自智慧型行動裝置的出現，應用程式的使用如今充斥於許多人的日常生活。然而部分不肖應用程式於未經使用者同意之下，私自收集、濫用以及傳送用戶個人資料之情形，使得針對行動裝置平台使用者隱私顧慮的相關議題開始受到了重視與討論。
本研究旨在效仿神經資訊系統之精神，探討應用程式權限要求隱私敏感度的提升，以及過去研究當中所提出能夠緩解使用者隱私顧慮相關措施，對於學生族群之情緒以及下載意圖的影響。透過募集資訊管理學系三、四年級學生作為受測對象，以實驗室實驗法收集腦波資料與受測者回覆資料兩者，並基於資料分析結果針對行動裝置使用者、應用程式開發者以及應用程式商店管理者三方提出相關建議。
研究結果顯示，應用程式權限要求的差異對於受測者評估下載與否之決策上，無法誘發出其情緒變化上的顯著不同並從腦波資料當中反映出來，並且相關隱私緩解措施的施予與否亦然；然而由受測者所自行回覆的下載意願資料當中發現，倘若單就隱私顧慮作為應用程式下載與否之唯一考量時，則應用程式權限要求隱私敏感度的提升確實會影響使用者的下載意願，而過去研究所提出之應用程式權限要求說明資訊、熱門程度資訊，以及本研究額外探討之品牌知名度資訊三者確實能夠提高其下載意願。

Since the advent of smart devices, nowadays app usage has been filled in daily lives. However, because some unscrupulous apps collect, misuse and transmit user's personal data without the user's consent, the privacy issues have begun to receive attention.
In this study, we explore the impact on students’ sentiment and download intentions when they encounter privacy issues from the perspective of NeuroIS. Specifically, we consider the effect of permission request with respect to privacy and some measures to mitigate user’s concern proposed in previous studies. By analyzing the EEG and self-reported data collected from junior and senior MIS students, useful recommendations could be made to mobile device users, app developers and app store manager, respectively.
Resulting from the EEG data, there is no significant emotional change when permission requirements differ or other privacy mitigation measures impose. However, the self-reported data shows that application permission requests decrease the download intentions when the privacy is the only concern. Furthermore, the application permission justification and popularity information, as well as the brand reputation, increase users’ download intentions.

目錄
 第一章　緒論	1
1.1	研究背景與動機	1
1.2	研究目的	2
1.3	研究對象與範圍	3
 第二章　文獻探討	4
2.1	應用程式商店內容的隱私顧慮問題	4
2.1.1	應用程式作業系統市場現況與隱私問題	4
2.1.2	使用者應用程式下載之評估	5
2.2	隱私計算理論	5
2.3	推敲可能性模式	7
2.3.1	概述	7
2.3.2	於隱私研究之相關應用	8
2.4	品牌知名度	9
2.4.1	品牌、品牌名稱與品牌知名度	9
2.4.2	對消費者決策影響之相關研究	9
2.5	神經資訊系統	10
2.5.1	概述	10
2.5.2	神經資訊系統之研究應用與優勢	10
 第三章　研究方法	12
3.1	研究假說之推導	13
3.2	構念操作化方式	16
3.3	實驗設計	17
3.3.1	實驗流程設計	17
3.3.2	腦波分析設計	21
3.3.3	實驗對象	24
3.3.4	實驗情境設計	25
 第四章　資料分析與結果	31
4.1	資料分析方法	31
4.2	樣本結構描述	31
4.3	假說驗證	32
 第五章　結論與建議	38
5.1	研究結果與討論	38
5.2	實務意涵	39
5.3	研究限制與建議	40
參考文獻	42
 附錄	51
附錄 A	各情境應用程式介紹與刺激呈現畫面	51
附錄 B	個人基本資料問卷	57
圖目錄
圖 3 1：實驗流程設計圖	19
圖 3 2：情境刺激施予流程設計圖	19
圖 3 3：腦波儀配戴無接觸不良範例	21
圖 3 4：腦波儀配戴接觸不良範例	21
圖 3 5：Emotiv EPOC	22
圖 3 6：腦波量測頻道位置參照圖	23
圖 3 7：單一受測者特定情境平均震幅強度數據產生流程圖	24
圖 3 8：Snapchat於Google Play的下載頁面資訊與權限要求畫面	26
圖 3 9：應用程式介紹	27
圖 3 10：情境刺激施予流程圖	28
圖 3 11：範例實驗情境	29
圖 3 12：下載意願回覆提示畫面	30
圖 4 1：各情境具下載意願之比率	35
圖A 1：練習情境應用程式介紹	51
圖A 2：練習情境（一）	51
圖A 3：練習情境（二）	52
