Enterprise Human Resource Management Research Articles

The correlative factors of enterprise culture and enterprise human resource based on data analysis and federated learning

Under the current big topic of enterprise management, how to cultivate, use, and maintain talents is the critical problem of modern human resource management. Based on big data mining, cloud computing, and other related model optimization technologies, this study explores the crucial significance of enterprise culture construction and enterprise human resource management in achieving the business objectives of the entire enterprise. The establishment of this model also means that the enterprise’s profit margin and business indicators have been improved and developed under a certain model. The case results demonstrate that the optimized competency model is significant to studying corporate culture management system behavior, policy analysis, and improving corporate human resource management policies.

Influencing Factors and Mechanisms of Value Co-Creation in Artificial Intelligence-Driven Human Resource Management: A System Dynamics Simulation

In the era of artificial intelligence, human resource management has undergone significant changes compared to traditional approaches regarding value creation methods and influencing factors. This research aims to utilize grounded theory to comprehensively explore the influencing factors of value co-creation in enterprise human resource management within the context of artificial intelligence. Additionally, this research seeks to capture the dynamic relationships, causal links, and evolutionary patterns among the various elements within the system by constructing a system dynamics model. The results indicated that (1) Environmental factors primarily play a regulatory role, organizational factors serve a supportive role, and participant factors act as the driving force in influencing value co-creation in human resource management. (2) In the context of artificial intelligence, both hardware infrastructure and software capabilities can significantly impact value co-creation in human resource management. This research complements current research on the influencing factors of value co-creation in enterprise human resource management. It offers new perspectives and frameworks for the theoretical development and practical application of value co-creation in this area, supporting companies in effectively managing and developing value co-creation in human resource management.

The Strategy of Human Resource Management Based on the K-Means Clustering Algorithm

With the continuous accumulation of enterprise data and the continuous development of technology, data-driven decision-making has become an important trend in enterprise management. Human resource management, as an important component of enterprise management, also requires the use of data analysis tools to optimize the decision-making process. Traditional human resource management strategy algorithms are often based on experience and intuition, lacking scientific data support. These algorithms often struggle to achieve ideal results when dealing with large and complex human resource data. This study aims to provide more scientific and accurate data support for human resource management by introducing the K-means algorithm. The main research purpose of this paper is to detect and identify the data in enterprise human resource management. Data mining can realize the comprehensive detection and analysis of poetry, but the application of data mining algorithms in human resource management data processing is not much. This paper hopes to analyze the anomaly of human resource data statistics by data mining method. According to the characteristics of the K-means algorithm and DBSCAN algorithm, a hybrid K-means algorithm is proposed in this study, which can automatically generate a more appropriate K value and realize parameter self-adaptation with less manual intervention. The optimized clustering K-means algorithm obtains the initial value of DBSCAN through calculation, and then the abnormal data of human resources statistics can be obtained through the second clustering calculation. The optimized K-means algorithm can detect human resource statistics data in real time, and give a new idea for human resource analysis of data anomalies.

Discussion on the Role of Chinese Traditional Culture in Enterprise Human Resource Management

Discussion on the Role of Chinese Traditional Culture in Enterprise Human Resource Management

Legal Risks and Prevention Strategies in Human Resources Management of Y Fujian Branch

As national laws, regulations and rules tend to improve, and the legal awareness of workers and the awareness of their rights gradually rises, the legal risks in the management of human resources in enterprises are increasing, and this change of situation has put forward higher requirements for the level of human resources management in enterprises. This paper mainly introduces the general situation of Y Fujian Branch and analyzes its human resource management status in detail. Then it analyzes the legal risk and its causes in human resource management. Finally, according to the legal risks existing in human resource management of Y Fujian Branch, the corresponding prevention strategies are put forward. It is hoped that this study can provide effective preventive strategies for Y Fujian Branch to fully cope with the legal risks in its human resource management, and can also provide corresponding reference value for other enterprises' human resource management.

