CMU logo
Expand Menu
Close Menu

THESIS PROPOSAL: Haiyi Zhu

When
-

Where
GHC 6501

Description
Committee: Robert Kraut (Co-Chair) (HCI & Tepper, CMU) Aniket Kittur (Co-Chair) (HCI, CMU) Jason Hong (HCI, CMU) Yuqing (Ching) Ren (Information and Decision Sciences, University of Minnesota) Yochai Benkler (Law, Harvard University) Document: http://www.cs.cmu.edu/~haiyiz/papers/Haiyi_Zhu_Thesis_Proposal.pdf Abstract: Peer production projects have successfully aggregated the efforts of millions of volunteers to produce complex and innovative artifacts, such as GNU/Linux and Wikipedia. The goal of my thesis is to probe these systems and identify the necessary dynamics, structures, and conditions that enhance or prevent the success of peer production projects. Particularly, my thesis contains two parts. In the first part, I examine one challenge facing peer production projects: how to manage contributors with differing interests, experiences, and commitments to achieve the desired, collective outcome. I suggest a shared leadership framework to explain leadership in peer production. According to the framework, members mutually influence each other by rewarding, regulating, directing and socializing each other. In my proposed work, I suggest that shared leadership can promote coherent and shared values in peer production projects. I propose an agent-based model to simulate how shared leadership facilitates value convergence and plan to conduct empirical analysis to test the effects. The second part of my thesis investigates innovation in peer production projects. Innovation is essential for handling opportunities and threats, and affects the continued success of the project. In my proposal, I seek to answer the following questions: How is innovation generated, implemented and diffused in peer production projects? How is that process different from conventional organizations? What factors influence successful innovation in peer production? In my proposal, I suggest three stages of innovation in peer production: distributed innovation generation, focused innovation implementation, and networked innovation diffusion. I further discuss factors that could affect the success of different innovation stages. I plan to conduct qualitative analysis to create a comprehensive list of factors relevant to the innovation process, and quantitative analysis to verify them.