The relationship between scientific knowledge—a critical input to technological systems—and invention value remains a central concern in science policy and innovation management. While existing studies have primarily focused on correlational analyses, yielding inconsistent findings, the integration of scientific knowledge into technological systems is not random but intimately linked to knowledge recombination patterns and invention team characteristics. The inconsistency in research findings likely stems from endogeneity issues caused by selection bias, which traditional regression analyses fail to address. Causal inference methods are thus necessary to accurately estimate the net causal effect of scientific knowledge on invention value, thereby providing more reliable evidence for science and technology policymaking.

Using a counterfactual causal framework, we employed Propensity Score Matching (PSM) and Generalized Propensity Score Matching (GPSM) to estimate the causal effects of both the presence and intensity of scientific knowledge inputs on patents' technological and commercial value. Existing measures of scientific knowledge input intensity focus solely on citation counts, overlooking variations in scientific literature impact. We address this limitation by developing the Patent Scientific Citation h-index (PSH), inspired by the h-index methodology, which integrates both quantitative and qualitative dimensions of scientific citations to more accurately assess patents' scientific knowledge absorption. We measured patents' technological value using two indicators: forward citation counts and technological generality. Commercial value was quantified through the frequency of patent transfers. Analyzing 1,685,970 utility patents granted by the USPTO (2001-2010) and their 6,473,214-citation links to 1,407,439 scientific papers, we established the following findings:

(1) Our findings demonstrate positive causal effects of scientific knowledge input on both the technological and commercial value of patents. Patents incorporating scientific knowledge receive significantly more forward citations than those without such inputs. This indicates that scientific knowledge integration enhances a patent's capacity to serve as a foundation for subsequent innovations. Moreover, scientific knowledge input significantly enhances patents' technological generality. Specifically, we observe that scientific knowledge incorporation enables the development of more influential general-purpose technologies. The theoretical mechanism underlying this relationship lies in how comprehensive scientific understanding enhances researchers' cognitive capabilities to effectively identify, access, and recombine knowledge from distant technological domains. Finally, patents incorporating scientific knowledge demonstrate significantly higher transfer frequencies compared to those without such knowledge inputs. This pattern suggests that science-based inventions exhibit enhanced potential for private value realization, primarily because established scientific frameworks provide a shared cognitive platform and common language among market participants.

(2) A nonlinear relationship exists between scientific knowledge input intensity and inventive value. Empirical analysis reveals a fluctuating "rise-decline-rise" pattern in patents' forward citations and transfer frequencies as the PSH index increases. Patents with either low or high PSH intensities demonstrate superior technological impact and market transaction potential. In low-PSH domains, moderate scientific knowledge integration maintains technological advancement while aligning with market cognition. Mid-range PSH shows diminishing returns due to potential divergence from user expectations. High-PSH patents leverage rich scientific knowledge to overcome technical barriers, yielding enhanced technological impact and market value. Regarding technological generality, our findings reveal that patents characterized by higher PSH indices embody more fundamental scientific principles. The universal applicability of these underlying principles facilitates technology extension and diffusion across diverse application contexts, resulting in enhanced levels of technological generality.

This study makes several significant contributions to the innovation policy literature. First, we employ a causal inference framework to establish the causal relationship between scientific knowledge input and inventive value. Second, we advance methodological development by introducing a novel approach that incorporates the H-index to quantify scientific knowledge input intensity. These empirically grounded findings provide robust evidence for optimizing science and technology policies, bridging the gap between theoretical frameworks and practical policy implementation.