On (Re-Scaled) Multi-Attempt Approximation of Customer Choice Model and its Application to Assortment Optimization
dc.contributor.author | Chung, Hakjin | |
dc.contributor.author | Ahn, Hyun-Soo | |
dc.contributor.author | Jasin, Stefanus | |
dc.date.accessioned | 2016-07-07T13:06:40Z | |
dc.date.available | 2016-07-07T13:06:40Z | |
dc.date.issued | 2016-06 | |
dc.identifier | 1322 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/122455 | |
dc.description.abstract | Motivated by the classic exogenous demand model and the recently developed Markov chain model, we propose a new approximation to the general customer choice model based on random utility called multi-attempt model, in which a customer may consider several substitutes before finally deciding to not purchase anything. We show that the approximation error of multi-attempt model decreases exponentially in the number of attempts. However, despite its strong theoretical performance, the empirical performance of multi-attempt model is not satisfactory. This motivates us to construct a modification of multi-attempt model called re-scaled multi-attempt model. We show that re-scaled 2-attempt model is exact when the underlying true choice model is Multinomial Logit (MNL); if, however, the underlying true choice model is not MNL, we show numerically that the approximation quality of re-scaled 2-attempt model is very close to that of Markov chain model. The key feature of our proposed approach is that the resulting approximate choice probability can be explicitly written. From a practical perspective, this allows the decision maker to use off-the-shelf solvers, or borrow existing algorithms from literature, to solve a general assortment optimization problem with a variety of real-world constraints. | en_US |
dc.subject | key word | en_US |
dc.subject.classification | Operations and Management Science | en_US |
dc.title | On (Re-Scaled) Multi-Attempt Approximation of Customer Choice Model and its Application to Assortment Optimization | en_US |
dc.type | Working Paper | en_US |
dc.subject.hlbsecondlevel | Management | en_US |
dc.subject.hlbtoplevel | Business | |
dc.contributor.affiliationum | Ross School of Business | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/122455/1/1322_Ahn.pdf | |
dc.owningcollname | Business, Stephen M. Ross School of - Working Papers Series |
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