網際網路與社群媒體的興起,顧客的行為模式與消費型態產生巨大變化,企業分析資料的方式面臨巨大影響與挑戰。這些非結構性的動態顧客資料,正是企業獲利以及尋找全新機會與發掘商機的關鍵所在。 本研究採用Osterwalder and Pigneur(2010)的商業模式為理論基礎,從顧客導向的策略方向進行探討,利用資料探勘技術發掘更有價值的指標,建構出商業智慧的決策框架。協助管理決策者做出更即時、更精確及更具可行性預測的決策。 本研究的實證分析結果如下:一、商業模式圖:理論的商業模式圖具備策略地圖的參考價值;數據的商業模式圖可以進行評估、驗證、修正或改善。二、數據框架:資料轉換成靈活的數據,提供各種類型數據的組合。三、決策框架:提供整體儀表板,隨時更新資料,掌握動態趨勢、特定事件或對象的特徵、警訊,以及領先指標。四、資料探勘:發掘更深層的預測性指標、關聯性指標與相關性指標。 本研究的學術貢獻如下:一、提供管理決策者一個結合理論基礎、科學方法與實務應用的決策框架。二、提供統一超商一個具有商業價值的決策方案,作為目前營運的改善藍圖與預測未來的決策參考。
In the era of the Internet and social media, it has undergone tremendous changes in customers' behavior. Similarly, the way of data analysis of organizations also has tremendous impact and challenges. These unstructured dynamic customer profiles are the key to profitability, new opportunities and potential business. This study adopted the business model of Osterwalder and Pigneur (2010) as the theoretical foundation and targeted the direction of customer-oriented strategy. Using data mining technology to explore more valuable indicators constructed a decision-making framework of business intelligence. The ultimate goal is to assist managements to make more accurate, robust, feasible and predictable decisions. The results of empirical analyses are as follows: 1. The theoretical business model canvas is presented as a strategy map; the data-based business model canvas can be evaluated, tested, corrected or improved. 2. The data framework is flexible in various combinations of data. 3. The decision framework provides an overall dashboard with updates the data whenever necessary, grasps dynamic trends, characteristics of events or an object, warning signals and leading indicators. 4. Data mining helps to explore predictive indicators, association indicators and correlation indicators. The contributions of this study are as follows: 1. It provides a model of decision framework that combines a theoretical foundation, scientific methods, and practical applications. 2. It provides a decision proposal with business insight to President Chain Store Corporation for the current operational improvement and future forecasts.