第五章 結論與建議
第五節 後續研究建議
國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
93
第四節 研究限制
首先，在樣本的界定與選擇方面，本研究在 700 份樣本中，僅選擇其中 436 位具 Line 公共服務類官方帳號使用經驗的樣本進行分析；且本研究所有問 卷均在同一問卷調查網中發送，許多填答者是該問卷調查網會員，樣本方面有 其侷限性。
在研究範圍方面，本研究以 Line 公共服務類官方帳號作為臺灣公部門行動 化的其中一個類型，但並未進一步將 Line 公共服務類官方帳號和公部門在其他 管道的行動化作為進行比較，也未將目前的行動政府和傳統電子政府進行比較。
此外，Line 官方帳號為公部門行動化的一部分，但真正的行動化、行動政府不僅 止於此，遠超過 Line 此單一媒體平臺，本研究以 Line 為例，但更大範圍的行動 政府有必要被研究。
第五節 後續研究建議
從過去有關行動政府的研究文獻中，除了以政府和群眾為主題外，也有研究 是專門討論行動化政府和企業，甚至是在行動化環境下，政府公部門和公部門之 間的關係，一個研究難以觸及所有的面向，因此，在政府和群眾的討論之外，其 他面向的討論也須要同樣的探究與討論。
另在理論架構上，本研究的觀念性架構建基於 TAM，僅包含吸引使用者採 用的正向因素，但並未調查採用採用官方帳號負面阻礙因素，例如隱私、信任、
安全等顧慮，另外一些外部的法律規範宣傳、技術或基礎設施不足等，這些面向 在過去研究中都曾被認為是影響群眾採用公部門媒體平臺以及妨礙行動化政府 的負面因素，值得進一步研究。
就 TAM 此一理論，雖然使用意向在 TAM 中一直都被作為是實際使用行為
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
94
的預測指標，但仍有些研究指出，使用意願其實和實際使用並沒有顯著關係。因 此，未來應可進一步針對 Line 公共服務類官方帳號的使用意願和實際使用進行 研究。
‧
‧
‧
‧
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
99 問卷題目
因素 負荷量
校正式題項 與總分之相 關係數
Cronbach's Alpha if Item
Deleted
刪除或保留
公共服務類官方帳號
‧
‧
‧
‧
‧
‧
‧
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
107 Q40 請問您的性別。
1 男性 2 女性 3 其他+文字框
Q41 請問您的年齡。
1 18 歲以下 2 18-24 歲 3 25-34 歲 4 35-44 歲 5 45-54 歲 6 55-64 歲 7 64 歲以上
Q42 請問您的教育程度。
1 國中以下 2 高中職 3 專科 4 大學 5 研究所以上
Q43 請問您的個人平均月收入（新臺幣：元）
1 無收入 2 20,000 以下 3 20,001~40,000 4 40,001~60,000 5 60,001~80,000 6 80,000 以上
Q44 請問您的職業。
1 農林漁牧 2 批發零售業 3 金融保險業 4 職業軍警 5 資訊業 6 學生 7 製造業 8 住宿餐飲業 9 不動產租賃業 10 公教 11 大眾傳播業 12 待業、退休
13 運輸、倉儲業 14 專業師級人員（指領有證照者，如律師）15 醫療保健業 16 社會福利服務業 17 家管 18 其他服務業 19 其他+文字框
Q45 請問您使用 Line 的頻率。
1 每天數次以上 2 幾乎每天 3 一禮拜 2-4 次 4 一禮拜 1 次 5 一個月 2-3 次 6 一個月 1 次或更少 7 無
‧
‧
新聞》，取自 http://news.tvbs.com.tw/old-news.html?nid=227244〈新媒體崛起 兩岸政府沒跟上〉（2014 年 7 月 3 日）。《旺報》，取自 http://www.chinatimes.com/newspapers/20140703001083-260310
王志弘譯（2008）。《看不見的城市》。臺北:時報。（原書 Calvino, I. [1972]. Invisible Cities,London, UK: Faber and Faber.）
邱皓政（1994）。《量化研究與統計分析》。臺北：五南 子報》。取自 http://www.chinatimes.com/realtimenews/20150901003742-260410 資策會（ 2015 ）。《2015 年第二季臺灣網路、行動調查數據報告》。取自資 策會網頁 http://www.find.org.tw/market_info.aspx?n_ID=8509
劉佳鑫（2013 年 4 月）。〈再見了，小綠人誰是下一個通訊軟體霸主？〉，《動 腦雜誌》。取自 http://www.brain.com.tw/news/articlecontent?sort=&ID=18494 羅之盈（2013 年 7 月）。〈虛實整合再進化~迎接 O2O 大商務時代〉，《數位
Agarwal, R., & Prasad, J. （1999）. Are Individual Differences Germane to the Acceptance of New Information Technologies? Decision Sciences, 30（2）, 361-391.
