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Enregistrement W2177642661

Knowledge Source and Small Business Competitiveness

2006· article· en· W2177642661 sur OpenAlex

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Notice bibliographique

RevueCompetition Forum · 2006
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueIntellectual Capital and Performance Analysis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTacit knowledgeCompetitive advantageBusinessKnowledge managementKnowledge value chainOrganizational learningPersonal knowledge managementBusiness process reengineeringExplicit knowledgeKnowledge economyMarketingComputer science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

EXECUTIVE SUMMARY This paper seeks to shows that information acquired by owners of small firms from certain sources helps the firms to be competitive. Data for this study was collected by mail from small business owners in three rural counties in West Texas. The result indicates that knowledge acquired by owners of small firms from colleagues, salespeople, trade publication family members, seminars and social contacts is significantly associated with perceived competitiveness. Only three of these sources-colleagues, family members and seminars, have a positive effect on perceived competitiveness. The results suggest the importance of tacit and explicit knowledge for decision-making and provide a framework for knowledge acquisition in small firms. Keywords: Knowledge source, small business, competitiveness, tacit knowledge, explicit knowledge INTRODUCTION Because many firms, including small business, have considered knowledge to be one of the most important factors for a firm's competitiveness, firms are showing increasing interest in implementing knowledge management processes and have begun to adopt knowledge management part of their overall strategy. Davenport and Prunsak (1997), maintain that knowledge management is often used to describe the process through which an organization develops, organizes, and share knowledge to achieve its competitive advantage. KPMG Management Consulting (1999) describes knowledge management as the systematic and organized attempt to use knowledge management within an organization to improve its performance. Schermerhorn (1999) argues that knowledge management compliments and enhances other organizational initiatives such Total Quality Management (TQM), Business Process Re-engineering (BPR), Organizational Learning (OL) and Organizational Development (OD). He therefore asserts that knowledge management provides a new and urgent focus of capturing, developing, and utilizing the knowledge of an organization to sustain its competitive position. Increasingly, knowledge is core to business success (McAulay et al., 1997), and the most successful organizations promote a learning climate. These organizations support the ongoing acquisition of knowledge and skill through learning. They encourage learning through creativity, imagination, exploration, discovery and intentional risk taking (McGill et al., 1992). Prior literature makes clear the positive relationship between knowledge management capabilities and firm performance (Gold, Malhota, and Segars, 2001). But to what extent is knowledge associated with competitiveness? What is the source of each type of knowledge a firm utilizes to accomplish its competitive and other organizational objectives? These questions have not been adequately addressed empirically, especially with respect to small firms (Dooley et al., 1999). This paper addresses these questions and extends the literature on the effect of the use of tacit and explicit knowledge on competitiveness. The next section of the paper presents a review of related literature. CONCEPTUAL FRAMEWORK Competitiveness and the performance of the firm can be explained by knowledge acquired from several sources and used in the marketing management process. In this regard, Dooley et al. (1999) note that process knowledge is a key driver of competitiveness. Process knowledge involves an objective science of the work process. Studies show that effective acquisition and use of process knowledge is associated with enhanced quality performance, (General Accounting Office, 1991). Process knowledge involves tacit and explicit considerations (Polanyi, 1966). Management and organizational theorists (Winters, 1987; Nonaka, 1994 and Quinn, et al., 1996) treated organizational knowledge a valuable strategic asset. March (1997), argues that management of intellectual capitals (knowledge) has become a central theme in modern business literature and a commonly cited source of competitive advantage. …

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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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,893
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

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

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 Opus0,012
Tête enseignante GPT0,197
Écart entre enseignants0,184 · 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