Online video platforms are an emerging form of two-sided markets that connects consumers and advertisers by offering consumers video content paired with advertisements. These platforms generate revenue from both sides: consumers pay membership fees, while advertisers are charged ad rates. To explore the dynamics of such platforms, this paper develops a game model that incorporates typical features of online video platforms, including customer streaming levels, ad aversion, and network externalities. It investigates how these factors influence the platform’s decisions regarding service modes (free versus hybrid), two-sided pricing (membership fees and ad rates), and advertisers’ advertising decisions. These findings reveal that the platform’s choice between free and hybrid service modes depends on a cost threshold—determined by the maximum customer stream level, the proportion of consumers with high ad aversion, and advertiser-side network externalities. Specifically, the platform adopts the hybrid mode when the ad-acceptance cost for highly ad-averse users exceeds the threshold; otherwise, it opts for the free mode. Moreover, the maximum level of customer stream positively affects ad rates in both service modes. In the hybrid mode, an increase in customer stream level leads to lower membership fees and higher optimal advertising volumes. These effects vary depending on the chosen service mode. Additionally, advertiser network externalities positively influence both optimal advertising volumes and ad rates, with stronger effects observed in the free mode compared to the hybrid mode. Conversely, customer network externalities negatively impact membership fees on the platform.

The multi-ratio fixed commission model used for O2O takeaway platforms can be categorized into MG and MS models, based on factors such as meal price and delivery distance. This paper proposes the concept of consumer sensitivity, assuming that consumers exhibit bounded ration, specifically, they are sensitive to the proportion of delivery fees relative to meal expenses. It analyzes the impact of factors such as consumer sensitivity, differences in meal price, and variations in delivery cost of the two models. It is found that the bounded rational behavior of consumers does not always have a negative impact on platform profits. Under the MS model, platform profits are more significantly affected by the bounded rational behavior of consumers. Regardless of the commission model adopted, the commission ratio for the SA merchant should be higher than that for the SD merchant. These research results expand the application of the Stackelberg game model in platform-based service settings and provide managerial insights for the platform to adjust the commission ratio under the fixed commission model.

This paper develops a Cournot competition model that incorporates emission reduction costs to compare the effects of emission tax and emission standard policies from the perspective of government. Considering the differences in emission reduction cost coefficients between two firms and the emission reduction targets set by the government, it analyzes the resulting impacts on producer surplus, consumer surplus and total emissions under each policy. The findings reveal that under an emission standard policy, regardless of the difference in emission reduction cost, higher emission standard set by the government lead to decreased emissions from both firms. In contrast, under the emission tax policy, a higher tax rate leads to lower total emissions only when the cost disparity between the two firms is relatively small. A higher tax rate set by the government is able to decrease the total emissions of the two firms. Additionally, both policies are found to disadvantage firms with higher emission reduction costs. The analysis of economic benefit and consumer surplus indicates that emission standard policy is more effective than the emission tax policy. This paper provides practical policy recommendations for governments aiming to regulate carbon emissions in different market environments.

In the context of carbon tax policy, this paper examines the construction of a secondary power supply chain consisting of a power generator (as the leader) and a power retailer (as the follower). It incorporates key factors such as renewable energy preference coefficient, the proportion of third-party financing institution, and the interest rate associated with debt financing, and establishes an equity financing model and a debt financing model. Using backward induction, the main researches are summarized as follows. First, under the equity financing model, the renewable energy investment, consumer demand, electricity price, consumer surplus, and retailer profit are all higher, while total carbon emissions are lower compared to in the debt financing model. Next, the profit of the supply chain member profit under the two financing models depends on either the proportion of third-party financing institution or the potential market demand. Finally, while an increase in the unit carbon tax can increase investment in renewable energy and leads to a reduction in total carbon emissions, it has a negative impact on demand and reduces the profits of both the power generator and the retailer.

