scholarly journals Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model

2011 ◽  
Author(s):  
Filip Matějka ◽  
Alisdair McKay
Keyword(s):  
Logit Model ◽  
Multinomial Logit Model ◽  
Multinomial Logit ◽  
Rational Inattention

scholarly journals Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model

2015 ◽  
Vol 105 (1) ◽  
pp. 272-298 ◽  
Author(s):  
Filip Matějka ◽  
Alisdair McKay
Keyword(s):  
Optimal Strategy ◽  
Logit Model ◽  
Imperfect Information ◽  
Multinomial Logit Model ◽  
Multinomial Logit ◽  
Information Frictions ◽  
Rational Inattention ◽  
Prior Beliefs

Individuals must often choose among discrete actions with imperfect information about their payoffs. Before choosing, they have an opportunity to study the payoffs, but doing so is costly. This creates new choices such as the number of and types of questions to ask. We model these situations using the rational inattention approach to information frictions. We find that the decision maker's optimal strategy results in choosing probabilistically in line with a generalized multinomial logit model, which depends both on the actions' true payoffs as well as on prior beliefs. (JEL D11, D81, D83)

Assortment Optimization under the Multinomial Logit Model with Random Choice Parameters

2014 ◽  
Vol 23 (11) ◽  
pp. 2023-2039 ◽  
Author(s):  
Paat Rusmevichientong ◽  
David Shmoys ◽  
Chaoxu Tong ◽  
Huseyin Topaloglu
Keyword(s):  
Logit Model ◽  
Multinomial Logit Model ◽  
Multinomial Logit ◽  
Random Choice ◽  
Assortment Optimization

scholarly journals A multinomial logit model of college stopout and dropout behavior

2008 ◽  
Vol 27 (3) ◽  
pp. 319-331 ◽  
Author(s):  
Leslie S. Stratton ◽  
Dennis M. O’Toole ◽  
James N. Wetzel
Keyword(s):  
Logit Model ◽  
Multinomial Logit Model ◽  
Multinomial Logit

scholarly journals Do Online Shoppers Attend Farmers’ Markets?

2019 ◽  
Vol 11 (10) ◽  
pp. 39
Author(s):  
Jean D. Gumirakiza ◽  
Mara E. Schroering
Keyword(s):  
United States ◽  
Logit Model ◽  
Online Shopping ◽  
Multinomial Logit Model ◽  
The United States ◽  
Multinomial Logit ◽  
Marketing Strategies ◽  
Farmers Markets ◽  
Online Purchases ◽  
Online Shoppers

Online shopping is changing ways in which offline markets operate. As the online shopping for fresh produce takes off, it is important to investigate its effects on existing physical market outlets. The main objective for this study is to explain how often online shoppers attend farmers’ markets. The study uses data that was collected in 2016 from a sample of 1,205 consumers residing in the south region of the United States who made at least two online purchases within six months prior to participating in this study. This study employed a multinomial Logit model and Stata was used to run the regression. Results show that the majority of these online shoppers never attended a farmers’ market. The relative probabilities for the online shoppers to “never” attend farmers’ markets, attend “occasionally”, and “frequently” are 0.54, 0.28, and 0.18 respectively. We found that the lack of awareness, inconvenient place and/or time, and low interests are major reasons for nonattendance. This study suggests that farmers’ markets could greatly benefit by developing marketing strategies targeting online shoppers.

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