Module SS 2017

Short description
This course generalizes the concepts of simple linear regression discussed in Business Statistics I to the case of multiple linear regression.

Topics

• Classical linear model assumptions
• Parameter estimation in multiple linear regression
• Model diagnostics
• Inference in multiple linear regression
• Model specification techniques
• Model selection techniques
• Introduction to the software package R

Learning objectives

• Students explain the classical linear model assumptions, run multiple linear regressions, check the diagnostics plots and interpret the results correctly.
• Students apply inference procedures in multiple linear regression models and compare the advantages and disadvantages of different inference procedures.
• Students apply specification techniques to improve the quality of models and interpret such models correctly.
• Students apply selection techniques to choose appropriate models.

Methods

• The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.
• Students are usually asked in advance to read corresponding parts of the lecture notes or of the textbook in order to prepare for the upcoming lectures.
• In the interactive lectures, statistical concepts will be introduced and motivated by discussing examples in detail. Assignments are offered to train these skills.
• During office hours, individual problems may be discussed with the lecturer.
• In order to analyse realistic data, the software package R will be used.

Recommended previous knowledge
Business Statistics I

Compulsory reading

• Wooldridge, J.M. (2013). Introductory Econometrics. (International Student Edition, 5th edition). Mason: South Western Cengage Learning.

Further reading

• Montgomery, D.C., Peck, A.E. & Vining, G.G. (2012). Introduction to Linear Regression Analysis. (5th edition). New York: John Wiley & Sons.
• Faraway, J.J. (2014). Linear Models with R. (2nd edition). Boca Raton: Chapman & Hall/CRC.

Our educational journey will be done in cooperation with Prof. Jan Mendling, WU Vienna - University of Economics and Business. We will attend lectures at the brand new campus of WU Vienna, the biggest university for social and economic sciences in Europe. Furthermore, company visits and social activities are part of this journey. The trip lasts from Sunday - Thursday (including travel).

This module is accredited as elective subject (i.e. it counts as 3 out of 12 ECTS in the elective subjects basket).

Activities
Besides a lecture at the new campus of the Vienna University of Economics and Business (WU Wien) by Univ. Prof. Dr. Jan Mendling, we plan the following activities:

• visit of the „Österreichische Post“ (Federal Mail) logistical center
• visit of the Viennese brewery: Ottakringer Brauerei AG
• introduction to typical Austrian cuisine

Schedule
Date: 18th April until 22th April (travelling on 18th April and 22th April)

Preliminary Agenda (need to be confirmed)
Tuesday: 18:00: get-together in the Hotel lobby, sightseeing-walk, dinner.
Wednesday: lectures at WU Wien, dinner in Schweizerhaus (Prater Vienna)
Thursday: lectures (half day) and short exam (see below for details), dinner at "Heurigen"
Friday: Österreichische Post (Austrian Federal Mail) and brewery visit.
Saturday: individual departure

Regulations require an examination in an elective subject. The exam will be conducted in the form of an exercise with relation to the lecture. You will be able to consult in groups and use all material (open book). Grading will be pass/not passed
There will be sufficient time to discover the city individually.

Accommodation
Students who took part in the last years, always recommended the following places to stay:

• Hotel Kummer at Mariahilferstrasse: http://www.gerstner-hotels.at/hotel-kummer/index.html (classic Vienna hotel with attractive pricing scheme, especially when sharing a room)

• Wombats City Hostel – THE LOUNGE at Mariahilferstrasse: http://www.wombats-hostels.com/vienna/the-lounge/

• Motel One Prater – this is near the WU Wien Campus, where lectures will take place, and close to Schweizerhaus: http://www.motel-one.com/en/hotels/vienna/wien-prater/

Cost & Registration
Please register until end of February for the study trip.

The cost for entry fees in Ottakringer Brewery are 6,- EUR which we will collect during the trip. All other costs have to be covered individually.

Travel
Travelling to Vienna should be organized individually. We can recommend the Austrian Federal Railways (www.oebb.at) leaving e.g. from Feldkirch or Zurich.

Some tips for booking a train ticket:

• There is always a limited amount of cheaper tickets -dedicated to specific trains - available (called Sparschiene).
• If you want to buy a regular ticket, you will be asked whether you have a ÖBB Vorteilscard (50 % discount). All people under 26 years can buy a Vorteilscard < 26 at low cost.

