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论文

供应链中断下顾客缺货反应对牛鞭效应的影响研究

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  • 1. 深圳信息职业技术学院, 广东 深圳 518172;
    2. 哈尔滨工业大学深圳研究生院, 广东 深圳 518055

收稿日期: 2014-12-26

  修回日期: 2015-12-06

  网络出版日期: 2016-07-27

基金资助

国家自然科学基金资助项目(71171064)

Impact of Customer Response to Stock-out on Bullwhip Effect:Under Supply Chain Disruption

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  • 1. Shenzhen Institute of Information Technology, Shenzhen 518172, China;
    2. Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen 518055, China

Received date: 2014-12-26

  Revised date: 2015-12-06

  Online published: 2016-07-27

摘要

传统的关于供应链牛鞭效应的研究,仅关注供应链上游成员间(供应商、制造商或零售商)的协调运作,而忽略缺货发生后顾客缺货反应对供应链动态性的影响。本文利用高层级Petri-net对包含两个制造商、两个零售商的供应链系统进行建模与仿真,定量地研究不同的缺货强度下顾客缺货反应对两条相互竞争的供应链牛鞭效应的影响。研究结果表明,顾客缺货反应对缺货品牌及其竞争品牌的牛鞭效应均存在显著影响,但各种缺货反应对牛鞭效应的影响程度有所差异,且供应链中断强度(主要体现为发生缺货的品牌市场份额以及缺货持续时间)亦对牛鞭效应产生显著影响。我们建议不同产品类型(对应不同的顾客反应组合)的管理者根据品牌的市场占有率、缺货持续时间等因素对不同类型的顾客进行购买行为的引导,以缓解牛鞭效应并保持市场份额。

本文引用格式

张小玲, 陆强 . 供应链中断下顾客缺货反应对牛鞭效应的影响研究[J]. 中国管理科学, 2016 , 24(7) : 54 -62 . DOI: 10.16381/j.cnki.issn1003-207x.2016.07.007

Abstract

Effective supply chain management is a critical capability to fulfill consumer demand. Since the ultimate goal of a performing supply network is to deliver products/services to the end customers, customer response to stock-out (a post-disruption event) should be an important variable. Incorporating the purchasing behavior into the supply network analysis to "bridge" customer responses to stock-out (a marketing phenomenon) and bullwhip effect (a supply chain phenomenon) requires more quantitative modeling, which is currently absent. Indeed, most supply chain modeling takes the end customer as a passive recipient of products/services provided by upstream elements and treats any unfilled orders as backlog. However, with more competitive worldwide sourcing, consumers increasingly shop at alternative outlets to find the items they need, which has significant impact on the supply chain dynamics of stock-out brand and competing brand, and even the overall supply network. In this paper, responses from different customers experiencing stock-out is modelled to effectively identify supply chain mitigation strategies.
In this research, a high-level Petri-net is developed to model a supply network with two brands of product and two stores, and five types of customer stock-out responses from marketing literature are identified. In the first experiment, the responses are incorporated in the model to quantitatively assess the correlation between customer response and bullwhip effect of both the stock-out brand and the competing brand. In the second experiment, the data from a marketing research of P&G Company is applied to analysis the impact of stock-out intensity on bullwhip effect of 5 specific product categories, which presented 5 different customer response compositions.
Based on the ANOVA analysis of the experiment results, some managerial relevance statements are provided for both the stock-out brand and competing brand. (1) For the stock-out brand, it's suggested that managers should a) focus on customers who prefer to switch store or delay purchase; and b) work together with their retailers to develop customers' store loyalty and encourage customers to substitute within the same brand in a different size. (2) For the competing brand, the manufacturer and its retailers should make great effort to distinguish the demand switched from the stock-out brand from the real demand and grab the opportunity to develop more loyalty customers. (3) Implication to managers for both the stock-out brand and the competing brand is that the incentive to customer behavior should vary with market share and stock-out duration in order to mitigate the bullwhip effect.
Through linking supply chain dynamics to customer purchase behaviors based on simulation technology, the impact of stock-out disruption is quantified from the viewpoint of customer behavior for improving supply chain efficiency. We expect that this paper can provide the foundation for a future stream of research for studying the complex topic of disruption stock-out risk in a supply chain by taking into consideration of customer behaviors from marketing perspective.

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