A Joint Latent-Class Model: Combining Likert-Scale Preference Statements With Choice Data to Harvest Preference Heterogeneity

2011 ◽  
Vol 50 (1) ◽  
pp. 83-110 ◽  
Author(s):  
William S. Breffle ◽  
Edward R. Morey ◽  
Jennifer A. Thacher
Keyword(s):  
Latent Class ◽  
Latent Class Model ◽  
Likert Scale ◽  
Preference Heterogeneity ◽  
Choice Data ◽  
Class Model ◽  
Model Combining

scholarly journals How do chocolate lovers balance taste and ethical considerations?

2016 ◽  
Vol 118 (2) ◽  
pp. 343-361 ◽  
Author(s):  
Eline Poelmans ◽  
Sandra Rousseau
Keyword(s):  
Latent Class ◽  
Latent Class Model ◽  
Preference Heterogeneity ◽  
Conditional Logit Model ◽  
Ethical Considerations ◽  
Class Model ◽  
Data Set ◽  
Content Type ◽  
Conditional Logit ◽  
Percent Response Rate

Purpose – The purpose of this paper is to investigate how chocolate lovers balance taste and ethical considerations when selecting chocolate products. Design/methodology/approach – The data set was collected through a survey at the 2014 “Salon du Chocolat” in Brussels, Belgium. The authors distributed 700 copies and received 456 complete responses (65 percent response rate). Choice experiments were used to estimate the relative importance of different chocolate characteristics and to predict respondents’ willingness to pay for marginal changes in those characteristics. The authors estimate both a conditional logit model and a latent class model to take possible preference heterogeneity into account. Findings – On average, respondents were willing to pay 11 euros more for 250 g fairtrade labeled chocolate compared to conventional chocolate. However, taste clearly dominates ethical considerations. The authors could distinguish three consumer segments, each with a different tradeoff between taste and fairtrade. One group clearly valued fairtrade positively, a second group valued fairtrade to a lesser extent and a third group did not seem to value fairtrade. Originality/value – Chocolate can be seen as a self-indulgent treat where taste is likely to dominate other characteristics. Therefore it is unsure to what extent ethical factors are included in consumer decisions. Interestingly the results indicate that a significant share of chocolate buyers still positively value fairtrade characteristics when selecting chocolate varieties.

scholarly journals Farmer preference for improved corn seeds in Chiapas, Mexico: A choice experiment approach

2017 ◽  
Vol 15 (3) ◽  
pp. e0116 ◽  
Author(s):  
Blanca I. Sánchez-Toledano ◽  
Zein Kallas ◽  
José M. Gil-Roig
Keyword(s):  
Choice Experiment ◽  
Latent Class ◽  
Latent Class Model ◽  
Multinomial Logit Model ◽  
Marketing Strategies ◽  
Preference Heterogeneity ◽  
Agricultural Policies ◽  
Class Model ◽  
Maize Seeds ◽  
Choice Variable

Appropriate technologies must be developed for adoption of improved seeds based on the farmers’ preferences and needs. Our research identified the farmers’ willingness to pay (WTP) as a key determinant for selecting the improved varieties of maize seeds and landraces in Chiapas, Mexico. This work also analyzed the farmers’ observed heterogeneity on the basis of their socio-economic characteristics. Data were collected using a semi-structured questionnaire from 200 farmers. A proportional choice experiment approach was applied using a proportional choice variable, where farmers were asked to state the percentage of preference for different alternative varieties in a choice set. The generalized multinomial logit model in WTP-space approach was used. The results suggest that the improved seed varieties are preferred over the Creole alternatives, thereby ensuring higher yields, resistance to diseases, and larger ear size. For the preference heterogeneity analyses, a latent class model was applied. Three types of farmers were identified: innovators (60.5%), transition farmers (29.4%), and conservative farmers (10%). An understanding of farmers’ preferences is useful in designing agricultural policies and creating pricing and marketing strategies for the dissemination of quality seeds.

scholarly journals Domestic airport passenger access mode choice decisions in a multi-airport region of South Africa

2014 ◽  
Vol 8 (1) ◽  
Author(s):  
Stephen Carstens
Keyword(s):  
South Africa ◽  
Willingness To Pay ◽  
Latent Class ◽  
Mode Choice ◽  
Latent Class Model ◽  
Preference Heterogeneity ◽  
Access Time ◽  
Class Model ◽  
Access Cost ◽  
Access Mode

