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An Integrated Model of Consumer Involvement Based on Fuzzy Automata

基於模糊自動機之消費者涉入整合模型

摘要


長久以來,在消費者行為和行銷研究領域裡,涉入己成為一個重要的變數。許多關於涉入的理論與發展己被提出,其中包括不同形式的涉入及其測量方式。在現實世界裡,每位消費者決策過程不只受單一涉入影響,但是從現有的文獻很難找到同時處理多種類型涉入及其前因和後果的研究。由於個人的意見和態度存在著複雜性和不確定性,且抽象的數據資料並不一定能表達人們內在想法,故本研究運用模糊集合解決不確定和不精確情況,且將人類的主觀意見轉化成精確的量化數值。本研究以消費者涉入為實證研究標的,全盤考量並收集消費者涉入的前因和後果資料。將消費者的涉入分為產品涉入,廣告涉入,購買涉入,情境涉入,和持久性涉入,以進一步討論不同涉入間之相互作用。我們利用模糊自動機的內部運作類似於個人消費涉入之概念,發展消費者涉入之整合模型。透過實證結果發現在涉入之模糊自動機中,相對於蘊含式,合成運算對結果之影響較為顯著。簡而言之,模糊自動機不僅可以處理大量的變數,也可處理不同類型的涉入。

並列摘要


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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