Curriculum

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Curriculum

The RSM MSc in Business Information Management programme is one academic year’s duration. Core courses are compulsory and will be offered during the autumn semester (22 EC). Master electives (18 EC) are offered during the spring semester, of which one elective can be chosen from another MSc programme. It is also possible to replace one elective with an internship or business project. During the year, students work on a master thesis project (20 EC).

Please note that certain electives may be very popular. Although we can place most students in the elective(s) of their choice, there are no guaranteed places.

    • Information technology (IT) is revolutionizing the way people and firms transact business. This process is only being accelerated with the development of social media and the availability of big data, which has enormous impact on our activities and the way organizations work and compete. This rapid movement towards the new information economy is being led by both established firms such as Wal-Mart, General Electric, and new entrepreneurial firms such as Google, Amazon, Facebook, YouTube, and Dropbox. As a master student of business information management, you need a thorough understanding of the latest technology trends, how firms embrace disruptive technologies, and what new business models emerge that allows firms to compete and lead in the information economy. This course will devote to the study of the strategic use of information, and provide you with the understanding of the role of information, the closely related role of information technology, major developments of e-commerce, and their implications on economics, marketing, and operational issues. This course will focus on problems unique to information-intensive businesses that you will soon encounter as a consultant, analyst, technologist, or entrepreneur.

      The course is a combination of lectures and a high degree of case analysis and discussions. In the class, you will work with real world examples ranging across different industries. The course will cover six themes: information strategy, business model and digital transformation, business-to-consumer e-commerce, electronic markets and auctions, information goods, and platform mediated networks.

      Review the course guide for more details.

      Taught by prof. T. Li.

    • This course and the accompanying reading materials aim to provide you with the knowledge and skills required for building information systems that drive business success. You will learn about the process of building modern information systems and about the requirements engineering, analysis, and design activities of software engineering. You will learn to identify stakeholders and requirements, to define the structure of an information system, to evaluate competing solutions for a business problem, and you will start to “speak business and IT”. You will gain insight into how important these activities are in creating information systems that are truly aligned with business needs. Throughout the course, you will also learn about selected topics in IT strategy and IT software project management. In your team project, you will develop the idea, the business justification, and the requirements for a novel business application.

      Review the course guide​​​​​​​ for more details.

      Taught by dr. Y. Ghiassi-Farrokhfal.

    • In today’s economy, data-driven decision making in firms increasingly replaces decision based on gut feelings. As data is becoming increasingly available for firms from sources both internal and external, the need to understand methods to process and analyze data grows steadily.

      Therefore, this course will equip students with the necessary tools to extract knowledge from data to succeed in their master theses and ultimately conduct their own research. To this end, students will be introduced to the fundamentals of selected empirical research methods (case studies and econometrics) and selected types of data provenance (observational, experimental, and survey data). Understanding these methods and data types will be essential for the students’ success in their master theses and, not only but especially, when considering pursuing an academic career after their master’s degree in form of a PhD. Students will have hands-on experience with data to acquire expertise in solving practical data-related issues. These skills are not only crucial to the success in this course but are valuable assets in other courses covering data analytics in their master’s programme as well as in their professional lives, of course.

      Review the course guide for more details.

      Taught by Dominik Gutt.

    • In Business Architecture & Transformation we aim to explain the role of digital and leadership capabilities within organizations and how to assess these capabilities. We will present you with the concept of operating models and demonstrate on real life examples which operating model fits which kind of company. We will explain the difference between digital operations and digital strategy. Further, we will look into how investments in IT can be assessed.   We will point out the importance of IT governance to achieve strategic alignment between IT and business. Finally, we will talk about what really makes a true management leader in IT.
       
      While you have looked into how to strategically use information and how to design business applications in the first block of your core courses we try to give you a perspective on how you can manage IT projects on a higher level. We look into the business and management perspective of transformation processes and how strategic decisions on a CIO-level should be made.
       
      This course is a combination of lectures, guest lecturers, in class case analysis, and discussions.
      Specific course guidelines will be made available via Canvas prior to the beginning of the course and need to be read and understood by each participant. Further, the textbook for the course needs to be purchased prior to the start of the course.

      Review the course guide for more details.

      Taught by dr. Markus Weinmann.

