scholarly journals Nutritional Knowledge and Health Consciousness: Do They Affect Consumer Wine Choices? Evidence from a Survey in Italy

Nutrients ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 84 ◽  
Author(s):  
Claudia Bazzani ◽  
Roberta Capitello ◽  
Elena Claire Ricci ◽  
Riccardo Scarpa ◽  
Diego Begalli
Keyword(s):  
Latent Class ◽  
Red Wine ◽  
Latent Class Model ◽  
Consumer Preference ◽  
Nutritional Knowledge ◽  
Alcohol Content ◽  
Higher Alcohol ◽  
Nutritional Information ◽  
Health Consciousness ◽  
Health Related

Wine is one of the few food products not subject to mandatory nutritional labelling, except for alcohol content. As such, health-related characteristics might be inferred by attributes related to production methods and alcohol content. This research focuses on the set of information currently reported on wine bottle labels, investigates the consumer’s use of such labels, and their preferences for information associated with ’naturalness’ such as clean labels and alcohol content. We conducted a survey on Italian consumers of red wine, which included a choice experiment. Results showed that health consciousness is an important driver in the use of wine labels. Estimates from a latent class model suggest that health consciousness, along with age, plays a significant role in defining consumer preference segments: the majority of our sample tended to prefer red wine characterized by ‘clean labels’, but younger and more health-conscious consumers showed a significant disutility for higher alcohol content. More traditional consumers revealed disutility for more unconventional ‘clean labels’, which were instead appreciated by a third group of consumers, called here ‘new clean trend lovers’. Preference for nutritional information such as lower alcohol content and clean labels distinguished the more health-conscious consumers, who belonged to the most likely preference class. Together, the results may suggest that nutritional information currently not mandatory for wine would be appreciated by a significant share of wine consumers.

Consumer preference for wine from hand-harvested grapes

2019 ◽  
Vol 122 (8) ◽  
pp. 2551-2567 ◽  
Author(s):  
Andrea Dominici ◽  
Fabio Boncinelli ◽  
Francesca Gerini ◽  
Enrico Marone
Keyword(s):  
Latent Class ◽  
Consumer Preferences ◽  
Latent Class Model ◽  
Interactive Effect ◽  
Consumer Preference ◽  
Random Parameter ◽  
Content Type ◽  
Organic Certification ◽  
Taste Heterogeneity ◽  
The Impact

Purpose The purpose of this paper is to investigate preferences for wine made from hand-harvested grapes, and the interactive effect between this attribute and organic certification. Design/methodology/approach Data were collected via an online choice experiment involving a sample of 408 Italian wine consumers. A random parameter logit was performed to estimate consumer preferences for wine attributes: harvest type, organic and the interaction between these. The experiment also includes geographical indications and price. Furthermore, a latent class model (LCM) is performed to investigate taste heterogeneity for the included wine attributes. Findings On average, consumers prefer the wine produced with hand-harvested grapes. The hypothesis of an interaction between organic and hand-harvested attributes is rejected. Using the LCM, the authors identify three segments with significant taste heterogeneity in terms of the magnitude and the sign of the parameters. Moreover, consumer attitudes towards food naturalness differ according to their belonging to the segments. Originality/value The novelty of this article is twofold. First, this study investigates, for the first time, the impact of the hand-harvested method on consumer wine preferences. Second, hand-harvesting and organic have independent values.

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 Impact of Nutritional Information on Consumers’ Willingness to Pay for Meat Products in Traditional Wet Markets of Taiwan

Foods ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1086
Author(s):  
Shang-Ho Yang ◽  
Ardiansyah Azhary Suhandoko ◽  
Dennis Chen
Keyword(s):  
Willingness To Pay ◽  
Dietary Habits ◽  
Meat Products ◽  
Nutrition Information ◽  
Key Factors ◽  
Random Utility Theory ◽  
Nutritional Information ◽  
Health Consciousness ◽  
Purchasing Intention ◽  
Health Related

The application of nutritional labels provides information regarding the health and nutritional value of products and allows consumers to engage in healthier dietary habits. However, not all types of retail markets provide full nutrition information for meat products. Since there is no nutritional information for fresh meat products in traditional wet markets, this study aimed to investigate consumer purchasing intention and willingness to pay (WTP) for this nutritional information in Taiwanese traditional wet markets. A total of 1420 valid respondents were examined using the random utility theory to explain consumer purchasing intention and WTP for nutritional information. Results showed that most (over 60%) consumers in traditional wet markets have positive purchasing intent for meat products with the nutrition information provided. Furthermore, the nutrition information in traditional wet markets significantly boosts consumers’ purchasing intention and WTP when consumers have a personal health awareness on meat, have proficient experience in buying meat, and continuously receive information from health-related media. Specifically, consumers’ shopping background and their level of health consciousness would be the key factors that would alter their WTP, if provided nutritional claims.

scholarly journals Consumer Preferences for Private Label Brand vs. National Brand Organic Juice and Eggs: A Latent Class Approach

2021 ◽  
Vol 13 (13) ◽  
pp. 7028
Author(s):  
Ellen J. Van Loo ◽  
Fien Minnens ◽  
Wim Verbeke
Keyword(s):  
Orange Juice ◽  
Latent Class ◽  
Consumer Preferences ◽  
Latent Class Model ◽  
Organic Food ◽  
Food Products ◽  
Organic Production ◽  
Private Label ◽  
National Brand ◽  
Major Barrier

