基于模糊自动机的消费者参与集成模型

Ting-Yu Chen, Hsiao-Pin Wang, Li-Hsuan Yen
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引用次数: 0

摘要

长期以来,参与已成为消费者行为和营销研究中的一个重要变量。目前已有大量关于涉入的文献,提出了涉入的不同类型,涉入的测量方法也随之出现。在现实世界中,每个消费者的决策过程都不受单一参与的影响,但在现有的文献中,我们很难找到同时讨论多种前因、后果和多种参与的研究。由于个人的观点和态度具有复杂性和不确定性的特点,调查的数据不一定能反映出被调查者的内心想法。本研究充分利用模糊集来解决不确定和不精确的条件,将属于人类的意见转化为更准确的数量。本实证研究以消费者涉入为研究对象,全面收集了大量消费者涉入的前因和后果。特别是将消费者涉入分为产品涉入、广告涉入、购买涉入、情境涉入和持久涉入,进一步探讨其相互作用。我们利用模糊自动机的内部运作类似于个体消费者涉入的发展,建立了一个消费者涉入的综合模型。实证结果表明,拟合模型除了依赖于隐含意义的选择外,还依赖于模糊自动机中成分的选择。模糊自动机不仅可以同时处理大量的变量,还可以处理不同类型的涉入之间的相互作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Integrated Model of Consumer Involvement Based on Fuzzy Automata
Involvement has become an important variable in consumer behavior and marketing research for a long time. Large amount of literature about involvement has existed now, and different types of involvement have been proposed, and so has the measurement of involvement. In real world, every consumer's decision-making process is not affected by just single involvement, but we are hard to find the research which discusses many antecedents, consequences, and more than one type of involvement at the same time from the existing literature. Because an individual's opinions and attitude have the characteristics of complexity and uncertainty, the data from investigation do not necessarily present a subject's inner minds. This study makes the most of the fuzzy sets, which solve uncertain and imprecise conditions, to transform the opinions belonging to human beings into the more accurate quantity. Consumer involvement is regarded as the object for this empirical study that comprehensively collects plenty of antecedents and consequences for consumer involvement. Especially, consumer involvement is categorized into product involvement, advertising involvement, purchase involvement, situational involvement, and enduring involvement to further discuss their interactions. We take advantage of the fuzzy automata that the inner operation resembles the development of consumer involvement for individuals to develop an integrated model of consumer involvement. The empirical results indicate that in addition to the selection of implications, a fitting model relies on the selection of compositions in the fuzzy automata. The fuzzy automata not only can deal with a great number of variables at the same time, but the interaction between different types of involvement as well.
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