Ahn, T., Ryu, S., & Han, I. （2007）. The impact of Web quality and playfulness on user acceptance of online retailing. Information & Management, 44, 263-275.
Ajzen, I. （1985） From intentions to actions: A theory of planned behavior, In J.
Kuhl & J. Beckmann （Eds.）, Action Control: From Cognition to Behavior （pp.
11-39）. New York, NY: Springer Verlag.
‧
Aladwani, A.M. （2002）. The development of two tools for measuring the easiness and usefulness of transactional Web sites. European Journal of Information Systems,
11（3）, 223-234.
Al-Debei, M.M., Jalal, D., & Al-Lozi, E. （2013）. Measuring web portals success: a respecification and validation of the DeLone and McLean information systems
success model. International Journal of Business Information Systems. 14（1）, 96-133.
Algahtani, A.F. （2011）. Evaluating the Effectiveness of the E-learning Experience in Some Universities in Saudi Arabia from Male Students Perceptions., Retrieved from http://etheses.dur.ac.uk/3215/1/Abdullah'sThesis.pdf?DDD29+
Al-Hujran, O. （2012）. Toward The Utilization Of M-Government Services In Developing Countries: A Qualitative Investigation. International Journal of Business
and Social Science, 3 （5）, 155-160.
Al-Khamayseh, S., E. Lawrence & A. Zmijewska（2006）. Towards Understanding Success Factors in Interactive Mobile Government. Retrieved from
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.98.3319&rep=rep1&type=p df
Al-Khouri, A.M. （2012）. Customer Relationship Management: Proposed Framework from a Government Perspective. Journal of Management and Strategy, 3（4）, 34-54.
Amin, H., Mohd. R. A., Hamid, S., Lada, S. & Anis, Z. （2008）. The adoption of mobile banking in Malaysia: The case of Bank Islam Malaysia Berhad. International
Journal of Business and Society, 9（2）, 43-53.
Anderson, J.C. and Gerbing D.W. （1988）: Structural Equation Modeling in Practice:
A Review and Recommended Two Step Approach. Psychological Bulletin, 103, 411-423.
Au, N., Ngai, E. W. T., & Cheng, T. C. E.（2008）. Extending the Understanding of End User Information Systems Satisfaction Formation: An Equitable Needs
Fulfillment Model Approach. MIS Quarterly（32）1, 43–66.
Bagozzi, R. P. & Y. Yi （1988）. On the Evaluation of Structural Equation Models.
Journal of the Academy of Marketing Science,16,74-94.
Ballou, D. P., Wang, R., Pazer, H.L., & Tayi G.K. （1998） . Modelling Information Manufacturing Systems to Determine Information Product Quality. Management
Science, 44（4）, 462–484.
Bani Ali, A. S. & Money, W. H. （2008）. Impact of organizational and project factors on acceptance and usage of project management software and perceived project success. Project Management Journal, 39（2）, 5-33.
Bentler, P. M., & Chou, C. P. （1987）. Practical issues in structural modeling.
‧
Sociological Methods & Research, 16, 78-117.
Baron, S., Patterson, A., & Harris, K（2006）. Beyond technology acceptance:
understanding consumer practice. International Journal of Service Industry
Management, 17（2）, 111–135.
Benbasat, I. & Barki, H. （2007）. Quo vadis TAM. Journal of the Association for
Information Systems, 8, 211–218.
