Pricing Competition Under Specific Discrete Choice Models

2020 ◽  
Vol 37 (02) ◽  
pp. 2050008
Author(s):  
Farhad Etebari
Keyword(s):  
Discrete Choice ◽  
Logit Model ◽  
Choice Model ◽  
Public Information ◽  
Multinomial Logit Model ◽  
Multinomial Logit ◽  
Discrete Choice Models ◽  
Nested Logit ◽  
Nested Logit Model ◽  
Substitution Pattern

Recent developments of information technology have increased market’s competitive pressure and products’ prices turned to be paramount factor for customers’ choices. These challenges influence traditional revenue management models and force them to shift from quantity-based to price-based techniques and incorporate individuals’ decisions within optimization models during pricing process. Multinomial logit model is the simplest and most popular discrete choice model, which suffers from an independence of irrelevant alternatives limitation. Empirical results demonstrate inadequacy of this model for capturing choice probability in the itinerary share models. The nested logit model, which appeared a few years after the multinomial logit, incorporates more realistic substitution pattern by relaxing this limitation. In this paper, a model of game theory is developed for two firms which customers choose according to the nested logit model. It is assumed that the real-time inventory levels of all firms are public information and the existence of Nash equilibrium is demonstrated. The firms adapt their prices by market conditions in this competition. The numerical experiments indicate decreasing firm’s price level simultaneously with increasing correlation among alternatives’ utilities error terms in the nests.

Investigation of Stochastic Network Loading Procedures

1998 ◽  
Vol 1645 (1) ◽  
pp. 94-102 ◽  
Author(s):  
J. N. Prashker ◽  
S. Bekhor
Keyword(s):  
Logit Model ◽  
Route Choice ◽  
Multinomial Logit Model ◽  
Multinomial Logit ◽  
Nested Logit ◽  
Stochastic Network ◽  
Nested Logit Model ◽  
Network Loading ◽  
Stochastic Loading ◽  
The Cross

The network loading process of stochastic traffic assignment is investigated. A central issue in the assignment problem is the behavioral assumption governing route choice, which concerns the definition of available routes and the choice model. These two problems are addressed and reviewed. Although the multinomial logit model can be implemented efficiently in stochastic network loading algorithms, the model suffers from theoretical drawbacks, some of them arising from the independence of irrelevant alternatives property. As a result, the stochastic loading on routes that share common links is overloaded at the overlapping parts of the routes. Other logit-family models recently have been proposed to overcome some of the theoretical problems while maintaining the convenient analytical structure. Three such models are investigated: the C-logit model, which was specifically defined for route choice; and two general discrete-choice models, the cross-nested logit model and the paired combinatorial logit model. The two latter models are adapted to route choice, and simple network examples are presented to illustrate the performance of the models with respect to the overlapping problem. The results indicate that all three models perform better than does the multinomial logit model. The cross-nested logit model has an advantage over the two other generalized models because it enables performing stochastic loading without route enumeration. The integration of this model with the stochastic equilibrium problem is discussed, and a specific algorithm using the cross-nest logit model is presented for the stochastic loading phase.

scholarly journals Railway and road discrete choice model for foreign trade freight between Antioquia and the Port of Cartagena

2016 ◽  
Vol 36 (3) ◽  
pp. 22 ◽  
Author(s):  
Juan Diego Pineda Jaramillo ◽  
Iván Reinaldo Sarmiento Ordosgoitia ◽  
Jorge Eliécer Córdoba Maquilón
Keyword(s):  
Qualitative Research ◽  
Discrete Choice ◽  
Logit Model ◽  
Choice Model ◽  
Stated Preference ◽  
Revealed Preference ◽  
Freight Transportation ◽  
Multinomial Logit Model ◽  
Discrete Choice Model ◽  
The Cost

Most Colombian freight is transported on roads with barely acceptable conditions, and although there is a speculation about the need for a railway for freight transportation, there is not a study in Colombia showing the variables that influence the modal choice by the companies that generate freight transportation. This article presents the calculation of demand for a hypothetical railway through a discrete choice model. It begins with a qualitative research through focus group techniques to identify the variables that influence the choice of persons responsible for the transportation of large commercial companies in Antioquia (Colombia). The influential variables in the election were the cost and service frequency, and these variables were used to apply a Stated Preference (SP) and Revealed Preference (RP) survey, then to calibrate a Multinomial Logit Model (MNL), and to estimate the influence of each of them. We show that the probability of railway choice by the studied companies varies between 67% and 93%, depending on differences in these variables.

