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研究生:洪睿圻
研究生(外文):Jui-Chi Hung
論文名稱:應用大數據嵌入式智能口腔檢查系統提高患者口腔衛生效能之研究
論文名稱(外文):Apply Big Data Embeded with Oral Intelligence Check Up System Enhance Patient Oral Health Performance
指導教授:趙嘉成趙嘉成引用關係
指導教授(外文):Chia-Cheng Chao
口試委員:施國琛洪國興
口試日期:2016-06-13
學位類別:碩士
校院名稱:國立臺北教育大學
系所名稱:資訊科學系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
語文別:英文
論文頁數:131
中文關鍵詞:大數據社會交換理論科技接受模型後接受模型
外文關鍵詞:big dataSocial exchange theoryThe Information Adoption ModelPost-Acceptance Model
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數據在我們的世界中金額已被爆炸和分析大數據集,所謂的大數據將成為競爭的關鍵基礎,支撐生產率增長,創新和消費者剩餘的新浪潮,以及物聯網將燃油指數增長的數據中,在可預見的未來。社會交換理論是基於一個前提,即人的行為或社會互動活動,有形和無形的交換,尤其是獎勵和成本。近二十研究測試TAM在口腔保健和更多的經驗理論提升口腔保健IT論文的理論,日益被描繪成一個對口腔保健方面合適的理論,研究應用大數據嵌入式智能口腔檢查系統提高患者口腔衛生效能。
TAM is increasingly portrayed as a fitting theory for the oral health care context, to explore the possible impact of information technology use and the use of performance factors. 1. In this study, integration proposed A Post-Acceptance Model of IS Continuance. The Information Adoption Model to explore the development of oral check up system using the intention of continuing research model.
OHI system provide users of oral health related consulting services as well as experience sharing, but also allows many users want to do anything to this site can query information. The contributions of this research as follows: it is evident that TAM has had widespread application in explaining oral health care providers’ reactions to oral health IT. Most impressive is that the relationship between PU and intention to use or actual use of oral health IT is significant in every test, suggesting that to promote use and acceptance, the oral health IT must be perceived as useful. But in addition to the apparent strength of TAM in oral health care studies, there are remaining challenges. Both are addressed next, followed by a discussion of future directions of TAM research in oral health care.

TABLE OF CONTENTS
Chapter 1.Introduction 1
1.1 Rationale and motivation of this research 1
1.2. Research Purpose 2
1.3. Research Processes 4
Chapter 2.Literature 7
2.1. Social exchange theory 7
2.2. Tam model Technology acceptance model 13
2.2.1. Perceived usefulness 17
2.2.2. Perceived ease of use 18
2.2.3. Trust to use 20
2.2.4. Satisfaction 21
2.2.5. Continue to use 22
2.2.6. Indicator 24
2.3.Big data 27
2.4. Illustrate intelligence oral check up system 35
Chapter 3.Research method 39
3.1 Research scope 39
3.2 Research model and hypothesis 41
3.3 Research process 43
3.4 Research method 45
3.4.1 Data collection and preparation 45
3.4.2 Data mining method 47
3.4.3 Statistic method 47
3.5 Questionnaire design 51
3.5.1 Validity 52
3.5.2 Reliability 56
3.6 Questionnaire analysis method 57
3.6.1 Descriptive statistics 58
3.6.2 Validity analysis 58
3.6.3 Reliability analysis 58
3.6.4 Path analysis 58
Chapter 4.Research finding and discussion 61
4.1. Descriptive statistics: 61
4.2. Descriptive statistics description: 64
4.4. Pearson coefficient correlation analysis (Model I & Model II): 70
4.5. Regression analysis (Model I & Model II): 71
4.6. From research finding 74
Chapter 5.Conclusion 79
Reference 83
Appendices A : Figures 107
Appendices B : Tables 115
Appendices C : Questionnaire 127



LIST OF TABLES
Table 1:Factor Analysis of Perceived Usefulness and Ease of Use Items (Davis, 1989) 115
Table 2:Validity of scales 116
Table 3:Research scope 116
Table 4:Sample Demographic 117
Table 5:Mean of OHI Usefulness 118
Table 6:Mean of OHI ease of use 119
Table 7:Mean of OHI Trust to use 120
Table 8:Mean of OHI Satisfaction to use 121
Table 9:Mean of OHI Continue to use 122
Table 10:Descriptive Statistics of Model I 122
Table 11:Descriptive Statistics of Model II 122
Table 12:Correlations of Model I 123
Table 13:Correlations of Model II 123
Table 14:ANOVA(b) of Model I 123
Table 15:Coefficients(a) of Model I 123
Table 16:Model Summary of Model I 124
Table 17:ANOVA(b) of Model II 124
Table 18:Coefficients(a) of Model II 124
Table 19:Model Summary of Model II 124
Table 20:List of empirical results of Hypotheses 125


LIST OF FIGURES
Figure 1 : Research process 107
Figure 2 : Johnson & R.Johnson (1995) 107
Figure 3: Technology acceptance model (Davis, 1989) 108
Figure 4: Post-Acceptance Model (Bhattacherjee, 2001) 108
Figure 5 :Data science in the context of closely related processes in the organization. 109
Figure 6: Intelligence oral check up system 109
Figure 7: Intelligence oral check up system 110
Figure 8: Intelligence oral check up system 110
Figure 9: Research model 111
Figure 10:Research model with hypothesis 111
Figure 11: Research process 112
Figure 12: Data Analysis Method 113
Figure 13: Correlation Coefficient formula 113
Figure 14: Correlation Coefficient 113

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