scholarly journals The evolution of choice set formation in dwelling and location with rising prices: A decadal panel analysis in the Greater Toronto Area

2021 ◽  
Vol 14 (1) ◽  
pp. 1227-1247
Author(s):  
Jason Hawkins ◽  
Khandker Nurul Habib
Keyword(s):  
Discrete Choice ◽  
Latent Class ◽  
Discrete Choice Models ◽  
Single Family ◽  
Greater Toronto Area ◽  
Home Location ◽  
Price Increases ◽  
Choice Set Formation ◽  
Choice Set

Home location choice is based on both the characteristics of the dwelling (e.g., size, style, number of bedrooms) and the location (e.g., proximity to work, quality of schools, accessibility). Recent years have seen a steep increase in the price of housing in many major cities. In this research, we examine how these price increases are affecting the types of dwelling and locations considered by households. A large sample of real estate listings from 2006 and 2016 from the Greater Toronto Area is used to develop the empirical models. Two recently developed discrete choice models are used in the study: a nested logit model with latent class feedback (LCF) and a semi-compensatory independent availability logit (SCIAL) model. A method of alternative aggregation is proposed to overcome the computational hurdle that often impedes the estimation of choice set models. We find a significant increase in the probability of larger households considering townhouses and apartments over detached single-family dwellings between 2006 and 2016.

scholarly journals Social Networks and Choice Set Formation in Discrete Choice Models

Econometrics ◽  
2016 ◽  
Vol 4 (4) ◽  
pp. 42 ◽  
Author(s):  
Bruno Wichmann ◽  
Minjie Chen ◽  
Wiktor Adamowicz
Keyword(s):  
Social Networks ◽  
Discrete Choice ◽  
Choice Models ◽  
Discrete Choice Models ◽  
Choice Set Formation ◽  
Choice Set

A Comparative Empirical Study of Discrete Choice Models in Retail Operations

2021 ◽  
Author(s):  
Gerardo Berbeglia ◽  
Agustín Garassino ◽  
Gustavo Vulcano
Keyword(s):  
Empirical Study ◽  
Discrete Choice ◽  
Operations Management ◽  
Latent Class ◽  
Markov Chain Model ◽  
Choice Models ◽  
Discrete Choice Models ◽  
Chain Model ◽  
Retail Operations ◽  
Demand Models

Choice-based demand estimation is a fundamental task in retail operations and revenue management, providing necessary input data for inventory control, assortment, and price-optimization models. The task is particularly difficult in operational contexts where product availability varies over time and customers may substitute into the available options. In addition to the classical multinomial logit (MNL) model and extensions (e.g., nested logit, mixed logit, and latent-class MNL), new demand models have been proposed (e.g., the Markov chain model), and others have been recently revisited (e.g., the rank list-based and exponomial models). At the same time, new computational approaches were developed to ease the estimation function (e.g., column-generation and expectation-maximization (EM) algorithms). In this paper, we conduct a systematic, empirical study of different choice-based demand models and estimation algorithms, including both maximum-likelihood and least-squares criteria. Through an exhaustive set of numerical experiments on synthetic, semisynthetic, and real data, we provide comparative statistics of the predictive power and derived revenue performance of an ample collection of choice models and characterize operational environments suitable for different model/estimation implementations. We also provide a survey of all the discrete choice models evaluated and share all our estimation codes and data sets as part of the online appendix. This paper was accepted by Vishal Gaur, operations management.

Exploring Marketing to Engineering Information Mapping in Mass Customization: A Presentation of Ideas, Challenges and Resulting Questions

2011 ◽  
Author(s):  
Scott Ferguson ◽  
Andrew Olewnik ◽  
Phil Cormier
Keyword(s):  
Discrete Choice ◽  
Mass Customization ◽  
Latent Class ◽  
Mixed Logit ◽  
Choice Models ◽  
Discrete Choice Models ◽  
Hierarchical Bayes ◽  
Customer Preferences ◽  
Lack Of Information ◽  
Engineering Information

The paradigm of mass customization strives to minimize the tradeoffs between an ‘ideal’ product and products that are currently available. However, the lack of information relation mechanisms that connect the domains of marketing, engineering, and distribution have caused significant challenges when designing products for mass customization. For example, the bridge connecting the marketing and engineering domains is complicated by the lack of proven tools and methodologies that allow customer needs and preferences to be understood at a level discrete enough to support true mass customization. Discrete choice models have recently gained significant attention in engineering design literature as a way of expressing customer preferences. This paper explores how information from choice-based conjoint surveys might be used to assist the development of a mass customizable MP3 player, starting from 140 student surveys. The authors investigate the challenges of fielding discrete choice surveys for the purpose of mass customization, and explore how hierarchical Bayes mixed logit and latent class multinomial logit models might be used to understand the market for customizable attributes. The potential of using discrete choice models as a foundation for mathematically formulating mass customization problems is evaluated through an investigation of strengths and limitations.

scholarly journals Validity and Reliability

2020 ◽  
pp. 111-123
Author(s):  
Petr Mariel ◽  
David Hoyos ◽  
Jürgen Meyerhoff ◽  
Mikolaj Czajkowski ◽  
Thijs Dekker ◽  
...  
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Model Comparison ◽  
Choice Models ◽  
Criterion Validity ◽  
Discrete Choice Models ◽  
Validity And Reliability

AbstractThis chapter concerns different aspects of validity and reliability of a discrete choice experiment. Firstly, it focuses on three essential concepts for assessing the validity of the welfare estimates obtained in the choice experiment, namely content, construct and criterion validity. Secondly, it discusses how the reliability of the recorded choices can be assessed. It then discusses issues related to model comparison and selection. Finally, it addresses prediction in discrete choice models as a way to assess the quality of a model.

scholarly journals School Choice in Amsterdam: Which Schools are Chosen When School Choice is Free?

2019 ◽  
Vol 14 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Nienke Ruijs ◽  
Hessel Oosterbeek
Keyword(s):  
School Choice ◽  
Secondary School ◽  
Discrete Choice ◽  
Discrete Choice Models ◽  
Tuition Fees ◽  
Catchment Areas ◽  
National Newspaper ◽  
The City ◽  
Incoming Students

Using discrete choice models, this paper investigates the determinants of secondary school choice in the city of Amsterdam. In this city, there are many schools to choose from and school choice is virtually unrestricted (no catchment areas, low or no tuition fees, short distances). We find that school choice is related to exam grades and the quality of incoming students, but not to progression in lower grades, no delay in higher grades, and a composite measure of quality published by a national newspaper. Furthermore, students appear to prefer schools that are close to their home and schools that many of their former classmates in primary school attend.

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