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.

Smallholder preferences and willingness-to-pay measures for microcredit

2018 ◽  
Vol 10 (3) ◽  
pp. 462-481 ◽  
Author(s):  
Zhao Ding ◽  
Awudu Abdulai
Keyword(s):  
Willingness To Pay ◽  
Interest Rates ◽  
Latent Class ◽  
Smallholder Farmers ◽  
Mixed Logit ◽  
Latent Class Models ◽  
Preference Heterogeneity ◽  
Content Type ◽  
Lower Interest Rate ◽  
Class Models

Purpose The purpose of this paper is to examine smallholders’ preferences and willingness to pay for microcredit products with varying attribute combinations, in order to contribute to the debate on the optimal design of rural microcredit. Design/methodology/approach Data used in this study are based on a discrete choice experiment from 552 randomly selected respondents. Mixed logit and latent class models are estimated to examine the choice probability and sources of preference heterogeneity. Endogenous attribute attendance models are applied to account for attribute non-attendance (ANA) phenomenon, focusing on separate non-attendance probability as well as joint non-attendance probability. Findings The results demonstrate that preference heterogeneity and ANA exist in the smallholder farmers’ microcredit choices. Averagely, smallholder farmers prefer longer credit period, smaller credit size, lower transaction costs and lower interest rate. Guarantor collateral method and installment repayment positively affect their preferences as well. Moreover, respondents are found to be willing to pay more for the attributes they consider important. The microcredit providers are able to attract new customers under the current interest rates, if the combination of attributes is appropriately adjusted. Originality/value This study contributes to the debate by assessing the preference trade-off of different microcredit attributes more comprehensively than in previous analyses, by taking preference heterogeneity and ANA into account.

scholarly journals SELECTION OF BREEDING STOCK BY U.S. MEAT GOAT PRODUCERS

2017 ◽  
Vol 49 (3) ◽  
pp. 416-437 ◽  
Author(s):  
NARAYAN NYAUPANE ◽  
JEFFREY GILLESPIE ◽  
KENNETH MCMILLIN ◽  
ROBERT HARRISON ◽  
ISAAC SITIENEI
Keyword(s):  
Latent Class ◽  
Mixed Logit ◽  
Nationwide Survey ◽  
Latent Class Models ◽  
Discrete Choice Experiments ◽  
Preference Heterogeneity ◽  
Breeding Stock ◽  
Meat Goat ◽  
Class Models ◽  
Selection Of

AbstractUsing nationwide survey data, we investigate U.S. meat goat producer preferences and willingness to pay for meat goat breeding stock attributes. Discrete choice experiments were employed, and mixed logit and latent class models were used for analysis. Results showed that producers preferred animals that were highly masculine/feminine, had good structure and soundness, and were of the Boer breed, whereas they preferred fewer animals that were older, of Kiko and Spanish breeds, and priced higher. Significant preference heterogeneity was found among the respondents. Larger-scale producers had greater preference for high masculinity/femininity, good structure and soundness, and Boer bucks.

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.

Some New Methods for an Old Problem: Modeling Preference Changes and Competitive Market Structures in Pretest Market Data

1997 ◽  
Vol 34 (1) ◽  
pp. 130-142 ◽  
Author(s):  
Ulf Böckenholt ◽  
William R. Dillon
Keyword(s):  
Latent Class ◽  
New Product ◽  
Latent Class Models ◽  
Preference Heterogeneity ◽  
Time Varying ◽  
Modeling Framework ◽  
Market Structures ◽  
Before And After ◽  
Class Models ◽  
Choice Probabilities

Despite the enormous amounts of resources devoted to concept and product testing and the continued use of pretest market (PTM) modeling procedures, estimates of new product failures are still alarmingly high. The primary objectives of PTM modeling are to forecast the market share/sales volume of a new product and to determine the sources of new product share at the aggregate market level. The authors describe a new approach that is designed to provide a parsimonious description of competitive changes before and after a new product is introduced by identifying latent segments (i.e., groups of consumers) that vary in size and composition with respect to the relative preferences for a set of brands before and after a new product is introduced. Each latent segment represents a particular preference state characterized by a set of segment-level choice probabilities. The modeling framework is based on a class of dynamic latent class models that explicitly recognize two major types of preference heterogeneity: (1) heterogeneity caused by before-after changes in latent preferences for the brands (i.e., time-varying relative choice probabilities) and/or (2) heterogeneity caused by consumers changing their latent preference segment in response to a new product (i.e., time varying latent segment probabilities). As is demonstrated in the empirical application, the dynamic latent class models provide a comprehensive framework for understanding how a new product changes the competitive landscape.

On the robustness of latent class models for diagnostic testing with no gold standard

2021 ◽  
Author(s):  
Matthew R. Schofield ◽  
Michael J. Maze ◽  
John A. Crump ◽  
Matthew P. Rubach ◽  
Renee Galloway ◽  
...  
Keyword(s):  
Gold Standard ◽  
Latent Class ◽  
Diagnostic Testing ◽  
Latent Class Models ◽  
No Gold Standard ◽  
Class Models

STARD-BLCM: Standards for the Reporting of Diagnostic accuracy studies that use Bayesian Latent Class Models

2017 ◽  
Vol 138 ◽  
pp. 37-47 ◽  
Author(s):  
Polychronis Kostoulas ◽  
Søren S. Nielsen ◽  
Adam J. Branscum ◽  
Wesley O. Johnson ◽  
Nandini Dendukuri ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Latent Class ◽  
Latent Class Models ◽  
Class Models
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