Supplementary Material of "Why is Regularization Underused? An Empirical Study on Trust and Adoption of Statistical Methods"

We investigate this implementation gap in a large-scale empirical study of trust in, and acceptance of, regularization techniques, based on N = 606 data analysts. Drawing on measurement frameworks from technology acceptance research, we survey practitioners and embed a randomized experiment to test whether written methodological recommendations increase trust or intended use. Instead, adoption intentions are strongly associated with analysts' perceptions of ease of implementation and practical benefit, such as improved bias control or interpretability.

Perceived social norms also emerge as a central driver. These results indicate that uptake of statistical methodology depends less on formal recommendations than on usability, perceived utility, and community practice.