    • The exponential growth in data generation and storage creates new business opportunities but also leads to major technical and managerial challenges. New tools, methods, and organizational changes are necessary to take advantage of these growing amounts data, popularly known as Big Data. Major determinants for the surge of Big Data include the amount of information generated on the internet, the evolving strategy of firms to collect data from sources both internal and external along the entire product and process lifecycle, the growth of social media, mobile applications, and the increasing availability of sensor based technologies. 

      This course will introduce students to what characterizes "Big Data" (e.g., volume, variety, velocity, and veracity) and to their main challenges. The course will cover the fundamentals of Data Science, including data preparation, modeling, evaluation, and deployment. Specifically, students will learn how to identify data problems and opportunities, and how to structure, design and deploy data-driven solutions that provide value to the business sector. Students will have hands-on experience solving practical cases using Big Data tools and technologies available in the market.

      Review the course guide​​​​​​​ for more details.

      Taught by dr. R Crisostomo Pereira Belo

    • How can information and communication technologies (ICTs) be used to create societal impact and promote social change? The advent of Interned-based communication, such as social media, online platforms and communities, has created new opportunities for organizations and businesses to mobilize large online crowds to exchange information, gain resources, obtain new skills and knowledge, and eventually achieve social change in sustainable development, health, environment, and the social sector. While there are several examples in academic research and practice of the use of technologies for social purposes, it is also important to develop a critical understanding of the effectiveness of these practices and their societal impact.

      This course offers a unique combination of topics at the intersection of sociology and business information management to understand new organizational forms produced by ICTs and aiming at social change. We will analyze and discuss how ICTs can be used as a possible way to find solutions to some of the world’s most challenging social problems across a range of domains (e.g., social welfare, health, environment, education, sustainable development, activism). In addition, we will also critically analyze advantages and disadvantages of ICTs use for social purposes.

      Why it is important?

      • The driving motivation of this elective is to develop a critical understanding of and ability to design and evaluate the use of ICTs to solve relevant problems and issues of our society.

      Practically, this course will offer insights about 

      • How we, as citizens, can directly engage and collaborate in the solution of societal problems via an effective and responsible use of ICTs.
      • How organizations and businesses can make effective use ICTs for social purposes.

      Review the course guide for more details.

      Taught by dr. Anna Priante​​​​​​​

    • Many of the most successful companies of the digital age such as Google, Facebook, Apple, Microsoft or Amazon can be characterized as platforms. A platform connects distinct user groups, thereby creating value by enabling interactions between these groups. They are governed by market forces such as network effects that are distinct from traditional markets and therefore have attracted the attention of scholars in strategy and economics, but also policy makers and business gurus.

      The goal of this course is to introduce students to current research on platforms from the fields of strategy and economics and apply it to management and public policy related questions on platform markets.  

      Review the course guide​​​​​​​​​​​​​​ for more details.

      Taught by dr. Dainis Zegners.

    • Many choices are made in digital environments, however, not only the sheer number of choices but also their presentation may influence our decisions and distort us, because we have only limited cognitive capacities to cope with lots of choices. In this course, we will focus on digital decisions, made in digital environments such as websites or apps, with emphasis on how these decisions deviate from rational and/or ethical standards. Understanding how digital environments influence our choices can help to improve our decision-making.

      Review the course guide​​​​​​​​​​​​​​ for more details.

      This course is taught by dr. Markus Weinmann.

    • Firms need to innovate to stay competitive. Kodak and Nokia are amongst the many examples of companies that paid the price for not keeping up with the market. However, innovation is difficult and while successful innovations promise large returns, many projects fail. This has never been more accurate than in the Digital Age, as fast-paced and complex technologies now permeate businesses and products.

      Review the course guide​​​​​​​​​​​​​​ for more details.

      Taught by dr. Philipp Cornelius.

    • Foundational information technologies, in particular, Artificial Intelligence (AI) algorithms, Internet-of-Things (IoT) systems, and Blockchain infrastructure, will create new foundations for business and its interaction among businesses, governments, customers, and the earth. These technologies will create opportunities for circular business models, i.e., to do business within the ecological and planetary boundaries of the earth. Instead of the ‘take, make, and dispose’ attitude of the traditional and linear business, circular business will create value with the design of ‘recycle, refurbish, reuse, and maintain’ processes. Both the circular and digital transformation will influence customer relationships, redefine products and services, change the operations and value chain processes, enable new ways of collaboration in business ecosystems, and will shift the information frontier further, with fresh, fast, and more reliable information relevant for circular business models. Next generation business models will need to develop both the circular and digital capabilities in a holistic configuration of people, processes, and technologies.

