The effects of trust and shared vision on inward knowledge transfer in subsidiaries' intra- and inter-organizational relationships

By Li Li. 2005

290 citations recorded by the source corpus.

Subfields: Communication, Sociology and Political Science, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/ef2dbc327e0885ecdafdb536c902de194dad3118

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In Communication

In Sociology and Political Science

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Citations in the corpus

Business and management in China: A review of empirical research in leading international journals (2007, background): “L. Li (2005) examined the impact of trust and shared vision on inward knowledge transfer to the subsidiary from both the subsidiary´s corporate and external relations.”
Parent Company Benefits from Reverse Knowledge Transfer: The Role of the Liability of Newness in MNEs (2011, background): “Similarly, the intensity of exposure to a corporate vision and shared norms (i.e., the number of years that a particular subsidiary has been operating within the MNE network) provides a subsidiary with experience in dealing with internal relationships (Foss & Pedersen, 2002; Li, 2005).”
Teacher perceptions of school culture and their organizational commitment and well-being in a Chinese school (2011, background): “Shared vision seems to be a less studied concept in the school contexts; however, research in other fields, for example business management, has shown that shared vision plays a vital role in bringing the members together and thus the commitment and well-being of the organizational members ( Li 2005”
Social Capital and Knowledge Integration in Digitally Enabled Teams (2008, background): “In short, a shared understanding facilitates the exchange of meaningful communication needed for exchange and combination for knowledge creation (Nahapiet and Ghoshal 1998, Li 2005).”
Do Perceptions of Ethical Conduct Matter During Organizational Change? Ethical Leadership and Employee Involvement (2014, background): “They also depend on the integrity of management during uncertain times (Li 2005).”
A multi-level perspective on innovation ecosystems for path-breaking innovation (2017, background): “Future empirical work informed by this proposition can operationalize the learning variable in terms of knowledge transfer across ecosystem boundaries (Maurer, Bartsch, and Ebers, 2011), drawing on survey data (Li, 2005) and social network analysis (Sammarra and Biggiero, 2008).”