Research over two decades has advanced the knowledge of how to assess predictive validity. We believe this has value to information systems (IS) researchers. To demonstrate, we used a widely cited study of IS spending. In that study, price-adjusted diffusion models were proposed to explain and...

Rule-based forecasting (RBF) uses rules to combine forecasts from simple extrapolation methods. Weights for combining the rules use statistical and domain-based features of time series. RBF was originally developed, tested, and validated only on annual data. For the M3-Competition, three major...

Rule-based forecasting (RBF) is an expert system that uses features of time series to select and weight extrapolation techniques. Thus, it is dependent upon the identification of features of the time series. Judgmental coding of these features is expensive and the reliability of the ratings is...