During the transformation of economic growth mode, the misallocation of production factors has become one of the key obstacles to achieving high-quality economic development. This paper constructs an estimation model by incorporating energy as a factor into the Cobb-Douglas production function. It calculates the degree of energy misallocation and analyzes the spatial correlation features of 30 provinces from 2005 to 2020 based on relative distortion coefficients. Furthermore, it decomposes economic growth into factor inputs and total factor productivity to reveal the differentiated economic growth mode among regions. In a counterfactual analysis framework, it estimates the potential for carbon reduction under scenarios of effective energy allocation. The findings indicate that China’s overall energy misallocation index is 1.501, indicating a moderate overallocation of energy. Among regions, the eastern region exhibits better energy allocation efficiency compared to the central and northeast regions, while western region faces the most severe misallocation issues. Energy misallocation shows significant positive spatial correlation but lacks evident spatial migration characteristics. Capital, labor, and energy inputs play a leading role in contributing to economic growth, with most provinces still following a factor-driven growth model. Only a few regions have transitioned to innovation-driven development. The results from representative cities are consistent with provincial-level findings. Under efficient energy allocation, China’s carbon reduction potential ranges from 13.85% to 16.94%, with the central and western regions showing higher sensitivity to energy misallocation. Resource-based cities exhibit notably higher carbon reduction potential than non-resource-based cities, while declining cities have the highest potential overall. This paper not only provides a novel perspective on factor misallocation and the underlying drivers of China’s economic growth, but also offer valuable insights for policy-making aimed at promoting high-quality economic development and achieving China’s goal of carbon peaking in 2030.

Industry 4.0, represented by disruptive technologies such as virtual reality, cloud computing, and the Internet of Things, has led to the reshuffling of global traditional industries. It brings industrial transformation in various countries, reinvention and convergence of industries, forming a new industrial standards, industrial patterns and business models. The huge demand of national economic development for disruptive technologies makes it an important prerequisite to seize the initiative of innovation to accurately identify the field of disruptive technologies, accurately forecast the direction of disruptive technologies, and correctly guide the development of disruptive technologies. Based on the characteristics of cross-border convergence and diffusion of disruptive technologies, this paper proposes a dynamic prediction model architecture of disruptive technologies based on patent data from the perspective of technology convergence. Virtual reality, a representative disruptive technology, is selected and serves as the empirical object of this paper. The life cycle of this technology is creatively fitted by constructing a patent co-occurrence network and analyzing the cumulative number of patent co-occurrence, with 2010 identified as the dynamic starting point for the current prediction phase. To address data disequilibrium, a dynamic prediction model is developed using link similarity indices and machine learning classification algorithms. A comparison of various prediction models shows that the global similarity index outperforms the local similarity index in forecasting subversive technologies, and the random forest algorithm emerges as the most effective classifier. The prediction results suggest that the most promising areas for technological convergence with virtual reality include near-eye display devices, digital data processing technologies, and digital video transmission systems. By scientifically designing the prediction process for disruptive technologies, this paper not only effectively improves forecasting accuracy, but also provides theoretical foundation and methodological reference for identifying critical timing and selecting appropriate prediction models for the development of disruptive technologies.

This paper proposes a power trading model based on a multi chain energy blockchain to address key challenges in traditional single chain power exchanges, such as limited stability, low efficiency, and credit ratings for energy producers and sellers. To enhance trading efficiency, a resource chain is introduced for adaptive rent-seeking and dynamic matching between supply and demand nodes, achieving decentralized resource scheduling and management. The practical Byzantine fault tolerance (PBFT) consensus mechanism is adopted on the power chain to ensure secure verification and consistent collaboration, effectively preventing unauthorized tampering of transaction data. Additionally, by incorporating a repayment capability index, a peer-to-peer (P2P) energy interaction model is established on the trading chain, promoting transparent pricing and improving credit rating between producers and sellers. Experimental results show that the multi-chain energy blockchain not only ensures fairness in transaction settlements, but also effectively improves energy utilization efficiency and enhances the credibility of transactions, providing theoretical and decision-making support for optimizing power trading models.

