博碩士論文 984401021 詳細資訊




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姓名 蔡君明(Juin-Ming Tsai)  查詢紙本館藏   畢業系所 企業管理學系
論文名稱 系統動態觀點之創新擴散:以遠距健康照護為例
(Innovation Diffusion Based on System Dynamics Perspective: the Case of Telehealth)
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摘要(中) 創新概念的商業化往往伴著隨高度風險,如果能事先洞察創新擴散的動態過程,將有助於企業降低風險與維持在市場上的競爭力。創新的擴散涵蓋技術創新、使用者接受考量以及政策環境等因素的交互影響。然而,過去關於擴散議題的研究往往侷限於以歷史資料外推預測的結果,對於影響擴散的因素缺乏全面性的探討。因此,亟需一個能整納多元因素並提供更精準預測的評估系統。
本研究以新興產業中的遠距健康照護服務為例,探討創新擴散預測。典型的遠距健康照護服務主要由健康資訊整合中心、使用者、醫療單位與資通訊環境所組成。隨著世界人口急遽老化,各種使用資通訊技術的健康照護創新服務因應而生,遠距健康照護儼然已成為眾多新興產業中最具代表的產業之一。然而,遠距健康照護在台灣尚屬起步階段,未來的發展更是充滿著許多不確定性。本研究提出以系統動態觀點歸納影響遠距健康照護服務擴散的因子,以整合建構健康照護服務的動態擴散模型,並進一步以敏感度分析找出促進與抑制擴散的關鍵因素。
研究結果發現,遠距健康照護所採用的技術已進入成熟階段,產業的發展重點應更著重在服務的創新與整合;政策推動、市場需求是最主要的促進擴散因子;醫療法規則是最關鍵的抑制擴散因子。最後,本研究提出未來十五年的遠距健康照護服務擴散的五種情境預測與建議,希望提供未來創新服務規劃與策略佈局時參考。
摘要(英) The commercialization of the concept of innovation is often accompanied by a high degree of risk. Getting an insight into the dynamic process of innovation diffusion can be conducive to reducing risk and maintaining a competitive edge in the market. The diffusion of innovation covers technical innovation and the mutual interaction between the acceptance of users and the factors of political environments. However, previous studies on diffusion have been mostly limited by the propositions acquired from historical data and have lacked a comprehensive exploration of the influential factors affecting diffusion. A more accurate evaluation system that considers the multi-factor process is highly desired.
This research presents the diffusion of innovation for the emerging industries such as telehealth. A typical telehealth service is composed of an integrated center for health information, users, medical units and ICT (Information and Communication Technology) environments. With the rapid aging of the world’s population, telehealth has become one of the most important applications in the emerging industries. However, telehealth is still in the early stages and investment from government is still small scale. There are many uncertainties for the future development of this industry in Taiwan. This study concluded the factors affecting the diffusion in order to integrate and construct a system dynamics model for emerging industries and, using the analysis of sensitivity, further explore the key factors that either promote or inhibit diffusion.
The results show that the technology for telehealth is already at a mature stage and the emphasis on development in this industry should be placed upon the innovation and integration of services; the policy promotion and market demands are the main factors in enhancing diffusion. Medical regulations are the most critical factors in inhibiting diffusion. In addition, this study also proposes five kinds of scenario forecasts for telehealth service diffusion in the next 15 years, as well as suggestions that can provide guidance for future technology planning and strategic deployment.
