Correction: From Source to Target: Leveraging Transfer Learning for Predictive Process Monitoring in Organizations (Business & Information Systems Engineering, (2025), 10.1007/s12599-025-00969-9)

Weinzierl S, Zilker S, Ließmann A, Käppel M, Wang W, Matzner M (2026)

Publication Type: Journal article, Erratum

Publication year: 2026

Journal

Business & Information Systems Engineering Springer Verlag (Germany)

Abstract

In the original manuscript, the following acknowledgements were missing: Martin Matzner acknowledges funding from the Bavarian State Ministry of Economic Affairs, Regional Development and Energy (StMWi) on “PräMi” (Grant DIK-2307-0002// DIK0533/01) and the German Research Foundation (DFG) on “CoPPA” (Grant 456415646). Furthermore, the authors want to thank Matthias Stierle for his contribution to the initial discussions on the general idea of this research project and Florian Gatzlaff for his support during the project’s early stages. In Table 10, the upper line was wrong. It should be between the headline and the second line. Prediction performance of our TL-based PPM technique with the proposed activity encoding created with different pre-trained embedding models for the inter-organizational use case (average and standard deviation over five runs) Embedding model Precision Recall F1-score MCC AUCROC Train and test on LS 0.735 (±.003) 0.694 (±.003) 0.708 (±.002) 0.293 (±.007) 0.730 (±.005) Train and test on LT 0.769 (±.012) 0.769 (±.037) 0.766 (±.024) 0.330 (±.034) 0.775 (±.018) Train on LS, test on LT 0.739 (±.020) 0.755 (±.050) 0.724 (±.021) 0.206 (±.029) 0.711 (±.020) Train and test on LS 0.738 (±.003) 0.693 (±.009) 0.708 (±.006) 0.300 (±.005) 0.733 (±.003) Train and test on LT 0.756 (±.025) 0.745 (±.062) 0.747 (±.047) 0.294 (±.074) 0.748 (±.037) Train on LS, test on LT 0.723 (±.021) 0.669 (±.054) 0.685 (±.040) 0.193 (±.052) 0.689 (±.043) Train and test on LS 0.734 (±.005) 0.701 (±.010) 0.713 (±.006) 0.294 (±.008) 0.732 (±.004) Train and test on LT 0.769 (±.005) 0.774 (±.014) 0.770 (±.009) 0.333 (±.012) 0.784 (±.005) Train on LS, test on LT 0.735 (±.030) 0.718 (±.070) 0.713 (±.041) 0.215 (±.073) 0.689 (±.021) Train and test on LS 0.738 (±.002) 0.691 (±.010) 0.707 (±.008) 0.300 (±.003) 0.735 (±.002) Train and test on LT 0.676 (±.042) 0.735 (±.045) 0.692 (±.013) 0.084 (±.050) 0.638 (±.007) Train on LS, test on LT 0.760 (±.057) 0.484 (±.138) 0.483 (±.142) 0.173 (±.049) 0.646 (±.019) Train and test on LS 0.735 (±.004) 0.700 (±.011) 0.713 (±.008) 0.296 (±.009) 0.736 (±.006) Train and test on LT 0.715 (±.062) 0.766 (±.038) 0.727 (±.052) 0.174 (±.174) 0.690 (±.064) Train on LS, test on LT 0.766 (±.043) 0.618 (±.173) 0.619 (±.167) 0.245 (±.073) 0.692 (±.042) Train and test on LS 0.736 (±.003) 0.694 (±.009) 0.708 (±.007) 0.296 (±.006) 0.732 (±.006) Train and test on LT 0.772 (±.007) 0.781 (±.016) 0.775 (±.009) 0.342 (±.016) 0.782 (±.005) Train on LS, test on LT 0.721 (±.014) 0.668 (±.089) 0.681 (±.069) 0.188 (±.051) 0.681 (±.026) Train and test on LS 0.736 (±.003) 0.691 (±.003) 0.706 (±.002) 0.294 (±.006) 0.728 (±.005) Train and test on LT 0.766 (±.012) 0.775 (±.019) 0.769 (±.014) 0.324 (±.031) 0.762 (±.022) Train on LS, test on LT 0.707 (±.009) 0.550 (±.040) 0.585 (±.039) 0.130 (±.017) 0.655 (±.014) Note. Best results for training on LS and testing on LT are marked in bold The captions for Fig. 3 and Fig. 4 were wrong. They should be as follows: Fig. 3 Intra- and inter-organizational TL for PPM Fig. 4 Overview of our TL-based PPM technique (TL-specific and general resources that need to be transferred from the source context S to the target context T are colored blue and gray, respectively) In Sect. 2.2 (and throughout the paper), “a RNN” was wrong. It should be “an RNN”. In the last paragraph in Sect. 5.1 (p. 15), one part of the penultimate sentence was missing. The sentence should be as follows: As ML metrics, commonly used in outcome-oriented PPM are calculated, such as the area under the receiver operating characteristic curve (AUCROC) and the F1-score (Teinemaa et al. 2019). The original article has been corrected.

Authors with CRIS profile

Sven Weinzierl Lehrstuhl für Digital Industrial Service Systems Sandra Zilker Lehrstuhl für Digital Industrial Service Systems Annina Ließmann Lehrstuhl für Digital Industrial Service Systems Martin Käppel Lehrstuhl für Digital Industrial Service Systems Weixin Wang Lehrstuhl für Digital Industrial Service Systems Martin Matzner Lehrstuhl für Digital Industrial Service Systems

How to cite

APA:

Weinzierl, S., Zilker, S., Ließmann, A., Käppel, M., Wang, W., & Matzner, M. (2026). Correction: From Source to Target: Leveraging Transfer Learning for Predictive Process Monitoring in Organizations (Business & Information Systems Engineering, (2025), 10.1007/s12599-025-00969-9). Business & Information Systems Engineering. https://doi.org/10.1007/s12599-026-00988-0

MLA:

Weinzierl, Sven, et al. "Correction: From Source to Target: Leveraging Transfer Learning for Predictive Process Monitoring in Organizations (Business & Information Systems Engineering, (2025), 10.1007/s12599-025-00969-9)." Business & Information Systems Engineering (2026).

BibTeX: Download