{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/87956"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/87956","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Dynamic pricing with reference price effects","abstract":"This dissertation mainly focuses on the models and the corresponding dynamic pricing problems that incorporate reference price effects, a concept developed in economics and marketing literature that try to capture the dependency of consumers purchasing behavior on past prices. Conceptually, reference price is a price expectation consumers develop from their observations of historical prices. Since it can not be physically observed, various models have been proposed to operationalize its formation. We empirically compare some of the models in the literature and extend the literature by proposing a new reference price model. In addition, we present analysis on the dynamic pricing problems under these models assuming consumers are loss/gain neutral or loss-averse. We find that constant pricing strategies are a robust solution to the problem regardless of which reference price models one may choose. Empirical evidences, however, indicate that loss/gain neutral or loss-averse behavior may not be a universal phenomenon. We analyze the dynamic pricing problem when consumers exhibit gain-seeking behavior. In sharp contrast to the loss-averse case, even myopic pricing strategies can result in complicated cyclic price paths. We show for a special case that a cyclic skimming pricing strategy is optimal and provide conditions to guarantee the optimality of high-low pricing strategies. With the understanding of the qualitative behavior of the optimal pricing strategies under various settings, we develop efficient algorithms to compute the optimal prices in both loss-averse and gain-seeking case. We demonstrate the efficiency and robustness of our algorithms by applying them to a practical problem with real data. Finally, we extend the above considered single-product setting to multi-product setting and analyze the corresponding dynamic pricing problems.","abstract_html":"This dissertation mainly focuses on the models and the corresponding dynamic pricing problems that incorporate reference price effects, a concept developed in economics and marketing literature that try to capture the dependency of consumers purchasing behavior on past prices. Conceptually, reference price is a price expectation consumers develop from their observations of historical prices. Since it can not be physically observed, various models have been proposed to operationalize its formation. We empirically compare some of the models in the literature and extend the literature by proposing a new reference price model. In addition, we present analysis on the dynamic pricing problems under these models assuming consumers are loss/gain neutral or loss-averse. We find that constant pricing strategies are a robust solution to the problem regardless of which reference price models one may choose. Empirical evidences, however, indicate that loss/gain neutral or loss-averse behavior may not be a universal phenomenon. We analyze the dynamic pricing problem when consumers exhibit gain-seeking behavior. In sharp contrast to the loss-averse case, even myopic pricing strategies can result in complicated cyclic price paths. We show for a special case that a cyclic skimming pricing strategy is optimal and provide conditions to guarantee the optimality of high-low pricing strategies. With the understanding of the qualitative behavior of the optimal pricing strategies under various settings, we develop efficient algorithms to compute the optimal prices in both loss-averse and gain-seeking case. We demonstrate the efficiency and robustness of our algorithms by applying them to a practical problem with real data. Finally, we extend the above considered single-product setting to multi-product setting and analyze the corresponding dynamic pricing problems.","abstract_has_math":false,"creators":["Hu, Zhenyu"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Industrial Engineering","degree_department":null,"school":null,"contributors":["Chen, Xin","Olshevsky, Alex","Petruzzi, Nicholas C.","Wang, Qiong"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-29T20:37:38Z","date_published":"2015-09-29T20:37:38Z","updated_at":"2026-07-22T22:26:31Z","subjects":["dynamic pricing","reference price effects"],"languages":["en"],"rights":["Copyright 2015 Zhenyu Hu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/87956","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Chen, Xin","Olshevsky, Alex","Petruzzi, Nicholas C.","Wang, Qiong"]},{"key":"dc:creator","label":"Author","values":["Hu, Zhenyu"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-29T20:37:38Z","2015-08","2015-06-04","2015-8"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Industrial Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["dynamic pricing","reference price effects"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2015 Zhenyu