關鍵字(中) ★ 創新擴散
★ 系統動態
★ 遠距健康照護
★ 新興產業
★ 預測
關鍵字(英) ★ Innovation Diffusion
★ System Dynamics
★ Telehealth
★ Emerging Industry
★ Forecasting
論文目次 ABSTRACT(CHINESE) I
ABSTRACT II
ACKNOWLEDGMENTS(CHINESE) IV
TABLE OF CONTENTS V
LIST OF FIGURES VII
LIST OF TABLES VIII
CHAPTER 1 INTRODUCTION 1
CHAPTER 2 HEALTHCARE AND TELEHEALTH APPLICATIONS 7
2.1. POPULATION AGEING 7
2.2. TELEHEALTH SYSTEM 9
2.3. THE CURRENT STATE OF THE TELEHEALTH MARKET 12
CHAPTER 3 LITERATURE REVIEW 15
3.1. DIFFUSION AND FORECASTING 15
3.2. DIFFUSION AND SYSTEM DYNAMICS 19
3.3. INFORMATION SYSTEM SUCCESS MODEL 23
3.4. TECHNOLOGY ACCEPTANCE MODEL 27
3.5. POLICY AND ENVIRONMENT 30
CHAPTER 4 RESEARCH DESIGN 34
4.1. SOURCES OF DATA 34
4.2. RESEARCH MODEL AND OPERATIONAL DEFINITION 35
4.3. METHODOLOGY 43
CHAPTER 5 RESULTS AND DISCUSSIONS 48
5.1. BASE CASE 48
5.2. ADVANCED TECHNOLOGY CASES 50
5.3. MEDICAL REGULATION CASES 54
5.4. POLICY PROMOTION CASES 58
5.5. ANALYSIS OF ALTERNATIVE SCENARIOS 63
CHAPTER 6 CONCLUSION 70
6.1 RESEARCH CONCLUSIONS 70
6.2 THEORETICAL AND MANAGERIAL IMPLICATIONS 72
6.3 LIMITATIONS AND FUTURE RESEARCH 75
REFERENCE 78
APPENDIX A: TYPICAL DIFFUSION MODELS (S-CURVE MODELS) 91
APPENDIX B: SYSTEM DYNAMICS MODEL 95
APPENDIX C: TAIWAN HEALTH INDICATORS 108
參考文獻 Abu-Eisheh, S.A., Mannering, F. (2002), “Forecasting automobile demand for economies in transition: a dynamic simultaneous-equation system approach”, Transportation Planning and Technology, 25,311-331.
Adamson, I., Shine, J. (2003), “Extending the new technology acceptance model to measure the end user information systems satisfaction in a mandatory environment: A bank’s treasury”, Technology Analysis & Strategic Management, 15(4), 441-455.
Agarwal S, Lau C.T. (2010), “Remote Health Monitoring Using Mobile Phones and Web Services”, Telemedicine and e-Health, 16(5), 603-607.
Aggelidis, V.P., Chatzoglou, P.D. (2009), “Using a modified technology acceptance model in hospitals”, International Journal of Medical Informatics, 78(2), 115-126.
Aggelidis, V.P., Chatzoglou, P.D. (2012), “Hospital information systems: Measuring end user computing satisfaction (EUCS)”, Journal of Biomedical Informatics, 45(3), 566-579.
Ahn, T., Ryu, S., Ingoo, H. (2007), “The impact of Web quality and playfulness on user acceptance of online retailing”, Information and Management, 44(3), 263-275.
Bass, F.M. (1969), “A new product growth model for consumer durable”, Management Science, 15, 215-227.
Bass, F.M., Krishnan, T.V., & Jain, D.C. (1994), “Why the Bass model fits without decision variables”, Marketing Science, 13, 203-223.
Basberg, B. (1987), “Patents and the Measurement of Technological Change: A Survey of the Literature”, Research Policy, 16(2-4), 131-141.
Bharati, P., Chaudhury, A. (2004), “An empirical investigation of decision making satisfaction in web-based decision support systems”, Decision Support Systems, 37(2), 187-197.
Blank, S.C. (2008), “Insiders’ Views on Business Models Used by Small Agricultural Biotechnology Firms: Economic Implications for the Emerging Global Industry”, AgBioForum, 11(2), 71-81.
Bonnet, C.L. (1986), “Nature of R&D/Marketing Cooperation in the Design of Technologically Advanced New Industrial Products”, R&D Management, 16(2), 117-126.
Casey, T., Töyli, J. (2012), “Mobile voice diffusion and service competition: A system dynamic analysis of regulatory policy”, Telecommunications Policy, 36(3), 162-174.
Chi, K.C., Nuttall, W.J., Reiner, D.M. (2009), “Dynamics of the UK natural gas industry: System dynamics modelling and long-term energy policy analysis”, Technological Forecasting & Social Change, 76, 339-357.