Faced with unbalanced medical resource distribution and varying patient choices preferences, this paper develops a queuing game model to analyze the behavior of two types of patient within a tertiary-community hospital medical consortium. It compares doctor-sharing and bed-sharing strategies under two organizational structures, subordination and subcontracting, to explore the optimal resource-sharing strategy and consortium configuration under medical resource constraints. The findings provide new operational ideas and management insights for improving collaboration and resource integration among medical consortiums in China. Specifically, the doctor-sharing strategy is more effective in reducing patient travel costs and alleviating resource imbalances between hospitals, especially when either doctors or beds are in short supply. When doctors are relatively abundant, bed-sharing strategy allows for higher patient admissions, provided there is only a slight shortage of beds. Additionally, resource allocation is more efficient under the subordination model, while subcontracting performs comparably under specific conditions involving resources levels and competitive dynamics. This paper provides theoretical support for optimizing the structure and resource allocation mechanisms within China’s healthcare consortiums.

The quality and safety of medical and health products are of great importance and remain a major concern for both the government and society. These issues become even more pronounced during public health emergencies, where the imbalance between supply and demand intensifies the tension between corporate profit motives and quality ethics. In this context, improving the quality supervision mechanism to ensure effective regulation of product quality with limited regulatory resources becomes a pressing challenge. This paper incorporates the concept of quality ethics and constructs a four-party evolutionary game model involving enterprises, third-party organizations, government regulators, and consumers, analyzes the stability of each participant and the influence of key variables on system evolution through MATLAB R2020b simulation. The results show that reducing production costs, imposing reputational penalties on enterprises that produce low-quality products, and establishing a robust punitive mechanism can significantly improve the quality and safety of healthcare products. Moreover, guiding enterprises to adopt appropriate cost-benefit reference systems can help them manage uncertainty during public health emergencies and mitigates the effects of bounded rationality and decision-making bias on behavioral decisions. Further, improving the oversight of third-party organizations, strengthening enforcement by governmental regulators, and enhancing consumer awareness are essential to prevent biased decision-making and to ensure the effective functioning of a coordinated quality supervision system. Finally, cultivating quality ethics among all stakeholders is also a vital approach to resolving quality issues in the healthcare product industry.

Utilizing the attention-based view and treating the Central Environmental Protection Inspection (CEPI) initiated in early 2016 as a quasi-natural experiment, this paper examines the impact and underlying mechanisms of CEPI on corporate sustainable performance across a panel of 915 listed firms spanning the period between 2013 and 2019. Employing a time-varying difference-in-differences (DID) model, the findings reveal a significant improvement corporate sustainable performance of firms within heavy-polluting industries following the implementation of CEPI. Mediation analysis indicates that CEPI contributes to elevating corporate sustainable performance by increasing environmental awareness among both the public and top-level management. Further analysis reveals that industry competition mitigates the positive effects of CEPI corporate sustainable performance, whereas corporate financing constraints amplify it. This paper not only provides empirical evidence supporting the effectiveness of the China’s environmental governance efforts in enhancing corporate sustainable performance, but also offers policy recommendations and managerial insights for improving the efficiency of environmental protection inspection mechanisms and facilitating the green, low-carbon transformation of enterprises.

This paper investigates the impact of government subsidies on the investment decisions of specialized and emerging “small giant” public companies using data from 2020 to 2021. The analysis reveals an inverted U-shaped relationship between the amount of government subsidies and the corporate research and development (R&D) investment. Further subgroup test shows that in firms receiving low levels of government subsidies, subsidies are significantly positively related to the R&D investment and show no significant relationship with enterprises diversification. This suggests that moderate government subsidies are conducive to specialized and emerging enterprises to cultivate their core business. Conversely, in the high-subsidy group, government subsidies are significantly negatively correlated with R&D investment and positively correlated with enterprise diversification. This indicates that excessive government subsidies tend to lead specialized and new enterprises to deviate from the core business and pursue unrelated diversification. Given the generally low level of corporate governance among these enterprises, there is a significant negative relationship between diversification and enterprise value, which is manifested as a “diversification discount”.

