Dynamic simulation research on the effect of resource heterogeneity on knowledge transfer in R&amp;D alliances

Zhang, Hui; Zhou, Minfei; Rao, Huguang; Zhou, Dan

doi:10.1080/14778238.2020.1767521

Cited by 9 publications

(22 citation statements)

References 79 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As shown in Figure 8, ensuring that the transfer threshold is within a relatively high range can promote effective knowledge transfer, while too small a transfer threshold hinders knowledge transfer. The transfer threshold refers to the degree of knowledge senders stick to their core knowledge, so the key to increasing the transfer threshold lies in the project team (Zhang et al. , 2020).…”

Section: Discussionmentioning

confidence: 99%

“…, 2020). And others simultaneously took the amount of knowledge transferred and the receiver's knowledge stock into account (Zhang et al. , 2020).…”

Section: Methodsmentioning

confidence: 99%

“…, 2020). To maintain their competitiveness, organizations will only transfer knowledge when the transfer threshold is within a certain range, and knowledge transfer activity will stop if the threshold is exceeded (Zhang et al. , 2020).…”

Section: Methodsmentioning

confidence: 99%

“…The amount of knowledge innovation refers to the incomes of knowledge resources acquired by participants by applying innovation capabilities and the input of knowledge innovation costs (Dangelico et al. , 2010; Zhang et al. , 2020).…”

Section: Methodsmentioning

confidence: 99%

“…In the field of knowledge management, the SD method has received extensive attention from scholars, which is a technology based on feedback control theory and computer simulation (Zolfagharian et al. , 2014; Zhang et al. , 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

See 4 more Smart Citations

System dynamics approach of knowledge transfer from projects to the project-based organization

Zhou

Deng

Hwang

et al. 2022

IJMPB

View full text Add to dashboard Cite

PurposeAlthough knowledge transfer in the context of projects and project-based organizations (PBOs) has gained increasing attention from academia and industry, it is not clear how knowledge transfers from projects to their parent PBOs. This research aims to explore the main factors influencing knowledge transfer from projects to their parent PBOs, and analyze how these factors integrate the transfer process as system components using the system dynamics (SD) method.Design/methodology/approachBased on the literature review, investigation and interview, this paper adopts the event analysis to obtain the influencing factors from historical cases and establishes a conceptual model of knowledge transfer from five dimensions, which simultaneously considers the knowledge sender, knowledge receiver and the relationship between the knowledge sender and receiver, knowledge features and transfer context. Then, the relationships between variables in the qualitative model were clarified, and a quantitative model including seven feedback loops was established using the SD model. Lastly, the system simulation and sensitivity analysis of the main parameters were realized in Vensim PLE software.FindingsThe simulation analysis results show that the model can simulate the knowledge transfer process from projects to the PBO to a certain extent. This research fully demonstrates the impact of variables from five dimensions on knowledge transfer and incorporates the knowledge gap and transfer threshold in the research category. Moreover, the rationality of seven feedback loops proposed in the model was verified. And the effects of various factors on the amount of knowledge transferred and the PBO's knowledge stock were examined through sensitivity analysis. Furthermore, recommendations for developing an integrated knowledge transfer mechanism of PBOs and projects to enhance transfer effect are offered.Research limitations/implicationsThis research provides other researchers with a systematic understanding of transfer process from projects to PBOs, and insight for further research on knowledge transfer in project and organization contexts. Furthermore, this study guides researchers to focus on the causal processes that constitute knowledge transfer and explores the expected and unexpected phenomena generated over time. However, some variables involved in the transfer process are simplified, and the establishment of a more complex dynamic model needs further research and discussion.Practical implicationsBy establishing a simulation model for knowledge transfer from projects to their parent PBOs, this study helps project teams and PBOs grasp the overall picture of the transfer process. Especially, this paper provides target-oriented recommendations for project and PBO managers to implement effective knowledge transfer practices, which have certain practical values for knowledge cultivation, coordination, reuse and innovation in the organization.Originality/valueThis study contributes to knowledge management and project management literature by simulating the knowledge transfer process from projects to their parent PBOs. Additionally, this paper provides a reference for PBO and project managers to establish an integrated knowledge-transfer mechanism in the work process and comprehensively implement effective knowledge transfer practices.

show abstract

Section: Discussionmentioning

confidence: 99%

“…, 2020). And others simultaneously took the amount of knowledge transferred and the receiver's knowledge stock into account (Zhang et al. , 2020).…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 3 more Smart Citations

System dynamics approach of knowledge transfer from projects to the project-based organization

Zhou

Deng

Hwang

et al. 2022

IJMPB

View full text Add to dashboard Cite

show abstract

Digitalization of cross‐border R&D alliances: Configurational insights and cognitive digitalization biases

Bouncken

Fredrich

Sinkovics

et al. 2022

Global Strategy Journal

View full text Add to dashboard Cite

Firms implement digital technology for improving coordination and communication in cross-border R&D alliances. However, there is great ambivalence regarding how digitalization influences cross-border knowledge transfers. Our analysis clarifies some of this ambivalence by providing different configurations of absorptive capacity in cross-border R&D alliances. The fuzzy-set qualitative comparative analysis (fsQCA) reveals only low absorptive capacity achievement in most configurations of digital technology implementation. The findings indicate effects of cognitive digitalization biases, under which firms take the benefits of digital technology for granted while ignoring deep-level challenges rooted in the contextuality of international ties. However, high absorptive capacity is achievable when (1) allying with bigger and younger partners, (2) under technological similarity, and (3) coping with the associated digitalization biases. Managerial Summary: Firms are eager to grasp the potential of digital technology. Within R&D alliances, digital technology is deemed to facilitate better coordination and communication. However, advantages from

show abstract

Knowledge Workers, Innovation Linkages and Knowledge Absorption: An Interactive Mechanism Study

Wang,

Zhang

2024

J Knowl Econ

View full text Add to dashboard Cite

Dynamic simulation research on the effect of resource heterogeneity on knowledge transfer in R&D alliances

Cited by 9 publications

References 79 publications

System dynamics approach of knowledge transfer from projects to the project-based organization

System dynamics approach of knowledge transfer from projects to the project-based organization

Digitalization of cross‐border R&D alliances: Configurational insights and cognitive digitalization biases

Knowledge Workers, Innovation Linkages and Knowledge Absorption: An Interactive Mechanism Study

Contact Info

Product

Resources

About