Quantifying preference heterogeneity in transit service desired quality using a latent class choice model

2020 ◽  
Vol 139 ◽  
pp. 119-133 ◽  
Author(s):  
Gamal Eldeeb ◽  
Moataz Mohamed
Keyword(s):  
Latent Class ◽  
Choice Model ◽  
Preference Heterogeneity ◽  
Transit Service ◽  
In Transit

scholarly journals Assessing Preference Heterogeneity for Mobility-on-Demand Transit Service in Low-Income Communities: A Latent Segmentation Based Decision Tree Method

2021 ◽  
Author(s):  
Xilei Zhao ◽  
Xinyi Wang ◽  
Xiang Yan ◽  
Zhuoxuan Cao
Keyword(s):  
Decision Tree ◽  
Low Income ◽  
Latent Class ◽  
Stated Preference ◽  
Important Variable ◽  
Preference Heterogeneity ◽  
Step Method ◽  
Transit System ◽  
Transit Service ◽  
On Demand

Abstract The future of public transit service is often envisioned as Mobility-on-Demand (MOD), i.e., a system that integrates fixed routes and shared on-demand shuttles. The MOD transit system has the potential to provide better transit service with higher efficiency and coverage. However, little research has focused on understanding traveler preferences for MOD transit and preference heterogeneity, especially among the disadvantaged population. This study addresses this gap by proposing a two-step method, called latent segmentation based decision tree (LSDT). This method first uses a latent class cluster analysis (LCCA) that extracts traveler profiles who have similar usage patterns for shared modes. Then, decision trees (DT) are adopted to reveal the associations between various factors with preferences for MOD transit across different clusters. We collected stated-preference data among two low-resource communities, i.e., Detroit and Ypsilanti, Michigan. The LCCA model divides the entire sample into three clusters, i.e., shared-mode users, shared-mode non-users, and transit-only users. We find that job accessibility by transit is the most important variable for all the cluster-specific DT to model the MOD transit preference, and it negatively associated with the MOD transit preference. For transit-only users, gender and car ownership are the second-important variables, but neither of them appears in the DT for the other two clusters. In particular, female transit-only users have lower preference for MOD transit, possibly due to safety concerns. The LSDT method can generate richer insights than a single DT fitted to the overall sample by better accounting for heterogeneity. The findings gained from this approach can inform better-targeted strategies to plan for MOD transit services.

A binary choice model with partial observability for panel data

2020 ◽  
Vol 15 (4) ◽  
pp. 315-322
Author(s):  
Ekaterina Batalova ◽  
Kirill Furmanov ◽  
Ekaterina Shelkova
Keyword(s):  
Job Search ◽  
Latent Class ◽  
Choice Model ◽  
Maximum Likelihood Estimates ◽  
Binary Choice ◽  
Panel Model ◽  
Binary Response Variable ◽  
Monitoring Survey ◽  
Binary Choice Model ◽  
Time Invariant

We consider a panel model with a binary response variable that is a product of two unobservable factors, each determined by a separate binary choice equation. One of these factors is assumed to be time-invariant and may be interpreted as a latent class indicator. A simulation study shows that maximum likelihood estimates from even the shortest panel are much more reliable than those obtained from a cross-section. As an illustrative example, the model is applied to Russian Longitudinal Monitoring Survey data to estimate a proportion of the non-employed population who are participating in job search.

Air Passengers’ Preferences for Aviation Voluntary Carbon Offsetting: A Co-benefits Perspective

2021 ◽  
pp. 004728752110303
Author(s):  
Beile Zhang ◽  
Brent W. Ritchie ◽  
Judith Mair ◽  
Sally Driml
Keyword(s):  
Discrete Choice ◽  
Latent Class ◽  
Choice Model ◽  
Choice Modeling ◽  
Positive Outcomes ◽  
Market Segments ◽  
Discrete Choice Modeling ◽  
Educational Benefits ◽  
Carbon Offsetting ◽  
Simple Reduction

