Putnam has developed a theory of social capital to explain the effect of decreasing community participation and civic engagement on declining institutional performance. Subsequently, there has been much speculation as to whether emerging virtual communities can counteract this trend. The authors apply the findings of computer-mediated communication and virtual communities to the networks, norms, and trust of social capital and also examine the possible effects of virtual communities on the privatization of leisure time. They conclude that social capital and civic engagement will increase when virtual communities develop around physically based communities and when these virtual communities foster additional communities of interest. Through a preliminary analysis, the authors identify potential communities of interest including education, exchange of general community information, and opportunities for government and political participation. They conclude with a discussion of current trends and research needs.
Robert Putnam (1993) has developed a theory of social capital to explain the effect of decreasing community participation and civic engagement on declining institutional performance. Subsequently, there has been much speculation as to whether emerging virtual communities can counteract this trend. We apply the findings of computer-mediated communication and virtual communities to the networks, norms, and trust of social capital and also examine the possible effects of virtual communities on the privatization of leisure time. We conclude that social capital and civic engagement will increase when virtual communities develop around physically based communities and when these virtual communities foster additional communities of interest. Through a preliminary analysis, we identified potential communities of interest including education, exchange of general community information, and opportunities for government and political participation. We conclude with a discussion of current trends and research needs.
Geo-fencing has been predicted to be a multi-billion dollar market in areas such as retail, ambient intelligence, entertainment, healthcare, etc. Businesses have been adopting geo-fencing technology, and now there are several platform providers such as Google, Qualcomm, Esri, Urban Airship, and others. These tools are continuing to attract application developers; however, best practices for choosing the specific performance options within this technology is still ambiguous. For example, Esri provides a geo-trigger service that allows developers to send targeted messages to users when they enter, exit, or dwell in a geo-fenced area. This service also provides the ability to choose higher levels of accuracy or battery saving by offering different location tracking profiles. This paper investigated two geo-trigger tracking profiles (Fine and Adaptive) to assess their performance in small, outdoor, geo-fenced areas; these two profiles are the most accurate but vary in their battery-use. The results show the Adaptive tracking profile to provide 100% reliability and average accuracy of 68.53 meters in geo-fences between 20-70 meter radii. In addition, the Adaptive tracking profile saved 15.20% battery-life while the user is stationery and 9.23% while the user is moving.
The authors developed and evaluated an expert system-based training system using Information Systems Design Theory (ISDT). First, an Expert System for Training (EST) was designed and implemented, and then a version of EST without expertise features, called IST, was also created. In order to evaluate which training system (if any) delivers better training, a three-group quasi-experiment was used. Each group was trained to use Statistical Process Control (SPC). One group was trained using the EST; outcomes for this group were significantly the highest among the three. A second group was trained using the IST; outcomes were not as high as the first group but significantly higher compared with the control group. The control group was trained with traditional means. Results show that the ISDT led to a useful purposely-developed application for enhancing the training of workers who have limited education but need to know about a very specific and complex field where the availability of trainers is limited. The authors call for further research that uses this ISDT to build purposely-developed software to support training of complex tasks.
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