摘要 : To assist researchers in optimally fitting practical events and strengthen the available data analysis toolkits, we propose a new distributional method constructed using a trigonometric function. Henceforth, the proposed method is based on the cosine function and referred to as a new cosine trigonometric- G (NCT- G ) function. The incorporation of the cosine function in the development of the NCT- G method leads to significantly improved and optimal versions of the conventional probability distributions. By applying the NCT- G method, we concentrate on a new variant of the Weibull distribution, namely, a new cosine trigonometric Weibull (NCT-Weibull) distribution. Due to the implementation of the cosine function, we promptly show that the NCT-Weibull distribution has more flexibility in terms of density and hazard functions. Some mathematical features of the NCT-Weibull distribution, notably those associated with quartiles, are computed. We derive the estimators for the new distribution. Moreover, we assess these point estimators via conducting simulation studies for various parameter values. Finally, intending to establish the fitting superiority of the NCT-Weibull distribution, we consider two data sources from the human resource and radiation science. According to certain fitting criteria, the empirical exploration indicates that the NCT-Weibull distribution demonstrates optimal performance.

摘要 : This paper focuses on improving the list of potential methods utilized for examining real-world data. The contributed work focuses on providing a new distribution technique leveraging a familiar trigonometric function. Consequently, the proposed approach is primarily founded on the cosine function and is thus termed the new cosine- G (NC- G ) method. Another main focus of this research is on the implementation of the Weibull distribution as a special case scenario of the NC- G method. This effort leads to a new distribution, specifically, a new cosine-Weibull (NC-Weibull) distribution. For the NC-Weibull distribution, we investigate different mathematical characteristics. This investigation is especially based on the exploration of the quantile-inspired properties. For the parameters of the NC-Weibull distribution, the mathematical expressions of the point estimators are computed. Aiming to assess the performance of the estimators, a simulation study for different parameter combination values is also carried out. In addition to these efforts, we also check the performance of the NC-Weibull distribution in the practical scenarios. This process is based on the utilization of two practical data sets, which are related to the student management system and radiation. Our empirical exploration based on statistical tests shows that the NC-Weibull distribution repeatedly offers the best output as compared to rival distributions.

摘要 : This study investigates the critical role of government subsidy policy objectives in influencing firms' total factor productivity (TFP) through the lens of conflicting policy goals between equity and efficiency. Utilizing panel data from Chinese manufacturing listed companies spanning 2010–2022, the research employs heterogeneous policy analysis to demonstrate that employment subsidies (targeting social equity) and R&D subsidies (focusing on economic efficiency) both achieve their intended objectives — expanding labor employment for the former and stimulating R&D investment for the latter — yet exhibit divergent effects on TFP. Specifically, employment subsidies create labor redundancy systematically depressing TFP growth. In contrast, R&D subsidies significantly boost TFP. The findings reveal an inherent trade-off in government subsidy design: employment-oriented policies may undermine productivity, whereas innovation-driven initiatives struggle to address employment absorption. This research provides theoretical and practical guidance for optimizing government subsidy policies, emphasizing the diversity and complexity of policy goals, and revealing the challenges in achieving both fairness and efficiency.

摘要 : This study examines how corporate digital transformation contributes to environmental responsibility by reducing pollution expenses among Chinese A-share listed firms between 2011 and 2020. We construct a firm-level digital transformation index using text analysis of annual report disclosures. The results show that digital transformation significantly lowers pollution expenses, both directly through enhanced process efficiency and indirectly by fostering innovation and easing financing constraints. These effects are stronger in firms subject to higher analyst attention and in high-tech industries. Robustness tests—including alternative measurements, Tobit models, and instrumental variable analysis—support the reliability of our findings. This research advances the literature on sustainability and corporate social responsibility by clarifying the mechanisms and conditions under which digital transformation reduces environmental costs. The findings provide practical implications for policymakers and business leaders in emerging markets seeking to align digitalization strategies with environmental objectives.

