Coordination and Collaborative Value Creation Mechanisms: from a Transactional Platform to an Innovative Ecosystem

Abstract

In the context of the implementation of the national project «Data Economy», the classic transactional model of digital platforms is showing signs of exhausting its extensive growth potential: user base growth is slowing, customer acquisition costs are rising, and bilateral network effects are stagnating. The relevance of this study is determined by the need to ensure technological sovereignty and sustainable growth of the platform sector of the economy. The goal of the study is to identify and systematize the coordination mechanisms that enable the transformation of transactional platforms into innovative ecosystems based on value co-creation. The object of the study is digital platforms and business ecosystems, and the subject is the mechanisms for participant coordination and value co-creation. The methodology combines a conceptual synthesis of theories of platform economics, ecosystem management, and service-dominant logic with a case study of the practices of the largest Russian B2C ecosystems based on open sources. The author proposes a platform evolution matrix reflecting the transition from directive management of closed resources to the orchestration of open architecture, and systematizes three groups of coordination mechanisms: institutional, architectural, and informational. Predictive and generative AI algorithms, combined with compositional network effects, are shown to form the core of an innovation ecosystem. A two-block metric system has been developed demonstrating the economic efficiency of the transition: service integration and cross-use of data reduces marginal user acquisition costs by 30-40% and increase the LTV/CAC ratio by 1.5-2 times. The practical significance lies in the development of a toolkit for platform orchestrators in developing institutional and technological rules that incentivize complementors to engage in collaborative innovation. Future research opportunities lie in adapting the matrix to the conditions of industrial B2B ecosystems and quantitatively verifying the proposed metrics.