Hu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/87956"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This dissertation mainly focuses on the models and the corresponding dynamic pricing problems that incorporate reference price effects, a concept developed in economics and marketing literature that try to capture the dependency of consumers purchasing behavior on past prices. Conceptually, reference price is a price expectation consumers develop from their observations of historical prices. Since it can not be physically observed, various models have been proposed to operationalize its formation. We empirically compare some of the models in the literature and extend the literature by proposing a new reference price model. In addition, we present analysis on the dynamic pricing problems under these models assuming consumers are loss/gain neutral or loss-averse. We find that constant pricing strategies are a robust solution to the problem regardless of which reference price models one may choose. Empirical evidences, however, indicate that loss/gain neutral or loss-averse behavior may not be a universal phenomenon. We analyze the dynamic pricing problem when consumers exhibit gain-seeking behavior. In sharp contrast to the loss-averse case, even myopic pricing strategies can result in complicated cyclic price paths. We show for a special case that a cyclic skimming pricing strategy is optimal and provide conditions to guarantee the optimality of high-low pricing strategies. With the understanding of the qualitative behavior of the optimal pricing strategies under various settings, we develop efficient algorithms to compute the optimal prices in both loss-averse and gain-seeking case. We demonstrate the efficiency and robustness of our algorithms by applying them to a practical problem with real data. Finally, we extend the above considered single-product setting to multi-product setting and analyze the corresponding dynamic pricing problems.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2015-09-29 without embargo terms","The student, Zhenyu Hu, accepted the attached license on 2015-06-02 at 13:50.","The student, Zhenyu Hu, submitted this Dissertation for approval on 2015-06-02 at 13:52.","This Dissertation was approved for publication on 2015-06-04 at 14:31.","DSpace SAF Submission Ingestion Package generated from Vireo submission #8257 on 2015-09-29 at 13:21:25","Made available in DSpace on 2015-09-29T20:37:38Z (GMT). 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Since it can not be physically observed, various models have been proposed to operationalize its formation. We empirically compare some of the models in the literature and extend the literature by proposing a new reference price model. In addition, we present analysis on the dynamic pricing problems under these models assuming consumers are loss/gain neutral or loss-averse. We find that constant pricing strategies are a robust solution to the problem regardless of which reference price models one may choose. Empirical evidences, however, indicate that loss/gain neutral or loss-averse behavior may not be a universal phenomenon. We analyze the dynamic pricing problem when consumers exhibit gain-seeking behavior. In sharp contrast to the loss-averse case, even myopic pricing strategies can result in complicated cyclic price paths. We show for a special case that a cyclic skimming pricing strategy is optimal and provide conditions to guarantee the optimality of high-low pricing strategies. With the understanding of the qualitative behavior of the optimal pricing strategies under various settings, we develop efficient algorithms to compute the optimal prices in both loss-averse and gain-seeking case. We demonstrate the efficiency and robustness of our algorithms by applying them to a practical problem with real data. Finally, we extend the above considered single-product setting to multi-product setting and analyze the corresponding dynamic pricing problems.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2015-09-29 without embargo terms","The student, Zhenyu Hu, accepted the attached license on 2015-06-02 at 13:50.","The student, Zhenyu Hu, submitted this Dissertation for approval on 2015-06-02 at 13:52.","This Dissertation was approved for publication on 2015-06-04 at 14:31.","DSpace SAF Submission Ingestion Package generated from Vireo submission #8257 on 2015-09-29 at 13:21:25","Made available in DSpace on 2015-09-29T20:37:38Z (GMT). No. of bitstreams: 2 HU-DISSERTATION-2015.pdf: 1477783 bytes, checksum: ff7cd040798c4a472b1cf15e18569f09 (MD5) LICENSE.txt: 4206 bytes, checksum: 1bb1ebe7094aaab6fc780dd1ab408926 (MD5) Previous issue date: 2015-06-04"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/87956"],"dc:language":["en"],"dc:rights":["Copyright 2015 Zhenyu Hu"],"dc:subject":["dynamic pricing","reference price effects"],"dc:title":["Dynamic pricing with reference price effects"],"dc:type":["text"],"thesis:degree_discipline":["Industrial Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:31Z"}