Data/hora: 10/06/2024 16:25:23

Provedor de dados: 	31	
País: 	United States	
Título: 	Consumers' Demand for Pork Quality: Applying Semantic Network Analysis	
Autores: 	Grebitus,   Carola; Bruhn,   Maike.	
Data: 	2006-05-05	
Ano: 	2006	
Palavras-chave: 	Cognitive structures; Concept mapping; Food quality; Network analysis; Semantic networks; Spreading activation network model; Food Consumption/Nutrition/Food Safety; Livestock Production/Industries.	
Resumo: 	Consideration of consumers' demand for food quality entails several aspects. Quality itself is a complex and dynamic concept, and constantly evolving technical progress may cause changes in consumers' judgment of quality. To improve our understanding of the factors influencing the demand for quality, food quality must be defined and measured from the consumer's perspective (Cardello, 1995). The present analysis addresses the issue of food quality, focusing on pork-the food that respondents were concerned about. To gain insight into consumers' demand, we analyzed their perception and evaluation and focused on their cognitive structures concerning pork quality. In order to more fully account for consumers' concerns about the origin of pork, in 2004 we conducted a consumer survey of private households. The qualitative approach of concept mapping was used to uncover the cognitive structures. Network analysis was applied to interpret the results. In order to make recommendations to enterprises, we needed to know what kind of demand emerges from the given food quality schema. By establishing the importance and relative positions of the attributes, we find that the country of origin and butcher may be the two factors that have the biggest influence on consumers' decisions about the purchase of pork.	
Tipo: 	Working or Discussion Paper	
Idioma: 	Inglês	
Identificador: 	21036

http://purl.umn.edu/18402	
Editor: 	AgEcon Search	
Relação: 	Iowa State University&gt;Center for Agricultural and Rural Development&gt;CARD Working Paper Series

CARD Working Paper 06-WP 423	
Formato: 	33

application/pdf