Urban innovation and development are a core driver for promoting the industrial, economic, and social development of cities. However, the factors that affect the innovation and development of cities lack systematic analysis as well as interaction analysis. Based on a multidimensional perspective, this study suggests that natural, economic, and social factors are three major factors conditioning urban innovation and development. A grounded theoretical qualitative method is further adopted to code relevant research literatures, news reports and interview materials, resulting in an onion factors model. We find that natural factors–including environmental quality, geographic location, and city scale–are prerequisite for conditioning urban innovation and development. Economic factors are also key, including economic level, industrial structure, industrial agglomeration, and technological innovation. Social factors are guarantee factors, including administrative hierarchy, cultural environment, population structure, and government management and services, i.e., they are essential for cities to become adaptable in the current dynamic situation. The study provides theoretical support and practical directions for the formulation of policies for urban innovation development.

This study investigates the mechanism of digital linguistic landscapes in enabling engineering education for smart construction according to the educational dimensions of A (ability), S (skill), and K (knowledge). A questionnaire survey was conducted based on the core concepts of the informative dimension and symbolic dimension in digital language landscape as well as the ability dimension, knowledge dimension, and skill dimension in engineering education. Structural equation modeling (SEM) was used as the test method. The results of the research demonstrate that the informative dimension and symbolic dimension are two main aspects of DLL in education of engineering students for smart construction. Additionally, DLL has a significant positive impact on the ability, knowledge, and skill education of engineering students for smart construction. The research has theoretical and practical significance, as it not only enriches research on the relationship between DLL and engineering education for smart construction but also expands the theoretical understanding of engineering education from the perspective of linguistics. Furthermore, the study explores the path of the practical application of digital language landscape to engineering education for smart construction.

No abstract