ĐẠI HỌC QUỐC GIA HÀ NỘI TRƯỜNG QUẢN TRỊ VÀ KINH DOANH --------------------- NGUYỄN ĐỨC MINH THE IMPACT OF SMART AUTOMATION ON EMPLOYEE PERFORMANCE IN SAMSUNG DISPLAY VIETNAM TÁC ĐỘNG CỦA TỰ ĐỘNG HÓA THÔNG MINH ĐẾN HIỆU SUẤT LÀM VIỆC CỦA NHÂN VIÊN TẠI SAMSUNG DISPLAY VIETNAM LUẬN VĂN THẠC SĨ QUẢN TRỊ KINH DOANH Hà Nội - 2024 ĐẠI HỌC QUỐC GIA HÀ NỘI TRƯỜNG QUẢN TRỊ VÀ KINH DOANH --------------------- NGUYỄN ĐỨC MINH THE IMPACT OF SMART AUTOMATION ON EMPLOYEE PERFORMANCE IN SAMSUNG DISPLAY VIETNAM TÁC ĐỘNG CỦA TỰ ĐỘNG HÓA THÔNG MINH ĐẾN HIỆU SUẤT LÀM VIỆC CỦA NHÂN VIÊN TẠI SAMSUNG DISPLAY VIETNAM Chuyên ngành: Quản trị kinh doanh Mã số: 8340101.01 LUẬN VĂN THẠC SĨ QUẢN TRỊ KINH DOANH NGƯỜI HƯỚNG DẪN KHOA HỌC: PGS. NGUYỄN NGỌC THẮNG Hà Nội - 2024 DECLARATION I hereby declare that this is my own research project under the instruction of Assoc. Nguyen Ngoc Thang. The data and results stated in the content of the thesis are truthful and have never been published in any previous research.
The research results and documents of others (citations, tables, tables, formulas, graphs and other documents) used in this thesis have been specifically cited by the author. I am fully responsible to the thesis defense council, HSB and the law for the above commitments. Hanoi, 25 March 2024 Nguyen Duc Minh i ACKNOWLEDGMENTS I would like to present my sincere gratitude to my thesis supervisor, Associate Professor Nguyen Ngoc Thang, for his exceptional mentorship. His critical analysis, helpful suggestions, and commitment to my academic development have greatly influenced the direction of my study.
Besides precious academic advices, his kind support in using of scientific tools helps me a lot in completing effectively this thesis. I extend my appreciation to the faculty members including excellent experts, lecturers and the coordinator of the MBA program, Ms. Thuy Duong for their invaluable contributions to my education. Their lectures, discussions, and academic insights have broadened my horizons and inspired me to pursue this study.
Additionally, I would like to acknowledge the assistance of Board of Director of Samsung Display Vietnam for providing not only financial support but also convenient working schedule for the education and research. Lastly, I want to express my appreciation to my colleagues who have contributed to the data survey at Samsung Display Vietnam. This thesis is a testament to the collective effort of those who have contributed in various ways. I am truly fortunate to have such an incredible network of support.
