English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 84662/113307 (75%)
造訪人次 : 22351064      線上人數 : 603
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/122258
    請使用永久網址來引用或連結此文件: http://nccur.lib.nccu.edu.tw/handle/140.119/122258


    題名: 第三方國際物流商運輸資源配置模型建置之研究
    A Research on Developing a Transportation Model for third-party international logistics providers
    作者: 倪爾瑾
    Ni, Erh-Chin
    貢獻者: 林我聰
    Lin, Woo-Tsong
    倪爾瑾
    Ni, Erh-Chin
    關鍵詞: 物流商
    運輸資源配置
    運輸風險不確定性
    Logistics providers
    Transportation resource allocation
    Uncertainty of transportation risks
    日期: 2018
    上傳時間: 2019-02-12 15:41:46 (UTC+8)
    摘要: 經濟與市場全球化的發展,為快速回應市場需求,必須縮短供應鏈的規劃週期與配送時間,以達到快速交貨。本研究提出評估物流商能力做運輸資源最適分配並考量風險因素。並考量如何安排運輸資源完成訂單需求。方法參考Sheu(2006)於以下五個程序,包括:(1)訂單資料處理(2)客戶訂單分組(3)客戶訂單組排序(4)集裝箱分配(5)運輸載具分配。而不同的貨物性質在運輸時需考量運輸風險不確定性。如運輸工具的不同,在運輸時所面臨的風險不確定性就不同;而面對緊急訂單、新訂單需求時,可能導致讓物流商要調派人力或者車輛去滿足此訂單需求。因此本研究多加考量運輸資源調撥成本和運輸風險成本讓運輸資源配置模型更加完善,並協助物流商最適運輸資源配置。
    With the development of economic and market globalization, in order to quickly respond to market demands, the supply chain's planning cycle and delivery time must be shortened to achieve rapid delivery. This study proposes to assess the ability of logistics providers to optimize resource allocation and consider risk factors. How logistics providers arrange transportation resources to complete orders. This method refers to Sheu (2006) (1) order data processing (2) customer order grouping (3) customer order group ranking (4) container assignment (5) transport vehicle assignment. It is necessary to consider the uncertainty of transportation risks and the additional costs of rush orders and new orders. Therefore, this study considers more transportation resource allocation costs and transportation risk costs, makes the transportation resource allocation model more completely, and helps logistics providers to optimize the allocation of transportation resources.
    參考文獻: Ambulkar, S., Blackhurst, J., & Grawe, S. (2015). Firm's resilience to supply chain disruptions: Scale development and empirical examination. Journal of operations management(33), pp.111-122.
    Aqlan, F., & Lam, S. S. (2015). A fuzzy-based integrated framework for supply chain risk assessment. International Journal of Production Economics(161),pp.54-63.
    Bogataj, D., & Bogataj, M. (2007). Measuring the supply chain risk and vulnerability in frequency space. International Journal of Production Economics, (108:1-2),pp.291-301.
    Chen, Chao Hua and Yeh, Che Cheng,(2015). Simulation Optimization Analysis of the Operational Model for B2C On-line Shopping Platform with VMI and Revenue Sharing, Journal of e-Business (17:4), pp. 459-478.
    Du, M., and Yi, H., (2013). Research on Multi-Objective Emergency Logistics Vehicle Routing Problem under Constraint Conditions, Journal of Industrial Engineering and Management (6:1), pp. 258.
    Eckerd, A., and Girth, A. M.,(2017). Designing the Buyer–Supplier Contract for Risk Management: Assessing Complexity and Mission Criticality, Journal of Supply Chain Management (53:3), pp. 60-75.
    Feng Cheng Min, Y. C. Y., and Lin Yi Chen.,(2007). The Impact of Collaborative Transportation Management on Supply Chain, Transportation Planning Journal (36:3), pp. 333-370.
    Gómez, J. C. O., Duque, D. F. M., Rivera, L., and García-Alcaraz, J. L.,(2017). Decision Support System for Operational Risk Management in Supply Chain with 3pl Providers, in Current Trends on Knowledge-Based Systems. Springer, pp. 205-222.
