A Study on the Relationship between the Typology of Knowledge-Intensive Businesses (KIBs) and Performance Measurement Systems (PMS): Evidence from Taiwan
Notice bibliographique
Résumé
This study utilizes the source of knowledge (internal or external) to derive four types of knowledge-intensive businesses (KIBs): non-KIB, knowledge creator, knowledge introducer, and knowledge integrator. Moreover, this study investigates the differences among the four types of KIB in their organizational characteristics and performance measurement system (PMS). The proposed model is empirically evaluated using survey data collected from top or middle managers of 127 Taiwan companies i n which 109 companies are classified as KIBs. Based on the analysis of multiple regressions and MANOVA, the empirical results reveal that there are significant differences in the organizational characteristics and PMS among the four types of KIBs. There are three main contributions in this research: (1) we categorize the KIBs into four types by using the main source of internal or external knowledge in the companies. This typology of KIBs would contribute to our understanding of knowledge management. (2) This study uses environmental uncertainty, innovation strategy, size and absorptive capacity to construct the organizational configuration of different KIBs. (3) We find that there are significant differences among the four types of KIB in the financial or non-financial PMS. This study utilizes the source of knowledge (internal or external) to derive four types of knowledge-intensive businesses (KIBs): non-KIB, knowledge creator, knowledge introducer, and knowledge integrator. Moreover, this study investigates the differences among the four types of KIB in their organizational characteristics and performance measurement system (PMS). The proposed model is empirically evaluated using survey data collected from top or middle managers of 127 Taiwan companies i n which 109 companies are classified as KIBs. Based on the analysis of multiple regressions and MANOVA, the empirical results reveal that there are significant differences in the organizational characteristics and PMS among the four types of KIBs. There are three main contributions in this research: (1) we categorize the KIBs into four types by using the main source of internal or external knowledge in the companies. This typology of KIBs would contribute to our understanding of knowledge management. (2) This study uses environmental uncertainty, innovation strategy, size and absorptive capacity to construct the organizational configuration of different KIBs. (3) We find that there are significant differences among the four types of KIB in the financial or non-financial PMS.
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.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».