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Assortment Optimization in the Presence of Focal Effect: Operational Insights and Efficient Algorithms

https://doi.org/10.2139/ssrn.4504023
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45/45 checkable references clean · checked 2026-08-27

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

24 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 45 checked references that resolve
resolves10.1287/mnsc.2020.3681
Assortment Optimization Under Consider-Then-Choose Choice Models
resolves10.1287/mnsc.2022.4492
The Exponomial Choice Model for Assortment Optimization: An Alternative to the MNL Model?
resolves10.1287/opre.2021.0060
Assortment Optimization Under the Multinomial Logit Model with Utility-Based Rank Cutoffs
resolves10.1287/mnsc.2021.4069
A Comparative Empirical Study of Discrete Choice Models in Retail Operations
resolves10.1007/s00453-019-00610-8
Assortment Optimisation Under a General Discrete Choice Model: A Tight Analysis of Revenue-Ordered Assortments
resolves10.1287/opre.2016.1505
A Markov Chain Approximation to Choice Modeling
resolves10.1287/opre.2022.2281
Network Revenue Management Under a Spiked Multinomial Logit Choice Model
resolves10.1287/mnsc.2021.4256
Decision Forest: A Nonparametric Approach to Modeling Irrational Choice
resolves10.1016/j.jcps.2014.08.002
Choice overload: A conceptual review and meta‐analysis
resolves10.1509/jmkr.46.3.410
Assortment Size and Option Attractiveness in Consumer Choice among Retailers
resolves10.1007/978-3-319-11008-0
Integer Programming
resolves10.1287/opre.2014.1256
Assortment Optimization Under Variants of the Nested Logit Model
resolves10.1287/mnsc.2015.2176
Online Shopping Intermediaries: The Strategic Design of Search Environments
resolves10.1287/opre.2017.1628
Revenue Management Under the Markov Chain Choice Model
resolves10.1287/ijoc.1050.0135
Implementing Sponsored Search in Web Search Engines: Computational Evaluation of Alternative Mechanisms
resolves10.1287/opre.2014.1328
A General Attraction Model and Sales-Based Linear Program for Network Revenue Management Under Customer Choice
resolves10.1287/mnsc.2014.1931
Constrained Assortment Optimization for the Nested Logit Model
resolves10.1007/978-1-4939-9606-3
Revenue Management and Pricing Analytics
resolves10.1287/opre.2021.2127
Assortment Optimization and Pricing Under the Multinomial Logit Model with Impatient Customers: Sequential Recommendation and Selection
resolves10.1137/1024022
Computers and Intractability: A Guide to the Theory of NP-Completeness (Michael R. Garey and David S. Johnson)
resolves10.1287/mnsc.2015.2289
Choosing to Choose: The Effects of Decoys and Prior Choice on Deferral
resolves10.1086/208899
Adding Asymmetrically Dominated Alternatives: Violations of Regularity and the Similarity Hypothesis
resolves10.1287/opre.2023.2469
Technical Note—New Bounds for Cardinality-Constrained Assortment Optimization Under the Nested Logit Model
resolves10.1016/j.orl.2019.09.009
Assortment optimization under the multinomial logit model with product synergies
resolves10.1287/msom.2022.0659
The Choice Overload Effect in Online Recommender Systems
resolves10.1257/jel.20211524
Rational Inattention: A Review
resolves10.1017/jwe.2018.34
Mitigating Choice Overload: An Experiment in the U.S. Beer Market
resolves10.1257/aer.20130047
Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model
resolves10.1287/mksc.1070.0310
Informing, Transforming, and Persuading: Disentangling the Multiple Effects of Advertising on Brand Choice Decisions
resolves10.1016/j.dam.2012.03.003
A branch-and-cut algorithm for the latent-class logit assortment problem
resolves10.1080/15332861.2016.1148971
Drivers of E-store Patronage Intentions: Choice Overload, Internet Shopping Anxiety, and Impulse Purchase Tendency
resolves10.1287/opre.1120.1063
Robust Assortment Optimization in Revenue Management Under the Multinomial Logit Choice Model
resolves10.1002/(SICI)1520-6378(199602)21:1<35::AID-COL4>3.0.CO;2-6
Comparative studies on color preference in Japan and other Asian regions, with special emphasis on the preference for white
resolves10.1086/651235
Can There Ever Be Too Many Options? A Meta-Analytic Review of Choice Overload
resolves10.1287/msom.2020.0900
JD.com: Transaction-Level Data for the 2020 MSOM Data Driven Research Challenge
resolves10.1177/002224379202900301
Choice in Context: Tradeoff Contrast and Extremeness Aversion
resolves10.1287/mnsc.1030.0147
Revenue Management Under a General Discrete Choice Model of Consumer Behavior
resolves10.1287/mksc.1100.0590
The Effect of Media Advertising on Brand Consideration and Choice
resolves10.1287/mksc.2017.1072
The Power of Rankings: Quantifying the Effect of Rankings on Online Consumer Search and Purchase Decisions
resolves10.1007/BF01212473
Parallel search for the best alternative
resolves10.1016/j.orl.2012.08.003
Capacitated assortment and price optimization under the multinomial logit model
resolves10.1287/mnsc.2017.2790
The Impact of Consumer Search Cost on Assortment Planning and Pricing
resolves10.1287/mnsc.2016.2520
Consumer Choice Models with Endogenous Network Effects
resolves10.2307/1910412
Optimal Search for the Best Alternative
resolves10.1287/mksc.1050.0170
An Integrated Choice Model Incorporating Alternative Mechanisms for Consumers’ Reactions to In-Store Display and Feature Advertising
The 24 references without a DOI — listed, not checked
no DOI — not checkedref1
no DOI — not checkedThe click-based MNL model: A framework for modeling click data in assortment optimization
no DOI — not checkedref5
no DOI — not checkedAssortment optimization with visibility constraints
no DOI — not checkedref10
no DOI — not checkedref13
no DOI — not checkedref18
no DOI — not checkedref20
no DOI — not checkedRobust assortment optimization under the Markov chain choice model
no DOI — not checkedA random consideration set model for demand estimation, assortment optimization, and pricing
no DOI — not checkedAssortment optimization under the sequential click-based choice model
no DOI — not checkedExtremeness seeking: When and why consumers prefer the extremes
no DOI — not checkedref32
no DOI — not checkedref33
no DOI — not checkedref37
no DOI — not checkedDiscrete choice via sequential search
no DOI — not checkedThe focal Luce model
no DOI — not checkedref43
no DOI — not checkedref46
no DOI — not checkedDynamic joint assortment and pricing optimization with demand learning
no DOI — not checkedref52
no DOI — not checkedA nonparametric approach with marginals for modeling consumer choice
no DOI — not checkedref54
no DOI — not checkedref62
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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