Enterprise Decision Research Articles

New Ideas of Teaching Reform of Management Accounting in Colleges and Universities Under Artificial Intelligence

The wide application of artificial intelligence technology has had a profound impact on all walks of life. Education is no exception, especially the teaching of management accounting. As an important basis for enterprise decision-making, management accounting s teaching content, methods and means need to keep pace with The Times to adapt to the development of artificial intelligence era. Based on this, the thesis mainly discusses and analyzes the teaching reform of management accounting in universities from the perspective of artificial intelligence.

Revealing academic networks’ impact: driving innovation in Chinese high-tech enterprises

ABSTRACT Innovation is a critical aspect in China’s development as a great modern socialist country and in realizing its second-century goals. As key decision-makers in enterprises, the academic network resources carried by senior executives are seldom noticed. This study is going to explore whether senior executives’ academic network relationships (i.e. senior executives are or were employed by universities or research institutions) will spur corporate innovation performance. Drawing on panel data from Chinese A-share high-tech listed companies from 2014 to 2021, the study examines this relationship through multiple linear regression analysis and investigates the mediating role of R&D manipulation in this connection. The results of the study show that the more academic network relationships embedded in senior executives, the better the high-tech firms’ innovation performance. Additionally, R&D manipulation serves as an intermediary factor between senior executives’ academic network relationships and corporate innovation performance. Furthermore, when these individuals hold key positions and have a higher level of academic background, the facilitating effect of senior executives’ academic network relationships is more pronounced. This study broadens the application scope of social network theory and provides valuable insights for high-tech companies aiming to augment their knowledge-based innovation performance and refine their managerial recruitment strategies.

The Impacts of Regulatory Approaches to Carbon Quotas on Third-Party Logistics Low-Carbon Financing Strategies and Emission Reduction Effects

Carbon emission reduction is an important issue for sustainable development. The logistics industry is a key area for carbon emission reduction. The modern logistics supply chain includes logistics parks (fourth-party logistics, 4PL) and small, medium and micro logistics enterprises settled in the parks (third-party logistics, 3PL). Facing the pressure of the need for sustainable development, 3PL enterprises need to invest a lot of money in green transformation. However, 3PL enterprises are subject to serious financial constraints. In order to break the capital constraints, 3PL enterprises can raise funds from banks or from 4PL financing. Under the carbon quota policy, the government can regulate the 4PL or the 3PL. Therefore, this paper uses the Stackelberg game model to build a green financing strategy model of small and medium-sized logistics enterprises considering different supervision methods under carbon quotas, explores the optimal emission reduction decision-making process of small and medium-sized logistics enterprises, and provides solutions to the financing problems of small and medium-sized logistics enterprises in realizing sustainable development. The study found that the decisions of enterprises under different governmental supervision methods are affected by carbon quotas, and the government’s supervision of 3PL is more conducive to carbon emission reduction; in this scenario, the 4PL financing strategy is more likely to be adopted compared with bank financing, because 4PL charge lower service fees, thus encouraging 3PL to increase their low-carbon investment. Finally, this paper puts forward two different carbon emission supervision methods and considers the green financing services of 4PL; this provides references for government supervision and the sustainable development strategies of logistics enterprises.

Impact of debt maturity and cash holding on investment decisions in Vietnamese companies

The study used data from 520 listed firms between 2004 and 2020 to ascertain the relationship between debt maturity, cash holding, and investment decisions in Vietnamese enterprises. The use of more conservative tactics results from the rise in agency costs. Increased cash holding encouraged businesses to employ internal resources to reduce external financing risks, favorably impacting investment decisions. The negative link between investment decisions and intangible assets indicates increased external funding costs. A high tax shield benefited the investment since it freed up financial flows for productive assets. The robustness test revealed that cash holding positively corresponds with investment decisions in consumer and technology enterprises and that technology firms are incredibly responsive to changes in debt maturity.

Does environmental regulation promote enterprise environmental protection investments? A quasi-natural experiment from river chief system in the Yangtze river delta of China

The investment decisions of enterprises are affected by environmental regulations designed to protect the environment, so environmental regulations may change companies' investment behavior in environmental protection. This study focuses on the River Chief System (RCS)1, an innovative environmental regulation related to river governance which officially launched in China in 2014. Based on data collected from heavy-polluting companies in the Yangtze River Delta, we use the difference-in-differences model (DID Model)2 and focus on RCS's impacts on micro-environmental protection investments. Our findings reveal that the RCS is conducive to expanding the scale of enterprises' environmental protection investments. Industrial structural upgrades appear to have a masking effect wherein the one-sided pursuit of industrial structural upgrades may slow economic growth and cause enterprises to reduce the scale of environmental investments. We recommend that the allocation of environmental investment should be based on the characteristics of local markets and public participation, and maintain a balance between secondary and tertiary industries, government and business incentives.

