- Lecture and discussion
- papers to read
- lab course tutorials
- assignments
Syllabus
Registration via LPIS
Day | Date | Time | Room |
---|---|---|---|
Wednesday | 10/04/17 | 01:30 PM - 05:00 PM | D4.1.212 GIS Lab |
Wednesday | 10/11/17 | 01:30 PM - 05:00 PM | D4.1.212 GIS Lab |
Wednesday | 10/18/17 | 01:30 PM - 06:00 PM | D4.1.212 GIS Lab |
Wednesday | 10/25/17 | 01:30 PM - 06:00 PM | D4.1.212 GIS Lab |
Wednesday | 11/08/17 | 01:30 PM - 05:00 PM | D4.1.212 GIS Lab |
Wednesday | 11/15/17 | 01:30 PM - 05:00 PM | D4.1.212 GIS Lab |
Wednesday | 11/22/17 | 01:30 PM - 05:00 PM | D2.0.038 |
- exploratory geospatial analysis
- location/allocation analysis
- cloud-based services and open-source data infrastructures & tools
We will use real-world data and case studies in various industries for
- Locating facilities, e.g., a new warehouse of a major retail chain, a new hub/spoke in a distribution network
- Allocating, e.g., customers to retail/service outlets, regional warehouses to a central warehouse, resources to production sites
- Evaluating , e.g., service/infrastructure networks and customer potentials, trade area and distribution/production network (re-)design, geospatial risks and sustainability effects
The topics are addressed from a methodological-theoretical as well as an empirical perspective, both with a particular emphasis on spatial aspects. Considerable attention will be paid to gaining hands-on experience in the application of spatial analysis techniques of events that occur on and alongside networks in empirical practice, using spatial analytics methods and tools like ArcGIS Desktop and ArcGIS Online as well as Open-Source Software like GeoDa, CrimeStat, GWR or SANET.
Students learn selected theoretical and empirical methods and get a good understanding of the fundamental questions that are addressed in the context of SCM, the methods with which these are addressed, and the current state of affairs in the literature.
By the end of this course students
- possess a relevant background and a good mastery of models, methods and techniques used in the domain
- have the ability to select and apply appropriate modeling tools in specific decision making contexts
- readings and assignments (45)
- active participation in class discussion (5)
- final exam (50)
Grading scale:
- Excellent (1): 87.5% - 100.0%
- Good (2): 75.0% - <87.5%
- Satisfactory (3): 62.5% - <75.0%
- Sufficient (4): 50.0% - <62.5%
- Fail (5): <50.0%
Prerequisite for passing the course: minimum performance of 40% in the final examination.
For incoming exchange students: 10 ECTS in Supply Chain Planning, Global Supply Chain Design, Transport/Logistics (Network) Management/Analysis/Planning, Operations Research, or Geographic Information Systems and Analysis, Spatial Business Intelligence/Location Analytics.
Office hours: please, send email to petra.staufer-steinnocher@wu.ac.at to make an appointment
Unit | Date | Contents |
---|---|---|
1 | 10/04/17 | Lecture and discussion
Learning materials for Unit 1: Exploratory geospatial analysis Computer lab
|
2 | 10/11/17 | Excursion to WIGeoGIS Knowledge Day
Doodle poll (if more than 50% of the students vote for the Excursion, hands-on training and discussion of methods and tools will be extended to unit 3) Venue: Wolke 19, Ares Tower, Donau-City-Str 11, 1220 Wien Public transport from Campus WU: U2 (direction Karlsplatz) to Praterstern, change to U1 (direction Leopoldau) and exit at stop Wien Kaisermühlen-VIC, then walk about 8 minutes to Ares Tower ( Marcel-Prawy-Promenade); see e.g. Wiener Linien arrival at 1:15 PM at the latest! Opening: 1:30 PM
|
3 | 10/18/17 | Lecture and discussion Location-Allocation-Models in SCM Please read carefully to be prepared for this unit and for the next lab-unit:
Download learning materials More hands-on ESDA with ArcGIS, CrimeStat and GeoDa
|
4 | 10/25/17 | Hands-on Location-Allocation-Modeling in ArcGIS and Extensions Learning materials for Unit 4: Lab tutorial: Location-Allocation Models |
5 | 11/08/17 | Lecture and discussion Location Analytics in the Cloud 1: Foundations and Applications
Download learning materials: Slides Location Analytics in the Cloud
|
6 | 11/15/17 | Lecture and discussion Location Analytics in the Cloud 2: Geospatial Data
Download learning materials: Slides Geospatial Data in the Cloud Computer Lab: hands-on LAGD in the Cloud: ArcGIS Online and Extensions |
7 | 11/22/17 | Written exam: models and methods |
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