A Behavioral Study of Assortment Planning
References
- (2009) Anchoring effects: Evidence from art auctions. Amer. Econom. Rev. 99(3):1027–1039.Crossref, Google Scholar
- (1985) Discrete Choice Analysis: Theory and Application to Travel Demand (MIT Press, Cambridge, MA).Google Scholar
- (2001) Reducing assortment: An attribute-based approach. J. Marketing 65(3):50–63.Crossref, Google Scholar
- (2012) Managers and students as newsvendors. Management Sci. 58(12):2225–2233.Link, Google Scholar
- (2005) Retail assortment planning in the presence of consumer search. Manufacturing Service Oper. Management 7(4):330–346.Link, Google Scholar
- (1996) Versions of the sign test in the presence of ties. Biometrics 52(4):1242–1251.Crossref, Google Scholar
- (2000) Building store loyalty through store brands. J. Marketing Res. 37(3):281–291.Crossref, Google Scholar
- (2017) How P&G and American Express are approaching AI. Harvard Bus. Rev. (March 31), https://hbr.org/2017/03/how-pg-and-american-express-are-approaching-ai.Google Scholar
- (2018) What’s your cognitive strategy? MIT Sloan Management Rev. 59(4):19–23.Google Scholar
- (2016) A “wide” variety: Effects of horizontal versus vertical display on assortment processing, perceived variety, and choice. J. Marketing Res. 53(5):682–698.Crossref, Google Scholar
- (2020) People reject algorithms in uncertain decision domains because they have diminishing sensitivity to forecasting error. Psych. Sci. 31(10):1302–1314.Crossref, Google Scholar
- (2019) The Handbook of Behavioral Operations, Wiley Series in Operations Research and Management Science (Wiley, Hoboken, NJ).Google Scholar
- (2017) Modeling strategic behavior in the competitive newsvendor problem: An experimental investigation. Production Oper. Management 26(7):1383–1398.Crossref, Google Scholar
- (2012) Which products should you stock? Harvard Bus. Rev. (November), https://hbr.org/2012/11/which-products-should-you-stock.Google Scholar
- (2006) Product variety and inventory decisions under a locational consumer choice model. Management Sci. 52(10):1528–1543.Link, Google Scholar
- (2005) Regular quantal response equilibrium. Experiment. Econom. 8(4):347–367.Crossref, Google Scholar
- (2013) Data collection in a flat world: The strengths and weaknesses of Mechanical Turk samples. J. Behav. Decision Making 26(3):213–224.Crossref, Google Scholar
- (2010) Reference dependence in multilocation newsvendor models: A structural analysis. Management Sci. 56(11):1891–1910.Link, Google Scholar
- (2011) The online laboratory: Conducting experiments in a real labor market. Experiment. Econom. 14(3):399–425.Crossref, Google Scholar
- (2000) When choice is demotivating: Can one desire too much of a good thing? J. Personality Soc. Psych. 79(6):995–1006.Crossref, Google Scholar
- (1979) Prospect theory: An analysis of decision under risk. Econometrica 47(2):263–292.Crossref, Google Scholar
- (2020) Field experiment on the profit implications of merchants’ discretionary power to override data-driven decision-making tools. Management Sci. 66(11):5182–5190.Link, Google Scholar
- (2011) Optimal and competitive assortments with endogenous pricing under hierarchical consumer choice models. Management Sci. 57(9):1546–1563.Link, Google Scholar
- (2015) Assortment planning: Review of literature and industry practice. Agrawal N, Smith S, eds. Retail Supply Chain Management, International Series in Operations Research & Management Science, vol. 223 (Springer, Boston), 175–236.Crossref, Google Scholar
- (2017) Task decomposition and newsvendor decision making. Management Sci. 63(10):3226–3245.Link, Google Scholar
- (2018) Running behavioral operations experiments using Amazon’s Mechanical Turk. Production Oper. Management 27(5):973–989.Crossref, Google Scholar
- (2014) Judgmental forecasting: Cognitive reflection and decision speed. Production Oper. Management 23(7):1146–1160.Crossref, Google Scholar
- (2010) Running experiments on Amazon Mechanical Turk. Judgment Decision Making 5(5):411–419.Crossref, Google Scholar
- (2017) Beyond the Turk: Alternative platforms for crowdsourcing behavioral research. J. Experiment. Soc. Psych. 70:153–163.Crossref, Google Scholar
- (2019) Behavioral ordering, competition and profits: An experimental investigation. Production Oper. Management 28(9):2242–2258.Crossref, Google Scholar
- (2011) Incorporating context effects into a choice model. J. Marketing Res. 48(4):767–780.Crossref, Google Scholar
- (2014) Observation bias: The impact of demand censoring on newsvendor level and adjustment behavior. Management Sci. 60(5):1334–1345.Link, Google Scholar
- (2021) How AI can help with assortment planning. Progressive Grocer 100(1):76–80.Google Scholar
- (1988) Status quo bias in decision making. J. Risk Uncertainty 1(1):7–59.Crossref, Google Scholar
- (2000) Decision bias in the newsvendor problem with a known demand distribution: Experimental evidence. Management Sci. 46(3):404–420.Link, Google Scholar
- (1989) Choice based on reasons: The case of attraction and compromise effects. J. Consumer Res. 16(2):158–174.Crossref, Google Scholar
- (1992) Choice in context: Tradeoff contrast and extremeness aversion. J. Marketing 29(3):281–295.Google Scholar
- (2020) A unified analysis for assortment planning with multi-purchase using marginal distribution models. Preprint, submitted July 23, https://dx.doi.org/10.2139/ssrn.3638783.Google Scholar
- (2024) Network-based representations and dynamic discrete choice models for multiple discrete choice analysis. Transportation Res. Part B Methodological 184:102948.Crossref, Google Scholar
- (2012) Learning consumer tastes through dynamic assortments. Oper. Res. 60(4):833–849.Link, Google Scholar
- (1999) On the relationship between inventory costs and variety benefits in retail assortments. Management Sci. 45(11):1496–1509.Link, Google Scholar
- (2019) A meta-analysis of newsvendor experiments: Revisiting the pull-to-center asymmetry. Production Oper. Management 28(1):140–156.Crossref, Google Scholar

