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论文

考虑下侧风险厌恶参与者的技术外包合同研究

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  • 1. 教育部人文社会科学重点研究基地清华大学现代管理研究中心, 北京 100084;
    2. 清华大学经济管理学院, 北京 100084;
    3. 清华大学经济学研究所, 北京 100084

收稿日期: 2016-03-12

  修回日期: 2016-07-07

  网络出版日期: 2017-06-29

基金资助

国家自然科学基金资助项目(71232007)

Study on Enterprise Technology Outsourcing with Downside Risk Averse Agent

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  • 1. Research Institute of Humanities and Social Sciences at Universities, Research Center for Contemporary Manayement, Tsinghua University, Beijing 100084, China;
    2. School of Economics and Management, Tsinghua University, Beijing 100084, China;
    3. Institute of Economics, Tsinghua University, Beijing 100084, China

Received date: 2016-03-12

  Revised date: 2016-07-07

  Online published: 2017-06-29

摘要

本文构建了企业技术外包活动中技术需求企业与创新提供商之间的委托代理问题。由于直接面临研发风险,创新提供商为风险厌恶参与者,本文使用在险价值(Value-at-Risk)作为其风险厌恶程度的测度,并在此基础上求解最优合同参数,与传统均值—方差(M-V)效用函数的对比发现:1)随着风险波动的加剧,VaR测度下单位支付增加,而在M-V效用函数下降低;2)随着风险厌恶水平的提高,合同单位支付增加,而M-V效用函数降低;3)随着风险厌恶水平的提升,VaR下的固定支付部分也相应增加;4)VaR的两个要素对于合同的固定支付与单位支付的影响不同,保留利润水平不会影响单位支付水平,而置信水平对二者均有影响。VaR测度在克服M-V方法理论缺陷的同时,将提供更符合直觉的管理启示。

本文引用格式

任龙, 刘骏 . 考虑下侧风险厌恶参与者的技术外包合同研究[J]. 中国管理科学, 2017 , 25(4) : 184 -189 . DOI: 10.16381/j.cnki.issn1003-207x.2017.04.022

Abstract

To acquire competitive advantages in an ever-changing business environment, many business gurus step up to outsource their non-core activities to third-party members. Except for some basic activities such as operations and marketing, R&D outsourcing has become prominent since 1970s. There are many success examples such as IDEO, an international design and consulting firm founded in California, in 1991, participating in the design of Apple Mouse. Different from other activities, R&D outsourcing is with high uncertainty and information asymmetry. The risk sharing and information issues are very important for both participants. To tackle with these problems, a principal-agent like R&D outsourcing problem between a technology provider and buyer is studied. Since the buyer can't observe the provider's R&D effort, an optimal contract must be designed to alleviate the moral hazard problem. The contract is composed of two parts, namely fixed payment and unit payment. Fixed payment mean no matter what the random output is, the provider will get this part. The unit payment is the gain for each unit output. Faced directly to R&D risks, the technology supplier is regarded as a downside risk averse agent. The provider's risk aversion attitude is modeled with Value-at-Risk (VaR) constraint. By solving this optimization problem with KKT conditions, the VaR results are compared against the seminal mean-variance framework, and it is founol that: 1) the unit payment under VaRincreases as the demand volatility increases, while it decreases under M-V framework; 2) as the risk aversion increases, unit payment in VaR increases while M-V decreases; 3) as the provider becomes more risk averse, the fixed payment under VaR increases; 4) reserved profit and risk control level plays different roles in determine the optimal parameters, the reserved profit doesn't impact on the unit payment while the risk control level influences them both. VaR method not only overcomes the shorting comings of mean-variance method in theory, such as M-V can't separate upper gains with downside loss. The VaR method also provides much more clear managerial insights for technology outsourcing problem.

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