Drawing on the ‘buzz-and-pipeline’ framework, this paper examines the impact of intra- and interregional collaboration linkages on the innovation capacity of cities, as evidenced by the co-publication networks existing among 217 Chinese cities located in 20 city-regions. The results show that (1) intra- and interregional linkages have an inverted ‘U’-shaped and positive relationship with innovation capacity, respectively; (2) the positive effects of intra- and interregional linkages on urban innovation can be enhanced when combined with triadic closure and structural holes, respectively; and (3) there exists a complementary relation between intra- and interregional linkages in facilitating cities’ innovation capacity.

The sustainable logic between the Agricultural Heritage System (AHS) and environmental synergy has been significantly changing with China’s urban–rural relationship shift from binary opposition to a stronger network exchange. During the process of transformation, China’s AHS rural areas encounter two major development trends and social realities, i.e., whether to continue conventional characteristic agricultural development or detach from conventional characteristic agricultural resources to achieve industrial transformation. Our aim is to analyze the structure, identity and functional transformation characteristics of AHS rural areas from the urban and rural scale, as well as to build an explanatory framework for transformation mechanisms. A total of 109 counties and five cases of important AHS areas in China are taken as research objects, combining quantitative and qualitative analyses to analyze the transformation of AHS rural areas from two aspects. On the one hand, for changes in single development elements, there are three development elements and corresponding transformation dimensions: (1) Land structure: there is a synergistic change between the increase in urbanization rate and the loss of rural land, with associated changes in space and production structure. (2) Population identity: the rural population loss in high-urbanization-level areas is severe, where farmers are combined or separated from traditional agriculture. (3) Industry function: the trend of non-agricultural development of the industrial economy is obvious, and the traditional functions of agriculture are facing a continuation or a deep transformation. On the other hand, for relations among development elements, combined with a regression analysis and field investigation, we try to explain how the development elements and characteristic elements influence each other while working together on the transformation of AHS rural areas. The transformation depends on the path of the original industrial structure, while the urban–rural income ratio, regional distribution and land urbanization rate all positively stimulate the transformation from agricultural industries to non-agricultural ones. Moreover, the transformation of AHS rural areas is also affected by the characteristic elements of their special agricultural heritage, specifically, whether the heritage is scalable, scarce or socialized, etc., and these special attributes can determine the different development forms of heritage elements in the modern agricultural industrial system.

Intercity cooperation networks are critical for addressing regional imbalances and advancing sustainable regional development, yet existing studies typically focus on specific functional domains, rather than the overall intercity cooperation network. To bridge this gap, this study examines the intercity cooperation network in the Pearl River–Xijiang Economic Belt (21 cities, 2014–2023), analyzing its spatio-temporal evolution and influence mechanisms through Social Network Analysis (SNA) and partial least squares structural equation modeling (PLS-SEM). The results reveal the following: (1) the network has undergone three policy-driven development stages: initial–accelerated–steady; (2) a spatial pattern of “east—dominant, west—weak” has emerged, shaped by the radiating influence of core cities; and (3) institutional proximity and cooperation investment are key drivers of network formation, while geographical and organizational proximity exhibit negative impacts. These findings underscore the need for related regional development strategies to foster a more vital and open cooperation network. Overall, this study deepens the understanding of intercity cooperation by revealing its macro-level patterns and influence mechanisms, and provides practical implications for policymakers committed to promoting sustainable regional development.

Shrinking cities suffer from a decreased level of resident activities. As a result, areas with low levels of resident activities may become breeding grounds for social issues. To ease and prevent social issues, it is important to deploy physical space optimisation strategies to effectively guide the distribution of resident activities in shrinking cities. To support the development of such spatial strategies, this paper introduces machine learning-based methods for analysing the nuanced non-linear relationship between resident activities and physical space in shrinking cities. Utilising dual-scale grids, this study calculates multi-source spatial elements, which are subsequently integrated with resident activity data to construct a gradient boosting decision tree model. It then analyses the weight of different spatial elements’ impacts on resident activities and their nonlinear relationships. The model proposed in this study demonstrates good precision in construing the relationship between resident activities and physical space. Based on the research findings, strategies for different types of spatial development in shrinking cities are drawn out. This paper advocates for the application of this analytical approach before conducting spatial planning in shrinking cities to maximise the effectiveness of spatial development in guiding resident activities.