This paper aims to examine correlations in shopping situations. First, there is a certain amount of correlation between alternative choices. Specifically, the alternatives from different categories but from a same brand might be purchased together. Second, alternative choice and quantity choice...

A Bayesian method to detect structural changes in multivariate dynamic linear model is introduced and it is applied to predicting and dating the turns in business cycle. As many researchers use for business cycle analysis, the composite leading index (CLI) and the composite coincident index...

In this study, we suggest a framework to investigate and recover the actual impact of extreme online ratings and to understand biases in suppliers' expectations about box office sales, based on the nature of extreme behaviors, willingness to rate and skepticism, and information symmetry in the...

In this study, we explore the issue of how to enhance forecast of the box office sales, an all-time question for managers in the motion picture industry. The conceptual core of our approach is the expected sales. The expected sales of agents in the movie market (i.e. screen managers at supply...

It is well known that an unexpected level change in time series can cause persistent forecasting errors, depending on the change size and the underlying time series process. This relationship is demonstrated particularly with macroeconomic and financial time series. Forecasting literature...

The effect of sticker shock, price difference between reference price and shelf price, is crucial in forecasting consumer demand. In marketing literature, several papers have modeled the impact of reference prices on brand choice via the sticker shock formulation. However, the effect of sticker...

Most forecasting models often fail to produce appropriate forecasts because they are built on the assumption that data is being generated from only one stochastic process. However, in many real world problems, the time series data are generated from one stochastic process initially and then...

Different data frequency is a common problem in many research fields; therefore, it should be handled before a particular study is well under way. Many novel ideas including disaggregation techniques, which are the major interest of this study, have been suggested to mitigate the nuisances of...

This empirical paper compares the forecasting accuracy of a two-stage MNL model with that of an ordinary MNL model. The explanatory variables used in this study include individual choice set and physiological responses of the subject. Designed experiment was conducted to acquire the choice set...

This paper proposes a brand-level forecasting model that incorporates both first purchase diffusion and the replacement component in sales. The model consists of a two-stage procedure in which customers are presented with purchase occasions according to a diffusion process or replacement...