Consumer willingness to pay for quality attributes of fresh seafood: A labeled latent class model

2015 ◽  
Vol 41 ◽  
pp. 225-236 ◽  
Author(s):  
Thong Tien Nguyen ◽  
Wolfgang Haider ◽  
Hans Stubbe Solgaard ◽  
Lars Ravn-Jonsen ◽  
Eva Roth
Keyword(s):  
Willingness To Pay ◽  
Latent Class ◽  
Latent Class Model ◽  
Quality Attributes ◽  
Class Model

scholarly journals Consumer Preference and Willingness to Pay for Azaleas: Effect of State Labeling and Various Types of Retail Outlets

HortScience ◽  
2016 ◽  
Vol 51 (8) ◽  
pp. 1026-1030
Author(s):  
Madiha Zaffou ◽  
Benjamin L. Campbell
Keyword(s):  
Willingness To Pay ◽  
Online Survey ◽  
Latent Class ◽  
Latent Class Model ◽  
Consumer Preference ◽  
Class Model ◽  
Home Improvement ◽  
Retail Outlets ◽  
Locally Grown ◽  
The Impact

Over the last decade, there has been a move by many consumers to purchase locally grown products. Many studies have focused on food with limited studies examining plants. Using an online survey of Connecticut residents in conjunction with a choice experiment, we examine the impact of various attributes (e.g., local labeling, retail outlet, color, bloom, and price) on preference and willingness to pay (WTP) for azaleas. Results of the latent class model (LCM) indicate that only one of the latent classes, ≈43% of the sample, valued local labeling. Furthermore, the same class that valued local also preferred a nursery/greenhouse outlet over a home improvement center/mass merchandiser. Recommendations for the different retail outlets are given based on the results.

scholarly journals Are Consumers Willing to Pay a Premium for Pure Rice Noodles? A Study of Discrete Choice Experiments in Taiwan

2020 ◽  
Vol 12 (15) ◽  
pp. 6144
Author(s):  
Yu-Hui Chen ◽  
Kai-Han Qiu ◽  
Kang Ernest Liu ◽  
Chun-Yuan Chiang
Keyword(s):  
Willingness To Pay ◽  
Marketing Strategy ◽  
Discrete Choice ◽  
Metropolitan Area ◽  
Latent Class ◽  
Corn Starch ◽  
Latent Class Model ◽  
Choice Experiments ◽  
Discrete Choice Experiments ◽  
Class Model

Most consumers in Taiwan have never eaten pure rice noodles (PRNs) and some may mistakenly treat corn starch-based rice noodles as PRNs. This study examines consumers’ willingness to pay (WTP) for PRNs using discrete choice (DC) experiments with a blind tasting test to understand consumers’ ability to identify PRNs with varying rice content on the basis of their appearance and taste. Collecting data from the Taipei metropolitan area, our DC experimental results of both pre- and post-experiment conditions show that Taiwanese consumers do prefer PRNs and their WTP for PRNs was strengthened. A latent class model highlights that attribute preferences tend to differ by group and thus rice content ratios should be properly labeled so that consumers can make a better choice according to their preferences. Our WTP estimates also imply that offering tasting trials to consumers is an effective marketing strategy to encourage potential purchases of PRNs for the rice noodle industry.

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 Is India Ready for Alt-Meat? Preferences and Willingness to Pay for Meat Alternatives

2020 ◽  
Vol 12 (11) ◽  
pp. 4377 ◽  
Author(s):  
Rashmit S. Arora ◽  
Daniel A. Brent ◽  
Edward C. Jaenicke
Keyword(s):  
Willingness To Pay ◽  
Choice Experiment ◽  
Latent Class ◽  
Consumer Preferences ◽  
Latent Class Model ◽  
Future Price ◽  
Indian Market ◽  
Viable Option ◽  
Class Model ◽  
Generation Plant

Little is known about the consumer preferences of next-generation plant-based and cell-based meat alternatives, two food technologies that offer a demand-side solution to the environmental, nutritional, and other societal concerns associated with animal-intensive agriculture. To address this gap, this paper estimates consumers’ willingness to pay for four sources of protein (conventional meat, plant-based meat, cell-based meat, and chickpeas) in a developing country with rising demand for meat—India. A latent class model of a discrete choice experiment conducted in Mumbai identifies four heterogeneous segments in the Indian market. Aggregating across all four segments, respondents are willing to pay a premium for plant-based meat and a smaller premium for cell-based meat over the price of conventional meat. However, our main findings show that these premiums strongly differ across the four consumer-class segments. The results offer important insights into future price points and policy options that might make these meat alternatives commercially successful, and therefore, a viable option in addressing societal concerns.

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 A Comparison of Mixture Modeling Approaches in Latent Class Models With External Variables Under Small Samples

2017 ◽  
Vol 78 (6) ◽  
pp. 925-951 ◽  
Author(s):  
Unkyung No ◽  
Sehee Hong
Keyword(s):  
Sample Size ◽  
Latent Class ◽  
Latent Class Model ◽  
Mixture Modeling ◽  
Small Sample ◽  
Outcome Variable ◽  
Parameter Estimates ◽  
Class Model ◽  
Modeling Approaches ◽  
Distal Outcome

The purpose of the present study is to compare performances of mixture modeling approaches (i.e., one-step approach, three-step maximum-likelihood approach, three-step BCH approach, and LTB approach) based on diverse sample size conditions. To carry out this research, two simulation studies were conducted with two different models, a latent class model with three predictor variables and a latent class model with one distal outcome variable. For the simulation, data were generated under the conditions of different sample sizes (100, 200, 300, 500, 1,000), entropy (0.6, 0.7, 0.8, 0.9), and the variance of a distal outcome (homoscedasticity, heteroscedasticity). For evaluation criteria, parameter estimates bias, standard error bias, mean squared error, and coverage were used. Results demonstrate that the three-step approaches produced more stable and better estimations than the other approaches even with a small sample size of 100. This research differs from previous studies in the sense that various models were used to compare the approaches and smaller sample size conditions were used. Furthermore, the results supporting the superiority of the three-step approaches even in poorly manipulated conditions indicate the advantage of these approaches.

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