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研究生: 丁彥翔
Ting, Yen-Hsiang
論文名稱: 以整合模型評估影響雲端服務系統之 採用因素與策略改善
Using the Integration Models for Evaluating the Improvement Strategies of Cloud Service System Adoption
指導教授: 黃啟祐
Huang, Chi-Yo
學位類別: 碩士
Master
系所名稱: 工業教育學系
Department of Industrial Education
論文出版年: 2013
畢業學年度: 101
語文別: 英文
論文頁數: 95
中文關鍵詞: 雲端運算任務技術適配模式資訊系統成功模式決策實驗室網路流程分析法結構方程模型VIKOR法
英文關鍵詞: Cloud Computing Technology, Task-Technology Fit (TTF), Information System Success Model (ISSM), DEMATEL based Network Process (DNP), Structural Equation Modeling (SEM), VIKOR
論文種類: 學術論文
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  • 資訊與通訊技術的快速發展及消費性電子產品的快速普及帶動雲端運算技術的進步與普及。然而,雲端運算的評估與應用一直是企業內資訊科技經理人的重大挑戰。就雲端運算系統而言,雖然全球已有不少大型企業建置,但一般企業仍有許多考慮因素,故分析與評估雲端運算技術對公司之適合度與是否能成功導入非常重要。唯過去少有相關文獻由技術適配與資訊系統兩構面探討技術採用與否,因此,本研究首先將回顧任務技術適配度、資訊系統成功模式與雲端運算相關文獻,探討影響企業導入雲端運算技術及資訊系統是否成功之重要因素,除藉由決策實驗室網路流程分析法歸納專家意見,建構因素間之因果關係與各因素之權重外,並同時以結構方程模型調查一般雲端系統使用者的意見作為比較,最後使用VIKOR法,訂定提升雲端運算之技術適合度與雲端服務系統成功之策略。本研究將邀集資訊科技專家針對中華電信所提供之雲端運算服務進行之實證分析,並調查影響企業使用者採用雲端服務之重要因素。實證結果顯示從產業專家的角度而言,使用者滿意度為最重要者,採用策略上以資源彈性、降低成本、整合策略為最佳。本研究結果將可為雲端服務廠商研發與行銷策略訂定之依據,也可作為分析其它資訊系統採用與系統成功建立策略之用。

    The advances in information and communication technology (ICT) and rapidly diffused novel consumer electronics products increase demands accelerates the adoptions of cloud computing applications. However, evaluation and application of cloud-based applications is always challenging for information technology (IT) managers’ decisions of technology adoption. Though some leading firms have already adopted the cloud computing based systems, a lot of firms still have barriers to do so. Therefore, an analysis and evaluation of factors influencing the adoption and the final success of the cloud service based systems are very critical. However, past researches on related issues are very limited. Thus, this research aims to develop an analytic framework to derive critical factors influencing the adoption and the final success of the cloud based systems. At first, the literature being related to the Task-Technology Fit Model (TTF), Information System Success Model (IS Success Model) as well as recent advances in the cloud computation technology will be reviewed. Then, a multiple criteria decision making (MCDM) framework consisting of the Decision Making Trial and Evaluation Laboratory (DEMATEL) based Network Process (ANP) will be introduced for constructing the decision problem and deriving weights versus each criterion based on experts’ opinions. Further, the theoretical framework and corresponding hypotheses will be tested based on business users’ opinions by using the structural equation modeling (SEM) method. Finally, the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) as the tool for ranking the alternatives will be proposed for defining strategies for enhancing the adoption as well as information system success rate. An empirical analysis based on the cloud computation services being provided by China Telecom Corp. Taiwan will be used for verifying the feasibility of the analytic framework. The empirical study based on industrial experts present that user satisfaction is the most important. In adoption strategies that resources flexibility, low cost, and integration are the best. The results of this research can serve as the basis for marketing and R&D strategy definitions for cloud computation service providers. The analytic framework can also serve as the basis for strategy definitions aiming to enhance the adoption rate as well as successes of other information systems.