Flights go from Altenrhein-St.Gallen (Peoples Airline) and Zürich (AUA, Swiss) to Wien-Schwechat (VIE).

Arriving by car is possible, the P+R Ottakring might be the best solution then (U3 connects you with the city).

We will use public transportation during the trip. Tickets are available at all vending machines of "Wiener Linien".

Short description
In the second Innovation Lab, students engage in a competitive collaboration challenge to develop innovative solutions for a real-life business problem.

Topics

• Innovation
• Competition
• Collaboration

Learning objectives

• Students will recognize the complex nature of the management of innovation within organizations.
• Students will apply innovation management frameworks, models and methods to the given task.
• Students will develop a sustainable solution for the selected case study.
• Students will evaluate the developed solution with appropriate methods regarding its advantages and constraints.

Methods

• The module integrates theoretical knowledge and practical skills in a competitive setting between students.
• A jury evaluates the students' solutions against innovativeness and usefulness and provides them with feedback and advice.
• The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.

Compulsory reading

• Trott, P. (2013). Innovation Management and New Product Development, 5th ed., Harlow: Pearson Education Limited.
• Ahmed, P. K. & Shepherd, C. D. (2011). Innovation Management: Context, Strategies, Systems and Processes, Harlow: Pearson Education Limited.

Short description
A three-day workshop will serve as a case study in which the students participate. This is followed by a reflection phase during which literature review and research will be applied to their experiences. Finally participants have to document their key findings and lessons learned in a written seminar work and prepare a presentation to transfer this new knowledge to their fellow students.

Topics

• Managing Human Resources
• Leadership
• Operations Organisation and Organisational Behaviour
• Project, Change and Conflict Management
• Competence Management and Delegation
• Teambuilding

Learning objectives

• Students will know how communication and cooperation can be designed.
• Students will know fundamentals about motivation and rewarding schemes.
• In a case setting, students will learn about coordination and decision taking.

Methods

• The participants will constantly be evaluated throughout this workshop by peer-review, performance review and the degree to which they have achieved their objectives. Project and Process Management will be applied as powerful Management Tools.

• The concept of the workshop is to create a simulation of real business situations. Because there does not exist any absolute formula for success the students are empowered and encouraged to find their own solutions. The lecturers in this module offer active guidance and feedback during this process. The students are also given time to reflect upon their experiences as the workshop progresses by writing a personal "Leadership Diary".

Compulsory reading
A list of references will be distributed in class in accordance with the content of the workshop.

Further reading

• Adams, J. S. (1965). Inequity in social exchange. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 2, pp. 267-299). New York: Academic Press.
• Armstrong, M. (2006): Strategic Human Resource Management: A Guide to Action. 3. Aufl., Thomson-Shore.
• Beel, J. (2007). Project Team Rewards - rewarding your project Team. First Edition. CreateSpace LLC, Scotts Valley, USA.
• Drucker, P. F. (1954). The Practice of Management. New York: Harper & Row.
• Herzberg, F. and Mausner, B. and Bloch Snyderman, B. (1993). The Motivation to Work (10th Edition). Transaction Publishers.
• Malik, F. (2006). Managing Performing Living. Campus Verlag
• Maslow, A. (1943). A Theory Of Human Motivation in Psychological Review 50 (4) pp. 370-96.

Short description
In their Master’s thesis, students use scientific methods and work in accordance with standards of scientific writing. The Master’s thesis is typically related to the major (BPM or Data Science) chosen by the student.

Learning objectives

• Students will formulate appropriate research questions.
• Students will identify appropriate theories to explain empirical phenomena.
• Students will identify suitable research methods in order to seek answers to specific research questions.
• Students will use appropriate qualitative, quantitative, and design-oriented approaches to seek answers to their research question/questions. Mere conceptual works are also possible.

Methods

• The thesis is supervised by a supervisor and a co-supervisor, both of whom should be members of the Institute of Information Systems.
• The Master’s thesis is defended in an oral exam, where students may be asked questions related to their studies that may go beyond the content of their Master’s thesis.
• The official editing time is defined on the thesis proposal and may not exceed 22 weeks. A shorter editing time is possible.

