Kurs-Code DatZM001
Kreditpunkte 3
Stundenzahl insgesamt (im Auditorium)
Vorlesungen (Stundenzahl)8
Stundenzahl fŅr Seminare und praktische Arbeitsaufträge16
Arbeit im Labor (Stundenzahl)0
Selbststandige Arbeit des Studenten (Stunden)57
Bestätigt am (Datum)04.10.2023
Kurs ausgearbeitet von (Lehrkraft)
Nataļja Vronska
Iveta Kokle-Narbuta
Zur einfŅhrenden LektŅre empfohlen
1. Diez F., Bussin M., Lee V. Fundamentals of HR Analytics. Emerald Publishing Limited, 2019, p. 281
2. Edwards M. R., Edwards K. Predictive HR analytics: mastering the HR metric. Kogan Page, 2019, p. 536
3. Fitz-enz J. The new HR analytics: predicting the economic value of your company's human capital investments. New York, AMACOM, 2010, p. 368
4. Winston W. Microsoft Excel 2019 Data Analysis and Business Modeling. Microsoft Press, 2019, p. 880
5. Collie R. Power Pivot and Power BI. Holy Macro! Book, 2016, p. 314
6. Kusleika D., Alexander M. Excel 2019 Power Programming with VBA. Wiley, 2019, p. 784
Weiterfuhrende Literatur
1. Alvarez F., Stone D., Castano A., Garcia-Izquierdo A. Human Resources Analytics: A systematic Review from a Sustainable Management Approach. Journal of Work and Organizational Psychology 38, 2022, pp. 129-147.
2. Belizon M., Kieran S. Human resources analytics: A legitimacy process. Human Resource Management Journal. 32, 2022.
3. Margherita A. Human resources analytics: A systematization of research topics and directions for future research. Human Resource Management Review, 32, 2021.
4. Alexander M., Kusleika D., Walkenbach J. Excel 2019 Bible. Wiley, 2018, p. 1120
5. Jelen B., Alexander M. Microsoft Excel 2019 Pivot Table Data Crunching. Microsoft Press, 2019, p. 512
Zur LektŅre vorgeschlagene Zeitschriften
1. Peiseniece, L. (2010). Cilvēkresursu vadīšanas novērtēšanas metodes un to pilnveidošanas virzieni Latvijas lielajos uzņēmumos. Promocijas darbs. Rīga: LU.
https://core.ac.uk/download/71754104.pdf
2. Dombrovska, L.R. (2009). Cilvēkresursu kapitāla vadība. Rīga: Zvaigzne ABC.