The demand for imported fruit in China has increased dramatically since it first appeared in Chinese markets around 1993. Although imported fruit is much more expensive than domestically produced fruit and people’s income is much lower in China than in developed countries, imported fruit still attracts many willing buyers. Conventional concepts such as meeting basic needs or increasing consumer awareness of the importance of fresh fruit to a healthy lifestyle cannot adequately explain this phenomenon, as there is an abundance of fresh, cheap, local produce available in almost every Chinese market. There must be other factors influencing buying behaviour. To explore these factors and to examine the dynamics of the market for imported fruit, this research adopted a mixed qualitative-quantitative methodology guided by the paradigm of phenomenology. The research examined the characteristics of imported fruit itself, criteria imposed by Chinese buyers on these characteristics, the intended uses of imported fruit and their associated consumption values. To shed light on the possible influence of socio-economic factors, the research also compared buyers from two Chinese cities, Guangzhou and Urumqi. The former is one of the most developed cities in China and the latter is regarded as among the more backward and conservative cities in China. The research identified ten attributes that appeal to Chinese buyers. Six relate to the fruit’s physical attributes: that it has better appearance and packaging, lower chemical residues, better or different taste, and freshness. The remaining four relate to symbolic attributes associated with the fruit: that it represents achievement, wealth, personality and social status. Five intended uses of imported fruit were identified: for gifts, self-consumption, children, aged parents and patients. Four consumption values underlying these intentions were also identified: symbolism, concern for health, meeting basic needs and hedonism. However, the research revealed that no single combination of intended use and consumption value drives the demand for imported fruit in the Chinese market. Most frequently, it is a mix of hedonic and symbolic values behind a range of different intended uses that stimulates demand. Pursuing hedonic and symbolic values also leads to the visual quality of imported fruit generally being the most appealing attribute to Chinese buyers, a pattern common to both Guangzhou and Urumqi. These findings make a significant contribution to empirical knowledge about Chinese consumer behaviour. Results provide valuable insights into the interrelationships among product attributes, intended uses, consumption values and cultural values, and would give essential guidance to the development of strategies to market imported fruit in China. The research also examined limitations of current analytical approaches to the study of consumer behaviour. It demonstrated that approaches based on neural networks and fuzzy logic could be used independently or combined with conventional statistical methods to improve the explanation of consumer behaviour in this case. A comparison was carried out between the most popular form of neural networks (feedforward networks) and multivariate statistical methods in terms of their ability to predict behavioural intention through consumers’ attitudes towards products. Results demonstrated that neural networks were capable of capturing nonlinear aspects of complex relationships and producing better predictions than conventional statistical models. To explore consumer cognitive patterns, the research also compared K-means clustering with a Self-organizing Map (SOM) neural network in terms of the ability to cluster consumers on the basis of perceptions towards imported fruit attributes. Results indicate a superior outcome when K-means is used in conjunction with SOM in clustering analysis: using SOM to determine the ‘natural’ numbers of clusters and using K-means to do clustering. Finally, to quantitatively evaluate the impact of consumption values, this research develops a new approach that combines Means-end Chain theory with fuzzy logic theory. Given the global importance of the Chinese market, the successful application of neural networks and fuzzy logic in this study of the behaviour of Chinese consumers purchasing imported fruit could have wider ramifications. If the approach were proven in other applications, it could significantly improve the ability to understand the demand for consumer goods in China.

The demand for imported fruit in China has increased dramatically since it first appeared in Chinese markets around 1993. Although imported fruit is much more expensive than domestically produced fruit and people’s income is much lower in China than in developed countries, imported fruit still attracts many willing buyers. Conventional concepts such as meeting basic needs or increasing consumer awareness of the importance of fresh fruit to a healthy lifestyle cannot adequately explain this phenomenon, as there is an abundance of fresh, cheap, local produce available in almost every Chinese market. There must be other factors influencing buying behaviour. To explore these factors and to examine the dynamics of the market for imported fruit, this research adopted a mixed qualitative-quantitative methodology guided by the paradigm of phenomenology. The research examined the characteristics of imported fruit itself, criteria imposed by Chinese buyers on these characteristics, the intended uses of imported fruit and their associated consumption values. To shed light on the possible influence of socio-economic factors, the research also compared buyers from two Chinese cities, Guangzhou and Urumqi. The former is one of the most developed cities in China and the latter is regarded as among the more backward and conservative cities in China. The research identified ten attributes that appeal to Chinese buyers. Six relate to the fruit’s physical attributes: that it has better appearance and packaging, lower chemical residues, better or different taste, and freshness. The remaining four relate to symbolic attributes associated with the fruit: that it represents achievement, wealth, personality and social status. Five intended uses of imported fruit were identified: for gifts, self-consumption, children, aged parents and patients. Four consumption values underlying these intentions were also identified: symbolism, concern for health, meeting basic needs and hedonism. However, the research revealed that no single combination of intended use and consumption value drives the demand for imported fruit in the Chinese market. Most frequently, it is a mix of hedonic and symbolic values behind a range of different intended uses that stimulates demand. Pursuing hedonic and symbolic values also leads to the visual quality of imported fruit generally being the most appealing attribute to Chinese buyers, a pattern common to both Guangzhou and Urumqi. These findings make a significant contribution to empirical knowledge about Chinese consumer behaviour. Results provide valuable insights into the interrelationships among product attributes, intended uses, consumption values and cultural values, and would give essential guidance to the development of strategies to market imported fruit in China. The research also examined limitations of current analytical approaches to the study of consumer behaviour. It demonstrated that approaches based on neural networks and fuzzy logic could be used independently or combined with conventional statistical methods to improve the explanation of consumer behaviour in this case. A comparison was carried out between the most popular form of neural networks (feedforward networks) and multivariate statistical methods in terms of their ability to predict behavioural intention through consumers’ attitudes towards products. Results demonstrated that neural networks were capable of capturing nonlinear aspects of complex relationships and producing better predictions than conventional statistical models. To explore consumer cognitive patterns, the research also compared K-means clustering with a Self-organizing Map (SOM) neural network in terms of the ability to cluster consumers on the basis of perceptions towards imported fruit attributes. Results indicate a superior outcome when K-means is used in conjunction with SOM in clustering analysis: using SOM to determine the ‘natural’ numbers of clusters and using K-means to do clustering. Finally, to quantitatively evaluate the impact of consumption values, this research develops a new approach that combines Means-end Chain theory with fuzzy logic theory. Given the global importance of the Chinese market, the successful application of neural networks and fuzzy logic in this study of the behaviour of Chinese consumers purchasing imported fruit could have wider ramifications. If the approach were proven in other applications, it could significantly improve the ability to understand the demand for consumer goods in China.