過去的十年間，敏捷軟體開發已漸成主流，它以更快速、更精簡的方式產出有品質的軟體。軟體公司紛紛轉進敏捷軟體開發，此風潮仍顯著，這也是本論文研究此領域的起因。近年來，探討敏捷軟體開發的學術文獻有著顯注增長，本論文第一項研究即針對在2001至2012年間，發表於SCI學術期刊中有關敏捷軟體開發的221篇文獻進行探索及分析，並彙整成資料庫以利後續研究使用。第一項研究中首先發現一群核心的敏捷軟體開發研究者，他們深耕此領域多年，後進可先從他們的研究脈絡中找到新的研究方向，同時並發現在2008年後有著為數較多的文獻開始探討採用敏捷軟體開發模型後的研究，而這也引發了本論文的第二項研究：軟體公司在轉型至敏捷開發過程中各階段的策略考量因素為何？為數不少的研究針對轉型策略提出框架，然僅少數研究從組織在各個不同階段，所採取的轉型策略，進行長時間的研究。本文第二項研究即透過個案的方式，研究一間上市軟體公司在2007至2013年間導入、轉型至敏捷軟體開發過程中，組織在各個不同階段所採用的策略、方針與決策因子進行研究。此項研究發現組織轉型過程中可以分成四個階段，逐步轉型，而非一次到位，並發現採用的策略需將其影響的層級是組織文化、組織結構或僅是實踐方法納入考量。敏捷軟體開發廣泛的被認為具備提高開發團隊生產力的能力，但有鑒於敏捷實踐方式各異，而敏捷團隊在決策改善生產力重要因素時的困難度頗高，由此引發本文第三項研究：影響敏捷開發團隊生產力的重要因素為何？有沒有一個結構化的決策模型可界定、找出最重要且需改善的重要因素。在體認各敏捷團隊決策的異質性，本文第三項研究採多準則決策模型用以構建客觀、有效的分析決策方法。我們由文獻探索中擷取分佈在四個維度中影響敏捷軟體開發團隊生產力的十項關鍵因素，透過多準則決策過程將所有重要因素依優先順序排出，決策者即可將80%的時間花在改善最重要的20%因素。本論文研究可提供組織在未來在導入敏捷軟體開發和改善敏捷軟體研發團隊生產力時的參考。

Agile software development (ASD) has taken the place of the traditional plan-driven software development approach over the past decades and has become more popular and mainstream in the improved, faster, and cheaper delivery of quality software. Transitioning to the agile style of software development has become an inexorable phenomenon among software companies. Framed by this context, we conduct a series of research on agile methodologies. In recent years, the number of scholarly publications on ASD has grown significantly. Study 1 conducted here presents findings on top scholars and publications in the ASD field from 2001 to 2012 based on 221 publications in the Science Citation Index journals. It summarizes the most influential researchers and finds a steady stream of studies on post-adoption after 2008. This leads to the further study of the key initiatives and strategic decisions during agile transition. Numerous studies have reviewed and synthesized the frameworks adopted in transitioning to agile. However, few works have examined how an organization transitions to agile through longitudinal study and from a strategic perspective.
Transitioning to ASD as a significant organizational initiative is a strategic decision that should be made in connection with the target organization’s key objectives. A dependable anticipation of how a new methodology is likely to affect strategic objectives helps organization managers select the methodology that maximizes the benefits provided to the organization. Study 2 conducted here presents findings on the initiatives, strategic decisions, and approaches of a Fortune 500 company that transitioned to agile from 2007 to 2013. Moreover, the transition occurred in four phases and considered the impacts on culture, structure, and practice. Agile methods are widely believed to potentially improve the productivity of the software development team. Given the variety of agile practices, agile teams face difficulty in the decision-making process. Study 3 conducted here proposes a multiple criteria decision-making approach to the construction of an objective and effective analytical model of the critical factors that influence agile team productivity. We synthesize ten influential productivity factors across four dimensions from empirical studies. The decision-making process prioritizes the factors so that the decision maker can adopt the Pareto approach: focusing on the 20% strategies that bring 80% of the gain. This thesis can serve as a comprehensive reference for practitioners transitioning to agile or enhancing agile team productivity.

