This study delves into the nuanced impact of leadership styles on state-owned enterprises (SOEs) performance in Northeast China. It aims to discern how transformational, transactional, and authoritative leadership approaches influence organizational outcomes, framed within the context of sustainable leadership theory. Employing a quantitative methodology, the research analyzes survey data from employees across various SOEs to assess the relationship between leadership styles and company performance, including aspects such as job satisfaction, employee motivation, and operational efficiency. The findings reveal a clear dichotomy: transformational and transactional leadership styles positively correlate with improved performance metrics, fostering an environment of innovation, motivation, and job satisfaction. Conversely, authoritative leadership is shown to detrimentally affect these same metrics, potentially hindering organizational growth and employee morale. This research contributes to the broader discourse on leadership and organizational performance by highlighting the critical role of leadership style in enhancing the sustainable development of SOEs, particularly within China’s socio-political and economic fabric. Practical implications suggest a shift towards more adaptive, employee-centered leadership approaches to spur performance and sustainability in SOEs. The originality of this study lies in its specific focus on the Chinese context, offering insights into the leadership dynamics within SOEs and proposing actionable strategies for fostering leadership that align with sustainability and organizational excellence principles.

How to improve enterprise performance has been a research topic widely studied by scholars for a long time. As economic globalization deepens, the business competition becomes increasingly harsh. Technology-based small and medium-sized enterprises (SMEs) play an important role in the rapid development of the country’s economy, especially in China. This study aims to investigate the mediating effect of knowledge integration capability in the relationship between corporate social capital and enterprise performance. The sample group used in this study were 300 technology-based SMEs in China. The research tool was a questionnaire adapted from previous scholars, which passed assessment in terms of content validity and reliability. Data were analyzed using structural equation modelling. The results show that: 1) corporate social capital has a positive impact on enterprise performance, but the impact differs between well-performing and poor-performing enterprises; and 2) knowledge integration ability plays a mediating role in the relationship between corporate social capital and enterprise performance, and the mediating role is the same for both well-performing and poor-performing enterprises. But it played a partial mediating role in the good-performance comparison group and a complete mediating role in the poor-performance comparison group. This study is useful for enterprise management in cultivating and developing the abundant social capital of enterprises and expanding channels for knowledge integration ability to increase enterprise performance.

The impact of human activities on the quality of urban environment has become increasingly prominent and urban soil pollution problems on the health of local residents also gradually prominent. In addition, the study of heavy metal pollution in urban surface soil is an important part of the evolution model of urban geological environment so it is necessary to analyze the heavy metal pollution in urban soil. In this paper, the data of the given samples are processed and analyzed by MATLAB software and EXCEL spreadsheet. The three - dimensional image model and the planar model of metal element space are established by interpolation method. The spatial distribution of eight kinds of heavy metal elements in the city is presented in detail. For the urban environment, especially the macro-grasp of soil pollution, regulation provides a simple and accurate three-dimensional spatial distribution model of pollutants. Combined with data analysis of the urban area of different areas of heavy metal pollution to make a preliminary judgment. The data show that in the five types of cities, heavy soil pollution is the most serious in industrial areas. A method of imagination of the data analysis is boldly used and then combined with the distribution map, they found a source of pollution. For the spatial distribution of heavy metal elements, this paper uses EXCEL to calculate the data and MATLAB to map the data which showed a detailed and intuitive distribution map according to the distribution map can be analyzed in different areas of pollution; For the second question, this paper uses a method of design to deal with the data, part of the data for the results of the more effective show to determine the cause of pollution. For the third question, this article will be more serious pollution or a wider range of local screening, analysis, and then speculate the location of pollution sources. For other pollution information, this article is based on the modeling process encountered in the thought of the factors given.

Since the proposal of the low-carbon economy plan, all countries have deeply realized that the economic model of high energy and high emission poses a threat to human life. Therefore, in order to enable the economy to have a longer-term development and comply with international low-carbon policies, enterprises need to speed up the transformation from a high-carbon to a low-carbon economy. Unfortunately, due to the massive volume of data, developing a low-carbon economic enterprise management model might be challenging, and there is no way to get more precise forecast data. This study tackles the challenge of developing a low-carbon enterprise management mode based on the grey digital paradigm, with the aim of finding solutions to these issues. This paper adopts the method of grey digital model, analyzes the strategy of the enterprise to build the model, and makes a comparative experiment on the accuracy and performance of the model in this paper. The results show that the values of MAPE, MSE and MAE of the model in this paper are the lowest. And the r^2 of the model in this paper is also the highest. The MAPE value of the model in this paper is 0.275, the MSE is 0.001, and the MAE is 0.003. These three indicators are much lower than other models, indicating that the model has high prediction accuracy. r² is 0.9997, which is much higher than other models, indicating that the performance of this model is superior. With the support of this model, the efficiency of building an enterprise model has been effectively improved. As a result, developing an enterprise management model for the low-carbon economy based on the gray numerical model can offer businesses new perspectives into how to quicken the shift to the low-carbon economy.

With the development and progress of the era, digital construction has become an important topic for enterprise development in the new era. Practice has shown that by actively carrying out corresponding digital construction work, enterprises can more comprehensively and systematically analyze the industry development and market prospects, which helps to promote the reasonable adjustment
of internal and external management work modes and the improvement of management efficiency, and has a positive guiding role for the healthy development cycle of enterprises. In this article, the author combines a large amount of research cases to conduct research on the effect of digital construction on enterprise development in the new era and proposes corresponding optimization measures, hoping to further promote the full play of information technology value, in order to safeguard the development of enterprises.