圖A 4：練習情境（三）	52
圖A 5：練習情境（四）	53
圖A 6：正式情境應用程式介紹	53
圖A 7：低隱私敏感度情境	54
圖A 8：高隱私敏感度情境	54
圖A 9：高應用程式熱門程度情境	55
圖A 10：應用程式權限要求說明情境	55
圖A 11：高品牌知名度情境	56

表目錄
表 3 1：研究構念之操作化定義	17
表 4 1：樣本結構表	31
表 4 2：假說一ANOVA檢定結果表	33
表 4 3：假說二ANOVA檢定結果表	34
表 4 4：假說三ANOVA檢定結果表	34
表 4 5：假說四ANOVA檢定結果表	35

一、英文部分
[1]	Aaker, D. A. (1996). Measuring brand equity across products and markets. California Management Review, 38(3), 102–120.
[2]	Acquisti, A., John, L. K., &Loewenstein, G. (2013). What is privacy worth? The Journal of Legal Studies, 42(2), 249–274.
[3]	Al-Hudhud, G., Alzamel, M. A., Alattas, E., &Alwabil, A. (2014). Using brain signals patterns for biometric identity verification systems. Computers in Human Behavior, 31, 224–229.
[4]	Alexander, R. S. (1960). Marketing definitions: A glossary of marketing terms. American Marketing Association.
[5]	App Annie. (2017). App Economy Forecast: Mobile App Store Revenue to Exceed $139B in 2021. Retrieved March10, 2018, from https://www.appannie.com/en/insights/market-data/app-annie-forecast-2017-mobile-app-store-revenue-exceed-139-billion-2021/
[6]	Balebako, R., Marsh, A., Lin, J., Hong, J. I., &Cranor, L. F. (2014). The privacy and security behaviors of smartphone app developers.
[7]	Bansal, G., &Zahedi, F. (2008). The moderating influence of privacy concern on the efficacy of privacy assurance mechanisms for building trust: A multiple-context investigation. ICIS 2008 Proceedings, 7.
[8]	Bansal, G., Zahedi, F. “Mariam,” &Gefen, D. (2010). The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online. Decision Support Systems. 
[9]	Barnes, S. B. (2006). A privacy paradox: Social networking in the United States. First Monday, 11(9).
[10]	Barrera, D., Kayacik, H. G., vanOorschot, P. C., &Somayaji, A. (2010). A methodology for empirical analysis of permission-based security models and its application to android. In Proceedings of the 17th ACM conference on Computer and communications security (pp. 73–84). ACM.
[11]	Bartholow, B. D., &Amodio, D. M. (2009). Brain Potentials in Social Psychological research. Methods in Social Neuroscience, 198.
[12]	Bhattacherjee, A., &Sanford, C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. MIS Quarterly, 805–825.
[13]	Bouwman, H., &Van DeWijngaert, L. (2009). Coppers context, and conjoints: a reassessment of TAM. Journal of Information Technology, 24(2), 186–201.
[14]	Broniarczyk, S. M., &Alba, J. W. (1994). The importance of the brand in brand extension. Journal of Marketing Research, 214–228.
[15]	Budnitz, M. E. (1997). Privacy protection for consumer transactions in electronic commerce: why self-regulation is inadequate. SCL Rev., 49, 847.