References
1. MacCormack, A., Product-development practices that work: How internet companies build software. MIT Sloan Management Review 2001. 42(2): p. 75-84.
2. Swink, M., S. Talluri, and T. Pandejpong, Faster, better, cheaper: A study of NPD project efficiency and performance tradeoffs. Journal of Operations Management, 2006. 24(5): p. 542-562.
3. Harter, D.E., M.S. Krishnan, and S.A. Slaughter, Effects of process maturity on quality, cycle time, and effort in software product development. Management Science, 2000. 46(4): p. 451-466.
4. Royce, W.W. Managing the development of large software systems: concepts and techniques. in Proceedings: IEEE WESCON. 1970.
5. Baskerville, R., et al., Is Internet-speed software development different? Ieee Software, 2003. 20(6): p. 70-77.
6. De Cesare, S., et al., Examining perceptions of agility in software development practice. Communications of the ACM, 2010. 53(6): p. 126-130.
7. !!! INVALID CITATION !!!
8. Charette, R.N., Why software fails. IEEE Spectrum, 2005. 42(9): p. 42-49.
9. Whittaker, B., What went wrong? Unsuccessful information technology projects. Information Management and Computer Security, 1999. 7(1): p. 23-30.
10. Green, P., Measuring the Impact of Scrum on Product Development at Adobe Systems, in System Sciences (HICSS), 2011 44th Hawaii International Conference on. 2011: Kauai, HI. p. 1-10.
11. Striebeck, M. Ssh! We are adding a process...[agile practices]. in Agile Conference, 2006. 2006. IEEE.
12. Sanchez, J.C., L. Williams, and E.M. Maximilien, On the sustained use of a test-driven development practice at IBM, in AGILE 2007. 2007: Washington, DC.
13. Begel, A. and N. Nagappan, Usage and Perceptions of Agile Software Development in an Industrial Context: An Exploratory Study, in Empirical Software Engineering and Measurement, 2007. ESEM 2007. First International Symposium on 2007: Madrid. p. 255-264.
14. Bowers, P., Highpoints from the agile software development forum. Crosstalk, 2002: p. 26-27.
15. Benefield, G. Rolling out agile in a large enterprise. in Hawaii International Conference on System Sciences, Proceedings of the 41st Annual. 2008. IEEE.
16. Qumer, A. and B. Henderson-Sellers, A framework to support the evaluation, adoption and improvement of agile methods in practice. Journal of Systems and Software, 2008. 81(11): p. 1899-1919.
17. Reifer, D.J., How good are agile methods? Ieee Software, 2002. 19(4): p. 16-18.
18. Dyba, T. and T. Dingsoyr, Empirical studies of agile software development: A systematic review. Information and Software Technology, 2008. 50(9-10): p. 833-859.
19. Beck, K., et al. Manifesto for Agile Software Development. 2001 [cited 2011 December]; Available from: http://agilemanifesto.org/.
20. Abrahamsson, P., et al. Agile software development methods review and analysis. 2002. 3-107.
21. Cohen, D., M. Lindvall, and P. Costa, An introduction to agile methods, in Advances in Computers. 2004, Elsevier Academic Press Inc: San Diego. p. 1-66.
22. Erickson, J., K. Lyytinen, and K. Siau, Agile modeling, agile software development, and extreme programming: The state of research. Journal of Database Management, 2005. 16(4): p. 88-100.
23. Williams, L., Agile Software Development Methodologies and Practices, in Advances in Computers, Vol 80. 2010, Elsevier Academic Press Inc: San Diego. p. 1-44.
24. Williams, L. and A. Cockburn, Agile software development: It's about feedback and change [Special issue]. Computer, 2003. 36(6): p. 39-85.
