MétaCan
Menu
Retour à la cohorte
Enregistrement W2953515272 · doi:10.1108/jkm-03-2018-0190

Evaluating the role of social capital, tacit knowledge sharing, knowledge quality and reciprocity in determining innovation capability of an organization

2019· article· en· W2953515272 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.

Notice bibliographique

RevueJournal of Knowledge Management · 2019
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueKnowledge Management and Sharing
Établissements canadiensConcordia University
Organismes subventionnairesnon disponible
Mots-clésTacit knowledgeKnowledge managementKnowledge sharingReciprocity (cultural anthropology)Structural equation modelingSocial capitalBusinessKnowledge value chainCommon-method varianceCompetitive advantageExplicit knowledgeQuality (philosophy)MarketingOrganizational learningPsychologyComputer scienceSocial psychologySociology

Résumé

récupéré en direct d'OpenAlex

Purpose Knowledge sharing has become an integral part of organizations’ business strategies, along with aiding organizations to grow and innovate in the market, and gain competitive advantage. This paper aims to concentrate on the role of tacit knowledge sharing in fostering innovation capability of an organization. Specifically, the study considers social capital (relational, cognitive and structural) as an important precursors to tacit knowledge sharing, which in turn, influences innovation capability of an organization. The study further discusses the role that knowledge reciprocation plays in successful tacit knowledge sharing. The relation between knowledge quality and innovation capability is also discussed in the paper. Design/methodology/approach The investigation started with a review of extant literature in the field of knowledge sharing and innovation to derive a set of constructs. A set of hypotheses was developed based on the identified constructs, which was subsequently validated through a primary survey based on a structured questionnaire on a sample size of 190 respondents from the Indian industrial domain. The survey responses were subsequently analysed using the statistical technique of structural equation modeling and conclusions were drawn from the findings. Additionally, careful attention was paid in eliminating the common method bias, which is often associated with a primary survey. Findings A set of six hypotheses were derived based on the identified constructs and were subsequently validated. While validating the hypotheses, it was observed that while knowledge reciprocity, relational social capital and cognitive social capital was positive associated with tacit knowledge sharing, structural social capital did not have a significant effect on the same. Additionally, it was also observed that both tacit knowledge sharing and the quality of knowledge were positively associated with innovation capability. Practical implications The present day business marked by intense competition requires firms to be more aware of their innovative capabilities. Effective sharing of knowledge or information can be deemed as a vital component in achieving this objective. Organizations that practice and nurture innovation activities can use the findings of the current study as a part of their knowledge management strategy. In addition to using the explicit knowledge, which are structured in nature, organizations can also start using tacit knowledge to harness their innovation potential – and the findings from the current study can act as a motivational tool for them to do so. Originality/value Although there is a growing body of literature concerning the role of knowledge management in innovation, there still a dearth in discussing the role of tacit knowledge sharing in exploiting the innovation capability of an organization. The main discussion of this paper brings together a set of important constructs that exhibits the significant role that tacit knowledge sharing plays in determining the innovation capability of an organization. Furthermore, it tries to marry the concepts of social capital and tacit knowledge sharing with innovation capability, therefore adding significantly to the body of literature in knowledge management as well as innovation.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,011
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,475
Score d'incertitude au seuil0,738

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0110,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,078
Tête enseignante GPT0,407
Écart entre enseignants0,329 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle