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Dynamism of Manufacturing SMEs in the North-Atlantic Islands: A Case Study

2000· article· en· W207072952 sur OpenAlex

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venuePublié dans une revue dont le pays d'attache est le Canada.
no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
Aucune affiliation canadienne. Une base fondée sur la seule affiliation (le devis habituel) n'aurait jamais vu ce travail. C'est l'un des travaux qui justifient l'inversion de la base.

Notice bibliographique

RevueCanadian Journal of Regional Science · 2000
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueRegional Development and Policy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDynamismExternalityCompetition (biology)BusinessRural areaFunction (biology)Transaction costIndustrial organizationEconomyEconomicsEconomic geographyFinance
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Research into industrial districts has enabled attention to be redirected towards the Marshallian externalities relating to the economies of conglomeration generated by the concentration of businesses on the same site and in the same sector (Beccatini 1992). These economies of conglomeration are in fact the set of benefits obtained by businesses grouped together in a city area, regardless of sector (Tellier 1993; Polese 1994). Geographical proximity helps reduce transaction costs for businesses, which are thus able to take advantage of what Perrin (1990) refers to as territorial synergy. Similarly, Proulx (1991) mentions the benefits of urban areas over rural areas, including concentrations of better financial, brokerage and transportation services and the existence of networks that facilitate contacts and provide information on market development. This same view is also taken by Gofette-Nagot and Schmitt (1998), who postulate that proximity permits interactions between physical and human resources, thus allowing businesses to cope better with national and international competition. Together, these various considerations give some idea of the handicaps or difficulties faced by businesses in rural and island environments outside the major cities. In recent years, the number of studies of rural businesses has grown considerably, suggesting, as we have already shown (Joyal and Deshaies 1998, 2000), that thanks to the contribution of new technologies, even businesses that are geographically isolated are able to function well. Davidson et al (1994) note that in Sweden, as far as proximity of markets and supply sources is concerned, the facilities available in local infrastructures and the availability of financial assistance are still important elements. However, like Nelson (1998), we believe we have shown that the absence of economies of conglomeration in rural environments is no longer an insurmountable obstacle. It was this observation that led us to compare the situation of SMEs (Small and Medium-sized Entreprises) in island environments and in rural or non-city environments, using a case study to see whether a specific form of dynamism actually exists. Development conditions in island environments are known to be similar to local development conditions. As Cote (1996, 1997, 2000) pointed out, in many such environments social players must learn to rely on their own means and organisational skills in order to meet their own needs. At first glance, it is easy to identify similarities between small and medium-sized enterprises with island locations and those in rural communities. Both are situated at a distance from major decision-making centres and information centres. Their remote locations provide an additional challenge, since they are unable to take advantage of the territorial synergic effects available to city businesses, and there is no local dynamic likely to create an impetus. According to Falcone et al (1996), the greatest obstacle facing rural entrepreneurs is their relative isolation. It is easy to understand why -- they simply cannot count on the same support and assistance as their counterparts in cities or more densely populated areas. The goal of this paper is to see whether the characteristics of rural SMEs also apply to island SMEs. We begin by presenting their characteristics against the background situation, and go on to identify some research guidelines. We then describe the survey methodology, the challenges and dynamism of the SMEs studied for the research, and the factors underlying their entrepreneurial vitality. The Backgound Situation According to Illouz-Winiki and Paillard (1998), a rural area is an environment in which the population is scattered in small towns or villages over a relatively large area that is sometimes, but not always, less developed economically than the other regions of a given country. Rural areas are also distinguished by the presence of primary activities in the natural resource sector, such as farms, outdoor leisure activities, sandpits and gravel quarries, agro-tourism firms and so on. …

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.

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)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,463
Score d'incertitude au seuil0,826

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,032
Tête enseignante GPT0,297
Écart entre enseignants0,265 · 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