An Analysis of the Application of Performance Appraisal in Enterprise Human Resource Management

An Analysis of the Application of Performance Appraisal in Enterprise Human Resource Management

Research on the Development of Human Resource Management in Contemporary Chinese Enterprises

Over time, human resource management has evolved from a purely administrative function to a key business partner closely linked to an organization's strategy. This contemporary human resource management increasingly relies on technology, and these technology tools provide HR professionals with more data and insights to support more effective decision making. To improve their competitiveness, enterprises must fully tap the potential of human resources. At present, Chinese enterprises have some problems and deficiencies in human resource management, and it is urgent to analyze the root causes of the problems and actively reform the management system and measures according to the actual situation of enterprises. Therefore, this study will analyze the current situation of enterprise human resource management and put forward management strategies, which is of great significance for enterprise reform.

Social Media and Cloud Computing Impact on Human Resource Management in Multinational Enterprises

To address the issues of high storage costs for human resource data, resource management of human resource systems, and employee social interaction in human resource management, this study proposes an adaptive intelligent HR data placement strategy based on genetic algorithms. Additionally, a fitness model and an employee social interaction model are presented. The fitness model utilizes genetic algorithms to optimize data storage strategy and server load balancing, resulting in reduced overall costs and efficient resource utilization. This is achieved by comprehensively considering data transmission latency and storage costs. The employee social interaction model analyzes social media blog post topics and employee ranks, and employs a co-training method to predict employee interactions. The experimental results indicated that the placement strategy can improve the HR data transfer by nearly 50% and effectively reduce the standard deviation of server load by about 10-15%. The accuracy, recall, F1 value, and precision of the employee social interaction model were 77.89%, 63.97%, 70.32%, and 71.78%, respectively. The proposed strategy and model demonstrated higher accuracy and robustness in predicting and analyzing employee social interactions, thus providing more reliable decision support for human resource management.

Research on Enterprise Human Resource Management Reform Strategy in the Era of Big Data

In the 21st century, with the development of the Internet, mobile devices, and information technology, society has entered a new era: the era of big data. With the help of big data technology, enterprises can obtain massive market and consumer data, realize in-depth analysis of business and market, and enable enterprises to have a deeper understanding of consumer needs, preferences, and behaviors. At the same time, big data technology can also help enterprises carry out human resource management innovation and improve the performance and competitiveness of enterprises. Of course, from another perspective, enterprises in this era are also facing severe challenges. In the face of massive data processing and analysis, it requires superb data processing and analysis capabilities. Secondly, enterprises need to reconstruct their management system to adapt to the changes in the era of big data. Enterprises must treat data as assets and establish a perfect data management system. In addition, enterprises also need to pay attention to protecting customer privacy and data security to avoid data leakage and abuse. In this context, this paper will explore the thinking of enterprise human resource management innovation in the era of big data, and put forward some suggestions on enterprise human resource management innovation.

Research on Alibaba company’s Digital Human Resource management and Recruitment Information Platform: A systematic case study

In the 21st century, As data-based human resource management, AI HRM technologists and digital recruitment have become a major trend in the development of enterprises, the multi-faceted video interview artifact will help enterprises to digitally transform their recruitment and create a revolution in video interview efficiency. Although Human resource management, digital recruitment, and the training of talents have gained a lot of experience and methodology. Moreover, This study also uses the Documentary analysis and TAM theoretical model for analysis. The aspect of digital human resource management includes many factors. Alibaba company starts from the human business and human resource meets the end of the business. Alibaba company defines five key end-to-end digital processes and specifications here: employee onboarding, employee deployment, and employee satisfaction. Performance-based compensation, employee ability training, and employee turnover optimization. To sum up, The research of this paper mainly uses the mixed method of qualitative analysis and quantitative mixed analysis to conduct research and analysis, and uses excel or SPSS 27 software to perform ANOVA analysis on the sample data, and concludes the importance of human resources digitization and recruitment to Ali-baba company. The findings of the study not only not only deepen the research on the development of digital human resource management in enterprises, but also provide valuable reference for the research and development of AI technology and new digital technology for human resource management and recruitment platforms.