Many retailers have expanded and diversified their private label food product assortment by offering premium-quality private label food products such as organic products. With price being identified as the major barrier for organic food purchases, private label organic food products could be a suitable and more affordable alternative for many consumers. While numerous studies have examined consumer preferences for organic food, very few organic food studies have incorporated the concept of private labels. This study addresses this research gap by studying consumer preferences and willingness to pay for national brand and private label organic food using a latent class model. Specifically, this study analyzes consumer preferences for organic eggs and orange juice and the effect of national branding versus private label. Findings show heterogeneity in consumer preferences for production method and brand, with three consumer segments being identified based on their preferences for both juice and eggs. For eggs, about half of the consumers prefer private label and organic production, whereas one-quarter clearly prefers organic, and another quarter is indifferent about the brand and the organic production. For orange juice, the majority (75%) prefer the national brand. In addition, one-quarter of the consumers prefers organic juice, and about one-third values both organic and the national brand.

scholarly journals Head-to-head comparison of clustering methods for heterogeneous data: a simulation-driven benchmark

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gregoire Preud’homme ◽  
Kevin Duarte ◽  
Kevin Dalleau ◽  
Claire Lacomblez ◽  
Emmanuel Bresso ◽  
...  
Keyword(s):  
Hierarchical Clustering ◽  
Latent Class ◽  
Latent Class Model ◽  
Real Life ◽  
Heterogeneous Data ◽  
Mixed Data ◽  
Categorical Variables ◽  
Clustering Methods ◽  
Model Based ◽  
Partitioning Around Medoids

AbstractThe choice of the most appropriate unsupervised machine-learning method for “heterogeneous” or “mixed” data, i.e. with both continuous and categorical variables, can be challenging. Our aim was to examine the performance of various clustering strategies for mixed data using both simulated and real-life data. We conducted a benchmark analysis of “ready-to-use” tools in R comparing 4 model-based (Kamila algorithm, Latent Class Analysis, Latent Class Model [LCM] and Clustering by Mixture Modeling) and 5 distance/dissimilarity-based (Gower distance or Unsupervised Extra Trees dissimilarity followed by hierarchical clustering or Partitioning Around Medoids, K-prototypes) clustering methods. Clustering performances were assessed by Adjusted Rand Index (ARI) on 1000 generated virtual populations consisting of mixed variables using 7 scenarios with varying population sizes, number of clusters, number of continuous and categorical variables, proportions of relevant (non-noisy) variables and degree of variable relevance (low, mild, high). Clustering methods were then applied on the EPHESUS randomized clinical trial data (a heart failure trial evaluating the effect of eplerenone) allowing to illustrate the differences between different clustering techniques. The simulations revealed the dominance of K-prototypes, Kamila and LCM models over all other methods. Overall, methods using dissimilarity matrices in classical algorithms such as Partitioning Around Medoids and Hierarchical Clustering had a lower ARI compared to model-based methods in all scenarios. When applying clustering methods to a real-life clinical dataset, LCM showed promising results with regard to differences in (1) clinical profiles across clusters, (2) prognostic performance (highest C-index) and (3) identification of patient subgroups with substantial treatment benefit. The present findings suggest key differences in clustering performance between the tested algorithms (limited to tools readily available in R). In most of the tested scenarios, model-based methods (in particular the Kamila and LCM packages) and K-prototypes typically performed best in the setting of heterogeneous data.

scholarly journals An ecological latent class model of adolescent risk and protective factors: Implications for substance use and depression prevention

2021 ◽  
pp. 016502542110055
Author(s):  
Benjamin L. Bayly ◽  
Sara A. Vasilenko
Keyword(s):  
Substance Use ◽  
Native American ◽  
Latent Class ◽  
Latent Class Model ◽  
Single Parent ◽  
Low Risk ◽  
Heavy Episodic Drinking ◽  
Health Study ◽  
Adolescent Risk ◽  
Parent Relationship

To provide a comprehensive view of the unique contexts shaping adolescent development in the U.S., we utilized latent class analysis (LCA) with indicators of risk and protection across multiple domains (family, peers, school, neighborhood) and examined how latent class membership predicted heavy episodic drinking, illicit substance use, and depression in adolescence and 6 years later when participants were young adults. Data came from Wave 1 (W1) and Wave 3 (W3) of the nationally representative U.S.-based Add Health study ( N = 6,649; Mage W1 = 14.06; Mage W3 = 20.38; 53.8% female; 56.1% White/European American, 22.8% Black/African American, 9.5% Hispanic, 6.7% Biracial, Asian or Pacific Islander 4.2%, American Indian/Native American 0.7%). A six-class solution was selected with classes named: Two Parent: Low Risk, Two Parent: Relationship Risks, Two Parent: Neighborhood Risks, Single Parent: Low Risk, Single Parent: Relationship Risks, and Single Parent: Multidimensional Risk. Subsequent analyses suggested that adolescent social relationships are particularly important for prevention interventions as the classes marked by substance using peers and a lack of closeness to parents and teachers in adolescence (Two Parent: Relationship Risks and Single Parent: Relationship Risks) had consistently poorer outcomes in adolescence and young adulthood.

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