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cc-by-nc-nd (c) Elsevier, 2017
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/107742

Do we really know the predictors of competence-creating R&D subsidiaries? Uncovering the mediation of dual network embeddedness

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Many changes have been recorded in the R&D role played by the foreign subsidiaries of multinational corporations (MNCs), to the extent that today many are recognised as key players in the development of firm innovation-related competences. Given this trend, we examine the predictors of a subsidiary's R&D role as a competence-creating contributor to the MNC's long-term success. Traditionally, the predictors of subsidiaries' R&D roles have been sought in the specific features of the internal corporate and external host-country environments. However, we find that favourable corporate- and country-level conditions may not necessarily lead to the enhancement of a subsidiary's R&D role unless dual embeddedness - that is, the subsidiary's embeddedness in the knowledge networks of the MNC (internal embeddedness) and in those of the host country (external embeddedness) - is well established. The main contribution of this paper is the development of a multiple mediation model that disentangles the way in which corporate and host-country environments interrelate with a subsidiary's dual embeddedness in the expected configuration of its competence-creating R&D role. In developing the model, we use the PLS-SEM method to estimate the relationship between these elements and, eventually, to forecast the subsidiary's competence-creating R&D role. The proposed model should help managers shape the fate of the subsidiary's R&D strategic role.

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ACHCAOUCAOU IALLOUCHEN, Fariza, MIRAVITLLES MATAMOROS, Paloma and LEÓN-DARDER, Fidel. Do we really know the predictors of competence-creating R&D subsidiaries? Uncovering the mediation of dual network embeddedness. Technological Forecasting and Social Change. 2017. Vol. 116, num. March, pags. 181-195. ISSN 0040-1625. [consulted: 14 of August of 2026]. Available at: https://hdl.handle.net/2445/107742

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