Green development, aimed at increasing green total factor productivity (GTFP) is an essential pathway to reconciling the contradiction between economic development and environmental/resource constraints thereby facilitating high-quality economic development. Essentially, GTFP reflects a form of resource allocation efficiency that incorporates environmental factors. Shifts in local government’s attention to green development can lead to resource reallocation, which in turn affects GTFP. This paper employs textual analysis of local government work reports from 266 cities between 2011 and 2021 to explore the impact of local governments’ green development attention on local GTFP. The findings reveal that increased governmental focus on green development significantly improves GTFP, primarily by promoting green technological progress. Furthermore, the development of financial technology (fintech) positively moderates the relationship between green development and GTFP, enhancing the effectiveness of policy focus. The effect is more pronounced in large cities, resource-based cities, and those with higher levels of human capital accumulation. Overall, the government’s attention to green development not only promote environmental sustainability but also contributes to economic growth.

Reversal online portfolio strategy can make full use of the reversal effect in the stock market, and the backtest results on most data sets show that the reversal online portfolio strategy can obtain higher cumulative returns. Based on the reversal effect of stock price in the financial market, an expert opinion pool is constructed and a competitive online portfolio by aggregating expert opinions is established. First, the reversal effect of stock prices in windows is used to construct investment strategies representing the expert opinion, and expert opinion pools are obtained based on different window lengths. Then, a weak aggregating algorithm is used to assign trust weight to each expert, and an online portfolio strategy is constructed by aggregating expert opinions. The competitive performance analysis proves that the strategy constructed can follow the offline optimal expert opinion. The numerical results show that the performance of the strategy is better than that of online strategies related.

Bond default prediction faces multitude challenges, including severely imbalanced samples, concept drift, and the difficulty of identifying hard-to-classify samples. Existing models, both basic ones and improved ones to address individual issues, often fall short of meeting these complex demands. To address this, this paper proposes a concise composite loss function based on cross-entropy loss, termed as TW-focal loss, which adjusts the loss weights of different samples by incorporating tailored improvement factors, enabling the model to effectively learn from default samples, new samples and hard-to-classify samples. Using publicly issued credit bond data in China from 2014 to 2022, and adopting XGBoost as the experimental model, the empirical results show that TW-focal loss effectively controls the Type I error rate while reducing the Type II error rate. Compared to the standard cross-entropy loss, the performance evaluation index Gmean has increased by 46.4%, and by 12.9% compared to the weighted cross-entropy loss that focused on imbalance. Additionally, using the SHAP interpretation method, this paper analyzes the distribution of feature importance and the partial dependency curves under different loss functions. The results reveal that the model can control the recognition of default samples by altering the impact degree and range of features. This paper provides an effective attempt to complete the design of bond default prediction models and to explore the discriminative logic of the models.

The current literature on imitation behavior among peer firms primarily focus on firms in the same industry. However, as shareholder becomes prevalent in the finance market, firms are faced with competitions not only from their industry counterparts but also from investee peers—firms that share common shareholders. Based on awareness-motivation-capability, this paper investigated why and how philanthropy performance of investee peers influences the philanthropy performance of focal firms. Using a sample of Chinese listed firms from 2008 to 2018, it is found that philanthropy performance of investee peers positively affects the philanthropy performance of focal firms. Additionally, both environmental complexity and the degree of shareholder ownership positively moderate this relationship, strengthening the peer influence effect. This paper contributions to the current research on peer effect in corporate philanthropy behavior by extending the scope beyond industry peers to include investee peers. It also enriches the application of awareness-motivation-capability model and adds more antecedents of corporate philanthropy behavior.

Small and medium-sized enterprises can obtain more financing opportunities by relying on supply chain networks, and the structural characteristics of supply chain networks are closely related to their financing performance. This paper, based on the research approach of “network–capability–performance”, investigates the relevant mechanisms that affect the financing performance of small and medium-sized enterprises in the supply chain network, the effect of supply chain network structure on the entire process of financing performance by affecting the innovation ability of enterprises, and the moderating role of supply chain complexity in the entire intermediary model. Based on survey data from over 300 enterprises in Xi’an, and using structural equation modeling and process analysis methods, the empirical findings reveal that the innovation capability of enterprises mediates the relationship between supply chain network heterogeneity and supply chain financing performance. However, supply chain complexity has a negative moderating effect throughout the mediating process, weakening the influence of innovation capability in complex supply chain environments. In contrast, the innovation capability of enterprises does not mediate the relationship between supply chain network size and financing performance. Nevertheless, supply chain complexity plays a negative moderating role in this pathway, dampening the positive influence of network size on financing outcomes. This paper not only deepens the application of information asymmetry theory and extends the theoretical understanding of supply chain finance, but also provides management references for supply chain financing practices of SME in different research contexts.

