簡易檢索 / 詳目顯示

回結果列表
研究生： 林易昇
Lin, Yi-Sheng
論文名稱： 商業分析於敏捷管理之契合度及應用：以電商產業為例
Analyzing the application and fit of agile project management in business analytics: The Case of E-commerce Industry
指導教授： 謝英哲
Hsieh, Ying-Che
口試委員: 翁晶晶
Weng, Jing-jing
李昕潔
Lee, Sin-jie
學位類別： 碩士
Master
系所名稱： 科技管理學院 - 國際專業管理碩士班
International Master of Business Administration(IMBA)
論文出版年： 2021
畢業學年度： 109
語文別： 英文
論文頁數： 76
中文關鍵詞： 敏捷管理 、電子商務 、商業分析 、商業智慧 、資料視覺化
外文關鍵詞： Agile Project Management, E-Commerce, Business Analytics, Business Intelligence, Data Visualization
相關次數： 點閱：3  下載：0 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

    • N/A

    Business analytics has been a buzzword in recent years. The business analytics field in Taiwan has started to grow but not fully implemented to most of the industry. In coordination of the way business is conducted nowadays and the explosion growth of data production, Taiwan has gradually step into global market regardless of global enterprise or startup. Therefore, to manage the business and dig into potential market, business analytics is an unavoidable trend that each firm are willing to devote into it.
    This research aims at analyzing the current application of business analytics in the e-commerce industry. It is a qualitative research to identify both the internal and external factor that will affect business analytics projects. Additionally, since agile has been applied and is mature in most of companies in Taiwan. This research will help evaluate the fitness of agile method and business analytics to provide a reference for companies.
    The result of the research reveal that there are three main challenges firms need to overcome before conduct BA projects in agile way. However, there are still some flexibility for firm to adjust according to different situation. By following the guideline, a better practice of business analytics project can be expected.

    ABSTRACT..........................................................................................................................I ACKNOWLEDGEMENT...................................................................................................II TABLE OF CONTENTS...................................................................................................III CHAPTER 1 INTRODUCTION..........................................................................................1 1.1 Research Background and Motivation...................................................................1 1.2 Research Objectives...............................................................................................3 1.3 Research Questions................................................................................................4 CHAPTER 2 LITERATURE REVIEW...............................................................................5 2.1 Business Analytics..................................................................................................5 2.1.1 Business Intelligence...................................................................................5 2.1.2 Big Data......................................................................................................7 2.2 Project Management ............................................................................................10 2.2.1 Traditional Project Management..............................................................12 2.2.2 Modern Project Management....................................................................14 CHAPTER 3 METHODOLOGY.......................................................................................19 3.1 Methodology Design............................................................................................19 3.2 Data Collection.....................................................................................................21 3.2.1 Data Analyzing…..….................................................................................22 3.3 Interview...............................................................................................................25 3.3.1 Interview Introduction...............................................................................25 3.3.2 Interview Design........................................................................................26 3.3.3 Interview Questions...................................................................................26 3.3.4 Interviewee Profile....................................................................................28 CHAPTER 4 BUSINESS INTELLIGENCE & ANALYTICS..........................................29 4.1 BI&A Framework and Introduction.....................................................................29 4.2 Business Intelligence and Data Analytics............................................................32 CHAPTER 5 BUSINESS ANALYTICS AND AGILE IN E-COMMERCE.....................36 5.1 Business Analytics in the E-commerce Environment..........................................36 5.2 Business Analytics Application in E-commerce..................................................37 5.3 Value of Business Analytics for E-commerce......................................................39 5.4 Value of Agile on E-commerce.............................................................................45 CHAPTER 6 RESULTS AND DISCUSSIONS.................................................................50 CHAPTER 7 CONCLUSIONS AND LIMITATIONS......................................................65 7.1 Major Findings.............................................................................................................65 7.2 Limitations and Future Research..................................................................................66 REFERENCE ....................................................................................................................69

