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Social Network Analysis and Mining

An architectural framework for developing a recommendation system to enhance vendors’ capability in C2C social commerce

  • 01-12-2018
  • Original Article
Published in:
Authors
Supattana Sukrat
Borworn Papasratorn
Published in
Social Network Analysis and Mining | Issue 1/2018

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Abstract

The rapid growth of social networking usage has initiated a new business model called C2C s-commerce which has opened a novel opportunity for SNS users to conduct commercial activities among members. Novice vendors (low-maturity merchants) perform business using a trial-and-error method. Through learning by doing, capability enhancement in online business arrangements to become a mature vendor is difficult and takes time. Having a recommendation system can effectively and systematically support inexperienced vendors to conduct online business and enable vendors to become high-maturity merchants. This study proposes architecture of a C2C s-commerce recommendation system presented in conjunction with its input, process, and output. The architecture was devised to infer from information collected from case study interviews, observation, and secondary research methods. Artificial intelligence technologies and big data were considered to design the proposed framework in order to generate efficient recommendations for capability enhancement in online business arrangements.

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previous article Emissions abating technology adoption in a coal trading network
next article Detecting overlapping communities in LBSNs by fuzzy subtractive clustering
Title
An architectural framework for developing a recommendation system to enhance vendors’ capability in C2C social commerce
Authors
Supattana Sukrat
Borworn Papasratorn
Publication date
01-12-2018
Publisher
Springer Vienna
Published in
Social Network Analysis and Mining / Issue 1/2018
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-018-0500-7
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