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.

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.

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 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.

Preferences Toward COVID-19 Diagnostic Testing Features: Results From a National Cross-Sectional Survey

2021 ◽  
pp. 089011712110340
Author(s):  
Bhagyashree Katare ◽  
Shuoli Zhao ◽  
Joel Cuffey ◽  
Maria I. Marshall ◽  
Corinne Valdivia
Keyword(s):  
Logit Model ◽  
Nasal Swab ◽  
Latent Class ◽  
Diagnostic Testing ◽  
Mixed Logit ◽  
Monetary Incentive ◽  
Monetary Incentives ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Nationally Representative

Purpose: Describe preferences toward COVID-19 testing features (method, location, hypothetical monetary incentive) and simulate the effect of monetary incentives on willingness to test. Design: Online cross-sectional survey administered in July 2020. Subjects: 1,505 nationally representative U.S. respondents. Measures: Choice of preferred COVID-19 testing options in discrete choice experiment. Options differed by method (nasal-swab, saliva), location (hospital/clinic, drive-through, at-home), and monetary incentive ($0, $10, $20). Analysis: Latent class conditional logit model to classify preferences, mixed logit model to simulate incentive effectiveness. Results: Preferences were categorized into 4 groups: 34% (n = 517) considered testing comfort (saliva versus nasal swab) most important, 27% (n = 408) were willing to trade comfort for monetary incentives, 19% (n = 287) would only test at convenient locations, 20% (n = 293) avoided testing altogether. Relative to no monetary incentives, incentives of $100 increased the percent of testing avoiders (16%) and convenience seekers (70%) that were willing to test. Conclusion: Preferences toward different COVID-19 testing features vary, highlighting the need to match testing features with individuals to monitor the spread of COVID-19.

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 Economic Valuation of Local Environmental Amenities: A Case Study of Bahir Dar City, Amhara Regional State, Ethiopia

2021 ◽  
pp. 698-711
Author(s):  
Mekuannet Worku ◽  
Tefera Berihun Taw ◽  
Malaku Tarekegn
Keyword(s):  
Logit Model ◽  
Mixed Logit ◽  
Sampling Technique ◽  
Preference Heterogeneity ◽  
Primary Data ◽  
Mixed Logit Model ◽  
Palm Tree ◽  
Bahir Dar ◽  
Environmental Amenities ◽  
Attribute Levels

This study estimates the economic value of local environmental amenities in Bahir Dar city which is one of the tourist attraction sites in Ethiopia. The study employed choice experiment valuation method by identifying four environmental amenities attributes (Lake Tana, urban park, palm tree and street cleanliness). The study used probability multi-stage random sampling technique. The analysis was based on primary data surveyed from households in Bahir Dar city. The study presented nine choices set for each respondent; each choice set has three alternatives including the status quo option. The study employed a mixed logit model. The result showed that all improved attribute levels have positive signs and statistically significant. As expected and consistent with economic theory the monetary cost has negative signs and significant. The mixed logit model showed that there is preference heterogeneity in some attribute levels. Based on the finding, the study recommends that the city administration and the concerned body expected to implement the hypothetical policy scenario so as to improve environmental amenity.

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