A study of the impact of digital transformation and corporate green performance

Based on the data of A-share listed companies in Shanghai and Shenzhen from 2018 to 2022, this paper investigates the impact of corporate digital transformation on corporate green performance from the perspective of corporate digital transformation. It is found that there is a significant negative relationship between the degree of corporate digital transformation and green performance, and this significant negative relationship still holds after using the propensity score matching method. The examination of the mediating role of financing constraints suggests that the negative effect of digital transformation on firms' green performance will increase as financing constraints decrease. Heterogeneity studies show that the inhibitory effect of digital transformation on green performance is stronger among private firms. The article enriches the research on the factors affecting green performance, and also sheds some light on the decision-making of enterprises regarding green performance.

Impact of connected dispensing technology with advanced analytics in a multicenter health system.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. This study was designed to evaluate the impact of enterprise inventory optimization (EIO) technology and analytics on pharmacy labor, costs, and medication availability within a large integrated delivery network (IDN). This article describes a mixed-methods, postmarket observational study assessing the impact of a solution of disparate technologies including automated dispensing cabinets (ADCs), centralized pharmacy inventory software, and controlled substance vaults connected by an inventory optimization analytics (IOA) tool. Four study modules were implemented over a 10-month period. The intervention consisted of implementation of the IOA software, linking the disparate automated technologies. Transactional data was collected and aggregated with user perception survey data in both the pre- and postintervention periods. Descriptive and comparative statistical testing was used to assess outcomes. A total of 11 facilities with bed counts ranging between 22 and 908 beds were included in this study. At an enterprise level, users were able to complete an average of 2.8 times more periodic automated replenishment (PAR) level changes post intervention, resulting in an estimated enterprise labor avoidance of over 1 full-time equivalent (2,099 labor hours) annually. Despite an enterprise decision to increase ADC inventory on hand from a 3-day supply to a 5-day supply, 5 sites (45%) had a decrease in total inventory, while 9 sites (82%) saw a decrease in ADC inventory costs. Additionally, 7 sites (64%) saw a reduction in the ADC stockout percentage and all 11 sites (100%) saw a decrease in the central pharmacy stockout percentage post intervention. Integration and optimization of connected inventory management technology was observed to have positive impacts on improving labor productivity, reducing ADC inventory carrying costs, and increasing medication availability.

The Impact of Confucian Culture on Corporate Environmental Governance

Using A-share listed companies in Shanghai and Shenzhen from 2010 to 2019 and the density of Confucian temples and schools near sample company headquarters, this paper uses regression analysis to estimate the impact of Confucian culture on corporate environmental governance. Enterprise environmental capital investment as a percent of total assets is the dependent variable used as a proxy for environmental governance. The log of the number of the number of Confucian temples and Confucian academies within a 200-kilometer radius of the company's registered location plus one is the independent variable. This study finds that the environmental capital expenditures increase by 0.007% for every unit increase in the independent variable. Similar results are found when the radius is expanded to 300 kilometers. The greater the influence of Confucian culture is, the more inclined enterprises are to participate in corporate environmental governance. Additionally, environmental governance information disclosure can be a key influence path for this correlation. Further analysis finds that the relationship between Confucian culture and environmental governance is stronger with more experienced managers, a more developed institutional environment, and after 2015 following the People's Republic of China’s enactment of the Environmental Protection Law. This study expands the literature on the factors that influence Confucian culture on corporate environmental governance, enriches the empirical evidence of the influence of the informal system of corporate environmental governance on enterprise decision-making, and confirms the modern commercial value of Confucian culture.

The Effect of Uncertainty Regarding Transfer Pricing Regulations and Administrative Practices on Corporate Investment Decisions

This article examines the role of uncertainty arising from changes in transfer pricing regulations on the investment decisions of multinational enterprises. The authors’ findings highlight the significant effect of transfer pricing uncertainty and illustrate the importance of establishing international standards to enhance certainty.