    1. Anastasia Griva, Cleopatra Bardaki, Katerina Pramatari, Dimitris Papakiriakopoulos (2018). Retail business analytics: Customer visit segmentation using market basket data. Expert Systems with Applications Vol. 100, pp. 1-16
    2. Anjali Grupta (2014). E-commerce: Role of e-commerce in today’s business. International Journal of Computing and Corporate Research. ISSN: 2249-054X. Vol. 4.
    3. Amir Gandomi, Murtaza Haider (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management Vol. 35, Issue 2, Pages 137-144
    4. Beath, C., Becerra-Fernandez, I., Ross, J., & Short, J. (2012). Finding value in the information explosion. MIT Sloan Management Review, 53, 18–20.
    5. Bergen Adair (2018). Business Intelligence vs Business Analytics: A Comparison of the Difference Between Them, SelectHub. Available at: https://www.selecthub.com/business-intelligence/business-intelligence-vs-business-analytics/
    6. BluEnt (2018). Why Agile Methodology is Perfect For the eCommerce Industry, BluEnt. Available at: https://www.bluent.net/blog/why-agile-methodology-is-perfect-for-the-ecommerce-industry
    7. Chin, G.: Agile Project Management: How to Succeed in the Face of Changing Project Requirements. AMACOM, New York (2004)
    8. Chow, T., Cao, D.-B.: A survey study of critical success factors in agile software projects. J. Syst. Softw. 81, 961–971 (2008)
    9. Columbus, L. (2014). Making analytics accountable: 56 % Of executives expect analytics to contribute To 10 % Or more growth in 2014. Forbes. Available at: http://www.forbes.com/sites/louiscolumbus/2014/12/10/making-analytics-accountable-56-of-executives-expect-analytics-to-contribute-to-10-or-more-growth-in-2014/#761c65a95b56 (Accessed on the 2nd of February, 2016).
    10. Davenport, T. H. (2006). Competing on Analytics. Harvard Business Review, 84, 98–107.
    11. Davenport, T.H., Harris, J.G., (2007b). The dark side of customer analytics. Harvard Business Review 85, 37 − +.
    12. Davenport, T.H., 2012. The Human Side of Big Data and High-Performance Analytics. International Institute for Analytics, pp. 1–13.
    13. Gangwar, H., 2020. Big Data Analytics Usage and Business Performance: Integrating the Technology Acceptance Model (TAM) and Task Technology Fit (TTF) Model. The Electronic Journal of Information Systems Evaluation, 23(1), pp. 45-64
    14. Gartner (2021). Big Data. Available at: https://www.gartner.com/en/information-technology/glossary/big-data
    15. Gunasekaran, Angappa and Yusuf, Yahaya Y. and Adeleye, Ezekiel O. and Papadopoulos, Thanos (2017). Agile Manufacturing Practices: The Role of Big Data and Business Analytics with Multiple Case Studies. International Journal of Production Research . pp. 1-13.
    16. Hass, K.B.: The blending of traditional and agile project management. PM World Today 9, 1–8 (2007)
    17. He, Xin James (2014) "Business Intelligence and Big Data Analytics: An Overview," Communications of the IIMA: Vol. 14 : Iss. 3 , Article 1. Available at: https://scholarworks.lib.csusb.edu/ciima/vol14/iss3/1
    18. Hsinchun Chen, Roger H. L. Chiang and Veda C. Storey, (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly Vol. 36, No. 4, pp. 1165-1188
    19. IBM, (2012). What is big data? Available at: http://www-01.ibm.com/software/data/bigdata/what-is-big-data.html (Accessed 2nd of March, 2016).
    20. Jackson, M.B.: Agile: a decade in. Project Management Institute (2012)
    21. Jewels, Tony J. and Timbrell, Greg T., "Towards a definition of B2C & B2B e-commerce" (2001). ACIS 2001 Proceedings. 56.
    22. Kasey Panetta (2021). Gartner Top 10 Data and Analytics Trends for 2021. Gartner. Available at: https://www.gartner.com/smarterwithgartner/gartner-top-10-data-and-analytics-trends-for-2021/
    23. Kauffman, R. J., Srivastava, J., & Vayghan, J. (2012). Business and data analytics: new innovations for the management of E-commerce. Electronic Commerce Research and Applications, 11, 85–88.
    24. Ken Schwaber, Jeff Sutherland (2020). The Scrum Guide.
    25. Kidd, P.T., Karwowski, W.: Advances in Agile Manufacturing: Integrating Technology, Organization and People. IOS Press, Amsterdam, Washington, DC (1994)
    26. Kira Carr (2017). Agile Project Management Vs. Traditional Project Management, Knowledgehut. Available at: https://www.knowledgehut.com/blog/agile/agile-project-management-vs-traditional-project-management
    27. Kiron, D., Shockley, R., Kruschwitz, N., Finch, G., & Haydock, M. (2012b). Analytics: the widening divide. MIT Sloan Management Review, 53, 1–22.
