Systematic behavior research for understanding consumer decision making.
This study incorporates means-end chain (MEC) theory and dynamic programming for understanding the implications of consumer decision making. The conceptual framework of this study can help programmers design information systems for analyzing consumption behaviors. Such analyses will provide marketers with meaningful information for formulating marketing strategies. The main contributions of this article are as follows: (1) to enable researchers to obtain information for consumer cognitive hierarchies utilizing an information system, (2) to enhance the functions of traditional MEC methodology and provide an integrated method for analyzing consumption information, and (3) to construct an information system for analyzing consumer decision-making processes.
Lin
Chin-Feng
CF
National Pingtung Institute of Commerce, Taiwan. cfl@npic.edu.tw
D000465:Algorithms; D035841:Behavioral Research / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D003657:Decision Making / Q000502:physiology*; D006801:Humans; D015233:Models, Statistical