隨著消費者行為的改變與與宅經濟的潮流，電子商務近年來呈現快速的成長。在電商平台中，為能達到精準行銷的目的，推薦符合消費者需求的個性化廣告(Online Behavioral Advertising, OBA)已成為各大電商平台重要的行銷與廣告媒介。OBA廣告是基於消費者的輪廓、線上瀏覽軌跡、過往檢索紀錄等個人隱私資訊，透過推薦系統向消費者推薦/預測其可能所需的廣告資訊，用以協助消費者降低搜尋資訊。但是，OBA在為消費者帶來福祉的同時，卻也隱藏著隱私洩漏方面的潛在風險。過往研究認為，隱私關注是消費者網上購物的過程中重要的影響因素之一。因此，本研究以OBA廣告為主為核心，並以自我參照理論與隱私計算理論為基礎，探討廣告自我相關、隱私價值傾向、隱私關注、知覺隱私侵入、廣告推薦疑慮與廣告點擊意願間相互的影響效果。
本研究以便利抽樣方式，針對一年內有使用過台灣常見電商平台，且年滿20歲的消費者進行樣本調查，透過網路問卷最終共蒐集604份有效樣本。接著，應用結構方程模型與SPSS進行假說檢定，包含路徑分析、中介與調節效果的驗證。研究結果發現，廣告自我相關、隱私價值傾向對隱私關注有正向影響關係。另外，隱私關注、知覺隱私侵入對廣告點擊意願產生負向的影響性；在中介效果的分析中發現，知覺隱私侵入具有部分中介效果。

E-commerce has its sprouting growth over recent years with the change of consumer behavior and the trend of Stay-at-Home Economy. To reach the goal of precision marketing on E-commerce platforms, diverse E-commerce platforms recommend OBA (Online Behavioral Advertising) to correspond to the consumers’ needs, has been the important media in marketing and advertising. Based on some personal privacy information such as profiles of consumers, online browser tracking, previous search records, and so on, OBA assists consumers in reducing search information by recommending/ predicting their needs of advertising information through the recommendation system. However, with the incoming pros OBA brings to consumers, meanwhile it also brings potential risk of data breach. In the previous studies, privacy concern is among one of the vital contributing factors when consumers shop online. Therefore, based on self-referencing theory and privacy calculus theory, this research focuses on OBA as the core, investigating perceived ad relevance, disposition to value privacy, privacy concerns, perception of intrusion, and the mutual effect of influence between ad recommended skepticism and click-through intentions.
In this study, we employ the method of convenience sampling through web questionnaire survey for the consumers whose age are more than twenty years old; at the same time, had once used Taiwan’s common e-commerce platforms; and finally collect 604 effective samples in total. It then goes on to apply Structural Equation Modeling and SPSS to examine experimental hypothesis, including the verification of path analysis, mediated and regulatory effect. From the study results, we find that when it comes to perceived ad relevance, disposition to value privacy, perceived ad relevance and privacy concerns, they have a significant positive effect on o perception of privacy intrusion. When it comes to privacy concerns and perception of intrusion, they have a significant negative effect toward ad click-through intentions. While perception of privacy intrusion has an intervening effect toward privacy concerns and ad click-through intentions.

