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Much of this research is conducted using individual-level behavioral data obtained through partnering with online music communities.

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In the online dating domain, Professor Ramaprasad is examining the role that technology-enabled features, such as anonymous browsing, have on matching outcomes. Management Restricted to U2 and U3 students. More recently, Professor Ramaprasad has started to look at the role of emotions in motivating individuals to pay for music; a critical challenge in the music industry today.

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In the domain of music, Professor Ramaprasad examines the relationship between social media-enabled interactions and music consumption. Discusses economic, strategic and organizational issues of these models.

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Here, she has worked with her colleagues to examine the role of social media in knowledge co-creation as well as to identify the purposes and strategies for social media use in health care organizations.

Professor Ramaprasad joined the Faculty of Management in fall Drawing from her interest in examining social media, Professor Ramaprasad has started to extend this research to the domain of health care. Discusses the role of the information systems in enabling new digital business models within and across organizations.

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Winter Summer Information Systems: Focuses on platforms and models of the sharing economy in different industries as well as new forms of business activities enabled by technologies. She also examines motivations for contributing to and drivers of engagement in online music communities.

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This research is currently being extended to examine other features of Sirsa dating that are unique to the online environment.

Professor Ramaprasad has also served on a variety of other conference program committees as associate editor, session chair, discussant and reviewer. She holds a B.

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This research is conducted in conjunction with a large North American online dating site, who worked with her and her co-authors to design a randomized field experiment, a design that allows them to understand the true causal relationship between the feature and the outcome.

She has presented her work at a variety of IS conferences and to industry audiences.

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