Optimizing environmental costs and economic benefits in new energy vehicle production: A case study of FAW Hongqi in China

This study focuses on the environmental cost accounting and economic benefit optimization of China’s FAW Hongqi New Energy Vehicle manufacturing enterprise under uncertain conditions, within the context of the emission permit system This study calculates the pollution situation throughout the manufacturing and production process of FAW Hongqi new energy vehicles, and constructs a multi-level environmental cost evaluation system for FAW Hongqi new energy vehicle manufacturing projects. Through the interval fuzzy model of FAW Hongqi new energy vehicle manufacturing projects, the maximum economic benefits of the enterprise are simulated. The research results indicate that the pollution emissions of enterprises are mainly concentrated in the three processes of welding, painting, and final assembly. Enterprises use their own exhaust gas and wastewater treatment devices to meet the standards for pollution emissions. At the same time, solid waste generated during the automobile manufacturing process is handed over to third-party companies for treatment. Secondly, based on the accounting results of enterprise pollution source intensity and a multi-layer environmental cost evaluation system, the environmental costs of enterprises are accounted for, and the environmental costs are represented in interval form to reduce uncertainty in the accounting process. According to the accounting results of enterprise environmental costs, the main environmental costs of enterprises are environmental remediation costs caused by normal pollution discharge and purchase costs of environmental protection facilities. Pollutant emission taxes and routine environmental monitoring costs are relatively low. Enterprises can adopt more scientific solutions from the aspects of environmental remediation and environmental protection facilities to reduce environmental costs. After optimization by the fuzzy interval uncertainty optimization model, the economic benefits of the FAW Hongqi new energy vehicle manufacturing project were [101,254.71, 6278.5413] million yuan. Compared with the interval uncertainty optimization model, the lower bound of economic benefits increased by 57.68%, and the upper bound decreased by 12.08%, shortening the results of the economic benefits interval. Clarify the current environmental pollution situation of FAW Hongqi’s new energy vehicle manufacturing enterprise, provide data support for sustainable development of the enterprise, and provide reasonable decision-making space for enterprise decision-makers.

Smart grid enterprise decision-making and economic benefit analysis based on LSTM-GAN and edge computing algorithm

As the next-generation power system, smart grid presents challenges to enterprises in managing and analyzing massive data, meeting complex operational and decision-making demands, and predicting future power demand for grid optimization. This paper aims to proposed a fusion algorithm for smart grid enterprise decision-making and economic benefit analysis, enhancing the accuracy of decision-making and predictive capability of economic benefits. The proposed method combines techniques such as Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), and edge computing. The LSTM model is employed to model historical data of the smart grid. The GAN model generates diverse scenarios for future power demand and economic benefits. The proposed method is evaluated on four public datasets, including the ENTSO-E Dataset, and outperforms several traditional algorithms in terms of prediction accuracy, efficiency, and stability. Notably, on the ENTSO-E Dataset, the proposed algorithm achieves a reduction of over 46.6% in FLOP, and a decrease in inference time by over 48.3%, and an improvement of 38% in MAPE. The novel fusion algorithm proposed in this paper demonstrates significant advantages in accuracy and predictive capability, providing a scientific basis for smart grid enterprise decision-making and economic benefit analysis while offering practical value for real-world applications.

Digital government and corporate leverage: Evidence from China

Corporate leverage is an indicator of economic health, and this topic has attracted a great deal of attention since the international financial crisis of 2008. This paper constructs a model of enterprise decision-making under a digital government and theoretically analyzes how the government digital reform impacts corporate leverage and the mechanism of this impact. Theoretical analysis has previously shown that digital reforms by governments help to ease the information asymmetry between banks and enterprises, which in turn affects the actual economic activities of enterprises. Based on these findings, the “one-stop government service” natural experiment used in this paper and the empirical analysis using a multiphase difference-in-differences (DID) method show that digital government can inhibit the short-term debt financing of enterprises while improving their long-term debt financing. This study further finds that the digital government can improve the level of long-term debt for long-term use, thereby reducing corporate leverage. By enriching the theoretical and empirical research on government digital reform, this paper contributes significant theoretical and practical insights to the literature on corporate leverage in the context of government factors.

Analysis of production decision-making evolution of steel enterprises under carbon border adjustment mechanism

This work explored the changes in production decision-making trends of Chinese steel enterprises under the influence of the carbon border adjustment mechanism. First, using evolutionary game theory, the interactive mechanism of complex production strategies among steel enterprises considering the carbon border adjustment mechanism was studied, including the impact of government subsidy coefficients, additional profits and carbon tax prices on enterprise decision-making. Second, the influence of key parameters on the dynamic evolutionary process was analysed. On this basis, the empirical simulation method was used to verify the game model and the main conclusions. Finally, the sensitivity analysis of the selected parameters was determined using Matlab software. The results showed that additional profits from green investment, government subsidy coefficients, input-output values and carbon tax prices had a higher impact on the evolution of enterprise production strategies. The results of this study provide a decision-making basis for the selection of future production methods for steel enterprises.

Optimal strategies for innovation and market allocation in joint production

Capacity sharing is an important way for relevant enterprises to save production materials. This paper constructs a capacity sharing decision-making model that considers market competition intensity, and introduces the independent market size of participating entities into the model design. This paper explores the impact mechanism of factors such as market competition intensity, independent market size of participating entities, and innovation cost coefficient on system decision-making. Research has found that the increase in independent market size has a consistent impact on the innovation and pricing decisions of enterprises sharing production capacity. Although the increase in independent market size enhances the sharing ability of production line innovation costs, it may not necessarily alleviate the problem of excessive competition among participating entities in overlapping markets. It is also necessary to specifically consider the impact of market competition intensity. The specific research conclusions provide decision-making basis for enterprises to participate in the process of capacity sharing, and also provide theoretical basis for relevant government departments to intervene in the process of capacity sharing.

Research on the Game Behavior of Environmental Protection Strategies Between Government and Enterprises

In recent years, the global environment has been deteriorating. To achieve win-win environmental protection and economic development, the Chinese government has issued various environmental governance policies. However, as an important part of the economy and society, enterprises often ignore the impact on the environment while realizing economic development. Therefore, how the government and enterprises develop appropriate environmental protection strategies to achieve parallel environmental protection and development has become the main problem faced at present. Based on the method theory and practical application of game theory, experts in related fields have studied this problem deeply. According to the different research subjects, this paper starts from five different research objects, such as the mutual influence between government and enterprises under environmental governance, the regulation between governments at all levels, the evolution game of government-enterprise-media, the evolution game of government-enterprise-public, and the game of government-enterprise-media-public, introduces the analysis of the decisions of government and enterprises based on game theory, put forward advice to consider the influence of other factors and explore the connection between various factors, to provide detailed reference for scientific governance environment and realize economic sustainable development.

Bottleneck alleviation and scheduling optimization of flexible manufacturing system based on information-energy flow model

The identification and alleviation of bottleneck machines in manufacturing systems are of paramount importance for optimizing production decision-making in enterprises. Extensive research has been conducted by numerous scholars on the identification of bottleneck machines; however, there is a relative scarcity of research, particularly in the context of flexible manufacturing systems, regarding how to effectively alleviate the identified bottlenecks. In this paper, a novel hyper-heuristic evolutionary scheduling algorithm with a bottleneck alleviation strategy based on the information-energy flow model (HESA-BA-IEF) is proposed for training dispatching rules and optimizing decision-making in flexible job shops with bottleneck machines. HESA-BA-IEF constructs an information-energy flow model for flexible job shops based on complex networks. Through this model, dynamic changes in machine processing status and energy consumption during the scheduling process can be effectively simulated, facilitating the accurate identification of bottleneck machines. Moreover, the algorithm adopts the genetic programming hyper-heuristics and introduces a scheduling mechanism considering the alleviation of bottleneck machines to optimize the makespan and total energy consumption, while simultaneously alleviating bottlenecks. Experiments show that HESA-BA-IEF generates dispatching rules that optimize scheduling and alleviate bottlenecks simultaneously. Furthermore, statistical analysis reveals a 7.71% reduction in bottleneck metrics of production line due to 30.40% scheduling rounds with bottleneck alleviation mechanism in effect.

Defining Inheritance Risk Management as A New Concept Towards Sustainability of Family Businesses

This study investigates the relationship between success, Inheritance Risk Management (IRM), and sustainability in family businesses. This paper is based on a quantitative approach. The population includes family-owned businesses located in Abu Dhabi that have been in operation for at least two generations. The study sample consisted of family-owned business members. However, this paper focuses only on measuring variables and testing hypotheses for the proposed measurement. Due to the complexity of the model, Smart PLS-4 was used. Through an analysis of empirical data and theoretical frameworks, the research explores the direct and mediated relationships between these key variables. The findings underscore the critical role of success in driving effective risk management practices within family enterprises. Furthermore, the study highlights the significance of IRM in promoting the sustainability and resilience of family businesses over time. The results reveal a direct positive correlation between success and sustainability, emphasizing the importance of achieving and maintaining success for long-term viability. Additionally, the mediating role of IRM underscores its crucial contribution to the overall sustainability of family businesses. The study identifies various challenges in managing inheritance risks and ensuring the continuity of family enterprises, including maintaining family control, balancing family and operational responsibilities, succession planning, grooming successors, and respecting family elders. By addressing these challenges and leveraging IRM strategies, family businesses can navigate uncertainties and capitalize on opportunities, ensuring continued success across generations. These findings provide valuable insights for strategic decision-making and resource allocation in family enterprises, guiding efforts to enhance governance structures, succession planning, and risk mitigation practices. In addition, this research contributes to advancing our understanding of the complexities surrounding family businesses and underscores the importance of proactive risk management and strategic planning for long-term sustainability.

Preference of Chinese food production enterprises to government regulatory Information——A choice experiment approach

In recent years, despite the fact that the Chinese government is closely monitoring food safety, the perception of food production enterprises is not obvious. The reason is that information asymmetry hinders the effective transmission of regulatory information to food production enterprises. In the present research, a choice test is conducted to explore the preference of decision-makers for the information on government regulations in 224 food production enterprises with violations. It is found out that the decision-makers of food production enterprises have a strong preference for the regulatory information released by local governments. With a preference for reference information, compared to those who violate the law just once, decision-makers in food production companies that have several infractions exhibit a high "reference dependence" mentality. Also, the preference of different decision-maker characteristics shows an evident heterogeneity, as does the preference of various enterprises for the regulatory information about food safety. It is recommended that the government should improve the mechanism of disclosing the information about food safety, and focus on tailoring the information to different types of enterprises.

СУЧАСНІ ПІДХОДИ ОЦІНКИ ДО ОЦІНЮВАННЯ ЕФЕКТИВНОСТІ ДИВЕРСИФІКАЦІЇ БІЗНЕС-ПРОЦЕСІВ В НЕСТАБІЛЬНИХ ЕКОНОМІЧНИХ УМОВАХ

The study is aimed at highlighting modern methods of assessing the effectiveness of business process diversification, taking into account unstable economic conditions. The following methods were used to solve the tasks: the dialectical method of scientific knowledge, the method of analysis and synthesis; the method of comparison, description and generalisation. As a result of the study, approaches to assessing the effectiveness of business process diversification strategies, including marketing, strategic, financial and risk approaches, were clarified and systematised. Particular attention is paid to the financial approach, which allows to qualitatively and quantitatively assess the effectiveness of diversification strategies, taking into account various aspects of their implementation. It is also determined that the successful implementation of busi ness process diversification can have a positive impact on the economic, technological and resource aspects of an enterprise, ensuring increased profitability, introduction of innovative technologies and efficient use of resources in the context of European integration. It has been found that the use of different approaches to assessing the effectiveness of diversification allows to comprehensively consider its impact on the enterprise and determine the prospects for its development. The results of the study can be applied in the management of strategic decisions of enterprises in various sectors of the economy, such as: business economics, finance, management, administration. In the context of economic instability, it is important to use a variety of approaches to assess the effectiveness of business process diversification, which will allow enterprises to adapt to changes and ensure sustainability in development. Such an integrated approach will help to increase competitiveness and successfully function in an unpredictable market environment.

Marketing Strategy of Private Enterprises Based on Bayesian Dynamic Panel Model of Machine Learning Algorithms

Machine learning algorithms have attracted widespread attention in both industry and academia. This article mainly studies the marketing strategy decision-making of private listed enterprises based on Bayesian panel data model. By constructing a Bayesian static panel data model and a Bayesian dynamic panel data model, an empirical analysis was conducted on the debt financing decisions of private enterprises from two aspects: external financial environment and internal governance. The experimental results show that the MC error and standard deviation of parameter estimation for Bayesian static panel data model and Bayesian dynamic panel data model are both very small. This method contains more information, increases observation data and degrees of freedom. This article provides important theoretical guidance for the coordinated development of private listed enterprises and state-owned enterprises. It is conducive to promoting the coordinated development of the entire national economy.