Exploration on human resource management and prediction model of data-driven information security in Internet of Things

The advent of the Internet of Things (IoT) has accelerated the pace of economic development across all sectors. However, it has also brought significant challenges to traditional human resource management, revealing an increasing number of problems and making it unable to meet the needs of contemporary enterprise management. The IoT has brought numerous conveniences to human society, but it has also led to security issues in communication networks. To ensure the security of these networks, it is necessary to integrate data-driven technologies to address this issue. In response to the current state of human resource management, this paper proposes the application of IoT technology in enterprise human resource management and combines it with radial basis function neural networks to construct a model for predicting enterprise human resource needs. The model was also experimentally analyzed. The results show that under this algorithm, the average prediction accuracy for the number of employees over five years is 90.2 %, and the average prediction accuracy for sales revenue is 93.9 %. These data indicate that the prediction accuracy of the model under this study's algorithm has significantly improved. This paper also conducted evaluation experiments on a wireless communication network security risk prediction model. The average prediction accuracy of four tests is 91.21 %, indicating that the model has high prediction accuracy. By introducing data-driven technology and IoT applications, this study provides new solutions for human resource management and communication network security, promoting technological innovation in the fields of traditional human resource management and information security management. The research not only improves the accuracy of the prediction models but also provides strong support for decision-making and risk management in related fields, demonstrating the great potential of big data and artificial intelligence technology in the future of enterprise management and security.

Challenges and Opportunities for Corporate Human Resource Management in the Context of Artificial Intelligence

With the continuous development and maturity of Internet technology, big data and artificial intelligence have gradually become the new products of the 21st century, and their applications are expanding while promoting the development of science and technology. As artificial intelligence has the advantages of fast, accurate and convenient, its application in the field of enterprise human resource management has brought a new working mode for enterprise human resource management and put forward higher requirements for enterprise human resource managers. On this basis, this paper gives an overview of the development and application of artificial intelligence, discusses the specific application of artificial intelligence in enterprise human resource management, focuses on the challenges and opportunities faced by enterprise human resource management in the context of artificial intelligence, and aims to bring technical support to relevant departments.

Digital Transformation of Enterprise Human Resource Management Enabled by Big Data

With the continuous development of big data technology, the digital transformation of enterprise human resource management has become a development trend. Human resources is one of the most important resources of enterprises, which is crucial to the competitiveness of enterprises. Enterprises need to attract, retain, and motivate excellent employees, thereby enhancing the innovation ability of enterprises and improving competitiveness and market share in the market. To maintain advantages in the fierce market competition, enterprises need to adopt more scientific and effective human resource management methods to enhance organizational efficiency and competitiveness. At the same time, this paper analyzes the dilemma faced by enterprise human resource management, points out the new characteristics of enterprise human resource management enabled by big data, and puts forward feasible suggestions for enterprise digital transformation.

Problems and Countermeasures of Performance Appraisal in Enterprise Human Resource Management

With the rapid advancement of science in society, driven by the highly updated enterprise technology system, human resource management plays an increasingly important role in the production and operation activities of enterprises, and has become an important factor determining the core competitiveness of enterprises. Therefore, exploring the performance appraisal management of enterprises in human resource management is of great significance for further improving the competitiveness of enterprises and making better use of the advantages of human resources. Based on the theory of performance appraisal management in human resources and taking Xu Fu Ji Food Company as an example, this paper points out the current status and existing problems of the enterprise, such as unclear assessment purpose, neglect of the overall performance management of the enterprise, lack of performance appraisal training and summary links, and puts forward the advantages of clarifying the purpose of performance management, attaching importance to the overall team assessment, and increasing the intensity of performance appraisal training and summary Make suggestions.