[16]	Calhoun, V. D., Adali, T., Pearlson, G. D., &Kiehl, K. A. (2006). Neuronal chronometry of target detection: fusion of hemodynamic and event-related potential data. NeuroImage, 30(2), 544–553.
[17]	Charlton, S. G. (2002). Measurement of cognitive states in test and evaluation. Handbook of Human Factors Testing and Evaluation, 2, 97–126.
[18]	Chin, A. G., Harris, M. A., &Brookshire, R. (2018). A bidirectional perspective of trust and risk in determining factors that influence mobile app installation. International Journal of Information Management, 39, 49–59.
[19]	Christofides, E., Muise, A., &Desmarais, S. (2009). Information disclosure and control on Facebook: Are they two sides of the same coin or two different processes? Cyberpsychology & Behavior, 12(3), 341–345.
[20]	Crawford, H. J., Clarke, S. W., &Kitner-Triolo, M. (1996). Self-generated happy and sad emotions in low and highly hypnotizable persons during waking and hypnosis: laterality and regional EEG activity differences. International Journal of Psychophysiology, 24(3), 239–266.
[21]	Culnan, M. J., &Armstrong, P. K. (1999). Information privacy concerns, procedural fairness, and impersonal trust: An empirical investigation. Organization Science, 10(1), 104–115.
[22]	Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319–340.
[23]	Delorme, A., &Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9–21.
[24]	Derlega, V. J., Metts, S., Petronio, S., &Margulis, S. T. (1993). Sage series on close relationships. Self-disclosure.
[25]	Dimoka, A., &Davis, F. D. (2008). Where does TAM reside in the brain? The neural mechanisms underlying technology adoption. ICIS 2008 Proceedings, 169.
[26]	Dimoka, A., Davis, F. D., Gupta, A., Pavlou, P. A., Banker, R. D., Dennis, A. R., …Gefen, D. (2012). On the use of neurophysiological tools in IS research: Developing a research agenda for NeuroIS. MIS Quarterly, 679–702.
[27]	Dimoka, A., Pavlou, P. A., &Davis, F. D. (2011). Research commentary—NeuroIS: The potential of cognitive neuroscience for information systems research. Information Systems Research, 22(4), 687–702.
[28]	Dinev, T., Bellotto, M., Hart, P., Russo, V., Serra, I., &Colautti, C. (2006). Privacy calculus model in e-commerce–a study of Italy and the United States. European Journal of Information Systems, 15(4), 389–402.
[29]	Dinev, T., &Hart, P. (2004). Internet privacy concerns and their antecedents-measurement validity and a regression model. Behaviour & Information Technology, 23(6), 413–422.
[30]	Dinev, T., &Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80.
[31]	Dinev, T., Xu, H., Smith, J. H., &Hart, P. (2013). Information privacy and correlates: an empirical attempt to bridge and distinguish privacy-related concepts. European Journal of Information Systems, 22(3), 295–316. 
[32]	Dove, A., Manly, T., Epstein, R., &Owen, A. M. (2008). The engagement of mid‐ventrolateral prefrontal cortex and posterior brain regions in intentional cognitive activity. Human Brain Mapping, 29(1), 107–119.
[33]	Duan, W., Gu, B., &Whinston, A. B. (2009). Informational cascades and software adoption on the internet: an empirical investigation. MIS Quarterly, 23–48.
[34]	Enck, W., Gilbert, P., Han, S., Tendulkar, V., Chun, B.-G., Cox, L. P., …Sheth, A. N. (2014). TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones. ACM Transactions on Computer Systems (TOCS), 32(2), 5.
[35]	Fatourechi, M., Bashashati, A., Ward, R. K., &Birch, G. E. (2007). EMG and EOG artifacts in brain computer interface systems: A survey. Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology, 118(3), 480–494. 
[36]	Featherman, M. S., &Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474.
[37]	Felt, A. P., Chin, E., Hanna, S., Song, D., &Wagner, D. (2011). Android permissions demystified. In Proceedings of the 18th ACM conference on Computer and communications security (pp. 627–638). ACM.
