產品涉入係指消費者認知該產品與其內在需求、興趣和價值觀的攸關程度與重視程度。結合直覺模糊集合及自動機，本研究發展統合前因與後果之產品涉入整合模型。本研究所建構之直覺模糊自動機，係以動態系統將輸入之前因（即個人因素與標的物／刺激因素）做轉換，產生系統輸出（即行為變數）；其中，該轉換是透過變動之內部狀態（即產品涉入）共同作用而達成。本研究藉由實證資料驗證所發展模型之可行性與正確性，根據實証結果指出直覺模糊自動機之成效端賴蘊含式與合成運算之擇定。整體而言，標準合成運算之實証結果較佳，且搭配不同蘊含式之預測能力相似。

Product involvement refers to the degree of importance consumers attach to a product or their subject recognition of a product's value. By coupling Atanassov's intuitionistic fuzzy sets and finite automata, we develop an integrated model of product involvement with its antecedents and consequences. We use an intuitionistic fuzzy automaton which is a dynamic system op-erating in discrete time that transforms sequences of the antecedents (personal and ob-ject/stimulus factors) received at the input of the system to sequences of the consequences (behavioral effects) produced at the output of the system. The transformation is accomplished by a changing internal state, i.e., product involvement. The empirical results indicate the fact that a fitting model relies on both the selection of implications and compositions in the in-tuitionistic fuzzy automata. On the average, the standard composition has the better effects used in the machine whether it combines with any kind of implicators.