We propose a Hidden Markov Model (HMM) approach to identifying on-shelf out-of-stock (OOS) by detecting changes in sales patterns due to unobserved states of the shelf. We calibrate our model using point-of-sales (POS) data from a big-box retailer. We validate our approach using visual...

Companies in diverse industries have to decide the pricing policy of their inventory over time. This decision becomes particularly complex when customers accommodate their purchase decision in the hope of future discounts and promotions. With such uncertainty, many of these customers may end up...

In this research we propose a web-based adaptive self-explicated approach for multi-attribute preference measurement (conjoint analysis) with a large number (ten or more) of attributes. Our approach overcomes some of the limitations of previous self-explicated approaches. We developed a...

In this research we propose a web-based adaptive self-explicated approach for multi-attribute preference measurement (conjoint analysis) with a large number (ten or more) of attributes. In the empirical application reported here the proposed approach provides a substantial and significant...