首都经济贸易大学学报2026，Vol.28Issue(2)：16-28,13.DOI:10.13504/j.cnki.issn1008-2700.2026.02.002
数据、算法、算力要素赋能智能经济的理论逻辑与实践路径
The Theoretical Logic and Practical Path of Data,Algorithm,and Computing Power Factors to Empower the Intelligent Economy
摘要
Abstract
As an advanced form of digital economy,the intelligent economy is becoming a key engine for high-quality economic development.Its core driving force comes from the collaborative empowerment of three new pro-duction factors:data,algorithm,and computing power.Based on the analytical framework of historical materialism and endogenous growth theory,this paper systematically demonstrates the historical inevitability of the evolution of the three major factors into basic production factors,and constructs the theoretical logic of the three-dimensional coupling of"data(value carrier)-algorithm(decision engine)-computing power(basic support)".This paper holds that the three major factors realize the release of endogenous growth momentum through the capitalization process,and the data experience the butterfly process of"resource-asset-capitalization".The algorithm forms tech-nical barriers and competitive advantages through the intellectual property system,and the computing power con-structs the infrastructure ecology through economies of scale and financial innovation.The three jointly reshape the production function and promote the leap of new quality productive forces.The internal mechanism is reflected in the positive feedback cycle and multiplier amplification effect.Data provides fuel for algorithm training,and com-puting power provides support for algorithm operation.The algorithm creates new knowledge output by mining data value and improving computing power efficiency,thus forming a new resource allocation mode of"data traction,al-gorithm regulation,and computing power drive". This paper further reveals that the three major factors still face systematic challenges in the process of capitali-zation accumulation,such as the governance paradox between data non-rivalry and capital exclusivity,the aliena-tion of labor process caused by the black box of algorithms,the global power imbalance in the distribution of com-puting resources,and the impact of the organic composition of digital capital on the traditional employment struc-ture.Given the above problems,this paper puts forward the following policy implications and practical paths:(1)deeply cultivating intelligent ecology,and building an independent R&D system covering key technology break-throughs,systematic innovation,and open-source ecological construction;(2)deepening institutional innovation to improve the governance framework of data property rights definition,algorithm responsibility identification,and computing power resource allocation;(3)deepening policy coordination to coordinate technological innovation,in-dustrial development,personnel training and regional coordination policies;(4)grasping the integration of human and machine,and innovating the knowledge education system and labor protection mechanism.By clarifying the in-ternal mechanism and value transformation path of the collaborative empowerment of the three factors,this paper provides more targeted theoretical support and decision-making basis for policymakers to optimize the factor alloca-tion and cultivate new quality productive forces.关键词
智能经济/数据/算力/算法/要素化/新质生产力Key words
intelligent economy/data/computing power/algorithm/factorization/new quality productive forces分类
管理科学引用本文复制引用
冯科..数据、算法、算力要素赋能智能经济的理论逻辑与实践路径[J].首都经济贸易大学学报,2026,28(2):16-28,13.基金项目
国家社会科学基金重点项目"数字经济推动农村地区共同富裕的机制与路径研究"(22AJL008) （22AJL008）
