JOURNALISM AND SOCIAL MEDIA: THE TRANSFORMATION OF JOURNALISM IN THE AGE OF SOCIAL MEDIA AND ONLINE NEWS

The evolution of social media has dramatically changed the way people access daily news updates. Instead of buying printed newspapers, nowadays, more and more people are getting news through social media, such as Facebook, Twitter, YouTube, BuzzFeed, among others. As social media has become one of the dominant and growing sources of news and information for millions of people, it has also turned journalism’s traditional one-way communication into two-way conversations where journalists find themselves being able to actively engage with audiences. This article shows how the way journalists and news organizations around the globe create and deliver news have changed to adapt to the new norms.  Article visualizations

Growth Strategy with social Capital and Physical Capital- Theory and Evidence: the Case of Vietnam

URL des Documents de travail : http://ces.univ-paris1.fr/cesdp/cesdp2014.htmlDocuments de travail du Centre d'Economie de la Sorbonne 2014.45 - ISSN : 1955-611XWe study the impact of social capital in both simple theoretical and empirical model with the main assumption is the price of physical capital is a decreasing function of social capital. In our theoretical model, there exists a critical value such that firm will not invest in social capital if its saving is lower than the critical value and otherwise. Moreover, the output depends positively and non-linearly on the social capital. Our empirical model that captures the impact of physical capital, human capital, and social capital using the database from Survey of Small and Medium Scale Manufacturing Enterprises (SMEs) in Vietnam 2011, confirms the conclusions of the theoretical model.Dans ce papier, nous étudions l'impact du capital social dans un modèle simple à la fois théorique et empirique. L'hypothèse cruciale est que le coût du capital physique, grâce aux contacts sociaux diminue par rapport aux dépenses en capital social. Dans le modèle théorique, nous montrons qu'il existe un seuil critique de l'épargne destinée aux dépenses en capital social. Les firmes dont l'épargne est inférieur à ce seuil ne vont pas investir en capital social. Nous montrons de plus que les productions dépendent positivement des dépenses en capital social. Les résultats du modèle empirique, en utilisant les données de Survey of Small and Medium Scale Manufacturing Enterprises du Vietnam de l'année 2011, confirment les résultats du modèle théorique

Pursuing environmental sustainability in the fast fashion industry: A qualitative exploratory research

Objectives: The main objectives of this study were to explore processes associated with producing fast fashion apparels that negatively impact the environment, to explore the sustainability initiatives that big clothing manufacturers and retailers in the fast fashion industry have adopted, and to explore the reporting practice of fast fashion firms concerning their environmental performance. Summary: For this study, a qualitative content analysis was conducted to analyze a sample of five corporate reports or sustainability reports of fast fashion companies for the fiscal year of 2016. The findings related to the environmental impact of fast fashion industry were addressed by the literature review, while findings on environmental initiatives and reporting practices on environmental performance of fast fashion companies were based on the content analysis of the reports. Conclusions: The environmental impact of the fast fashion industry stems from transportation, cultivation of raw materials, processing of fibers, and textile waste. Environmental initiatives taken by fast fashion companies can be categorized into product design, process design, supply chain, and customer engagement and awareness. Reporting practices of fast fashion firms on their performance are found to be focused on certain indicators; putting the environmental indicators within the context of the sustainability measures taken, it can be concluded that the measures bring about positive environmental performance outcomes for companies

The impact of recentralisation on FDI : evidence from a quasi-natural experiment

This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under Grant No. 502.02-2020.09.Although decentralised governance has been one of the most salient political regimes worldwide over the past few decades, many countries have started to realise various shortcomings associated with their decentralisation process. As a consequence, a number of central governments have attempted to pursue recentralisation reforms in order to reclaim authority from the localities. This government reform can lead to significant changes in institutional arrangements, and subsequently, may influence various aspects of socio-economic activities. However, the real impact of recentralisation reform still remains ambiguous. In this paper, we examine how recentralisation may affect foreign direct investment (FDI) inflows. We exploit the pilot recentralisation reform that temporarily abolished the intermediate legislative branches in some provinces in Vietnam as a quasi-natural experiment. The result shows that recentralisation leads to a significant reduction in FDI inflows. Our results are robust to a number of sensitivity analyses and falsification tests. Overall, our findings contribute to the literature on the determinants of FDI and provide new evidence on the real effect of recentralisation reform.Publisher PDFPeer reviewe

Bayesian Deep Net GLM and GLMM

Deep feedforward neural networks (DFNNs) are a powerful tool for functional approximation. We describe flexible versions of generalized linear and generalized linear mixed models incorporating basis functions formed by a DFNN. The consideration of neural networks with random effects is not widely used in the literature, perhaps because of the computational challenges of incorporating subject specific parameters into already complex models. Efficient computational methods for high-dimensional Bayesian inference are developed using Gaussian variational approximation, with a parsimonious but flexible factor parametrization of the covariance matrix. We implement natural gradient methods for the optimization, exploiting the factor structure of the variational covariance matrix in computation of the natural gradient. Our flexible DFNN models and Bayesian inference approach lead to a regression and classification method that has a high prediction accuracy, and is able to quantify the prediction uncertainty in a principled and convenient way. We also describe how to perform variable selection in our deep learning method. The proposed methods are illustrated in a wide range of simulated and real-data examples, and the results compare favourably to a state of the art flexible regression and classification method in the statistical literature, the Bayesian additive regression trees (BART) method. User-friendly software packages in Matlab, R and Python implementing the proposed methods are available at https://github.com/VBayesLabComment: 35 pages, 7 figure, 10 table

Fluorescent biosensor using whole cells in an inorganic translucent matrix

8 pagesInternational audienceAn optical biosensor based on vegetal cells entrapped in an inorganic translucent matrix and fluorescence detection has been developed. The biosensor uses Chlorella vulgaris immobilized in a translucent support produced from sol-gel technology. The translucence of the structure enables the algal active layer to be placed directly in contact with the optical fibers for fluorescence detection. This configuration has many advantages over the use of an opaque support because no space between the optical fibers and the active layer is required to collect fluorescence. This reagentless biosensor allows determination of diuron as an anti-PSII herbicide and its long term activity is assessed