近年來由於無線通訊科技的快速成長，市面上衍生發展出許多行動應用服務，行動監控服務即為其中一項應用服務。行動監控服務是在無線網路環境下，藉由行動通訊設備來操作監控設備。
然而針對這項新興的應用服務，過去尚未有任何文獻去探討其影響使用者的主要採用因素，為了來研究影響使用者對行動監控之認知與使用的關鍵因素，並驗證使用者認知與行為意願間的關係，本研究以科技接受模式為研究架構之基礎進行研究，並考慮其他可能影響使用者行為模式之變項，加入創新擴散理論和計劃行為理論等相關理論發展出本研究架構，探討認知娛樂性、認知易用性、認知有用性、自我效能、相容性、成本、認知網路安全和隱私侵犯對消費者的行動監控服務採用意願之影響分析。
本研究以行動裝置使用者為研究對象，透過傳統問卷和網路問卷方式進行樣本資料蒐集，資料經由分析後顯示，認知娛樂性、認知有用性、相容性、成本、認知網路安全性和隱私侵犯對使用行動監控的行為意願有顯著的影響，其中以認知娛樂性影響程度最高。此外認知易用性的影響則較不顯著，然而其對有用性和娛樂性的影響仍相當顯著。

With the rapid development of wireless communication technology, there are a variety of mobile application services nowadays, and mobile surveillance is one of that. Mobile surveillance is that using mobile communication equipment to operate surveillance equipments via wireless network.
In connection with this developing application service, there is no previous study analyzes the factors that influence users’ adoption of mobile surveillance. In order to investigate what determines mobile surveillance adoption, and test the relationship between users’ perception and behavior intent, this study takes Technology Acceptance Model (TAM) as the main theory structure, and considers other factors that may influence user behavior. Innovation Diffusion Theory (IDT) and Theory of Planned Behavior (TPB) will be referred to develop this research structure. Inquire how the perceived enjoyment, perceived ease of use, perceived usefulness, self-efficacy, compatibility, cost, perceived web security and privacy invasion influence the intention of adopting mobile surveillance.
This study took people using mobile equipment as the sampling object, and developed traditional and on-line questionnaires to gather sample data. Our findings indicated that all variables except perceived ease of use and self-efficacy significantly affected users’ behavioral intent. Among them, the perceived enjoyment had the most significant influence. Furthermore, a somewhat puzzling finding was the negative influence of perceived ease of use on behavioral intention to use, but perceived ease of use still significantly affected perceived usefulness and perceived enjoyment.

一、英文文獻
1.Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: A replication. MIS Quarterly, 16(2), 227-247.
2.Agarwal, R. and Prasad, J., "The antecedents and consequents of user perceptions in information technology adoption." Decision Support System, 22,15-29, 1998.
3.Agarwal, R. and Prasad, J., "The Role of Innovation Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies." Decision Sciences, 28(3), 557-582, 1997.
4.Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694.
5.Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361-391.
6.Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
7.Atkinson, M., and Kydd, C. (1997). Individual characteristics associated with World Wide Web use: an empirical study of playfulness and motivation. The DATA BASE for Advances in Information Systems, 28(2), 53-62.
8.Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191-215.
9.Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37, 122-147.
10.Bellman, Steven., Lohse, Gerald L ＆ Johnson,Eric J., (1999), Predictors of online buying behavior, Association for Computing Machinery, Communication of the ACM,New York,42(12),Dec, 32-38.
11.Busselle, R., Reagan, J., Pinkleton, B., and Jackson, K., "Factors Affecting Internet Use in a Saturated-Access Population." Telematics and Informatics, 16, 45-58, 1999.
12.Bylinski, G. (1991). How companies spy on employees. Fortune, November 4, 131–140.
13.Chau, P. Y. K. (1996). An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems, 13(2), 185-204.
14.Chau, P. Y. K. (2001). Influence of computer attitude and self-efficacy on IT usage behavior. Journal of End User Computing, 13(1), 26-33.
15.Chau, P.Y.K. and Hu, P.J-H., "Information Technology Acceptance by Individual Professionals: A Model Comparison Approach." Decision Science, 32(4), 699-719, 2001.
16.Chellappa, R. K. ＆ Pavlou, P., (2002), Perceived Information Security, Financial Liability, and Consumer Trust in Electronic Commerce Transactions, Journal of Logistics Information Management ,15(5/6), 358-368.
17.Chin, W. C., & Todd, P. A. (1995). On the use, usefulness and ease of use of structural equation modeling in MIS research: A note of caution. MIS Quarterly, 19(2), 237-246.
18.Clarke, R. “Information Technology and Dataveillance,” Communications of the ACM (31:5), 1998, pp.498–512.