論文審定書 i
中文摘要 ii
英文摘要 iii
圖目錄 vii
表目錄 viii
壹、緒論 1
第一節 研究背景 1
第二節 研究動機 4
第三節 研究問題 7
第四節 研究目的 7
貳、 文獻探討 9
第一節 個性化廣告(Online Behavioral Advertising, OBA) 9
第二節 自我參照理論與廣告自我相關 13
第三節 隱私計算理論與隱私價值傾向 15
第四節 隱私關注 16
第五節 知覺隱私侵入 17
第六節 廣告推薦疑慮 18
第七節 廣告點擊意願 19
參、研究方法 21
第一節 研究架構 21
第二節 假說推論 22
第三節 研究方法與問卷蒐集 27
第四節 研究變項之操作型定義 28
第五節 前測分析結果 30
第六節 資料分析 33
第四章 資料分析與結果 34
第一節 正式問卷結果與分析 34
第二節 CFA多元常態、違犯估計檢定與信效度分析 36
第三節 結構模型分析（整體結構模型配適性、路徑分析） 40
第五章 結論與建議 44
第一節 研究結論與討論 44
第二節 理論意涵 46
第三節 實務意涵 48
第四節 研究限制與未來建議 50
參考文獻 52
附錄：正式問卷 57

中文文獻
【網購調查系列一】 網購消費占比達16.5% 愛用電商平台大排名。（2019年 6 月）資策會。取自https://mic.iii.org.tw/news.aspx?id=516。
Top 10台灣十大網路購物電商平台排名。（2020年 5 月）。Similarweb。取自https://www.top10.com.tw/life/938/top-10-online-shopping-website/。
後新冠肺炎時代 跨境電商發展日趨白熱化。（2020年 5 月）。Accenture。https://udn.com/news/story/7238/4555613。

英文文獻
Ahn, S. J., & Bailenson, J. N. (2011). Self-endorsing versus other-endorsing in virtual environments. Journal of Advertising, 40(2), 93-106.
Aguirre, E., Mahr, D., Grewal, D., De Ruyter, K., & Wetzels, M. (2015). Unraveling the personalization paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness. Journal of retailing, 91(1), 34-49.
Baek, T. H., & Morimoto, M. (2012). Stay away from me. Journal of advertising, 41(1), 59-76.
Bleier, A., & Eisenbeiss, M. (2015). The importance of trust for personalized online advertising. Journal of Retailing, 91(3), 390-409.
Boerman, S. C., Kruikemeier, S., & Zuiderveen Borgesius, F. J. (2017). Online behavioral advertising: A literature review and research agenda. Journal of advertising, 46(3), 363-376.
Borgesius, F. Z. (2015). Improving Privacy Protection in the area of Behavioural Targeting Short summary PhD thesis, 1–9.
Celsi, R. L., & Olson, J. C. (1988). The role of involvement in attention and comprehension processes. Journal of Consumer Research, 15(2), 210e224.
Chellappa, R. K., & Sin, R. G. (2005). Personalization versus privacy: An empirical examination of the online consumers' dilemma. Information Technology and Management, 6, 181-202.
Culnan, M. J., & Armstrong, P. K. (1999). Information privacy concerns, procedural fairness, and impersonal trust: An empirical investigation. Organization science, 10(1), 104-115.
Dahlén, M. (2001). Banner advertisements through a new lens. Journal of advertising Research, 41(4), 23-30.
Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information systems research, 17(1), 61-80.
Drèze, X., & Hussherr, F. X. (2003). Internet advertising: Is anybody watching?. Journal of interactive marketing, 17(4), 8-23.
Edwards, S. M., Li, H., & Lee, J. H. (2002). Forced exposure and psychological reactance: Antecedents and consequences of the perceived intrusiveness of pop-up ads. Journal of advertising, 31(3), 83-95.
Escalas, J. E. (2007). Self-referencing and persuasion: Narrative transportation versus analytical elaboration. Journal of Consumer Research, 33(4), 421-429.
Friestad, M., & Wright, P. (1994). The persuasion knowledge model: How people cope with persuasion attempts. Journal of consumer research, 21(1), 1-31.
Gironda, J. T., & Korgaonkar, P. K. (2018). iSpy? Tailored versus invasive ads and consumers’ perceptions of personalized advertising. Electronic Commerce Research and Applications, 29, 64-77.
Goldfarb, A. (2014). What is different about online advertising?. Review of Industrial Organization, 44(2), 115-129.
Ham, C. D. (2017). Exploring how consumers cope with online behavioral advertising. International Journal of Advertising, 36(4), 632-658.
