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“喆学（217）：精读博士论文
《软件平台系统的治理策略与第三方开发商的接入决策研究》
软件平台的跟进性技术投资策略与定价决策（3）”
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Dear, this is the LearingYard Academy!
Today, the editor brings the
“Zhexue (217): Intensive reading of doctoral thesis
“Research on the Governance Strategy of Software Platform Systems
and the Access Decisions of Third-Party Developers”
Software platform follow-up technology investment strategy and pricing decision (3)”
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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博士论文《软件平台系统的治理策略与第三方开发商的接入决策研究》软件平台的跟进性技术投资策略与定价决策。
This post will introduce the doctoral dissertation "Research on Governance Strategies of Software Platform Systems and Access Decisions of Third-Party Developers" from three aspects: mind map, in-depth reading content, and knowledge supplement.
一、思维导图（Mind Maps）
二、精读内容（Intensive reading content）
1.内生平台2最优投资技术功能水平(Optimal Investment Technology Function Level of Endogenous Platform 2)
在平台 2 制定投资策略并选择投资功能水平的情境中，通过逆向归纳与最优化分析可知：当单位开发技术成本较低时，平台 2 会选择最高技术水平，以此在竞争中获得显著优势；当成本较高时，平台 2 需权衡投资带来的收益增长与成本支出，最终选择低于最高值的技术水平。
In the scenario where Platform 2 formulates its investment strategy and selects its investment function level, backward induction and optimization analysis reveal that: when the unit development technology cost is low, Platform 2 will choose the highest technology level to gain a significant competitive advantage; when the cost is high, Platform 2 needs to weigh the increased returns from investment against the cost expenditure, ultimately choosing a technology level lower than the highest value.
该部分研究表明，平台开发技术的单位成本会直接影响最优技术水平的选择：当成本较低时，平台 2 的最优技术水平会超过平台 1；当成本较高时，其最优技术水平则会落后于平台 1。同时，研究还通过数值实验，在成本较低的场景下，分析了用户与开发商双向的网络效应对平台 2 最优技术水平的具体影响，相关结论可从对应图表与观察结果中得到验证。
This part of the research shows that the unit cost of platform development technology directly affects the selection of the optimal technology level: when the cost is low, Platform 2's optimal technology level will exceed that of Platform 1; when the cost is high, its optimal technology level will lag behind that of Platform 1. Furthermore, the study also analyzed the specific impact of the bidirectional network effect between users and developers on the optimal technology level of Platform 2 in a low-cost scenario through numerical experiments. The relevant conclusions can be verified from the corresponding charts and observations.
该部分研究揭示了用户到开发商的网络效应对平台 2 最优技术水平的影响。观察发现，随着这一网络效应的增强，平台 2 的最优技术水平会随之提升。这是因为网络效应增强会提升开发商加入平台的意愿，此时平台 2 主动提高技术水平，一方面能增强自身在与平台 1 竞争中的优势，吸引更多用户加入；另一方面，用户规模的扩大又会通过网络效应进一步提升开发商的收入，帮助他们弥补整合技术所付出的成本，从而维持开发商的加入意愿，最终推动平台整体收益增长。对应的实验图表也直观呈现了这一正相关关系，不同初始技术水平的曲线均随网络效应强度的提升而上升，验证了上述结论。
This part of the research reveals the impact of the user-to-developer network effect on the optimal technology level of Platform 2. Observations show that as this network effect strengthens, the optimal technology level of Platform 2 increases accordingly. This is because enhanced network effects increase developers' willingness to join the platform. Platform 2 then proactively improves its technology, which on the one hand strengthens its competitive advantage over Platform 1, attracting more users; on the other hand, the expanded user base further increases developers' revenue through network effects, helping them offset the costs of integrating technology, thus maintaining developers' willingness to join and ultimately driving overall platform revenue growth. The corresponding experimental charts visually demonstrate this positive correlation; the curves for different initial technology levels all rise with increasing network effect strength, validating the above conclusion.
研究发现，开发商到用户的网络效应对平台 2 最优技术水平的影响，会因用户到开发商的网络效应强度不同而变化：前者强度较小时，平台 2 的最优技术水平会随其增加先升后降；前者强度较大时，平台 2 的最优技术水平则会随其增加持续上升，这一规律也在对应实验图表中得到验证。
The study found that the impact of the developer-to-user network effect on Platform 2's optimal technology level varies depending on the strength of the user-to-developer network effect: when the former is weak, Platform 2's optimal technology level initially increases and then decreases; when the former is strong, Platform 2's optimal technology level continuously increases, a pattern also verified in the corresponding experimental charts.
