Purchase intention of organic food under the influence of attributes, consumer trust and perceived value. Issue 3 (15th July 2019)

• Record Type: Journal Article
• Authors: Curvelo, Isabelle Cristina Galindo; Watanabe, Eluiza Alberto de Morais; Alfinito, Solange
• Is Part Of: Revista de gestão. Volume 26:Issue 3(2019)
• Page Start: 198
• Page End: 211
• Publication Date: 2019-07-15
• Subjects: Organic food -- Sensory appeal -- Trust -- Perceived value -- Purchase intention; Management -- Periodicals; Industrial management -- Periodicals; Business -- Periodicals; 658
• DOI: 10.1108/REGE-01-2018-0010
• Languages: English
• ISSNs: 1809-2276

Abstract

Abstract : Purpose: The consumption of organic food increases worldwide, which raises the need for studies that try to understand the variables that affect the consumption of this kind of food. The purpose of this paper is to analyze the influence of attributes, consumer trust and perceived value on purchase intention of organic food. Design/methodology/approach: A descriptive quantitative research was conducted through a survey of 247 valid cases of organic food consumers. For the purposes of analysis, exploratory factorial and linear regression analyzes were chosen. Findings: Exploratory factor analysis showed that all tested constructs were valid for the Brazilian context. Linear regression analyses showed that emotional value, consumer trust and the attribute "sensory appeal" affect the purchase intention of organic food. Emotional value had a stronger relationship and sensory appeal showed a negative relationship with purchase intention. Practical implications: Research results can help managers increase the likelihood of buying organic foods through strategic marketing management focused on emotional value and sensory appeal factors. Originality/value: The study offers value to the study of organic foods in view that this theme is not much explored in the Brazilian scenario even with the market in an increasing pattern, as well as the combination of perceived value, attributes, trust and purchase intention as variables in a single prediction model.