Core Viewpoint - The article emphasizes the importance of establishing a payment mechanism for high-quality data as a fundamental requirement for the marketization and valuation of data, which is essential for fostering a robust data market and enhancing the digital economy's growth potential [1][2][4]. Group 1: Importance of Paying for Quality Data - Paying for quality data is essential for recognizing its intrinsic value as a new production factor and is a key measure to overcome current data circulation challenges [1][2]. - The payment mechanism serves as a cost compensation and innovation incentive for data "factorization," ensuring that the value of data is recovered and distributed effectively [2][5]. - The market demand for quality data is rapidly increasing, with over 4,500 data products listed on the Shanghai Data Exchange in 2024, leading to a transaction volume exceeding 4 billion RMB, reflecting a diverse supply and rising value [3][4]. Group 2: Mechanisms and Challenges - The payment mechanism acts as a benchmark for data "valuation," helping to reflect market demand for different types and qualities of data, thus guiding data flow to areas where it can create the most value [4][5]. - There are significant challenges in recognizing the value of quality data, including a lack of stable payment expectations and insufficient capabilities of data circulation service institutions [7][8]. - The establishment of a payment mechanism is crucial for building a fair and efficient data market system, addressing issues like information asymmetry and enhancing transaction efficiency [5][6]. Group 3: Market Awareness and Cultural Shift - Cultivating a market culture that values payment for quality data is necessary for deepening market-oriented reforms and stimulating the internal growth of the digital economy [8][9]. - Government departments are encouraged to take the lead in establishing data transaction-related systems and promoting a consensus on the value of data [8][9]. - Enterprises should recognize the strategic value of paying for quality data as a means to enhance competitiveness and innovation capabilities, viewing it as a critical investment for future growth [9][10]. Group 4: Future Directions - There is a need to accelerate the development of a data factor market and enhance the positive incentives for paying for quality data, which will help eliminate low-quality data and ensure reasonable returns for quality providers [10][11]. - Establishing a unified data quality governance system and developing third-party evaluation and certification mechanisms are essential for improving market trust and reducing risks associated with information asymmetry [10][11]. - Supporting various data transaction models and financial products, such as data asset pledge financing and data insurance, will facilitate the flexible allocation of data across different scenarios [10][11].

专题：2025中国企业竞争力年会 "2025中国企业竞争力年会"于12月9日至10日在北京举行。中经传媒智库特聘研究员、道衍数科（杭 州）联合创始人梁超杰，华科融资租赁有限公司常务副总裁杨星统一股份总经理，统一石化CEO李嘉， 深圳国家高技术产业创新中心大数据平台与信息部部长、中国科学技术情报学会创新情报专业委员会主 任委员卢春江， 景区交易数据要素化文化和旅游部技术创新中心主任、票付通创始人CEO苏万生， 北 京清竞数智科技有限公司CTO王吴越等共同探讨"数据要素市场如何赋能千行百业"。 王吴越强调，数据供给的核心是适配人工智能发展需求，"当前数据热点已从传统数据库转向人工智能 原生数据（AINet），供得出的先决条件是将数据加工为标准化高质量数据集"。他介绍，团队通过参与 国家数据局高质量数据集评测平台建设、与深圳数据交易所合作可信数据空间项目，实现了大模型语料 训练数据的合规交付，而可信数据空间技术则成为加速数据流通的关键工具。在政务数据应用中，其技 术支撑已落地海淀区公共数据智能体评测场景，验证了标准化数据与技术工具的协同价值。 票付通苏万生聚焦文旅场景的公共数据应用痛点，分享了特殊人群优惠购票的数据 ...

Core Insights - The "2025 China Enterprise Competitiveness Conference" was held in Beijing on December 9-10, showcasing the advancements of Qingdao Data Group in public data operations and its strategic business segments [3][6]. Group 1: Business Segments - Qingdao Data Group has developed four core business segments: data operation and service transactions, data industry investment, artificial intelligence model research, and data infrastructure construction [3][6]. - The data operation segment includes the establishment of a public data operation center, data asset registration and evaluation center, and a big data trading center [3][6]. Group 2: Public Data Operations - The group has integrated over 700 million data resources through social data collaboration, utilizing trusted data spaces and data hosting models for data fusion [3][6]. - Qingdao Data Group focuses on market demands by creating nine specialized areas, including finance, healthcare, marine, smart manufacturing, and electronic guarantees, supporting over 20 applications for various municipal departments [3][6]. Group 3: Data Asset Transformation - The company has established a national first data asset registration and evaluation center, promoting the "Qingdao Model" for data asset incorporation [4][7]. - The transformation of data resources into assets is facilitated through compliance reports, data property registration, value evaluation reports, and cost aggregation reports, a model adopted by over 50 cities nationwide [4][7]. Group 4: Capitalization and Industry Empowerment - Qingdao Data Group leads the establishment of the first national data asset securitization alliance, with a 2 billion yuan data asset securitization project currently applied for at the Shenzhen Stock Exchange, with plans for issuance at the Shanghai Stock Exchange [4][7]. - The group is also pioneering data asset equity practices, enabling data to participate in social distribution as a production factor, thereby allowing financial institutions to treat data as an asset [4][7].