25. Siau, K., Agile Information Systems Development - A retrospective review of JDM from 2003 to 2005 and a discussion on publication emphasis of JDM for the next two to three years [Special issue]. Journal of Database Management, 2005. 16(4): p. 1-99.
26. Damiani, E., M. Marchesi, and G. Succi, Agile methodologies for software production - Preface [Special issue]. Journal of Systems Architecture, 2006. 52(11): p. 609-707.
27. Abrahamsson, P., K. Conboy, and X.F. Wang, 'Lots done, more to do': the current state of agile systems development research [Special issue]. European Journal of Information Systems, 2009. 18(4): p. 281-383.
28. Greer, D. and Y. Hamon, Agile Software Development [Special issue]. Software-Practice & Experience, 2011. 41(9): p. 943-996.
29. Dyba, T., Special Section on Best Papers from XP2010 [Special section]. Information and Software Technology, 2011. 53(5): p. 507-508.
30. Chua, C., et al., Measuring Researcher-Production in Information Systems. Journal of the Association for Information Systems, 2002. 3(1).
31. Glass, R.L. and T.Y. Chen, An assessment of systems and software engineering scholars and institutions (1999-2003). Journal of Systems and Software, 2005. 76(1): p. 91-97.
32. Inkpen, A.C. and P.W. Beamish, An Analysis of Twenty-Five Years of Research in the Journal of International Business Studies. Journal of International Business Studies, 1994. 25(4): p. 703-713.
33. Zou, S.M., Contributions to international advertising research - An assessment of the literature between 1990 and 2002 Journal of Advertising, 2005. 34(1): p. 99-110.
34. Jones, A., Some thoughts and reflections on authorship. Alcohol and Alcoholism, 1996. 31(1): p. 11-15.
35. DuBois, F.L. and D. Reeb, Ranking the international business journals. Journal of International Business Studies, 2000. 31(4): p. 689-704.
36. Meho, L.I. and C.R. Sugimoto, Assessing the Scholarly Impact of Information Studies: A Tale of Two Citation Databases-Scopus and Web of Science. Journal of the American Society for Information Science and Technology, 2009. 60(12): p. 2499-2508.
37. Shull, F., et al., What Do We Know about Test-Driven Development? Ieee Software, 2010. 27(6): p. 16-19.
38. Holmstrom, H., et al., Agile practices reduce distance in global software development. Information Systems Management, 2006. 25(3): p. 7-18.
39. Eisenhardt, K. and M. Graebner, Theory building from cases: opportunities and challenges. Academy of Management Journal, 2007. 50(1).
40. Conboy, K., Agility from first principles: Reconstructing the concept of agility in information systems development. Information Systems Research, 2009. 20(3): p. 329-354.
41. Hoda, R., J. Noble, and S. Marshall, Developing a grounded theory to explain the practices of self-organizing Agile teams. Empirical Software Engineering, 2012. 17(6): p. 609-639.
42. Gu, Y., Global knowledge management research: A bibliometric analysis. Scientometrics, 2004. 61(2): p. 171-190.
43. Williams, L. Realsearch - Software Engineering at NCSU. [cited 2014 February]; Available from: http://www.realsearchgroup.org/realsearch/.
44. Highsmith, J. and A. Cockburn, Agile software development: The business of innovation. Computer, 2001. 34(9): p. 120-122.
45. Boehm, B., Get ready for agile methods, with care. Computer, 2002. 35(1): p. 64-+.
46. Nerur, S., R. Mahapatra, and G. Mangalaraj, Challenges of migrating to agile methodologies. Communications of the Acm, 2005. 48(5): p. 72-78.
47. Chow, T. and D.B. Cao, A survey study of critical success factors in agile software projects. Journal of Systems and Software, 2008. 81(6): p. 961-971.
48. Boehm, B. and R. Turner, Management challanges to implementing Agile Processes in traditional development organizations. Ieee Software, 2005. 22(5): p. 30-39.
49. Erdogmus, H., M. Morisio, and M. Torchiano, On the effectiveness of the test-first approach to programming. Ieee Transactions on Software Engineering, 2005. 31(3): p. 226-237.
