Impact of entrepreneurship on technological innovation in the digital age: a knowledge management perspective
Notice bibliographique
Résumé
Purpose This study aims to use the knowledge management perspective to examine the mechanism through which entrepreneurship drives firms’ technological innovation in the digital age. The objective is to develop a multi-stage integrated theoretical model to explain how entrepreneurship exerts its influence on firms’ technological innovation with a particular focus on the knowledge management perspective. The findings can be used for the cultivation of entrepreneurship and for the promotion of continuous technological innovation activities. Design/methodology/approach This study uses a case-based qualitative approach to examine the relationship between entrepreneurship and technological innovation. The authors first analyze the case of SANY and then explore the mechanism of how entrepreneurship can promote a firm’s technological innovation from the perspective of knowledge management based on the technology-organization-environment framework. An integrated theoretical model is then developed in this study. Findings Based on a case study, the authors propose that there are three main processes of knowledge management in firms’ technological innovation: knowledge acquisition, knowledge integration and knowledge creation. In the process of knowledge acquisition, the joint effects of innovation spirit, learning spirit, cooperation spirit and global vision drive the construction and its healthy development of firms’ innovation ecosystem. In the process of knowledge integration, the joint effects of innovation spirit, cooperation spirit and learning spirit help complete the integration of knowledge and further the accumulation of firms’ core knowledge resources. In the process of knowledge creation, the joint effects of mission spirit, learning spirit and innovation spirit encourage the top management team to establish long-term goals and innovation philosophy. This philosophy can promote the establishment of a people-oriented incentive mechanism that helps achieve the transformation from the accumulation of core knowledge resources to the research and innovation of core technologies. After these three stages, firms are passively engaged in the “reverse transfer of knowledge” step, which contributes to other firms’ knowledge management cycle. With active knowledge acquisition, integration, creation and passive reverse knowledge transfer, firms can achieve continuous technological innovation. Research limitations/implications This study has important theoretical implications in entrepreneurship research. This study helps advance the understanding of entrepreneurship and literature on the relationship between entrepreneurship and technological innovation in the digital age, which can broaden the application of knowledge management theories. It can also help better understand how to develop healthy firm-led innovation ecosystems to achieve continuous optimization of knowledge and technological innovation in the digital age. Originality/value This study proposes an integrated theoretical model to address the issues of entrepreneurship and firms’ technological innovation in the digital age, and it is also one of few studies that focuses on entrepreneurship and innovation from a knowledge management perspective.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,005 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,000 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».