Universität Wien FIND

040906 KU Selected Special Topics of Public and Non-Profit Management (MA) (2021W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
REMOTE

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 50 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

Thursday 07.10. 08:00 - 12:30 Digital
Thursday 14.10. 08:00 - 12:30 Digital
Thursday 21.10. 08:00 - 12:30 Digital
Thursday 04.11. 08:00 - 12:30 Digital
Thursday 09.12. 08:00 - 12:30 Digital
Thursday 16.12. 08:00 - 12:30 Digital

Information

Aims, contents and method of the course

http://pnpm.univie.ac.at/minormajor-pnpm/

Please open this website to obtain further information regarding in which Master study plans this course can be selected (e.g., Business Administration, International Business Administration, Economics, Statistics, Business Informatics).
At the beginning (first session), we will introduce the method linear optimization and demonstrate the application area of resource scheduling in public and non-profit management (PNPM).

The first part of this course on how to best provide goods and services in PNPM focuses on staff scheduling illustrated on the health care sector related to nurses and medical doctors. Next, we discuss models for nurse scheduling based on the literature. Finally, students solve nurse scheduling problems related to international literature. The students critically evaluate applied staff scheduling systems especially in the health care, disaster management, and education as well as other areas of PNPM.

In the second part of this course, we apply benchmarking approaches to evaluate an optimal resource allocation (e.g., staff, equipment, capital) in Decision Making Units (DMUs) in PNPM (e.g., medical organizations, schools/universities, disaster management, environment, energy, sports/art/culture). We explain the method of Data Envelopment Analysis (DEA) for benchmarking which is then applied on several examples together with the students.

To promote connection to the practice, there will be an opportunity for an excursion to practice/politics/science or to attend a talk.

Assessment and permitted materials

All oral & written homework assignments have to follow scientific guidelines: https://pnpm.univie.ac.at/minormajorwahlfach-pnpm/).
• All files of the homeworks (oral and written part) must be electronically turned in a day before the presentation on the moodle platform (1 x doc-file, 1x ppt-file, 2x pdf-files)
• The printed versions of the slides of the homeworks are part of the final grade and have to be turned in at the University of Vienna, OMP 1, porter, Mailbox Rauner latest on the day of the presentation). Please ONLY print one slide on ONE page on the front of the paper sheet! Please do NOT print on the back of the paper sheet!
• The quality of the printed version of the homeworks is part of the final grade.

Presentation:
• Each presentation should take up to 10 minutes (small homeworks Ozkarahan/DEA ) and up to 20 minutes (main homework on staff scheduling).
• There should be a short discussion with the auditorium after the presentation.
• The use of the beamer/online tool is expected (legible slides).
• The quality of the presentations is part of the final grade.

Requirements for a positive grade (min. 50%):
• Positive participation in the blocked sessions.
• All oral and written assignments have to be positively evaluated.
• To pass the class, it is only allowed to miss not more than two blocked class sessions.
• All files are check for plagiatism!

Attendance/Participation in units (Kahoots): max. 5 x 4 = 20% Participation Workshops LP, Staff Scheduling, DEA: max.3 x 5= 15 %
Presentation Homework Ozkarahan: max. 10 %
Slides Homework Ozkarahan: max. 10%
Presentation Homework DEA: max. 5 %
Slides Homework Hausübung DEA: max. 5 %
Presentation Homework Staff Scheduling: max. 10 %
Slides Homework Staff Scheduling: max. 25 %

"1": 90%-100%
"2": 80%-89,75%
"3": 66%-79,75%
"4": 50%-65,75%
"5": <49,75% or missing of more than two block class session or plagiatism of homework paper

Minimum requirements and assessment criteria

Attendance/Participation in units (Kahoots): max. 5 x 4 = 20% Participation Workshops LP, Staff Scheduling, DEA: max.3 x 5= 15 %
Presentation Homework Ozkarahan: max. 10 %
Slides Homework Ozkarahan: max. 10%
Presentation Homework DEA: max. 5 %
Slides Homework Hausübung DEA: max. 5 %
Presentation Homework Staff Scheduling: max. 10 %
Slides Homework Staff Scheduling: max. 25 %

"1": 90%-100%
"2": 80%-89,75%
"3": 66%-79,75%
"4": 50%-65,75%
"5": <49,75% or missing in more than two block class session or plagiatism of homework paper