Ham, C. D., & Nelson, M. R. (2016). The role of persuasion knowledge, assessment of benefit and harm, and third-person perception in coping with online behavioral advertising. Computers in Human Behavior, 62, 689-702.
Hoffman, D. L., & Novak, T. P. (2000). Advertising pricing models for the world wide web. Internet publishing and beyond: The economics of digital information and intellectual property, 5, 2-16.
Ibrahim Altaweel, Nathaniel Good, and C. J. H. (2015). Web Privacy Census. Retrieved from https://techscience.org/a/2015121502/
Jai, T. M. C., Burns, L. D., & King, N. J. (2013). The effect of behavioral tracking practices on consumers’ shopping evaluations and repurchase intention toward trusted online retailers. Computers in Human Behavior, 29(3), 901-909.
Jung, A. R. (2017). The influence of perceived ad relevance on social media advertising: An empirical examination of a mediating role of privacy concern. Computers in Human Behavior, 70, 303-309.
Jung, J., Shim, S. W., Jin, H. S., & Khang, H. (2016). Factors affecting attitudes and behavioural intention towards social networking advertising: a case of Facebook users in South Korea. International journal of Advertising, 35(2), 248-265.
Knowles, E. S., & Linn, J. A. (2004). Resistance and Persuasion. Mahwah, NJ: Erlbaum.
Komar, H., & Tunjungsari, H. K. (2019). Pengaruh online behavioural advertising dan consumer trust pada sikap dan niat konsumen merespon online advertising. Jurnal Muara Ilmu Ekonomi dan Bisnis, 3(1), 71-81.
Kim, H., Huh, J., 2015. Perceived relevance and privacy concern regarding online be- havioral advertising and their role in consumer responses. J. Curr. Issues Res. Advert. 38, 92–105.
Lambrecht, A., & Tucker, C. (2013). When Does Retargeting Work? Information Specificity in Online Advertising. Journal of Marketing Research, 50(5), 561–576.
Li, H., Edwards, S. M., & Lee, J. H. (2002). Measuring the intrusiveness of advertisements: Scale development and validation. Journal of advertising, 31(2), 37-47.
Li, H., Sarathy, R., & Xu, H. (2011). The role of affect and cognition on online consumers' decision to disclose personal information to unfamiliar online vendors. Decision Support Systems, 51(3), 434-445.
Li, W., & Huang, Z. (2016). The research of influence factors of online behavioral advertising avoidance. American Journal of Industrial and Business Management, 6(09), 947.
Liang, Y. (2018). Predictable or Serendipitous? The Effect of Retargeted Advertising on Consumer Decision. Proceedings 2018 Pacific Asia Conference on Information Systems, pp150.
Kim, H., & Huh, J. (2017). Perceived relevance and privacy concern regarding online behavioral advertising (OBA) and their role in consumer responses. Journal of Current Issues & Research in Advertising, 38(1), 92-105.
Mangleburg, T. F., & Bristol, T. (1998). Socialization and adolescents' skepticism toward advertising. Journal of advertising, 27(3), 11-21.
Obermiller, C., & Spangenberg, E. R. (1998). Development of a scale to measure consumer skepticism toward advertising. Journal of consumer psychology, 7(2), 159-186.
Obermiller, C., Spangenberg, E., & MacLachlan, D. L. (2005). Ad skepticism: The consequences of disbelief. Journal of advertising, 34(3), 7-17.
Ozcelik, A. B., & Varnali, K. (2019). Effectiveness of online behavioral targeting: A psychological perspective. Electronic Commerce Research and Applications, 33, 100819.
Pavlou, P., & Stewart, D. W. (2000). Measuring the effects and effectiveness of interactive advertising: A research agenda. Journal of Interactive Advertising, 1(1), 61-77.
Pechmann, C., & Stewart, D. W. (1990). The effects of comparative advertising on attention, memory, and purchase intentions. Journal of Consumer Research, 17(2), 180-191.
