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November 27, 2012

Professor awarded grant for time-banking mobile app

Carroll

John Carroll, Penn State’s Edward M. Frymoyer Professor of Information Sciences and Technology, has been awarded a National Science Foundation grant to continue his development of a time banking mobile application.

Time banking is a system of favors done for others to earn credits, doctoral student Keith Han said.

“Doing things for others is the social glue that holds society together and makes us worthwhile,” Carroll (graduate) said. “People’s value for themselves increases when they do things for others.”

By taking money out of the equation, everyone and their time is treated equally, Carroll said.

“Time banking is more focused on economically deprived communities who have more time than money on their hands,” Victoria Bellotti, principal scientist and developer of PARC's Opportunity Discovery research and strategic investment targeting program, wrote in an email.

Carroll’s idea for a mobile app was to make favors more spontaneous.

Currently, time banking is web based so transactions are not synchronized in real time, Han said. But with a mobile application, people will be able to find requests closer to them.

With the time banking application, people will be able to do smaller favors, Carroll said.

“Everyone is overbooked,” Carroll said. “People relying on others strengthens the fabrics of society.”

Currently an Android time banking application is complete and will be studied over the next six months, Carroll said.

After the study period, Carroll said the partnership with TimeBanks USAhas plans to adopt the system.

“The idea is that two years from now, new people will be time banking from smart phones,” Carroll said.

The success of the application depends on the participants, Carroll said.

When the application is released, Carroll said they look forward to seeing what types of requests people post.

“Ultimately, we think this work could lead to more interesting context-aware computing solutions that truly leverage information about location and predicted schedules to assign tasks more proactively based on who can most efficiently and conveniently do them,” Bellotti wrote.

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