      Review the course guide for more details.

      Taught by Prof. Eric van Heck

    • There is a pressing need for innovative information processes which address individual needs while at the same time guiding individual behavior towards the common good of society. For example, by integrating personal information collected from wearable devices with public health services to simultaneously provide self-care guidance and improve healthcare system efficiency. One challenge of information processes like this is to preserve individual privacy while collecting adequate population-level information to effectively guide behavior at scale. This is a complex and challenging problem which requires novel approaches.

      This course seeks new ways to address complex behavioral problems by putting human needs at the center of new process development. Students will apply behavioral theories together with business process modeling techniques to create human-centered processes within an assigned problem domain. Students participate in an iterative and hands-on learning process involving presentations, discussions, and assignments. Class participation is mandatory.

      Review the course guide for more details.

      Taught by Dr. Jeffrey Sweeney

    • BIM students have the opportunity to combine the writing of their thesis with an internship at a company and replacing an elective course with this internship. The internship must be directly related to the thesis and students can only take this course after formal approval by the thesis coordinator. The company-based research project will be assessed separately from the thesis (on a pass/fail basis) by the thesis coordinator in consultation with the thesis coach and a company supervisor.

      BIM students have the opportunity to combine the writing of their thesis with an internship at a company during one of the elective blocks (block 3, 4, or 5) and replacing the free elective course with this internship. This means that:

      • During the CRP elective, students will work ‘full-time’ for 5 days a week at the company (168 hours);
      • In the other two elective blocks students will work at the company ‘part-time’ for 2 days a week (224 hours);
      • The internship must be for a total of 392 hours to qualify for the BIM CRP.

       

      It is also important that the internship is related to the thesis (so only 'content' internships qualify) and students need to decide on an internship in consultation with their thesis coach and the master thesis coordinator. The BIM CRP will be assessed separately from the thesis (on a pass/fail basis) by the thesis coach in consultation with a company supervisor.

       

       Students need to find an internship company that:

      • Will allow them to work fulltime during one of the elective blocks and max 2 days a week during the rest of the elective period;
      • Will offer them the opportunity to work on a topic that they can write their thesis on. As mentioned, only ‘content internships’ qualify;

      Will offer them the opportunity to collect company-specific data (for that specific company) that they really need to write their thesis. 

      THIS ELECTIVE COUNTS AS A FREE ELECTIVE FOR BIM STUDENTS ONLY. IN OTHER WORDS: in order to graduate you MUST complete at least two BIM program electives!

      Review the course guide​​​​​​​​​​​​​​ for more details.

      Taught by dr. D Tsekouras.

    • This course aims to strengthen your abilities as future managers with one of the most important yet mostly missing skills for managers: the art of programming. Managers with programming experience are able to be involved in the decision-making process of their developers. They can also --at high level-- understand whether or not each developer is performing well. In this course, we will focus on one of the most widely used programming languages: Java. This course also lays the foundation for learning other important programming languages. You should not expect to be developers in few weeks. You should rather treat this course as an intense programming tutorial for absolute beginners. It is assumed that the registered students have no previous knowledge of programming. After taking this course, you will learn how to excel in Java even further or to start learning a new programming language from scratch. Java is greatly structured to be an easy-to-learn, yet a powerful programming language..

      Review the course guide​​​​​​​​​​​​​​ for more details.

      Taught by dr. Y Ghiassi-Farrokhfal.

    • Social Networks shape many aspects of how people and organizations interact, take decisions, and ultimately perform. With the advent of Social Media (e.g., Facebook and Twitter) and with the increasing digitization of all forms of communication and business processes, Network Analytics has become a valued asset to better understand how different agents interact and how to best take advantage of the network structure to increase overall system performance. This course will cover the fundamentals of network science, the methods, theories, and the procedures for data collection and analysis in very large social networks. Covered topics include clustering, information diffusion, organizational design, viral marketing, social media and others.

      This course provides the basics of network data analytics, including fundamental network- and node-level metrics, as well as more advanced analysis methods, with attention to the application areas where these can and have been used. Students will engage in in-class projects in which they collect and analyze network data using the tools and methods covered in class. Students will apply these methods to specific networks, such as social media networks (e.g., Twitter), co-worker networks, organization networks, and product networks.

