Research on Prolong of 2007 China Tourism Satellite Account Compilation
Notice bibliographique
Résumé
Because of the undefined boundaries of the tourism industry,the objective of tourism statistics has been largely to provide feedback to individual trading groups,rather than to the interpretation and analysis of a highly standardized production activity.This apparent limitation within tourism statistics makes it difficult to gauge the scale and status of the tourism industry.Since the closing years of the last century,the Tourism Satellite Account(TSA) framework has gradually become the internationally accepted scientific method for conducting statistical investigations of tourism.However,there are a number of constraints associated with this method.Firstly,the compilation of a TSA requires a large-scale sample survey and considerable costs in terms of capital and human and physical resources.Secondly,the results obtained from the application of this method entail a certain degree of deviation from people's daily experiences with which tourism is evidently more closely associated compared with industrial activities and productive service activities.Thirdly,the challenges of matching the statistical results of a TSA with the demands of sectionalism are considerable compared with the simpler consideration of gross income from tourism and its proportionate contribution to GDP as indicators of the size of the tourism industry.However,in terms of accuracy,gross income from tourism as a proportion of GDP provides only a speculative measure of the industry's total economic contribution.As an indicator,it does not meet the requirements of the principles of statistics.Consequently,China's macro statistics on tourism present a dilemma in the long term:on one hand,they are accurate but not good to use; on the other hand,they are good to use but not accurate.This dilemma has led to the inability of the tourism industry to ascertain its own status.It has also failed to penetrate research discourses on the national economy and industry.Moreover,some evident errors in theory and practice regarding the calculation of the scale of the tourism industry have resulted in superficial perceptions about the tourism economy within society,but rarely in rational quantitative support.A discussion on the pros and cons of statistical methods used to investigate tourism is,in our view,futile.Instead,we believe it is necessary to extend beyond this discussion to initiate action relating to statistical accounting of the tourism industry.This is important,because it is possible to calculate the main index of the TSA based on China's current statistical system.In this study,we combine a TSA and input-output theory with a survey of inbound and domestic tourism.We develop a set of algorithm processes to account for added value of the tourism industry that meet the standards of international statistics and the TSA.Our findings indicate that the added value of the tourism industry accounts for 2.67% of China's GDP; a figure that is comparable to those obtained for the United States,Canada,and several other countries.It should be noted that this proportion reflects only the direct contribution of the tourism industry to the total national economy,and does not include indirect impacts due to associated effects.One factor that may commonly be excluded from the calculation process is that of sales prices in the tourism survey data,with the compilation of input-output tables being based on producer prices.We eliminated the significant difference of prices through targeted conversion according to tax rates for different industries.The algorithm process developed in this study contributes to an objective and accurate understanding of the status of the tourism industry in the national economy.It provides a precise and effective basic framework for calculating the full impact of the tourism economy using a computable general equilibrium model and an input-output price effect model.
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 | 0,003 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,009 | 0,017 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,002 |
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 ».