臺灣博碩士論文加值系統

在近十年間，智慧物流受到企業高度重視及討論，主要原因在於全球物流業的高度競爭，以至於物流營運的效率及技術皆有突破性的發展，其主要植基於資料分析技術在物流之應用日益茁壯，進而使物流資訊更迅速且準確地傳遞，同時也使資訊流與物流流程的連結更緊密。而在智慧物流的快速發展下，其倉庫管理、裝卸運輸、配送發貨以及訂單處理的自動化應用水平不斷提升，也使得物流資訊系統與物流商、供應商、製造商、中盤商以及顧客緊密相連，同時，也將在運輸網路中蒐集的資料即時傳遞與共享給相關單位，進而發展出以資料分析與串聯為基礎的智慧物流架構。然而，關於智慧物流及資料分析技術在物流之應用的具體內涵為何，雖已有一些開拓性探討，但是仍不足以視為通用性定義而加以採用。為此，資料分析技術在物流之應用及智慧物流的相關文獻是相當需要整合的。
本研究從資料分析在智慧物流之應用的角度，探討C公司如何從傳統物流公司轉型為以資料分析為營運基礎的物流公司，透過設計科學法探討目前C公司所面臨的問題，並分析當前資料分析在物流流程運用之關鍵技術為何、如何導入資料分析技術軟硬體設備、人力組織規劃及培育、通用資料分析之應用以及進階資料分析之應用，以解決C公司當前郵件流面臨之問題，並提高C公司在物流業之競爭力。

In the past decade, smart logistics has been highly discussed by companies, mainly because of the high competition in the global logistics industry, so that the efficiency and technology of logistics operations have breakthrough development, which is mainly based on the application of data analytics technology in logistics It is becoming stronger, which makes logistics information more quickly and accurately transmitted, and at the same time makes the connection between information flow and logistics process closer. With the rapid development of smart logistics, the automation application level of its warehouse management, loading and unloading transportation, distribution and delivery and order processing have been continuously improved, which also makes the logistics information system closely connected with logistics providers, suppliers, manufacturers, mid-market vendors and customers. At the same time, a smart logistics structure based on coordination and optimization technologies will be developed. However, regarding the specific connotation of the application of smart logistics and data analytics technology in logistics, although there have been some pioneering discussions, it is still not enough to be adopted as a general definition. For this reason, the application of data analytics technology and the related literature of smart logistics need to be integrated.
This research explores how C Company transforms from a traditional logistics company to a smart logistics company. It explores the current problems faced by C company through design science research approach, analyzing the current data, the key technologies used in the logistics process, how to carry out the human organization planning and cultivation of the data analytics team, and how to build the infrastructure of the data analytics software and hardware to solve the problems faced by C company's current mail flow and improve C company's competitiveness in the logistics industry.
Key words：Mail/Parcel Flow, Data Analytics, Smart Logistics

中文摘要 i
ABSTRACT ii
目 錄 iii
表目錄 v
圖目錄 vi
第一章 緒論 1
1.1 研究動機 1
1.2 研究目的 2
1.3研究流程 4
第二章 文獻探討 7
2.1通用智慧物流系統 7
2.2大數據管理系統在物流之應用 12
2.3資料分析技術與應用 14
第三章 研究方法與設計 19
3.1個案研究法 (Case Study) 19
3.2觀念模式建構法 (Conceptual Modeling) 20
3.3文獻回顧法 (Literature Review) 21
3.4設計科學法 (Design Science Research) 22
3.5研究設計 29
第四章 C公司智慧物流實驗室建置及大數據之發展與人才養成 31
4.1 C公司資通訊技術單位現況分析 31
4.2 智慧物流之科技層面劃分 32
4.3 從郵件流檢視智慧物流科技需求 33
4.4 智慧物流實驗室之建置規劃 36
4.5 物流大數據資料分析管理系統 38
4.6資料分析團隊 40
第五章 C公司資料分析應用與組織設計之探討 43
5.1郵件流智慧化之系統架構與要素 43
5.2郵件流智慧化大數據資料分析系統基礎設施之設計規劃 47
5.3通用資料分析系統之應用 53
5.4進階資料分析系統之應用 69
5.5 C公司郵件流資料分析團隊組織規劃 90
5.6資料分析系統導入與應用之延伸性理論 96
第六章 結論與建議 99
6.1 研究結果 99
6.2 研究貢獻 100
6.3 研究限制 100
6.4 未來研究建議 101
參考文獻 102

中文文獻
王亞維(2010)，物聯網關鍵技術分析與發展探討，科技信息所。
郭戎晉（2017），法規調適與監理沙盒—日本產業競爭力強化法之觀察，財團法人資訊工業策進會科技法律研究所，頁225-236。
王獻美(2015)，基於大數據的智慧雲端物流理論_方法及其應用研究，浙江理工大學機
械工程博士。
林桓（2018），我國法規影響評估，現代國家中立法權之行使及其界限，新學林出版，頁3-47。
張芳風、李俊韜 (2011)，雲端架構下的物流公共信息平台設計及探討，商業週刊，第二十三卷第二期，頁211-233。
荊心、張璟 (2013)，複雜事件處理技術及其在物流物聯網中的應用，國家自然科學基金。

英文文獻
Ackoff, R. (1987) President’s symposium: OR, a post-mortem. Operations Research, 35(3), pp. 471–474.
