Optimizing Offline Product Design and Online Assortment Policy: Measuring the Relative Impact of Each Decision

References

• Abhishek KG (2023) 16 awesome examples of e-commerce personalization from top brands. Accessed September 29, 2023, https://web.archive.org/web/20231025093319/https:/www.moengage.com/blog/lessons-from-5-ecommerce-companies-acing-personalization/.Google Scholar
• Agrawal S, Avadhanula V, Goyal V, Zeevi A (2019) MNL-bandit: A dynamic learning approach to assortment selection. Oper. Res. 67(5):1453–1485.Link, Google Scholar
• Altug M, Aydinliyim T (2016) Counteracting strategic purchase deferrals: The impact of online retailers’ return policy decisions. Manufacturing Service Oper. Management 18(3):376–392.Link, Google Scholar
• Bai Y, El Housni O, Rusmevichientong P, Topaloglu H (2022) Coordinated inventory stocking and assortment personalization. Preprint, submitted December 11, http://dx.doi.org/10.2139/ssrn.4297618.Google Scholar
• Ball MO, Queyranne M (2009) Toward robust revenue management: Competitive analysis of online booking. Oper. Res. 57(4):950–963.Link, Google Scholar
• Bernstein F, Kök AG, Xie L (2015) Dynamic assortment customization with limited inventories. Manufacturing Service Oper. Management 17(4):538–553.Link, Google Scholar
• Besbes O, Zeevi A (2011) On the minimax complexity of pricing in a changing environment. Oper. Res. 59(1):66–79.Link, Google Scholar
• Caro F, Gallien J (2007) Dynamic assortment with demand learning for seasonal consumer goods. Management Sci. 53(2):276–292.Link, Google Scholar
• Chen N, Gallego G (2022) A primal–dual learning algorithm for personalized dynamic pricing with an inventory constraint. Math. Oper. Res. 47(4):2585–2613.Link, Google Scholar
• Chen X, Wang Y, Zhou Y (2018) An optimal policy for dynamic assortment planning under uncapacitated multinomial logit models. Preprint, submitted May 12, https://arxiv.org/abs/1805.04785.Google Scholar
• Chen X, Feldman J, Jung SH, Kouvelis P (2021) Approximation schemes for the joint inventory selection and online resource allocation problem. Preprint, submitted November 8, http://dx.doi.org/10.2139/ssrn.3956503.Google Scholar
• China Purchasing Agent (2021) Shipping from China to Amazon FBA: The ultimate guide 2022. Accessed January 1, 2022, https://chinapurchasingagent.com/shipping-from-china-to-amazon-fba/.Google Scholar
• Davis S, Hagerty M, Gerstner E (1998) Return policies and the optimal level of “hassle”. J. Econom. Bus. 50(5):445–460.Crossref, Google Scholar
• Dong L, Kouvelis P, Tian Z (2009) Dynamic pricing and inventory control of substitute products. Manufacturing Service Oper. Management 11(2):317–339.Link, Google Scholar
• Elmaghraby W, Keskinocak P (2003) Dynamic pricing in the presence of inventory considerations: Research overview, current practices, and future directions. Management Sci. 49(10):1287–1309.Link, Google Scholar
• Feng Q, Luo S, Zhang D (2014) Dynamic inventory–pricing control under backorder: Demand estimation and policy optimization. Manufacturing Service Oper. Management 16(1):149–160.Link, Google Scholar
• Ferreira KJ, Simchi-Levi D, Wang H (2018) Online network revenue management using Thompson sampling. Oper. Res. 66(6):1586–1602.Link, Google Scholar
• Gallego G, Wang R (2014) Multiproduct price optimization and competition under the nested logit model with product-differentiated price sensitivities. Oper. Res. 62(2):450–461.Link, Google Scholar
• Gallego G, Iyengar G, Phillips R, Dubey A (2004) Managing flexible products on a network. Working paper, Columbia University, New York.Google Scholar
• Golrezaei N, Nazerzadeh H, Rusmevichientong P (2014) Real-time optimization of personalized assortments. Management Sci. 60(6):1532–1551.Link, Google Scholar
• Gong X, Goyal V, Iyengar GN, Simchi-Levi D, Udwani R, Wang S (2022) Online assortment optimization with reusable resources. Management Sci. 68(7):4772–4785.Link, Google Scholar
