Why Do We Buy Traditional Foods?

Contini, Caterina; Boncinelli, Fabio; Casini, Leonardo; Pagnotta, Gabriele; Romano, Caterina; Scozzafava, Gabriele

doi:10.1080/10454446.2016.1141137

Cited by 14 publications

(15 citation statements)

References 31 publications

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“…As for the variable “origin”, there is extensive literature that links traditional products with the place of origin (Verbeke and Roosen, 2009; Cerjak et al , 2014; Contini et al , 2016). European Union have a regulation (Becker and Staus, 2008) that relates the quality product with environmental and traditional characteristics, to the place of origin (European Union, 2006).…”

Section: Resultsmentioning

confidence: 99%

Factors associated with the consumption of traditional foods in central Mexico

Serrano-Cruz

Espinoza‐Ortega

Sepúlveda³

et al. 2018

BFJ

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Purpose The purpose of this paper is to identify the factors associated with the consumption of traditional foods (TFs) in central Mexico. Design/methodology/approach A total of 512 surveys were applied to consumers in central Mexico. The survey included a free word association with TF and an example, the food choice questionnaire, and the sociodemographic characteristics of respondents. A binary logistic regression was carried out comparing regular TF consumers with non-regular TF consumers. Findings Men tend to eat TFs in more regular way than women. People with heavier consumption habits associate TF with “authenticity/way of doing”, “origin” and “habit”, which are reinforced both by TF examples and the FCQ variables. Foods considered traditional were classified as cooked (elaborated under specific recipes of gastronomic heritage) and uncooked. Both groups comprise central foods, basic in the Mexican diet, in which maize, chili and beans are outstanding. Research limitations/implications The study did not comprehend the whole country and not consider specific food categories. Practical implications Provides important information on the factors that drive consumption of TFs in Mexico, information that may be useful in valorisation processes. Social implications Results may support the commercialisation of these foods, and lead to an improvement in the livelihoods of producers of TFs. Originality/value In Mexico, the study of consumers has not been addressed. Therefore, this is a pioneer study that documents the factors associated with the consumption of TFs.

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Section: Resultsmentioning

confidence: 99%

Factors associated with the consumption of traditional foods in central Mexico

Serrano-Cruz

Espinoza‐Ortega

Sepúlveda³

et al. 2018

BFJ

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“…Beyond extended methodologies, CUB modeling is also under active development for applications; in this respect, we quote original marketing research in the field of food preferences and sensory analysis: Piccolo and D’Elia (2008), Iannario et al (2012), Corduas, Cinquanta, and Ievoli (2013), Capecchi et al (2016), Mauracher, Procidano, and Sacchi (2016), and Contini et al (2016). We also quote recent new perspectives and applications (Hwang, Sohn, and Oh 2015; Low 2017; Finch and Hernández Finch 2020; Hu, Zhou, and Sharma 2020; and Xu and Zhang 2021), providing evidence of an increasing international interest toward the CUB paradigm.…”

Section: Discussionmentioning

confidence: 99%

Fitting mixture models for feeling and uncertainty for rating data analysis

Cerulli

Simone

Iorio

et al. 2022

The Stata Journal: Promoting communications on statistics and S

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In this article, we present the command cub, which fits ordinal rating data using combination of uniform and binomial (CUB) models, a class of finite mixture distributions accounting for both feeling and uncertainty of the response process. CUB identifies the components that define the mixture in the baseline model specification. We apply maximum likelihood methods to estimate feeling and uncertainty parameters, which are possibly explained in terms of covariates. An extension to inflated CUB models is discussed. We also present a subcommand, scattercub, for visualization of results. We then illustrate the use of cub using a case study on students’ satisfaction for the orientation services provided by the University of Naples Federico II in Italy.

