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Erschienen in: Information Systems and e-Business Management 4/2020

14.12.2018 | Original Article

RETRACTED ARTICLE: Network evolution analysis of e-business entrepreneurship: big data analysis based on taobao intelligent information system

verfasst von: Zheng Ye, Jianzhuang Zheng, Ruiyi Tu

Erschienen in: Information Systems and e-Business Management | Ausgabe 4/2020

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Abstract

In recent years, the entrepreneurial development of taobao village based on e-business has led to a new round growth of rural economy in China. This paper constructs a evolution analysis framework of taobao village entrepreneurial network based on the big data of taobao intelligent information system from the year 2007–2016. The social network analysis software Gephi was applied to analyze the data. The result is that: Firstly, the early emerged online shops with high betweenness centrality degree, which mastered important resources and power within the network, formed a strong entrepreneurial demonstration effect to the other shops. Secondly, in taobao village, the number of strong relationship shops increased, entrepreneurial network gradually dispersed characteristics of clustering, entrepreneurial network community structure strength enhanced, division quality optimization, and the transmission performance and efficiency of entrepreneurial network improved. The entrepreneurial network has a typical characteristic of “acquaintance” network business conduction. Thirdly, the entrepreneurial network density of Lin’an taobao village showed a significant downward trend, which may be more conducive to the homogeneous agricultural products sales shops to access to heterogeneous resources, so as to obtain more long-term future development.

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Metadaten
Titel
RETRACTED ARTICLE: Network evolution analysis of e-business entrepreneurship: big data analysis based on taobao intelligent information system
verfasst von
Zheng Ye
Jianzhuang Zheng
Ruiyi Tu
Publikationsdatum
14.12.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Information Systems and e-Business Management / Ausgabe 4/2020
Print ISSN: 1617-9846
Elektronische ISSN: 1617-9854
DOI
https://doi.org/10.1007/s10257-018-0390-2

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