      Review the course guide​​​​​​​​​​​​​​ for more details.

      Taught by dr. R Crisostomo Pereira Belo.

    • Advanced business analytics is becoming a key driver of competitive advantage. Only firms that can harness their data and develop strong analytic capabilities across all their business functions will be able to survive in fast-moving modern markets. In this course, students will learn how to use Python to analyse large data sets and apply them to business problems.

      To be able to follow this course, students need to have prior coding experience (e.g., BM06BIM BIM Research Methods I).

      View the course guide for more details.

      This course is taught by dr. PB Cornelius

    • With the explosion of Big Data from social media and technologies, such as RFID, GPS, and sensor-data, organizations are increasingly confronted with the need to develop analytics capabilities to take advantage of their data. This gives many great opportunities to work on the cutting edge of science and business.
       
      In order to design a practical Business Analytics application, we will explain throughout the course how to use the programming language and software environment R to collect, analyze, and visualize relevant data, be they publicly available data (social media or otherwise) or internal data from a company.

      Review the course guide​​​​​​​​​​​​​​ for more details.

      Taught by dr. J. van Dalen and dr. D. Zegners.

    • Deep Learning represents one of the most exciting advances in machine learning with many groundbreaking applications being developed in recent years from areas such as image recognition and speech analysis to machine translation and game-play. Underlying these advances are various types deep neural networks and although these can be very technical, in this course we will try to de-mystify them a little bit, so you will be better able to assess the possibilities and limitation in business practice. We will cover three main topics:

      1. Neural Networks
      2. Recurrent Neural Networks (used particularly in text analysis and time series analysis)
      3. Convolutional Neural Network (used particularly in image processing)

      The main focus of this course is practical and emphasizes learning-by-doing: you will be doing a lot of coding in R and in the main project go through the whole CRISP-DM cycle from the real, practical problem to the final model results and proposed deployment. We put you in the role of the ‘analytics translator’: sufficiently grounded in both the technical aspects and the organizational aspects to be able to function as a bridge between the pure specialists in these areas, so that you will understand the technical, organizational and ethical aspects of deep learning applications.

      Review the course guide​​​​​​​​​​​​​​ for more details.

      Taught by dr. Otto Koppius.

    • Data is a crucial resource and at the core of many companies’ business models. Hence, collecting, analyzing, and understanding data is one of the key competencies for future professionals in business. This course will consist of seminar sessions that familiarize students with the basic ways of collecting, organizing, and analyzing data to succeed in a data-driven society, be it in academia or in business. This course will mainly use online reviews as an example for these exercises.

      Review the course guide​​​​​​​ for more details.

      This course is taught by dr. Dominik Gutt.

    • BIM students have the opportunity to combine the writing of their thesis with an internship at a company and replacing an elective course with this internship. The internship must be directly related to the thesis and students can only take this course after formal approval by the thesis coordinator. The company-based research project will be assessed separately from the thesis (on a pass/fail basis) by the thesis coordinator in consultation with the thesis coach and a company supervisor.

      BIM students have the opportunity to combine the writing of their thesis with an internship at a company during one of the elective blocks (block 3, 4, or 5) and replacing the free elective course with this internship. This means that:

      • During the CRP elective, students will work ‘full-time’ for 5 days a week at the company (168 hours);
      • In the other two elective blocks students will work at the company ‘part-time’ for 2 days a week (224 hours);
      • The internship must be for a total of 392 hours to qualify for the BIM CRP.

       

      It is also important that the internship is related to the thesis (so only 'content' internships qualify) and students need to decide on an internship in consultation with their thesis coach and the master thesis coordinator. The BIM CRP will be assessed separately from the thesis (on a pass/fail basis) by the thesis coach in consultation with a company supervisor.

       

       Students need to find an internship company that:

      • Will allow them to work fulltime during one of the elective blocks and max 2 days a week during the rest of the elective period;
      • Will offer them the opportunity to work on a topic that they can write their thesis on. As mentioned, only ‘content internships’ qualify;

      Will offer them the opportunity to collect company-specific data (for that specific company) that they really need to write their thesis. 

