王福如

周建新

人文社會科學學院

文化產業研究博士學位課程(中文學制)

博士

2024

當博物館遇上AI：參觀者的博物館AI感知與溢價支付意願的研究

When Museums Meets AI: A Study on Visitors' AI Perception of Willingness to Pay Premium

博物館AI感知 ; 心理意象 ; 體驗價值 ; 消費者創新性 ; 溢價支付意願

Museum AI Perception ; Mental Imagery ; Experiential Value ; Consumer Innovativeness ; Willingness to Pay a Premium

公開日期：28/5/2028

近年來，隨著數字技術的快速演進，人工智能從過去的低智能水平邁向現今的強智能水平，引發了新一輪的科技革命。與此同時，人工智能應用已經成為各個行業領先戰略的重要基礎。因此，在人工智能時代的大背景下，研究博物館的數字化轉型以及人工智能對博物館消費者行為的影響變得尤為重要。特別是當前學界對人工智能如何影響博物館參觀者的消費決策機制尚不明確。本研究聚焦於博物館中的溢價支付意願，系統地探討了博物館AI感知如何影響溢價支付意願，並且引入體驗價值和心理意象作為平行中介變量，以探究博物館AI感知與溢價支付意願關係之間的作用機制。此外，還引入消費者創新性作為調節變量。本研究採用定量研究方法，通過在綫問卷調查收集樣本數據，使用Amos和SPSS軟件，通過結構方程模型和迴歸分析對研究模型的擬合度指標、顯著性等關鍵統計指標進行分析。研究結果顯示，博物館AI感知對溢價支付意願有顯著的正向作用，並且AI感知會通過正向影響心理意象和體驗價值而間接影響溢價支付意願，證明了心理意象和體驗價值的中介作用。研究還發現，消費者創新性對博物館AI感知與溢價支付意願之間的直接和間接關係（通過心理意象和體驗價值）具有正向的調節作用。結合技術接受模型（TAM）、創新擴散理論（IDT）和心理意象理論（MIT）為這些結果做了理論闡釋，這不僅為博物館研究提供了新的理論視角，也為實踐指導提供了依據。

In recent years, with the rapid iteration and evolution of digital technology, artificial intelligence (AI) has advanced from previous low-intelligence levels to current high-intelligence levels, triggering a new round of technological revolutions. Meanwhile, AI applications have become a crucial foundation for leading strategies across various industries. Therefore, against the backdrop of the AI era, studying the digital transformation of museums and how AI influences consumer behavior in museums has become particularly important. Especially, the academic community has yet to clearly understand how AI impacts the consumption decision-making mechanisms of museum visitors. This study focuses on the willingness to pay a premium in museum, systematically exploring how museum AI perception affects willingness to pay a premium. It introduces experiential value and mental imagery as parallel mediating variables to examine the mechanism of the relationship between museum AI perception and willingness to pay a premium. Additionally, consumer innovativeness is introduced as a moderating variable. This study adopts quantitative research methods, collecting sample data through online questionnaires, and uses Amos and SPSS software to analyze key statistical indicators such as model fit indices and significance through structural equation modeling and regression analysis.The results show that museum AI perception has a significant positive effect on the willingness to pay a premium, and AI perception indirectly affects this willingness by positively influencing mental imagery and experiential value, confirming the mediating role of mental imagery and experiential value. The study also finds that consumer innovativeness positively moderates both the direct and indirect relationships (through mental imagery and experiential value) between museum AI perception and willingness to pay a premium. The integration of the Technology Acceptance Model, Diffusion of Innovation Theory, and Mental Imagery Theory provides theoretical explanations for these findings, offering new theoretical perspectives and practical guidance for museum studies.