青岛数据集团首席数据官 赵传启：青岛数据集团定位于公共数据运营，通过场景和创新对公共数据进 行开发利用，赋能120余家企业完成数据资产入表，10余家企业开展数据资产证券化和数据资产质押， 探索出一条"运营赋能+服务变现"的可持续经营和盈利路径，形成"以公共数据运营撬动数据要素市 场"的发展模式。 0:00 ...

数据确权、入表、定价均应围绕数据产品展开。 近期，国家数据局组织12家央企牵头开展首批国有企业数据资源开发利用试点工作，标志着数据要素市 场化正式从"政策框架搭建"迈入"实体实践破冰"关键阶段。作为国民经济关键领域核心数据持有者、产 业链供应链枢纽，央国企牵头试点不仅关乎自身数据价值释放，更对全行业确立数据治理规范、打通资 产化路径具有全局示范意义。 面对数据要素价值释放中"不敢开放、不愿流通"的核心堵点，以及数据汇聚、价值挖掘等现实难题，证 券时报记者专访了拥有丰富地方大数据治理实践经验的原海南省大数据管理局局长董学耕，深度剖析央 国企试点的独特价值、破局路径与数据要素市场的长远发展方向。 央国企为何成为数据要素市场"先锋队"? 证券时报：数据要素市场化从政策走向实践，央国企作为试点主力，在核心数据禀赋、产业链枢纽地位 上的独特价值是什么?"国家队"引领模式对全国数据资源有序释放有哪些基础作用? 董学耕：在数据要素市场化从政策走向实践的关键转折期，央国企作为试点主力，其独特价值源于我国 经济体制的核心特征，在能源、电力、通信等国民经济关键基础领域，央国企占据主导地位，核心数据 资源也主要由其掌握。因此，由央 ...

Core Viewpoint - The article discusses the transition of data factor marketization from policy framework to practical implementation, highlighting the role of state-owned enterprises (SOEs) as pioneers in this process [1][2]. Group 1: Role of State-Owned Enterprises - SOEs are positioned as key players in the data factor market due to their dominance in critical sectors like energy, electricity, and telecommunications, where they hold significant data resources [2]. - The selection of SOEs as pilot entities aims to leverage their influence to encourage other market participants, including private enterprises, to engage in the orderly release of data resources [2]. Group 2: Balancing Data Security and Value Release - A critical aspect of the pilot program is balancing data security with value release, which is essential for encouraging participation from small and medium-sized enterprises (SMEs) [3]. - The approach involves assessing security needs based on specific application scenarios to ensure that safety measures are appropriately matched to data risk levels [3]. Group 3: Establishing Trustworthy Data Spaces - The concept of a "trustworthy data space" is emphasized as a foundational infrastructure for data circulation, combining technical support with a comprehensive regulatory framework [4][5]. - Two types of trustworthy data spaces are identified: enterprise-level and industry-level, with the former being more practical for current pilot initiatives [5][6]. Group 4: Data Productization and Assetization - The article stresses that data assetization should focus on data products, which are defined by their ability to generate cash flow and provide measurable benefits [8][9]. - The process of data assetization should follow a sequence of productization before moving to assetization, ensuring that data products are linked to stable revenue streams [9]. Group 5: Goals and Feasibility of the Pilot Program - The pilot program aims to engage over 100,000 SMEs by 2027, leveraging the established ecosystems of the participating SOEs to provide data services that meet the needs of various industries [10]. - The initiative is expected to extend its impact beyond directly associated enterprises, encouraging participation from local state-owned enterprises and private companies [10]. Group 6: Long-term Development of the Data Factor Market - For the long-term success of the data factor market, three areas need improvement: institutional development, spatial expansion, and stakeholder collaboration [11]. - SOEs are tasked with leading by example, while local governments and data exchanges play supportive roles in facilitating data product transactions and ensuring policy alignment [11]. Group 7: Integration with Artificial Intelligence - The pilot program also aims to support the development of high-quality industry data sets necessary for training AI models, thereby enhancing the capabilities of technology companies and benefiting SMEs [12].

数据确权、入表、定价均应围绕数据产品展开。 近期，国家数据局组织12家央企牵头开展首批国有企业数据资源开发利用试点工作，标志着数据要素市场化正式从"政策框架搭建"迈入"实体实践破冰"关键阶段。 作为国民经济关键领域核心数据持有者、产业链供应链枢纽，央国企牵头试点不仅关乎自身数据价值释放，更对全行业确立数据治理规范、打通资产化路径具有全 局示范意义。 面对数据要素价值释放中"不敢开放、不愿流通"的核心堵点，以及数据汇聚、价值挖掘等现实难题，证券时报记者专访了拥有丰富地方大数据治理实践经验的原海 南省大数据管理局局长董学耕，深度剖析央国企试点的独特价值、破局路径与数据要素市场的长远发展方向。 央国企为何成为数据要素市场"先锋队"？ 证券时报：数据要素市场化从政策走向实践，央国企作为试点主力，在核心数据禀赋、产业链枢纽地位上的独特价值是什么？"国家队"引领模式对全国数据资源有 序释放有哪些基础作用？ 董学耕： 在数据要素市场化从政策走向实践的关键转折期，央国企作为试点主力，其独特价值源于我国经济体制的核心特征，在能源、电力、通信等国民经济关键 基础领域，央国企占据主导地位，核心数据资源也主要由其掌握。因此，由央国企 ...