Chu, W.L, Wu, F.S., Kao, K.S., Yen, D.C. (2009), “Diffusion of mobile telephony: An empirical study in Taiwan”, Telecommunications Policy, 33, 506-520.
Cooper, R.G., Kleinschmidt, E.J. (1987), “Success Factors in Product Innovation”, Industrial Marketing Management, 16(4), 215-223.
Coyle, R.G. (1996), “System Dynamics Modelling: A Practical Approach”, Chapman and Hall, London.
Crenshaw, E.M., Robison, K.K. (2006), “Globalization and the Digital Divide: The Roles of Structural Conduciveness and Global Connection in Internet Diffusion”, Social Science Quarterly, 87(1), 190-207.
Davis, F.D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, 13(3), 319-340.
Dekimpe, M.G., Parker, P.M., Sarvary, M. (1998), “Staged Estimation of International Diffusion Models: An Application to Global Cellular Telephone Adoption”, Technological Forecasting & Social Change, 57, 105-132.
DeLone, W.H., McLean, E.R. (1992). “Information System 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 System Success: A Ten-Year Update”, Journal of Management Information Systems, 19(4), 9-30.
deVeer, A., Fleuren, M., Bekkema, N., Francke, A. (2011), “Successful implementation of new technologies in nursing care: a questionnaire survey of nurse-users”, BMC medical informatics and decision making, 11(1), 67. doi:10.1186/1472-6947-11-67
deVeer, A.J., Francke, A.L. (2010), “Attitudes of nursing staff towards electronic patient records: a questionnaire survey”, International journal of nursing studies, 47(7), 846-854.
Diaz, R. Behr, J.G., Tulpule, M. (2012), “A System Dynamics Model for Simulating Ambulatory Health Care Demands. Simulation in Healthcare, 7(4), 243-250.
DOH (2012),“Statistics on NHI Medical Care”, Retrieved Dec 22, 2012, from http://www.doh.gov.tw/EN2006/DM/DM2.aspx?now_fod_list_no=12537&class_no=390&level_no=2
Ess, S.M., Schneeweiss, S., Szucs, T.D. (2003), “European healthcare policies for controlling drug expenditure”, PharmacoEconomics, 21(2), 89-103.
Fishbein, M., Ajzen, I. (1975), “Belief, Attitude, Intention, and Behavior:An Introduction to Theory and Research Reading”, MA: Addison-Wesley.
Ford, A. (1997), “System dynamics and the electronic power industry”, System Dynamics Review, 13(1), 57-85.
Forrester, J.W. (1980), “Information Sources for Modeling the National Economy”, Journal of the American Statistical Association, 75(371), 555-566.
Forrester, J.W. (1961), “Principles of systems”, MA: MIT Press, Cambridge.
Forrester, J.W. (1969), “Urban Dynamics”, MA: MIT Press, Cambridge.
Free C., Phillips, G., Felix, L., Galli, L., Pate, V., Edwards, P. (2010), “The effectiveness of M-health technologies for improving health and health services: a systematic review protocol”, BMC Research Notes, 3(1), 250.
Freeman C. (1986), “The Economics of Industrial Innovation”, 2nd ed., MA: MIT Press, Cambridge.
Gagnon, M.P., Orruno, E., Asua, J., Abdeljelil, A.B., Emparanza, J. (2012), “Using a Modified Technology Acceptance Model to Evaluate Healthcare Professionals’ Adoption of a New Telemonitoring System”, Telemedicine and E-Health, 8(1), 54-59.
Gatignon, H.A., Robertson, T.S. (1985), “A propositional inventory for new diffusion research”, Journal of Consumer Research, 11, 849-867.
Gefen, D., Straub, D.W. (1997), “Gender differences in the perception and use of E-mail: An extension to the technology acceptance model”, MIS Quarterly, 21(4), 389-400.
Groebel, A. (2003), “Should we regulate any aspects of wireless?”, Telecommunications Policy, 27, 435-455.
Gruber, H., Verboven, F. (2001a), “The diffusion of mobile telecommunications services in the European Union”, European Economic Review, 45, 577-588.
Gruber, H., Verboven, F. (2001b). “The Evolution of Markets Under Entry and Standards Regulation: the Case of Global Mobile Telecommunications”, International Journal of Industrial Organization, 19, 1189-1212.
