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Albany, NY -- (SBWIRE) -- 07/15/2014 -- Wheel loaders are one of the major segments of construction equipment industry. These are used extensively in numerous fields ranging from building structures to mining and farming. It can perform four general tasks: scooping, digging, dumping and carrying. Loaders are used mainly for loading materials into trucks, laying pipe, clearing rubble, and digging. There are various makes and models of wheel loaders, which can be categorized into heavy wheel loader and the light wheel loader.
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The growth of the global wheel loader market has witnessed a significant incline in 2013 after plunging in previous year which was majorly due to the weakening demand in China. However, a considerable growth is anticipated in the coming years.
The key factors driving growth of the global wheel loaders industry include rising global construction expenditure, increasing urban population, accelerating global income and China’s booming construction industry. Some of the noteworthy trends and developments of this industry are the expanding rental market for wheel loaders and the development of emerging markets like India, Indonesia. However, the growth of global wheel loader industry is hindered by the strict regulatory compliance imposed on manufacturers and adverse economic condition.
The present report offers a comprehensive analysis of the worldwide wheel loader. The competition in the global market is intense with few large players viz. Caterpillar, Komatsu, Liebherr, Volvo and Liugong. The competitive landscape in China, Brazil, North America and Europe along with the company profiles of the leading players in the market is discussed in detail.
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By combining SPSS Inc.’s data integration and analysis capabilities with our relevant findings, we have predicted the future growth of the industry. We employed various significant variables that have an impact on this industry and created regression models with SPSS Base to determine the future direction of the industry. Before deploying the regression model, the relationship between several independent or predictor variables and the dependent variable was analyzed using standard SPSS output, including charts, tables and tests.
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