    中文摘要 i Abstract ii Chapter 1 Introduction 1 1.1 Research Backgrounds 1 1.2 Research Motivations and Problems 3 1.3 Research Objectives and Limitations 4 1.4 Research Method and Framework 5 Chapter 2 Literature Review 8 2.1 Cloud Computing 8 2.1.1 The Definition of Cloud Computing 9 2.1.2 Essential Characteristics of Cloud Computing 11 2.1.3 Cloud Computing’s Service and Deployment Models 13 2.1.4 The Key Drivers to Adoption of Cloud Computing 16 2.1.5 The Advantages and Challenges of Cloud Computing 18 2.1.6 Adoption of Cloud Computing Strategies Definition 21 2.2 Task-technology fit (TTF) 25 2.3 Information System Success Model (ISSM) 29 Chapter 3 Research Method 33 3.1 Modified Delphi Method 33 3.2 DEMATEL based Network Process (DNP) 36 3.3 Structural Equation Modeling (SEM) 41 3.3.1 Path Analysis 45 3.3.2 Goodness of Fit Criteria 46 3.4 VIKOR 47 3.5 Integration Model 51 Chapter 4 Empirical Study 53 4.1 Criteria Definition by Modified Delphi Method 53 4.2 Decision Problems Structuring on Experts Based DNP 54 4.3 Testing of the Reliability by Cronbach’s Alpha 59 4.4 Empirical Study on Business Cloud Service Users by SEM 59 4.5 Rank the Cloud Adoption Strategies by VIKOR 62 Chapter 5 Discussion 65 5.1 Discussion on Differences Between Experts’ Aspects and Mass Users’ Opinions Based on the DNP and SEM Results 65 5.2 Strategic Implications Based on Compromise Solutions by VIKOR 71 Chapter 6 Conclusions 75 References: 77 Appendix A: Questionnaire of Experts for Cloud Service System 88 Appendix B: Questionnaire of Enterprise users for Cloud Service System 92

    Agarwal, R. & Prasad, J. (2007). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28(3), 557-582.
    Ambra, J. D. & Rice, R. E. (2001). Emerging factors in user evaluation of the World Wide Web. Information & Management, 38(6), 373-384.
    Amrhein, D. (2009). Forget defining cloud computing. Ulitzer. http://dustinamrhein.ulitzer.com/node/1018801
    Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., & Zaharia, M. (2009). Above the clouds: a Berkeley view of cloud computing. [Technical Report No.UCB/EECS-2009-28] Retrieved from http://x-integrate.de/x-in-cms.nsf/id/DE_Von_Regenmachern_und_Wolkenbruechen_-_Impact_2009_Nachlese/$file/abovetheclouds.pdf
    Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., & Zaharia, M. (2010). A view of cloud computing. Communications of the ACM, 53(4), 50-58.
    Babcock, C. (2010). Management strategies for the cloud revolution: how cloud computing is transforming business and why you can’t afford to be left behind. USA: McGraw-Hill.
    Barnes, F. R. (2010). Putting a lock on cloud-based information. Information Management Journal, 44(4), 26.
    Brooks, K. W. (1979). Delphi technique: expanding applications. North Central Association Quarterly, 54(3), 377-385.
    Buyya, R., Yeo, C. S., Venugopal, S., Broberg, J., & Brandic, I. (2009). Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation Computer Systems, 25(6), 599-616.
    Carlo D. S. & John T. M. (2010). Forecasting task-technology fit: The influence of individuals, systems and procedures on forecast performance. International Journal of Forecasting, 26(1), 144-161.
    Chen, N. C. & Lin, A. (2012). Cloud computing as an innovation: Percepetion, attitude, and adoption. International Journal of Information Management, 32(6), 533-540.
    Chen, Y. (2010). Cloud computing strategy. Taiwan: CWbook.
    Chen. Y. C., Lien. H. P. & Tzeng, G. H. (2010). Measures and evaluation for environment watershed plans using a novel hybrid MCDM model. Expert System with Applications, 37(2), 926-938.
    Cheng, R. (2010, Feb 8). Cloud computing: what exactly is it anyway. [The Wall Street Journal]. Retrieved from http://online.wsj.com/article/SB10001424052748703580904574638391318085158.html
    Chiu, W. Y., Tzeng, G. H., & Li, H. L. (2010). Advances in intelligent decision technologies: proceedings of the second KES international symposium IDT 2010, Scientific Publishing Services Pvt. Ltd, Chennai, India.
    Custer, R. L., Scarcella, J. A. and Stewart, B. R. (1999). The modified Delphi technique-a rotational modification, Journal of Vocational and Technical Education, 15(2), 50-58.
    Dalkey, N. & Helmer, O. (1963). An experimental application of the Delphi method to the use of experts. Management Science, 9(3), 458-467.
    Dalkey, N. C. (1972). The Delphi method: an experimental application of group opinion. In: N. C. Dalkey, D. L. Rourke, R. Lewis, and D. Snyder (Eds.), Studies in the Quality of Life. MA: Lexington Books.
    DeLone, W. H. & McLean, E. R. (1992). Information systems success: the quest for the dependent variable. Information Systems Research, 3(1), 60-95.
