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Better UK Productivity: An Inside Job

2001· article· en· W274547855 sur OpenAlexaboutno aff
S.J. Dorgan, John Dowdy, Peter Whawell

Notice bibliographique

RevueThe McKinsey Quarterly · 2001
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueGlobal trade and economics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésProductivityProduct (mathematics)Gross domestic productManufacturingLabour economicsPound (networking)EconomicsBusinessManufacturing sectorEconomic growthMarketing
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Poor labor productivity may turn UK manufacturing companies into easy targets for foreign buyers. Modern management techniques could be the answer. The decline of Britain's manufacturing sector is not in dispute, though the causes of that decline have prompted much debate. The popular candidates are the general shift of manufacturing toward lower-cost developing countries and the recent high value of the pound sterling. But while such exogenous factors doubtless play a part, the troubles of the UK manufacturing sector result in large measure from a factor that, fortunately, lies squarely within its managers' control: labor productivity. The proof lies in the productivity of foreign-owned plants in the United Kingdom. In US-owned plants there, for example, labor is about 80 percent more productive on average than it is in UK-owned plants--in every sector. As a result, overall productivity is suffering and so, consequently, are both UK manufacturing's contribution to the country's gross domestic product and the financial performance of individual manufacturers. While it is true that--with the exception of the United States--developed nations generally have lost trade in manufactured goods to developing markets over the past ten years, manufacturing's share of GOP fell faster in the United Kingdom than in any other Group of Seven (G-7) country, reaching just 17.7 percent at the end of 1999. This shrinkage isn't explained by extraordinary growth in the United Kingdom's nonmanufacturing sectors, whose average annual gain in output from 1989 to 1999 was 2 percent a year. By contrast, manufacturing's average annual growth over the same period was only 0.4 percent. In Canada, France, and the United States, manufacturing has actually gained share in recent years; in Germany, Italy, and Japan, the losses have been smaller than those in the United Kingdom. Some argue that the relatively weak recent growth of the UK manufacturing sector is attributable in part to its dependence on faltering old-economy industries such as food processing, paper, and textiles. In the United States, by contrast, the faster-growing electronics and mechanical-engineering industries, which support the new economy, dominate manufacturing. But even after the disparity between the sector mix in the United Kingdom and the United States is factored out, figures for the period from 1995 to 1999 show that the US manufacturing sector still grew at a rate of almost 4 percent a year while its UK counterpart notched growth of just half a percent. On the financial front, UK manufacturing has destroyed more than [pound]80 billion ($110 billion) in value over the past ten years, and the already substantial difference between the UK and the US manufacturing sectors' net rate of return appears to be widening (Exhibit 1). So too does the gap in total productivity between manufacturing in the United Kingdom, on the one hand, and in Canada, France, Germany, Italy, Japan, and the United States, on the other. Total US productivity, for example, which was 29 percent greater than the United Kingdom's in the period from 1994 to 1996, had become 38 percent greater by 1998. Many observers suggest that an increase in capital investment will bridge the gap. A close look at the figures, however, suggests that the level of capital investment is not the problem, nor is raising it the solution. The United Kingdom's rate of capital expenditure has been growing, and at 14 percent of the value of output in 1998 it now matches the levels of the country's strongest competitors: Germany, with 15 percent, and the United States, with 13.6 percent. Capital intensity -- the ratio between the contributions of capital (the numerator) and labor (the denominator) to production--remains low in the UK manufacturing sector because of its previously low capital spending. But while the United Kingdom's capital stock is catching up--albeit from a low base--there are diminishing returns to further capital investment in terms of labor productivity. …

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,013
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,099
Score d'incertitude au seuil0,331

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,013
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0030,003
Communication savante0,0110,007
Science ouverte0,0010,006
Intégrité de la recherche0,0040,003
Charge utile insuffisante (le modèle a refusé de juger)0,0990,037

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 Opus0,062
Tête enseignante GPT0,216
Écart entre enseignants0,154 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2001
Routes d'admission1
Résumé présentoui

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