Innovation mentor community of practice: a social network analysis perspective

Gunda Esra Altinisik, M. N. Aydin
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Abstract

Purpose To exploit collaboration-driven innovation, in recent years, many government-sponsored innovation programs and mentor services have emerged. These services support an effective exchange of knowledge among innovation actors, including innovation mentors and enable mentor connectedness as an important factor to develop and sustain effective innovation mentors’ community of practice (CoP). The purpose of this paper is to examine the degree of connectedness in an innovation mentor CoP. Design/methodology/approach In this study, the innovation mentors CoP as part of a national innovation program is considered a network. The connectedness and assortative mixing of this CoP and the effects of these two on each other were examined by using social network measures, including component analysis, the giant component (GC) and assortativity. Findings The authors provide the analytical interconnectedness results for both the GC and the whole network with network analysis and assortativity measurements of three attributes of mentors (institution, title and degrees). The degree of correlation of community for the GC shows preferential attachment between high-ranking and low-ranking mentors, while preferential attachment was not observed for the whole network. The correlation coefficient for the institution attribute has the highest value for GC, while the title has the highest value for the whole network. Originality/value The study is one of the early attempts to apply social network analysis for an innovation mentor CoP. This study reveals the criticality of evaluating the GC and the whole network separately and provides a number of research and practical directions that will contribute to the development of the innovation mentor CoP.
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创新导师实践社区:社会网络分析视角
目的为了利用合作驱动的创新,近年来,出现了许多政府资助的创新项目和导师服务。这些服务支持创新参与者(包括创新导师)之间的有效知识交流,并使导师之间的联系成为发展和维持有效创新导师实践社区的重要因素。本文的目的是检验创新导师CoP的连通性程度。设计/方法/方法在本研究中,作为国家创新计划一部分的创新导师CoP被视为一个网络。通过使用社会网络测量,包括成分分析、巨大成分(GC)和分类性,检验了这种CoP的连通性和分类混合,以及这两者对彼此的影响。结果作者通过对导师三个属性(机构、头衔和学位)的网络分析和分类测量,为GC和整个网络提供了分析互联性的结果。GC的社区相关度显示高级别和低级别导师之间的优先依恋,而整个网络没有观察到优先依恋。GC的机构属性相关系数最高,而整个网络的标题相关系数最高。独创性/价值该研究是将社交网络分析应用于创新导师CoP的早期尝试之一。本研究揭示了单独评估GC和整个网络的重要性,并提供了一些研究和实践方向,这些方向将有助于创新导师CoP的发展。
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来源期刊
CiteScore
6.30
自引率
10.30%
发文量
32
期刊介绍: The International Journal of Innovation Science publishes fundamental and applied research in innovation practices. As the official journal of the International Association of Innovation Professionals (IAOIP), the journal is a forum for the exchange of advanced knowledge in innovation, including emerging technologies and best practices, tools and techniques, metrics, and organization design and culture; as well as the stakeholder engagement, change management, and leadership skills required to ensure innovation succeeds. Areas of Coverage: -Innovation processes, methods, techniques- Individual''s role in Innovation- Improvements in HR, marketing, finance, or other disciplines that enable innovation- Innovation practices in specific industries or countries- Innovation centers, incubators, labs...- Regional or national economic development/policies related to innovation- Innovation competency, skills- Innovation conventions, competitions, or training- Innovation for entrepreneurs-Regional impacts on innovation- Growing innovationthrough university programs- Attracting innovative companies and entrepreneurs
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