Evaluating the Impact of Governance and Funding Models on Open Source Software Success: A Quantitative and Qualitative Analysis

Open Source Software (OSS) projects, offering public accessibility and modifiability, have burgeoned with the advent of blockchain and other emerging technologies. Despite this growth, understanding the factors influencing their success remains complex. This study seeks to determine whether OSS projects with different funding and governance models exhibit varying GitHub development activities. The methodology involved a two-part approach. First, a broad quantitative analysis of OSS activity levels was conducted using data from 660 OSS projects hosted on GitHub. This analysis, performed with Google Cloud’s BigQuery API, included repository metadata such as repository names, dates, actor IDs, actor logins, and 28 distinct events, including total activities, distinct commits, and forks, covering the period from 2013 to 2023. Second, a qualitative deep dive into project backgrounds was performed to assess the influence of governance and funding models on project success. Preliminary results indicate varied activity levels across different project types, suggesting that specific governance and funding models may significantly impact OSS success, although the data is not yet fully realized. The study aims to provide a nuanced understanding of these correlations, ultimately guiding future developers and stakeholders in optimizing project design and funding approaches to enhance OSS sustainability and growth. This abstract is part of a collection in which the overarching large project under Dr. Jiasun Li was subdivided into discrete critical tasks that were carried out by multiple individuals or smaller teams. Abstracts in this collection read similarly given the shared project goals, but represent distinct tasks completed by the abstract authors towards finalizing the described analysis.

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Publication Details

Journal
George Mason University
Published
2024-10-11
DOI
https://doi.org/10.13021/jssr2024.4255
Primary Topic
Open Source Software Innovations
Type
article
Field-Weighted Citation Impact
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article

Evaluating the Impact of Governance and Funding Models on Open Source Software Success: A Quantitative and Qualitative Analysis

George Mason University
Open Source Software Innovations
article

Evaluating the Impact of Governance and Funding Models on Open Source Software Success: A Quantitative and Qualitative Analysis

article en

Abstract

Open Source Software (OSS) projects, offering public accessibility and modifiability, have burgeoned with the advent of blockchain and other emerging technologies. Despite this growth, understanding the factors influencing their success remains complex. This study seeks to determine whether OSS projects with different funding and governance models exhibit varying GitHub development activities. The methodology involved a two-part approach. First, a broad quantitative analysis of OSS activity levels was conducted using data from 660 OSS projects hosted on GitHub. This analysis, performed with Google Cloud’s BigQuery API, included repository metadata such as repository names, dates, actor IDs, actor logins, and 28 distinct events, including total activities, distinct commits, and forks, covering the period from 2013 to 2023. Second, a qualitative deep dive into project backgrounds was performed to assess the influence of governance and funding models on project success. Preliminary results indicate varied activity levels across different project types, suggesting that specific governance and funding models may significantly impact OSS success, although the data is not yet fully realized. The study aims to provide a nuanced understanding of these correlations, ultimately guiding future developers and stakeholders in optimizing project design and funding approaches to enhance OSS sustainability and growth. This abstract is part of a collection in which the overarching large project under Dr. Jiasun Li was subdivided into discrete critical tasks that were carried out by multiple individuals or smaller teams. Abstracts in this collection read similarly given the shared project goals, but represent distinct tasks completed by the abstract authors towards finalizing the described analysis.

George Mason University
George Mason University (US)
Openalex Percentile: Top 37%
Open Source Software Innovations
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