The benefit of cultivated land use is an essential indicator for measuring the optimal allocation of cultivated land resources and the high-quality development of agriculture. Taking Shiyan City, Xiangyang City, and Suizhou City in Northern Hubei as the research objects, this paper presents an evaluation index system for cultivated land use efficiency from the perspectives of ecology, economy, and society. The entropy TOPSIS method and the obstacle degree model were applied to estimate the cultivated land use efficiency and identify obstacle factors in the three study areas from 2010 to 2020, and the results were as follows. (1) The comprehensive benefit level of cultivated land utilization in Northern Hubei showed an upward trend, and the individual benefit levels of cultivated land utilization in different cities were significantly different. Xiangyang City had outstanding economic performance, Shiyan City had the fastest growth rate of ecological benefits, and various benefits of Suizhou City were “steady”. (2) The fluctuation ranges of the obstacle factors for cultivated land use were relatively large in the Northern Hubei region. From 2010 to 2016, the effective irrigation index, land-averaged fertilizer input level, agricultural input–output ratio, and per capita income of farmers were the main factors restricting the improvement of cultivated land utilization efficiency in Northern Hubei. During 2017–2020, the per capita pesticide input level, per capita grain output, forest coverage rate, land output rate, and agricultural mechanization efficiency became the main obstacles restricting the improvement of cultivated land-use efficiency. (3) All cities of Northern Hubei should take measures according to local conditions, implement specific policies to address the restrictive factors of cultivated land use, improve the level of cultivated land-use benefit in the region, and promote the coordination and unity of the economic, ecological, and social benefits of cultivated land use.

In this article, we construct an evaluation index system based on the DPSIRM framework to determine the water resources carrying capacity of Shiyan City. Then, we use an obstacle model to calculate and analyze the factors that constrain the improvement in the water resources carrying capacity in the city. The research results are as follows: (1) The water resources carrying capacity of Shiyan City was on the rise during 2011–2021, and the water resources carrying capacity of Shiyan City was continuously improved. (2) The management system is the primary obstacle subsystem, followed by the driving force system, the response system, the pressure system, the state system, and the influence system. (3) Among the specific factors, the top three obstacles are sewage treatment investment, the proportion of guaranteed harvest area in drought and flood, and the average annual fertilizer applied per unit of cultivated land. These primary factors restrict Shiyan City from improving its water resources carrying capacity. This study has important practical significance for understanding the resilience of the water system in Shiyan City; exploring the changes in the water resources carrying capacity and its obstacle factors; and guiding the development, utilization, and management of water resources in Shiyan City.

The global new energy vehicle (NEV) industry is undergoing accelerated technological iteration, forcing firms to confront uncertain technological trajectories, high R&D investment, and intensified innovation risks. Acquiring external knowledge to reduce trial-and-error costs has therefore become critical. Existing research predominantly examines policy support and internal firm resources, while paying insufficient attention to strategic interactions among firms. Drawing on peer effects, social learning, and information asymmetry theories, this study uses Chinese NEV enterprises as the research setting to examine how peer firms’ innovation behavior influences focal firms’ technological innovation decisions. The findings show a significant positive peer effect in NEV technological innovation: focal firms adjust their R&D decisions by observing peer firms. This influence is consistent with information transmission, experiential learning, and competitive pressure, with leading firms’ innovation practices providing particularly important technical references for followers. The intensity of the peer effect varies across firm characteristics and external environments. By examining how these conditions moderate peer effects, this study provides indirect evidence on whether the underlying mechanism is more consistent with information-driven rational learning or competition-driven strategic imitation. Notably, stronger competitive pressure (measured by a lower Herfindahl–Hirschman Index), greater financing constraints (measured by the absolute value of the SA index), and higher ownership concentration amplify peer influence, whereas economic policy uncertainty weakens it by reducing the reliability of external innovation signals. This study extends research on the determinants of technological innovation in the NEV sector from a corporate-interaction perspective, reveals the role of peer learning and strategic imitation in industrial technology upgrading, and offers theoretical foundations and practical implications for optimizing innovation strategies, enhancing technological competitiveness, and promoting coordinated industrial development.

To promote the high-quality development of the new-energy-vehicle industry, this paper takes the provincial panel data from 2016 to 2023 as its research object and adopts the coupling coordination degree model to measure the coupling coordination level of the coupling coordination degree (D) between new-energy-vehicle industrial-chain development capacity (U1) and green innovation (U2), and to analyze its spatiotemporal evolution characteristics. The research shows that China’s new-energy-vehicle industry presents a feature of high coupling and low coordination between new-energy-vehicle industrial-chain development capacity and green innovation, with an overall fluctuating upward trend evolving from imbalance toward coordination. Spatially, the coupling coordination level forms an obvious gradient pattern of high in the east, medium in the central region, and low in the west. Some central–western provinces achieve periodic improvement, accompanied by short-term year-to-year fluctuations.