喆学（185）：精读硕士论文SaaS云外包激励机制的应用和结束语

摘要：This post will introduce the application and conclusion of the SaaS cloud Outsourcing incentive mechanism of the intensive reading

分享兴趣，传播快乐，

增长见闻，留下美好。

亲爱的您，这里是LearingYard学苑！

今天小编为您带来文章

“喆学（185）：精读硕士论文

《双重信息不对称下SaaS云外包激励机制研究》

SaaS云外包激励机制的应用和结束语”

欢迎您的访问！

Share interest, spread happiness,

increase Knowledge, and leave beautiful.

Dear, this is the LearingYard Academy!

Today, the editor brings the

“Zhexue (185): Intensive reading of

《Research on the Incentive Mechanism of SaaS Cloud outsourcing

under Double Information Asymmetry》

Application and conclusion of SaaS cloud outsourcing incentive mechanism”

Welcome to visit!

本期推文将从思维导图、精读内容、知识补充三个方面介绍精读硕士论文《双重信息不对称下SaaS云外包激励机制研究》SaaS云外包激励机制的应用和结束语。

This post will introduce the application and conclusion of the SaaS cloud Outsourcing incentive mechanism of the intensive reading master's thesis "Research on the Incentive Mechanism of SaaS Cloud Outsourcing under Double Information Asymmetry" from three ASPects: mind map, intensive reading content, and knowledge supplement.

一、思维导图（Mind Maps）

二、精读内容（Intensive reading content）

(1) SaaS云外包激励机制的应用(Application of SaaS cloud outsourcing incentive mechanism)

1.云外包激励机制适用条件

1. Applicable conditions of cloud outsourcing incentive mechanism

本文针对多任务SaaS云外包，构建多任务与两阶段动态委托代理模型，用逆向归纳法求解最优激励系数。机制适用于含独立软硬件服务的多任务场景，单任务或云商主导合同不适用。激励效果受云商市场占比、风险规避度、成本系数及任务波动方差影响，企业须先调研这些参数，才能设定有效线性激励合同。

This paper constructs a multi-task and two-stage dynamic principal-agent model for multi-task SaaS cloud outsourcing and uses the backward induction method to solve the optimal incentive coefficient. The mechanism is applicable to multi-task scenarios with independent software and hardware services. It is not applicable to single-task or cloud vendor-led contracts. The incentive effect is affected by the cloud vendor's market share, risk aversion, cost coefficient, and task volatility variance. enterprises must first investigate these parameters before setting up effective linear incentive contracts.

2.SaaS云外包激励机制应用场景

2. Application Scenarios of SaaS Cloud Outsourcing Incentive Mechanisms

本文激励机制适用于两类场景：一是云商同时提供硬件（基建部署维护）与软件（开发升级）服务，静动态机制均可甄别能力并激励最优努力；二是客户通过平台分别选AIP负责硬件、ASP负责软件，仅静态机制适用，可识别双方能力并激励其投入。

This incentive mechanism applies to two scenarios: First, when cloud providers provide both hardware (infrastructure deployment and maintenance) and software (development and upgrades) services, both static and dynamic mechanisms can identify capabilities and incentivize optimal efforts. Second, when customers select an AIP to handle hardware and an ASP to handle software through the platform, only static mechanisms apply, identifying the capabilities of both parties and incentivizing their investment.

(2)结束语(Conclusion)

1.总结(Summary)

SaaS云外包以低成本、个性化破解企业信息化难题，其健康运行依赖合理契约。本文从硬件与软件双任务出发，构建多任务及两阶段动态委托代理模型，用MATLAB数值实验确定并验证最优激励参数，剖析各因素对收益共享系数与两阶段激励的影响，为客户甄别服务商能力、激发高质量服务、降低信息不对称提供可操作工具，助力SaaS云外包市场持续发展。

SaaS cloud outsourcing solves enterprise informatization challenges with low cost and personalized services. Its healthy operation depends on reasonable contracts. Starting from the dual tasks of hardware and software, this paper constructs a multi-task and two-stage dynamic principal-agent model. MATLAB numerical experiments are used to determine and verify the optimal incentive parameters. The impact of various factors on the revenue sharing coefficient and two-stage incentives is analyzed. This paper provides operational tools for customers to identify service providers' capabilities, stimulate high-quality services, and reduce information asymmetry, thereby promoting the sustainable development of the SaaS cloud outsourcing market.

