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Forecasting Models in Research Work: Some Stances
Author Name : Sudarshan Roy
ABSTRACT
The endeavour has tried to understand forecasting models in research work. Forecasting is a technique which estimates or predicts future trends using historic data. And research is to see what everybody has seen and is think what nobody else has thought in a particular domain. Businesses may apply forecasting technique to determine how to allot their funds or strategy for expected expenses for the forthcoming period of time. And the forecasting models are such tools what are being used in businesses or research work to predict the outcomes concerning sales, demand, supply, consumer behaviour and many more. Such models are particularly advantageous in the field of sales promotion and the marketing activities. There may be several forecasting approachesfor businesses use to get the desired information.Such models may be of qualitative (Delphi Method, Market Survey, Executive Opinion, etc.)and quantitative (Time Series, Associative Models, etc.) in nature. And the research work is nothing but to see what everybody has seen and to think what nobody else has thought. Thus, the endeavour will evaluate the basic concept of forecasting techniques, various forecasting models, concept of research work, common types of forecasting models, time series model, economic model, judgmental model, the Delphi method, features of forecasting, advantages and limits of forecasting, qualitative forecasting, advantages and limitations of qualitative forecasting, quantitative forecasting, decomposition of time series, exponential smoothing, stationary time series, evaluation of forecast accuracy and its advantages.Though, the primary objectives of the endeavour are to make the researcher familiar with the forecasting models in research work, yet the study specifically has tried to make the researcher familiar with the forecasting models in research work and to discuss various forecasting models.
Keywords:Forecasting Models, Research Work, Qualitative Forecasting, Quantitative Forecasting, Smoothing, Stationary, Time Series.