||A Study on the Innovation Resistance Factors of Users Using Face Scanning with Augmented Reality Glasses Try-on Service
||Department of Information Management
||In recent years, Augmented Reality and face scanning technology have gradually matured. Major companies have caught up with the trend of investment or research to develop their own innovative products. This results in the continuous launch of related applications and has been reshaping many past industries, services, ideas and ways of doing things. However, not every innovation service or product can be accepted or favored by consumers, so it is very important to investigate consumers’ resistance factors to innovation services. Products can be further improved and make consumers go from resisting innovation to accepting innovation through understanding the reasons for the resistance. Therefore, based on the Innovation resistance theory, this study explored the resistance factors of users using face scanning with Augmented Reality glasses try-on service. In addition, we adopted self-presence as the moderator to explore whether it can moderate the relationship between each barrier and innovation resistance. A total of 332 valid samples were collected through an online survey. We used SmartPLS 3.0 as the structural equation model (SEM) technique to do analysis. The results show that value barrier, privacy risk barrier, performance risk barrier, tradition barrier, and image barrier are important resistance factors of users using face scanning with Augmented Reality glasses try-on service. And self-presence can moderate the effects of value barrier, privacy risk barrier, performance risk barrier, image barrier on innovation resistance.
第1章 緒論 1
1.1 研究背景 1
1.2 研究動機與目的 2
第2章 文獻探討與假說推論 4
2.1 實境技術 4
2.2 臉部辨識與掃描 5
2.3 創新抵制 (Innovation Resistance) 6
2.3.1 創新的定義 6
2.3.2 創新、新技術的採用與抵制 7
2.3.3 創新抵制理論 (Innovation Resistance Theory) 9
2.4 研究架構 11
2.4.1 採用創新的障礙 12
2.4.2 調節變數-自我臨場感(Self-presence) 16
第3章 研究方法與步驟 20
3.1 問卷調查法 20
3.2 研究主題 20
3.3 資料蒐集方式 23
3.4 變項定義與衡量 23
3.4.1 使用障礙 24
3.4.2 價值障礙 24
3.4.3 風險障礙 25
3.4.4 傳統障礙 26
3.4.5 印象障礙 27
3.4.6 創新抵制 27
3.4.7 自我臨場感 28
第4章 研究結果 29
4.1 一般敘述性統計 29
4.2 量測模型 29
4.3 結構模式(Structural model) 33
4.4 分析結果 34
第5章 研究發現與討論 38
第6章 研究結論與建議 41
6.1 研究結論 41
6.2 管理意涵 41
6.3 研究限制與後續研究建議 43
第7章 參考文獻 44
圖 2 1研究架構 12
圖 3 1臉部掃描示意圖 21
圖 3 2臉部掃描示意圖 21
圖 3 3臉部掃描示意圖 21
圖 3 4臉部模型示意圖 22
圖 3 5臉部模型示意圖 22
圖 3 6臉部掃描列表示意圖 22
圖 3 7臉部數據示意圖 22
圖 3 8臉部數據示意圖 22
圖 3 9臉部數據示意圖 22
圖 3 10擴增實境試戴眼鏡示意圖 22
圖 4 1模型分析結果 33
圖 4 2自我臨場感對價值障礙與創新抵制行為意圖之間關係的調節效果分析 35
圖 4 3自我臨場感對隱私風險障礙與創新抵制行為意圖之間關係的調節效果分析 36
圖 4 4自我臨場感對績效風險障礙與創新抵制行為意圖之間關係的調節效果分析 36
圖 4 5自我臨場感對印象障礙與創新抵制行為意圖之間關係的調節效果分析 37
表 2 1應用創新抵制理論之研究整理 10
表 3 1使用障礙問項 24
表 3 2價值障礙問項 24
表 3 3隱私風險障礙問項 25
表 3 4績效風險障礙問項 26
表 3 5傳統障礙問項 26
表 3 6印象障礙問項 27
表 3 7創新抵制問項 27
表 3 8自我臨場感問項 28
表 4 1受測者之敘述性統計 29
表 4 2信度檢測結果 30
表 4 3效度檢測結果 30
表 4 4因素負荷量、交叉負荷量、平均數測量結果 31
表 4 5偏度、峰度、區別效度測量結果 32
表 4 6 R Square分析結果 33
表 4 7分析結果 34
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