隨著企業愈加依賴人工智慧（Artificial Intelligence, AI）強化其數位行銷能力（Digital Marketing Capability, DMC），現有文獻對於企業如何在不同環境情境下，將智慧資本（Intellectual Capital, IC）有效轉化為數位行銷競爭優勢的理解仍相當有限。本研究立基於敏捷行銷與動態能力理論，主張智慧資本需透過企業 AI 能力（AI Capability, AIC）方能轉化為具體的數位行銷成效，且此轉換過程會受到開發式創新（Exploitative Innovation, EI）與外部技術動盪（Technological Turbulence, TT）之重要影響。本研究蒐集台灣北、中、南部企業之問卷資料，採用 PROCESS Model 72 進行統計推論，並以結構方程驗證性因數分析（CFA）驗證研究構面與測量模式之效度。實證結果強力支持智慧資本經由企業 AI 能力影響數位行銷能力之中介效果；當模型納入 AI 能力後，智慧資本對數位行銷能力的直接效果不再顯著，顯示 AI 能力在此傳導機制中扮演核心關鍵角色。另一方面，研究亦發現開發式創新雖未對智慧資本或 AI 能力的個別路徑產生顯著干擾，但與外部技術動盪之三階交互作用卻達到顯著水準，顯示兩者會共同形塑企業運用 AI 能力的價值高度。條件式間接效果分析進一步指出：在低技術動盪情境下，智慧資本經由 AI 能力提升數位行銷能力的間接效果最為強烈；相對地，當外部技術動盪高且開發式創新較低時，此一間接效果幾乎消失。整體而言，本研究不僅深化我們對外部動盪環境中智慧資本、AI 能力與數位行銷能力三者關係的理解，也揭示開發式創新與技術動盪在關鍵能力轉換機制中的邊際條件角色。研究結果對於企業在不確定環境中如何配置智慧資源、發展 AI 能力並建構行銷競爭優勢，提供重要之理論意涵與實務指引。

As firms increasingly rely on artificial intelligence (AI) to strengthen their digital marketing capability (DMC), scholarly understanding remains limited regarding how internal intellectual capital (IC) is transformed into digital marketing advantages under varying environmental conditions. Drawing on the Agile Marketing and the literature on exploitative innovation, this study argues that intellectual capital enhances digital marketing capability primarily through AI capability (AIC), and that this indirect effect is shaped by two critical contextual factors: exploitative innovation (EI) and external technological turbulence (TT). Using survey data collected from firms across northern, central, and southern Taiwan, we employed PROCESS Model 72 for statistical estimation and conducted confirmatory factor analyses to validate construct reliability and validity. The results provide strong support for the mediating role of AI capability in the IC to DMC linkage. Once AI capability is included in the model, the direct effect of intellectual capital on digital marketing capability becomes nonsignificant, underscoring AI capability as the central mechanism through which IC is converted into marketing value.
Although exploitative innovation alone does not significantly strengthen either the IC to AI capability or the AI capability to DMC paths, its joint interaction with technological turbulence yields a significant three way moderating effect. Conditional indirect effect analyses further show that, under low technological turbulence, the indirect effect of IC on DMC through AI capability is strongest. In contrast, when technological turbulence is high and exploitative innovation is low, this indirect effect nearly disappears.
Overall, the findings refine our understanding of capability formation under dynamic environments and reveal the boundary conditions under which AI capability translates organizational knowledge resources into superior digital marketing outcomes. The study provides both theoretical insight and practical guidance for firms seeking to leverage AI strategically in uncertain and fast-changing technological contexts.

論文審定書 i
誌謝 ii
摘要 iv
Abstract v
目錄 vii
圖 次 ix
表 次 x
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 5
第二章 文獻探討 7
第一節 企業數位行銷能力 7
第二節 企業智慧資本 9
第三節 企業AI能力 11
第四節 企業內部開發式創新 13
第五節 外部技術動盪 14
第六節 敏捷行銷 17
第七節 動態能力理論 19
第八節 研究缺口 23
第九節 研究假設與研究架構 25
第三章 研究設計與方法 39
第一節 研究流程 40
第二節 研究設計與量表 40
第三節 研究樣本、測量工具 43
第四節 測量工具與操作化程序 43
第五節 信度與效度檢驗 45
第六節 效度分析的理論基礎與實證驗證 46
第七節 模型估計與資料分析程序 48
第八節 研究倫理與資料保護 49
第四章 研究發現與討論 51
第一節 研究發現 51
第二節 研究討論 67
第五章 研究學術意涵與管理意涵 73
第一節 學術意涵延伸 73
第二節 管理意涵延伸 76
第六章 研究限制與未來研究方向 80
第七章 結論 82
參考文獻 86
附錄 99
Digital Marketing Capabilities: 99
Intellectual Capital: 100
Technology Capability: (AI Capability) 101
Organizational Ambidexterity Capabilities 102
Radical Innovation 103
Market Turbulence 103

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