Generation of breakthrough innovation through a knowledge management perspective: the case of small software firms
Notice bibliographique
Résumé
The literature on how is managed by radical innovators is embryonic, and the domain is still being mapped out. With this thesis, we aim to further the understanding of how small software firms (SSFs) manage and organize internally to generate breakthrough innovations. Our two research questions are formulated as follows: (Q1) How do SSFs create, transfer, retain, and protect their knowledge? (Q2) How do SSFs organize internally to manage their knowledge? The first question (Q1) refers to the management of in SSFs engaged in breakthrough innovation activities. In this study we explored four management processes: creation, transfer, retention, and protection. The second question (Q2) concerns SSFs' organizational settings. We investigated SSFs' physical infrastructures, organizational structures, organizational cultures, and information technology tools, a set of variables that we called knowledge organizational infrastructure. In order to answer these two questions, five cases of SSFs engaged in breakthrough innovation activities were explored. The setting of this research is the Canadian software industry. This industry is the most important and fastest growing component of the Canadian Information and Communication Technology (ICT) sector since 1997 (Industry Canada, 2006). The research design is explorative multiple-case studies (Yin, 2003; Eisenhardt, 1989). Data was collected through diverse sources including, semi-structured interviews, non-participant observations, internal documents, and public data. This research follows an interpretative approach, since phenomena is understood through the meanings people assign to them. The five explored SSFs were analyzed through the lenses of the management (Nonaka, 1994) and resource-based view (Penrose, 1959) perspectives. This study extends the literature examining knowledge management and knowledge organizational in SSFs seeking to generate radical innovation. We found that SSFs put in place specific management processes, to mange knowledge, and particular organizational infrastructures, to organize internally and enable management processes. By analyzing the specificities of SSFs' knowledge management and knowledge organizational and the way these and infrastructures relate to each other in each explored SSF, we created a of small radical innovating firms. We propose five ideal organization types: (1) collaborative; (2) artistic; (3) formalized; (4) synergistic; and (5) balanced. We argue that classifying small radical innovating firms into a taxonomy of ideal organizational types helps scholars and practitioners to better understand specific relationships between management processes and organizational infrastructures, and elucidate the way those relationships influence the generation process of radical innovation. What emerges from our data is that radical innovation processes in SSFs are strongly influenced by the particularities of their organizational infrastructure, management processes, and technological mainstream activities. Keywords: small firms, software industry, management processes, organizational infrastructure, breakthrough innovation.
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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 | 0,006 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,014 | 0,014 |
| Communication savante | 0,011 | 0,006 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,004 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».