I look forward to receiving feedback and suggestion from experts, professors and colleagues so that my thesis can be most complete and applied effectively in the company. ii CONTENTS DECLARATION. ii LIST OF TABLES .vi LIST OF FIGURES. viii CHAPTER 1: INTRODUCTION.1 Rationale of the thesis .4 Research objective and questions .6 CHAPTER 2: THEORETICAL BACKGROUND .1 Definition of Employee Performance (EP) .2 Measurement of Employee Performance .1 Key Performance Indicators (KPI) .3 Factors affect employee performance .1 Human resource management (HRM) .5 Smart automation in industrial manufacturing .28 CHAPTER 3: RESEARCH METHODOLOGY .2 Sample and survey administration .3 Data analysis method .2 Statistics description measurement .3 Pair-wise t -test .4 Pearson correlation analysis .45 CHAPTER 4: RESULTS AND DISCUSSION .1 Introduction of Samsung Display Vietnam .2 Introduction of Laser technology department in SDV.1 Department‘s function and duty .2 Size and human resource structure .3 Smart automation in the department .3 Cronbach‘s alpha reliability analysis .1 Reliability test of Smart automation level in SDV (A1 scale) .2 Reliability test of HR management (A2 scale) .3 Reliability test of Job security (A3 scale) .4 Reliability test of Company performance (A4 scale).5 Reliability test of Labor management effectiveness (A5 scale) .6 Reliability test of Employee benefit (A6 scale) .7 Reliability test of Employee performance (A7 scale) .4 Descriptive statistics summarization .5 Paired-wise t-test analysis .6 Pearson correlation analysis .7 Linear regression analysis .66 iv CHAPTER 5: CONCLUSION .77 v LIST OF TABLES Table 3.1Smart automation in Company (A1) .5 Labor management effectiveness (A5) .1Human resource structure .2 Statistics reliability of Smart automation – A1 scale .3 Item-Total Statistics reliability of the Smart automation variables .4 Statistics reliability of HR management – A2 scale .5 Item-Total Statistics reliability of HR management .6 Statistics reliability of Job security – A3 scale .7 Item-Total Statistics reliability of Job security variables .8 Statistics reliability of Company performance – A4 scale .9 Item-Total Statistics reliability of Company performance .10 Statistics reliability of Labor management effectiveness – A5 scale .11 Item-Total Statistics reliability of Labor management effectiveness .12 Statistics reliability of Employee benefit – A6 scale .13 Item-Total Statistics reliability of Employee benefit .14 Statistics reliability of Employee performance – A7 scale .15 Item-Total Statistics reliability of Employee performance .16 Descriptive statistics for A1~A7 .17 Pair-wise-t-test of the 7 measurement groups.18 Paired sample correlations of the 6 measurement groups.19 Matrix of Pearson correlation between the 7 measurement groups.20 Regression model summary.22 Liner regression coefficients.67 vii LIST OF FIGURES Figure 2.1 360-degree feedback diagram.1 Laser material processing.3 Smart automation in Laser department in 2019&2023.4 Statistical frequency of measurement group A1~A7.5 Histogram of standard residual.6 Normal P-Plot of Regression standardized residuals.66 viii CHAPTER 1: INTRODUCTION 1.1 Rationale of the thesis The Fourth Industrial Revolution, or Industry 4.0, is defined by the incorporation of cutting-edge technologies and intelligent automation into industrial and manufacturing processes.
A number of technologies, including robotics, artificial intelligence (AI), and the internet of things (IoT), are key factors in the transition of conventional industrial processes into intelligent, effective, and networked systems. Across a range of industries, this revolution has the potential to improve product quality, lower prices, boost productivity, and develop new business models. Applications of AI technology and its related fields have resulted in the development of a new form of automation that helps replace human capabilities, especially cognitive functions like learning and problem-solving, in performing tasks that were once done by humans. This type of automation, according to C.
Coombs et al. [1] is defined as intelligent automation. Unlike previous forms of automation, intelligent automation enables AI machines to learn, adapt, and improve over time. An alternative term, smart automation, was studied by M.
Schmitz et al. [2] as potential applications of robotic process automation (RPA), machine learning (ML) and related hot topics. Recent research performed by J. Singh et al.
[3] has shown potentials of emerging smart automation, which is an integration of advanced technologies including AI, IoT, data analytics, cloud services …, in industrial manufacturing to manage complexity, enhance information awareness, improve processes, and stay competitive. Applications of advanced technologies, especially smart automation with AI, Robotics … have developed strongly and rapidly in Samsung Display Vietnam. This drastically changes the human resource structure, job needs, methods of equipment management, production management and human resource management. The study of the impact of smart automation on employee performance is a crucial area of research and analysis for several reasons, covering work transformation, employee well-being, skill requirements, productivity and efficiency, organization performance, decision making, competitive advantage and ethical considerations.
1 First, smart automation affects workplace transformation, which is the fast- changing nature of work across many industries. Comprehending their impact on staff productivity is crucial for adjusting to the evolving workplace and guaranteeing a seamless shift to alternative methods of operation. The second factor that is impacted is employee well-being. AI and automation have the ability to enhance several areas of the workplace, such decreasing monotonous jobs, optimizing workflows, and boosting productivity.