Ackoff, R. L. (1989) “From Data to Wisdom,” Journal of Applied Systems Analysis vol. 16: pp. 3-9.
Ahearne, M., Jelinek, R. and Jones, E. (2007) Examining the effect of salesperson service behavior in a competitive context. Journal of Academy of Marketing Science, vol.35, no.4, pp.603-616.
Allen, D., Colligan, D., Finnie, A., & Kern, T. (2000) Trust, power, and interorganizational information systems: The case of the electronic trading community TransLease. Information Systems Journal, 10(1), pp. 21–40.
Argyris, C. (1997) Field theory as a basis for scholarly consulting. Kurt Lewin Award Lecture. Journal of Social Issues, 53(4), pp. 811–827.
Argyris, C. & Sch¨on, D. A. (1996). Organizational learning II. Reading, MA: Addison-Wesley.
Argyris, C., Putnam, R., & Smith, D. M. (1985). Action science. San Francisco, CA: Jossey-Bass.
Baesens, B. (2017) Profit Driven Business Analytics: A Practitioner’s Guide to Transforming Big Data into Added Value. NJ: Wiley.
Beer, M. (2003).Why total quality management programs do not persist. Decision Sciences, 34(4), 623–642.
Baskarada, S &Koronios, A. (2013) “Data, Information, Knowledge, Wisdom (DIKW): A Semiotic Theoretical and Empirical Exploration of the Hierarchy and its Quality Dimension”, Australasian Journal of Information Systems vol. 18, iss.1: pp.5-24.
Bourgeois, L.J., III. (1979).Toward a method of middle-range theorizing. Academy of Management Review, 4(3), pp. 443–447.
Byckling, E., Hameri, A., Pettersson, T., & Wenninger, H. (2000). Spin-offs from CERN and the Case of TuoviWDM. Technovation, 20(2), pp. 71–80.
Camerer, C. (1985).Redirecting research in business policy ands trategy.Strategic Management Journal, 6(1), pp. 1–15.
Chakravorty, S. S., & Hale, D. N. (2008). The evolution of manufacturing cells: An action research study. European Journal of Operational Research, 188(1), pp. 153–168.
Coghlan, D., & Brannick, T. (2001). Doing action research in your own organization. London, UK: Sage.
Cohen, M. D., March, J. G., & Olsen, J. P. (1972). A garbage can model of organizational choice. Administrative Science Quarterly, 17(1), pp. 1–25.
Cooley, M. (1980). Architect or Bee? The Human / Technology Relationship. Monroe: South End Press.
Corbett, C., & Van Wassenhove, L. N. (1993). The natural drift: What happened to operations research? Operations Research, 41(4), pp.625–640.
Dasgupta, S. (2003). Multidisciplinary creativity: The case of Herbert A. Simon. Cognitive Science, 27(5), pp. 683–707.
Dennett, D. (2003). Freedom evolves. London, UK: Penguin Books.
Dennis, D.R., &Meredith, J.R. (2000).An analysis of process industry production and inventory management systems. Journal of Operations Management, 18(6), pp. 683–699.
DeTreville, S., Edelson, N.M., Kharkar, A.N., &Avanzi, B. (2008).Constructing useful theory: The case of Six Sigma. Operations Management Research, 1(1), pp. 15–23.
Donaldson, L. (2001). The contingency theory of organizations. Thousand Oaks, CA: Sage.
Dubois, A., &Gadde, L.E. (2002).Systematic combining: An abductive approach to case research. Journal of Business Research, 55(7), pp. 553–560.
Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), pp. 532–550.
Främling, K., Kärkkäinen, M., Ala-Risku, T., & Holmström, J. (2007). Design patterns for managing product lifecycle information. Communications of the ACM, 50(6), pp. 75–79.
Gamma, E., Helm, R., Johnson, R., & Vlissides, J. (1995). Design patterns. Reading, MA: Addison-Wesley.