    DeLone, W. H. & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems, 19(4), 9-30.
    Demarest, G. & Wang, R. (2010). Oracle Cloud Computing [Oracle White Paper]. Retrieved from http://www.oracle.com/us/technologies/cloud/oracle-cloud-computing-wp-076373.pdf
    Duckstein, L. & Opricovic, S. (1980). Multiobjective optimization in river basin development. Water Resources Research. 16(1), 14-20.
    Durkee, D. (2010). Why cloud computing will never be free? Communications of the ACM, 53(5), 62-69.
    Educause. (2009). 7 things you should know about cloud computing. Retrieved from http://net.educause.edu/ir/library/pdf/EST0902.pdf
    Freimer M. & Yu, P. L. (1976). Some new results on compromise solutions for group decision problems. Management Science, 22(6), 688-693.
    Gabus, A. & Fontela, E. (1972). World problems an invitation to further thought within the framework of DEMATEL, Battelle Geneva Research Centre, and Geneva, Switzerland.
    Gebauer J. & Shaw M. J. (2004). Success factors and impacts of mobile business applications: Results from a mobile e-procurement study. International Journal of Electronic Commerce, 8(3), 19-41.
    Galbraith, C. & Schendel, D. (1983). An empirical analysis of strategy types. Strategic Management Journal, 4(2), 153-173.
    Goodhue, D. L. (1995). Understanding user evaluations of information systems. Management Science, 41(12), 1827-1844.
    Goodhue, D. L. (1998). Development and measurement validity of a task-technology fit instrument for user evaluations of information system. Decision Sciences, 29(1), 105-138.
    Goodhue, D. L. & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213-236.
    Goscinski, A. (2010). Toward dynamic and attribute based publication, discovery and selection for cloud computing. Future Generation Computer Systems, 26(7), 947-970.
    Grossman, R. L. (2009). The Case for Cloud Computing. IT Professional, 11(2), 23-27.
    Grover, V. & Goslar, M. D. (1993). The initiation, adoption, and implementation of telecommunications technologies in U.S. organizations. Journal of Management Information Systems, 10(1), 141-163.
    Hammond, S. (2008). Cloud computing: IT of the future or powder puff? Retrieved rom http://enterpriseinnovation.net/article/cloud-computing-it-future-or-powderpuff
    Hartig, K. (2009). What is cloud computing? Cloud Computing Journal, Retrieved from http://cloudcomputing.sys-con.com/node/579826
    Harvard Business Review. (2010). What we’re watching in cloud computing? Harvard business review, (June): 24-30.
    Hong L., Jeff S., Jay H. S., Ed J., Catherine, S., & Sudip, C. (2009). Developing an enterprise cloud computing strategy. [Intel White Paper] Retrieved from http://www.intel.com/content/www/us/en/cloud-computing/software-as-a-service--saas-/intel-it-developing-cloud-computing-strategy-paper.html
    Huang, C. Y. & Tzeng, G. H. (2007). Reconfiguring the innovation policy portfolios for Taiwan’s SIP mall industry. Technovation, 27(12), 744-765.
    IBM. (2009). Get started with cloud through the right business based IT strategy (IBM Repot). Retrieved from http://www-304.ibm.com/industries/publicsector/fileserve?contentid=222872
    Ip, R. K. F. & Wagner, C. (2008). Weblogging: A study of social computing and its impact on organizations. Decision Support Systems, 45(2), 242-250.
    Jiang, J. J., Klein, G., & Carr, C. L. (2002). Measuring information system service quality: SERVQUAL from the other side, MIS Quarterly, 26(2), 145-166.
    Jithesh, M. & Vasvi, B. (2010). A Cloud Computing Solution in Universities (IBM Report). Retrieved from http://www.ibm.com/developerworks/webservices/library/ws-vcl/
    Jones, J. & Hunter, D. (1995). Qualitative research: Consensus methods for medical and health services research. British Medical Journal, 311(5), 376-380.
    Judd, R. C. (1972). Forecasting to consensus gathering: Delphi grows up to college needs. College and University Business, 53(1), 35-38.
    Junglas, I. A., Abraham, C., & Watson, R. T. (2008). Task-technology fit for mobile and locatable information system. Decision Support Systems, 45(4), 1046-1057.
    Karimi, J., Somers, T. M., & Gupta, Y. P. (2004). Impact of environmental uncertainty and task characteristics on user satisfaction with data. Information Systems Research, 15(2), 175-193.
    Kenneth, C. L. & Jane, P. L. (2012). Management Information Systems: Managing the Digital Firm. New York: Pearson.