19.Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
20.Culnan, M. “Consumer Awareness of Name Removal Procedures: Implications for Direct Marketing,” Journal of Direct Marketing (9, 2), 1995, pp. 10–19.
21.Culnan, M. “How Did They My Name? An Exploratory Investigation of Consumer Attitudes toward Secondary Information Use,” MIS Quarterly (17:3), 1993, pp. 341–363.
22.Culnan, M., and Armstrong, P. “Information Privacy Concerns, Procedural Fairness, and Impersonal Trust: An Empirical Investigation,” Organization Science (10:1), 1999, pp. 104–115.
23.D. Young, Handicapping M-commerce, Wireless Review, 1 August 2000, viewed 1 January 2003, http://wirelessreview. com/ar/wireless_handicapping_mcommerce/index.htm.
24.D.H. Sonnenwald, K.L. Maglaughlin, M.C. Whitton, Using innovation diffusion theory to guide collaboration technology evaluation: work in progress, in: Proceedings of the IEEE 10th International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE'01), viewed 1 January 2003, http://www.adm.hb.se/personal/dis/wetice-2001.pdf.
25.Doll, W. J., Hendrickson, A., & Deng, X. (1998). Using Davis's perceived usefulness and ease-of-use instruments for decision making: A confirmatory and multi-group invariance analysis. Decision Science, 29(4), 839-869.
26.E. Constantinides, The 4S Web-marketing mix model, electronic commerce research and applications, Elsevier Science 1(1), 2002, pp. 57-76.
27.E. Karahanna, D.W. Straub, N.L. Chervany, Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs, MIS Quarterly 23(2), 1999, pp. 183-213.
28.F. Fukuyama, Trust Still Counts in a Virtual World, Forbes ASAP Supplement, No. 01337051, 1996, p. 33, 69.
29.F.D. Davis, Perceived usefulness, perceived ease of use, and user acceptance of information technologies, MIS Quarterly 13(3), 1989, pp. 319-340.
30.Fang, X., Chan, S., Brzezinski, J., Xu, S. Moderating effects of task type on wireless technology acceptance (2005) Journal of Management Information Systems, 22 (3), pp. 123-157.
31.Fishbein, M. and Ajzen, I., “Belief, attitude, intention and behavior: An introduction to theory and research.” Reading (MA): Addison-Wesley, 1975.
32.Godwin, JU 2001, ‘Privacy and Security concerns as a major barrier for e-commerce: a survey study’, Information Management & Computer Security, vol. 9, no. 4, pp. 165-174.
33.Green, G. S. (1997). Occupational Crime, 2nd ed. Chicago: Nelson-Hall.
34.Greenberg, S., & Kuzuoka, H. (2000). Using digital but physical surrogates to mediate awareness, communication and privacy in media spaces. Personal Technologies, 4, 182–198.
35.Greenman, C. "On the Net, Curiosity Has A Price: Registration," New York Times, December 23, 1999.
36.H. Heijden, Factors influencing the usage of website: the case of generic portal in the Netherlands, Information & Management 40 (6), 2003, pp. 541-549.
37.Harris, L. and Associates and Westin, A.F. Harris-Equifax User Privacy Surveys, Equifax Inc., Atlanta, Georgia, 1998
38.Hebert, L. C. (2002). Methods and extent of employer use of electronic monitoring and surveillance. Employee Privacy Law, 1: Section 8A:1.
39.Hong, W., Thong, J. Y. L., Wong, W. M., & Tam, K. Y. (2001). Determinants of user acceptance of digital libraries: An empirical examination of individual differences and system characteristics. Journal of Management Information Systems, 18(3), 97-124.
40.Hsu, C. W. (2006). Privacy concerns, privacy practices and web site categories toward a situational paradigm. Online Information Review, 30(5), 569–586.
41.Igbaria, M., & Iivari, J. (1995). The effects of self-efficacy on computer usage. Omega, 23(6), 587-605. Jackson, C. M., Chow, S., & Leitch, R. A. (1997). Toward an understanding of the behavioral intention to use an information system. Decision Sciences, 28(2), 357-389.
42.Imsook Ha, Youngseog Yoon, Munkee Choi, Determinants of adoption of mobile games under mobile broadband wireless access environment, Information & Management 44, 2007, pp. 276-286.
43.J. Rock, Mobile commerce: the next big thing or just plain hype, TheWeekly Corporate Growth Report 1121, 18 December 2000, pp. 11093, 11104.
44.Jen-Her Wu, Shu-Ching Wang, What drives mobile commerce? An empirical evaluation of the revised technology acceptance model, Information & Management 42, 2005, pp. 719-729.
