Neural Networks Based Forecasting for Romanian Clothing Sector

Logica Bănică, Daniela Pirvu () and Alina Hagiu
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Daniela Pirvu: University of Pitesti

Chapter Chapter 9 in Intelligent Fashion Forecasting Systems: Models and Applications, 2014, pp 161-194 from Springer

Abstract: Abstract Clothing industry enjoys a high level of attention on all world markets, despite the prolonged economic crisis. Companies have turned to knowledge and research, processing and analyzing information obtained from the market analysis, surveys, their own and their competitor’s sales evolution, and are making use of short- and medium-term forecasts as powerful tools for the top management. The paper presents a twofold approach regarding forecasting of the financial indicators and trends related to the Romanian clothing industry, firstly at macroeconomic level, taking into account the interest of potential investors in this field, and secondly at microeconomic level, representing the analysis of the results for an operational company.

Keywords: Clothing industry; Forecasting software; Financial indicators (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-39869-8_9

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DOI: 10.1007/978-3-642-39869-8_9

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