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Special Issue on Simple Versus Complex Forecasting

Journal of Business Research

Volume 68, Issue 8, Pages 1657-1818 (August 2015)

  1. Simple versus complex forecasting: The evidence. 1678-1685
    Green, K. C., & Armstrong, J. S., http://dx.doi.org/10.1016/j.jbusres.2015.03.026
  2. Golden Rule of Forecasting: Be conservative. 1717-1731
    Armstrong, J. S., Green, K. C., & Graefe, A., http://dx.doi.org/10.1016/j.jbusres.2015.03.031
  3. Is there a Golden Rule? 1742-1745
    Fildes, R., & Petropoulos, F., http://dx.doi.org/10.1016/j.jbusres.2015.01.059
  4. Is a more liberal approach to conservatism needed in forecasting? 1753-1754
    Goodwin, P., http://dx.doi.org/10.1016/j.jbusres.2015.01.060
  5. The Golden Rule of Forecasting: Objections, refinements, and enhancements. 1702-1704
    Soyer, E., & Hogarth, R. M., http://dx.doi.org/10.1016/j.jbusres.2015.03.029
  6. Conservative forecasting with the damped trend. 1739-1741
    Gardner Jr., E. S., http://dx.doi.org/10.1016/j.jbusres.2015.03.033
  7. Golden rule of forecasting rearticulated: Forecast unto others as you would have them forecast unto you. 1768-1771
    Green, K. C., Armstrong, J. S., & Graefe, A., http://dx.doi.org/10.1016/j.jbusres.2015.03.036
  8. The bias bias. 1772-1784
    Brighton, H., & Gigerenzer, G., http://dx.doi.org/10.1016/j.jbusres.2015.01.061
  9. Simple versus complex selection rules for forecasting many time series. 1692-1701
    Fildes, R., & Petropoulos, F., http://dx.doi.org/10.1016/j.jbusres.2015.03.028
  10. Forecasting new product trial with analogous series. 1732-1738
    Wright, M. J., & Stern, P., http://dx.doi.org/10.1016/j.jbusres.2015.03.032
  11. Decomposition of time-series by level and change. 1755-1758
    Tessier, T. H., & Armstrong, J. S., http://dx.doi.org/10.1016/j.jbusres.2015.03.035
  12. Improving forecasts using equally weighted predictors. 1792-1799
    Graefe, A., http://dx.doi.org/10.1016/j.jbusres.2015.03.038
  13. Picking profitable investments: The success of equal weighting in simulated venture capitalist decision making. 1705-1716
    Woike, J. K., Hoffrage, U., & Petty, J. S., http://dx.doi.org/10.1016/j.jbusres.2015.03.030
  14. Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping. 1746-1752
    Syntetos, A. A., Babai, M. Z., & Gardner Jr., E. S., http://dx.doi.org/10.1016/j.jbusres.2015.03.034
  15. Relative performance of methods for forecasting special events. 1785-1791
    Nikolopoulos, K., Litsa, A., Petropoulos, F., Bougioukos, V., & Khammash, M., http://dx.doi.org/10.1016/j.jbusres.2015.03.037
  16. Improving forecasts for noisy geographic time series. 1810-1818
    Huddleston, S. H., Porter, J. H., & Brown, D. E., http://dx.doi.org/10.1016/j.jbusres.2015.03.040
  17. When simple alternatives to Bayes formula work well: Reducing the cognitive load when updating probability forecasts. 1686-1691
    Goodwin, P., http://dx.doi.org/10.1016/j.jbusres.2015.03.027
  18. Collective wisdom: Methods of confidence interval aggregation. 1759-1767
    Lyon, A., Wintle, B. C., & Burgman, M., http://dx.doi.org/10.1016/j.jbusres.2014.08.012
  19. Communicating forecasts: The simplicity of simulated experience. 1800- 1809
    Hogarth, R. M., & Soyer, E., http://dx.doi.org/10.1016/j.jbusres.2015.03.039