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      科研管理 2019, Vol. 40 Issue       (9) :170-180 论文   DOI:
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3.电子科技大学经济与管理学院,四川 成都611731
       Incentive mechanism in SaaS cloud outsourcing by considering the impact of service investment
       Tang Guofeng1,3, Li Dan2,3
       1. College of Business Planning, Chongqing Technology and Business University, Chongqing 400067, China; 
2. School of Economics, Southwest University of Political Science and Law, Chongqing 401120, China;
3. School of Economics and Management, University of Electronic Science and Technology, Chengdu 611731, Sichuan, China
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摘要 客户企业在实施SaaS云外包时,面临因效率参数不可观测所引发的云服务提供商(Cloud Service Provider,CSP)道德风险问题。针对该问题,在考虑服务投资影响效率参数分布情况下,以客户企业期望收入最大化为目标,应用委托—代理理论设计了云外包激励机制,并对合约性质及激励效果进行了分析。研究表明,激励相容性的自我实施条件由效率参数改进的边际效用、努力的边际负效用及边际产出决定;最优努力水平是效率参数的减函数;服务投资与效率参数进一步改进的条件概率间存在一定的相关关系;最优激励机制可由固定服务报酬及收益共享构成的线性合约表示。
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关键词CSP(云服务提供商)   效率参数   服务投资   道德风险   机制设计     
Abstract: With the development of Internet and alleviation of cyber-cost, cloud computing service outsourcing represented by SaaS (Software as a Service) has exerted indispensable impacts on giving incentives to the combination of enterprises and network. Moreover, customer enterprises can have easy access to a great variety of application software renting service which is provided by application servers owned by CSP(Cloud Service Provider) through Internet. At present, although the size and number of users of SaaS cloud outsourcing service market in China are expanding dramatically, the development of SaaS service market is not smooth. The principal-agent problem which is triggered off by asymmetric information and CSP has become the main risk factor affecting the robustness of outsourcing cooperation between customer enterprise and CSP, and also one of the main reasons hindering progress of SaaS cloud outsourcing mode. 
There is a rapidly growing literature on service outsourcing, which indicates that incentive mechanism design in the form of contract plays a significant part in alleviating side effects stemmed from asymmetric information in outsourcing cooperation. The design of SaaS cloud outsourcing incentive mechanism has been the academic focus since cloud outsourcing theory research was carried on. The research on incentive mechanism design of SaaS cloud outsourcing in academia is extended and expanded based on the research findings of application service outsourcing incentive mechanism design under ASP (Application Service Provider) mode. On the basis of the research on incentive mechanism design of application service outsourcing, the research on incentive mechanism design of SaaS cloud outsourcing in academia mainly focuses on how to design optimal outsourcing contract in asymmetric information scenario. Scholars started their research from a great variety of perspectives such as transaction cost, information scenario, contract content, supply chain coordination, fair preference, uncertain service environment, performance-price ratio and so on. Particularly, some research unfolds the fact that external service environment such as network conditions and network security exert vital impacts on actual operation performance of SaaS cloud outsourcing.
Current research has validated that CSP generally invests a certain amount of money to improve the external network environment before the process of service production, and then there exists moral hazard with hidden external network environment information between customer enterprise and CSP during the process of service production. At present, the vast majority of research on incentive mechanism design under moral hazard with CSP’s hidden information is limited to qualitative analysis. However, there is insufficient research on how to design the optimal incentive mechanism based on quantitative research methods, and less consideration is given to the impact of service investment. In this paper, we study how to mitigate the risk of SaaS cloud outsourcing cooperation triggered off by asymmetric information through the design of outsourcing incentive mechanism on the basis of Principal-Agent Theory under the condition that the efficiency parameter information and service effort level of CSP cannot be observed by customer enterprise, considering the impacts of CSP service investment on the probability distribution of efficiency parameter.
This paper divides the establishment process of SaaS cloud outsourcing cooperation between customer enterprise and CSP into three stages. The first stage is mechanism design, in which customer enterprise design incentive mechanism in the form of contract menu corresponding to the service revenue of customer enterprise and service remuneration obtained by CSP. The second stage is contract signing, in which CSP decides whether to accept outsourcing contract or not based on whether the expected utility obtained by choosing contract menu for service production is greater than the reserved utility. The third stage is contract execution, CSP chooses the optimal effort level for service production and optimal investment level for improving the external network environment, and then customer enterprise pays CSP according to the signed outsourcing contract. Moreover, according to the actual scenario of SaaS cloud outsourcing services, this paper sets up hypothetical conditions for the revenue function, contract menu and risk attitude of customer enterprise, as well as the cost function and risk attitude of CSP.
Apparently, the outsourcing cooperation relationship between customer enterprise and CSP is actually a dynamic game relationship with incomplete information. As a result, this research issue is analyzed by reverse induction method. In the first place, the incentive compatibility constraint and participation constraint of optimal outsourcing incentive mechanism are analyzed on the basis of Principal-Agent Theory, then a programming model is established. In the second place, this paper analyzes properties of the optimal contract after solving the programming model, which involves marginal negative effect of CSP’s effort level, monotonic property of effort level function, relevance between risk ratio and service investment. Moreover, this paper extends the designed outsourcing incentive mechanism to linear contract form. Finally, the inference of the manifestation of linear contract is proposed.
From what has been analyzed above, the following four conclusions can be drawn. Firstly, the incentive mechanism designed by customer enterprise has property of incentive compatibility if it can ensure that the marginal utility of CSP obtained after service production is negatively proportional to the marginal utility of CSP consumed during the process of service production, and ensure that the marginal revenue of customer enterprise is less than zero. Secondly, CSP will put lower effort level to control the service cost when the external network environment is worse, otherwise it will choose to put higher effort level. Thirdly, there exists a correlation between service investment and possibility of further improvement in external network environment, which depends on the monotony of risk ratio. Finally, the optimal incentive mechanism of SaaS clouding outsourcing designed by customer enterprise can be represented by a linear contract consisting of fixed service reward and sharing revenue.
In addition, the future research direction on design of SaaS cloud outsourcing incentive mechanism is discussed. In the actual operation scenario of SaaS cloud outsourcing, service investment made by CSP in order to improve its external network environment can be not only monetary but also non-monetary, which involves coordinating projects, choosing appropriate technology and so on. However, this paper only considers that service investment is monetary, which can be observed by customer enterprise. Further research can be extended to the design of incentive mechanism for SaaS cloud outsourcing when service investment is non-monetary.
Keywords CSP (Cloud Service Provider)   efficiency parameter   service investment   moral hazard   mechanism design     
Received 2016-08-18; published 2019-09-16
Corresponding Authors: 唐国锋     Email: cqguofengtang@163.com
唐国锋,李丹.考虑服务投资影响的SaaS云外包激励机制研究[J]  科研管理, 2019,V40(9): 170-180
Tang Guofeng, Li Dan.Incentive mechanism in SaaS cloud outsourcing by considering the impact of service investment[J]  Science Research Management, 2019,V40(9): 170-180
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