Bitner, Mary J. & Amy R.（1994）. Encounter Satisfaction versus Overall Satisfaction Versus Quality. In Rust T. & Oliver L. （Ed.）Service Quality: New Directions in Theory and Practice（ pp. 72–84）. New York, NY:Sage Publications Inc.
Brackett, L. K., & Carr, B. N.（2001）. Cyberspace Advertising vs. Other Media:
Consumer vs. Mature Student Attitudes. Journal of Advertising Research. 41（5）, 23-33.
Brücher, H., & Baumberger, P. （2003）. Using Mobile Technology to Support eDemocracy. Paper presented at the Proceedings of the 36th Hawaii International Conference on System Sciences, Hawaii, HI.
Carroll, J. （2005）. Risky Business: Will Citizens Accept M-government in the Long Term? Retrieved from
http://mobility.grchina.com/lab/Archives/EuromGov2005/PDF/9_R376JC.pdf
Carroll, J. （2005）. Risky Businesss: Will Citizens Accept M-government in the Long Term? In I. Kushchu, & M. H. Kuscu （Ed.）, Proceedings of the Euro mGov （pp.
77-87）. Brighton, UK: Mobile Government Consortium International Publications.
Cantwell, B.（2002）. Why Technical Breakthroughs Fail: A History of Public Concern with Emerging Technologies, Working Report, Auto-ID Center, MIT, Cambridge （MA）.
Chismar, W. G. & Wiley-Patton, S. （2002）. Does the Extended Technology Acceptance Model Apply to Physicians? Paper presented at the proceedings of the 26th Conference of the American Medical Informatics Association Symposium, San Antonio, TX.
Chong, A. Y. L. （2013）. Mobile commerce usage activities: The roles of
demographic and motivation variables. Technological Forecasting and Social Change,
80 （7）, 1350–1359.
Chong, A. Y. L. （2013）. Predicting M-commerce adoption determinants: A neural network approach. Expert Systems with Applications, 40 （2）, 523–530.
Chun, S. A., Shulman, S., Sandoval, R., & Hovy, E. （2010）. Government 2.0:
Making connections between citizens, data and government. Information Polity, 15
（1/2）, 1-9.
‧
Comrey, A. L. （1973）. A first course in factor analysis. New York: Academic Press.
Cronbach, L. J. （1990）. Essentials of psychological testing （5th ed.）. New York:
Harper &Row.
Cruz, P., L. B. F. Neto, P. Munoz-Gallego, & T. Laukkanen. （2010）. Mobile banking rollout in emerging markets: Evidence from Brazil. International Journal of Bank
Marketing, 28（5）, 342-371.
Dasgupta, S., R. Paul, & S. Fuloria.（2011）. Factors affecting behavioral intentions towards mobile banking usage: Empirical evidence from India. Romanian Journal of
Marketing, 3（1）, 6-28.
Davis, F.D. （1989）. A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. In F.D. Davis （Eds.）,
Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology （pp. 319-340）. Cambridge, MA: ,Sloan School of Management, MIT.
Davis, F.D., Bagozzi, R.P.,& Warshaw, P.R. （1989）. User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science ,35（8）, 982-1003.
DeLone, W., & McLean, E.（2003）. The DeLone and McLean Model of Information System Success: A Ten-Year Update. Journal of Management Information Systems , 19（4） ,9-30.
Dishaw, M.T. & Strong, D.M. （1999）. Extending the Technology Acceptance Model with Task-Technology Fit Constructs. Information and Management, 36（1）, 9-21.
Ducoffe, R. H. （1996）. Advertising value and advertising on the web. Journal of
Advertising Research, 36（5）, 21-35.
Eggers, W.D. & Jaffe, J. （2013）. Gov on the go: Boosting Public Sector Productivity by Going Mobile. Deloitte University Press. Retrieved from
http://dupress.com/articles/gov-on-the-go
Ekelin, A. （2007）. The Work to Make eParticipation Work. Doctoral Dissertation Series, 11. Retrieved from:
http://www.bth.se/fou/forskinfo.nsf/6753b78eb2944e0ac1256608004f0535/06c223cb d4e0037dc12572dd004a9ca1/$file/Ekelin_diss.pdf
El-Kiki, T. & E. Lawrence （2006）. Mobile User Satisfaction and Usage Analysis Model of mGovernment Service. Retrieved from
http://www.m4life.org/proceedings/2006/PDF/11_El-Kiki.pdf
eMarketer （2014）. Smartphone users worldwide will total 1.75 billion in 2014.
