結合層級分析與多元尺度於智慧型手機品牌

Abstract

今日，在極為競爭與快速變化之商業環境下，企業必要與它們主要的競爭對手有所區別，特別地在產品設計與服務創新方面以確保並擴大在市場的佔有率。考量消費者聲音的產品設計與市場定位乃為鞏固消費者忠誠度與吸納更多新消費群最重要的第一步。而在現實中消費者對於品牌的感覺和看法是比較模糊和主觀的，且不易量化與分析。本文透過視覺性與系統化提出了一種混合框架之評估方式，結合了層級程序分析(AHP)、多元尺度分析(MDS)和權重績效分析(IPA)歸納出消費者對於品牌和功能屬性間架構與關係，特別是整合層級程序分析結合多元尺度分析上可以進而匯出一張表示屬性的最佳特性與辨識度於品牌上的知覺圖。為了細分消費者群集以利市場區隔則使用了偏好圖來提供評估者評價屬性和評估消費者對各品牌的偏好程度。此外，權重績效分析可以提供決策者對目標企業進行標竿分析。台灣地區結果顯示，擁有屬性競爭優勢之領先品牌有HTC、APPLE和SAMSUNG，另外四個品牌屬性競爭較弱勢為落後品牌。目前評估者選擇之理想品牌為HTC，是所有評估者最偏好之品牌。最後利用IPA分析可以提供和協助決策者快速做決策與分析。

Today, to survive in an extremely competitive and turbulent business environment, enterprises are forced to differentiate themselves from their main competitors along one or multiple dimensions, particularly in product design or service innovation. One of the most important strategies is product positioning that is capable to consolidate customers’ loyalties and even to acquire distinct groups, concurrently. In reality, customers’ overall perceptions of competing brands are usually vaguer and more subjective than their preferences toward product/service attributes. To systematically visualize their underlying structure among respondents, brands, and attributes, this paper proposes a hybrid framework which combines analytical hierarchy process (AHP), multidimensional scaling (MDS), with the importance-performance analysis (IPA). In particular, by integrating AHP with MDS, a perceptual map is employed to display which attributes best characterize/distinguish benchmarking brands. In order to form a basis for customer segmentation, a preference map is generated to reveal how respondents perceive evaluation attributes and how they favor various competing brands. Furthermore, the IPA could offer decision support to assist a target enterprise in carrying out benchmarking analysis. In Taiwan, the results show that the attributes of competitive advantage leading brand HTC, APPLE, and the SAMSUNG, four other brand attributes competition is weaker for backward brand. Respondents to select the ideal brand HTC, is the most preferred brand for all respondents. Finally, the IPA analysis can provide and assist decision-makers to make decisions and analysis.