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“…Geographical distribution of the consumers’ sample in the extant studies. Most of the studies included in this literature review focused on the OO preference for Italian (35.5%) [ 7 , 8 , 9 , 11 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ] and Spanish (24.4%) [ 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 ] consumers, followed by studies focused on the OO preference of consumers from Greece (11.1%) [ 51 , 52 , 53 , 54 , 55 ], the USA (6.7%) [ 56 , 57 , 58 ], Chile [ 59 , 60 ], UK and German [ 61 , 62 ] and Tunisia [ 63 , 64 ] (4.4%), Japan [ 65 ], Brazil [ 66 ], Netherlands [ 30 ], Switzerland [ 67 ], Uruguay [ 68 ], France [ 63 ] (2.2%).…”

Section: Content Analysismentioning

confidence: 99%

“…In order to provide a report, we group the size of the studies into four categories: less than 200 consumers, between 200 and 500 consumers, between 500 and 1000 consumers, and more than 1000 consumers. It emerges that 31.1% of the studies involve a sample with a size of less than 200 consumers [ 27 , 28 , 31 , 36 , 48 , 52 , 53 , 56 , 57 , 58 , 62 , 66 , 67 , 68 ], 33.3% of the studies involve a sample with a size between 200 and 500 consumers [ 30 , 36 , 39 , 40 , 42 , 43 , 44 , 45 , 46 , 49 , 59 , 60 , 63 , 64 , 69 ], 22.2% of the studies involve a sample with a size between 500 and 1000 consumers [ 29 , 32 , 33 , 37 , 41 , 47 , 51 , 61 , 70 ] and only 11.11% of the studies involve a sample with a size more than 1000 consumers [ 34 , 38 , 54 , 55 , 65 ]. In 8.8% of the reviewed studies, the sample size is not declared [ 7 , 8 , 9 , 50 ].…”

Section: Content Analysismentioning

confidence: 99%

“…Thirty-two reviewed studies have focused on consumer acceptance and preferences for origin-related cues associated with the EVOO product. Most of the studies reported as origin cues were important drivers for EVOO or OO choices [ 7 , 8 , 9 , 11 , 27 , 30 , 32 , 34 , 36 , 39 , 41 , 43 , 44 , 45 , 46 , 49 , 51 , 53 , 57 , 59 , 60 , 61 , 63 , 65 , 66 , 67 , 69 , 71 ]. An exception to these findings was Mtimet et al’s [ 64 ] study, according to which the region of origin attribute is not related to Tunisian consumers’ purchasing decisions of EVOO.…”

Section: Content Analysismentioning

confidence: 99%

See 1 more Smart Citation

Consumer Acceptance and Preference for Olive Oil Attributes—A Review

Latino

Devitiis

Corallo

et al. 2022

Foods

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Olive oil is largely produced in southern European countries. It encompasses a mix of search (e.g., price, color, packaging features), experience (e.g., taste), and credence attributes (e.g., organic, health claim). The importance of these attributes on consumers’ attitudes and preferences for Olive oil has been explored quite extensively in the past. However, a recent body of literature has focused on product nutritional information and health claims in shaping consumers’ attitudes and preferences for Olive oil. This work aims to offer an updated review of consumers’ acceptance and preferences for Olive oil features. Applying the Systematic Literature Review method, a sample of 47 studies published over the last 20 years was reviewed through descriptive and content analysis. The following attributes, grouped in search, experience, and credence categories, were discussed: origin, sustainability, brand, health and safety, the production process, packaging, color, taste and flavor, and product features. The discussion of marketing and research implications closes the study. The study provides an overview of the literature background of consumer behaviors of Olive Oil, investigating the recent literature focused on product nutritional information and health claims.

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Why Do We Buy Traditional Foods?

Cited by 14 publications

References 31 publications

Factors associated with the consumption of traditional foods in central Mexico

Factors associated with the consumption of traditional foods in central Mexico

Fitting mixture models for feeling and uncertainty for rating data analysis

Consumer Acceptance and Preference for Olive Oil Attributes—A Review

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