Glaser, B.G., &Strauss, A.L. (1967).The discovery of grounded theory: Strategies for qualitative research. Hawthorne, NY: Aldine de Gruyter.
Goldenberg, J., Lehmann, D., & Mazursky, D. (2001). The idea itself and the circumstances of its emergence as predictors of new product success. Management Science, 47(1), pp. 69–84.
Gregor, S., & Jones, D. (2007). The anatomy of a design theory. Journal of the Association for Information Systems, 8(5), pp. 313–335.
Guide, D., & Van Wassenhove, L. (2007). Dancing with the devil: Partnering with industry but publishing in academia. Decision Sciences, 38(4), pp. 531–546.
Hameri, A., & Nihtilä, J. (1998). Computerized product process: Measurement and continuous improvement. Research in Engineering Design, 10(3), pp. 166–177.
Hempel, C. G. (1965). Aspects of scientific explanation and other essays in the philosophy of science. New York, NY: Free Press.
Hevner, A., March, S., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28(1), pp. 75–105.
Hillier, F.S. and Hillier, M.S. (2019) Introduction to Management Science. (6e) NY: McGraw-Hill.
Huber, G. P., & Power, D. J. (1985). Retrospective reports of strategic-level managers: Guidelines for increasing their accuracy. Strategic Management Journal, 6(2), pp. 171–180.
Jabeur, N., Al-Belushi, T., Mohamed, M., and Gharra, H. (2017). “Toward Leveraging Smart Logistics Collaboration with a Multi-Agent System Based Solution,” Procedia Computer Science vol. 109C: pp. 672–679.
Jackson, R. (1999) Information Design. Cambridge: MIT Press. p. 267.
Jones, T. C., & Dugdale, D. (2002). The ABC bandwagon and the juggernaut of modernity. Organizations and Society, 27(2), pp. 121–163.
Jones, T. C., & Dugdale, D. (2002). The ABC bandwagon and the juggernaut of modernity. Organizations and Society, 27(2), pp. 121–163.
Josephson, J. R. (1996). Conceptual analysis of abduction. In J. R. Josephson & S. G. Josephson (Eds.), Abductive inference: Computation, philosophy, technology. Cambridge, UK: Cambridge University Press, pp. 5–30.
Josephson, J. R., & Josephson, S. G. (Eds.). (1996). Abductive inference: Computation, philosophy, technology. Cambridge, UK: Cambridge University Press.
Joy, G (2016). How Connected Cars Are Driving The IoT Network, https://www.connectedcar-news.com/news/2016/nov/30/how-connected-cars-are-driving-iot-network/.
Kaplan, R. S. (1998). Innovation action research: Creating new management theory and practice. Journal of Management Accounting Research, 10, pp. 89–118.
Kärkkäinen, M., & Holmström, J. (2002). Wireless product identification: Enabler for handling efficiency, customisation, and information sharing. Supply Chain Management: An International Journal, 7(4), pp. 242–252.
Kijewska, K., Małecki, K. and Iwan, S. (2016) “Analysis of Data Needs and Having for the Integrated Urban Freight Transport Management System,” In: Mikulski J. (eds) Challenge of Transport Telematics. TST 2016. Communications in Computer and Information Science vol 640: pp. 135-148.
Klahr, D. &Simon, H. A. (1999).Studies in scientific discovery: Complementary approaches and convergent findings. Psychological Bulletin, 125(5), pp. 524– 543.
Korczak, J. & Kijewska, K. (2019) “Smart Logistics in the Development of Smart Cities,”
Transportation Research Procedia vol.39: pp. 201–211.
Lisa. M, (1996).The Use of the case study method in logistic research. Psychological Bulletin, 125(5), pp. 524– 543.
Martin, W. & Markus, K. (2013) Big Data in Logistics - DHL perspective to move beyond the hype, Solutions & Innovation: Trend Research.
Matthew, L. & Wenhong, L. (2013) “The Art and Science of Practice: A Comparison of Technical and Soft Skill - Requirements for Analytics and OR Professionals,” Interfaces, Vol. 43, No. 2), pp. 194-197.
Megan, J. B. & Robert, M. D. (2020). The U.S. Postal Service Five-Year Strategic Plan, Office of Strategic Planning Publications.
McFarlane, D., & Sheffi, Y. (2003). Impact of automatic identifcation on supply chain operations. International Journal of Logistics Management, 14(1), 1– 17.
Michael, J. R. (2011) Offering Sensor Network Services Using the Postal Delivery Vehicle Fleet , Postal Regulatory Commission.
Michael, W. (2012).Big Data Analytics Infrastructure. Data Science Central Community.
Meredith, J.R. (2001).Hopes for the future of operations management. Journal of Operations Management, 19(4), pp.397–402.