Entry requirements

• A minimum of 60 ECTS must be achieved before registration.
• The modules Business Statistics I and Research Methods must be passed successfully.
• A research proposal (exposé) signed by the first supervisor and the academic director must be submitted to the study administration in parallel to module registration.

Recommended previous knowledge

• It is highly recommended that the research proposal (exposé) is developed within the module "Research Seminar"

Colloquium

• Colloquium (mid-term presentation) is usually held about two months prior to the submission of the final master's thesis.
• In the colloquium, students are expected to report on their progress and experience in writing their master's thesis.
• The outcome of the colloquium is graded "passed" or "failed".
• The colloquia for the summer term in 2017 will be held on: April 6 - April 7, 2017, starting from 09.00. A detailed schedule will be communicated two weeks prior to these dates.

Submissions and deadlines

• A copy of signed thesis proposal (Exposé) must be submitted until July 1st. (for the winter term) and February 1st (for the summer term) to: Exposé Submission link
• The master's thesis must be submitted until November 30th (for the winter term) and June 30th (for the summer term) to the the central service desk.
• The submission of master's thesis must include: (1) a CD ROM containing thesis' digital copy (at the central service desk) and (2) direct submission of thesis' digital copy to the supervisor and co-supervisor (via e-mail).
• If any of the dates above falls on a weekend or public holiday, the deadline is automatically extended until the next working day. Please also check the opening times of the central service desk, especially during summer months.

Compulsory reading

• Creswell, J.W. (2008) Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, 3rd Edition, Sage Publications
• Saunders, M.N.K.; Thornhill, A.; Lewis, P.; Leedy P.D.; Ormrod, J.E. (2007) Research Methods for Business Students: AND "Practical Research, Planning and Design", Financial Times Prentice Hall

Short description
The course covers the fundamentals of supply chain management, so it focuses on the coordination of problems related to the provision of products and services and the flow of goods.

Topics

• Demand forecasting
• Process flow analysis
• Service process management
• Inventory management
• Location planning
• Production planning
• Scheduling
• Network management

Learning objectives

• Students will know about the main concepts, theories, and methods in supply chain management.
• In a business game, students will recognize and analyze typical coordination problems along the supply chain.
• In exercises, students will use analytical methods like linear programming, dynamic programming, regression analysis, and exponential smoothing, and state-of-the-art algorithms and heuristics like Silver-Meal and Branch-and-Bound.
• In case studies, students will use these methods to identify business problems, generate solutions, and compare their solutions in terms of quality and accuracy.

Methods

• The module involves interactive lectures with exercises to integrate theoretical knowledge and practical skills.
• Case studies are used to show how the course contents are related.
• A business game is used to illustrate typical coordination problems along the supply chain.
• The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.

Recommended previous knowledge

• Students are expected to have basic knowledge and skills in operations management.

Compulsory reading

• Chopra, S., & Meindl, P. (2012). Supply Chain Management: Strategy, Planning, and Operation (5th edition). Pearson: Edinburgh Gate et al.

Short description
The course focuses on systems analysis and design, including methods and approaches for developing and implementing information systems in organizations.

Topics

• Introduction to object-oriented systems
• Project planning and initiation
• Requirements analysis (i.e., requirements gathering and structuring)
• Systems modeling (i.e., UML modeling languages)
• Systems implementation

Learning objectives

• Students will know how information systems can be modeled and designed.
• Students will know basic methods of systems modeling and design (i.e. UML modeling languages) in order to analyze, design, and implement information systems.
• Students will use methods of systems modeling in order to analyze, design, and implement information systems.

Methods

• The module integrates theoretical knowledge and practical skills in an interactive lecture.
• The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.

Recommended previous knowledge

• Gries, P., Campbell, J., & Montojo J. (2013). Practical Programming: An Introduction to Computer Science Using Python 3. Pragmatic Bookshelf: Frisco, TX, USA.
• Valacich, J. S., & George, J. F. (2016). Modern Systems Analysis and Design. Pearson: New York.

Compulsory reading

• Rosenberg, D. & Stephens, M. (2007). Use Case Driven Object Modeling with UML. Apress: New York.
• Kölling, M. (2015). Introduction to Programming with Greenfoot: Object-Oriented Programming in Java with Games and Simulations. Prentice Hall: Upper Saddle River.