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- W4280491443 endingPage "121747" @default.
- W4280491443 startingPage "121747" @default.
- W4280491443 abstract "• Megaprojects provide potential opportunities for technological capability expansion. • There is more than one path leading to high expansion performance for participants. • The antecedent conditions show relationships of complementarity and substitutability. Megaprojects are considered to be platforms providing participants with potential opportunities for technological innovation and capability development, but it is unclear which participants can benefit more from them and how. Taking the expansion performance in technological capability as the specific objective, this paper seeks to investigate what combination of antecedent conditions can enable participants in megaprojects to achieve high performance. Applying fuzzy-set Qualitative Comparative Analysis (fsQCA) to the sample of main participating companies in the Hong Kong–Zhuhai–Macao Bridge project, we find that megaprojects do not automatically lead to a significant expansion in technological capability of participants, and no single condition is sufficient in isolation or absolutely necessary for high performance. We uncover three pathways to high expansion performance, among which the conditions show relationships of complementarity and substitutability. This study enhances the theoretical understanding of the process of megaprojects promoting participants’ growth, and offers new insights into the complex causality of performance differences in capability development." @default.
- W4280491443 created "2022-05-22" @default.
- W4280491443 creator A5020618879 @default.
- W4280491443 creator A5028283138 @default.
- W4280491443 creator A5075454987 @default.
- W4280491443 creator A5087807401 @default.
- W4280491443 date "2022-08-01" @default.
- W4280491443 modified "2023-10-08" @default.
- W4280491443 title "Explaining the expansion performance in technological capability of participants in megaprojects: A configurational approach" @default.
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- W4280491443 doi "https://doi.org/10.1016/j.techfore.2022.121747" @default.
- W4280491443 hasPublicationYear "2022" @default.