ICT contribution to growth; the case of tunisia

The aim of this paper is to examine the impact of Information and Communication Technologies (ICT) on the growth of developping countries and especially on the Tunisian economy. The first part of the article summerizes the relationship between growth, productivity and ICT. We show that under some necessary conditions ICT may boost the growth in the developping countries. In the second part of the article, we estimate the contribution of ICT to the growth of Tunisia due to ICT diffusion and adoption. We compare our econometric estimation to the results obtained in France and United States.croissance économique, TIC, productivité, développement économique, Tunisie.

Energy Consumption, Economic Growth and CO2 Emissions in Middle East and North African Countries

This article extends the recent findings of Liu (2005), Ang (2007), Apergis et al. (2009) and Payne (2010) by implementing recent bootstrap panel unit root tests and cointegration techniques to investigate the relationship between carbon dioxide emissions, energy consumption, and real GDP for 12 Middle East and North African Countries (MENA) over the period 1981–2005. Our results show that in the long-run energy consumption has a positive significant impact on CO2 emissions. More interestingly, we show that real GDP exhibits a quadratic relationship with CO2 emissions for the region as a whole. However, although the estimated long-run coefficients of income and its square satisfy the EKC hypothesis in most studied countries, the turning points are very low in some cases and very high in other cases, hence providing poor evidence in support of the EKC hypothesis. Thus, our findings suggest that not all MENA countries need to sacrifice economic growth to decrease their emission levels as they may achieve CO2 emissions reduction via energy conservation without negative long-run effects on economic growth.Environmental Kuznets Curve, carbon dioxide emissions, energy consumption, growth

Regional disparities and ICTs diffusion in Tunisia

The aim of this article consists in showing in what the emergence of new generation of information and communication technologies can be a worsening factor of imbalances between urban zones and rural zones and contribute to a thickening of the urban zones. Contrary to presupposed theoretical praising the capacity of these technologies to rebalance the development and to reverse the location of economic agents with their location. We will show in what these technologies could lead to a greater urban concentration in the less developed Countries (LDC’s). Indeed, four complementary explanatory factors are explained and illustrated in the case of Tunisia. The territorial dynamics engaged by the concentration of industries in the cities finds a second breath with the ICT.disparités spatiales, fracture numérique, Technologies de l’information et de la communication, Exode rural, localisation spatiale.

Usage capacities of ICTs in emergent economies

This contribution to the study of the factors’ allocation modes of Information and Communication Technologies (ICT) by firms of emerging economies gets over the dual approach concentrated on the lack of uses of equipment and on their consequences. Authors focus on the dynamics of use, as opposed to the dynamics of adoption. The main assumption of this contribution is that the differentials of competitiveness related to ICT are less dependant on the level of the investments than on the level of their use. This approach always introduces notions like individual learning, cooperation dynamics, general purpose technologies, information and coordination levels.Capacité d’usage, capacité d’absorption, technologies de l’information et de la communication, innovation organisationnelle, technologies génériques, développement économique

The missed link between adoption and usage of ICT in the south Mediterranean countries

The main assumption of the paper is that the differentials of competitiveness related to ICT are nowadays less dependant on the level of the investments than on the level of their use. ICT are generally studied within the framework of developed economies and less of their impact on developing and emerging economies. Our study based upon the observation of 408 firms over four Mediterranean countries shows that the main problem is linked to the management of these firms.capacité d’usage, Technologies de l’Information et de la Communication, innovation organisationnelle, technologies génériques, développement Economique.

Les effets des technologies de l'information et de communication sur la croissance économique; le cas de la Tunisie

The aim of this paper is to examine the impact of Information and Communication Technologies (ICT) on the growth of developping countries and especially on the Tunisian economy. The first part of the article summerizes the relationship between growth, productivity and ICT. We show that under some necessary conditions ICT may boost the growth in the developping countries. In the second part of the article, we estimate the contribution of ICT to the growth of Tunisia due to ICT diffusion and adoption. We compare our econometric estimation to the results obtained in France and United States

Testing the causality between electricity consumption, energy use and education in Africa

We investigate the existence of causal relationships between energy consumption and education (enrollment in primary secondary and higher education) for a sample of 16 African countries over the period 1971-2010 (according to availability of countries' data). We use the panel-data approach of Kónya (2006), which is based on SUR systems and Wald tests with country specific bootstrap critical values. Our results show that education and energy use are strongly linked in Africa. There is bidirectional causality between primary, secondary and higher education and energy use for several countries. Moreover, electricity consumption plays a crucial role in the energy-education links in Africa.http://deepblue.lib.umich.edu/bitstream/2027.42/132984/1/wp1084.pd

A chronological exploration of the evolution of housing typologies in Gulf cities

This paper traces the evolution of housing typologies in four major cities in the Gulf region, namely Doha, Dubai, Abu Dhabi and Manama. The study reviews the formation and historical events in the region, which had a significant impact on new social as well as economic realities and consequently evolving housing types during the last two centuries. The methodological approach is based on reviewing a number of case studies representing local housing typologies throughout distinctive historic periods which were categorized in four periods: the post-nomadic, traditional, modern, and contemporary. The main objective is to identify the process of transformation by applying a comparative assessment of the different periods in order to examine continuities or ruptures between them. Thus, particular layout elements were analysed and compared. Conclusions are drawn to underline contemporary challenges while offering projections for future housing typologies in the selected cities and other similar ones

Computer Numerical Control CNC Machine Health Prediction using ‎Multi-domain Feature Extraction and Deep Neural Network Regression

Tool wear monitoring has become more vital in intelligent production to enhance Computer Numerical Control CNC machine health state. Multidomain features may effectively define tool wear status and help tool wear prediction. Prognostics and health management (PHM) plays a vital role in condition-based maintenance (CBM) to prevent rather than detect malfunctions in machinery. This has great advantage of saving costs of fault repair including human effort, financial costs as long as power and energy consumption. The huge evolution of Industrial Internet of Things (IIOT) and industrial big data analytics has made Deep Learning a growing field of research. The PHM society has held many competitions including PHM10 concerning CNC milling machine cutters data for tool wear prediction The purpose of this paper is to predict tool wear of CNC cutters and. We adopted a multi-domain feature extraction method for health statement of the cutters. and a deep neural network DNN method for tool wear prediction