Gupta, R., Jain, K. (2012), “Diffusion of mobile telephony in India: An empirical study”, Technological Forecasting & Social Change, 79, 709-715.
Ha, S., Stoel, L. (2009), “Consumer e-shopping acceptance: Antecedents in a technology acceptance model”, Journal of Business Research, 62(5), 565-571.
Hanafizadeh, M.R., Saghaei, A., Hanafizadeh, P. (2009), “An index for cross-country analysis of ICT infrastructure and access”, Telecommunications Policy 33, 385-405.
Hanson, J., Percival, J., Aldred, H., Brownsell, S., Hawley, M (2007), “Attitudes to telecare among older people, professional care workers and informal carers: a preventative strategy or crisis management?”, Universal Access in the Information Society, 6(2), 193-205.
Harmon, R.R., Cowan, K.R. (2009), “A multiple perspectives view of the market case for green energy”, Technological Forecasting & Social Change, 76, 204-213.
Hebert, M.A., Korabek, B. (2004), “Stakeholder readiness for telehomecare: implications for implementation”, Telemedicine Journal and e-Health, 10(1), 85-92.
Heidenberger, K., Flessa, S. (1993), “A system dynamics model for AIDS policy support in Tanzania”, European Jouranl of operational Research, 70(2), 167-176.
Hekkert, M.P., Suurs, R.A.A., Negro, S.O., Kuhlmann, S., Smits, R.E.H.M. (2007), “Functions of innovation systems: A new approach for analyzing technological change”, Technological Forecasting & Social Change, 74, 413-432.
Hernandez, B., Jimenez, J., Martin, M.J. (2008), “Extending the technology acceptance model to include the IT decision-maker: A study of business management software”, Technovation, 28(3), 112-121.
Homer, J., Hirsch, G., Minniti, M., Pierson, M. (2004), “Models for collaboration: how system dynamics helped a community organize cost-effective care for chronic illness”, System Dynamics Review, 20(3), 199-222.
Horton, K. (2008), “The use of telecare for people with chronic obstructive pulmonary disease: implications for management”, Journal of Nursing Management, 16(2), 173-180.
Hung, S.W., Tsai, J.M. (2012), “Dynamic Diffusion Model for Considering Technological Characteristics and Price Changes: Using LCD TVs as an Example”, Journal of Technology Management, 17(1), 1-26.
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., Zinatelli, N., Cragg, P., Cavaye, A.L.M. (1997), “Personal computing acceptance factors in small firms: A structural equation model”, MIS Quarterly, 279-305.
Im, I., Kim, Y., Han, H.J. (2008), “The effects of perceived risk and technology type on users’acceptance of technologies”, Information & Management, 45(1), 1-9.
Jain, D.C., & Rao, R.C. (1990), “Effect of price on the demand for durable: modeling, estimation and finding”, Journal of Business and Economic Statistics, 8, 163-170.
Kalish, S. (1985), “A new product adoption model with pricing advertising and uncertainty”, Management Science, 31, 1569-1585.
Karahanna, E., Straub, D. W., & Chervany, N. L. (1999), “ Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs”, MIS Quarterly, 23 (2), 183-213.
Kiiski, H., Pohjola, M. (2002), “Cross-country Diffusion of the Internet”, Information Economics and Policy, 14, 297-310.
Kim, B., Han, I. (2011), “The role of utilitarian and hedonic values and their antecedents in a mobile data service environment”, Expert Systems with Applications, 38(3), 2311-2318.
Kim, C., Oh, E., Shin, N., Chae, M. (2009), “An empirical investigation of factors affecting ubiquitous computing use and U-business value”, International Journal of Information Management, 29(6), 436-448.
Kim, D.Y., Park, J., Morrison, A.M. (2008), “A Model of Traveller Acceptance of Mobile Technology”, International Journal of Tourism Research, 10(5), 393-407.
Kohli, R., Lehmann, D.R., Pae, J. (1999), “Extent and impact of incubation time in new product diffusion”, Journal of Product Innovation Management, 16, 134-144.
