文章基本信息

标题：A Comparative Study of Pull and Push Production Methods for Supply Chain Resilience
本地全文：下载
作者：Chia-Ling Huang, Rong-Kwei Li, Chih-Hung Tsai, Yi-Chan Chung, Chun-Hsien Shih
期刊名称：International Journal of Operations and Logistics Management
印刷版ISSN：2309-8023
电子版ISSN：2310-4945
出版年度：2014
期号：270
页码：1-15
出版社：Academy of Business & Scientific Research
摘要：The earthquake of March 11, 2011, seriously affected the production of electronic parts in Japan. This disruptive event highlights the challenge that businesses face in how to manage and mitigate this type of risk. Resilient supply chains and emerging disciplines of supply chain management (SCM) that incorporate event readiness can provide an efficient response, and often are capable of recovering to their original state after the disruptive event. There are generally two methods of managing a supply chain in current supply chain management practice: a pull system or a push system. Based on the characteristics of resilient supply chains and general prescriptions of pull supply chain system, the pull supply chain system can provide better resilience than the push supply chain system. This study designs an experiment to evaluate the ability of both management methods to provide resilience ability. Experiments results reveal that two main findings: (1) during the disruption period, if the initial system inventory of both systems is enough to cover the demand during the disruption period, the actual damage is far less than expected for the period. If most of the inventory can be cleared while maintaining sales, financial performance will be better than normal; (2) the pull system outperforms the push system for its ability to restore the system to stable operation after the disruption. This is because the pull system uses the precious capacity to produce only those goods with insufficient or no inventory. Thus, the pull system can efficiently use limited capacity after the disruption. If goods that are not needed now are produced, they will turn into inventory that will eat up the limited capacity of production and eventually prevent manufacturers from producing what is truly needed now.