal rights

This manuscript does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of InformaticsNew Jersey Institute of TechnologyNewarkUSA
  2. 2.International Business SchoolBeijing Foreign Studies UniversityBeijingChina
  3. 3.Institute for Social ResearchUniversity of MichiganAnn ArborUSA
  4. 4.College of Communication and InformationKent State UniversityKentUSA

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