摘要 : In response to environmental challenges, governments have paid increasing attention to environmental protection, but its potential impact on corporate green innovation has yet to be explored. Built on the attention-based view and institutional theory, this paper constructs a research framework to explain whether and how government environmental attention stimulates corporate green innovation. Based on the panel data of Chinese listed firms, our empirical findings validate a positive relationship between government environmental attention and corporate green innovation. Mechanism tests construct a chain mediating model and show that government subsidies, corporate environmental attention, and their sequential chain linage are key mechanisms of this relationship. Our findings still stand after a set of robustness checks. Overall, this paper uncovers the complicated mechanisms through which government environmental attention influences corporate green innovation and provides policy implications for emerging economies.

摘要 : With the development of information technology and the gradual implementation of digital technology application scenarios, the form of competition is evolving from competition between enterprises to one between supply chains. In addition, facing the complex market environment, in order to achieve better development, enterprises from different supply chains have also begun to seek cooperation. Therefore, in an era of digital economy, competition and cooperation among enterprises have been transformed into competition and cooperation among supply chains. Price is the main factor in the supply chain. However, with the continuous transformation of consumers' consumption concept, service has gradually become an important factor affecting consumers' decisions. Thus, it is important to study the price and service level strategies simultaneously in the supply chain.This paper considers two supply chains, each consisting of a manufacturer and a retailer, the retailers determine prices and service levels, and manufacturers determine wholesale prices. To explore the price and service strategies of retailers in various supply chain structures, as well as the optimal profits of the supply chains, this paper constructs four models of the total integration (TI), the horizontal competition and vertical integration (HCVI), the horizontal integration and vertical competition (HIVC), and the total competition (TC) structures. Firstly, the manufacturers determine the wholesale prices as leaders, and the retailers decide the prices and service levels as followers. Then, the optimal price, service level, market demand, and supply chain profit are obtained by using backward induction for four supply chain structures. Secondly, the optimal strategies in the four supply chain structures are compared, to find the optimal supply chain structure. Finally, the paper investigates the relationship between the optimal price and service level of different supply chain structures in the symmetric market and asymmetric market. These findings will provide a decision-making basis for strategy selection.Furthermore, this paper investigates how the intensity of price competition and service competition affects the optimal price, service level, demand and supply chain profit. The findings include: (1)Of the four supply chain structures, the TI structure makes the highest profits. In the HIVC structure, retailers have the highest decision-making efficiency and respond quickly to the market. As price competition is fiercer, the retailers have begun to shift from price competition to service competition. The TC structure makes higher profits than the partial competition structures (i.e., HCVI, HIVC), which indicates that supply chain profits in the total competition situation are not always the worst. (2)In the HIVC structure, the less intense price competition leads to a higher price and lower service level. Although this may increase supply chain profits, it has a detrimental effect on consumers. Therefore, the collusion between retailers will decrease supply chain profits. (3)In the HCVI structure, vertical integration reduces the impact of double marginalization, which leads to lower price, and lower supply chain profit. In addition, the optimal strategies of manufacturers and retailers are analyzed through numerical examples in the asymmetrical market, and the effects of the intensity of price and service competition on the optimal price, service level and supply chain profit are explored.This paper mainly studies price and service level strategies of retailer in different supply chain structures. In this study, the manufacturer is the leader, and the retailer is the follower in the supply chain. However, retailers such as Suning, Walmart, and JD are often the leaders in the supply chain. Furthermore, this paper does not consider the effect of consumers' preferences. For instance, some consumers may pay more attention to the cost-effectiveness of products, while others may pay more attention to the value-added services of products. These are all issues that we will study in the future.