Retrieved from: http://www.emarketer.com/Article/Smartphone-
Users-Worldwide-Will-Total-175-Billion-2014/1010536#sthash.igY5dhaW. dpuf Ericsson （2015）. Mobility Report. Available online:
‧
Fishbein, M., & Ajzen, I. （1975）. Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Boston, MA: Addison-Wesley.Fortunati, L. （2006）. User Design and Democratization of the Mobile Phone, First Monday, Web site: http://www.firstmonday.org.
Gao, L., & Bai, X. （2014）. An empirical study on continuance intention of mobile social networking services. Asia Pacific Journal of Marketing and Logistics, 26（2）, 168–189.
Gao, L., Waechter, K. A., & Bai, X. （2015）. Understanding consumers continuance intention towards mobile purchase: A theoretical framework and empirical study – A case of China. Computers in Human Behavior, 53, 249–262.
Gao, T., Rohm, A. J., Sultan, F. & Pagani, M. （2013）. Consumers un-tethered: A threemarket empirical study of consumers mobile marketing acceptance, Journal of
Business Research, 66 （12）, 2536–2544.
Gefen, D., & Straub, D. （2000）. The Relative Importance of Perceived Ease-of-Use in IS Adoption: A Study of e-Commerce Adoption, Journal of Association for
Information Systems, 1（8）, 1-21.
Gefen, D., Karahanna, E, Straub, D.W. （2003）. Trust and TAM in online shopping:
an integrated model, MIS Quarterly, 27（1）, 51-90
Gefen, D., Straub, D. W., & Boudreau, M.C. （2000）. Structural Equation Modeling and Regression: Guidelines for Research Practice. Communications of the
Association for Information Systems, 4（7）, 1-70.
Geoffrey, A. S., & Mcmillan, S. （2005）. A success factor model for m-government.
Paper presented at the Proceeding of the First European Conference on Mobile Government. Brighton, UK.
Gordon, E. & de Souza e Silva, A. （2011）. Net Locality: Why Location Matters in a Networked World. New York, NY: Wiley.
Gorsuch, R. L. （1983）. Factor analysis. Hillsdale, NJ: Lawrence Erlbaum Associates.
Grant, K., Hackney, R., & Edgar, D. （2010）. Strategic Information Systems Management.Andover, MA: Cengage Learning.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. （2006）.
Multivariate data analysis （6th ed.）. Upper Saddle River, NJ: Prentice-Hall.
Hofmann, S., Räckers M., Beverungen D., & Becker J. （2013）. Old Blunders in New Media? How Local Governments Communicate with Citizens in Online Social
Networks. Paper presented at the 46th Hawaii International Conference on System Sciences, Hawaii, HI.
‧
Hogg,R., Martignoni,R. & Stanoevska-Slabeva, K. （2007）. Understanding Todays Mobile Users Expectations of Tomorrows Mobile Services, paper presented at the 16th IST Mobile and Wireless Communications Summit, Budapest, Hungary.
Hong , S. J., Thong, J. Y. L., Moon, J. Y., & Tam, K.Y. （2008）. Understanding the behavior of mobile data services consumers. Info Syst Front, 10, 431-445
Hsu, C.L, Lu, H. P. & Hsu, H.H. （2007）. Adoption of the mobile Internet: An empirical study of multimedia message service（MMS）, Omega, 35（6）, 715-726.
Hung, Y. H., Wang, Y. S. & Chou, S. C. T. （2007）. Determinants of User Acceptance of the e-Government Services: The Case of Online Tax Filing and Payment System, Government Information Quarterly 23（1）, 97-122.
Igbaria, M., Guimaraes, T., & Davis, G.B. （1995）. Testing the Determinants of Microcomputer Usage via a Structural Equation Model. Journal of Management
Information Systems.11（4）, 87-114.