2025

中文

171

致謝 I
摘 要 IV
ABSTRACT V
目 錄 VII
圖目錄 X
表目錄 XI
第一章 緒 論 1
1.1研究背景與問題提出 1
1.2研究對象及概念界定 3
1.2.1 博物館 3
1.2.2 參觀者 5
1.2.3人工智能 5
1.2.4博物館消費 5
1.2.5博物館 AI感知 6
1.2.6體驗價值 6
1.2.7心理意象 6
1.2.8消費者創新性 7
1.2.9溢價支付意願 7
1.3研究意義 7
1.3.1理論意義 7
1.3.2現實意義 8
1.4研究目的 9
1.5研究內容 9
1.5.1開發和界定參觀者的博物館AI感知量表 9
1.5.2參觀者的博物館AI感知對溢價支付意願的影響 10
1.5.3參觀者的博物館AI感知與溢價支付意願之間的發生機制 10
1.5.4消費者創新性在參觀者的博物館AI感知與溢價支付意願之間的調節作用。 11
1.6研究思路與流程設計 11
1.7研究創新點 12
1.7.1理論創新 12
1.7.2實踐創新 13
第二章 文獻綜述 14
2.1人工智能與博物館的相關研究 14
2.1.1人工智能發展綜述 14
2.1.2人工智能在博物館中的運用 16
2.2博物館人工智能的感知研究 18
2.2.1博物館人工智能感知的定義 18
2.2.2人工智能感知（AI Perception）的前因變量研究 19
2.2.3人工智能感知（AI Perception）的結果變量研究 21
2.2.4人工智能感知的应用 22
2.3心理意象的相關研究 23
2.3.1定義及相关研究 23
2.3.2心理意象的前因研究 26
2.3.3心理意象的結果研究 27
2.4 體驗價值的相關研究 28
2.4.1定義 28
2.4.2體驗價值的前因研究 29
2.4.3體驗價值的結果變量研究 31
2.5 溢價購買意願的相關研究 32
2.5.1定義 32
2.5.2溢價購買意願的前因研究 33
2.5.3溢價購買意願的結果研究 35
2.6 消費者創新性的相關研究 35
2.6.1定義 35
2.6.2消費者創新性的前因研究 36
2.6.3消費者創新的結果變量研究 40
2.7理論基礎 41
2.7.1技術接受模型（Technology Acceptance Model） 41
2.7.2創新擴散理論（Diffusion of Innovations Theory） 44
2.7.3心理意象理論（Mental Imagery Theory） 47
2.8本章總結 51
2.8.1 現有文獻的貢獻與理論價值 51
2.8.2 現有研究的不足與理論缺口 52
2.8.3 對本研究的理論支持與研究啟示 52
第三章 研究模型與研究假設 54
3.1研究模型 54
3.2研究假設 54
3.2.1博物館AI感知與溢價支付意願的關係研究 54
3.2.2心理意象作為博物館AI感知與溢價支付意願的中介機制 57
3.2.3體驗價值作為博物館AI感知與溢價支付意願的中介機制 59
3.2.4消費者創新性的調節作用 61
第四章 博物館AI感知量表的開發設計 64
4.1 研究設計 64
4.2 博物館AI感知量表的開發思路 66
4.2.1 理論依據 66
4.2.2 開發原則 67
4.3 題項生成 68
4.3.1維度內容的構成 68
4.3.2 題項內容生成 69
4.3.3專家效度檢驗 70
4.4 預調研 72
4.4.1樣本特徵 72
4.4.2數據分析 72
4.5探索性因子分析 73
4.5.1 數據收集 73
4.5.2 因子結構分析 73
4.5.3 結構方程模型檢驗 75
4.6驗證性因子分析 78
4.6.1數據收集與描述 79
4.6.2 測量工具與測量模型 79
4.6.3驗證性因子分析結果 80
第五章 實證研究設計與方法 84
5.1 研究設計 84
5.2 研究變量與測量 84
5.2.1博物館AI感知 85
5.2.2體驗價值 85
5.2.3 心理意象 86
5.2.4 溢價支付意願 86
5.2.5 消費者創新性 86
5.3 問卷設計 87
5.3.1 問卷設計 87
5.4數據收集與清洗 90
5.4.1問卷髮放與樣本選擇 90
5.4.2數據清洗 90
5.5 樣本數據特徵 90
5.6 描述統計分析 92
5.7 相關性分析 93
5.8信度分析 94
5.9共同方法偏差 94
5.10共線性分析 96
5.11 驗證性因子分析 97
5.12 數據結果與假設檢驗 99
5.12.1主效應與中介效應分析與結果 99
5.12.2 調節效應分析與結果 100
第六章 研究結論 104
第七章 討論 107
7.1研究結論的討論 107
7.2 理論貢獻 108
7.3 實踐啟示 110
第八章 研究局限與未來方向 114
參考文獻 116
個人簡歷 165
附錄1：訪談提綱 167
附錄2：調查問卷 169

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