Analyzing Bus Passengers’ Satisfaction in Dhaka using Discrete Choice Models

2019 ◽  
Vol 2673 (2) ◽  
pp. 758-768 ◽  
Author(s):  
Mohammed Quddus ◽  
Farzana Rahman ◽  
Fredrik Monsuur ◽  
Juan de Ona ◽  
Marcus Enoch
Keyword(s):  
Service Quality ◽  
Influencing Factors ◽  
Transport System ◽  
Discrete Choice ◽  
Logit Model ◽  
Mixed Logit ◽  
Multinomial Logit ◽  
Discrete Choice Models ◽  
Bus Service ◽  
Bus Transport

The bus transport system in Dhaka is unsafe, unreliable, inefficient and struggles to cope with the day-to-day mobility of its massive population. Consequently, measuring the performance of bus service quality (SQ) from the customers’ perspective is fundamental in planning a sustainable bus transport system for Dhaka, and in developing the associated policies and regulations. Although there are some studies addressing the performance of the public transport systems in Bangladesh, little research considers how service quality attributes affect passengers’ satisfaction. The purpose of this paper is to examine a relationship between bus service quality and its influencing factors in Dhaka. Using a customer satisfaction survey with a sample size of 955, discrete choice models (e.g., multinomial logit and mixed logit) have been developed. The results indicate that the inhabitants, as expected, are dissatisfied with their bus services (less than 10% rated service quality as “excellent/good”) and service attributes such as comfort level and driver skills were found to be the most important contributors toward the “poor” and “very poor” perceptions of service quality. Other influencing factors are punctuality, safety, entry and exit processes, waiting times, and vehicle condition. One surprising finding was that the multinomial logit model provides better goodness-of-fit for the sample data relative to the mixed logit model implying that bus users in Dhaka may represent a homogeneous group as they do have access to other modes. Findings from this study can be utilized to develop policies and regulations to improve bus transport in Dhaka.

A Mode Choice Model for a Public Transport Transfer Center in Istanbul

2011 ◽  
Vol 97-98 ◽  
pp. 606-610
Author(s):  
Huseyın Onur Tezcan ◽  
Fatih Yonar ◽  
Sabahat Topuz Kiremitci
Keyword(s):  
Public Transport ◽  
Logit Model ◽  
Choice Model ◽  
Mode Choice ◽  
Multinomial Logit Model ◽  
Multinomial Logit ◽  
Questionnaire Data ◽  
Mode Choice Model

The aim of this study is to understand the reasons behind the mode choice preferences of passengers using a public transport transfer center. For this aim, a questionnaire data obtained at an interim transfer center in Istanbul is utilized. This interim center hosts stops for paratransit, bus and metro modes. A multinomial logit model of modal preferences is estimated and the coefficient results of this model are used to analyze and compare modes.

A Monté Carlo Comparison of Estimators for the Multinomial Logit Model

1989 ◽  
Vol 26 (1) ◽  
pp. 56-68 ◽  
Author(s):  
David S. Bunch ◽  
Richard R. Batsell
Keyword(s):  
Discrete Choice ◽  
Logit Model ◽  
Repeated Measures ◽  
Predictive Accuracy ◽  
Multinomial Logit Model ◽  
Multinomial Logit ◽  
Point Estimation ◽  
Test Statistics ◽  
Chi Square ◽  
Mnl Model

Marketing researchers use the multinomial logit (MNL) model to analyze discrete choice, and estimate parameters either by maximum likelihood (ML) or minimum logit chi square (MLCS). Some controversy persists, however, over which is better. Review articles in marketing recommend ML over MLCS, but the statistics literature suggests that MLCS should be preferred. No studies have directly compared the performance of ML and MLCS in a marketing context. The authors assess the relative performance of ML, MLCS, and three other candidate estimators for MNL marketing applications involving repeated-measures datasets collected by means of multiple-subset designs. In contrast to most previous findings in the statistics literature, the results strongly support the use of ML. ML is found to outperform the other estimators on a variety of point estimation, predictive accuracy, and statistical inference criteria and ML test statistics are found to have asymptotic behavior for datasets involving relatively few replications.

