Rapid growth and rapid internationalization: the case of smaller enterprises from Canada
Notice bibliographique
Résumé
Purpose The main objective of this paper is to develop a deeper understanding of high growth and rapid internationalization characteristics in terms of: empirically characterizing growth deriving the profile of high‐growth enterprises, exploring influential factors in high‐growth, pointing out the factors that stimulate internationalization, presenting the combined influence of these factors in both the high‐growth and early internationalizing enterprises, and formulating research‐based policy recommendation for longer and higher growth rates and for decreasing the chances of demise in such younger firms. Design/methodology/approach The authors have built a longitudinal sample of more than 1,140 micro, small and medium‐sized enterprises that have grown at exceptionally high rates for at least five years at the earlier stages of their life‐cycle, and even from inception in some cases. The data‐base's origin is a popular Canadian business publication, the Canadian Business Magazine, which annually identifies and ranks growing firms in order to publish an annual list called “Profit 100: Canada's 200 fastest‐growing companies”. Findings The findings of this analysis point to a rich population of high‐growth enterprises with diverse ages, locations, sizes and revenues that manage to achieve high domestic and international growth for much longer and in ways not explained by the extant literature across time and industries. Research limitations/implications This research carries the limitations of secondary data. In spite of its richness in terms of the high growth rates, annual lists offer a limited number of attributes per firm. It would be highly recommendable to use case studies in future research and broadly based surveys are necessary for deeper understanding of both the high and rapid growth and internationalization as well as the influential factors, including the internal characteristics of its agents, especially the management. Practical implications This research indicates that rapid growing enterprises (RGEs) and rapid internationalizing enterprises (RIEs) are distinctive firms and are primarily small and medium‐sized enterprises. Although the relative frequency of the appearance of various firm size‐categories varies over time, RGEs are found across all the size and age categories. Although their total number as a proportion of all continuing firms in the economy is small, they are among the highly prominent and contributing corporate citizens. Social implications This topic deserves the attention of scholars for the remarkable potential it offers to uncover the puzzle of growth, which is a time‐dependent phenomenon. HGEs attain higher growths in shorter times; thus requiring a relatively shorter tracing of the growing firms. The topic also deserves the special attention of policy makers as HGEs generate employment, income, social benefits, taxes and wealth at much higher and faster rates than an average growing firm. Originality/value The attractive features of HGEs' and RIEs' high‐growth phenomenon compelled the authors to explore the topic in more depth than initially intended. By examining rapidly‐growing smaller and younger enterprises, this study covers a wide gap in the extant literature of growth pertaining to the internationalization of smaller firms and thereby contributes the interaction of the two fields.
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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 | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,007 |
| Études des sciences et des technologies | 0,021 | 0,004 |
| Communication savante | 0,007 | 0,002 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».