Core Viewpoint - The development vitality and resilience of the private economy in Henan Province are directly related to the effectiveness of resource allocation and the strength of element guarantees, as highlighted in the recent press conference on high-quality development of the private economy in 2025 [1] Group 1: Energy - Investment in energy projects has exceeded 100 billion yuan for three consecutive years, with total installed power capacity surpassing 160 million kilowatts and renewable energy accounting for over 50% of installed capacity [2] - Private enterprises have significantly increased their participation in the energy sector, with over 90% of photovoltaic power stations and 70% of biomass power generation projects built by private companies [2] - The service level for obtaining electricity in Henan has reached a leading position nationwide, with the processing time for various user categories not exceeding 5 to 32 working days [2] Group 2: Data - Private enterprises are crucial contributors to the digital economy and data market construction, with the digital economy scale in Henan exceeding 2 trillion yuan [3] - The province has accelerated the construction of data infrastructure, achieving 247,300 5G base stations and a computing power scale of 9.8 EFlops [3] - Policies such as "computing power vouchers" have been introduced to reduce costs for enterprises, and several private companies have been recognized as key data enterprises for support [3] Group 3: Talent - The province is focused on breaking down institutional barriers to create a favorable talent development ecosystem for private enterprises, allowing for direct applications for professional titles without restrictions [4] - In 2023, 34,500 individuals directly applied for intermediate and senior professional titles, with 82% of evaluation institutions being private enterprises [4] - Financial support has been provided to 6,200 enterprises, with a total of 63.59 million yuan in one-time expansion subsidies to promote youth employment [4][5] Group 4: Land - The government is addressing land use challenges for private enterprises by ensuring equal allocation of land resources and optimizing land use policies [6] - The "Land Selection Cloud" platform is utilized to improve public infrastructure and optimize resource allocation based on market demand [6] - Flexible land supply models, such as long-term leasing and combined leasing and sale, are being implemented to lower land costs and improve approval efficiency [6]

一、读懂控价：品牌价格体系的 "稳定器" （一）控价的核心定义 控价即价格管控，指品牌通过策略、规则与技术，规范产品流通环节售价，确保其在合理区间，避免低 价倾销、乱价等破坏市场秩序的行为，维护价格稳定与公正。 在激烈的市场竞争中，品牌价格体系是生命线，混乱的价格会损害品牌形象、消费者信任与市场份 额。"控价" 作为维护价格稳定的核心手段，已成为品牌运营的关键。本文结合安托数据能力，解读科 学价格机制与高效投诉流程，助力品牌筑牢价格防线。 （二）品牌为何必须重视控价？ 科学价格机制是控价前提，结合安托数据经验，品牌可从三方面设计： （一）精准定位价格区间：双向测算 成本端：核算生产、研发、物流等全链路成本，设定最低售价以覆盖成本并留合理利润，避免渠道商低 价抛售。 市场端：借安托数据监测竞品价格、促销与份额，分析消费者价格接受度，设定指导价，平衡竞争与性 价比。 （二）分级设定价格体系：适配渠道场景 线上：官方旗舰店设 "标杆价"（与指导价一致，少大幅降价）；第三方店铺价格可浮动 5%-10%，需签 协议定最低价。 线下：实体店因额外成本，价格可高于线上 5%-15%，以线下体验弥补价差；商场专柜针对高端客群 ...

Group 1 - The 2025 Global Data Business Conference was held on November 25-26 at the Shanghai International Conference Center, showcasing the latest achievements and resources in the data field, attracting nearly ten thousand participants [1][3] - The exhibition area vividly interpreted the theme "Showcasing Diversity, Planting 'Data' to Form a Forest," highlighting the vibrant growth of the data ecosystem [1] - The "Data Element X" competition featured excellent projects, with numerous professional guests engaging in constructive discussions and frequent interactions [1] Group 2 - The conference included various segments such as the National Data Group Alliance Exhibition, Shanghai Digital Economy Achievement Exhibition, and Data Element Construction Exhibition, which gathered industry insights and forward-looking shares [3] - A special exhibition area created by China Unicom, Shanghai Data Group, Pudong New District, Huawei, Shanghai Yidian, and Chongqing Digital Resource Group attracted many professionals for exchange and discussion [5] - The invited enterprise exhibition area showcased over twenty outstanding companies, demonstrating their professional capabilities, innovative achievements, and application practices in the data field, fostering intense interaction and idea exchange among peers [5]