Analysis of Stated Preferences for Intermodal Bicycle-Transit Interfaces

1996 ◽  
Vol 1556 (1) ◽  
pp. 86-95 ◽  
Author(s):  
Dean Taylor ◽  
Hani Mahmassani
Keyword(s):  
Survey Data ◽  
Discrete Choice ◽  
Choice Model ◽  
Stated Preference ◽  
Discrete Choice Models ◽  
Stated Preferences ◽  
Nested Logit ◽  
Facility Type ◽  
Potential Factors ◽  
Work Trip

One proposed means of increasing use of both transit and bicycles is to replace long automobile trips with “bike and ride” trips. In this study, a stated-preference survey was conducted using hypothetical scenarios within which respondents ranked their preferences for making a work trip by automobile only, park and ride, or bike and ride. The survey addressed numerous potential factors that might influence this choice, including three policy variables that were systematically varied in the scenarios: on-street bicycle facility type, bicycle parking facility type, and bicycle access distance to transit. The survey data are summarized and used to estimate discrete choice models. A nested logit choice model was developed as the preferred model. From this model, inferences are drawn about many factors. Conclusions are drawn about the three main policy variables. In short, the results support the notion that bicycle lockers are the preferred parking facility to increase bike and ride use. The results also indicate that bike lanes are superior to wide curb lanes as an incentive for casual and inexperienced cyclists, but that bike lanes and wide curb lanes are an identical incentive for experienced cyclists.

scholarly journals Performance Analysis of Mixed Logit Models for Discrete Choice Models

2019 ◽  
pp. 563-575
Author(s):  
Jaka Nugraha
Keyword(s):  
Discrete Choice ◽  
Logit Model ◽  
Mixed Logit ◽  
Likelihood Estimation ◽  
Multinomial Logit Model ◽  
Discrete Choice Models ◽  
Logit Models ◽  
Nominal Data ◽  
Mixed Logit Models ◽  
Mnl Model

Mixed Logit model  (MXL) is generated from Multinomial Logit model (MNL) for discrete, i.e. nominal, data. It eliminates its limitations particularly on estimating the correlation among responses.  In the MNL, the probability equations are presented in the closed form and it is contrary with in the MXL. Consequently, the calculation of the probability value of each alternative get simpler in the MNL, meanwhile it needs the numerical methods for estimation in the MXL.  In this study, we investigated the performance of maximum likelihood estimation (MLE) in the MXL and MNL into two cases, the low and high correlation circumstances among responses. The performance is measured based on differencing actual and estimation value.  The simulation study and real cases show that the MXL model is more accurate than the MNL model. This model can estimates the correlation among response as well. The study concludes that the MXL model is suggested to be used if there is a high correlation among responses. 

Assortment Optimization and Pricing Under the Multinomial Logit Model with Impatient Customers: Sequential Recommendation and Selection

2021 ◽  
Author(s):  
Pin Gao ◽  
Yuhang Ma ◽  
Ningyuan Chen ◽  
Guillermo Gallego ◽  
Anran Li ◽  
...  
Keyword(s):  
Logit Model ◽  
Choice Model ◽  
Multinomial Logit Model ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Multinomial Logit ◽  
Impatient Customers ◽  
Purchasing Decisions ◽  
Assortment Optimization ◽  
Decision Variables

Sequential Recommendation Under the Multinomial Logit Model with Impatient Customers In many applications, customers incrementally view a subset of offered products and make purchasing decisions before observing all the offered products. In this case, the decision faced by a firm is not only what assortment of products to offer, but also in what sequence to offer the products. In “Assortment Optimization and Pricing Under the Multinomial Logit Model with Impatient Customers: Sequential Recommendation and Selection”, Gao, Ma, Chen, Gallego, Li, Rusmevichientong, and Topaloglu propose a choice model where each customer incrementally view the assortment of products in multiple stages, and their patience level determines the maximum number of stages. Under this choice model, the authors develop a polynomial-time algorithm that finds a revenue-maximizing sequence of assortments. If the sequence of assortments is fixed, the problem of finding revenue-maximizing prices can be transformed to a convex program. They combine these results to develop an effective approximation algorithm when both the sequence of assortments and prices are decision variables.

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