Abstract
Nonprofit organizations and the public sector have increasingly adopted data science techniques and analytics tools to harness the potential of data-driven decision-making. This systematic literature review aims to explore the key topics and trends in this research area. Our study analyzed 4,478 relevant articles published between 2019 and 2023 using VOSviewer. Trend and keyword occurrence analyses reveal that the rise in data-driven decision-making, particularly in managing the COVID-19 pandemic, led to a surge in publications from 2019 to 2021. However, the number of publications subsequently declined from 2021 to 2023. The keyword co-occurrence analysis identifies six major clusters centered around ‘data science’, ‘decision-making’, ‘nonprofit organizations’, ‘artificial intelligence’, ‘covid’, and ‘performance’. Furthermore, the authorship analysis highlights a list of influential scholars who have contributed to the field.
Recommended Citation
Sundaramurthy, Subashree; Huang, Haiyan; and Umapathy, Karthikeyan, "A SYSTEMATIC LITERATURE REVIEW OF THE APPLICATIONS OF DATA SCIENCE AND DATA ANALYTICS IN NONPROFIT AND PUBLIC SECTORS" (2025). SAIS 2025 Proceedings. 35.
https://aisel.aisnet.org/sais2025/35