    Lee, Y. S., Huang, J. C., & Hsu, Y. S. (2008). Using modified Delphi method to explore the competition strategy for software companies of Taiwan. Journal of Informatics & Electronics, 13(1), 39-50.
    Lijun, M., Chan, W. K., & Tse, T. H. (2008). A tale of clouds: Paradigm comparisons and some thoughts on research issues. Asia-Pacific Services Computing Conference, 11, 464-469.
    Lin, C. L., Hsieh, M. S.,& Tzeng, G. H. (2010). Evaluating vehicle telematics system by using a novel MCDM techniques with dependence and feedback. Expert System with Application, 37(10), 6723-6736.
    Lin, W. S. (2012). Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives. International Journal of Human-Computer Studies, 70(7), 498-507.
    Lina A. & Chen, N. C. (2012). Cloud computing as an innovation: Percepetion, attitude, and adoption. International Journal of Information Management, 1142(8) 1-8.
    Linstone, H. A. & Turoff, M. (1975). The Delphi method: Techniques and applications, reading. MA: Addison-Wesley.
    Liou, J. J. H., Tzeng, G. H., & Chang, H. C. (2007). Airline safety measurement using a hybrid model. Journal of Air Transport Management, 13(4), 243-249.
    Liou, J. J. H., Tsai, C.Y. Lin, R. H., & Tzeng, G. H. (2011). A modified VIKOR multiple-criteria decision method for improving domestic airlines service quality. Journal of Air Transport Management, 17(2), 57-61.
    Luis, M. V., Luis, R. M., Caceres J., & Lindner, M. (2009). A break in the clouds: towards a cloud definition. ACM SIGCOMM Computer Communication Review, 39(1), 50-51.
    Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., & Ghalsasi, A. (2011). Cloud computing — The business perspective. Decision Support Systems, 51(1), 176-189.
    Martin, M. J. C. (1994). Managing Innovation and Entrepreneurship in Technology-Based Firms. John New York: Wiley and Sons Inc.
    Mather, T., Latif, S., & Kumaraswam, S. (2009). Cloud Security and Privacy: An Enterprise Perspective on Risks and Compliance. USA: O’Reilly Media, Inc.
    Mcfarlan, W. (1984). Information technology changes the way you compete. Harvard Business Review, 62(4), 98-103.
    Mell, P. & Grance, T. (2009). Effectively and securely using the cloud computing paradigm, NIST, Retrieved from http://csrc.nist.gov/organizations/fissea/2009-conference/presentations/fissea09-pmell-day3_cloud-computing.pdf
    Mohr, J., Sengupta, S., & Slater, S. (2010). Marketing of high-technology products and innovations (3 rd.). USA: Pearson, Inc.
    Murry, J. W. & Hammons, J. O. (1995). Delphi: A versatile methodology for conducting qualitative research. The Review of Higher Education, 18(4), 423-436.
    NIST. (2011). The NIST Definition of Cloud Computing (Special Publication 800-145). Retrieved from http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf
    Osei, B. K. M. & Ko, M. (2004). Exploring the relationship between information technology investments and firm performance using regression splines analysis. Information and Management, 42 (1), 1-13.
    Opricovic, S. (1998). Multicriteria Optimization of Civil Engineering Systems, Faculty of Civil Engineering, Belgrade.
    Opricovic, S. & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455.
    Opricovic, S. & Tzeng, G. H. (2007). Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, 178(2), 514-529.
    Osei, B. K. M. & Ko, M. (2004). Exploring the relationship between information technology investments and firm performance using regression splines analysis. Information and Management, 42(1), 1-13.
    Pai, F. Y. & Huang, K. I. (2011). Applying the technology acceptance model to the introduction of healthcare information systems. Technological Forecasting and Social Change, 78(4), 650-660.
    Pai, J. C. & Tu, F. M. (2011). The acceptance and use of customer relationship management (CRM) systems: An empirical study of distribution service industry in Taiwan. Expert Systems with Applications, 38(1), 579-584.
    Pao-Lien, W., Huang, J. H., Tzeng, G. H., & Shwu-Ing, W. (2010). Causal modeling of web-advertising effects by improving SEM based on DEMATEL technique. International Journal of Information Technology & Decision Making, 9(05), 799-829.
    Parkes, A. (2013). The effect of task–individual–technology fit on user attitude and performance: An experimental investigation. Decision Support Systems, 54, 997-1009.
    Petter, S., DeLone, W., & McLean E. (2008). Measuring information systems success: models, dimensions, measures, and interrelationships. European Journal of Information Systems, 17, 236-263.
