China's economy has entered a new stage of development, necessitating the enhancement of new-quality productivity to achieve economic transformation and upgrading. Innovation capability plays a crucial role in boosting new-quality productivity. Although existing literature has explored various factors influencing new-quality productivity, there is a scarcity of research examining its impact from the perspective of county-level innovation capability. Taking 88 counties in Guizhou Province from 2011 to 2021 as the research objects, this paper constructs index systems for county-level innovation capability and new-quality productivity, respectively, and employs empirical analysis to study the static and dynamic impact effects of county-level innovation capability on new-quality productivity. The results indicate that: Firstly, the direct and indirect effects of county-level innovation capability in Guizhou on new-quality productivity are both significantly positive; Secondly, the mechanism of this effect involves upgrading the three elements of productivity – "laborers, labor objects, and means of labor"; Thirdly, under the static mechanism, the direct effect of county-level innovation capability in the Central Guizhou Urban Agglomeration is significantly positive, while the indirect effect of county-level innovation capability in non-Central Guizhou Urban Agglomeration is significantly negative; Fourthly, under the dynamic mechanism, the direct effect of the county-level innovation capability progress index on the new-quality productivity progress index is significantly positive, while the indirect effect is not significant. Moreover, the conclusions drawn from the perspective of heterogeneity in the dynamic mechanism are consistent with those of the overall county-level samples.

Digital economy integrates with real economy to foster new productive forces. Existing studies use coordination models, input-output models, and single indicators to measure China's digital-physical integration depth, lacking comprehensive representation. This paper constructs an evaluation index system from two dimensions: digital economy materialization and real economy digitization. It uses "entropy-TOPSIS" method to measure China's overall and provincial digital-physical integration depth from 2012 to 2023. Robustness tests are conducted using "projection tracing-simulated annealing" and other methods. Regional differences and trends are characterized using Dagum Gini coefficient and Kernel density estimation. Findings show: China's digital-physical integration deepens, especially post-2017. The digitization of the real economy aligns with overall integration, while digital economy materialization surges post-2019. Regional disparities in integration depth narrow over time, with inter-regional differences as the main source. Spatial autocorrelation exists in provincial integration development, with a higher probability of upward transfer. Low-level provinces are more influenced by neighbors for upward "leap".These conclusions provide data and policy insights for accelerating China's digital-physical integration and developing new productive forces.

This article aims to connect with the national economic accounting system, measure the added value scale of China’s smart agriculture, and evaluate its industrial linkage effect and final demand effect. Therefore, based on the Statistical Classification of Digital Economy and Its Core Industries (2021) by the National Bureau of Statistics, this article decomposes the digital industrialization part of the agricultural sector using input-output tables from more than 100 departments, measures the scale of China’s smart agriculture, and evaluates its effects. Research has found that: (1) The average scale of smart agriculture in China is 371.388 billion yuan, accounting for 5.58% of the agricultural category and only 0.47% of GDP, indicating that there is huge development space for smart agriculture in China. At the same time, both smart agriculture and traditional agriculture have an average annual growth rate lower than the GDP growth rate of the same period, indicating that in the trend of industrial structure adjustment, efforts should still be made to increase agricultural development. (2) From the perspective of industrial correlation, there is a significant backward connection between China’s smart agriculture and the core industries of the digital economy, especially the digital product manufacturing industry. The development of smart agriculture has shifted from initial infrastructure construction to improving production service efficiency and digital technology innovation; At the same time, the demand and supply driving effects of smart agriculture and traditional agriculture on other industries in the national economy are almost equal. However, compared to traditional agriculture, smart agriculture is not sensitive to changes in supply and demand of other industries in the national economy. (3) From the sensitivity analysis of final demand, smart agriculture is a consumption dependent industry, but the promotion of smart agriculture by various final demands is relatively small, and the expansion of effective demand mostly affects traditional agriculture. This study not only provides an analytical framework for subsequent academic research, but also provides high academic guidance for the policy community.

