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研究生： 陳彥安
Chen, Yen-An
論文名稱： 基於GAI之知識整合行銷支援模式設計與技術開發
Design and Development of GAI-Based Knowledge Integration Marketing Support Model and Technology
指導教授： 陳裕民
Chen, Yu-Ming
共同指導教授: Hsu, MaxWell K.
Hsu, Maxwell K.
陳育仁
Chen, Yuh-Jen
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 製造資訊與系統研究所
Institute of Manufacturing Information and Systems
論文出版年： 2025
畢業學年度： 113
語文別： 中文
論文頁數： 125
中文關鍵詞： 行銷決策支援 、大型語言模型 、檢索增強生成 、知識圖譜
外文關鍵詞： Marketing Decision Support, Large Language Models, Retrieval-Augmented Generation, Knowledge Graph
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    • 隨著市場競爭日趨激烈，行銷決策的品質直接影響企業的市場表現和財務績效。然而，中小企業在行銷管理方面普遍面臨專業人才不足、資源有限以及行銷經驗難以系統化累積等挑戰。傳統的行銷決策過程高度依賴個人經驗與直覺判斷，缺乏標準化流程和知識管理機制，導致決策品質不穩定且知識傳承困難。
    本研究提出整合式行銷決策支援模式，旨在透過大型語言模型技術與企業私有資料的整合，為中小企業建立客觀、一致且全面的行銷決策支援系統。研究首先設計OOPDCA (Observation-Objective-Plan-Do-Check-Assessment-Analysis-Action) 行銷活動循環框架，將傳統PDCA (Plan-Do-Check-Act) 循環擴展為八階段的完整循環系統。同時，提出三層次行銷決策支援模式，包括行銷細節支援、OOPDCA樣板產生和OOPDCA決策支援，針對不同層級的決策需求提供差異化支援。
    在技術實現方面，本研究採用檢索增強生成(RAG)技術開發行銷數位分身平台，使用LightRAG框架結合知識圖譜與向量表示。透過文件元素分析、圖片描述提取和元素整合等技術，將圖表資料轉化為結構知識庫。系統能夠理解企業特定的行銷環境，提供客製化決策建議，並具備多模態資料處理能力。
    實驗結果顯示，行銷數位分身成功實現三層次決策支援功能，能夠有效理解和運用企業私有知識，提供專業且相關的行銷建議。本研究不僅為中小企業提供實用的行銷決策支援工具，也為大型語言模型在企業專業領域的應用提供參考，對促進企業數位轉型和提升行銷效率具有重要意義。

    Small and medium-sized enterprises (SMEs) face challenges in marketing decision-making, including insufficient professional talent, limited resources, and difficulties in experience transfer. Traditional decision-making processes rely on personal experience and lack standardized procedures. This study develops an intelligent marketing decision support model that integrates large language models with enterprise private data to establish an objective and consistent decision support system.
    The research proposes an eight-stage OOPDCA marketing cycle framework and a three-tier decision support model (marketing detail support, template generation, and decision support). Technically, a Marketing Digital Twin platform is developed using RAG architecture with the LightRAG framework to process multimodal enterprise data, transforming text and charts into structured knowledge bases.
    Experimental validation demonstrates that the system successfully achieves three-tier decision support and effectively utilizes enterprise private knowledge to provide professional recommendations. This study provides practical decision-making tools for SMEs and holds significant importance for enterprise digital transformation and marketing efficiency enhancement.

    摘要 ii 致謝 ix 圖目錄 xiii 表目錄 xv 第一章、緒論 1 1.1 研究背景 1 1.2 研究動機 2 1.3 研究目的 4 1.4 研究問題 4 1.5 研究項目與方法 6 1.6 研究步驟 9 第二章、文獻探討 10 2.1 領域文獻探討 10 2.1.1 行銷知識管理 10 2.1.2 行銷決策支援 10 2.1.3 中小企業行銷現況 11 2.2 相關技術探討 12 2.2.1 大型語言模型（LLM） 12 2.2.2 檢索增強生成技術（RAG） 13 2.2.3 LightRAG 15 2.3 相關研究：企業導入大型語言模型應用現況 16 2.4 文獻探討總結 17 第三章、整合式行銷決策支援模式方法設計 19 3.1 整合式行銷決策支援模式構思 19 3.1.1 現行中小企業行銷決策制定現況 （As-Is） 19 3.1.2 整合式行銷決策支援模式 （To-Be） 20 3.2 OOPDCA行銷活動循環設計 21 3.3 三層次行銷決策支援模式設計 25 3.4 行銷數位分身（Marketing Digital Twin）功能定義與開發方法設計 28 3.4.1 行銷數位分身功能設計 28 3.4.2 行銷數位分身開發方法設計 29 第四章、資料分析與資料處理技術開發 31 4.1 資料種類與需求定義 31 4.1.1 行銷工具及基本概念 31 4.1.2 OOPDCA行銷活動循環定義 32 4.1.3 企業內部資料 32 4.2 資料來源與收集方法 33 4.2.1 行銷工具及基本概念資料收集方法 34 4.2.2 OOPDCA行銷活動循環定義資料收集方法 34 4.2.3 企業內部資料收集方法 34 4.3 資料處理與分析技術開發 42 4.3.1 文件元素分析與提取技術開發 42 4.3.2 圖片描述提取技術開發 45 4.3.3 元素整合技術開發 51 第五章、行銷數位分身模型技術開發 52 5.1以LightRAG建構行銷數位分身方法設計 52 5.2 檢索知識庫準備技術開發 53 5.2.1 LightRAG建立核心索引知識庫流程 53 5.2.2 LightRAG自定義知識圖譜資料前處理 56 5.2.3 實作LightRAG自定義知識圖譜 65 5.2.4 視覺化知識圖譜 69 5.3 數據檢索與生成回答方法技術開發 71 5.3.1 生成回答流程 71 5.3.2 知識圖譜查詢的上下文構建 76 5.3.3 圖片資料檢索過程驗證 79 5.4 行銷數位分身網頁設計與開發 85 5.5 實驗 87 5.5.1 實驗方法 87 5.5.2 實驗結果與分析 89 第六章、結論 91 6.1 研究成果與創新 91 6.2 研究貢獻 93 6.3 未來展望 94 參考文獻 96 附錄 100

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