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    Towards Better Management of Open Source Software Communities: Feedback Triage and Managerial Response

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    Name:
    azu_etd_21314_sip1_m.pdf
    Embargo:
    2026-05-13
    Size:
    1.855Mb
    Format:
    PDF
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    Author
    Wang, Zisu
    Issue Date
    2024
    Keywords
    econometrics
    feedback triage
    GitHub
    machine learning
    managerial response
    open source software
    Advisor
    Ge, Yong
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Embargo
    Release after 05/13/2026
    Abstract
    Over the last three decades, open source software (OSS) has experienced long-lasting growth in its popularity among developers and applications at different management information systems. A fundamental difference between the development of OSS and traditional software is that OSS requires and benefits from voluntary participation and contributions from OSS communities. Despite the importance of OSS communities, there remains limited knowledge regarding how to manage the ever-growing OSS communities, especially the increasing amount of feedback from OSS users. To address this limitation, the first essay combines contextual bandit and survival analysis methods to develop a novel tool that automatically assigns users’ feedback from OSS communities to the most appropriate developers. Evaluated on a real-world dataset of OSS projects and their feedback, I show that our tool can efficiently identify developers who can effectively resolve the assigned issue. Despite the improvement in the efficiency and effectiveness of feedback resolution, little do we know how addressing user feedback affects the performance of OSS projects. In the second essay, I fill this knowledge gap by examining the causal effects of feedback response and resolution on the popularity and code reuse of OSS projects. Leveraging recent developments in econometrics, I show that responding to and resolving user feedback can significantly boost OSS projects’ performance. I also evaluate different strategies in feedback response and resolution. Results indicate that addressing user feedback generally leads to more popularity and code reuse when responses and resolutions are provided in a timelier and more intensive manner, and when OSS projects prioritize bug reports and feature enhancement requests over general questions. Overall, this dissertation examines how and why OSS projects should respond to and resolve community feedback and contributes to the knowledge and tools towards better management of OSS communities.
    Type
    Electronic Dissertation
    text
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Management Information Systems
    Degree Grantor
    University of Arizona
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