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題名：探討「方法目的鏈」理論之演繹、擴展與整合建構模式
作者：傅貞夙
作者(外文)：Fu, Chen-Su
校院名稱：國立成功大學
系所名稱：企業管理學系
指導教授：吳萬益
學位類別：博士
出版日期：2010
主題關鍵詞：方法目的鏈；消費知覺圖；內容分析；抽象性分析；階梯矩陣；混合市場區隔；Means-end chain；Hierarchical value map；Content analysis；Abstractness analysis；Laddering matrix；Hybrid segmentation
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自Gutman與Reynolds二位學者於1970年代末期倡導「方法目的鏈」理論以來，方法目的鏈理論已經是一項重要的行銷理論。方法目的鏈主張消費者消費某一特定產品應有對該項產品的某一（些）屬性偏好，而這一（些）屬性偏好將可引發其消費後之消費結果，進而滿足其價值追求，此種產品的「屬性—結果—價值」連結認知內涵，可採階梯法所繪製的消費知覺圖，來描繪消費者與產品之間的關係。
「方法目的鏈」理論發展迄今，已成為剖析消費者行為理論的重要方法。在方法目的鏈理論的發展進程中，學者多半採用多變量分析整合「方法目的鏈」理論的應用模式，改善「方法目的鏈」理論的分析方法，卻少有針對階梯法以及階梯法所建構之消費者知覺內容進行改善。由於階梯法所繪製的知覺圖有著研究人員主觀判斷的缺點，為了克服該項缺點，本研究乃發展出「階梯—矩陣分析模式」，並藉該項分析方法推演其程式邏輯，客觀揭露關連矩陣彙總表中的消費偏好資訊，以提供程式設計人員「階梯—矩陣程式流程」之程式設計邏輯，期能作為開發「方法目的鏈」理論分析應用軟體之基礎。本研究除了改善「方法目的鏈」理論分析方法外，並結合其他行銷觀念，推演與發展出「方法目的—混合區隔模式」與「行銷審計認知層級模式」，提供管理學者與行銷人員更具發展性與應用性的方法目的鏈理論分析方法。總體而言，本研究所提出之「階梯—矩陣分析模式」、「階梯—矩陣程式流程」、「方法目的—混合區隔模式」與「行銷審計認知層級模式」等四項分析模式，以有形產品之汽車和飲料以及無形產品的便利商店服務品項和銀行服務等為實證標的，透過深度訪談與結構式問卷進行資料蒐集工作，其實證分析之結果，應可有效輔助與擴展「方法目的鏈」理論之強化、發展與應用層面，研究人員與行銷人員除可採用本研究之分析方法作為各類產品或產業之實證分析方法外，並可假本研究之分析方法，擴展與豐富行銷理論之內涵。
In the late 1970s, Gutman and Reynolds (1979) introduced the means-end chain (MEC) theory. The MEC theory has become an important marketing theory. The basic notion of MEC theory is that product attributes are means to help consumers achieve desired ends, namely, values through the consequences of product consumptions. Product attributes, consequences and values are thus assumed to be linked hierarchically in a cognitive structure. The attribute-consequence-value hierarchies derived from consumers through a laddering technique can be used to generate a hierarchical value map (HVM), which graphically denotes a set of means-end chains. Such HVM describes the consumer-product relationships.
Today, many researchers have confirmed the significance of MEC theory for understanding consumer behaviors. In the development of MEC theory, most methodological articles focus on the MEC applications of multivariate analysis integration, but only rarely emphasize the improvement of the qualitative laddering technique. Owing to its deficits related to the subjective judgment of researchers in predetermining the cutoff value for HVM construction, the laddering technique requires for further improvement. To overcome these weaknesses of MEC analysis, this dissertation presents a novel laddering-matrix analysis (LMA) and its programming procedure termed a laddering-matrix programming procedure (LMPP) to explore the information of the summary implication matrix without bias, thus providing extremely useful material for developing MEC computer software. Furthermore, integrating the MEC theory with other marketing concepts and methodologies, the author proposes the means-end hybrid segmentation model (MHSM) and the hierarchical cognition of marketing audit (HCMA) model to provide researchers and marketers with new insights for MEC development and application. In this dissertation, cars and beverages are selected as the research objects of tangible products whereas bank services and the service items of convenience stores are the representatives for intangible products. One-on-one in-depth interviews and structural questionnaires are employed to confirm the effectiveness of the proposed four models. The proposed four models (LMA, LMPP, MHSM and HCMA) are expected to contribute to MEC enhancement, development and application. Future research may consider adopting these models to investigate various products and industries and utilizing them to deduce new insights of marketing theories.
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