5 resultados para Z32


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Cette étude s’applique à démontrer comment la relation documentaire peut être mise à l’épreuve du pardon dans deux films mettant en scène des bourreaux. Comment est-il possible de concevoir un dispositif cinématographique éthique avec la participation d’anciens criminels ? C’est la question que se sont posée les cinéastes Avi Mograbi et Rithy Panh. L’objectif de cette recherche sera de relever comment le pardon intervient explicitement, mais aussi implicitement, dans la forme documentaire. Il s’agira de comprendre comment ces films, "Z32" et "S21 la machine de mort khmère rouge", s’élaborent socialement, politiquement et esthétiquement du tournage à la réception, afin de cerner le potentiel symbolique et performatif du pardon dans la reconstruction du lien avec autrui.

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Understanding the determinants of tourism demand is crucial for the tourism sector. This paper develops a dynamic panel model to examine the determinants of inbound tourists to Siem Reap airport, Phnom Penh airport, and land and waterway borders in Cambodia. Consistent with the consumer theory of tourism consumption, a 10% increase in the origin country GDP per capita is predicted to increase the number of tourist visits to Siem Reap airport by 5.8%. A 10% increase in the real exchange rate between the origin country and Cambodia is predicted to decrease the number of tourist visits by 0.89%. In contrast, the number of foreign tourists in a previous period has little effect on the number of foreign tourists in the current period. Additionally, the determinants are different by the mode of entry to Cambodia.

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Forecasting tourism demand is crucial for management decisions in the tourism sector. Estimating a vector autoregressive (VAR) model for monthly visitor arrivals disaggregated by three entry points in Cambodia for the years 2006–2015, I forecast the number of arrivals for years 2016 and 2017. The results show that the VAR model fits well with the data on visitor arrivals for each entry point. Ex post forecasting shows that the forecasts closely match the observed data for visitor arrivals, thereby supporting the forecasting accuracy of the VAR model. Visitor arrivals to Siem Reap and Phnom Penh airports are forecast to increase steadily in future periods, with varying fluctuations across months and origin countries of foreign tourists.