[38]	Felt, A. P., Egelman, S., &Wagner, D. (2012). I’ve got 99 problems, but vibration ain’t one: a survey of smartphone users’ concerns. In Proceedings of the second ACM workshop on Security and privacy in smartphones and mobile devices (pp. 33–44). ACM.
[39]	Felt, A. P., Ha, E., Egelman, S., Haney, A., Chin, E., &Wagner, D. (2012). Android permissions: User attention, comprehension, and behavior. In Proceedings of the eighth symposium on usable privacy and security (p. 3). ACM.
[40]	Ferstl, E. C., Rinck, M., &VonCramon, D. Y. (2005). Emotional and temporal aspects of situation model processing during text comprehension: An event-related fMRI study. Journal of Cognitive Neuroscience, 17(5), 724–739.
[41]	Gartner. (2017). Gartner Says Worldwide Sales of Smartphones Grew 7 Percent in the Fourth Quarter of 2016. Retrieved March10, 2018, from https://www.gartner.com/newsroom/id/3609817
[42]	Govani, T., &Pashley, H. (2005). Student awareness of the privacy implications when using Facebook. Unpublished Paper Presented at the “Privacy Poster Fair” at the Carnegie Mellon University School of Library and Information Science, 9, 1–17.
[43]	Gu, J., Xu, Y. C., Xu, H., Zhang, C., &Ling, H. (2017). Privacy concerns for mobile app download: An elaboration likelihood model perspective. Decision Support Systems, 94, 19–28.
[44]	Ha, H.-Y. (2004). Factors influencing consumer perceptions of brand trust online. Journal of Product & Brand Management, 13(5), 329–342. Harmon-Jones, E., &Allen, J. J. B. (1998). Anger and frontal brain activity: EEG asymmetry consistent with approach motivation despite negative affective valence. Journal of Personality and Social Psychology, 74(5), 1310.
[45]	Hoyer, W. D., &Brown, S. P. (1990). Effects of brand awareness on choice for a common, repeat-purchase product. Journal of Consumer Research, 17(2), 141–148.
[46]	Hui, W. (2010). Brand, knowledge, and false sense of security. Information Management & Computer Security, 18(3), 162–172. Jordan Robertson. (2012). Android apps collect too much user data, researcher says. Retrieved March6, 2018, from https://www.smh.com.au/technology/android-apps-collect-too-much-user-data-researcher-says-20121102-28oie.html
[47]	Keith, M. J., Babb, J., Furner, C., Abdullat, A., &Lowry, P. B. (2016). Limited Information and Quick Decisions: Consumer Privacy Calculus for Mobile Applications.
[48]	Keller, K. L. (2003). Strategic brand management: Building, measuring, and managing brand equity. Aufl., Upper Saddle River.
[49]	Kelly, A. E., &McKillop, K. J. (1996). Consequences of revealing personal secrets. Psychological Bulletin, 120(3), 450.
[50]	Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Research Reviews, 29(2–3), 169–195.
[51]	Klopfer, P. H., &Rubenstein, D. I. (1977). The concept privacy and its biological basis. Journal of Social Issues, 33(3), 52–65.
[52]	Knutson, B., Adams, C. M., Fong, G. W., &Hommer, D. (2001). Anticipation of increasing monetary reward selectively recruits nucleus accumbens. Journal of Neuroscience, 21(16), RC159-RC159.
[53]	Kuan, K. K. Y., Zhong, Y., &Chau, P. Y. K. (2014). Informational and normative social influence in group-buying: Evidence from self-reported and EEG data. Journal of Management Information Systems, 30(4), 151–178.
[54]	Laurenceau, J.-P., Barrett, L. F., &Pietromonaco, P. R. (1998). Intimacy as an interpersonal process: The importance of self-disclosure, partner disclosure, and perceived partner responsiveness in interpersonal exchanges. Journal of Personality and Social Psychology, 74(5), 1238.
