Factors that determine the level of interaction in wikis, blogs and forums in private virtual communities
|Factors that determine the level of interaction in wikis, blogs and forums in private virtual communities|
|Author(s)||Valerio G., Rangel I., Flores M.|
|Published in||Proceedings of the IADIS International Conference Web Based Communities and Social Media 2013, Proceedings of the IADIS International Conference Collaborative Technologies 2013|
|Keyword(s)||Blogs, Forums, Virtual communities, Wikis (Extra: Construction sectors, Determinant factors, Forums, Interaction levels, Knowledge transfer, Social media platforms, Virtual community, Wikis, Blogs, Construction industry, Internet, Knowledge management, Tools, Virtual reality)|
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Factors that determine the level of interaction in wikis, blogs and forums in private virtual communities is a 2013 conference paper written in English by Valerio G., Rangel I., Flores M. and published in Proceedings of the IADIS International Conference Web Based Communities and Social Media 2013, Proceedings of the IADIS International Conference Collaborative Technologies 2013.
Transformative changes due to globalization and the revolution of knowledge are forcing organizations to constantly innovate and create new capabilities in order to meet the pressure of increasing performance. One of these innovations is the creation of virtual communities as mechanisms to facilitate knowledge transfer, especially when companies have distributed experts around the globe. CEMEX, a multinational Mexican company from the construction sector, deployed a the IBM Connections social media platform that internally is called SHIFT. With the general objective of identifying the factors that determine the level of interaction throughout Wikis, Blogs and Forums, a mixed nature research was performed. Relating the qualitative section of the research, 990 activities were observed and analyzed inside the platform. Different uses given to each of the tools were identified as well as the potential factors that could affect the interaction. Also, the quantitative statistical analysis determined which of these factors had the greatest impact on the interaction. Overall, the results showed that each tool has different determinant factors that impact the interaction level.
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