IDEAS home Printed from https://ideas.repec.org/a/igg/jwsr00/v13y2016i3p64-87.html
   My bibliography  Save this article

Building and Analyzing of Enterprise Network: A Case Study on China Automobile Supply Network

Author

Listed:
  • Liqiang Wang

    (School of Computer Science and Technology, Shandong University, Jinan, China)

  • Shijun Liu

    (Key Laboratory of Shandong Province for Software Engineering, School of Computer Science and Technology, Shandong University, Jinan, China)

  • Li Pan

    (School of Computer Science and Technology, Shandong University, Jinan, China)

  • Lei Wu

    (School of Computer Science and Technology, Shandong University, Jinan, China)

  • Xiangxu Meng

    (Engineering Research Center of Digital Media Technology, Ministry of Education, School of Computer Science and Technology, Shandong University, Jinan, China)

Abstract

Social business moves beyond linear, process-driven organizations to create new, dynamic, networked businesses that focus on customer value. Enterprise network (EN) is used to support social business by maximizing current and future opportunities and facilitate network-enabled processes, which can lead to value co-creation. EN is a multi-level hypergraph model with enterprises, employees, products and other related entities. In this paper the authors refine the EN model and present the foundation of EN to support social businesses. Then they introduce a case study on China automobile supply network (CASN). For the similarity with social networks, they verify power-law and small world theories in EN with statistical results on this data set. These theories are fitful in EN, but some new characteristics exist. The structure of EN consists of star-shaped clusters and the authors extract ego networks taking suppliers and manufacturers as the ego respectively. With the structure and distribution features of EN, they present the enterprise business similarity analysis method based on common-neighbors. And they also introduce the tentative work to detect Dunbar circles in EN. To analyze the data in a more intuitional and effective way, the authors use some data visualization tools to process the data in EN.

Suggested Citation

  • Liqiang Wang & Shijun Liu & Li Pan & Lei Wu & Xiangxu Meng, 2016. "Building and Analyzing of Enterprise Network: A Case Study on China Automobile Supply Network," International Journal of Web Services Research (IJWSR), IGI Global, vol. 13(3), pages 64-87, July.
  • Handle: RePEc:igg:jwsr00:v:13:y:2016:i:3:p:64-87
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJWSR.2016070104
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jwsr00:v:13:y:2016:i:3:p:64-87. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.