Network analysis of innovation mentor community of practice

dc.authoridPerdahci, Ziya Nazim/0000-0002-1210-2448
dc.authoridAydin, Mehmet/0000-0002-3995-6566
dc.authoridALTINISIK, Gunda Esra/0000-0003-0205-745X
dc.authorwosidaltınışık, gunda/IAN-6099-2023
dc.authorwosidPerdahci, Ziya Nazim/C-8387-2015
dc.authorwosidAydin, Mehmet/ABI-4816-2020
dc.contributor.authorAydın, Mehmet Nafiz
dc.contributor.authorAydin, Mehmet Nafiz
dc.contributor.authorPerdahci, Ziya Nazim
dc.contributor.authorPasin, Merih
dc.date.accessioned2023-10-19T15:11:45Z
dc.date.available2023-10-19T15:11:45Z
dc.date.issued2023
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, Turkiyeen_US
dc.description.abstractPurposePositive 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.citation1
dc.identifier.doi10.1108/K-10-2022-1479en_US
dc.identifier.issn0368-492X
dc.identifier.issn1758-7883
dc.identifier.scopus2-s2.0-85151971334en_US
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1108/K-10-2022-1479
dc.identifier.urihttps://hdl.handle.net/20.500.12469/5205
dc.identifier.wosWOS:000961052300001en_US
dc.identifier.wosqualityN/A
dc.khas20231019-WoSen_US
dc.language.isoenen_US
dc.publisherEmerald Group Publishing Ltden_US
dc.relation.ispartofKybernetesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSocial network analysis (SNA)en_US
dc.subjectCommunity of practice (CoP)en_US
dc.subjectInnovation mentorsen_US
dc.subjectCompetencesen_US
dc.titleNetwork analysis of innovation mentor community of practiceen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublicationa66a9279-fa0c-4915-816f-40c93cee4747
relation.isAuthorOfPublication.latestForDiscoverya66a9279-fa0c-4915-816f-40c93cee4747

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