The ground access mode used by air passengers to an airport has a vital impact on infrastructural and environmental decisions. An important aspect of a passenger’s mode choice is the sensitivity to factors such as access time and access cost. The objective of this research was to analyse air passenger’s sensitivity to access mode choice attributes, that is,access time, access cost, parking time and parking cost at two airports in Johannesburg, South Africa. A stated choice experiment was used to obtain the information and a latent class model was estimated. In general, discrete choice experiments are designed to reveal respondent(preference) heterogeneity and the latent class model allows for this heterogeneity to be modelled discretely. The estimated results indicated that three latent classes provided the best fit with preference heterogeneity evident from the set of parameter estimates. The access mode used was found to be the only significant covariate in the class assignment model. The respondents’ willingness to pay for a reduction in access time was estimated and it indicated that respondents had the highest access time willingness-to-pay value for the taxi as access mode. In addition, it was estimated that passengers being dropped off at the airport had a higher access time willingness-to-pay than passengers that used their own vehicles to the airport. The research results confirmed the presence of respondent heterogeneity (according to access mode) which resulted in different access time willingness-to-pay values.

scholarly journals Accounting for Attribute Non-Attendance and Common-Metric Aggregation in the Choice of Seat Belt Use, a Latent Class Model with Preference Heterogeneity

Algorithms ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 84 ◽  
Author(s):  
Mahdi Rezapour ◽  
Khaled Ksaibati
Keyword(s):  
Goodness Of Fit ◽  
Latent Class ◽  
Latent Class Model ◽  
Seat Belt ◽  
Mixed Logit ◽  
Continuous Distribution ◽  
Preference Heterogeneity ◽  
Class Model ◽  
Seat Belt Use ◽  
The Right

A choice to use a seat belt is largely dependent on the psychology of the vehicles’ occupants, and thus those decisions are expected to be characterized by preference heterogeneity. Despite the importance of seat belt use on the safety of the roadways, the majority of existing studies ignored the heterogeneity in the data and used a very standard statistical or descriptive method to identify the factors of using a seatbelt. Application of the right statistical method is of crucial importance to unlock the underlying factors of the choice being made by vehicles’ occupants. Thus, this study was conducted to identify the contributory factors to the front-seat passengers’ choice of seat belt usage, while accounting for the choice preference heterogeneity. The latent class model has been offered to replace the mixed logit model by replacing a continuous distribution with a discrete one. However, one of the shortcomings of the latent class model is that the homogeneity is assumed across a same class. A further extension is to relax the assumption of homogeneity by allowing some parameters to vary across the same group. The model could still be extended to overlay some attributes by considering attributes non-attendance (ANA), and aggregation of common-metric attributes (ACMA). Thus, this study was conducted to make a comparison across goodness of fit of the discussed models. Beside a comparison based on goodness of fit, the share of individuals in each class was used to see how it changes based on various model specifications. In summary, the results indicated that adding another layer to account for the heterogeneity within the same class of the latent class (LC) model, and accounting for ANA and ACMA would improve the model fit. It has been discussed in the content of the manuscript that accounting for ANA, ACMA and an extra layer of heterogeneity does not just improve the model goodness of fit, but largely impacts the share of class allocation of the models.

scholarly journals Customers’ Mode Choice Behaviors of Express Service Based on Latent Class Analysis and Logit Model

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Lian Lian ◽  
Shuo Zhang ◽  
Zhong Wang ◽  
Kai Liu ◽  
Lihuan Cao
Keyword(s):  
Logit Model ◽  
Choice Behavior ◽  
Latent Class ◽  
Latent Class Model ◽  
Policy Research ◽  
Multinomial Logit Model ◽  
Class Model ◽  
Taste Heterogeneity ◽  
Using Data ◽  
Service Choice

As the parcel delivery service is booming in China, the competition among express companies intensifies. This paper employed multinomial logit model (MNL) and latent class model (LCM) to investigate customers’ express service choice behavior, using data from a SP survey. The attributes and attribute levels that matter most to express customers are identified. Meanwhile, the customers are divided into two segments (penny pincher segment and high-end segment) characterized by their taste heterogeneity. The results indicate that the LCM performs statistically better than MNL in our sample. Therefore, more attention should be paid to the taste heterogeneity, especially for further academic and policy research in freight choice behavior.

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