Examination topics

See literature

Reading list

All essential course material is available on the E-Learning-Platform

Linear Optimization
• Günther, H.-O. (1993) Produktionsmanagement, Einführung mit Übungsaufgaben, Heidelberg
• Hillier, F.S., Lieberman, G.J. (1988) Operations Research, Einführung, München

Nurse Scheduling
• Van den Bergh, J., Beliën, J., De Bruecker, P., Demeulemeester, E., & De Boeck, L. (2013) Personnel scheduling: A lit-erature review, European Journal of Operational Research, Vol. 226, No. 3, pp. 367-385.
• Brucker, P., Qu, R., & Burke, E. (2011) Personnel scheduling: Models and complexity, European Journal of Opera-tional Research, Vol. 210, No. 3, pp. 467-473.
• De Causmaecker, P., & Vanden Berghe, G. (2011) A categorisation of nurse rostering problems, Journal of Scheduling, Vol. 14 No. 1, pp. 3-16.
• Burke, E.K., De Causmaecker, P., Vanden Berghe, G., Van Landegheme, H. (2004) The state of the art of nurse roster-ing, Journal of Scheduling, Vol. 7, No. 6, pp. 441-499.
• Gutjahr, W.J, Rauner, M.S. (2007) An ACO algorithm for a dynamic regional nurse-scheduling problem in Austria, Computers & Operations Research, Vol. 41, No. 3, pp. 642-666.

Nurse Scheduling (Homework Ozkarahan)
• Ozkarahan, I., A Disaggregation Model of a Flexible Nurse Scheduling Support System (1991) Socio-Economic Plan-ning Sciences, Vol. 25, No. 1, pp. 9-26.
• Rauner, M.S. (1999) A note on “A disaggregation model of a flexible nurse scheduling support system” by Irem Ozkarahan, Socio-Economic Planning Sciences 25 (1991), pp. 9-26”, Socio-Economic Planning Sciences, Vol. 33, No. 2, pp.173-177.

DEA
• Ozcan, Y. (2008) Health Care Benchmarking and Performance Evaluation, An Assessment using Data Envelopment Analysis (DEA), Springer, New York.
• O'Neill, L., Rauner, M.S., Heidenberger, K., Kraus, M. (2008) A cross-national comparison and taxonomy of hos-pital efficiency studies using data envelopment analysis, Socio-Economic Planning Sciences, Vol. 42, No. 3, p. 158-189.
• Cooper, W.W., Seiford, L.M., Zhu, J. (2004) Handbook on Data Envelopment Analysis, Kluwer, Boston.
• Charnes, A., Cooper, W.W., Rhodes, E. (1978) Measuring the efficiency of decision making units, European Journal of Operational Research, Vol. 2, p. 429-444.
• Kohl, S., Schoenfelder, J., Fügener, A., & Brunner, J. O. (2018). The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals. Health Care Management Science, 1-43.
• Meyer, M., Wohlmannstetter, V. (1985) Effizienzmessing in Krankenhäusern, Zeitschrift für Betriebswirtschaft, Vol. 55, p. 262-280.
• Bürkle, B. (1994) Data Envelopment Analysis, Zeitschrift für öffentliche und gemeinwirtschaftliche Unternehmen, Vol. 17, p. 273-291.
• Sommersguter-Reichmann, M., & Stepan, A. (2015). The interplay between regulation and efficiency: Evidence from the Austrian hospital inpatient sector. Socio-Economic Planning Sciences, 52, 10-21.

DEA (Homework DEA)
• Dyson, R.G., Allen, R. Camanho, A.S., Podinovski, V.V. ,Sarrico C.S., Shale E. A. (2001) Pitfalls and protocols in DEA, European Journal of Operational Research, Vol. 132, No. 2, p. 245-259.

Manpower Planning
• Von Eiff, W., Stachel, K. (2006) Professionelles Personalmanagement: Erkenntnisse und Best-Practice-Empfehlungen für Führungskräfte im Gesundheitswesen, Münster
• Grütz, M. (1984) Computerunterstützte Personalbedarfsermittlung für den Krankenpflegebereich auf der Grundlage von Dienstzeitplanungen, Nürnberg
• Trill, R. (2002) Krankenhaus-Management: Aktionsfelder und Erfolgspotentiale, NeuwiedMoodle.

Association in the course directory

Last modified: Th 23.03.2023 00:14