Firm-level innovation in New Zealand
Notice bibliographique
Résumé
Innovation is an issue that has attracted considerable research interest in economics. Innovation related data, collected via firm based surveys, has become the norm for many countries (e.g. Canada, United States, Malaysia, Taiwan, Australia). In New Zealand the main survey instrument of this type is the Business Operation Survey (BOS), which is an integrated, modular survey developed by Statistics New Zealand (SNZ). The survey has been operating annually since 2005 and includes up to three "modules" each with its own specific objectives. The first module focuses on business performance and the characteristics of participating firms. The longitudinal dimension of these data enables changes over time to be analyzed and facilitates the investigation of causal relationships. The second module operates on a rotational basis, where the survey content alternates between innovation and business use of Information and Communication Technology (ICT). The innovation module replaced the Innovation Survey, which was last run in 2003. This paper seeks to identify the innovative behaviour of New Zealand firms using the Longitudinal Database (LBD) that stems from the 2006 SNZ IBULDD (Improved Business Understanding via Longitudinal Database Development) initiative. IBULDD links business related data (including BOS) into an integrated longitudinal database. Starting from a detailed review of the international innovation research literature, a list of potential regression variables was established. A new set of probit regression models are proposed where four different innovation outcomes were developed and tested in an attempt observe the stability of the models over time. In summary the results of presented in the paper are: Firstly, New Zealand firms appear to experience smaller positive size and market power effects than found internationally due to the unique (micro-sized) firm demographics. The large impact of SMEs and the relatively flat market structure appear to have disadvantaged individual businesses in the innovation space as well as potentially New Zealand as a whole. Secondly, general investment may be more beneficial than specific R&D projects. R&D projects generally require large quantities of resources from participants, and the pay-off periods tend to be longer. Without sufficient economies of scale it is extremely risky for firms to participate. In contrast, small scale investments aimed at technology acquisition, product improvements and market entry appear to be more cost effective options in the short run. Exporting and direct investment overseas are two preferred channels for seeking market information and innovation opportunities. Finally, favorable regional environments are innovation enhancing, however once an acceptable level has been reached diminishing marginal returns appear to set in quite quickly. From a policy prospective, it seems necessary to alter the policy setting in response to the current market environment and over-investment in infrastructure is not recommended, given resource constraints and potential opportunity costs.
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 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 | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».