Abstract
Large-scale organizations have used social computing platforms for various purposes. This research focuses on how hospitals utilize these platforms to attract potential customers (which represents the " extensivity" of a social computing platform) and generate interests in specific topics (which represents the " intensivity" of a platform). Specifically, we examine the effects of size of a hospital (or " size" ) and the time that the social computing platform has been in existence (or " time" ) on extensivity and intensivity. Our findings show that time is a significant variable on both dimensions; whereas size affects intensivity under certain conditions. We discuss the implications of these findings, and set the stage for future research.
Original language | English (US) |
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Pages (from-to) | 253-261 |
Number of pages | 9 |
Journal | Journal of Computational Science |
Volume | 2 |
Issue number | 3 |
DOIs | |
State | Published - Aug 2011 |
Keywords
- Adoption effectiveness
- Data envelopment analysis
- Health information technology
- Information economics
- Social computing
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science
- Modeling and Simulation