    Govindan, K., and Chaudhuri, A.,(2016). Interrelationships of Risks Faced by Third Party Logistics Service Providers: A Dematel Based Approach, Transportation Research Part E: Logistics and Transportation Review (90), pp. 177-195.
    Govindan, K., Khodaverdi, R., and Vafadarnikjoo, A., (2016). A Grey Dematel Approach to Develop Third-Party Logistics Provider Selection Criteria, Industrial Management & Data Systems (116:4), pp. 690-722.
    Govindan, K., Palaniappan, M., Zhu, Q., & Kannan, D.,(2012). Analysis of third party reverse logistics provider using interpretive structural modeling. International Journal of Production Economics(140:1),pp. 204-211.
    Hu, T.-L., and Sheu, J.-B., (2003). A Fuzzy-Based Customer Classification Method for Demand-Responsive Logistical Distribution Operations, Fuzzy Sets and Systems (139:2), pp. 431-450.
    Ho, W., Zheng, T., Yildiz, H., & Talluri, S. (2015). Supply chain risk management: a literature review. International Journal of Production Research, (53:16), pp.5031-5069.
    Huang, S., Axsäter, S., Dou, Y., & Chen, J. (2011). A real-time decision rule for an inventory system with committed service time and emergency orders. European journal of operational research, (215:1),pp. 70-79.
    Johansen, S. G., and Thorstenson, A., (1998). An Inventory Model with Poisson Demands and Emergency Orders, International Journal of Production Economics (56), pp. 275-289.
    König, A., and Spinler, S., (2016). The effect of logistics outsourcing on the supply chain vulnerability of shippers: Development of a conceptual risk management framework, The International Journal of Logistics Management(27:1), pp.122-141.
    Liu et al., (2011). An Emergency Order Allocation Model Based on Multi-Provider in Two-Echelon Logistics Service Supply Chain, Supply chain management: an international journal (16:6), pp. 391-400.
    Lam, J. S. L., and Dai, J.,(2015). Developing Supply Chain Security Design of Logistics Service Providers: An Analytical Network Process-Quality Function Deployment Approach, International Journal of Physical Distribution & Logistics Management (45:7), pp. 674-690.
    Larson, P. D., and Halldorsson, A., (2004). Logistics Versus Supply Chain Management: An International Survey, International Journal of Logistics: Research and Applications (7:1), pp. 17-31.
    Nooraie, S. V., and Parast, M. M., (2015). A Multi-Objective Approach to Supply Chain Risk Management: Integrating Visibility with Supply and Demand Risk, International Journal of Production Economics (161), pp. 192-200.
    Sheu, J.-B. ,(2006). A Novel Dynamic Resource Allocation Model for Demand-Responsive City Logistics Distribution Operations, Transportation Research Part E: Logistics and Transportation Review (42:6), pp. 445-472.
    Yu, C.-S., and Li, H.-L., (2000). A Robust Optimization Model for Stochastic Logistic Problems, International journal of production economics (64:1-3), pp. 385-397.
    Yang et al., (2011). Hybrid Zigbee RFID sensor network for humanitarian logistics centre management. Journal of Network and Computer Applications(34:3), pp.938-948.
    Zhen et al., (2014). Discussion on Key Problems and Counter Measures of Logistics Management in Construction Supply Chains, Journal of Engineering Management(28:4),pp.32-35.
    描述: 碩士
    國立政治大學
    資訊管理學系
    105356007
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0105356007
    資料類型: thesis
    DOI: 10.6814/THE.NCCU.MIS.002.2019.A05
    顯示於類別:[資訊管理學系] 學位論文

    文件中的檔案:

    檔案 大小格式瀏覽次數
    600701.pdf1462KbAdobe PDF0檢視/開啟


    在政大典藏中所有的資料項目都受到原著作權保護.


    社群 sharing

    著作權政策宣告
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