2.讨论与管理洞察(Discussion and Management Insights)
本章聚焦软件平台的跟进性技术投资策略，通过构建博弈模型，填补了竞争平台在该类技术投资决策上的研究空白。研究发现，当开发商整合技术与平台开发技术的单位成本均较低，或前者成本低、后者成本高但跟进平台的技术功能水平较低时，跟进投资是最优策略；反之则不应跟进。用户到开发商的网络效应增强会提升平台的投资意愿，而开发商到用户的网络效应的影响则取决于开发商的整合成本：整合成本高时，平台投资意愿会降低；整合成本低时，投资意愿会提高。此外，当平台决定投资时，若自身开发成本较低，可选择最高功能水平的技术以获取竞争优势；若开发成本较高，则需平衡收益与成本，选择中等功能水平的技术。
This chapter focuses on follow-up technology investment strategies for software platforms. By constructing a game theory model, it fills a research gap in the decision-making process for competitive platforms in this type of technology investment. The study finds that follow-up investment is the optimal strategy when the unit costs of developer integration technology and platform development technology are both low, or when the former is low and the latter is high but the follow-up platform's technology functionality is low; conversely, it should not be followed. Enhanced network effects from users to developers increase a platform's willingness to invest, while the impact of network effects from developers to users depends on the developer's integration costs: high integration costs decrease a platform's willingness to invest; low integration costs increase it. Furthermore, when a platform decides to invest, if its own development costs are low, it can choose the highest level of technology to gain a competitive advantage; if development costs are high, it needs to balance benefits and costs and choose a technology with a medium level of functionality.
本章研究为竞争软件平台的跟进性技术投资提供了多方面的实践启示。首先，研究明确了平台是否跟进投资的决策依据，重点考察技术功能水平、平台开发成本与开发商整合成本等因素，指出当两类成本均较低时，平台应选择跟进投资，这一点也得到了苹果与谷歌在应用内搜索技术上的实践印证。其次，研究能帮助平台根据技术功能水平、成本与网络效应等因素的变化动态调整投资策略，例如在开发商整合成本低但平台开发成本高时，若对方技术功能水平提升，不跟进反而可能成为最优选择；而用户到开发商的网络效应增强时，则应考虑跟进。最后，研究还提示先投资技术的平台，需通过持续优化技术、强化技术壁垒来巩固竞争优势，如苹果在 AR 工具上的迭代升级。
This chapter provides several practical insights for competitive software platforms' follow-up technology investments. First, the study clarifies the decision-making criteria for platforms to follow up on investments, focusing on factors such as the level of technical functionality, platform development costs, and developer integration costs. It points out that when both types of costs are low, platforms should choose to follow up on investments, a point corroborated by the practices of Apple and Google in in-app search technology. Second, the study helps platforms dynamically adjust their investment strategies based on changes in factors such as the level of technical functionality, costs, and network effects. For example, when developer integration costs are low but platform development costs are high, not following up might be the optimal choice if the other party's technical functionality improves; conversely, when the network effect from users to developers strengthens, following up should be considered. Finally, the study also suggests that platforms that invest in technology first need to consolidate their competitive advantage by continuously optimizing the technology and strengthening technological barriers, as exemplified by Apple's iterative upgrades to AR tools.
三、知识补充（Knowledge supplement）
平台生态系统是以平台为核心，由多类相互依赖的参与主体共同构成的价值共创系统。平台通过规则、技术接口和治理机制，协调各主体之间的互动，而非通过传统层级控制实现价值创造。
A platform ecosystem is a value-co-creating system centered on a platform and comprised of multiple interdependent participants. The platform coordinates interactions among these participants through rules, technical interfaces, and governance mechanisms, rather than through traditional hierarchical control, to achieve value creation.
平台核心是生态系统的枢纽，负责基础设施建设、标准制定和治理安排。互补者包括开发者、内容提供者、服务商等，他们围绕平台提供差异化互补产品与服务。用户是需求侧主体，部分平台中用户同时具备生产者和消费者的双重身份。
The platform core is the hub of the ecosystem, responsible for infrastructure development, standards setting, and governance arrangements. Complementors include developers, content providers, and service providers, who offer differentiated and complementary products and services around the platform. Users are the demand-side participants; on some platforms, users simultaneously act as both producers and consumers.