Lederer, A.L., Maupin, D.J., Sena, M.P., Zhuang, Y.L. (2000), “The technology acceptance model and the World Wide Web”, Decision Support Systems, 29(3), 269-282.
Linstone, H.A. (1999), “Decision Making for Technology Executives: Using Multiple Perspectives to Improved Performance”, Artech House, Boston.
Linstone, H.A. (2003), “The 21st century: everyman as faust-technology, terrorism, and the multiple perspective approach”, Technological Forecasting & Social Change, 70(3), 283-296.
Lyneis, J.M. (2000), “System dynamics for market forecasting and structural analysis”, System Dynamics Review, 16(1), 3-25.
Mackay, M.M., Metcalfe, M. (2002), “Multiple method forecasts for discontinuous innovations”, Technological Forecasting & Social Change, 69, 221-232.
Maglaveras, N, Bonato, P., Tamura, T. (2010), “Guest Editorial Special Section on Personal Health Systems”, IEEE Transactions on Information Technology in Biomedicine, 14(2), 360-363.
Martinez-Moyano, I.J., Conrad, S.H., Andersen, D.F. (2011), “Modeling behavioral considerations related to information security” computers & security, 30, 397-409.
Mason, R.O. (1978), “Measuring Information Output: A Communication Systems Approach. Information Management”, 1(5), 219-234.
Meade N. (1984), “The use of growth curves in forecasting market development – A review and appraisal”, Journal of Forecasting, 3, 429-451.
Meade, N., Islam, T. (2006), “Modelling and forecasting the diffusion of innovation - a 25-year review”, Internal Journal of Forecasting, 22, 519-545.
Miller, E.A. (2007), “Solving the disjuncture between research and practice: Telehealth trends in the 21st century”, Health Policy, 82, 133-141.
Mitchell, V.W. (1999), “Consumer perceived risk: conceptualisations and models”, European Journal of Marketing, 33(1/2),163-195.
Moon, J.W., Kim, Y.G. (2001), “Extending the TAM for a World-Wide-Web context”, Information & Management, 38, 217-230.
Morris, M.G., Dillon, A. (1997), “How user perceptions influence software use”, IEEE software, 14(4), 58-65.
NCC (2012), “Fixed Network Telecommunication Monthly Report”, Retrieved May 20, 2012, from http://www.ncc.gov.tw/english/news_detail.aspx?ite_content_sn =258&is_history=0&pages=0&sn_f=1174
Negash, S., Ryan, T., Igbaria, M. (2003), “Quality and effectiveness in Web-based customer support systems”, Information and Management, 40(8), 757-768.
Pai, F.Y., Huang, K.I. (2011), “Applying the Technology Acceptance Model to the introduction of healthcare information systems”, Technological Forecasting & Social Change, 78, 650-660.
Pal, A., Mbarika, V.W.A., Cobb-Payton, F., Datta, P., McCoy, S. (2005), “Telemedicine diffusion in a developing country: The case of India (March 2004)”, IEEE Transactions on Information Technology in Biomedicine, 9(1), 59-65
Pardue, J.H., Clark, T.D.Jr., Winch, G.W. (1999), “Modeling Short- and Long-term Dynamics in the Commercialization of Technical Advances in IT Producing Industries”, System Dynamic Review, 15(1), 97-105.
Park, Y.S., Han, S.H. (2010), “Touch key design for one-handed thumb interaction with a mobile phone: Effects of touch key size and touch key location”, International Journal of Industrial Ergonomics, 40(1), 68-76.
Peres, R., Muller, E., Mahajan, V. (2010), “Innovation diffusion and new product growth models: A critical review and research directions”, International Journal of Research in Marketing, 27, 91-106.
Petter, S., Fruhling, A. (2011), “Evaluating the success of an emergency response medical information system”, International Journal of Medical Informatics, 80(7), 480-489.
Pitt, L.F., Watson, R.T., Kavan, C.B. (1995), “Service quality: A measure of information systems effectiveness”, MIS Quarterly, 19(2), 173-187.
Quaddus, M., Intrapairot, A. (2001), “Management policies and the diffusion of data warehouse: a case study using system dynamics-based decision support system”, Decision Support System, 31, 223-240.