50. George, B. and L. Williams, A structured experiment of test-driven development. Information and Software Technology, 2004. 46(5): p. 337-342.
51. Janzen, D. and H. Saiedian, Test-driven development: Concepts, taxonomy, and future direction. Computer, 2005. 38(9): p. 43-+.
52. Arisholm, E., et al., Evaluating pair programming with respect to system complexity and programmer expertise. Ieee Transactions on Software Engineering, 2007. 33(2): p. 65-86.
53. Layman, L., et al., Essential communication practices for Extreme Programming in a global software development team. Information and Software Technology, 2006. 48(9): p. 781-794.
54. Paulk, M.C., Extreme programming from a CMM perspective. Ieee Software, 2001. 18(6): p. 19-26.
55. Olague, H.M., et al., Empirical validation of three software metrics suites to predict fault-proneness of object-oriented classes developed using highly iterative or agile software development processes. Ieee Transactions on Software Engineering, 2007. 33(6): p. 402-419.
56. Turk, D., R. France, and B. Rumpe, Assumptions underlying agile software-development processes. Journal of Database Management, 2005. 16(4): p. 62-87.
57. Larman, C. and V.R. Basili, Iterative and incremental development: A brief history. Computer, 2003. 36(6): p. 47-+.
58. Fitzgerald, B., G. Hartnett, and K. Conboy, Customising agile methods to software practices at Intel Shannon. European Journal of Information Systems, 2006. 15(2): p. 200-213.
59. Alshayeb, M. and W. Li, An empirical validation of object-oriented metrics in two different iterative software processes. Ieee Transactions on Software Engineering, 2003. 29(11): p. 1043-1049.
60. Ramesh, B., et al., Can distributed software development be agile? Communications of the Acm, 2006. 49(10): p. 41-46.
61. Sharp, H. and H. Robinson, An ethnographic study of XP practice. Empirical Software Engineering, 2004. 9(4): p. 353-375.
62. Nerur, S. and V. Balijepally, Theoretical reflections on agile development methodologies - The traditional goal of optimization and control is making way for learning and innovation. Communications of the Acm, 2007. 50(3): p. 79-83.
63. Cao, L., et al., A framework for adapting agile development methodologies. European Journal of Information Systems, 2009. 18(4): p. 332-343.
64. Lee, S. and H.S. Yong, Agile Software Development Framework in a Small Project Environment. Journal of Information Processing Systems, 2013. 9(1): p. 69-88.
65. Chuang, S.-W., T. Luor, and H.-P. Lu, Assessment of institutions, scholars, and contributions on agile software development (2001–2012). Journal of Systems and Software, 2014. 93: p. 84-101.
66. Baskerville, R., J. Pries-Heje, and S. Madsen, Post-agility: What follows a decade of agility? Information and Software Technology, 2011. 53(5): p. 543-555.
67. Narula, R., Technology, international business and Porter's" diamond": Synthesizing a dynamic competitive development model. MIR: Management International Review, 1993: p. 85-107.
68. Kitchenham, B., L. Pickard, and S.L. Pfleeger, CASE-STUDIES FOR METHOD AND TOOL EVALUATION. Ieee Software, 1995. 12(4): p. 52-62.
69. Zelkowitz, M.V., An update to experimental models for validating computer technology. Journal of Systems and Software, 2009. 82(3): p. 373-376.
70. Highsmith, J. and R.K. Wysocki How agile are organizations today? 2006. 7.
71. Wilson, N., Best Practices in Transitioning to Agile: The Pilot Project. 2012: Gartner Inc.
72. Cockburn, A. and J. Highsmith, Agile software development: The people factor. Computer, 2001. 34(11): p. 131-133.
73. Iivari, J. and N. Iivari, The relationship between organizational culture and the deployment of agile methods. Information and Software Technology, 2011. 53(5): p. 509-520.
74. West, D. and T. Grant Agile Development: Mainstream Adoption Has Changed Agility. 2010.
75. Royce, W.W., Managing the development of large software systems: concepts and techniques. IEEE WESCON, 1970: p. 328-339.
