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

机译:中国电子市场交易的空间和大数据分析

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摘要

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.
机译:本研究采用了大数据方法和重力模型来量化城市城市在线交易的范围和来源,并根据2011年6月到12月的淘宝平台的数据基于淘宝平台的数据来探索驱动力。比较 金吉地区长江三角洲和珠江三角洲表明,更高水平的经济发展对应了更发达的物流业和更多C2C淘宝商店。 回归结果说明了距离,GDP和人口密度是影响电子市场中交易量和交易数量的三个主要因素。 交易者按相对价值的数量和声誉也促进了交易的数量和数量。 此外,来自淘宝平台的大数据提供了证据表明重力模型在估计在线交易的数量。

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