If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.*Related content and download information correct at time of download. Design/methodology/approachThis paper was an empirical study based on structural equation modelling (SEM) with a sample of 293 employees from 31 high-technology firms in China. FindingsThe result indicated that (1) affective commitment had a significant positive effect on OPO but no effect on KPO; (2) OPO was positively related to both common and key knowledge sharing while KPO exerted a negative impact on both; (3) common knowledge sharing was positively related to key knowledge sharing; (4) the relationship between affective commitment and key knowledge sharing was multi-mediated by OPO and common knowledge sharing. Originality/valueOPO and KPO play an essential role in transferring the effect of employees' affective commitment to common knowledge sharing and key knowledge sharing, which unravels the blackbox of how effective commitment affects knowledge sharing.

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Document VersionBackground: Healthcare organizations face an increasing pressure to innovate while controlling care quality. We have little insight on how control of care quality interacts with knowledge sharing

A central part of technological innovation for industrial firms involves search for new external knowledge. A well‐established stream of literature on firms' external knowledge search has demonstrated that firms investing in broader search may have a great ability to innovate. In this paper, we explore the influences of technology search on firms' technological innovation performance along three distinctive dimensions: technical, geographic, and temporal dimensions, using a unique panel data set containing information on Chinese firms that were active in technology in‐licensing and patenting during the period 2000–2009. Our findings reveal that Chinese firms' technological innovation performances are related to external technology search in quite different ways from the ones suggested in the extant literature using evidence from developed countries. We find that Chinese firms searching ‘locally’ along the technical dimension have better technological innovation performance than those searching ‘distantly’. However, when a Chinese firm in‐license relatively old (mature) technologies or those from geographically nearby areas, it will be less bounded to searching familiar technical knowledge.

The relational resource-based view posits that performance differences among firms can be explained not only by the possession of internal resources but also by maintaining and developing relationships with external partners. However, studies in the extant literature usually address the separated roles of various external relationships of focal firms, but the literature has not addressed how relationships with different sets of knowledge partners are related to each other and influence focal firms' performance. Therefore, to fill this research gap, this study focuses on how technological resources acquired from one set of partners (licensing foreign technologies) may generate subsequent internal and relational rents in terms of technological innovation in the context of collaboration with an entirely different set of knowledge partners (local R&D partners). Specifically, we propose that local R&D collaborations need to be large in scale and broad in scope. The empirics are based on the analysis of a sample of 160 high-tech Chinese firms observed from 2000 to 2011. Consistent with our predictions, our findings contribute to extending the relational view by addressing the relations among the relationships of focal firms.

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In times of unprecedented change related to the ongoing digital transformation of business and society at large, a pressing contemporary management challenge is recognizing and translating these changes into digital business model innovation (DBMI). Academia potentially has much to offer in aiding this managerial challenge, yet research in the field remains vague with regard to what DBMI is. We detect conceptual ambiguity among scholars as a bottleneck that prevents advancements in the field of DBMI research. In this article, we aim to trace the foundation of key attributes of the DBMI concept and propose a novel definition. Our insights are based on a targeted, state-of-the-art literature review of 57 publications. We conclude with an exploration of avenues for future research, which we closely link to the broader fields of strategic management, information systems, and organization studies, thereby exposing the issue of DBMI to a wider audience. Overall, we aim to make a significant step toward construct clarity in DBMI research.

In this article, we provide a compelling case for demonstrating ''learning-bylicensing,'' and we further investigate the moderating effect of specific licensed-knowledge attributes on the innovation performance of licensee firms. This case is based on a unique dataset from the China State of Intellectual Property Office regarding technology-licensing activities and spanning the years 2000-2010. Using this dataset we make a longitudinal analysis of the lagging learning effect that transferee firms experience when they in-license technology. The empirical results from 71 Chinese electronic-industry firms reconfirm the concept of ''learning-by-licensing.'' Moreover, the results also indicate that both technology complexity and technology generality, which are attributes of licensed knowledge, have positive moderating effects on the relationship between technology in-licensing and the subsequent innovation performance of licensee firms. However, such a positive moderating effect was not found for the newness of technology.