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系統識別號 U0026-3007201912050700
論文名稱(中文) 隱私權政策偏好之研究-聯合分析法之應用
論文名稱(英文) A Research on the Privacy Policy Preference - Application of Conjoint Analysis
校院名稱 成功大學
系所名稱(中) 電信管理研究所
系所名稱(英) Institute of Telecommunications and Management
學年度 107
學期 2
出版年 108
研究生(中文) 洪俊中
研究生(英文) Jun-Zhong Hong
學號 R96061015
學位類別 碩士
語文別 英文
論文頁數 100頁
口試委員 指導教授-黃郁雯
口試委員-蔡東峻
口試委員-高凱聲
中文關鍵字 隱私權  隱私權政策  GDPR  聯合分析法  群集分析法 
英文關鍵字 Privacy  Privacy Policy  GDPR  Conjoint Analysis  Cluster Analysis 
學科別分類
中文摘要 資料在今天的經濟與企業活動中扮演著舉足輕重的角色,舉凡服務改善、成本管理、服務創新、精準行銷都有資料參與的身影。然而,取得資料並不容易,尤其個人資料的取得及使用,需要資料當事人的同意授權。隱私權政策便是用來連結資料當事人與資料使用者的橋梁,提供關於個人資料蒐集、用途、處理等必要的資訊,建立雙方信任的基礎。若隱私權條款所說明的資訊是合理可信的,則網路使用者或資料當事人便會傾向同意個人資料的使用。對於提供個人資料的意願與資料主體對於隱私屬性的態度息息相關,這些隱私屬性包含個人可識別資訊的蒐集、資料使用的透明度、對於個人資料的控制力、第三方資料來源的使用。
由於隱私屬性對於網路使用者的偏好有積極性影響,組織勢必需了解網路使用者決策的關鍵因素,以便更有效的安排與部屬隱私權政策條款。了解網路使用者對於隱私的主觀偏好,可以幫助我們更好的了解網路用者的行為傾向。本研究使用聯合分析法,檢視網路使用者對於隱私權條款的主觀偏好,歸納出網路使用者對於不同隱私屬性偏好的相對重要度。
根據網路使用者對於隱私權政策中,對隱私屬性的主觀偏好結果,本研究發現整體網路使用者最重視個人可識別資訊的蒐集,其次依序為第三方使用、對個人資料的控制能力、資料使用的透明度。而群集分析的結果顯示,控制敏感度族群所重視的隱私屬性,依序為個人資料的控制能力、第三方資料使用、資料使用透明度以及個人可識別資訊的蒐集;個資敏感族群所重視的隱私屬性,依續為個人可識別資訊的蒐集、資料使用透明度、控制能力及第三方資料使用。此外研究結果亦發現性別、年齡、網路使用活動及隱私識別程度等均與隱私權政策的偏好有關係。本研究依據偏好結果,對資料主管機關以及網頁管理者提出相關建議。
英文摘要 Data play an important role in today’s economy and result in significant competitive advantages for businesses. However, those data wouldn’t come without any cost. Customers’ consent is still a basic requirement before collecting and processing users’ personal information. Privacy policies play an important role in bridging websites and Internet users. The privacy policy is designed to build a trusting relationship between the organization and internet users by informing users about how their personal data will be used. Internet users will tend to be more satisfied with their online transactions if they believe that the underlying procedures are fair. Willingness to provide personal information online is closely related to attitudes about privacy including collection of personal information, transparency, control-ability, and third-party sharing. Since privacy regulations may have complex effects on users, organizations need to determine which regulation is exerting a stronger impact on individual decisions in order to construct adequate strategies. This research first examined the Internet users’ preference to privacy policy by conjoint analysis.
The result of joint analysis indicates that the overall participants are most concerned about the collection of personally identifiable information (PII) followed by the third-party sharing, the control ability, and transparency. The control-sensitive cluster weighed their control ability and third-party sharing heavily. The PII-sensitive cluster weighed the collection of PII heavily. Some suggestions for policymakers and internet managers were provided by on the result of the study.
論文目次 Table of Contents IV
List of Table VI
List of Figure VII
Chapter One Introduction 1
1.1 Background 1
1.2 Motivation and Research Objectives 4
Chapter Two Literature Review 6
2.1 Concept of the Privacy 6
2.2 Privacy Policy 8
2.3 The Personal Data Protection Regulatory 9
2.3.1 Fair Information Practice Principles 9
2.3.2 Better Protection under General Data Protection Regulation 12
2.3.3 The Personal Information Protection Act in Taiwan 16
2.4 Preferences Related to Privacy Policies 22
2.4.1 The Impact of Collection of Personally Identifiable Information 23
2.4.2 The Impact of Transparency 24
2.4.3 The Impact of Ability to Control 26
2.4.4 The Impact of Third Parties Sharing 27
Chapter Three Methodology 28
3.1 Research Framework 28
3.2 Conjoint Analysis Method 29
3.2.1 The Concept of Conjoint Analysis 29
3.2.2 Choosing Analysis Model 32
3.3 Designing Stimuli 33
3.3.1 Pre-study 33
3.3.2 Levels of Attributes 35
3.3.3 The Controlled Variables 39
3.3.4 The Validity of Attributes 44
3.4 Collection of Data 44
3.4.1 Presentation Method 44
3.4.2 Measure of Preference 45
3.4.3 Demonstration Method 45
3.4.4 Development of Stimulus 46
3.5 Evaluating Model Goodness-of-Fit 47
3.5.1 Part-worth Estimation 47
3.5.2 Aggregate Level and Disaggregate Level 47
3.5.3 Goodness-of-Fit Measure 48
3.6 Interpreting the Results 48
3.6.1 Description of Statistics Analysis 48
3.6.2 Accessing the Theoretical Consistency 49
3.6.3 Attribute Relative Importance 50
3.6.4 Cluster Analysis 50
3.7 Validating the Result 51
Chapter Four Data Analysis and Discussion 52
4.1 Data Collection Procedure 52
4.2 Goodness-of-Fit Measure 52
4.3 Structure of Sample 53
4.3.1 Background of Participants 53
4.3.2 Internet Behavior 55
4.3.3 Online Privacy Literacy 56
4.4 Result of the Conjoint Analysis 57
4.4.1 Attribute Relative Importance 57
4.4.2 Attributes Utility Estimation 59
4.4.3 Control Variables Analysis 61
4.4.4 Cluster Analysis Method 62
4.4.5 Conjoint Analysis of Each Cluster 65
4.4.6 The Comparison Between Two Clusters 74
4.5 Summary 78
4.5.1 The Overall Sample 78
4.5.2 The Control-sensitive Cluster 78
4.5.3 The PII-sensitive Cluster 79
4.5.4 Comparison with Two Clusters 80
Chapter Five Conclusion 81
5.1 Preference Toward Privacy Policies 81
5.1.1 General Discussion of the Results 81
5.1.2 Closer Discussion about Each Clusters 82
5.1.3 Difference Between Two Clusters 85
5.2 Suggestions for Future Research 87
5.2.1 Suggestions for Policymakers 87
5.2.2 Suggestions for Website Managers 89
5.3 Limitations of the Current Research 91
Reference 93
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