When does knowledge acquisition in R&amp;D alliances increase new product development? The moderating roles of technological relatedness and product-market competition

Frankort, Hans T. W.

doi:10.1016/j.respol.2015.10.007

Cited by 98 publications

(100 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Second, we conceptually argue and empirically verify that industrial R&D collaboration and innovation performance has an inverse U-shaped relationship. This result echoes an ongoing debate regarding the value creation of R&D alliances (Frankort, 2016 ;Sampson, 2007 ). Specifically, our finding deepens the discussion from the catch-up perspective of latecomer firms in an emerging economy.…”

Section: Discussion and Conclusion Findingssupporting

confidence: 82%

Catch‐up through Collaborative Innovation: Evidence from China

Liu

Ying

2016

Thunderbird Intl Bus Rev

View full text Add to dashboard Cite

Collaborative innovation has received the attention of management scholars for decades. The primary focus of our research is to explore the mechanisms that drive innovation catch‐up of latecomers in an emerging economy through research and development collaborations (i.e., academic and industrial collaborations). Using a sample of 1,066 firms in a high‐tech cluster in China, we find that collaborative innovation strategy has an inverse U–shaped effect on a firm's innovation performance. In addition, the relationship between collaborative innovation strategy and innovation performance is positively moderated by absorptive capacity © 2016 Wiley Periodicals, Inc.

show abstract

Section: Discussion and Conclusion Findingssupporting

confidence: 82%

Catch‐up through Collaborative Innovation: Evidence from China

Liu

Ying

2016

Thunderbird Intl Bus Rev

View full text Add to dashboard Cite

show abstract

“…Through knowledge acquisition, enterprises absorb external knowledge and integrate it with internal knowledge, so that its knowledge capital can increase. Knowledge acquisition capabilities also help companies respond to changes in competitive markets and make strategic adjustments quickly [39]. The stronger the knowledge acquisition capability, the more easily enterprises can integrate external and internal knowledge resources.…”

Section: Knowledge Acquisitionmentioning

confidence: 99%

“…In the knowledge recognition process, companies assess the quality of existing ideas, ignoring those that have no innovative value for the enterprise and focusing on identifying high-quality innovative ideas. In the knowledge acquisition process, enterprises evaluate the feasibility of implementing existing ideas and obtain knowledge resources from external users to transform them into internal knowledge resources [39]. Therefore, the knowledge recognition and knowledge acquisition abilities have a positive impact on the idea adoption and conversion rates in the user behavior subsystem.…”

Section: Causal Relationship Of Knowledge Management Subsystemmentioning

confidence: 99%

“…By investing a large amount of R&D and management, enterprises can ensure normal operation of the technical and organizational mechanisms, improve the application ability of knowledge resources, and ultimately help transform knowledge resources into innovation performance, which is reflected by the number of patents [39]. The innovation performance of an enterprise has a positive impact on its organizational and technical mechanisms by influencing financial resources [58].…”

Section: Causal Relationship Of Governance Mechanism Subsystemmentioning

confidence: 99%

See 1 more Smart Citation

Impact of Open Innovation Communities on Enterprise Innovation Performance: A System Dynamics Perspective

Gong

2019

Sustainability

View full text Add to dashboard Cite

Open innovation communities (OICs) can help enterprises make full use of external knowledge resources from users, but problems such as low user participation and low conversion rate of creative ideas impact the efficiency of OICs. Most studies on this topic employ qualitative or empirical methods from a static perspective, but ignore the effect of interaction between enterprises and users as well as the cumulative effect of time. A discussion on the dynamic evolution process of open innovation is lacking. Based on a review of the literature on OICs, innovation performance, and system dynamics, this study proposes a conceptual model of innovation performance impact, which comprises the knowledge management, governance mechanism, and user behavior subsystems. Xiaomi’s OIC in China was selected as the research object, and relevant data were collected through a web spider. According to the system dynamics modeling method, a causal relationship analysis was carried out on the three aforementioned interrelated subsystems. Then, a stock flow chart with 32 variables was constructed to determine the initial values and calculation equations for each variable. Finally, the model was constructed and verified using Vensim PLE software. The simulation results were as follows. (1) The number of product releases in the Xiaomi OIC was positively correlated with the number of posts, comments, and views. Compared with user interaction behavior (i.e., commenting and viewing), the impact of user innovation behavior (i.e., posting) on enterprise innovation performance (i.e., number of patents) is clearer. Specifically, regarding interaction behavior, the impact of the users’ commenting behavior on innovation performance (i.e., number of product releases) was relatively clearer than that of their viewing behavior. (2) Governance mechanism (i.e., R&D investment and management expense), which comprises technical and organizational mechanisms, positively affected the innovation performance of enterprises. Compared with the organizational mechanism (i.e., management expense), the impact of the technical mechanism (i.e., R&D investment) on the innovation performance was clearer. (3) Governance mechanism helped to increase the number of users in the OIC, and, in turn, affected the user innovation and interaction behavior. (4) The technical mechanism positively affected knowledge application capability, which, in turn, had a positive impact on the innovation performance of enterprises. Based on these findings, management strategies are proposed for the establishment and development of OICs.

show abstract

“…Several empirical contributions demonstrate that these seemingly contradictory findings stem from a complex and nuanced causal relationship, moderated by a number of contextual variables: markets for technology, sectoral characteristics, market competition and absorptive capacity (Grimpe and Sofka, 2016;Frankort, 2016;Tsai, 2009;Wu, 2012).…”

Section: _________________________mentioning

confidence: 99%

Knowledge transfer in interorganizational partnerships: what do we know?

Milagres

Burcharth

2018

BPMJ

View full text Add to dashboard Cite

This paper reviews the literature on knowledge transfer in inter-organizational partnerships. Our aim is to assess the advances in this field by addressing the questions: What factors impact knowledge transfer in interorganizational partnerships? How do these factors interact with each other? We carried out a systematic literature review in ten top journals between 2000-2017. We identified three overarching themes, which were organized according to fourteen research questions. The first theme discusses knowledge in itself and elaborates on aspects of its attributes. The second theme presents the factors that influence interorganizational knowledge transfer at the macroeconomic, interorganizational, organizational and individual levels. The third theme focuses on the consequences, namely effectiveness and organizational performance. In addition to providing a synthetic overview, we propose a novel theoretical framework that links antecedents, process and outcomes. Our analysis also identifies aspects that are either less well researched or contested. We conclude by suggesting directions for future research, methodological improvements and guidance for practice.

show abstract

When does knowledge acquisition in R&D alliances increase new product development? The moderating roles of technological relatedness and product-market competition

Abstract: When does knowledge acquisition in R&D alliances increase new product development? The moderating roles of technological relatedness and productmarket competition. Research Policy, 45(1), pp. 291-302.

Cited by 98 publications

References 71 publications

Catch‐up through Collaborative Innovation: Evidence from China

Catch‐up through Collaborative Innovation: Evidence from China

Impact of Open Innovation Communities on Enterprise Innovation Performance: A System Dynamics Perspective

Knowledge transfer in interorganizational partnerships: what do we know?

Contact Info

Product

Resources

About