Merton, R. K. (1957). Social theory and social structure (revised and enlarged). Glencoe, IL: Free Press.
Niiniluoto, I. (1999). Defending abduction. Philosophy of Science, 66(Proceedings), pp. 436–451.
Niiniluoto, I. (1993).The aim and structure of applied research. Erkenntnis, 38(1), pp. 1–21.
OIG. (1967). International Postal Big Data: Discussion Forum Recap. Hawthorne, U.S. Postal Service Office of Inspector General.
OIG.(2018) Coordination and Optimization Technologies and Postal Applications, Office of Inspector General |
Orlikowski, W., & Gash, D. (1994). Technological frames: Making sense of information technology in organizations. ACM Transactions on Information Systems, 12(2), pp. 174–207.
Peirce, C. S. (1878). Deduction, induction, and hypothesis. Popular Science Monthly, 13, pp. 470–482.
Pickering, A. (1995).Them angle of practice: Time, agency, and science. Chicago, IL: University of Chicago Press.
Popper, K. R. (1963). Conjectures and refutations. London, UK: Routledge.
Schmenner, R. W. & Swink, M. L. (1998). On theory in operations management. Journal of Operations Management, 17(1), pp. 97–113.
Randy, B. (2014). Business Analytics, the McGraw.Hill Companies.
Riham, A. & Muhammad, E (2017) Lelantos: A Blockchain-based Anonymous Physical Delivery System, Annual Conference on Privacy.
Robert, H. & Frank, S. (2013)Trends and Strategies in Logistics and Supply Chain Management, BVL International, 17(2), pp.51.
Rowley, J. (2007) "The Wisdom Hierarchy: Representations of the DIKW hierarchy," Journal
Of Information and Communication Science. vol.33 (2): pp. 163–180.
Scott, W. R. (2003). Introduction to J. D.Thompson (author). Organizations in action: Social science bases of administrative theory (transaction). New Brunswick, NJ: Transaction Publishers.
Senge, P., & Sterman, J. D. (1992). Systems thinking and organizational learning: Acting locally and thinking globally in the organization of the future. European Journal of Operational Research, 59(1), pp. 137–150.
Siemieniuch, C. E., & Sinclair, M. A. (2004). CLEVER: A process framework for knowledge lifecycle management. International Journal of Operations & Production Management, 24(11), pp. 1104–1125.
Simon, H. A. ([1969] 1996). The sciences of the artificial (3rd). Cambridge, MA: MIT Press.
Simon, H.A. (1973).Does scientific discovery have a logic? .Philosophy of Science, 40(4), pp. 471–480.
Simon, H.A. (2002).Forecasting the future or shaping it? Industrial and Corporate Change, 11(3), pp. 601–605.
Steenhuis, H.J., & de Bruijn, E. J. (2006). Publishing in OM: Does scientific paradigm matter? Paper presented at the 2006 Annual Meeting of the Academy of Management, Philadelphia, PA.
Trovinger, S. C., & Bohn, R. (2005). Setup time reduction for electronics assembly: Combining simple (SMED) and IT-based methods. Production and Operations Management, 14(2), pp. 205–217.
USPS, (2016). Creating Operational Efficiencies, https://about.usps.com/who-weare/financials/annualreports/fy2016/annual_report2016_tech_043.html.
USPS, (2015). Improving Customer Experience, https://about.usps.com/who-weare/financials/annualreports/fy2015/annual_report2015_tech_025.html.
Van Aken, J. E. (2004). Management research based on the paradigm of design sciences: The quest for field-tested and grounded technological rules. Journal of Management Studies, 41(2), pp. 219–246.
Van de Ven, A. H. (2007). Engaged scholarship: A guide for organizational and social research. New York, NY: Oxford University Press.
Van de Ven, A. H., & Johnson, P. E. (2006). Knowledge for theory and practice. Academy of Management Review, 31(4), pp. 802–821.
Whetten, D. A. (1989). What constitutes a theoretical contribution? Academy of Management Review, 14(4), pp. 490–495.
Williamson, O.E. (1985).The economic institutions of capitalism. New York, NY: Free Press.
Williamson, O.E. (1996).The mechanisms of governance .New York, NY: Oxford University Press.
Woodward, J. (1994). Industrial organization: Theory and practice (2nd). London, UK: Oxford University Press.
Woolsey, R. E. D. (1972). Operations research and management science today, or, does an education in checkers really prepare one for a life in chess? Operations Research, 20(3), pp. 729–737.
Ziliak, S., & McCloskey, D. (2008). The cult of statistical significance: How the standard error costs us jobs, justice, and lives. Ann Arbor, MI: University of Michigan Press.