This paper presents a mathematical programming model to reduce bias for both aggregate demand forecasts and lower echelon forecasts comprising a hierarchical forecasting system. Demand data from an actual service operation are used to illustrate the model and compare its accuracy with a standard...

This discussion paper deals with the estimation of a random coefficient model. The virtue of this approach is that it considers firm heterogeneity, which conventional SFA models do not. Applying the model to Polish farms, the results indicate that the conventional random and fixed effect models...

The authors propose new procedures for evaluating direct, indirect, and total effects in multilevel models when all relevant variables are measured at Level 1 and all effects are random. Formulas are provided for the mean and variance of the indirect and total effects and for the sampling...

Product-harm crises are among a firm s worst nightmares. Since marketing investments may be instrumental to convince consumers to purchase the firmamp;apos's products again, it is important to provide an adequate measurement of the effectiveness of these investments, especially after the crisis....

Group-level variance estimates of zero often arise when fitting multilevel or hierarchical linear models, especially when the number of groups is small. For situations where zero variances are implausible a priori, we propose a maximum penalized likelihood approach to avoid such boundary...

Renewable energy has been increasingly promoted and used to substitute non-renewable fossil-fuels, which cause negative effects on the environment. The Taiwan Statute for Renewable Energy Development has regulated and promoted renewable energy since 2009. A feed-in tariff (FIT) for renewable...