The study of the spatial and temporal patterns of carbon emissions and the influencing factors in the western region is of great significance to the realization of the “double carbon target”. In this paper, the panel data of 11 provinces in the western region from 2000 to 2022 was used to study the spatial and temporal patterns of carbon emissions based on the nighttime lighting data, and the extended STIRPAT model was used to explore the influencing factors of carbon emissions. It is found that the total carbon emissions in the west continue to rise, with obvious regional differences. There is significant high-high and low-low agglomeration of carbon emissions in the west. Although the influencing factors of carbon emissions among the western provinces, municipalities, and autonomous regions show significant differences, the energy structure is the main factor for the growth of carbon emissions, and the industrial structure plays an inhibitory effect.

Based on the data of A-share manufacturing listed companies from 2010 to 2022, the difference-in-difference model was used and technological innovation was introduced as a mechanism variable to explore the impact of “Made in China 2025” on the high-quality development of China’s manufacturing enterprises and the role of technological innovation in it. The results show that “Made in China 2025” has a significant role in promoting the high-quality development of China’s manufacturing enterprises, and the promotion effect is more significant in non-state-owned enterprises and enterprises in the central and eastern regions. “Made in China 2025” can promote the high-quality development of manufacturing enterprises by improving their technological innovation capabilities.

With increasingly globalized trade, efficiently, safely, and low-carbon distributing products is a critical challenge in the perishable supply chain network design(PSCND). A mixed-integer linear programming(MILP) model was developed considering perishability uncertainty, limited capacity of facility location, flow allocation and transport mood, aiming to minimize cost, carbon emissions and transportation time, as a case study, optimizing fresh-cut flower processing and pre-cooling centers in Kunming, Yunnan Province, China. The Weibull function was introduced to model the loss of perishable products during transportation. Given the intricate nature of the problem, a hybrid algorithm that integrated the minimum element method with the genetic algorithm was devised. The applicability and validity of our proposed model and algorithm was substantiated through rigorous numerical analysis. It draws out the impact of perishability on establishing processing and pre-cooling centers and modes of transport. Enterprises should decide on the mode of transport and adjust the number and capacity of processing and pre-cooling centers according to the perishability of products.

With the development of technology, the digital economy era has arrived. The 20th CPC National Congress report pointed out that “efforts should be made to enhance the resilience and security level of industrial chains and supply chains” and “promote the deep integration of innovation chains, industrial chains, capital chains and talent chains”, further clarifying the key tasks for modernizing industrial chains.The dairy industry is a long chain industry that involves agriculture, livestock, industry and services. Yili Group is the leading enterprise in China’s dairy products industry and is located at the core position of the entire industrial chain. Meanwhile, the supply chain is an important force that promotes the healthy and stable development of the entire industrial chain. Therefore, achieving digital supply chain management is a trend for future enterprises. The impact of digital transformation on supply chain operations at Yili from 2016 to 2023 was analyzed, identifed the current challenges faced by Yili Group’s supply chain management, and reasonable solutions are proposed.

As global environmental issues become more prominent, wind power, a low-pollution renewable energy source, has garnered attention. However, the variability and intermittency of wind resources pose challenges for predicting wind farm output, affecting power system scheduling and operation. To improve the accuracy of wind power forecasting, weather characteristics influencing power output must be fully considered. By modeling and predicting actual wind farm data, the effectiveness of different deep learning models for ultra-short-term forecasting was compared. The results show that a multivariate time prediction method based on a long short-term memory(LSTM) network effectively predicts wind power, achieving higher accuracy and stability than other deep learning models.

As an important part of the regional innovation system, the innovation ability of local universities is crucial to the high-quality development of the regional economy. Based on the panel data of 27 provinces in China from 2010 to 2022, the impact of data elementalization on the innovation ability of local universities was empirically explored. The results show that data elementalization significantly enhances the innovation ability of local universities, and the positive effect of different innovation quantile points is gradually enhanced. Data elementalization indirectly promotes the improvement of the innovation ability of local universities through intelligent innovation drive and industrial structure optimization. In the central and western regions, where the innovation intensity and industrialization level are low, the promotion effect of data elementalization on the innovation ability of local universities is more obvious.

Taking panel data from 39 listed commercial banks in China from 2013 to 2022, and empirical methods were used to study the impact and mechanism of digital finance development on the operational performance of commercial banks. The research results indicate that digital finance can significantly promote the improvement of operational performance of listed commercial banks. Digital finance has had a significant negative impact on the operational performance of commercial banks in the central and western regions. The impact of digital finance on the operational performance of state-owned commercial banks, joint-stock commercial banks and local commercial banks varies. The level of risk-taking plays a fully mediating role in the impact of digital finance on the operational performance of commercial banks.

As global environmental issues worsen, green innovation is recognized as a core strategy for the sustainable development of chemical fiber enterprises. In this study, based on the TOE framework, listed companies in the chemical fiber industry from 2018 to 2022 were selected. The dynamic QCA method was used to analyze how digitalization influences green innovation efficiency. Three paths were identified for improving the green innovation efficiency of these enterprises. The first path relied on the application of digital technologies, the second on the scale of the enterprise and government support, and the third on the balance between digital technologies, government support, and organizational factors. These configurations show strong explanatory power, although individual performance varies across companies.

Focusing on the annual report tone and listed companies in heavily polluting industries, a unique text analysis dictionary was firstly constructed based on annual reports and social responsibility reports. Then, using data from listed companies on the Shanghai and Shenzhen stock exchanges, generalized additive models(GAM) and Logit regression were applied to explore potential connections between annual report tone and the severity of violations, as well as different types of violations. The findings reveal a non-linear relationship between annual report tone and the severity of violations for listed companies in heavily polluting industries, which can be specifically divided into three stages. Additionally, there exists a significant linear correlation between annual report tone and specific violation types(e.g., fictitious profits, false disclosure), with certain tone features potentially serving as tools to conceal violations. Therefore, regulatory agencies should strengthen their regulatory measures based on text analysis. For investors, non-financial information deserves increased attention.

The Shandong Provincial Capital Economic Circle, centered around Jinan and radiatingto six surrounding cities, has formed a “1+6” urban development pattern and is an important growth pole for the rise and economic development of the central and western regions of Shandong Province. Collecting Economic indicator data from seven cities and 57 counties within the Shandong provincial capital economic circle, grey relational analysis method was used to measure the agglomeration level between different cities and industries. GeoDa software was used to conduct spatial econometric analysis on the clustering degree of primary, secondary, and tertiary industries within the economic circle. Based on panel data from seven cities within the economic circle from 2003 to 2021, the manufacturing and production service industry synergy agglomeration index was used as the core explanatory variable. Through empirical analysis of double fixed effects, the key driving factors affecting industry synergy are demonstrated, and rational suggestions are proposed.