Research on the Sustainable Evolution Mechanism of Dual-Dimensional Convergence Innovation in Digital Products

Abstract

The complex characteristics of cross-disciplinarity, dynamic expansion, ambiguity, diversity, and the rapid changes in demand significantly amplify the uncertainties in digital product innovation. The existing innovation theories, such as “stage-gate”, open innovation, agile development, and data-driven decision making, are insufficient for fully and effectively addressing these uncertainties. Based on a case study of a fintech app, we reveal that digital product innovation is similar to biological evolution, exhibiting dual life-like features of “inheritance” and “mutation” within “dual-dimensional convergence”. However, unlike natural evolution, the evolutionary process of digital product innovation can augment its use of the digital ecosystem and capabilities, establish a data-driven rapid proactive selection mechanism for the main three stages, and quickly enhance product competitiveness. The complexity of knowledge in the innovation process can be partially solved through the use of a micro-knowledge integration learning mechanism formed by the interactions of social and cognitive translation. This study also discovers that market competition and policy regulation are two unique innovation-driven characteristics in digital product innovation. This mechanism can achieve the earlier clarification of product evolution’s direction, reduce the three major uncertainties of innovation, and improve efficiency in the utilization of innovation resources to achieve sustainable development.