Excellence in corporate culture is the key to achieving sustainable business development. Sustainability can be a source of success, innovation and profitability for a company, driving the achievement of low-carbon goals for transport infrastructure enterprises. The aim of this study is to examine the relationship between corporate culture and corporate sustainability from the perspective of transport infrastructure enterprises, and to identify which corporate culture factors may have an impact on the sustainable low carbon development of transport infrastructure enterprises. To achieve this, we constructed a structural equation model based on 351 cases in Hunan Province and examined the relationship between corporate culture and sustainable low-carbon development using partial least squares structural equation modeling. The findings suggest that corporate values and corporate culture management capabilities play an important role in promoting sustainable development of transport infrastructure enterprises at the economic and low-carbon levels.

Due to the national economic development form and social development demand, in recent years, the government has been vigorously promoting the control of government-enterprise collusion in the bidding process of government projects in order to promote the standardization of the market. How to predict the vertical collusion behavior under different internal and external environments has become an important research content. Although the prediction of individual behavior is difficult to achieve, the prediction of group behavior has certain possibilities. In this paper, we propose a method for predicting and evaluating the vertical collusion behavior of government investment project bidding based on BP neural network analysis optimized by an annealing algorithm. First, drawing on the traditional evaluation model, the evaluation index system of government-enterprise collusion behavior is constructed from five dimensions: internal environment, external environment, policy development, enforcement effort, and feedback channel. Secondly, a machine learning method based on BP neural network optimized by an annealing algorithm is introduced to evaluate the influence of the change of initial conditions on the bidding collusion behavior. This study has certain significance for government managers to discover the problems and causes in policy formulation, which in turn can support the government in further improving the policy utility.

The research on the evolution of the competition culture of highway construction enterprises aims to provide suggestions for highway construction enterprises to respond to the call of the Belt and Road Initiative and cope with overseas market competition in the new era. Based on the TF-IDF algorithm to extract the keywords of each enterprise culture, 291 enterprise culture texts were used as the analysis samples, and the evolution pattern of the competition culture of construction enterprises was explored. Relevant suggestions are made with the help of visualization and other technical means. It was found that: the competition culture of enterprises shows a trend from catering to the market to the internal construction of enterprises; the internal construction of enterprises is mainly reflected in talent competition, technological innovation and the optimization of management; the higher the level of competition, the more talent and technological innovation are valued; the development of competition culture is driven by the policy environment; and the focus of competition culture is affected by the maturity of the market.