76. Moe, N.B., T. Dingsoyr, and T. Dyba, A teamwork model for understanding an agile team: A case study of a Scrum project. Information and Software Technology, 2010. 52(5): p. 480-491.
77. Beck, K., Extreme Programming Explained. 1999.
78. Trendowicz, A. and J. Munch, Factors Influencing Software Development Productivity - State-of-the-Art and Industrial Experiences, in Advances in Computers, Vol 77, M.V. Zelkowitz, Editor. 2009, Elsevier Academic Press Inc: San Diego. p. 185-241.
79. Melo, C.O., et al., Interpretative case studies on agile team productivity and management. Information and Software Technology, 2013. 55(2): p. 412-427.
80. Melo, C.O., et al. Agile team perceptions of productivity factors. in Agile Conference (AGILE), 2011. 2011. IEEE.
81. Melo, C.O. and F. Kon, Empirical Evaluation of Agile Practices Impact on Team Productivity, in Agile Processes in Software Engineering and Extreme Programming, A. Sillitti, et al., Editors. 2011. p. 322-323.
82. Sfetsos, P., et al., An experimental investigation of personality types impact on pair effectiveness in pair programming. Empirical Software Engineering, 2009. 14(2): p. 187-226.
83. Finnie, G.R., G.E. Wittig, and D.I. Petkov, Prioritizing software development productivity factors using the analytic hierarchy process. Journal of Systems and Software, 1993. 22(2): p. 129-139.
84. Esfahani, H.C., E. Yu, and M.C. Annosi. Towards the Strategic Analysis of Agile Practices. in CAiSE Forum. 2011.
85. Balijepally, V., et al., ARE TWO HEADS BETTER THAN ONE FOR SOFTWARE DEVELOPMENT? THE PRODUCTIVITY PARADOX OF PAIR PROGRAMMING. Mis Quarterly, 2009. 33(1): p. 91-118.
86. Layman, L., L. Williams, and L. Cunningham, Motivations and measurements in an agile case study. Journal of Systems Architecture, 2006. 52(11): p. 654-667.
87. Maurer, F. and S. Martel, Extreme programming - Rapid development for Web-based applications. Ieee Internet Computing, 2002. 6(1): p. 86-90.
88. Parrish, A., et al., A field study of developer pairs: Productivity impacts and implications. Ieee Software, 2004. 21(5): p. 76-79.
89. Choi, K.S., F.P. Deek, and I. Im, Exploring the underlying aspects of pair programming: The impact of personality. Information and Software Technology, 2008. 50(11): p. 1114-1126.
90. Moser, R., et al., A case study on the impact of refactoring on quality and productivity in an agile team, in Balancing Agility and Formalism in Software Engineering, B. Meyer, J.R. Nawrocki, and B. Walter, Editors. 2008. p. 252-266.
91. Marchenko, A., P. Abrahamsson, and T. Ihme, Long-term effects of test-driven development A case study, in 10th International Conference on Agile Processes in Software Engineering and Extreme Programming, XP 2009. 2009, Springer Verlag: Pula, Sardinia. p. 13-22.
92. Ribeiro, M.B., R.M. Czekster, and T. Webber, Improving productivity of local software development teams in a global software development environment. 2006 Ieee International Conference on Global Software Engineering, Proceedings. 2006. 253-254.
93. Parker, D.W., M. Holesgrove, and R. Pathak, Improving productivity with self-organised teams and agile leadership. International Journal of Productivity and Performance Management, 2015. 64(1): p. 112-128.
94. Sutherland, J., N. Harrison, and J. Riddle. Teams that finish early accelerate faster: A pattern language for high performing scrum teams. in 47th Hawaii International Conference on System Sciences, HICSS 2014. 2014. Waikoloa, HI: IEEE Computer Society.
95. Layman, L., L. Williams, and L. Cunningham. Exploring extreme programming in context: An industrial case study. in Proceedings of the Agile Development Conference, ADC 2004. 2004. Salt Lake City, UT.
