scholarly journals Knowledge transfer among international strategic alliance partners and its impact on innovation performance

2019 ◽  
Vol 6 (4) ◽  
pp. 203
Author(s):  
Madhavi Kapoor ◽  
Vijita S. Aggarwal
Keyword(s):  
Knowledge Transfer ◽  
Strategic Alliance ◽  
Innovation Performance ◽  
Alliance Partners

Learning and Knowledge Transfer in Strategic Alliances: A Social Exchange View

2005 ◽  
Vol 26 (3) ◽  
pp. 415-441 ◽  
Author(s):  
Senthil K. Muthusamy ◽  
Margaret A. White
Keyword(s):  
Knowledge Transfer ◽  
Social Exchange ◽  
Strategic Alliances ◽  
Social Exchange Theory ◽  
Strategic Alliance ◽  
Mutual Influence ◽  
Empirical Examination ◽  
Social Exchanges ◽  
Exchange Processes ◽  
Alliance Partners

Although social interactions and exchanges between partners are emphasized as imperative for alliance success, comprehensive examination of how social exchanges facilitate learning and knowledge transfer in strategic alliances is lacking. Drawing on social exchange theory, we examined the effects of social exchange processes between alliance partners on the extent of learning and knowledge transfer in a strategic alliance. An empirical examination of data collected from alliance managers of 144 strategic alliances revealed that social exchanges such as reciprocal commitment, trust, and mutual influence between partners are positively related to learning and knowledge transfer in strategic alliances.

Comprehending a knowledge framework as a source of dynamic capabilities in IJVs through PLS-SEM

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Madhavi Kapoor ◽  
Vijita Aggarwal
Keyword(s):  
Knowledge Transfer ◽  
Absorptive Capacity ◽  
Structural Equation ◽  
Dynamic Capabilities ◽  
Global Market ◽  
Innovation Performance ◽  
International Joint Ventures ◽  
Mediation Effect ◽  
Equation Modeling ◽  
Content Type

Purpose This study aims to investigate the relationship among knowledge transfer enablers, knowledge transfer process, absorptive capacity and innovation performance in the context of Indian international joint ventures (IJVs). These elements are woven with the thread of dynamic capabilities theory (DCT) into an integrated framework. Design/methodology/approach Data analysis is conducted on a quantitative survey of 196 IJVs with partial least squares structural equation modeling as the statistical technique. Findings Co-learning strategy, collaborative trust culture, information technology-based resources and systems and organizational structural design are found to be significant knowledge transfer enablers. Absorptive capacity has a complementary partial mediation effect on the positive relationship between knowledge transfer and innovation performance of Indian IJVs. Research limitations/implications The study has pioneered in explicating the criticality of IJV’s internal dynamics to cope with the global market dynamism in a much needed Indian context. Practitioners must focus on building dynamic capabilities in IJVs to make them sustainably competitive, as proposed and evaluated by this study. Further, IJV managers need to strategize their resources, routines and structure dynamically to foster knowledge transfer and innovativeness. Originality/value The comprehensive model on DCT offered by this study is rare to match in literature with a completely new context, which is the need of the hour.

scholarly journals Knowledge transfer and innovation performance of small and medium enterprises (SMEs): An informal economy analysis

Heliyon ◽  
2020 ◽  
Vol 6 (8) ◽  
pp. e04740
Author(s):  
Ayodotun Stephen Ibidunni ◽  
Aanuoluwa Ilerioluwa Kolawole ◽  
Maxwell Ayodele Olokundun ◽  
Mercy E. Ogbari
Keyword(s):  
Knowledge Transfer ◽  
Informal Economy ◽  
Small And Medium Enterprises ◽  
Innovation Performance ◽  
Medium Enterprises ◽  
Economy Analysis

scholarly journals Influence of Venture Capital and Knowledge Transfer on Innovation Performance in the Big Data Environment

2019 ◽  
Vol 12 (4) ◽  
pp. 188 ◽  
Author(s):  
Chuanrong Wu ◽  
Xiaoming Yang ◽  
Veronika Lee ◽  
Mark E. McMurtrey
Keyword(s):  
Big Data ◽  
Knowledge Transfer ◽  
Venture Capital ◽  
New Product ◽  
User Preferences ◽  
Innovation Performance ◽  
Venture Capitalists ◽  
New Knowledge ◽  
Data Environment ◽  
Start Ups

Technological innovation requires large investments. Venture capital (VC) is a prominent financial source for innovative start-ups. A venture capitalist will inevitably transfer knowledge to facilitate the innovation of a firm while monitoring and advising its portfolio companies. Only when a firm has its own valuable new knowledge and high growth potential would venture capitalists select it. At the same time, big data knowledge, such as customer demands and user preferences, is also important for the new product development of a firm in the big data environment. Therefore, private knowledge transferred from venture capitalists, new knowledge developed independently by a firm itself, and big data knowledge are the three main types of knowledge for venture-backed firms in the big data environment. To find the influences of VC and knowledge transfer on the innovative performance of venture-backed firms, a model of maximizing the present value of the expected profit of new product innovation performance of a venture-backed firm in the big data environment is presented. The model can help venture capitalists to determine the scale of investment and the optimal exit time and predict the internal rate of return (IRR). This model can also help innovative start-ups to illustrate the value and prospects of a project to attract investment in their business prospectus.

Multigroup analysis of higher-order model of knowledge variables in the context of global ventures through PLS-SEM

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vijita S. Aggarwal ◽  
Madhavi Kapoor
Keyword(s):  
Knowledge Transfer ◽  
Dynamic Capabilities ◽  
Group Analysis ◽  
Test Group ◽  
Organizational Factors ◽  
Innovation Performance ◽  
Primary Data ◽  
Future Research ◽  
Content Type ◽  
Knowledge Intensive

PurposeThe study purports at investigating the effect of organizational factors (strategy, culture, information technology and structure) on knowledge transfer and innovation performance in the context of Indian International joint ventures (IJVs) of varied ages and industries. All the variables are woven together in the framework of dynamic capabilities theory.Design/methodology/approachPLS-SEM was used to analyze the primary data collected from IJVs. The disjoint two-stage approach was applied to check the mediation in the model. The multigroup technique was deployed to test group-differences in the sample.FindingsThe four organizational factors, combined as a construct, are seen to have a positive impact on knowledge transfer, which facilitates innovation performance. But mediation analysis revealed the insignificant indirect relationship of organizational factors with innovation through knowledge transfer for the total sample. In-depth group analysis revealed that these results differ between young and mature IJVs and knowledge-intensive and non-knowledge intensive industries.Research limitations/implicationsThe number of organizational factors is limited to four, which can be further increased. Longitudinal studies for investigating the formation of dynamic capabilities can be the future research direction.Originality/valueThe research has provided hierarchical analysis for organizational factors, knowledge transfer and innovation performance with multigroup industrial and age-wise analysis of Indian IJVs, which is still unplumbed in international business literature.

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