Co-benefits are positive outcomes from voluntary carbon offsetting (VCO) programs beyond simple reduction in carbon emissions, which include biodiversity, air quality, economic, health, and educational benefits. Given the rates of aviation VCOs remain at less than 10%, this study investigated air passengers’ preferences for co-benefits as well as certification, location, and cost of VCO programs. Using discrete choice modeling, this study shows that aviation VCO programs with higher levels of co-benefits, particularly biodiversity and health benefits, are preferred by air passengers and confirms a preference for domestically based and certified VCO programs. The latent class choice model identified three classes with different preferences for VCO program attributes and demographic characteristics. The results of this study contribute to the knowledge of VCO co-benefits and imply that airlines should take note of this preference for biodiversity and health co-benefits when designing VCO programs and differentiate between market segments to increase the uptake of VCOs.

Attribute Non-Attendance and Consumer Preferences for Online Food Products in Germany

2020 ◽  
Vol 69 (1) ◽  
pp. 31-48
Author(s):  
P. Christoph Richartz ◽  
Lukas Kornher ◽  
Awudu Abdulai
Keyword(s):  
Latent Class ◽  
Consumer Preferences ◽  
Mixed Logit ◽  
Meat Products ◽  
Food Product ◽  
Latent Class Models ◽  
Preference Heterogeneity ◽  
Significant Heterogeneity ◽  
Processing Strategies ◽  
Class Models

In this article, we apply a choice experiment meth-od to examine consumers’ preferences for online food product attributes, using survey data for German consumers for meat products. We use both mixed logit and latent class models to analyze preference heterogeneity and sources of heterogeneity, as well as endogenous attribute attendance models to account for consumers’ attribute processing strategies. The empirical results reveal significant heterogeneity in preferences for online meat attributes among consumers. We also find that consumers’ willingness to pay estimates are highly influenced by their attribute processing strategies.

scholarly journals Análisis econométrico de la heterogeneidad de las preferencias de los individuos: Aplicación a la valoración económica de la conservación del paisaje agrícola de montaña

2011 ◽  
Vol 8 (1) ◽  
pp. 103 ◽  
Author(s):  
Sergio Colombo ◽  
Nick Hanley
Keyword(s):  
Latent Class ◽  
Random Parameter ◽  
Choice Models ◽  
Latent Class Models ◽  
Preference Heterogeneity ◽  
Stated Choice ◽  
Empirical Application ◽  
Random Parameter Logit ◽  
Class Models

The need to account for respondents’ preference heterogeneity in stated choice models has motivated researchers to apply random parameter logit and latent class models. In this paper we compare these three alternative ways of incorporating preference heterogeneity in stated choice models and evaluate how the choice of model affects welfare estimates in a given empirical application. Finally, we discuss what criteria to follow to decide which approach is most appropriate.

Exploring Differences in Preference Heterogeneity Representation and Their Influence in Product Family Design

2011 ◽  
Author(s):  
Eric Sullivan ◽  
Scott Ferguson ◽  
Joseph Donndelinger
Keyword(s):  
Logit Model ◽  
Latent Class ◽  
Latent Class Model ◽  
Mixed Logit ◽  
Multinomial Logit Model ◽  
Hierarchical Bayes ◽  
Product Line ◽  
Combinatorial Design ◽  
Preference Heterogeneity ◽  
Target Market

When using conjoint studies for market-based design, two model types can be fit to represent the heterogeneity present in a target market, discrete or continuous. In this paper, data from a choice-based conjoint study with 2275 respondents is analyzed for a 19-attribute combinatorial design problem with over 1 billion possible product configurations. Customer preferences are inferred from the choice task data using both representations of heterogeneity. The hierarchical Bayes mixed logit model exemplifies the continuous representation of heterogeneity, while the latent class multinomial logit model corresponds to the discrete representation. Product line solutions are generated by each of these model forms and are then explored to determine why differences are observed in both product solutions and market share estimates. These results reveal some potential limitations of the Latent Class model in the masking of preference heterogeneity. Finally, the ramifications of these results on the market-based design process are discussed.

Sign in / Sign up

Export Citation Format

Share Document