96. Misra, S.C., V. Kumar, and U. Kumar, Identifying some important success factors in adopting agile software development practices. Journal of Systems and Software, 2009. 82(11): p. 1869-1890.
97. Maxwell, K.D., L. VanWassenhove, and S. Dutta, Software development productivity of European space, military, and industrial applications. Ieee Transactions on Software Engineering, 1996. 22(10): p. 706-718.
98. Wagner, S. and M. Ruhe, A structured review of productivity factors in software development. Institut für Informatik-Technische Universität München, Tech. Rep. Technical Report TUMI0832, 2008.
99. De Barros Sampaio, S.C., et al. A review of productivity factors and strategies on software development. in Proceedings - 5th International Conference on Software Engineering Advances, ICSEA 2010. 2010.
100. Huijgens, H. and R. van Solingen, Measuring Best-in-Class Software Releases. 2013 Joint Conference of the 23rd International Workshop on Software Measurement and the 2013 Eighth International Conference on Software Process and Product Measurement (Iwsm-Mensura), 2013: p. 137-146.
101. Lee, G. and W. Xia, TOWARD AGILE: AN INTEGRATED ANALYSIS OF QUANTITATIVE AND QUALITATIVE FIELD DATA ON SOFTWARE DEVELOPMENT AGILITY. Mis Quarterly, 2010. 34(1): p. 87-114.
102. Hannay, J.E., et al., Effects of Personality on Pair Programming. Ieee Transactions on Software Engineering, 2010. 36(1): p. 61-80.
103. Mundra, A., S. Misra, and C.A. Dhawale, Practical Scrum-Scrum Team: Way to Produce Successful and Quality Software. Proceedings of the 2013 13th International Conference on Computational Science and Its Applications (Iccsa 2013), 2013: p. 119-123.
104. Santos, V., et al., The Influence of Organizational Factors on Inter-team Knowledge Sharing Effectiveness in Agile Environments. 2014 47th Hawaii International Conference on System Sciences (Hicss), 2014: p. 4729-4738.
105. Athanasiou, D., et al., Test Code Quality and Its Relation to Issue Handling Performance. Ieee Transactions on Software Engineering, 2014. 40(11): p. 1100-1125.
106. Wu, H.Y., et al., Exploring the critical influential factors of creativity for college students: A multiple criteria decision-making approach. Thinking Skills and Creativity, 2014. 11: p. 1-21.
107. Hicdurmaz, M., A Fuzzy Multi Criteria Decision Making Approach to Software Life Cycle Model Selection. 2012 38th Euromicro Conference on Software Engineering and Advanced Applications (Seaa), 2012: p. 384-391.
108. Athanasopoulos, G., C.R. Riba, and C. Athanasopoulou, A decision support system for coating selection based on fuzzy logic and multi-criteria decision making. Expert Systems with Applications, 2009. 36(8): p. 10848-10853.
109. Mardani, A., A. Jusoh, and E.K. Zavadskas, Fuzzy multiple criteria decision-making techniques and applications–Two decades review from 1994 to 2014. Expert Systems with Applications, 2015.
110. Hsieh, T.Y., S.T. Lu, and G.H. Tzeng, Fuzzy MCDM approach for planning and design tenders selection in public office buildings. International Journal of Project Management, 2004. 22(7): p. 573-584.
111. Satty, T.L., The analytic hierarchy process. 1980, New York: McGraw-Hill New York.
112. Dingsoyr, T., T. Dyba, and P. Abrahamsson. A preliminary roadmap for empirical research on agile software development. in AGILE conference. 2008.
113. Dingsoyr, T., et al., A decade of agile methodologies: Towards explaining agile software development. Journal of Systems and Software, 2012. 85(6): p. 1213-1221.
114. Freudenberg, S. and H. Sharp, Currents Trends, People, Projects The Top 10 Burning Research Questions from Practitioners. Ieee Software, 2010. 27(5): p. 8-9.