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889 result(s) for "Globalization Forecasting."
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Geopolitical Economy
Geopolitical Economy radically reinterprets the historical evolution of the world order, as a multi-polar world emerges from the dust of the financial and economic crisis. Radhika Desai offers a radical critique of the theories of US hegemony, globalisation and empire which dominate academic international political economy and international relations, revealing their ideological origins in successive failed US attempts at world dominance through the dollar. Desai revitalizes revolutionary intellectual traditions which combine class and national perspectives on ‘the relations of producing nations’. At a time of global upheavals and profound shifts in the distribution of world power, Geopolitical Economy forges a vivid and compelling account of the historical processes which are shaping the contemporary international order.
Vector-borne diseases and climate change: a European perspective
Climate change has already impacted the transmission of a wide range of vector-borne diseases in Europe, and it will continue to do so in the coming decades. Climate change has been implicated in the observed shift of ticks to elevated altitudes and latitudes, notably including the Ixodes ricinus tick species that is a vector for Lyme borreliosis and tick-borne encephalitis. Climate change is also thought to have been a factor in the expansion of other important disease vectors in Europe: Aedes albopictus (the Asian tiger mosquito), which transmits diseases such as Zika, dengue and chikungunya, and Phlebotomus sandfly species, which transmits diseases including Leishmaniasis. In addition, highly elevated temperatures in the summer of 2010 have been associated with an epidemic of West Nile Fever in Southeast Europe and subsequent outbreaks have been linked to summer temperature anomalies. Future climate-sensitive health impacts are challenging to project quantitatively, in part due to the intricate interplay between non-climatic and climatic drivers, weather-sensitive pathogens and climate-change adaptation. Moreover, globalisation and international air travel contribute to pathogen and vector dispersion internationally. Nevertheless, monitoring forecasts of meteorological conditions can help detect epidemic precursors of vector-borne disease outbreaks and serve as early warning systems for risk reduction.
Autoregressive models in environmental forecasting time series: a theoretical and application review
Though globalization, industrialization, and urbanization have escalated the economic growth of nations, these activities have played foul on the environment. Better understanding of ill effects of these activities on environment and human health and taking appropriate control measures in advance are the need of the hour. Time series analysis can be a great tool in this direction. ARIMA model is the most popular accepted time series model. It has numerous applications in various domains due its high mathematical precision, flexible nature, and greater reliable results. ARIMA and environment are highly correlated. Though there are many research papers on application of ARIMA in various fields including environment, there is no substantial work that reviews the building stages of ARIMA. In this regard, the present work attempts to present three different stages through which ARIMA was evolved. More than 100 papers are reviewed in this study to discuss the application part based on pure ARIMA and its hybrid modeling with special focus in the field of environment/health/air quality. Forecasting in this field can be a great contributor to governments and public at large in taking all the required precautionary steps in advance. After such a massive review of ARIMA and hybrid modeling involving ARIMA in the fields including or excluding environment/health/atmosphere, it can be concluded that the combined models are more robust and have higher ability to capture all the patterns of the series uniformly. Thus, combining several models or using hybrid model has emerged as a routinized custom.
Exploring the consequences of judgmental and quantitative forecasting on firms' competitive performance in supply chains
PurposeThe purpose of this study is to examine the impacts of different forecasting methods (judgmental, quantitative and mixed forecasting) on firms' supply chains and competitive performance.Design/methodology/approachWorking with three groups of manufacturing companies, we explore the consequences of judgmental, quantitative and mixed forecasting methods on firms' competitive performance in supply chains. The validity of constructs and path relationships was examined using structural equation modeling (SEM).FindingsOur findings indicate that supply chain efficiency influences both cost reduction and customer satisfaction. In addition, the three dimensions of supply chain performance are shown to be direct antecedents of competitive performance. Our empirical results reveal that although all studied forecasting methods meaningfully influence supply chain performance, the mixed method, compared to the other two methods, has greater capabilities to enhance supply chain performance.Originality/valueThis research provides originality and insight into supply chain practices through forecasting methods to improve competitive performance.
Construction Sector Contribution to Economic Stability: Malaysian GDP Distribution
The construction sector exerts an exceptional impact on economic development all over the world. Adequate buildings and infrastructures made by the construction sector ensure that a country reaches certain targets like social development, industrialization, freight transportation, sustainable development, and urbanization. This study aims to determine the construction sector’s connectivity with other sectors through complex linkages that contribute immensely to the economy and gross domestic product (GDP). The data were collected from the Department of Statistics Malaysia and the World Bank from the year 1970 to 2019, and the Pearson correlation test, the cointegration test, and the Granger causality test were conducted. The vector error correction model (VECM) was created for short-term and long-term equilibrium analysis and impulse response function (IRF) was performed to study construction industry behavior. Afterwards, the forecasting was done for the year 2020 to 2050 of the Malaysian economy and GDP for the required sectors. It was revealed that some sectors, such as agriculture and services, have forward linkages while other sectors, such as manufacturing and mining, are independent of construction sector causality, which signifies the behavior of the contributing sectors when a recession occurs, hence generating significant revenue. The Malaysian economy is moving towards sustainable production with more emphasis on the construction sector. The outcome can be used as a benchmark by other countries to achieve sustainable development. The significance of this study is its usefulness for experts all over the world in terms of allocating resources to make the construction sector a sustainable sector after receiving a shock. A sustainable conceptual framework has been suggested for global application that shows the factors involved in the growth of the construction industry to ensure its sustainable development with time.