[55]	Lawler, J. P., &Molluzzo, J. C. (2010). A study of the perceptions of students on privacy and security on social networking sites (SNS) on the internet. Journal of Information Systems Applied Research, 3(12), 3–18.
[56]	Lee, N., Broderick, A. J., &Chamberlain, L. (2007). What is ‘neuromarketing’? A discussion and agenda for future research. International Journal of Psychophysiology, 63(2), 199–204.
[57]	Lewis, K., Kaufman, J., &Christakis, N. (2008). The taste for privacy: An analysis of college student privacy settings in an online social network. Journal of Computer‐Mediated Communication, 14(1), 79–100.
[58]	Luck, S. J. (2014). An Introduction to the Event-Related Potential Technique (Second Edi). Bradford Books. 
[59]	Macdonald, E. K., &Sharp, B. M. (2000). Brand awareness effects on consumer decision making for a common, repeat purchase product:: A replication. Journal of Business Research, 48(1), 5–15.
[60]	Malhotra, N. K., Kim, S. S., &Agarwal, J. (2004). Internet Users’ Information Privacy Concerns (IUIPC): The Construct, the Scale, and a Causal Model. Information Systems Research, 15(4), 336–355. Retrieved from http://pqdd.sinica.edu.tw.ezproxy.lib.tku.edu.tw/twdaoapp/servlet/advanced?query=
[61]	McGann, R. (2005). Most active Web users are young, affluent. ClickZ Network, http://Www.Clickz.Com/3455741.
[62]	Mizoguchi, C., Kobayakawa, T., Saito, S., &Ogawa, H. (2002). Gustatory evoked cortical activity in humans studied by simultaneous EEG and MEG recording. Chemical Senses, 27(7), 629–634.
[63]	Mognon, A., Jovicich, J., Bruzzone, L., &Buiatti, M. (2011). ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features. Psychophysiology, 48(2), 229–240.
[64]	Moon, Y. (2000). Intimate Exchanges: Using Computers to Elicit Self‐Disclosure From Consumers. Journal of Consumer Research, 26(4), 323–339. 
[65]	Müller-Putz, G. R., Riedl, R., &Wriessnegger, S. C. (2015). Electroencephalography (EEG) as a Research Tool in the Information Systems Discipline: Foundations, Measurement, and Applications. CAIS, 37, 46.
[66]	Petty, R. E., &Cacioppo, J. T. (1979). Issue involvement can increase or decrease persuasion by enhancing message-relevant cognitive responses. Journal of Personality and Social Psychology, 37(10), 1915–1926. 
[67]	Petty, R. E., Cacioppo, J. T., &Goldman, R. (1981). Personal involvement as a determinant of argument-based persuasion. Journal of Personality and Social Psychology, 41(5), 847–855. 
[68]	Petty, R. E., Cacioppo, J. T., &Schumann, D. (1983). Central and peripheral routes to advertising effectiveness: The moderating role of involvement. Journal of Consumer Research, 10(2), 135–146.
[69]	Petty, R. E., &Wegener, D. T. (1998). Attitude change: Multiple roles for persuasion variables. In The handbook of social psychology, Vols. 1-2, 4th ed. (pp. 323–390). New York, NY, US: McGraw-Hill.
[70]	Riedl, R., Banker, R. D., Benbasat, I., Davis, F. D., Dennis, A. R., Dimoka, A., …Kenning, P. (2010). On the Foundations of NeuroIS: Reflections on the Gmunden Retreat 2009. CAIS, 27, 15.
[71]	Riedl, R., &Léger, P.-M. (2015). Neuro-Information-Systems (NeuroIS), 14.10.2015.
[72]	Rindfleisch, T. C. (1997). Privacy, information technology, and health care. Communications of the ACM, 40(8), 92–100.
[73]	S. Pichai. (2015). Billions of Android apps vulnerable to hackers - MarketWatch. Retrieved March6, 2018, from https://www.marketwatch.com/story/billions-of-android-apps-vulnerable-to-hackers-2015-02-27/
[74]	Shklovski, I., Mainwaring, S. D., Skúladóttir, H. H., &Borgthorsson, H. (2014). Leakiness and creepiness in app space: Perceptions of privacy and mobile app use. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 2347–2356). ACM.
