2023
DOI: 10.1109/tem.2021.3081143
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Does Institutional Distance Affect Transnational Knowledge Spillovers Between Countries?

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Cited by 1 publication
(7 citation statements)
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“…EMNEs usually do not compete directly in foreign markets, instead, they acquire intangible strategic assets (including knowledge, technology, brands, etc.) through overseas subsidiaries and utilize them in huge domestic markets, such as China (Ramamurti 2012;She et al 2021). Thus, when there is a large institutional distance between the home and host countries, EMNEs may use a lower proportion of PCNs in their subsidiaries because the greater participation of HCNs in overseas subsidiaries helps companies understand knowledge and organizational practices in the context of local conditions (Hyun, Oh and Paik 2015;Law et al 2009).…”
Section: The Third Goal (Managing Knowledge)mentioning
confidence: 99%
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“…EMNEs usually do not compete directly in foreign markets, instead, they acquire intangible strategic assets (including knowledge, technology, brands, etc.) through overseas subsidiaries and utilize them in huge domestic markets, such as China (Ramamurti 2012;She et al 2021). Thus, when there is a large institutional distance between the home and host countries, EMNEs may use a lower proportion of PCNs in their subsidiaries because the greater participation of HCNs in overseas subsidiaries helps companies understand knowledge and organizational practices in the context of local conditions (Hyun, Oh and Paik 2015;Law et al 2009).…”
Section: The Third Goal (Managing Knowledge)mentioning
confidence: 99%
“…Because invention patent applications represent the development of the most advanced technology and have the highest innovation and economic value, they are often used as agents of innovation performance (Filippetti, Frenz and Ietto-Gillies 2017; Zhou, Hong and Wu 2019). Patent applications can truly reflect the innovation performance of an enterprise, and they reflect lagging innovation activities; thus, this article will lag the variables by one period (She et al 2021). Since IPA is measured by quantity, we have performed a logarithmic conversion of patent data.…”
Section: Data and Samplesmentioning
confidence: 99%
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