Low carbon and digitalization are the general trends of manufacturing upgrading and transformation. Digital technology enables the whole process of green manufacturing and breaks down the spatial barrier. To achieve the dual carbon goals, the pressure-state-response (PSR) model, in which digital technology enables the green innovation of the manufacturing industry, was theoretically analyzed in this study. The measurement system of the digital green innovation (DGI) in the manufacturing industry was constructed according to the PSR framework. An evaluation model based on the analytic hierarchy process and the deviation maximization technique for order preference by similarity to an ideal solution method was constructed to measure the level of DGI. The results of this study from Chinese manufacturing are as follows. (i) The measurement system of the level of DGI in manufacturing industry includes a pressure system, state system and response system. (ii) In the past five years, the comprehensive index of the DGI in manufacturing industry has generally shown a trend of fluctuating rise. There are overall low and unbalanced phenomena in all regions. The gap decreased from 0.1320 to 0.1187, showing a gradually narrowing trend. (iii) Compared with other regions, the composite index of DGI is generally higher in the regions with a better ecological environment in the east and a more developed economy in the north. State parameters are higher than pressure and response parameters in most areas. (iv) Compared with other regions, the composite index of DGI in western and southern regions is lower, and the parameters of pressure, status and response are basically coordinated. (v) The application degree of digital technology, the emission intensity of waste water/exhaust gas of output value of one hundred million yuan and the expenditure intensity of digital technology adopted by enterprises are the key influencing factors of DGI in the manufacturing industry. This study not only proposed an evaluation index system of the digital green innovation level, but also puts forward policy guidance and practical guidance of digital technology to accelerate the green and intelligent manufacturing industry.

Digital green innovation management activities are the core of low-carbon intelligent development of prefabricated construction enterprises (PCEs) for sustainable urban development. PCEs have to seek joint venture partners to avoid the financial risk of digital green innovation projects. The purpose of this study is to develop a conceptual partner selection framework for the digital green innovation management of prefabricated construction towards urban building 5.0. In this study, first, symbiosis theory and six analysis methods were integrated to innovatively build a 3W1H-P framework system for the joint venture capital partner selection of digital green innovation projects. Second, the dual combination weighting method was innovatively proposed to avoid subjective and objective deviation in attribute weight and time weight. Finally, empirical research was carried out to verify the scientific nature, reliability, and practicability of the framework system and selection model. The results of this study show that the framework system and selection model proposed can be used to assist PCEs to select joint investment partners of digital green and innovative projects for sustainable urban development.

Rural revitalization has emerged as a core agenda in the global pursuit of sustainable development, with its success fundamentally hinging on enhancing the resilience of rural households to withstand shocks and restore their livelihoods. In contrast to mainstream research that primarily examines whether Medical Financial Assistance (MFA) reduces medical burden, this paper focuses on MFA as ex-post cash compensation and investigates whether and how it affects the sustainable livelihood recovery of low-income rural households following health shocks, thereby providing empirical evidence for understanding the foundational role of health security in rural revitalization. A quasi-natural experiment is constructed by leveraging the institutional feature that MFA eligibility is activated by exogenous health shocks. Using two-wave balanced panel data (2021–2022) from a nationally designated deep poverty-stricken county in Hebei Province, China, the Propensity Score Matching–Difference-in-Differences (PSM-DID) method and mediation models are employed for causal identification and mechanism testing. The findings indicate that (1) MFA significantly promotes household income recovery. It enables recipient households to recover per capita net income by an average of approximately 13.2% (p < 0.01), demonstrating a protective recovery effect, and simultaneously recovers per capita non-farm labor income by an average of approximately 13.8% (p < 0.05), revealing a developmental recovery effect. The latter is partially mediated by the non-farm labor participation rate (mediation ratio 51.7%, Sobel Z = 2.10). This finding validates the “time release effect,” demonstrating that MFA stimulates endogenous dynamics by restoring health capital and releasing labor previously constrained by family care responsibilities. It thereby extends the application of health capital theory from the individual to the household level. (2) Mechanism analysis shows that the protective recovery effect is fully mediated by the amount of MFA received (mediation ratio 326.7%, Sobel Z = 12.85), providing empirical evidence for precautionary saving theory in the context of targeted social assistance and revealing the potential productive attributes of the social safety net. (3) Heterogeneity analysis reveals clear group targeting and shock thresholds. The protective effect is concentrated among elderly households, while the developmental effect is primarily evident in middle-aged households. Both recovery effects manifest significantly only for households experiencing major disease shocks, confirming the theoretical expectation of “conditional effectiveness,” namely that policy effects are systematically moderated by household life-cycle characteristics and the severity of health shocks. This study demonstrates that MFA serves both as a safety net and an empowerment tool, but its effectiveness is highly contingent upon household characteristics and shock severity. By uncovering the foundational mechanisms through which health security contributes to rural household resilience, this study provides empirical evidence from China for building sustainable poverty prevention systems in the global process of rural revitalization.

Against the dual backdrop of the “dual carbon” goals and the digital transformation of the construction enterprises (CEs), green intelligent building technologies (GIBTs) have become the core driving force for improving quality and efficiency in the CEs and achieving low-carbon, sustainable development. Taking the collaborative innovation and development of GIBTs as the research context, this paper constructs an evolutionary game model involving three players (TPs), the government, CEs, and academic and research institutions (ARIs), to systematically analyze the evolution-stable strategies of the collaborative innovation system for GIBTs and their underlying mechanisms. The research findings indicate: (1) Government subsidy funds for collaborative innovation directed at both CEs and ARIs have distinct critical thresholds; the subsidy amount directly determines whether the system can converge to the ideal equilibrium of comprehensive three-player collaboration (participation, collaboration, collaboration). (2) The incentive effects of green incentives on the two types of innovation entities, CEs and ARIs, exhibit significant heterogeneity. Green incentives for CEs are highly sensitive core control parameters, while those for ARIs are weakly sensitive auxiliary parameters. (3) The cost-sharing ratios for research and development (R&D) between CEs and ARIs affect, respectively, the equilibrium level of the TPs collaboration and the stability of the system’s dynamic convergence. Relying solely on internal cost-sharing mechanisms between these two groups cannot achieve deep collaboration among TPs; it must be complemented by collaborative external policy adjustments such as government subsidy funds and green incentives. Such deep collaboration among TPs emphasizes the substantive enhancement of coordination efficiency and cooperative quality on the basis of full participation, reflecting the maturity and effectiveness of three-player innovation interaction. (4) Default penalties and the returns from CEs’ independent R&D constitute, respectively, the rigid constraint mechanism and the market-driven mechanism for collaborative innovation in GIBTs. Working in tandem, one exerting a restraining effect and the other a stimulating effect, they jointly regulate the cooperative behavior of CEs and ARIs, thereby resolving the dilemma of insufficient motivation for collaborative innovation in GIBTs. In terms of theoretical contributions, this study employs evolutionary game theory and numerical simulation methods to refine theories related to policy thresholds, differentiated incentives, collaborative governance, and the balance of benefits and risks among industry, ARIs. It also demonstrates that the underlying logic can serve as a reference for developing countries with similar industrial structures. In terms of practical contributions, this study recommends establishing subsidy allocation standards based on subsidy critical thresholds; implementing differentiated tax incentives for CEs, ARIs; scientifically designing R&D cost-sharing ratios; and improving mechanisms for penalty-based enforcement and incentives for independent R&D. Furthermore, it proposes advancing institutional development, policy implementation, and system optimization in a progressive manner, short-term, medium-term, and long-term, according to priority.