平台生态系统通常由以下几个核心要素构成：
A platform ecosystem typically consists of the following core elements:
1.平台核心(Platform Core)
作为生态系统的中心主体，平台核心负责提供基础设施与制度框架，包括技术支持、交易撮合以及整体规则设计，如准入规则、分配机制和治理结构。
As the central entity of the ecosystem, the platform core is responsible for providing infrastructure and the institutional framework, including technical support, transaction matching, and overall rule design, such as access rules, allocation mechanisms, and governance structures.
2.互补者（Complementors）
指依托平台提供互补产品或服务的参与主体，例如开发者、商家、内容创作者或第三方服务商，其创新和供给丰富了平台生态的价值。
These are participants who provide complementary products or services through the platform, such as developers, merchants, content creators, or third-party service providers. Their innovation and supply enrich the value of the platform ecosystem.
3.终端用户(End Users)
作为生态系统中价值实现的最终接受者，终端用户通过平台消费或使用互补者提供的产品与服务，其规模和活跃度直接影响平台生态的扩展与稳定。
As the ultimate recipients of value realization within the ecosystem, end users consume or use products and services provided by complementary partners through the platform. Their scale and activity directly impact the expansion and stability of the platform ecosystem.
4.技术架构(Technical Architecture)
包括平台提供的技术基础设施与接口体系，如 API、数据接口、算力资源、算法工具等，是连接平台核心与生态参与者、支撑价值共创的关键基础。
This includes the platform's technical infrastructure and interface system, such as APIs, data interfaces, computing resources, and algorithm tools. It is a crucial foundation connecting the platform's core with ecosystem participants and supporting value co-creation.
5.治理机制(Governance Mechanisms)
平台通过定价策略、激励与分成机制、行为约束、审核制度以及声誉与评价体系，对生态成员的行为进行协调和约束，以维持生态系统的健康运行。
The platform coordinates and constrains the behavior of ecosystem members through pricing strategies, incentive and revenue-sharing mechanisms, behavioral constraints, auditing systems, and reputation and evaluation systems to maintain the healthy operation of the ecosystem.
与传统产业链或供应链相比，平台生态系统在多个关键维度上存在显著差异：
Compared to traditional industrial or supply chains, platform ecosystems differ significantly in several key dimensions:
1.组织结构方面(Organizational Structure)
传统供应链通常呈现线性、层级化结构，上下游关系相对固定；而平台生态系统采用网络化、多边结构，不同参与主体通过平台进行并行连接与互动。
Traditional supply chains typically exhibit a linear, hierarchical structure with relatively fixed upstream and downstream relationships; while platform ecosystems adopt a networked, multilateral structure, with different participants connecting and interacting in parallel through the platform.
2.价值创造方式方面(Value Creation Methods)
在传统供应链中，价值主要由核心企业主导并沿链条逐级传递；平台生态系统则强调多主体参与下的价值共创，平台、互补者与用户共同参与价值生成过程。
In traditional supply chains, value is primarily driven by the core enterprise and passed down the chain level by level; platform ecosystems emphasize value co-creation through the participation of multiple stakeholders, with the platform, complementary partners, and
3.主体关系类型方面(Types of Stakeholder Relationships)
传统供应链中的企业关系以正式合同和长期合作为主，角色分工较为明确；平台生态系统中则普遍存在合作与竞争并存的关系，生态成员之间具有一定的替代性与博弈性。
In traditional supply chains, enterprise relationships are mainly based on formal contracts and long-term cooperation, with relatively clear role divisions; in platform ecosystems, relationships generally involve both cooperation and competition, with ecosystem members exhibiting a degree of substitutability and game theory.
4.控制与协调机制方面(Control and Coordination Mechanisms)
传统供应链依赖所有权安排和合同条款进行控制与协调；平台生态系统更多通过平台规则、算法机制和技术接口实现对生态成员行为的间接治理。
Traditional supply chains rely on ownership arrangements and contractual terms for control and coordination; platform ecosystems achieve indirect governance of ecosystem member behavior more through platform rules, algorithmic mechanisms, and technical interfaces.
5.系统边界方面(System Boundaries)
传统供应链的组织边界相对清晰且稳定；平台生态系统的边界具有开放性和动态性，新参与者可持续进入，生态结构随技术与市场环境不断演化。
The organizational boundaries of traditional supply chains are relatively clear and stable; the boundaries of platform ecosystems are open and dynamic, allowing new participants to continuously enter, and the ecosystem structure evolves with technological and market environments.
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翻译：谷歌翻译
参考资料：谷歌、Chat GPT
参考文献：苑楠. 软件平台系统的治理策略与第三方开发商的接入决策研究 [D]. 天津大学, 2022.
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