• Hess JD, Chu W, Gerstner E (1996) Controlling product returns in direct marketing. Marketing Lett. 7(4):307–317.Crossref, Google Scholar
• Hopp WJ, Xu X (2005) Product line selection and pricing with modularity in design. Manufacturing Service Oper. Management 7(3):172–187.Link, Google Scholar
• Jasin S, Kumar S (2012) A re-solving heuristic with bounded revenue loss for network revenue management with customer choice. Math. Oper. Res. 37(2):313–345.Link, Google Scholar
• Keskin NB, Li Y, Song J-S (2022) Data-driven dynamic pricing and ordering with perishable inventory in a changing environment. Management Sci. 68(3):1938–1958.Link, Google Scholar
• Li H, Huh WT (2011) Pricing multiple products with the multinomial logit and nested logit models: Concavity and implications. Manufacturing Service Oper. Management 13(4):549–563.Link, Google Scholar
• Li H, Webster S (2017) Optimal pricing of correlated product options under the paired combinatorial logit model. Oper. Res. 65(5):1215–1230.Link, Google Scholar
• Li G, Rusmevichientong P, Topaloglu H (2015) The d-level nested logit model: Assortment and price optimization problems. Oper. Res. 63(2):325–342.Link, Google Scholar
• Liu Q, Van Ryzin G (2008) On the choice-based linear programming model for network revenue management. Manufacturing Service Oper. Management 10(2):288–310.Link, Google Scholar
• Ma W, Simchi-Levi D (2017) Online resource allocation under arbitrary arrivals: Optimal algorithms and tight competitive ratios. Preprint, submitted June 20, http://dx.doi.org/10.2139/ssrn.2989332.Google Scholar
• Ma Y, Rusmevichientong P, Sumida M, Topaloglu H (2020) An approximation algorithm for network revenue management under nonstationary arrivals. Oper. Res. 68(3):834–855.Link, Google Scholar
• Méndez-Díaz I, Miranda-Bront JJ, Vulcano G, Zabala P (2014) A branch-and-cut algorithm for the latent-class logit assortment problem. Discrete Appl. Math. 164(1):246–263.Crossref, Google Scholar
• Ni J, Neslin SA, Sun B (2012) Database submission—The ISMS durable goods data sets. Marketing Sci. 31(6):1008–1013.Link, Google Scholar
• Oram A (2023) Prime big deal days: Everything you need to know about Amazon’s October Prime Day. Accessed September 23, 2023, https://www.cnet.com/deals/october-prime-day-2023/.Google Scholar
• Rusmevichientong P, Sumida M, Topaloglu H (2020) Dynamic assortment optimization for reusable products with random usage durations. Management Sci. 66(7):2820–2844.Link, Google Scholar
• Su X (2009) Consumer returns policies and supply chain performance. Manufacturing Service Oper. Management 11(4):595–612.Link, Google Scholar
• Talluri K, Van Ryzin GJ (1998) An analysis of bid-price controls for network revenue management. Management Sci. 44(11-part-1):1577–1593.Link, Google Scholar
• Talluri K, Van Ryzin GJ (1999) A randomized linear programming method for computing network bid prices. Transportation Sci. 33(2):207–216.Link, Google Scholar
• Topaloglu H (2013) Joint stocking and product offer decisions under the multinomial logit model. Production Oper. Management 22(5):1182–1199.Crossref, Google Scholar
• Ülkü MA, Gürler Ü (2018) The impact of abusing return policies: A newsvendor model with opportunistic consumers. Internat. J. Production. Econom. 203(September):124–133.Crossref, Google Scholar
• Ulu C, Honhon D, Alptekinoğlu A (2012) Learning consumer tastes through dynamic assortments. Oper. Res. 60(4):833–849.Link, Google Scholar
• Williams T (2023) Using Amazon return data to your advantage and reducing return rates. Accessed September 28, 2023, https://www.envisionhorizons.com/blog/using-amazon-return-data-to-your-advantage-and-reducing-return-rates.Google Scholar
• Zhang H, Rusmevichientong P, Topaloglu H (2018) Multiproduct pricing under the generalized extreme value models with homogeneous price sensitivity parameters. Oper. Res. 66(6):1559–1570.Link, Google Scholar