In response to the growing demand for new composite talents who possess both traditional craftsman skills and digital literacy in the era of industrial digitalization, there is a shared expectation among academic and practitioners to define the competencies of the digital craftsman. This paper explores the structural dimensions and competency model of digital craftsman using grounded theory, and subsequently develops and validates a competency measurement scale. The results show that digital craftsman competency includes four dimensions: solid craftsman foundation, strong digital literacy, agile transformation ability, and sustainable development ability. The developed scale consists of 19 items and demonstrates strong reliability and validity. This paper fills the theoretical gap in the conceptual structure of digital craftsmen competency, and provides a scientific competency measurement tool for future empirical research and practical applications in human resource management, particularly in digitally transforming enterprises.

Based on limited attention theory, this paper examines the significant impact of institutional investors’ attention diversion (referred to as distraction) on the major shareholders’ tunneling behavior in Chinese A-share listed companies on the Shanghai and Shenzhen Stock Exchanges from 2007 to 2022. The findings reveal that institutional investors’ distraction significantly exacerbates the tunneling behavior of major shareholders. This effect increases under conditions of financial distress and decreases with greater media coverage. The mechanism underlying this relationship is that distraction reduces corporate governance and increases information asymmetry, thus leading to more tunneling behavior of major shareholders. Moreover, distraction intensifies the damage caused by major shareholders’ tunneling behavior to the value of companies, although this moderating effect appears with a time lag. Firms with a high degree of tax avoidance and elevated information processing cost should be more cautious about the exacerbating effect of institutional investors’ distraction. The findings provide important implications for regulatory authorities to formulate relevant policies and effectively alleviate the tunneling behavior of major shareholders in Chinese listed companies.

Based on a sample of management discussion and analysis (MD&A) of A-share listed firms between 2002 and 2019, this paper measures the information content of MD&A of peer firms based on the vertical comparability of MD&A text and examines its impact on corporate investment efficiency. The findings show that the lower the vertical comparability, the higher the corporate investment efficiency. This finding is not explained by the tone of MD&A text of the peers. The channels include both the increase of industry-level information content and the enhancement of the monitoring of investors. The significance of these findings increases with disclosure timeliness, textual readability, firms’ information demand, as well as environmental volatility and competition level. Additionally, MD&A more likely contains good news than bad ones, and peers’ good news better guides corporate investment decisions. These findings support the positive spillover effect of MD&A text information.

With the increase number of “going global” enterprises in China, the demand for the deep integration of manufacturing and logistics industries has increased. It is of great significance to explore the implementation path of the deep integration and innovation development of “going global” enterprises. Based on the grounded theory, this paper conducts interviews and surveys with relevant managers of “going global” enterprises that conduct the deep integration of the two industries, and constructs a preliminary conceptual model of the implementation path for the deep integration and innovation development of “going global” enterprises. Based on this, through empirical test of questionnaire survey, this paper develops a final conceptual model of the implementation path for “going global” enterprises’ deep integration and innovation development of two industries. The findings show that the deep integration and innovation development of “going global” enterprises are affected by five core factors: external incentives, internal optimization, relationship strength, high-level embeddedness, and market power differences. Both internal optimization and relationship strength play a complete intermediary role between external incentives and the development performance of the integration of the two industries. On the one hand, “going global” enterprises have improved the performance of “going global” enterprises’ integrated development of two industries through internal optimization. On the other hand, by strengthening the relationship with cooperative enterprises, the performance of “going global” enterprises’ two industry integration development can be improved. The high level of embeddedness positively regulates the promotion of external incentives on internal optimization, and the difference of market forces negatively regulates the promotion of external incentives on relationship strength. This paper enriches the theoretical system of the integration of the two industries of enterprises, provides a practical strategic path and theoretical support for “going global” enterprises to realize the deep integration of manufacturing and logistics industry in the context of globalization, and offers a certain practical reference for “going global” enterprises to achieve high-quality development in the global competition.