[75]	Smith, H. J., Dinev, T., &Xu, H. (2011). Information privacy research: an interdisciplinary review. MIS Quarterly, 35(4), 989–1016.
[76]	Stone, E. F., &Stone, D. L. (1990). Privacy in organizations: Theoretical issues, research findings, and protection mechanisms. Research in Personnel and Human Resources Management, 8(3), 349–411.
[77]	Tan, X., Qin, L., Kim, Y., &Hsu, J. (2012). Impact of privacy concern in social networking web sites. Internet Research, 22(2), 211–233.
[78]	Thakur, R., &Summey, J. H. (2007). e-Trust: Empirical insights into influential antecedents. Marketing Management Journal, 17(2), 67–80.
[79]	Tufekci, Z. (2008). Can you see me now? Audience and disclosure regulation in online social network sites. Bulletin of Science, Technology & Society, 28(1), 20–36.
[80]	Venkatraman, V., Dimoka, A., Pavlou, P. A., Vo, K., Hampton, W., Bollinger, B., …Winer, R. S. (2015). Predicting advertising success beyond traditional measures: New insights from neurophysiological methods and market response modeling. Journal of Marketing Research, 52(4), 436–452.
[81]	vomBrocke, J., &Liang, T.-P. (2014). Guidelines for neuroscience studies in information systems research. Journal of Management Information Systems, 30(4), 211–234.
[82]	Wheeler, R. E., Davidson, R. J., &Tomarken, A. J. (1993). Frontal brain asymmetry and emotional reactivity: A biological substrate of affective style. Psychophysiology, 30(1), 82–89.
[83]	White, T. B. (2004). Consumer disclosure and disclosure avoidance: A motivational framework. Journal of Consumer Psychology, 14(1–2), 41–51.
[84]	Wolpaw, J., &Wolpaw, E. W. (2012). Brain-computer interfaces: principles and practice. OUP USA.
[85]	Wottrich, V. M., vanReijmersdal, E. A., &Smit, E. G. (2017). The privacy trade-off for mobile app downloads: The roles of app value, intrusiveness, and privacy concerns. Decision Support Systems.
[86]	Xu, H. (2010). Locus of control and location privacy: An empirical study in Singapore. Journal of Global Information Technology Management, 13(3), 63–87.
[87]	Xu, H., Teo, H.-H., &Tan, B. (2005). Predicting the adoption of location-based services: the role of trust and perceived privacy risk. ICIS 2005 Proceedings, 71.
[88]	Yang, L., Ma, R., Zhang, H. M., Guan, W., &Jiang, S. (2017). Driving behavior recognition using EEG data from a simulated car-following experiment. Accident Analysis & Prevention.
[89]	Yang, S.-C., Hung, W.-C., Sung, K., &Farn, C.-K. (2006). Investigating initial trust toward e-tailers from the elaboration likelihood model perspective. Psychology and Marketing, 23(5), 429–445. 
[90]	Zaltman, G., Dotlich, D. L., &Cairo, P. C. (2003). How customers think. Audio-Tech Business Book Summaries.

二、中文部分
[1]	曾祥炎, &陳軍. (2009). E-Prime 實驗設計技術.
[2]	林錦郎, 卓麗香, &張松山. (2017). 資訊隱私機制與信任對 Facebook 社群網站使用者行為意圖影響之研究. 全球商業經營管理學報, (9), 13–25.
[3]	蕭文龍, 黃莉君, &楊雅雯. (2016). 神經資訊系統文獻彙整分析. 東吳經濟商學學報, (92), 37–56.
[4]	蕭至惠, 洪筱婷, &蔡進發. (2008). 旅遊網站品牌知名度與價格標示對線上套裝旅遊購買意願之影響. 觀光休閒學報, 14(1), 83–107.