摘要 : Different micro-meteorological conditions can affect a driver's judgment of road conditions, leading to changes in following behavior. On rainy days, water films on the road reduce traction, increasing the likelihood of hydroplaning and traffic accidents. While there are existing following models under various weather conditions, research on the specific impact of micro-meteorological factors is insufficient. To achieve fine management in intelligent transportation and real-time monitoring of vehicle states, it's essential to study following behavior under different micro-meteorological conditions and establish corresponding models. This paper focuses on the Intelligent Driver Model (IDM) and the Wiedemann99 model, considering the impact of micro-meteorological conditions. By incorporating a driver's judgment factor, λ, the IDM and Wiedemann99 models are improved, leading to the development of new models: I-IDM and I-Wiedemann99. Simulation validation is used to choose speed and following distance as performance indicators for parameter calibration of the I-IDM and I-Wiedemann99 models, with the sum of Root Mean Square Percentage Error (RMSPE) as the goodness-of-fit function. Comparisons are made between the driving paths, speeds, and accelerations of following vehicles before and after calibration, verified through simulations. The conclusions are as follows: the average error and standard deviation of the improved I-IDM model are smaller than those of the I-Wiedemann99 model, with the maximum Root Mean Square Percentage Error (RMSPE) for I-IDM model parameter calibration being 0.4568 and the minimum being 0.1324. For the I-Wiedemann99 model, the maximum RMSPE is 0.4613 and the minimum is 0.1376. The parameter calibration results of the I-Wiedemann99 model are more dispersed compared to those of the I-IDM model, indicating that the I-IDM model simulates following behavior more effectively than the I-Wiedemann99 model. The findings of this study can provide a reference for further improving the theory of following behavior, and offer a theoretical basis and IoT technology support for refined traffic management under rainy conditions.

摘要 : The problem of residents' insufficient consumption has been a long-term concern in China, and reducing taxes and fees is an important aspect of the nation's active fiscal policy. This study constructs a four-department dynamic stochastic general equilibrium model involving heterogeneous households, manufacturers, local governments and the central bank to examine the impact of tax and fee reductions on household consumption. The results reveal three relevant findings. (1) Reduced government fees will crowd into overall household consumption, and the effect on output is not obvious in the medium or long term. (2) Reduced tax rates will crowd out household consumption, with a more obvious long-term impact on output and consumption. (3) The impact of these two types of shocks has different effects on indebted and debt-free households' consumption.

摘要 : The differences in logistics carbon emission and carbon absorption in different areas lead to potential conflicts in the green development of regional logistics. The Yangtze River Delta (YRD) in China is a critical coastal developed region for economic integration development and opening up, with logistics playing a substantial role in energy consumption and carbon emissions. Therefore, addressing the low-carbon transformation of logistics in the YRD is a matter of great concern. The framework of carbon balance accounting and prediction of logistics consist of 'basic accounting-factor analysis-prediction simulation' is constructed. Then, this study accounts the logistics carbon emissions (LCE) and logistics carbon capacity (LCC) in the four subregions (Shanghai, Jiangsu, Zhejiang and Anhui) from 2010 to 2021. Estimates the influencing factors of LCE through the geographically and Temporally Weighted Regression model (GTWR). Then, constructs the prediction model for the logistics carbon balance statue based on System Dynamics (SD) structure under four single-factor scenarios and two cross-factor scenarios from 2022 to 2030. Results showed that: (1) The logistics carbon deficit in the YRD is prominent. And the four sub-regions show different spatio-temporal evolution characteristics. (2) The influences of economic level and technical level on LCE are particularly obvious and also has spatio-temporal heterogeneity. (3) There is a trade-off between the pursuit of economic development and carbon emission control. S1 and S2 will continue to witness the increase of logistics carbon pollution. Under S3-S4, the effect of LCE reduction is relatively weak. S5 shows a significant carbon reduction effect, S6 could achieve a good balance between economic development and carbon emissions. (4) Promote the reform of transportation from highway to railway, ensure access to affordable and clean energy for logistic, promote the coordinated carbon reduction of regional logistics and synchronous construction of ecological and artificial carbon pool based on the conditions of developed coastal areas could be feasible paths to achieve carbon balance for YRD.