They could, however, also provide difficulties for workers, such as worries about job security, shifting responsibilities, and the requirement to learn new skills. Organizations can identify possible stressors and support efforts to increase employee well-being by evaluating the impact on staff performance. Skill Requirements: Smart automation may result in changes to the abilities required for various vocations. By comprehending the evolving skill requirements and making sure that employees have the abilities necessary to remain competitive and relevant in the labor market, employers can better prepare their staff for the future.
Productivity and Efficiency: In some activities, automation and artificial intelligence (AI) have the potential to increase productivity and efficiency. Organizations can determine which tasks are most suitable for automation by examining their effect on employee performance. This will free up employees to concentrate on more intricate and strategic tasks that call for human expertise. Organizational Performance: An organization's and its workers' respective performances are intimately related.
Organizations can improve overall organizational performance by optimizing their staff and implementing new technologies by knowing how smart automation influences employee performance. Making decisions: Putting smart automation into practice frequently necessitates large financial outlays as well as modifications to organizational procedures. Evaluating the effects of these changes on employee performance in-depth enables decision-makers to balance the advantages and disadvantages of the changes and make better decisions. 2 Competitive advantage: In a business environment that is changing quickly, companies who successfully use smart automation to help their workforce will have an advantage.
Researching how automation affects worker productivity might help develop more innovative and effective talent management plans. Ethical concerns: Automation and artificial intelligence may give rise to worries about algorithmic bias, data privacy, and job displacement. Understanding the influence of ethical concerns on employee performance can help identify and resolve them, ensuring a fair and inclusive workplace. As part of the industry 4.0 revolution, Samsung Display Vietnam (SDV) has implemented state-of-the-art automation and intelligence technologies, resulting in a dramatic transformation into a smart factory.
This shift has affected the organization's overall operations and organizational structures, as well as employee performance, operational performance, and human resource management. Organizations must examine how smart automation affects worker performance if they are to successfully traverse the benefits and difficulties presented by these cutting-edge technologies and create a more profitable and sustainable future for their workforce and business operations.2 Literature review Together with the fast development of industrial revolution 4.0, many researches have been conducted to study the contribution of intelligent automation on performance of an organization at both firm and employee level. Particularly, in 1997, impact of intelligent automation on four dimensions of organizational performance: operational performance, labor management effectiveness, worker‘s well-being and remuneration was studied by Wong et. al [4] by analyzing data of 52 electronics manufacturing firms in Singapore.
The largest gains were identified with operational performance and workers‘ well-being, followed by labor management effectiveness and remuneration. All these four dimensions were showed to have significant positive correlations. The study also confirmed importance of skills and training in improving automation outcomes, in which automation-specific skills are found to be important 3 for improving organizational performance, whereas generic skills training is necessary for labor management and worker‘s social well-being. More recently, in 2021, Vrontis [5] conducted a systematic evaluation of the effects of intelligent automation on human resource management (HRM).
The convergence of information technologies and human resource management, or eHRM, has caused significant changes in workforce management techniques in the HRM profession. These shifts are related to mass collaboration, virtual and real-time/flexible product and service innovation, simulation/synthetic reality, and virtual and virtual collaboration [6], [7], [8], [9], [10], [11]. Further emerging of advanced technologies such as IoT in HRM results in shifting from eHRM to a new phase defined by intelligent automation, in which all aspects of HRM consisting of technologies, employee & HR activities are modified and support the company to have benefit in cost savings, harmonization, integration and efficiency. Besides IoT technologies, the adoption of artificial technologies (AI) in HRM mainly focuses on recruiting, training and decision-making.
Ethical challenges related to human privacy are also discussed in [12]. Studies on robotic technologies has shown that simple jobs such as welding, painting, assembling associated with un-skilled employees will disappear and be replaced by more technical positions [13], [14]. Another research of impact of automation and digitalization on employment are reviewed in 2 manufacturing sectors, automotive and garments, to explain degree of change in labor activities and how these activities are organized [15].
