面對電子商務的蓬勃發展，讓貨架空間有限且毛利低的實體零售通路必須要更加了解消費者的決策，因此通路業者紛紛透過資料分析希望找出消費需求及偏好，以有效制定行銷策略提高消費者對實體零售通路的忠誠度。在眾多的模型中，多元羅吉斯模型因具有易於瞭解的數學架構及容易估計的優勢廣為實務及學術界使用，因此本研究也採用此模型做分析，並透過蒙地卡羅馬可夫鏈進行參數估計，本研究以美國零售通路啤酒銷售資料進行實證研究。實證結果顯示，「CausalAD」對於消費者有正面影響，意味著消費者可以透過CausalAD獲取更多商品促銷的資訊，進而增加購買。另外，優惠券的使用除了讓消費者享有折扣外還能更進一步將商品的促銷方案傳達給消費者。

Due to the competition from e-commerce, physical stores which have low margin and limited shelf space must grasp consumer decision-making. Therefore, to make effective marketing plan, retailers apply various data analysis techniques to better understand consumer preference and consumer demands. Among marketing models, multinomial logit model is one of the most popular approaches in both industry and academic because of its mathematical simplicity. Therefore, in this research, multinomial logit model was applied to analyze consumer brand choice in the US beer retail market. The empirical result shows that CausalAd and Coupon had positive impact on consumer brand choice.

摘要 i
Abstract ii
誌謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究流程 3
第二章 文獻探討 4
2.1 選擇模型 4
2.2 多元羅吉斯模型 5
2.3 層級貝氏模型 7
2.3.1 層級貝氏模型之簡介 7
2.3.2 層級貝氏模型相關文獻回顧 8
第三章 研究方法 10
3.1 貝氏統計 10
3.2 蒙地卡羅–馬可夫鏈演算法 11
3.2.1 Gibbs Sampling 12
3.2.2 Random–Walk Metropolis–Hasting Algorithm 13
3.3 多元羅吉斯模型 14
3.4 參數估計 14
3.5 模擬實驗 16
第四章 實證分析 19
4.1 敘述統計 19
4.2 實證結果 22
第五章 結論與限制 25
5.1 研究結論 25
5.2 研究建議 25
參考文獻 26

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