    28. Koutsabasis, P., Stavrakis, M., Viorres, N., Darzentas, J. S., Spyrou, T., & Darzentas, J. (2008). A descriptive reference framework for the personalisation of e-business applications. Electronic Commerce Research, 8, 173–192.
    29. Kopp, M., (2013). Seizing the big data opportunity, Ecommerce Times. Available at: http://www.ecommercetimes.com/story/78390.html (Accessed 2nd of March, 2016).
    30. Kung, D. S., Gordon, L. C., Lin, F., Shayo, C., & Dyck, H. (2013). 2013. IT-based System with Dynamic Pricing Algorithm. Business Journal for Entrepreneurs: Business Analytics.
    31. Liebowitz, J. (2013). Big data and business analytics. Boca Raton: CRC Press.
    32. Lisa A. Guion, David C. Diehl, and Debra McDonald (2011). Conducting an In-depth Interview. UF Department of Family Youth and Community Sciences.
    33. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., Byers, A.H., (2011). Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute.
    34. Mehra, G., (2013). 6 uses of big data for online retailers, Practical Ecommerce. Available at: http://www.practicalecommerce.com/ articles/3960-6-Uses-of-Big-Data-for-Online-Retailers (Accessed 2nd of March, 2016).
    35. Miller, G., (2013). 6 ways To use “big data” To increase operating mar- gins By 60 %. Available at: http://upstreamcommerce.com/blog/2012/04/11/6-ways-big-data-increase-operating-margins-60-part-2 (Accessed 2nd of March, 16).
    36. Nerur, S., Mahapatra, R., Mangalaraj, G.: Challenges of migrating to agile methodologies. Commun. ACM 48, 72–78 (2005)
    37. Phillips-Wren, Gloria; Iyer, Lakshmi S.; Kulkarni, Uday; and Ariyachandra, Thilini (2015) "Business Analytics in the Context of Big Data: A Roadmap for Research," Communications of the Association for Information Systems: Vol. 37 , Article 23.
    38. PMI: a guide to the project management body of knowledge (PMBOK guide). Project Management Institute, Inc., Newtown Square, PA (2012)
    39. Richard Vidgen,Sarah Shaw, David B.Grant (2017). Management challenges in creating value from business analytics. European Journal of Operational Research Vol. 261, Issue 2, Pages 626-639
    40. Saynisch, M.: Mastering complexity and changes in projects, economy, and society via project management second order (PM-2). Proj. Manage. J. 41, 4–20 (2010)
    41. Shahriar Akter, Samuel Fosso Wamba (2016). Big data analytics in E-commerce: a systematic review and agenda for future research. Electron Markets 26:173–194
    42. Shanks, Graeme; Bekmamedov, Nargiza; and Sharma, Rajeev: Creating value from business analytics systems: a process-oriented theoretical framework and case study 2011. Available at: https://ro.uow.edu.au/infopapers/3853
    43. Sherehiy, B., Karwowski, W., Layer, J.K.: A review of enterprise agility: concepts, frameworks, and attributes. Int. J. Ind. Ergon. 37, 445–460 (2007)
    44. Sliger, M. (2011). Agile project management with Scrum. Paper presented at PMI® Global Congress 2011—North America, Dallas, TX. Newtown Square, PA: Project Management Institute.
    45. Stare, A.: Agile project management–a future approach to the management of projects. Dyn. Relat. Manage. J. 2, 43–53 (2013)
    46. Stijn Viaene, Annabel Van den Bunder (2011). The Secrets to Managing Business Analytics Projects. MIT Sloan Management Review.
    47. The Economist, (2011). Building with big data: The data revolution is changing the landscape of business. Available at: http://www.economist.com/node/18741392 (Accessed 2nd of March, 2016).
    48. Thomas Bergmann, Waldemar Karwowski (2019). Agile Project Management and Project Success: A Literature Review. Advances in Human Factors, Business Management and Society(pp.405-414)
    49. Tuncay Bayrak (2015). A Review of Business Analytics: A Business Enabler or Another Passing Fad. World Conference on Technology, Innovation and Entrepreneurship. Procedia - Social and Behavioral Sciences 195 ( 2015 ) 230 – 239
    50. Wixom, B. H., Yen, B., & Relich, M. (2013). Maximizing value from business analytics. MIS Quarterly Executive, 12, 111–123.
    51. Ying Liu, Henry Han, Joan E. DeBello (2018). The Challenges of Business Analytics: Successes and Failures. 51st Hawaii International Conference on System Sciences
    52. Zhaohao Sun, Huasheng Zou, Kenneth Strang (2015). Big Data Analytics as a Service for Business Intelligence. IFIP International Federation for Information Processing. M. Janssen et al. (Eds.): I3E 2015, LNCS 9373, pp. 200–211

    QR CODE