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A Network Formation Model for Social Object Networks

In: Liss 2014

Author

Listed:
  • Somayeh Koohborfardhaghighi

    (College of Engineering, Seoul National University)

  • Jörn Altmann

    (College of Engineering, Seoul National University)

Abstract

Social networks can be differentiated according to the type of entities that are represented within them. Entities in human networks can act strategically to maximize their own payoffs during interactions with other humans. However, entities in social object network (e.g., SaaS service network) are not able to perceive the environment and act strategically upon that at any time. This paper contends that existing network formation models lack sufficient attention to social object networks. Therefore, we propose a new network formation model, through which we are able to explain how a SaaS service network emerges during the service composition procedure by service developers. The new network formulation model not only considers the usage frequency and reputation but also the similarity of the functionalities of the main SaaS services. It also explains how social objects (e.g., SaaS services) benefit from establishments of links between each other in the network.

Suggested Citation

  • Somayeh Koohborfardhaghighi & Jörn Altmann, 2015. "A Network Formation Model for Social Object Networks," Springer Books, in: Zhenji Zhang & Zuojun Max Shen & Juliang Zhang & Runtong Zhang (ed.), Liss 2014, edition 127, pages 615-625, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-43871-8_89
    DOI: 10.1007/978-3-662-43871-8_89
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    Cited by:

    1. Somayeh Koohborfardhaghighi & Jorn Altmann, 2016. "How Network Visibility and Strategic Networking Leads to the Emergence of Certain Network Characteristics: A Complex Adaptive System Approach," TEMEP Discussion Papers 2016130, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Aug 2016.
    2. Somayeh Koohborfardhaghighi & Jorn Altmann, 2016. "How Strategic Networking Impacts the Networking Outcome: A Complex Adaptive System Approach," TEMEP Discussion Papers 2016131, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Aug 2016.

    More about this item

    Keywords

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    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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