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Article
Publication date: 15 February 2021

Ningning Feng, Airong Zhang, Rieks D. van Klinken and Lijuan Cui

The purpose of this paper is to develop an integrative model where perceived competence, perceived warmth and “clean green image” of an exporting country are drivers for…

Abstract

Purpose

The purpose of this paper is to develop an integrative model where perceived competence, perceived warmth and “clean green image” of an exporting country are drivers for Chinese consumers' trust in food quality and food safety, which in turn predict their willingness to buy fresh fruit from this country.

Design/methodology/approach

Participants (N = 1,583) from the three metropolises in China were surveyed on their perceptions of the competence, warmth and clean green image of seven contrasting exporting countries and their trust in quality, trust in safety and willingness to buy fresh fruit imported from those countries.

Findings

Results support the proposed integrative model, explaining 39%–55% of the variance in willingness to buy. Clean green image was the strongest predictor of willingness to buy through enhanced trust in food quality. The effects of country competence and warmth on willingness to buy through trust in food safety and quality varied with exporting country.

Research limitations/implications

The integrative model and findings of this study can help agri-food industries develop an in-depth understanding of Chinese consumers and to develop targeted strategies to increase willingness to buy through improving consumer trust in food quality and safety.

Originality/value

This study extends the country image framework which previously only consisted of human characteristics (i.e. perceived competence and warmth) by incorporating environmental characteristics (i.e. clean green image) in examining consumers' willingness to buy imported fresh fruit.

Details

British Food Journal, vol. 123 no. 6
Type: Research Article
ISSN: 0007-070X

Keywords

Content available
Article
Publication date: 10 April 2009

Jin Chen and Jing Guo

652

Abstract

Details

The Electronic Library, vol. 27 no. 2
Type: Research Article
ISSN: 0264-0473

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