2022
DOI: 10.1504/ijtm.2022.123740
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Impact of partner heterogeneity on innovation performance through interaction behaviour in Chinese complex product R&D industries

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Cited by 4 publications
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“…The academic community has not yet reached a consensus on the conceptual definition and dimensional division of the interaction behavior of industry–university–research subjects. More research is conducted based on the interaction process, and it is believed that the interaction behavior is mainly expressed through the interaction process, such as through trust, communication, conflict, cohesion, coordination, and learning in the interaction process ( Tison and Poirier, 2021 ; Yang et al, 2022 ). One of the more representative definitions is Marks’ definition.…”
Section: Theory and Hypothesesmentioning
confidence: 99%
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“…The academic community has not yet reached a consensus on the conceptual definition and dimensional division of the interaction behavior of industry–university–research subjects. More research is conducted based on the interaction process, and it is believed that the interaction behavior is mainly expressed through the interaction process, such as through trust, communication, conflict, cohesion, coordination, and learning in the interaction process ( Tison and Poirier, 2021 ; Yang et al, 2022 ). One of the more representative definitions is Marks’ definition.…”
Section: Theory and Hypothesesmentioning
confidence: 99%
“…Secondly, focusing on the geographical location of industry–university–research subjects, it is shown that the objective geographical environment, including factors such as geographical proximity, geographical distance, and geographical concentration of industry–university–research subjects, affects the innovation performance of industry–university–research ( Wang and Luan, 2019 ; Zhang and Shen, 2019 ; Zhang and Chen, 2022 ). Thirdly, focusing on the characteristics of the industry–university–research cooperative subjects themselves, it is indicated that the resource environment, including diversity, heterogeneity, matching, and complementarity of industry–university–research subjects, affects the innovation performance of industry–university–research ( Li and Zhu, 2019 ; Zhang et al, 2021 ; Yang et al, 2022 ). Fourth, focusing on the external environment of industry–university–research, it is shown how factors such as the business environment, institutional development stage, market competition, financing environment, and government subsidies affect the innovation performance of industry–university–research ( Zhang et al, 2019 , 2021 , 2022 ; Song et al, 2022 ).…”
Section: Introductionmentioning
confidence: 99%
“…An increasing number of studies indicate that R&D networks are closely related to innovation (Arroyabe et al, 2015;Gilsing et al, 2008;Mazzola et al, 2018). Especially in the complex product systems (Cops) with technology-intensive activities, R&D networks are considered as a crucial channel for firms to obtain complementary resources and knowledge from partners (Guo et al, 2021;Jin et al, 2022;Yang et al, 2022). It has been argued that a firm's position in the R&D network can affect the speed and ease of accessing these resources.…”
Section: Introductionmentioning
confidence: 99%
“…Cops innovation is a process that is filled with high costs and risks. When building collaborative relationships, Cops firms often choose more reliable and stable firms (Guo et al, 2021;Yang et al, 2022). In China, guanxi can deepen understanding and establish trust (Lee and Dawes, 2005).…”
Section: Introductionmentioning
confidence: 99%
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