Small firm performance: modelling the role of innovative differentiation
Notice bibliographique
Résumé
Ansoff (1965) theorises early on in the development of strategic management as a field of study that structure follows strategy. Although this assertion has been the basis for considerable debate (e.g. Peters, 1984), what has been widely accepted is that the use of different types of strategies under suitable conditions, including firm structure and environment, will improve firm performance (Anderson & Atkins, 2001; Borch, Huse, & Senneseth, 1999). This argument forms one of the cornerstones of strategic management theory, and has been the topic of a great number of studies (Dess & Davis, 1984; Porter, 1980). In particular, the role of business or competitive strategies in firm performance has been studies widely (Cooper, Willard, & Woo, 1986; Covin, 1991; Mosakowski, 1993; Smallbone, Leigh, & North, 1995; Porter, 1980). Best known of these studies is the seminal work of Michael Porter (1980), who developed a typology of business strategies, or generic strategies as he termed it, to describe how firms will compete in a particular market. He identifies differentiation, cost-leadership and focus strategies as the broad strategies which most firms will use to compete. Mintzberg (1988) builds on this work, explaining that most of these business strategies can be viewed as some form of differentiation. The existence of a refined typology of business strategies is supported by Miller (1988) who suggests that the richer examination of business strategies by the above mentioned authors, have allowed for an improved understanding of the relationship between strategy and the context in which it occurs. Miller studies 89 small and diversified firms in the province of Quebec, Canada, to explore the relationships between structure, environment and Porter's generic strategies, using such refined typology which includes innovative and marketing differentiation. Variyam and Kraybill (1993) explain that the business strategies adopted by small firms will differ from large firms due to a number of factors, including economies of scale and organisational structure. Although received wisdom holds that a focus or differentiation strategy is most likely to be associated with a high level of performance in small and/or new firms, this assertion has not been widely investigated in empirical studies, and the existing evidence is conflicting. For example, Variyam and Kraybill (1993) suggest that small firms use numerous strategies, including product development, marketing and innovation in order to gain competitive advantage. On the other hand, Scozzi, Garavelli and Crowston (2005) argue that the number of innovative small firms may be limited. More specifically, Miller (1988) compares the behaviour of high and poor performing firms and finds that innovative differentiation is most likely to be pursued by high performers in uncertain environments. Specifically, he suggests that for small firms the nature of the environment will have a significant effect on the choice of business strategies. A number of other environmental factors have been identified as influencing the choice and success of business strategies in small firms. Variyam and Kraybill (1993) state that business strategies differ depending on industry sector, for example wholesale and retail sectors may use quality and product effectiveness strategies. Miller (1988) finds that corporate life cycle may also influence the choice of strategy, in particular, that innovative and focus strategies are more common in young firms. The firms in Miller's study were defined as small, employing fewer than 500 employees. This and other studies (e.g. Kamien & Schwartz, 1975; Tushman & Nelson, 1990) show that Schumpeter's (1947) earlier assertion that large firm size is essential for innovation does not hold for all small firms.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».