45.Jiunn-Woei Lian, Tzu-Ming Lin, Effects of consumer characteristics on their acceptance of online shopping: Comparisons among different product types. Computers in Human Behavior, 24(1), 48-65.
46.Johnson, R. D., & Marakas, G. M. (2000). Research report: The role of behavior modeling in computer skills acquisition - Toward refinement of the model. Information Systems Research, 11(4), 402-417.
47.Kelley, C., Delhagen, K., and Yuen, E. H. “Online Credit Card Security Confidence Erodes,“ Forrester Research, July 25, 2003, available at http://www.forrester.com/ER/Research/Brief/0,1317,17220,FF.html
48.L.D. Chen, M.L. Gillenson, D.L. Sherrell, Enticing online consumers: an extended technology acceptance perspective, Information & Management 39(8), 2002, pp. 705-719.
49.Laabs, J. J. (1992). Surveillance: Tool or trap? Personnel Journal, June, 96–104.
50.Lee, A., Schlueter, K., & Girgensohn, A. (1997). Sensing activity in video images. CHI’97 extended abstracts (pp. 319–320). ACM Press.
51.Lee, M.K.O., Cheung, C.M.K., Chen, Z. Acceptance of Internet-based learning medium: The role of extrinsic and intrinsic motivation (2005) Information and Management, 42 (8), pp. 1095-1104.
52.Liao, S., Shao, Y.P., Wang, H., and Chen, A., "The Adoption of Virtual Banking: An Empirical Study." International Journal of Information Management, 19, 63-74, 1999.
53.Liao, Z & Cheung, MT 2002, ‘Internet-based e-banking and consumer attitudes: an empirical study’, Information & Management, vol. 39, no. 4, pp. 283-295.
54.Liu, C., Marchewka, J.T., Lu, J., Yu, C.-S. Beyond concern: A privacy-trust-behavioral intention model of electronic (2004) Information and Management, 42 (1), pp. 127-142.commerce
55.M. Koufaris, Applying the technology acceptance model and flow theory to online consumer behavior, Information Systems Research 13(2), 2002, pp. 205-223.
56.Mason, R.O. Four Ethical Issues of the Information Age, MIS Quarterly (10:1), 1986, pp. 4-12.
57.Mathieson, K., Peacock, E., & Chin, W. W. (2001). Extending the technology acceptance model: The influence of perceived user resources. DATA BASE for Advances in Information Systems, 32(3), 86-112.
58.Mirella Kleijnen, Martin Wetzels, Ko de Ruyter, Consumer acceptance of wireless finance, Journal of Financial Services Marketing. London: Mar 2004. Vol. 8, Iss. 3; p. 206 (12 pages)
59.Moon, J. W., and Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information and Management, 38(4), 217-230.
60.Moore, G.C., Benbasat, I., "Development of an Instrument of Measure the Perceptions of Adopting an Information Technology Innovation." Information Systems Research, 2(3), 192-222, 1991.
61.Neter, J., Kutner, H. M., Wasserman, W., & Nachtsheim J. c. (1996), Linear Regression Models, 3rd ed., The McGraw-Hill Companies, Inc.
62.Ngai, E.W.T.,Gunasekaran, A. A review for mobile commerce research and applications (2007)Decision Support Systems,43(1),pp. 3-15.
63.Nunally, J.C. (1978), Psychometric theory (2nd ed.). New York: McGraw-Hill
64.O'Cass, A., & Fenech, T. (2003). Web retailing adoption: Exploring the future of Internet users web retailing behavior. Journal of Retailing and Consumer Services, 10(2), 81-94.
65.P.Y. Chen, L.M. Hitt, Measuring switching costs and the determinants of customer retention in Internet-enabled businesses: a study of the online brokerage industry, Information Systems Research 13(3), 2002, pp. 255-274.
66.Peslak, A. R. (2006). PAPA revisited: A current empirical study of the mason framework. The Journal of Computer Information Systems, 46(3), 117–123.
67.Pin Luarn, Hsin-Hui Lin, Toward an understanding of the behavioral intention to use mobile banking, Computers in Human Behavior 21, 2005, pp. 873-891.
68.R. Agarwal, J. Prasa, Aconceptual and operational definition of personal innovativeness in the domain of information technology, Information Systems Research 9(2), 1998, pp. 204-301.
69.Ranganathan, C., & Ganapathy, S. (2002). Key dimensions of business-to-consumer web sites. Information and Management, 39(6), 457–465.
70.Rogers, E.M., "Diffusion of Innovations." 4th, New York: Free Press, 1995.
71.Rosenberg, R. S. (1999). The workplace on the verge of the 21st century. Journal of Business Ethics, 22, 3–14.