The Impact of Artificial Intelligence on Enterprise Human Resource Management

Artificial intelligence is an important product of the progress of scientific and technological development, which has been widely promoted in various industries and fields of society, and has achieved good application results, with broad development space and prospects. Especially in the full application of enterprise human resource management work, artificial intelligence reflects a great advantage, realizing the optimization of organizational structure and human resource management innovation, improving the overall work efficiency, etc., but at the same time, it also has certain negative impacts, such as the industry threshold enhancement, personnel elimination, etc., which has brought about certain negative impacts on the harmonious development of society. The purpose of this paper is to discuss the application of artificial intelligence in enterprise human resource management, and analyze its impact on enterprise human resource management, in order to further improve the application of artificial intelligence, to provide technical support for enterprise human resource management.

Editorial for Human Resources Management and Services (Volume 6, Issue 1)

Volume 6, Issue 1 covers a wide range of fields, mainly discussing issues related to human resource management in enterprises, hotels, schools and organizations; spanning Indonesia, the United States, China, Malaysia and several other countries. By reading these articles, readers can gain a broader understanding of the status and development trends of human resource management and services in various fields and countries in today’s society.

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.

Exploring the Digital Path of Human Resource Management in Innovation and Entrepreneurship Enterprises

The digitization of human resource management functions can enhance the adaptability of human resource management and promote the comprehensive digital development of innovative and entrepreneurial enterprises. This article first summarizes and evaluates the connotation and research status of the digitalization of enterprise human resource management. Secondly, it analyzes the influencing factors of digitalization of human resource management in innovative and entrepreneurial enterprises from three aspects: employee factors, organizational factors, and technological factors. Finally, it designs a digitalization plan for human resource management in innovative and entrepreneurial enterprises from four aspects: analyzing the current situation, preparing thoroughly, designing plans, and building systems. It emphasizes the value of digitalization of enterprise human resource management for innovative and entrepreneurial enterprises.

Genesis of human resource management paradigms

Human Resource Management emerged as a concept in the 1980s. The rebranding of personnel management quickly gained popularity, but many organizations needed to become acquainted with the evolution of theoretical research underlying this concept. This study aims to provide a brief and accessible overview of human resource management's evolution and current research in this field. An analysis of research on the origins of human resource management is conducted, addressing issues related to the functions, roles, and strategies of managers and current debates on how human resource management affects organizational effectiveness. The results of a retrospective analysis of approaches to interpreting the "personnel management" concept are presented. The theoretical framework for defining "enterprise human resource management" is justified. The genesis of human resource management paradigms is considered from technocratic thinking, based on managerial rationalism, to future-oriented management with a priority orientation towards strategic human resource management. It is noted that mastering advanced management technologies is impossible without mastering the fundamentals of the humanistic paradigm, which provides a comprehensive understanding of the evolution and functioning of various organizations, taking into account the deep mechanisms of human behavior and the development of human potential in the face of changing external environments. Additionally, business globalization implies that human resource management professionals must be more proactive in areas such as business ethics, corporate governance, and managing employees' work-life balance. Considering the stochastic nature of the external environment, uncertainty, political and economic instability, and economic globalization, it is noted that the potential of human resources serves as a tool for reducing business risks. In these conditions, business exists for people rather than people for business. It is noted that business globalization implies that human resource management professionals must be more proactive in areas such as business ethics, corporate governance, and managing employees' work-life balance. Changes in communication and information technologies, such as the digital revolution, satellite communication, and cellular networks, will require the adoption of strategic international or global models of personnel management, which will be implemented through radically new approaches to strategies, structures, organizational culture, personnel management practices, and labor relations. Keywords: human resource management, personnel management, organizational effectiveness, productivity leadership, management, organizational culture.

The Implementation Path of Digital Intelligent Transformation in Enterprise Human Resource Management in the Era of VUCA

The Implementation Path of Digital Intelligent Transformation in Enterprise Human Resource Management in the Era of VUCA