Paper Number
ICIS2025-1196
Paper Type
Short
Abstract
Theoretical saturation, commonly defined as the point at which no new theoretical insights emerge from additional data, is a central methodological component and quality indicator of grounded theory. However, establishing saturation is challenging and, as previous studies have noted, often done superficially, thereby threatening research transparency and quality. Thus, in this paper, theoretical saturation is reconceptualized as a probabilistic rather than a definite statement. After explaining theoretical saturation and reviewing existing approaches for addressing it, I present a general two-step method for estimating theoretical saturation and fostering reflection about the research and sampling process. In the first step, researchers generate data on the collection and analysis process, e.g., based on manual documentation or information from data analysis tools. In the second step, this data is analyzed, e.g., visually or statistically, to estimate theoretical saturation. I conclude by discussing implications, limitations, and future research opportunities of the proposed approach.
Recommended Citation
Brechtelsbauer, Bastian, "Towards an Approach for Estimating Theoretical Saturation" (2025). ICIS 2025 Proceedings. 2.
https://aisel.aisnet.org/icis2025/is_researchmethods/is_researchmethods/2
Towards an Approach for Estimating Theoretical Saturation
Theoretical saturation, commonly defined as the point at which no new theoretical insights emerge from additional data, is a central methodological component and quality indicator of grounded theory. However, establishing saturation is challenging and, as previous studies have noted, often done superficially, thereby threatening research transparency and quality. Thus, in this paper, theoretical saturation is reconceptualized as a probabilistic rather than a definite statement. After explaining theoretical saturation and reviewing existing approaches for addressing it, I present a general two-step method for estimating theoretical saturation and fostering reflection about the research and sampling process. In the first step, researchers generate data on the collection and analysis process, e.g., based on manual documentation or information from data analysis tools. In the second step, this data is analyzed, e.g., visually or statistically, to estimate theoretical saturation. I conclude by discussing implications, limitations, and future research opportunities of the proposed approach.
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25-Research