Riemenschneider, C.K., Hardgrave, B.C. (2001), “Explaining software development tool use with the technology acceptance model”, Journal of Computer Information Systems, 41(4), 1-8.
Roca, J.C., Chiu, C.M., Martínez, F.J. (2006), “Understanding E-Learning Continuance Intention: An Extension of the Technology Acceptance Model”, International Journal of Human -Computer Studies, 64(8), 683-696.
Rogers, E.M. (1995), “Diffusion of Innovation”, 4th ed., New York: The Free Press.
Rogers, E.M. (2003), “Diffusion of innovations”, 5th ed., New York: Free Press.
Rouvinen, P. (2006), “Diffusion of digital mobile telephony: are developing countries different?”, Telecommunications Policy, 30, 46-63.
Ryan, J.J.C.H., Mazzuchi, T.A., Ryan, D.J., Cruz, J.L., Cooke, R. (2012), “Quantifying information security risks using expert judgment elicitation”, Computers & Operations Research, 39, 774-784.
Satsangi, P.S., Mishra, D.S., Gaur, S.K., Singh, B.K. Jain, D.K. (2003), “Systems Dynamics Modelling, Simulation and Optimization of Integrated Urban System: A Soft Computing Approach”, Kybernetes, 32(5/6), 808-817.
Schiff, G.D. (2011), “System Dynamics and Dysfunctionalities: Levers for Overcoming Emergency Department Overcrowding”, Academic Emergency Medicine, 18(12), 1255-1261.
Senge, P.M. (1990), “The Fifth Discipline: The Art and practice of Learning Organization”, Currency Dubleday, New York.
Sethi, S.P., Prasad, A., & He, X. (2008), “Optimal advertising and pricing in a new-product adoption model”, Journal of Optimization Theory and Applications, 139, 351-360.
Shannon, C.E., Weaver, W. (1949), “The mathematical theory of communication”, University of Illinois Press, Urbana, Illinois.
Staller, K.M. (2004), “Runaway Youth System Dynamics: A Theoretical Framework for Analyzing Runaway and Homeless Youth Policy”, Families in Society, 85(3), 379-390.
Sterman, J.D. (2000), “Business Dynamics”, McGraw-Hill, New York.
Subramanian, G.H. (1994), "A replication of perceived usefulness and perceived ease of use measurement", Decision Sciences, 25(5/6), 863-873.
Swami, S., & Khairnar, P.J. (2006), “Optimal normative policies for marketing of products with limited availability”, Annals of Operations Research, 143, 107-121.
UN Population Division of the Department of Economic and Social Affairs (2010), “World Population Prospects: The 2010 Revision”, Retrieved May 1, 2013, from http://esa.un.org/unpd/wpp/Documentation/publications.htm
Venkatesh, V. (2000), “Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model”, Information System Research, 11(4), 342-365.
Venkatesh, V., Bala, H. (2008), "Technology Acceptance Model 3 and a Research Agenda on Interventions", Decision Sciences, 39(2), 273-315.
Venkatesh, V., Davis, F.D. (1996), “A model of the antecedents of perceived ease of use: Development and test”, Decision Sciences, 27(3), 451-481.
Venkatesh, V., Morris, M.G.; Davis, G.B.; Davis, F.D. (2003), "User acceptance of information technology: Toward a unified view", MIS Quarterly 27(3): 425-478.
Wang, Y.S. (2008), “Assessing e-commerce systems success: a respecification and validation of the DeLone and McLean model of IS success”, Information Systems Journal, 18(5), 529-557.
WHO (2012), “Connecting and caring: innovations for healthy ageing”, Retrieved August 8, 2012, from http://www.who.int/bulletin/volumes/90/3/12-020312/ en/index.html
Xue, Y., Liang, H. (2007), “Analysis of telemedicine diffusion: The case of China. IEEE Transactions on Information Technology in Biomedicine, 11(2), 231-233.
Yoon, C., Kim, S. (2009), “Developing the Causal Model of Online Store Success”, Journal of Organizational Computing and Electronic Commerce, 19(4), 265-284.
指導教授 洪秀婉(Shiu-Wan Hung) 審核日期 2013-7-16
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