      THIS ELECTIVE COUNTS AS A FREE ELECTIVE FOR BIM STUDENTS ONLY. IN OTHER WORDS: in order to graduate you MUST complete at least two BIM program electives!

      Review the course guide​​​​​​​ for more details.

      Taught by dr. D Tsekouras.

  • The BIM Company-Based Research Project (CRP) allows students to replace one free elective course in the program with a full-time thesis / research internship for one of the elective blocks (minimum of 168 hours). During the remaining two elective blocks, the student is recommended to continue working part-time and follow the remaining electives.

    The BIM CRP should seek to combine the writing of the thesis with an internship at a company during one of the elective blocks (Blocks, 3, 4, or 5). It is therefore important that the internship is related to the thesis and students will need to decide on an internship in consultation with their thesis coach and the master thesis coordinator. Students must be able to show that the internship will allow them to collect company-specific data (for that specific company), and that it is essential for their thesis project.

    The CRP will be assessed separately from the thesis (on a pass/fail basis) by the thesis coach, company supervisor and master thesis coordinator.

    If a student opts for the CRP, it will count as a free elective for 6 EC. This will give them the opportunity to work exclusively within the company for a period of 7 weeks. Thesis internships may be agreed for a longer period of time, but a minimum of 168 hours is expected and a maximum of 6 ECTS is credited. During the remaining two elective blocks, the student is recommended to work part-time and follow the remaining electives.

    THIS ELECTIVE COUNTS AS A FREE ELECTIVE FOR BIM STUDENTS ONLY. In order to graduate you MUST complete at least two other BIM Programme Electives! Please do not select this elective if you have not signed a contract yet.

    Review the course guide for more details.

    Taught by dr. D Tsekouras.

  • Firms need to innovate to stay competitive. Kodak and Nokia are amongst the many examples of companies that paid the price for not keeping up with the market. However, innovation is difficult and while successful innovations promise large returns, many projects fail. This has never been more accurate than in the Digital Age, as fast-paced and complex technologies now permeate businesses and products.

    Review the course guide for more details.

    Taught by Philipp Cornelius.

  • The BIM Honours Programme offers the most talented and motivated students in the MSc BIM program a challenging extracurricular course in BIM research and practice. Participation is by invitation only. A limited group of 25-30 students will be selected to follow an additional course that runs across the 3rd, 4th, and 5th block of their studies. Selected students are the best performing students of the MSc in BIM programme. The small group size ensures that students have many opportunities for interaction with faculty members and participating companies.

    The programme features involvement from multiple companies. The sessions will be highly interactive and require a strong preparation. Cooperation is sought with external partners, who introduce a series of challenges that students need to complete (e.g. consultancy project, data analytics challenge, business process training).

    Participation will be limited to the best students in the MSc programme of Business Information Management. The first step in the selection process will be a ranking based on all core courses (Blocks 1 and 2, weighted by ECTS). In the second step in the selection process, the highest ranking students will be asked to submit a motivation letter.

    For more information please click here.

    • One of the reasons companies hire university graduates, is because of their academic posture. This includes a critical attitude towards what is presented as “the truth”, the ability to assess the quality of research presented to them, and the competence to study a phenomenon in a structured way. These same qualities are required of you as you design and execute your Master thesis project. This course will focus on the basics of conducting sound scientific research and writing a good master thesis.

      Taught by dr. D. Tsekouras

    • During the year you will participate in a structured master thesis trajectory. You will start in September, during the core courses, to familiarize yourself with the research being done at our department and the relevant academic literature and topics available. Staff involved in this MSc will present their current research projects, and you will be invited to link your master thesis to one of these projects. Before Christmas you will decide on a final topic and be assigned a coach who is an expert in the subject area chosen. Early January a thesis clinic will provide you with the foundation that you will need to complete your thesis successfully. In February you will deliver your research proposal after which you will implement your research question and finalize your thesis before the summer. Staff and researchers will provide assistance by coaching you through the entire master thesis process.

      The following themes are examples of possible BIM Master Thesis topics:

      • The Impact of IT on Business
      • Online Human Behavior
      • Big Data and Analytics
      • Social Media and Digital Commerce
      • Green IT and Energy Business

Note regarding taking courses if you are not an RSM master student: RSM does not offer the possibility for non-RSM students (master or otherwise) to take RSM courses outside of official exchange partnerships or other inter-faculty agreements.