Pfeiffer, M., & Zinnbauer, M. (2010). Can old media enhance new media?: How traditional advertising pays off for an online social network. Journal of Advertising Research, 50(1), 42-49.
Phelps, J., D'Souza, G., & Nowak, G. (2001). Antecedents and consequences of con- sumer privacy concerns: An empirical investigation. Journal of Interactive Marketing, 15(4), 2-17.
Ricci, F., Rokach, L., & Shapira, B. (2011). Introduction to recommender systems handbook. In Recommender systems handbook (pp. 1-35). Springer, Boston, MA.
Rogers, T. B., Kuiper, N. A., & Kirker, W. S. (1977). Self-reference and the encoding of personal information. Journal of Personality and Social Psychology, 35(9), 677-688.
Ryu, G., Lim, E. A. C., Tan, L. T. L., & Han, Y. J. (2007). Preattentive processing of banner advertisements: The role of modality, location, and interference. Electronic Commerce Research and Applications, 6(1), 6-18.
Smit, E. G., Van Noort, G., & Voorveld, H. A. (2014). Understanding online behavioural advertising: User knowledge, privacy concerns and online coping behaviour in Europe. Computers in Human Behavior, 32, 15-22.
Smith, H. J., Dinev, T., & Xu, H. (2011). Information privacy research: an interdisciplinary review. MIS quarterly, 989-1015.
Trampe, D., Stapel, D. A., Siero, F. W., & Mulder, H. (2010). Beauty as a tool: The effect of model attractiveness, product relevance, and elaboration likelihood on advertising effectiveness. Psychology & Marketing, 27(12), 1101-1121.
Tran, T. P. (2017). Personalized ads on Facebook: An effective marketing tool for online marketers. Journal of Retailing and Consumer Services, 39, 230-242.
Ur, B., Leon, P. G., Cranor, L. F., Shay, R., & Wang, Y. (2012). Smart,Useful,Scary,Creepy: Perceptions of Online Behavioral Advertising. Symposium On Usable Privacy and Security.
Van Doorn, J., & Hoekstra, J. C. (2013). Customization of online advertising: The role of intrusiveness. Marketing Letters, 24(4), 339–351.
Varnali, K. (2021). Online behavioral advertising: An integrative review. Journal of Marketing Communications, 27(1), 93-114.
Varnali, K. (2019). Online behavioral advertising: An integrative review. Journal of Marketing Communications, 1-22.
Walrave, M., Poels, K., Antheunis, M. L., Van den Broeck, E., & van Noort, G. (2018). Like or dislike? Adolescents’ responses to personalized social network site advertising. Journal of Marketing Communications, 24(6), 599-616.
Xu, H., Dinev, T., Smith, J., & Hart, P. (2011). Information privacy concerns: Linking individual perceptions with institutional privacy assurances. Journal of the Association for Information Systems, 12(12), 1-10.
Yaveroglu, I., & Donthu, N. (2008). Advertising repetition and placement issues in on-line environments. Journal of Advertising, 37(2), 31-44.
Yu, C., Zhang, Z., Lin, C., & Wu, Y. J. (2020). Can data-driven precision marketing promote user AD clicks? Evidence from advertising in WeChat moments. Industrial Marketing Management, 90, 481-492.
Zhou, L. (2020). Product advertising recommendation in e-commerce based on deep learning and distributed expression. Electronic Commerce Research, 20(2), 321-342.
Zhu, Y. Q., & Chang, J. H. (2016). The key role of relevance in personalized advertisement: Examining its impact on perceptions of privacy invasion, self-awareness, and continuous use intentions. Computers in Human Behavior, 65, 442-447.
Zhu, Y. Q., & Kanjanamekanant, K. (2020). No trespassing: Exploring privacy boundaries in personalized advertisement and its effects on ad attitude and purchase intentions on social media. Information & Management, 58, 1-11.