The Application of Fuzzy Logic in Measuring Consumption Values: Using data of Chinese consumers buying imported fruit

The conventional approach used to examine consumption values of consumers for a given product category is the Means-End Chain (MEC) approach. The MEC retrieves values through establishing links between product attributes and consumption values by an interviewing technique called laddering. The laddering technique is a qualitative approach with limited ability to deal with segments of consumers who hold multiple consumption values. In this research fuzzy logic theory is applied in conjunction with laddering to measure the consumption values of Chinese consumers purchasing imported fruit. Results demonstrate that fuzzy logic is not only an effective approach to quantifying the consumption values that consumers pursue in a give context, but also, when consumers hold multiple values of unequal weights, it can reveal how consumption values are mingled.

[1]  Ran Wei,et al.  MASS MEDIA AND CONSUMERIST VALUES IN THE PEOPLE'S REPUBLIC OF CHINA , 1999 .

[2]  T. J. Reynolds,et al.  Laddering theory, method, analysis, and interpretation. , 2001 .

[3]  R. Stross The Return of Advertising in China: A Survey of the Ideological Reversal , 1990, The China Quarterly.

[4]  N. Feather Values and national identification: Australian evidence , 1994 .

[5]  A consumer-oriented approach to the marketing of food products: Application of means-end chain theory to the consumption of beef. , 1997 .

[6]  S. Moores Interpreting audiences: the ethnography of media consumption. , 1993 .

[7]  D. N. Hinkle The change of personal constructs from the viewpoint of a theory of construct implications , 1965 .

[8]  C. Samuel Craig,et al.  The changing dynamic of consumer behavior: Implications for cross-cultural research , 1997 .

[9]  R. Rust,et al.  Modeling Fuzzy Data in Qualitative Marketing Research , 2000 .

[10]  Michel Wedel,et al.  Agricultural marketing and consumer behavior in a changing world. Proceedings European Association of Agricultural Economists Seminar. , 1996 .

[11]  Carl F. Mela,et al.  Using fuzzy set theoretic techniques to identify preference rules from interactions in the linear model: an empirical study , 1995 .

[12]  Naresh K. Malhotra,et al.  Marketing Research: An Applied Orientation , 1993 .

[13]  George J. Klir,et al.  Fuzzy sets, uncertainty and information , 1988 .

[14]  Frenkel Ter Hofstede,et al.  Linking attribtes benefits and consumer values a powerful approach to market segmentation, brand positioning, and advertising strategy , 2000 .

[15]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[16]  Michel Dupagne,et al.  Effects of U.S. Television Programs on Foreign Audiences: A Meta-Analysis , 1994 .

[17]  H. Hruschka Market definition and segmentation using fuzzy clustering methods , 1986 .

[18]  Julie L. Ozanne,et al.  A Study of Information Search Behavior during the Categorization of New Products , 1992 .

[19]  Terry L. Childers,et al.  Understanding how Product Attributes Influence Product Categorization: Development and Validation of Fuzzy Set-Based Measures of Gradedness in Product Categories , 1999 .

[20]  A. Woodside,et al.  Personal Values and Consumer Psychology , 1984 .

[21]  M. Wedel,et al.  A Clusterwise Regression Method for Simultaneous Fuzzy Market Structuring and Benefit Segmentation , 1991 .

[22]  Ximing Sun,et al.  Attitudes and consumption values of consumers of imported fruit in Guangzhou, China , 2002 .

[23]  M. Wedel,et al.  A fuzzy clusterwise regression approach to benefit segmentation , 1989 .

[24]  M. Wedel,et al.  An investigation into the association pattern technique as a quantitative approach to measuring means-end chains , 1998 .

[25]  R. Pollay,et al.  Advertising, propaganda, and value change in economic development : The new cultural revolution in China and attitudes toward advertising , 1990 .

[26]  B. Loken,et al.  Alternative Approaches to Understanding the Determinants of Typicality , 1990 .