Igbaria, M., Iivari, J., & Maragahh, H.（1995）. Why Do Individuals Use Computer
Technology? A Finnish Case Study. Information and Management, 29, 227-238.
Ispir, N.B., & Suher, H.K. （2009） Perceived Ad Clutter Among Young Consumers:
New Media Expansion. Business Research Yearbook, 16（1）, 64-72.
Jiang, Z., Chan, J.C.F., Tan, B.C.Y., & Chua, W.S （2010）. Effects of Website Interactivity on Consumer Involvement and Purchase Intention, Journal of
Association of Information Systems, 11（1）, 1-5.
Jung, Y., Perez-Mira, B., & Wiley-Patton, S. （2009）. Consumer adoption of mobile TV: Examining psychological flow and media content. Computers in human behavior,
25（1）, 123-129.
Kargin, B. & Basoglu, N. （2006）. Adoption Factors of Mobile Services, Paper presented at the proceedings of the International Conference on Mobile Business, Copenhagen, Denmark.
Kessler, S. （2011）. 38% of college students cant go 10 minutes without tech.
Retrieved from Mashable Tech. Retrieved from: http://mashable.com/2011/05/
31/college-tech-device-stats/
Kim, B., Kang, M. & Jo, H. （2014）. Determinants of post-adoption behaviors of mobile communications applications: A dual-model perspective. International
Journal of Human-Computer Interaction, 30（7）, 1–46.
Kim, M., Chung, N., & Lee, C. （2011）. The effect of perceived trust on electronic commerce: Shopping online for tourism products and services in South Korea.
Tourism Management,32, 256–265.
King, W. R., & He, J. （2006）. A meta-analysis of the technology acceptance model.
Information & Management, 43（6）, 740-755.
‧
Klein, B. D. （2002）. When Do users Detect information quality Problems On The World Wide Web? Paper presented at the 8th Americas Conference on Information Systems, （pp. 1101-1103）.
Knapp, D. （2015）. Global mobile advertising revenue 2014. IAB report. Retrieved from
http://www.iab.com/wp-content/uploads/2015/08/Global_mobile_advertising_revenue _2014_report.pdf
Laukkanen, T. （2007）.Internet vs. mobile banking: comparing customer value perceptions. Business Process Management Journal, 13（6）, 788-797.
Loehlin, J.C., （1992） .Latent Variable Models: An introduction to factor, path and structural analysis（2nd ed.）. Hillsdale, New Jersey.
Liao, C. H., Tsou, C. W., & Huang, M. F（2007）. Factors influencing the usage of 3G mobile services in Taiwan. Online Information Review, 31（6）, 759–774.
Liaw, S.S. & Huang, H.M. （2003）. An investigation of user attitudes toward search engines as an information retrieval tool. Computers in Human Behavior, 19（6）, 751–765.
Limayem, M., & Hirt, S.G.（2003）. Force of Habit and Information Systems Usage:
Theory and Initial Validation. Journal of the Association for Information Systems （4）
3, 65-97.
Lu, J. （2014）. Are personal innovativeness and social influence critical to continue with mobile commerce? Internet Research, 24（2）, 134-159.
Luarn, P. & Lin, H. H. （2005） Toward an understanding of the behavioral intention to use mobile banking, Computers In Human Behavior, 21, 873-891.
Mallat, N., Rossi, M., Tuunainen, V. K., & Ö örni, A. （2009）. The impact of use context on mobile services acceptance: The case of mobile ticketing. Information &
Management, 46（3）, 190-195.
Marcus, R. （2002）. Great Global Grid: Emerging Technology Strategies （1st ed.）.
Victoria, Canada: Trafford Publishing.
Mathieson, K..（1991） Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior, Information Systems Research
2（3）, 173–191.
McMillan, & Downes J. （2000）. Defining Interactivity: A Qualitative Identification of Key Dimensions, New Media and Society, 2（2）, 157-179.
McMillan, S. （2010）. Legal and Regulatory Frameworks for Mobile Government.
Paper presented at the Proceedings of mLife 2010 Conferences. Brighton, UK.