72.S. Taylor, P. Todd, Decomposition and crossover effects in the theory of planned behavior: a study of consumer adoption intentions, International Journal of Research in Marketing 12, 1995, pp. 137-155.
73.Segars, A. H., & Grover, V. (1993). Re-examining perceived ease of use and usefulness: A confirmatory factor analysis. MIS Quarterly, 17(4), 517-525.
74.Stanton, J. M., & Barnes-Farrell, J. L. (1996). Effects of electronic performance monitoring on personal control. Journal of Applied Psychology, 81, 738-745.
75.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, 349–411.
76.Syed Shah Alam, Ali Khatibi, Mohd Ismail Sayyed Ahmad, Hishamuddin Bin Ismail. Factors affecting e-commerce adoption in the electronic manufacturing companies in Malaysia. International Journal of Commerce & Management. Indiana: 2007. 17(1/2); p. 125
77.Tamara Dinev, Paul Hart. Privacay Concerns and Levels of Information Exchange: An Empirical Investigation of Intended e-Services Use. E - Service Journal. Bloomington: 2006. Vol. 4, Iss. 3; p. 25
78.Taylor, S. and Todd, P.A., "Understanding Information Technology Usage: A Test of Competing Models." Information System Research, 6(2), 145-176, 1995.
79.Teo, Thompson S. H. (2001). Demographic and motivation variables associated with Internet usage activities. Internet Research, 11(2), 125-136.
80.Tornatzky, L.G. and Klein, K.J., "Innovation Characteristics and Innovation Adoption-Implementation: A Meta-Analysis of Findings." IEEE Transactions on Engineering Management, 29(1), 28-45, 1982.
81.Traub, S. H. (1996). Battling employee crime: A review of corporate strategies and programs. Crime and Delinquency, 42, 244–252.
82.Tripat Gill. Convergent Products: What Functionalities Add More Value to the Base? Journal of Marketing. Chicago: Mar 2008. 72(2); p.46
83.Vassilakis, C., Lepouras, G., Fraser, J., Haston, S., and ,Georgiadis, P. "Barriers to Electronic Service Development," e-Service Journal (4:1), Fall 2005, pp. 41-65.
84.Venkatesh, V, F. D. Davis, A model of the antecedents of perceived ease of use: Development and test. Decision Sci 27. 1996, pp. 451-481.
85.Venkatesh, V. and Davis, F.D., A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies, Management Science, 46(2), 2000, pp. 186-204.
86.Wang, Y.-S., Lin, H.-H., Luarn, P. Predicting consumer intention to use mobile service (2006) Information Systems Journal, 16 (2), pp. 157-179.
87.Webster, J. (1998). Desktop videoconferencing: experiences of complete users, wary users and non-users. MIS Quarterly, 22, 257-286.
88.Webster, J., and Martocchio, J. J. (1992). Microcomputer playfulness: development of a measure with workplace implications. MIS Quarterly, 19(2), 201-226.
89.Westin, A. F. "Opinion Surveys: What Consumers Have to Say about Information Privacy," Prepared Witness Testimony, The House Committee on Energy and Commerce, W.J. "Billy" Tauzin, Chairman, May 8, 2001.
90.Westin, A. F. Privacy and Freedom, Atheneum, New York, NY, 1967.
91.Wolfinbarger, M., & Gilly, M. C. (2003). eTailQ: Dimensionalzing, measuring and predicting etail quality. Journal of Retailing, 79, 183–198.
92.Yu, J., Ha, I., Choi, M., Rho, J. Extending the TAM for a t-commerce (2005) Information and Management,42(7),pp. 965-976.
93.Zweig, D., Webster, J. Where is the line between benign and invasive? An examination of psychological barriers to the acceptance of awareness monitoring systems (2002)Journal of Organizational Behavior,23(5),pp. 605-633.
二、中文文獻
1.王瓊鋒. (2007). 建構與驗證行動理財系統使用行為意圖模式之研究. 大葉大學資訊管理學系碩士在職專班碩士論文.
2.吳萬益、林清和(2000)，「企業研究方法」，初版，中華民國：華泰書局。
3.張彥淳. (2006). 影響消費者採用行動付款因素之研究. 國立中央大學資訊管理學系碩士在職專班碩士論文.
4.謝政益. (2003). 網路電話接受度之研究. 國立台灣科技大學資訊管理系研究所碩士論文.
5.魏碧梅. (2004). 台灣網際網路使用者對即時通訊之認知與實際使用狀況. 國立政治大學資訊管理研究所碩士論文.
三、網站資料、網路文獻
1.手軟科技
http://www.mo-soft.com/
2.行政院國家通訊通信發展推動小組
http://www.nici.nat.gov.tw/
3.資策會FIND網站
http://www.find.org.tw/find/home.aspx