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更好的需求信号,更好的决策?考虑环境风险的许可再制造供应链中大数据的评估。

Better Demand Signal, Better Decisions? Evaluation of Big Data in a Licensed Remanufacturing Supply Chain with Environmental Risk Considerations.

机构信息

School of Business Administration, South China University of Technology, Guangzhou, China.

Sun Yat-sen Business School, Sun Yat-sen University, Guangzhou, China.

出版信息

Risk Anal. 2017 Aug;37(8):1550-1565. doi: 10.1111/risa.12796. Epub 2017 Mar 30.

DOI:10.1111/risa.12796
PMID:28370119
Abstract

Big data ability helps obtain more accurate demand signal. However, is better demand signal always beneficial for the supply chain parties? To answer this question, we investigate a remanufacturing supply chain (RSC), where demand uncertainty is significant, and the value to reduce environmental risk is large. Specifically, we focus on a licensed RSC comprising an original equipment manufacturer (OEM) and a third-party remanufacturer (3PR). The latter pays a unit license fee to the former, and can be risk averse to the demand of remanufactured products. We show that the OEM and the risk-neutral 3PR always have incentives to improve their big data abilities to increase their profits. However, when the 3PR is risk averse, big data might hurt its profit: the value of big data is positive if its demand signal accuracy is sufficiently low. Interestingly, we find that while information sharing hurts the 3PR, it benefits the OEM as well as the supply chain. Thus, if costly information sharing is allowed, a win-win situation can be achieved. We also find that information sharing generates more valuation when the 3PR is risk averse than that when the 3PR is risk neutral. More importantly, we find that the 3PR's risk attitude and demand signal accuracy can significantly mitigate the negative environmental impact (measured by the amount of the waste): (1) the more risk neutral the 3PR is, the better the environment is; (2) the more accurate demand signal is, the better the environment is.

摘要

大数据能力有助于获得更准确的需求信号。然而,更好的需求信号总是对供应链各方有利吗?为了回答这个问题,我们研究了一个再制造供应链(RSC),其中需求不确定性很大,减少环境风险的价值很大。具体来说,我们关注的是一个由原始设备制造商(OEM)和第三方再制造商(3PR)组成的许可再制造供应链。后者向前者支付单位许可费,并且可能对再制造产品的需求持风险厌恶态度。我们表明,OEM 和风险中立的 3PR 总是有动力提高他们的大数据能力以增加他们的利润。然而,当 3PR 是风险厌恶时,大数据可能会损害其利润:如果其需求信号准确性足够低,则大数据的价值为正。有趣的是,我们发现虽然信息共享会伤害 3PR,但它也会使 OEM 和供应链受益。因此,如果允许昂贵的信息共享,可以实现双赢局面。我们还发现,当 3PR 是风险厌恶时,信息共享会产生更多的估值,而不是当 3PR 是风险中性时。更重要的是,我们发现 3PR 的风险态度和需求信号准确性可以显著减轻负面环境影响(以废物量衡量):(1)3PR 越中立,环境越好;(2)需求信号越准确,环境越好。

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