English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 110175/141113 (78%)
Visitors : 46563943      Online Users : 934
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/118047


    Title: Seller’s Optimal Credit Period and Delivery Number in EPQ Models when Production Costs have the Learningby- Experience Effects
    當賣家之生產成本具有經驗學習效應下最佳的信用交易期間和交貨次數
    Authors: 陳聖智
    Chen, Sheng-Chih
    Contributors: 傳播學院
    Keywords: 庫存管理;信用交易;學習性生產成本;經濟生產量
    Inventory management;Trade credit;Learning production cost;Economic production quantity
    Date: 2015-12
    Issue Date: 2018-06-26 17:24:19 (UTC+8)
    Abstract: 實務上賣家經常給買家固定的信用交易期間,以無息付款來刺激銷售量和市場的競爭力。此外,從經驗學習效應來看,銷售量愈大則生產量也愈大,而生產量增加則學習效應高,促使每單位生產成本跟著降低。因此,從賣家觀點,提供信用交易,不但增加銷售量,也帶來具有學習效應的單位生產成本降低。另一方面,給予信用交易不只增加信用期間的利息損失,還有增加違約風險率。現有文獻鮮少注意到這個事實。本研究配合信用交易對銷售和學習生產成本有正面影響,但對利息損失和違約風險卻有負面衝擊,建立生產系統中賣家最佳的信用交易期間和交貨次數模型來達到利潤最大化,這是混合整數規劃問題,本研究透過電腦軟體去解決。為簡化,論文中提出一優化啟發演算法,最後,用敏感度分析顯示一些觀點洞見和可顯著增加賣家的信用期間和總利潤的經驗學習效應。
    To stimulate sales and remain competitive, the seller usually offers the buyer a credit period to settle the purchase amount with no interest charges. In addition, the more quantity produced and sold, the cheaper the unit production cost due to the learning-by-experience effect. Therefore, from the seller`s perspective, offering trade credit increases sales volume, resulting in lower unit production cost. On the other hand, granting trade credit increases not only interest loss during credit period but also default risk. However, relatively little attention has been paid to the fact that trade credit increases sales volume and reduces the production cost due to the learning-by-experience effect. In this paper, we develop the seller`s optimal credit period and number of deliveries in an Economic Production Quantity model in which trade credit has positive impacts on sales and learning production cost while it has negative impacts on interest loss and default risk. We then formulate the problem as a mixed integer programming problem, and solve it by computer software. For simplicity, we propose a remarkably good heuristic algorithm. Finally, we use sensitivity analysis to show several managerial insights, and that the learning-by-experience effect can significantly increase the seller`s credit period and total profit.
    Relation: 管理學報(Journal of Management)(TSSCI), Vol.32, No.4, pp.385-398
    Data Type: article
    DOI 連結: http://dx.doi.org/10.6504/JOM.2015.32.04.03
    DOI: 10.6504/JOM.2015.32.04.03
    Appears in Collections:[數位內容與科技學士學位學程] 期刊論文

    Files in This Item:

    File Description SizeFormat
    385398.pdf1398KbAdobe PDF2474View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    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。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    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。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback