Current Enterprise Research Articles

The Value of Red Culture: Evidence from Enterprise environmental Performance

As an indispensable part of the red culture, the spirit of Long March has important guiding significance for the current enterprise environmental performance management and the supervision of violations. This paper uses the series of activities marking the 80th anniversary of the victory of the Long March to construct a quasi-natural experiment, and the regression analysis finds that in 2016 and the following years, the level of environmental performance of enterprises located along the Red Army's Long March has significantly improved, indicating that the spirit of Long March can promote the improvement of corporate environmental responsibility awareness. At the same time, from the perspective of entrepreneurial literacy and environmental supervision, this paper explores the mechanism of Long March spirit to improve enterprise environmental performance, so as to provide an example for the development path of socialist culture with Chinese characteristics.

Innovation of Management Accounting and Promotion of Enterprise Competitiveness

China is in the era of rapid development of big data, and the competition among enterprises is becoming more and more fierce. Simple financial accounting cannot meet the development goals of current enterprises. With the rise and development of management accounting, its work function has been gradually concerned by enterprises and society, and some enterprises have begun to realize the use of management accounting to improve their financial functions and enhance their competitiveness. In this scenario, the integration of financial accounting and management accounting is particularly important. Because the rise and development of management accounting in China is short, there are many problems in its application and development. From the perspective of innovative development of management accounting, this paper analyzes the problems of management accounting in modern enterprises, and puts forward how enterprises can use innovative ways of management accounting to enhance their competitiveness and help enterprises get long-term and steady development.

Key factors and path selection for enterprise digital transformation: configuration analysis based on fsQCA

The new digital technology revolution is spurring corporate digital transformation. Presently, the majority of enterprises are still in the digitalization stage. They have yet to pinpoint the key factors and suitable paths for their transformation. Therefore, this study aims to determine which and how factors affect this transformation to improve the current enterprise's digital transformation. We extract key elements affecting corporate digital transformation. Taking 98 representative businesses as examples, we utilize the fuzzy-set qualitative comparative analysis approach (fsQCA) to investigate how different factors combine to achieve digital transformation. The results show that: (1) No single factor can achieve digital transformation for enterprises, as it requires a combination of multiple factors. (2) Four configuration paths can lead to corporate digital transformation. (3) A business can equivalently substitute resource consolidation with strategic planning and human resources to drive digital transformation. This study offers multiple paths for achieving corporate digital transformation to guide businesses in their choice of digital transformation pathways.

Analysis of the Outstanding Problems in Enterprise Logistics Management

This paper first analyzes the main problems existing in the current enterprise logistics management, including the high logistics cost, the lack of information level, the lack of professional talents and the weak awareness of green logistics. In view of these problems, this paper puts forward a series of coping strategies, such as optimizing the layout of logistics network, strengthening the construction of information system, training professional logistics talents, promoting the development of green logistics and strengthening the coordination of supply chain. Through the implementation of these strategies, it aims to improve the efficiency and efficiency of enterprise logistics management and enhance the market competitiveness of enterprises. This study has important reference value for enterprises to improve logistics management practice and meet current challenges.

Evaluation of innovation efficiency of high-tech enterprise based on DEA and Malmquist index under the background of sustainable development

Purpose This paper aims to promote the higher quality development of high-tech enterprises in China. While science and technology have greatly promoted human civilization, resources have been excessively consumed and the environment has been sharply polluted. Therefore, it is particularly important for current enterprises to make use of scientific and technological innovation to maximize the benefits of mankind, minimize the loss of nature, and promote the sustainable development of our country. Design/methodology/approach By using DEA-Banker-Charnes-Cooper (BCC) model and DEA-Malmquist model, this paper comprehensively examines the innovation efficiency of high-tech enterprises from both static and dynamic perspectives, and conducts a provincial comparative study with the panel data of ten representative provinces from 2011 to 2020. Findings The research findings are as follows: the rapid number increase of high-tech enterprises in most provinces (cities) is accompanied by an ineffective input–output efficiency; the quality of high-tech enterprises needs to comprehensively examine both input–output efficiency and total factor productivity; and there is not a positive correlation between element investment and innovation performance. Research limitations/implications Because the DEA model used in this paper assumes that the improvement direction of invalid units is to ensure that the input ratio of various production factors remains unchanged but sometimes the proportion of scientific and technological activities personnel and the total research and development investment is not constant. In the future, the nonradial DEA model can be considered for further research. Due to historical data statistics, more provinces, cities and longer panel data are difficult to obtain. The samples studied in this paper mainly refer to the provinces and cities that ranked first in the number of national high-tech enterprises in 2020. Limited by the number of samples, DEA analysis failed to select more input and output indicators. In the future, with the accumulation of statistical data, the existing efficiency analysis will be further optimized. Originality/value Aiming at the misunderstanding of emphasizing quantity and neglecting quality in the cultivation of high-tech enterprises, this paper comprehensively uses DEA-BCC model and DEA Malmquist index decomposition method to make a comprehensive comparative study on the development of high-tech enterprises in ten representative provinces (cities) from two aspects of static efficiency evaluation and dynamic efficiency evaluation.

SCIENTIFIC AND METHODOLOGICAL ENSURING THE PROCESS FORMATION OF THE EMPLOYEE COMPETENCE MODEL

The article outlines the expediency of application and the main problematic issues of implementing the principles of the competency approach in personnel management of current enterprises, in particular, related to the process of formation and practical use of its main tool - the model of employee competencies. A scientific survey of the significant assets of scientists and practitioners on this topic was carried out, as a result of which it was established that there is a need to finalize currently unresolved tasks regarding the clarification of the sequence and the development of scientific and methodological support and practical recommendations for the construction of such models, since the given processes are mostly abstract, difficult for practical application due to the lack of clear instructions and tools for the implementation of each stage. The main goal of the article is to improve the process of forming the model of employee competencies by clarifying the sequence of its development, specifying actions at each stage and developing methodological tools for practical application. The process of forming the model of employee competencies was compiled, presented in the form of a logical sequence of specific ac­tions and decisions with the use of a specially developed toolkit, based on the choice of a certain approach and involves the construction of a model of competencies for employees of diffe­rent categories with a different number of constituent elements. For example, for employees in managerial posi­tions there are 4 constituent elements; for specialists and workers in labourer’s positions - 3 constituent elements etc. A scientific-methodical toolkit and relevant recommendations for its implementation were developed, an approbation was carried out on an example (a model of the competences of fitters in mechanical assembly works was developed). Competences of mechanical assembly fitters included in the developed model were assessed using the "360° method"; taking into account the weight factor of each competence, the general level of their competence is determined. The results of scientific research are the basis for making recommendations for improving the level of employees’ competence.

Integration and Innovation Path Analysis of Enterprise Marketing Data Management Based on Deep Learning

INTRODUCTION: To explore the integration and innovation path of enterprise marketing data management based on deep learning to adapt to today's competitive business environment. With the continuous development of information technology, enterprises are faced with a large amount of marketing data, and how to efficiently manage and integrate these data has become an essential issue for enterprises to improve their market competitiveness. Deep learning, as a necessary technical means of artificial intelligence, provides enterprises with more intelligent and precise data processing tools.OBJECTIVES: The primary purpose of the study is to solve the problems of marketing data management in traditional enterprises and to achieve better integration and management of data through deep learning technology. Specifically, the goal is to explore the potential of deep learning in improving data processing efficiency and accurately analyzing user behavior and trends. By achieving these goals, organizations can better understand market needs, develop more effective marketing strategies, and stand out in a competitive marketplace.METHODS: This study adopts a comprehensive approach, including a literature review, case study, and empirical analysis of deep learning algorithms. First, the main issues of current enterprise marketing data management and the latest progress in deep learning were understood through an in-depth study of the literature in related fields. Second, several enterprise cases were selected to gain a deeper understanding of the challenges and needs of enterprises in marketing data management through field research and data collection. Finally, a series of deep learning algorithms were designed and implemented to validate their effectiveness in real-world applications and analyze their impact on data integration and innovation paths.RESULTS: The results of the study show that deep learning has significant advantages in enterprise marketing data management. By using deep learning algorithms, enterprises are able to handle large-scale marketing data more efficiently and achieve intelligent data integration and accurate analysis. This not only improves the efficiency of data processing but also provides enterprises with deeper market insights that help develop more targeted marketing strategies.CONCLUSION: The results of the study are of guiding significance for enterprises to realize data-driven marketing decision-making, which provides strong support for enterprises to maintain their competitive advantages in the highly competitive market. Future research can further explore the application of deep learning in different industries and scenarios, as well as how to optimize deep learning algorithms further to meet the changing needs of enterprises.

Strategies for Leveraging the Role of Young Teachers in Enterprise Practical Courses Vocational Colleges in China

Enterprise practical courses are important courses that emphasize practical operations, professional ethics, integrate theory with practice, and possess specificity and flexibility. Teachers serve as advocates for school-enterprise cooperation and communication, maintain the connection between schools and society, and promote vocational education. However, there are several issues in current enterprise practical teaching, such as the separation between school learning and student enterprise practice, inconsistency between enterprise goals and student training, and lack of evaluation system for student internships. This article aims to address these issues by enhancing teachers' professional abilities and practical teaching levels, thereby providing better support and assistance for students' career development and employment competitiveness.

Exploring the Optimisation of Enterprise Performance Management in the Context of Artificial Intelligence

The impact of artificial intelligence on enterprises has gradually penetrated the human resource management of enterprises, and artificial intelligence is accelerating the excess of traditional human resources to predictive human resources, which also requires more talents in the field of artificial intelligence to devote themselves to enterprises. Through literature review and relevant cases, this paper finds that the current enterprise performance management has the problems of backward performance appraisal methods, lack of effective performance communication, and insufficient use of performance evaluation results. It is found that with the help of AI, enterprises can use big data and algorithms, enterprises can establish a more scientific performance management system, use AI to select appropriate performance management tools, and finally get effective performance appraisal results. Enterprises can use AI coaching and transparent performance feedback to promote performance communication and make performance results can play a role in promoting employee performance improvement. This paper concludes that the reasonable use of AI by enterprises can solve many existing problems of their performance management and can save time and labor costs for enterprises. Therefore, enterprises need to seize the opportunities brought by AI and pay attention to the research of AI technology to help improve performance management.

Mode Innovation and Discussion of Enterprise Financial Management in the New Economic Background

The development of the globalized economy has also made enterprise financial management work into a new stage of reform, the; transformation of the market economic system has also made the enterprise financial management work content and mode of change the traditional financial management model has failed to meet the needs of the current enterprise, and even hinder the development of enterprises. In the new economic background promoting financial management reform and innovation is not only the way of enterprise development. It is also in line with the trend of the times, where the article through the trend of economic development and in-depth analysis of the current financial management situation.By analyzing published literature and using the literature analysis method, we summarize the current problems in corporate financial management and propose corresponding solutions to the problems based on the key points of the problems, thereby providing reference and help for corporate development.

A practical tool to enable Indigenous enterprise planning and development grounded in culture

Globally, Indigenous people seek to develop sustainable livelihood options that enable them to practice their culture, look after their traditional estates and generate economic development outcomes for their wider community. Enterprise development can and may provide one such pathway. However, challenges can arise with regard to reconciling the core drivers of ‘economic development’ with aspirations to practice and preserve culture. Current enterprise development approaches and models do not always suit Indigenous contexts. In this paper, we present a practical tool to enable Indigenous leaders, their partners, and others, to consider enterprise development options grounded in culture that may generate multiple benefits including economic outcomes. Our tool combines critical review of alternative development models, with empirical research to outline a set of foundational principles, building blocks and potential enterprise development options. We apply the practical tool to a case study of a nascent enterprise from the northern Australia Indigenous-led bush products sector. The case study illustrates how enterprise development planning is integral and discussions should consider how to enable cultural governance, protection of Indigenous cultural and intellectual property, potential benefits and sharing, access to resources, as well as the ‘building blocks’ for enterprise development and consideration of different enterprise approaches. The practical tool aims to ensure development pathways build on local economies and ecologies, do not compromise culture and recognise the influence of extra-local political economies on lived experiences and outcomes.

Research on kitting evaluation method of complex electromechanical products

Precise and efficient product kitting evaluations are vital for boosting assembly performance and customer contentment for varied, small-batch, and intricate electromechanical products. However, current enterprise resource planning systems (ERP) provide inadequate support for analyzing the kitting of products. How to evaluate the degree to which customers' demands for a complete set of multiple products can be met when adjusting the importance level of customer demands without changing the customer demand date in the production system and affecting the scheduled customer orders has become one of the urgent problems that enterprises need to solve. In response to the above issues, this article presents a method for evaluating product kitting, which takes the maximum quantity of complete sets of products as the optimization objective, considers multiple constraints such as material inventory data and in process business data, and designs a multi-level BOM decomposition algorithm. Finally, a case study of a company producing core components for standard high-speed trains demonstrates the practicality and efficacy of the proposed method.

Machine learning and internet of things applications in enterprise architectures: Solutions, challenges, and open issues

SummaryThe rapid growth of the Internet of Things (IoT) has led to its widespread adoption in various industries, enabling enhanced productivity and efficient services. Integrating IoT systems with existing enterprise application systems has become common practice. However, this integration necessitates reevaluating and reworking current Enterprise Architecture (EA) models and Expert Systems (ES) to accommodate IoT and cloud technologies. Enterprises must adopt a multifaceted view and automate various aspects, including operations, data management, and technology infrastructure. Machine Learning (ML) is a powerful IoT and smart automation tool within EA. Despite its potential, a need for dedicated work focuses on ML applications for IoT services and systems. With IoT being a significant field, analyzing IoT‐generated data and IoT‐based networks is crucial. Many studies have explored how ML can solve specific IoT‐related challenges. These mutually reinforcing technologies allow IoT applications to leverage sensor data for ML model improvement, leading to enhanced IoT operations and practices. Furthermore, ML techniques empower IoT systems with knowledge and enable suspicious activity detection in smart systems and objects. This survey paper conducts a comprehensive study on the role of ML in IoT applications, particularly in the domains of automation and security. It provides an in‐depth analysis of the state‐of‐the‐art ML approaches within the context of IoT, highlighting their contributions, challenges, and potential applications.

Effect of incentive means based on enterprise management innovation reform on relieving the anxiety of employees

BackgroundIn the current enterprise management environment, employee anxiety has become a familiar and serious problem, affecting the work efficiency of employees and the overall operation effect of enterprises. The incentive means of enterprise management innovation reform may help alleviate employees’ anxiety.Subjects and MethodsThis study adopted a randomized controlled trial to select two representative enterprises, in which one enterprise (intervention group) implemented the incentive means of innovation reform, and the other enterprise (control group) maintained the original management style. Incentives for innovation and reform mainly include providing more career development opportunities, improving the working environment, and enhancing employee welfare. The self-rating anxiety Scale and job satisfaction questionnaire were used to evaluate the two groups of employees at regular intervals. The analysis software is SPSS23.0.ResultsThe six-month experiment found that employees in the control group experienced a significantly higher reduction in SAS scores than those in the control group and improved considerably job satisfaction. The average SAS score decreased by 30% in the intervention group, while the average SAS score decreased by only 5% in the control group. The intervention group reported a 20 percent increase in job satisfaction.ConclusionsThe innovation reform and incentive means of enterprise management can effectively alleviate the anxiety symptoms of employees and improve their job satisfaction. This provides enterprises a practical way to improve employees’ psychological state and work efficiency.AcknowledgementIn 2021, the horizontal scientific research project of Tianjin Sino German University of Applied Sciences (No. H2021-063).

Reflections on the Innovation of Enterprise Management Mode under the Background of Internet+

In recent years, the development concept of the Internet+ different kinds of jobs has received a lot of support, and enterprise management can also be deeply integrated with it. So the author aims to explore how companies innovate their management models in response to this trend in the context of the Internet+. To conduct in-depth research, the author used the survey method and the literature research method, focusing on individual company case studies and analyzing, comparing, and summarizing the large amount of data collected by the survey, and thinking about how to apply Internet+ to enterprise management and the Internet+. The result shows that the current enterprises have not changed their management methods in a timely manner, and still adopt traditional and inefficient management models. There is currently a lack of a platform that is more compatible with Internet+, which can maximize its role. The third is the lack of talents with professional skills and innovative thinking in the market. With the advantages of strong interactivity and high efficiency of the Internet platform, enterprises should reform and innovate their own management systems and management methods.

Blockchain in Healthcare: A Comprehensive Survey of Implementations and a Secure Model Proposal

Blockchain's core attributes, including decentralization, transparency, and immutability, have positioned it as a pioneering technology in the realm of financial technology (fintech) and have rendered it highly applicable across diverse industries. The current enterprise ecosystem has faced setbacks primarily due to a lack of trust in the existing infrastructure. This issue can be traced back to the centralized management of healthcare data, making it vulnerable to tampering and fraudulent activities, resulting in financial losses. The existing enterprise ecosystem failed due to the lack of trust in the currently in-place infrastructure. This problem can be attributed to the centralized healthcare data management, which is prone to tampering and fraudulent activities leading to capital loss. The present study relates to a comprehensive survey conducted in timespan from 2018 to 2022 on the implementation of blockchain technology in the healthcare industry, identifying and discussing the key challenges facing the healthcare industry, such as fraud, and scams against healthcare data. It is found that there is an enormous inclination towards the decentralization of patient-centric data. However, a rapid decline is reported due to the privacy and security concerns of the confidential and sensitive data. Moreover, it is noticed that most of the implementations utilized either Ethereum or Hyperledger. Based on the survey's findings, the study proposed a blockchain-based healthcare framework that can address the identified challenges by providing a secure and transparent platform for collecting, storing, and sharing patient health data while prioritizing security and privacy.

THEORETICAL ASPECTS OF STRATEGIC PERSONNEL MANAGEMENT RESEARCH

With the rapid economic development and increasingly fierce social competition, the accelerated development of global digitalization, the current enterprises are characterized by the development of informatization, and the role and impact of human resource management on enterprise performance are becoming more and more prominent. Enterprises are people-oriented, and on the basis of this concept, enterprises gradually explore a human resource management system suitable for enterprises. In the face of the current environment and the task of high-quality development of the country, traditional personnel management can no longer meet the needs of enterprise development, human resource management has gradually been upgraded to the level of strategic planning, and more and more enterprises realize the importance of strategic human resource management. In the face of many challenges, enterprises should be based on the industry, start from the aspect of talent management, stimulate the motivation of internal talents, and continuously improve the autonomy and creativity of internal talents in all aspects of work. Talent management is not only the basic condition for the normal operation of enterprises, but also the focus of whether enterprises can develop smoothly, and the conditions for the continuous improvement of economic benefits of enterprises. If enterprises want to make strategic results, they must establish the connection between human resources and enterprises at the strategic level, and sort out and formulate human resources work plans from corporate strategies. Human resource management has always occupied a very important position in enterprise management, and strategic human resource management is more suitable for the development of enterprises in the current economic and competitive environment. Based on the theory of strategic human resource management, this paper analyzes Huawei's concepts and tools for building a strategic human resources system based on its theoretical concepts, core contents, and importance in enterprises, in order to provide some experience and enlightenment for other enterprises.

The Role of Data Scientists in Modern Enterprises - Experience from Data Science Education

"Data Scientist" has often been considered as the sexiest job of the 21st century. As a consequence, the spectrum of data science education programs has increased significantly in recent years, and there is a high demand for data scientists at many companies. However, what training is required to become a data scientist? What is the role of data scientists in current enterprises? Is the training well-aligned to the practical needs of a job? In this article, we will address these questions by evaluating a survey of people who were trained in a continuing education program in data science in Switzerland. Our study sheds lights on the practical aspects of the data science education and how this newly-gained knowledge can successfully be applied in an enterprise. One of the highlights from the point of view of the database community is the important role of SQL in data science.

Application of computer aided audit system and innovation research of enterprise financial audit under the background of big data

In the rapid development of social economy and science and technology, in the face of the continuous increase of network information resources, the Internet, computer technology, information technology, etc., has changed the content form of daily life and social production, and brought great convenience for people's life and work. From the perspective of enterprise financial audit, the financial audit work with big data technology as the core is much higher than the traditional financial audit work in terms of work efficiency and work quality. Therefore, after understanding the development trend of enterprise financial audit work under the background of big data, this paper mainly studies the relationship between the current enterprise financial audit work and computer-aided audit system according to the emergence of computer-aided audit system in the new era, and defines the development direction of enterprise financial audit work in the future.

A personalized learning theory-based cyber-security training exercise

Current enterprises’ needs for skilled cyber-security (CS) professionals have prompted the development of diverse CS training programs and offerings. It has been noted that even though enterprise staff is now more aware of security threats, the number of successful attacks against companies has all but decreased over the years. Several criticisms were raised against current CS training offerings, which often made them inadequate, or unable to change participants’ behavior and security attitude. One of the main factors CS training programs are often not very effective is the lack of engagement or motivation of participants. This is often the result of training not being tailored to the needs or preferences of participants. In our previous work, we tackled this issue by developing a personalized learning theory-based model for developing CS training frameworks. In this work, we utilize the model to develop two CS training exercises: two game-based scenarios using the CS training video game Cyber CIEGE and one table-top team exercise. The exercises are later tested by involving a group of 12 students from the Norwegian Institute of Science and Technology (NTNU) Information Security master’s degree program. According to the results of the experiment and the feedback from the students, students felt more engaged during the exercises due to having been participants in their development process. This has in turn motivated them to continue using the training tools independently in their spare time. Further research is recommended to establish whether the training development model is adequate for different target groups, as well as better performing than other models when developing full-fledged training programs.