    Pettey, C. (2008). Gartner Says Cloud Computing Will Be As Influential As E-business (Gartner Report) Retrieved from http://www.gartner.com/it/page.jsp?id=766215
    Pitt, L. F., Watson, R. T., & Kavan, C. B. (1995). Service quality: a measure of information systems effectiveness. MIS Quarterly, 19(2), 173-187.
    Popovic, K. & Hocenski, Z. (2010). Cloud computing security issues and challenges. MIPRO, 2010 Proceedings of the 33rd International Convention, 344-349.
    Reynolds, E. & Bess, C. (2009). Clearing up the cloud: adoption strategies for cloud computing. Cutter it journal, 22(6), 7.
    Saaty, T. L. (1980). The Analytic Hierarchy Process. New York: McGraw-Hill.
    Sayadi, M. K., Heydari, M., & Shahanaghi, K. (2009). Extension of VIKOR method for decision making problem with interval numbers. Applied Mathematical Modeling, 33(5), 2257-2262.
    Scale, M. E. (2009). Cloud computing and collaboration. Library Hi Tech News, 26(9), 10-13.
    Schumacker, R. E. and Lomax, R. G. (1996). A Beginner’s Guide to Structural Equation Modeling, Mahwah, N.J.: Lawrence Erlbaum Associates, Publishers.
    Schumacker, R. E., & Lomax, R. G. (2004). A beginner's guide to structural equation modeling (Vol. 1): Lawrence Erlbaum.
    Seddon, P. B. (1997). A respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, 8(3), 240-253.
    Shimba, F. (2010). Cloud computing: strategies for cloud computing adoption. Dublin Institute of Technology.
    Shipley, G. (2009). Navigating the storm: governance, risk and compliance in the cloud. North America: InformationWeek.
    Smith, R. (2009). Computing in the cloud. Research Technology Management, 52(5), 65-68.
    Sultan, N. (2010). Cloud computing for education: A new dawn? International Journal of Information Management, 30(2), 109-116.
    Sung, W. C. (2001). Application of Delphi method, a qualitative and quantitative analysis, to the healthcare management. Journal of Healthcare Management, 2(2), 11-19.
    Tanya, J. M. & Jane, E. K. (2009). A task–technology fit view of learning management system impact. Computers & Education, 52(2), 496–508.
    Truong, D. (2010). How Cloud Computing Enhances Competitive Advantages: A Research Model for Small Businesses. Retrieved from http://dothang.wordpress.com/2011/04/16/how-cloud-computing-enhances-competitive-advantages-a-research-model-for-small-businesses/
    Tzeng, G. H., Lin, C. W. & Opricovic, S. (2005). Multi-criteria analysis of alternative-fuel buses for public transportation. Energy Policy, 33 (1) 1373-1383.
    Voas, J. & Zhang, J. (2009). Cloud computing: New wine or just a new bottle? IT Professional, 11(2), 15-17.
    Vouk, M. A. (2008). Cloud computing – Issues, Research and Implementation. Journal of Computing and Information Technology, 16(4), 235-246.
    Wang, C., Wang, Q. Ren, K., & Lou, W. (2010). Privacy-Preserving Public Auditing for Data Storage Security in Cloud Computing. INFOCOM, 2010 Proceedings IEEE, 1-9.
    Weiss, A. (2007). Computing in the clouds. NetWorker, 11(4), 16–25.
    Woodroof, J. and Burg, W. (2003). Satisfaction/dissatisfaction: are users predisposed? Information and Management, 40(4), 317-324.
    Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20(7), 557-585.
    Wright, S. (1934). The method of path coefficients. Annals Mathematical Statistics, 5(3), 161-215.
    Wright, S. (1960). Path coefficients and path regression: Alternative or complementary concepts. Biometrics, 16(2), 189-202.
    Wu, J. H., & Wang, Y. M. (2006). Measuring KMS success: A respecification of the DeLone and McLean’s model. Information & Management, 43(6), 728-739.
    Yen, D. C., Wu, C. S., Cheng, F. F., & Huang, Y. W. (2010). Determinants of users’ intention to adopt wireless technology: An empirical study by integrating TTF with TAM. Computers in Human Behavior, 26(5), 906-915.
    Yu, P. L. (1973). A class of solutions for group decision problems. Management Science, 19(8), 936-946.
    Zack, M. H. (2007). The role of decision support systems in an indeterminate world. Decision Support Systems, 43(4), 1664–1674.
    Zeleny M. (1982). Multiple Criteria Decision Making. New York: McGraw-Hill.
    Zhoua, T., Lub, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760-767.

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