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- W4385220602 abstract "Internationalization of corporate activities is a core aspect of research in International Business. While several theories explain internationalization decisions, the understanding of non-incremental, non-linear internationalization processes remains incomplete. In particular, a large-scale empirical analysis of these deviations from “classic” internationalization theory is missing. To this end, this study applies a machine learning model to identify a set of internationalization-process clusters. Based on the clustering, the study investigates factors that determine according to which pattern individual firms internationalize and explains how firms draw on the organizational learning process. Thereby, the study outlines that multiple theoretically distinct internationalization patterns may exist in parallel but apply to different firms. The study’s findings contribute to a more dynamic understanding of the heterogeneity of processes by which firms expand their foreign operations." @default.
- W4385220602 created "2023-07-25" @default.
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- W4385220602 date "2023-08-01" @default.
- W4385220602 modified "2023-09-27" @default.
- W4385220602 title "Understanding Internationalization Patterns" @default.
- W4385220602 doi "https://doi.org/10.5465/amproc.2023.14571abstract" @default.
- W4385220602 hasPublicationYear "2023" @default.
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