The concept of "Lucid waters and lush mountains are invaluable assets" suggests that leveraging the resource endowments of origin to cultivate geographical indications of agricultural products (AGIs) can facilitate local wealth generation, serving as an effective pathway to establish a long-term mechanism for increasing farmers' income. AGIs have a defined county-level scope; however, existing research has primarily focused on analyzing the impact of inter-provincial and inter-city geographical indications on farmers' income, neglecting the extent of benefits derived from county-level geographical indications and failing to explore whether these indications can consolidate the achievements of poverty alleviation efforts. In response, this study empirically examines the impact of agricultural product geographical indications on the urban-rural income gap and its underlying mechanisms using panel data from 1,417 counties in China, employing an interactive fixed effects model. The results indicate that AGIs confer common benefits to regions, enhancing agricultural production competitiveness and economic efficiency through scaled, standardized, and localized production, thereby effectively reducing the urban-rural income gap within counties and promoting shared prosperity. Heterogeneity analysis across different types of counties reveals that the income gap reduction effect of AGIs exhibits regional disparities. Specifically, compared to counties with higher levels of economic development, these indications significantly narrow the urban-rural income gap in counties located in the western region. The reduction effect is notably greater in counties outside the Yangtze River Economic Belt than in those within it. Additionally, the linear reduction effect of AGIs on the urban-rural income gap is more pronounced in poverty-stricken counties.

The township practice of participatory budgeting centered on residents’ participation is an important form of grass-roots democracy development and innovation, which manifests and practices the whole process of people’s democracy in grass-roots governance, and is an important tool for effective township governance. Most existing researches focus on the model discussion of a single case or the net effect of a single element, which lacks a general overview of the township practice of participatory budgeting in China, and lacks the academic discussion of its diversified realization mechanisms. Based on the TOE theoretical framework, the article analyzes 26 cases of participatory budgeting in townships using the clear-set qualitative comparative analysis method (csqca) and finds that the residents’ budgetary participation in townships is the result of the interaction of factors such as digital infrastructure, amount of budgetary funds, administrative dominant level, institutionalized arrangement, and residents’ participatory literacy, etc. There are four types of "technology-organization type" "technology-environment type" "organization-environment equilibrium type" and "technology-organization-environment three-wheel drive type" that drive the achievement of high levels of residents’ budgetary participation. To build an effective democratic foundation for township governance, participatory budgeting practices in townships should take into account the differences in local financial levels and resource endowments, and integrate and give full play to the synergistic effects of differentiated paths.

Farmer cooperatives connect small farmers without difference by playing the function of mutual assistance and cooperation, promote the effective connection between small farmers and modern agriculture, and enhance the sense of economic gain of farmers. Previous studies on the contribution of sense of gain have mainly focused on the theoretical cognitive level, with relatively few literature analyzing the impact of sense of gain from an empirical perspective. This paper takes Chongqing four rural revitalization of national key support county 1022 peasant households as sample, in the construction of economic sense exponential model, on the basis of reference "counterfactual analysis framework" and multiple linear regression and other statistical thinking, progressive step by step to answer the farmer cooperatives can ascend into social farmers economy get feeling, how to improve farmers get feeling, And the key issues such as the significant factors affecting the sense of economic gain of the participating farmers. The results show that the mutual assistance and cooperation function of farmer cooperatives can significantly improve the sense of economic gain of farmers, and the empirical results still hold after solving the endogeneity problem. The gender of household head and land elements had significant positive effects on the sense of economic gain of the participating farmers. Further analysis shows that joining farmers’ cooperatives can improve farmers’ sense of economic gain by reducing production costs, resolving production risks and expanding marketing channels. So, this paper puts forward further emphasize the leading role of farmers’ cooperatives on farmers, continue to encourage small farmers to actively participate in farmers’ cooperative development, from the cost of production, the production risk and marketing channel three aspects to deepen the cooperative benefit coupling mechanism, to strengthen the government’s guiding power of farmer cooperatives operation and policy incentive system construction.

Social credit construction is an important basis for improving market efficiency and promoting economic development. Based on the data of the China Household Finance Survey Project (CHFS), this paper empirically examines the effect and mechanism of social credit on household consumption. It is found that the optimization of social credit environment can significantly improve the per capita consumption level of households, and the conclusion is still valid after robustness test and endogeneity processing. The mechanism analysis shows that the optimization of social credit environment can promote the technological innovation of enterprises, improve the quality of products and services from the supply side, and promote consumption. At the same time, it can also promote consumer credit, ease household capital constraints from the demand side, and promote consumption. Further analysis shows that the driving effect of social credit improvement on residents’ consumption is more obvious in urban households, households with low dependency ratio and households of workers in formal units. From the institutional perspective of social credit, this paper expands the feasible path to promote residents’ consumption, and provides experience for optimizing the supply of social credit system and enhancing the basic role of consumption.