Millward Brown （2014）: AdReaction 2014 study. （n.d.）. Retrieved
from:https://www.millwardbrown.com/adreaction/2014/report/Millward-Brown_AdR
‧
Mir, I. （2011）. Consumer Attitude Towards M-Advertising Acceptance: A Cross-Sectional Study, Journal of Internet Banking and Commerce, 16（1）, 1-22.
Mohd,H., Syed-Mohamad, S. M., & Zaini, B. J. （2005）. Correlation between information quality, user acceptance and doctors attitude of EMR System. Retrieved from database （Researchgate）:
https://www.researchgate.net/publication/228851654_CORRELATION_BETWEEN_
INFORMATION_QUALITY_USER_ACCEPTANCE_AND_DOCTORS'ATTITUD E_OF_EMR_SYSTEM.
Moon, J. & Kim, Y. （2001）. Extending the TAM for a World-Wide-Web context.
Information and Management, 38, 217-230.
Mueller, R. O. （1997）. Structural equation modeling: Back to basics. Structural
Equation Modeling, 4, 353–369.
Nam, T. （2011）. Toward the New Phase of e-Government: An Empirical Study on Citizens Attitude about Open Government and Government 2.0. Retrieved from Web site:
https://www1.maxwell.syr.edu/uploadedFiles/conferences/pmrc/Files/Nam_Toward%
20the%20New%20Phase%20of%20E-government.pdf
Norris, D. F. （2010）. E-government... not e-governance... not e-democracy: Not now!
Not ever? In J. Davies & T. Janowski （Eds.）, Proceedings of the 4th International Conference on Theory and Practice of Electronic Governance （pp. 339-346）. New York, NY: ACM.
Nunnally, J. C. （1978）. Psychometric theory （2nd ed.）. New York, NY:
McGraw-Hill.
Okazaki, S. （2006）. What do we know about mobile internet adopters? A cluster analysis. Information & Management, 43, 127-141.
Nyalunga, D. （2006）. An enabling environement for public participation in local government. Retrieved from: http://www.ddp.org.za/information-material/articles/
Okazaki, S. & Mendez, F. （2013）. Exploring convenience in mobile commerce:
Moderating effects of gender, Computers in Human Behavior, 29（3）, 1234–1242.
Olson, P. （2013）. 10 Predictions for the mobile industry in 2013. Retrieved from:
http://www.forbes.com/sites/parmyolson/2013/01/02/10-predictions-for-the-mobile-in dustry-in-2013/
Pardo, T. A., Nam, T., & Burke, G. B. （2011）. E-Government interoperability:
Interaction of policy, management, and technology dimensions. Social Science
Computer Review, 30（1）, 7–23.
Patel, I., & White, G. （2005）. M-government: South African approaches and
‧
experiences. In I. Kushchu, & M. H. Kuscu （Ed.）, Proceeding of the EURO mGOV 2005 （pp. 313-323）. Brighton, UK: Mobile Government Consortium International Publications.
Pedro, Gustavo, Z. & Nelson, B. （2013）. An application framework for developing collaborative handheld decision-making tools. Behaviour & Information Technology,
33（5）, 470-485.
Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. （2004）. Consumer acceptance of online banking: an extension of the technology acceptance model.
Internet Research,14（3）, 224–235.
Poblet, M. （2011）. Rule of Law on the go: new developments of mobile governance.
Journal of Universal Computer Science, 17（3）, 498-512.
Punch, K （1998） Introduction to Social Research: Quantitatie and Qualitative Approaches, London , UK： Sage
Puschel, J., Mazzon, J. A. & Hernandez, J. M. C. （2010）. Mobile banking:
Proposition of an integrated adoption intention framework, International Journal of
Bank Marketing, 28（5）, 389-409.
Raftery, T. （2012）. Sustainability, Social Media and Big Data. Retrieved from :http://theenergycollective.com/tom-raftery/138166/sustainability-social-media-and-bi g-data
Rainie, L., & Wellman, B. （2012）. Networked: The new social operating system.
Rainie, L., & Wellman, B. （2012）. Networked: The new social operating system.