The Innovation Drivers of Digital Policy: How Firm Cost Heterogeneity Reshapes the Innovation Feedback Loop

The Paradox of Innovation in the Digital Age: How Cost Heterogeneity Reshapes Policy Effectiveness

The traditional paradigm of corporate innovation research focused on internal endowments—such as technological capabilities, human capital, and strategic orientation. However, with the leap in digital technology, the focus has rapidly shifted to Digital Transformation, which refers to how enterprises reshape resource allocation, production models, and business culture by integrating digital technologies to achieve leaps in efficiency and build competitive advantages. Digitalization is not just a tool for improving operational efficiency; it is a systemic force driving structural change within enterprises.

At the micro level, the application of digital technologies in production management and supply chain collaboration (such as BIIoT and blockchain) is profoundly changing the structure of enterprises, enhancing technological innovation and operational efficiency. Through these technologies, enterprises can achieve fine-tuned production scheduling and optimized resource allocation, thereby generating new points of value discovery alongside efficiency gains. This endogenous structural optimization means that corporate innovation is no longer just an isolated R&D activity but is closely coupled with systemic changes in the enterprise's organizational form.

However, this micro-level innovative behavior is ultimately shaped by the macro external environment—especially government digitalization policies. Literature points out that external factors, particularly government guidance, have a decisive impact on corporate innovation. In the pursuit of digital transformation, enterprises face not a single external pressure, but the challenge of "heterogeneous feedback" based on their own transformation costs.

The core analytical logic is this: digital transformation is not a uniform "one-size-fits-all" process for all enterprises. Different groups of enterprises with varying costs react significantly differently to government policies. Enterprises with lower digital transformation costs can more smoothly convert policy benefits into innovation drivers, providing positive feedback; whereas those with high transformation costs tend to respond to policies more cautiously and strategically, sometimes exhibiting localized, tactical responses due to financing constraints and connectivity barriers. This directly leads to structural differences in policy effectiveness when stimulating their innovation output.

This cost heterogeneity essentially reveals a key blind spot in current policy design: the effectiveness of a policy does not depend on the breadth of its grand narrative, but rather on its precise empowerment tailored to the differences among various subjects.This cost heterogeneity essentially reveals a key blind spot in current policy design: the effectiveness of a policy does not depend on the scope of its grand narrative, but on its precise enablement of different stakeholders.

To maximize policy effectiveness, mechanisms must focus on solving the core pain points for enterprises on their digital transformation path: reducing the "trilemma" of digital transformation—namely, connectivity costs, integration costs, and financing costs. When enterprises can effectively lower these barriers to entering the digital ecosystem, their response to government-guided policies will shift from "passive acceptance" to "active driving." Low-cost enterprises not only achieve digital transformation faster but also enhance their ability to acquire information and adapt in the external world, creating a positive feedback loop: low cost $\rightarrow$ faster transformation $\rightarrow$ stronger innovation output $\rightarrow$ more positive and constructive feedback on government policies $\rightarrow$ more precise optimization signals for policymakers.

From a global perspective, developed countries have taken a forward-looking approach at the level of industrial digital strategy, laying the technological and standard groundwork for the digital transformation of manufacturing. However, the challenge for developing economies lies in building a flexible policy system that can both guide technology adoption and accommodate the financing needs of small and medium-sized enterprises. Future policymakers need to move beyond simple subsidy models to build a multi-level, layered support network, tailoring digital roadmaps to different cost groups of enterprises, thereby transforming the macro digital vision into micro-level, achievable innovation actions for businesses.

In short, the success of a policy is no longer about "whether a digital policy is issued," but rather "how the policy is designed to effectively reduce the friction costs for enterprises to enter digital innovation." This demands that policy design possess high flexibility and granularity to adapt to the dynamic adaptive capabilities of enterprises as they continuously adjust during their transformation journey.