Social relationships such as blood ties and academic connections that come before an organization are generally considered to have a positive impact on organizational/team performance in the form of social capital. However, there is little attention paid to how social relationships affect individual behavior and further shape team performance after entering an organization/team. This study analyzes the micro mechanism by which social relationships affect team performance. It examines the impact of social relationships on individual behavioral choices, effort levels, and cooperation orientation through social comparison. Furthermore, it examines the shaping effect of task decomposability on team performance and establishes a social incentive framework for the influence of social relationships on team performance. The research results show that: firstly, social relationships have a positive impact on the effort level and cooperation orientation of individual behavioral choices; Secondly, both effort level and cooperation orientation have a positive impact on team performance, but in the context of smaller enterprise scale, the positive effect of effort level is stronger than that of cooperation orientation; Finally, task decomposability negatively moderates the relationship between individual behavioral choices and team performance. This study reveals the social incentive mechanism by which social relationships affect team performance, providing a new perspective for optimizing the matching of organizational tasks and organizational structure.

Government innovation subsidies and additional deduction for R&D expenses are important policy instruments to encourage enterprises to carry out exploratory and developmental innovation and to improve China's basic innovation capacity. Existing studies have mostly focused on the impact of government innovation subsidies on enterprises' dual innovation, and few have explored the effect of the policy of adding deduction for R&D expenses and included the two policies in the comparative analysis of the same theoretical framework. Using the data of A-share listed companies from 2008 to 2022, this paper finds that due to the difference in the design of policy mechanism, government innovation subsidy promotes dual innovation of enterprises, while additional deduction for R&D expenses only promotes the developmental innovation of enterprises, and there is no incentive for exploratory innovation, and this effect is not found in non-state-owned enterprises, eastern region enterprises, and enterprises in regions with a higher degree of marketization are more significant. Mechanism tests show that the level of market competition, the degree of managerial myopia and financing constraints are important mediating channels, and there is a difference in the effects of the two types of policies on the mediating variables, which results in different impacts on firms' dual innovation. Further analysis reveals that government innovation subsidies alone increase firms' preference for exploratory innovation; multiple large shareholders can play a corporate governance function and enhance the effect of the two types of policies on firms' dual innovation promotion.

Based on panel data of county-level carbon emissions in the Yellow River Basin from 2000 to 2021, this article uses spatial correlation analysis and geographic detector analysis to explore the spatiotemporal evolution pattern and influencing factors of county-level carbon emissions in the Yellow River Basin. The research results show that the total carbon emissions of counties in the Yellow River Basin have continuously increased from 2000 to 2021, with Inner Mongolia Autonomous Region and Henan Province ranking first in carbon emissions, and Qinghai Province ranking last. The average annual growth rate of carbon emissions shows an overall trend of "Upstream improvement, middle and downstream maintenance". The high carbon emission high concentration areas (H-H) in counties of the Yellow River Basin are mainly distributed in the middle and lower reaches of the Yellow River Basin, represented by Qingzhou City, Ruzhou City, and Guyang County, and exhibit a high carbon emission concentration characteristic of "clustered" distribution along both banks of the basin along the Yellow River Basin; The Low Low Agglomeration Areas (L-L) are mainly concentrated in the upper and middle reaches of the Yellow River Basin, represented by Diebu County, Dangchang County, and Yijun County. The level of fixed assets investment has the greatest impact on the upstream and downstream counties of the Yellow River basin, and the development level of the secondary industry has the greatest impact on the middle reaches of the Yellow River basin.

Based on the financing issues of the green supply chain under the condition of stochastic demand, this paper uses the Conditional Value-at-Risk (CVaR) method to study the financing problems considering the risk aversion and fairness preference of the core enterprise in the supply chain. Unlike previous studies that only used the mean-variance method to focus on the impact of the core enterprise's risk aversion on the green supply chain financing, this article employs the Conditional Value-at-Risk method. On the basis of overcoming the shortcomings of the mean-variance method, it simultaneously studies the impacts of the core enterprise's risk aversion and fairness preference on the green supply chain financing.The research findings are as follows: When suppliers increase their green investment in the supply chain and face capital constraint problems, compared with bank green credit, the financing method of advance payment by retailers is more beneficial to all entities in the supply chain. When considering both the risk aversion and fairness preference of retailers, the more risk-averse the retailers are, that is, the smaller the risk aversion coefficient is, the lower the profit level of the suppliers will be. The profit level of the retailers first increases and then decreases, and the impact of the suppliers' fairness preference on the retailers' profits will also be affected by the degree of the retailers' risk aversion.The research results enrich and expand the relevant studies on the financing strategies and influencing factors of the green supply chain, and provide a decision-making reference for alleviating the financing difficulties of small and medium-sized enterprises in the supply chain.