Network analysis of innovation mentor community of practice

dc.authorid Perdahci, Ziya Nazim/0000-0002-1210-2448
dc.authorid Aydin, Mehmet/0000-0002-3995-6566
dc.authorid ALTINISIK, Gunda Esra/0000-0003-0205-745X
dc.authorwosid altınışık, gunda/IAN-6099-2023
dc.authorwosid Perdahci, Ziya Nazim/C-8387-2015
dc.authorwosid Aydin, Mehmet/ABI-4816-2020
dc.contributor.author Aydın, Mehmet Nafiz
dc.contributor.author Aydin, Mehmet Nafiz
dc.contributor.author Perdahci, Ziya Nazim
dc.contributor.author Pasin, Merih
dc.contributor.other Management Information Systems
dc.date.accessioned 2023-10-19T15:11:45Z
dc.date.available 2023-10-19T15:11:45Z
dc.date.issued 2023
dc.department-temp [Altinisik, Gunda Esra; Aydin, Mehmet Nafiz] Kadir Has Univ, Dept Management Informat Syst, Kadir Has Campus Cibali, Istanbul, Turkiye; [Perdahci, Ziya Nazim] Mimar Sinan Fine Arts Univ, Dept Informat, Istanbul, Turkiye; [Pasin, Merih] IYTE, Dept Technol Design & Innovat Management, Izmir, Turkiye en_US
dc.description.abstract PurposePositive effect of knowledge sharing (KS) on innovation has come to the fore and government-supported innovation and mentoring communities or mentor networks have become widespread. This article aims to examine the community connectedness and mentors' preferences for professional competency-based KS of such innovation community of practice networks (CoPNs).Design/methodology/approachThe paper constructs a directed weighted CoPN model with a node-attribute-based novel fingerprint edge weights. Based on the CoPN, Social Network Analysis (SNA) metrics and measures including Giant Component (GC) were proposed and analyzed to identify mentors' connectedness preferences. The fingerprint was proposed as a novel binarized node attribute of competence. Jaccard similarity of fingerprints was proposed as edge weights to reveal correlations between competences and preferences for KS.FindingsThe work opted to conduct a survey of 28 innovation mentors to measure a CoPN. Both a name generator question and a second set of questions were employed to invite respondents to name their collaborators and indicate their professional competence. SNA metrics result in differing values for GC and the rest, which lead us to focus on GC to reveal salient metrics of connectedness. Jaccard similarity analysis results on GC demonstrate that mentors collaborate in an interdisciplinary manner.Originality/valueBased on the CoPN, the methods proposed may be effective in predicting preferred relationships for interdisciplinary collaborations, providing the managers with an analytical decision support tool for KS in practice. en_US
dc.identifier.citationcount 1
dc.identifier.doi 10.1108/K-10-2022-1479 en_US
dc.identifier.issn 0368-492X
dc.identifier.issn 1758-7883
dc.identifier.scopus 2-s2.0-85151971334 en_US
dc.identifier.scopusquality Q1
dc.identifier.uri https://doi.org/10.1108/K-10-2022-1479
dc.identifier.uri https://hdl.handle.net/20.500.12469/5205
dc.identifier.wos WOS:000961052300001 en_US
dc.identifier.wosquality N/A
dc.khas 20231019-WoS en_US
dc.language.iso en en_US
dc.publisher Emerald Group Publishing Ltd en_US
dc.relation.ispartof Kybernetes en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 1
dc.subject Social network analysis (SNA) en_US
dc.subject Community of practice (CoP) en_US
dc.subject Innovation mentors en_US
dc.subject Competences en_US
dc.title Network analysis of innovation mentor community of practice en_US
dc.type Article en_US
dc.wos.citedbyCount 1
dspace.entity.type Publication
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