SaaS cloud outsourcing offers low-cost, personalized solutions to enterprise informatization challenges, but its healthy operation relies on sound contracts. Starting from the dual tasks of hardware and software, this paper constructs a multi-task and two-stage dynamic principal-agent model. Using MATLAB numerical experiments, it determines and verifies the optimal incentive parameters. It also analyzes the impact of various factors on the revenue sharing coefficient and two-stage incentives. This provides clients with actionable tools to identify service providers' capabilities, stimulate high-quality services, and reduce information asymmetry, thereby contributing to the sustainable development of the SaaS cloud outsourcing market.

2.展望(Outlook)

未来研究可从四方面拓展：一是引入客户知识投入，探讨双边道德风险；二是考虑软硬件成本替代，设计耦合多任务契约；三是由“一对一”扩展为“一对多”共享服务模式；四是突破线性合同，尝试分段、多项式等非线性激励方案，以完善SaaS云服务外包契约理论。

Future research can be expanded in four areas: first, incorporating customer knowledge input to explore bilateral moral hazard; second, considering the cost substitution of software and hardware to design coupled multi-task contracts; third, expanding from a "one-to-one" to a "one-to-many" shared service model; and fourth, moving beyond linear contracts to explore nonlinear incentive schemes such as segmented and polynomial incentives to improve SaaS cloud service outsourcing contract theory.

三、知识补充（Knowledge supplement）

在SaaS云外包中，软硬件成本之所以会出现“替代”，是因为两者在资源投入、技术路径和性能优化上存在此消彼长的权衡关系：

In SaaS cloud outsourcing, the "substitution" of software and hardware costs occurs because of a trade-off between resource investment, technology path, and performance optimization:

1.性能补偿

1.Performance Compensation

提升硬件配置（如更强CPU、更大内存）可以弥补软件算法效率不足，减少代码优化、重构所需的人力投入；反之，通过优化软件架构（如分布式缓存、压缩算法）可降低对高端硬件的依赖，用“代码换算力”。

Improving hardware configuration (such as a more powerful CPU or larger memory) can compensate for software algorithm inefficiencies and reduce the manpower required for code optimization and refactoring. Conversely, optimizing software architecture (such as distributed caching and compression algorithms) can reduce reliance on high-end hardware, effectively converting code into computing power.

2.资源预算约束

2. Resource Budget Constraints

客户总预算固定时，多花钱购置高规格IaaS就意味着用于软件二次开发、测试的预算被压缩；反之，投入更多人力做精细开发和调优，就能租用更低配的机器仍满足SLA。

When a customer's total budget is fixed, spending more on high-spec IaaS means reducing the budget for software secondary development and testing. Conversely, investing more manpower in detailed development and tuning can allow for the use of lower-spec machines while still meeting SLAs.

3.运维与升级场景

3. Operations and Upgrade Scenarios

硬件维保、扩容产生边际成本上升后，云商往往倾向用软件层自动伸缩、容器化等手段来延缓设备追加；同样，若软件升级周期长，也可先靠横向加机器扛住业务增长，把开发成本“延时”。

As marginal costs for hardware maintenance and capacity expansion increase, cloud providers often use software-layer autoscaling and containerization to delay equipment additions. Similarly, if software upgrade cycles are long, they can initially add machines horizontally to accommodate business growth and "delay" development costs.

4.共享与复用

4. Sharing and Reuse

在“一对多”共享模式下，同一套高端硬件被多租户复用，摊薄了单客户成本，使客户更愿意接受“买硬件服务”而减少自研软件功能；若硬件无法复用，则倾向把功能做到软件层以共享代码，降低单客户硬件开销。

In a "one-to-many" sharing model, the same high-end hardware is reused by multiple tenants, diluting the cost per customer and making them more willing to "buy hardware as a service" and reduce the need for in-house developed software features. If hardware reuse is not possible, there is a tendency to move functionality to the software layer to share code and reduce hardware costs per customer.

因此，硬件投入和软件投入并非完全独立，而是可以通过“以硬换软”或“以软换硬”相互替代，导致成本结构出现弹性，这正是契约设计中需考虑成本替代强度的原因。

Thus, hardware and software investments are not completely independent; rather, they can be interchanged through "hardware for software" or "software for hardware," leading to cost flexibility. This is precisely why cost substitution intensity must be considered in contract design.

今天的分享就到这里了。

如果您对文章有独特的想法，

欢迎给我们留言，让我们相约明天。

祝您今天过得开心快乐！

That's all for today's sharing.

If you have a unique idea about the article,

please leave us a message,

and let us meet tomorrow.

I wish you a nice day!

翻译：谷歌翻译

参考资料：谷歌、Chat GPT

参考文献：吴琦超. 双重信息不对称下SaaS云外包激励机制研究 [D]. 合肥工业大学, 2020.