Digital Hr and Analytics
A.Y. 2022/2023
Learning objectives
The course Digital HR and Analytics aims to contribute to the MSc Management of human resources goals by offering grounded in research and connected to practice tools to understand and manage the intersection of HRM and technology. As the importance of digital technologies in the management of people has increased, so has research on tools, processes, and theories for doing this more effectively. Moreover, the adoption of digital technologies for HR purposes has gradually increased the relevance of advanced data analysis and visualization models and techniques to enhance strategic decisions, thus serving the needs of executives and top decision-makers of the organization. Therefore, the focus of the course will be on how the transformation of the HR function through technology is leading HR processes to become automated and data-driven and the new ways to manage workers through technology and data. Students will develop a thorough understanding of the impact of digital technologies and HR analytics on HR systems and will critically reflect upon the new role of the HR function in handling the managerial challenges that such transformations pose.
Expected learning outcomes
At the end of this course, students will be able to:
1. Define the main concepts and investigation areas related to digital HR and analytics
2. Describe the latest developments and challenges in the fields of digitalisation of HRM and HR analytics
3. Discuss the main theories useful to explain technology adoption and its effects in the HR domain
4. Consult and make a critical appraisal of the scientific literature on the major issues related to digital HR and HR Analytics
5. Identify and understand scientific evidence on success factors for the development and implementation of digital HR systems
6. Identify the various types of HR analytics useful to measure the effectiveness of digital HR practices implementation
7. Develop and assess digital HR solutions in order to face managerial challenges in the HR domain
1. Define the main concepts and investigation areas related to digital HR and analytics
2. Describe the latest developments and challenges in the fields of digitalisation of HRM and HR analytics
3. Discuss the main theories useful to explain technology adoption and its effects in the HR domain
4. Consult and make a critical appraisal of the scientific literature on the major issues related to digital HR and HR Analytics
5. Identify and understand scientific evidence on success factors for the development and implementation of digital HR systems
6. Identify the various types of HR analytics useful to measure the effectiveness of digital HR practices implementation
7. Develop and assess digital HR solutions in order to face managerial challenges in the HR domain
Lesson period: Third trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Third trimester
Course syllabus
The Digital HR & Analytics course is structured around 3 main modules. The first module deals with the digital transformation of the HR function and describes how technology affects work that is performed within the HR function and its role within the company. The main theoretical approaches to explain changes and challenges affecting digital HR will be presented. The second module presents different e-HRM functional areas (e.g., e-recruitment, e-selection, e-learning, e-performance management) and the success factors for designing and managing them. Finally, the last module introduces the main managerial challenges in digital HR (e.g., e-leadership, managing virtual teams, dark side). Analytics concepts and methodologies will be spread across the three modules in order to show practical examples and applications to real digital HR problems.
Prerequisites for admission
Preliminary knowledge of Human Resource Management, Human Resources Information Systems, and Organizational Behavior is recommended.
Teaching methods
The course is held through traditional lectures, small group activities, problem-based learning, case studies, and HR professionals or managers' company testimonials under the guidance of the teacher.
Teaching Resources
Required Course Materials for attending students: a list of references and recommended further readings to enable the students to gain a deeper awareness and understanding of each topic will be provided at the beginning of the course.
Required Course Materials for not attending students:
Bondarouk, T., Parry, E., & Furtmueller, E. (2017). Electronic HRM: Four decades of research on adoption and consequences. The International Journal of Human Resource Management, 28(1), 98-131.
Margherita A. (2022) Human resources analytics: A systematization of research topics and directions for future research. Human Resource Management Review, 32(2).
Marler, J.H., & Parry, E. (2016). Human resource management, strategic involvement and e-HRM technology. The International Journal of Human Resource Management, 27 (19), 2233-2253.
Thite, M. (2019). E-HRM: Digital Approaches, Directions, and Applications. New York: Routledge.
Required Course Materials for not attending students:
Bondarouk, T., Parry, E., & Furtmueller, E. (2017). Electronic HRM: Four decades of research on adoption and consequences. The International Journal of Human Resource Management, 28(1), 98-131.
Margherita A. (2022) Human resources analytics: A systematization of research topics and directions for future research. Human Resource Management Review, 32(2).
Marler, J.H., & Parry, E. (2016). Human resource management, strategic involvement and e-HRM technology. The International Journal of Human Resource Management, 27 (19), 2233-2253.
Thite, M. (2019). E-HRM: Digital Approaches, Directions, and Applications. New York: Routledge.
Assessment methods and Criteria
For attending students, the achievement of the expected learning outcomes will be assessed through:
1) a group project work on the analysis of collaborative networks in a remote working setting and the design of HR activities to solve issues emerged from the analysis. Through the project work, each group will get a mark from 0 to 30 cum laude.
2) a written test based on 15 multiple-choice questions (MCQs) and 3 open-ended questions. As regards the MCQs, there will be only one correct answer and one point will be awarded for each correct answer (zero points for each wrong or missing answer). For each open-ended question, the student will get a grade from 0 to 5. The final grade of the test (sum of the grade in the MCQs test + grade of the open questions) will go from 0 to 30 cum laude. The student will have 1.5 hours to complete the test.
The final mark will be the weighted average between the group project work evaluation (30%) and the individual final test (70%).
For not-attending students, the achievement of the expected learning outcomes will be assessed through a written test as described above.
1) a group project work on the analysis of collaborative networks in a remote working setting and the design of HR activities to solve issues emerged from the analysis. Through the project work, each group will get a mark from 0 to 30 cum laude.
2) a written test based on 15 multiple-choice questions (MCQs) and 3 open-ended questions. As regards the MCQs, there will be only one correct answer and one point will be awarded for each correct answer (zero points for each wrong or missing answer). For each open-ended question, the student will get a grade from 0 to 5. The final grade of the test (sum of the grade in the MCQs test + grade of the open questions) will go from 0 to 30 cum laude. The student will have 1.5 hours to complete the test.
The final mark will be the weighted average between the group project work evaluation (30%) and the individual final test (70%).
For not-attending students, the achievement of the expected learning outcomes will be assessed through a written test as described above.
SECS-P/10 - ORGANIZATION AND HUMAN RESOURCE MANAGEMENT - University credits: 9
Lessons: 60 hours
Professor:
Lazazzara Alessandra
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