Competition-Based Dynamic Pricing in Online Retailing: A Methodology Validated with Field Experiments
dc.contributor.author | Li, Jun | |
dc.contributor | Fisher, Marshall | |
dc.contributor | Gallino, Santiago | |
dc.date.accessioned | 2015-12-23T14:32:11Z | |
dc.date.available | 2015-12-23T14:32:11Z | |
dc.date.issued | 2017-01 | |
dc.identifier | 1265 | en_US |
dc.identifier.citation | Forthcoming at Management Science | |
dc.identifier.uri | https://hdl.handle.net/2027.42/116278 | |
dc.description.abstract | A retailer following a competition-based dynamic pricing strategy tracks competitors' price changes and then must answer the following questions: (1) Should we respond? (2) If so, respond to whom? (3) How much of a response? (4) And on which products? The answers require unbiased measures of price elasticity as well as accurate estimates of competitor significance and the extent to which consumers compare prices across retailers. There are two key challenges to quantify these factors empirically: first, the endogeneity associated with almost any type of observational data, where prices are correlated with demand shocks observable to pricing managers but not to researchers, and second, the absence of competitor sales information, which prevents efficient estimation of a full consumer-choice model. We address the first issue by conducting a field experiment with randomized prices. We resolve the second issue by exploiting the retailer's own and competitors' stockouts as a source of variation to the consumer choice set, in addition to variations in competitors' prices. We estimate an empirical model capturing consumer choices among substitutable products from multiple retailers. Based on the estimates, we propose and test a best-response pricing strategy through a carefully controlled live experiment that lasts five weeks. The experiment documents an 11 percent revenue increase while maintaining a margin above a retailer-specified target. | en_US |
dc.subject | Online Retailing | en_US |
dc.subject | Field Experiments | en_US |
dc.subject | Competition-Based Dynamic Pricing | en_US |
dc.subject | Stock-outs | en_US |
dc.subject | Consumer Choice | en_US |
dc.subject.classification | Operations and Management Science | en_US |
dc.title | Competition-Based Dynamic Pricing in Online Retailing: A Methodology Validated with Field Experiments | 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.affiliationother | University of Pennsylvania - Operations & Information Management Department | en_US |
dc.contributor.affiliationother | Dartmouth College - Tuck School of Business | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/116278/1/1265_Li.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/116278/2/1265_Li_Dec2015.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/116278/6/1265_Li_Feb2016.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/116278/8/1265_Li_Aug2016.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/116278/10/1265_Li_Nov2016.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/116278/12/1265_Li_Jan2017.pdf | |
dc.description.filedescription | Description of 1265_Li_Nov2016.pdf : November 2016 revision | |
dc.description.filedescription | Description of 1265_Li_Aug2016.pdf : August 2016 update | |
dc.description.filedescription | Description of 1265_Li_Feb2016.pdf : February 2016 revision | |
dc.description.filedescription | Description of 1265_Li_Dec2015.pdf : December 2015 revision | |
dc.description.filedescription | Description of 1265_Li_Jan2017.pdf : January 2017 revision | |
dc.owningcollname | Business, Stephen M. Ross School of - Working Papers Series |
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