(which are panel data approaches) are applied to model housing price forecasting function in Tehran's 20 different zones … forecasting problems in environments which are: uncertain, complex, and faced with a lack of proper data. Moreover, it is found … in actual data sets with respect to housing price forecasting. Moreover, the proposed approach can be applied to similar …

integrated moving average (ARIMA) forecasting method is utilized. Findings – The results of the ARIMA modeling clearly indicate …

then tested for its in- and out-of-sample forecasting ability. Findings – The results show that the model predicts the … set in binary forecasting models can produce useful predictions of changes in upward and downward movements of US house … as a sentiment indicator in binary forecasting models to predict turning points in the housing market.  …

utilise systems‐based forecasting to conduct an evaluation of inventory and forecasting systems being used to support its … – Analysis of the current inventory and forecasting system suggests a possible lack of forecasting precision. Current non …‐specific formulation of forecasting techniques implied several of the cost driver's demands were being miscalculated. This lack of …

. The authors compared exponential smoothing forecasting method to a word-of-mouth diffusion model which makes sense in a … production generated by an insufficient forecasting launched 40 days before customer orders). Research limitations … to use a forecasting model which is not currently used by the professionals during a sanitary crisis period. This model …

development initiative, the company has identified forecasting accuracy as of strategic importance to its operational efficiency …. The purpose of this paper is to undertake an evaluation of current month-to-date forecasting utilized by Virgin Atlantic … forecasting models is undertaken using error accuracy measures. Data in the form of historical chargeable weight over a seven …