Digital Business Innovation and Transformation master degree programme

Become a change agent! After your master degree, you'll lead your company into the future. You'll be able to coordinate and direct digital transformations, no matter what the industry. Because the future is digital.

The part-time master programme focuses on key business administration skills combined with expertise in digitalisation and innovation, as well as the ability to understand, motivate and lead people.

Be the change you want to see in companies!

Big data, the Internet of things (IoT), artificial intelligence, blockchain technology and robotics: just a few examples of digital innovations that are permanently changing the rules of the game for organisations. Companies must be well-prepared for new challenges in order to ensure their continued success and take advantage of the opportunities offered by digitalisation. Digital transformation shouldn't be a mere buzzword – it has to be reflected in the strategy, structures, corporate culture, and processes of a company.

And this is exactly what our programme prepares you for. As a graduate, you'll act as an ambassador for digitalisation and innovation: you'll see digitalisation as an opportunity and be able to show companies where potential for networking and ongoing development lies.

The master programme equips you with the skills you need to successfully manage digitalisation processes in companies. A powerful combination: business administration, digital and data expertise, and an understanding of the behavioural and sociological aspects of transformation.

New: Optimal compatibility thanks to virtual component

In a part-time degree programme, the compatibility with work and private life is one of the most important success factors. And this is exactly where our master programme scores: the courses on Fridays take place virtually from 2 p.m. Saturdays are spent on site in Krems. One block week in each of the first three semesters rounds off the offer.
The new model offers maximum flexibility and is of course also very attractive for all commuters.

Room for your individual interests

The study content of the master programme is optimally tailored to the needs of companies. A special feature of our degree programme is that 1 ECTS per semester (during the first 3 semesters) is available to you for self-directed learning. During this time, you can acquire new skills and set the direction yourself: for example, you can learn a new programming language or familiarise yourself with the latest tools. In this way, you are well prepared for lifelong learning.

International orientation

Since digitalisation continues to increasingly connect the world, the degree stands out for its strong international focus. Just a few examples: English as the language of instruction, countless international teachers, and the opportunity to spend semester 4 at one of our partner universities.

Certifications

In addition to the degree, this study programme enables you to receive two Austrian Standards personal certifications , namely the P53-Digital Officer and the P59-Innovation Risk Manager certificate.

Upon completion of the module "Data Analytics", you can earn an extra Tier 1 SAS Academic Specialisation (digital badge) in "Digital Business Analytics".

Studium Digital Business Innovation and Transformation - Professor hält einen Vortrag

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Studium Digital Business Innovation and Transformation - Studierende reden miteinander

" What makes the degree unique is our holistic approach to digitalisation. On the one hand, critical and analytical thinking are needed to fully exploit existing processes digitally. On the other hand, creativity is called for to explore potential and develop, test and, if necessary, integrate innovative products, services, and business models into the company. We call this process transformation. The challenge lies less in mastering the new digital technologies or ensuring profitability, but rather in bringing the human factor to the fore and incorporating it into the process. Our focus here is on customer-centric innovation using approaches such as design thinking, as well as on human-computer interaction, human development and communications, change and transformation management, leadership, and ethics. "
Programme director Roger Hage

A formula for success: theoretical knowledge + practical experience

The programme is built on three pillars.

1
1. The business basics
Semesters 1-4
The programme starts by covering business basics with a special emphasis on the strategic focus of companies. You'll deal specifically with corporate structure and prepare yourself to assume management tasks in digital settings.
You'll develop a deep understanding of the importance of continuous optimisation processes, but risk management is also an important element of the curriculum. You'll learn how to implement proactive company-wide risk management systems. In addition, you'll become familiar with tools for identifying and assessing risks. This will enable you to objectively assess opportunities and risks and therefore reach sustainable corporate decisions. Since technologies are developing rapidly, often exponentially, the degree prepares you for future scenarios and building corporate foresight: you learn how to continuously develop forward-looking strategies to prepare for future contingencies.
2
2. The core topics
Semesters 1-4
Innovation and digitisation have already become important corporate success factors and will become increasingly decisive for companies in the future. During your studies you'll learn how to embed these elements in your company and successfully transform existing processes. After graduation, you'll be excellently positioned to initiate and implement a transition from analogue to digital organisational structures.
In other words, you'll focus on how to make companies sustainable and competitive in the long term. You'll become an expert in ongoing change processes.
Digitalisation is a new discipline and as such is unable to tap into widely proven best practices. You will therefore learn how to experiment creatively and skilfully, and how to make evidence-based decisions, i.e. ones which are well-founded and data driven. You will gradually advance to become a data expert after taking a number of courses in data management and analysis, using statistical and programming tools such as R and SAS. You won’t be a fully-fledged data scientist or programmer, but by the end of the programme you'll be capable of working effectively alongside IT engineers and data scientists.
3
3. The practical training
Semesters 1-4
A practical focus is more than just a buzzword at IMC Krems; our lecturers share their real-life professional experience. Many of the programme’s lecturers are regarded as experts in the digital economy and can draw on international experience. Problems are discussed and dealt with on the basis of case studies. And the Innovation Lab, a joint project with companies in semester 2, gives students practical insights into the topics they have covered. You can select your project based on your interests and industry preferences. You can also learn from your fellow students by working in groups, all of whom can share their valuable experience from everyday professional settings.
The 4th semester is dedicated to your master thesis. Depending on your interests, your thesis will focus on a research-related or practical question. Ideally, your theses will examine a real-life project at your company. You can enhance your expertise on a topic of your choice and pick up valuable input from our experts. In parallel, you have the opportunity to spend a semester abroad at one of our numerous partner universities.

Curriculum

What can you expect from your studies? The curriculum provides an overview.
Click on the individual courses for further information.

Course	SWS	ECTS
Digital Business & Process Management
Business Analysis & Strategy Development
Business Analysis & Strategy Development	3	6
Business Analysis & Strategy Development Module: Business Analysis & Strategy Development Root module: Digital Business & Process Management Semester: 1 Course code: BASC1ILV Contact hours per week: 3 ECTS: 6 Course Content: Rhythm of Business: Strategy development and planning process (standard versus agile approach) Evaluating companies and their business environment with focus on the assessment of digital capabilities (maturity) and of digitization potential Methods and frameworks for strategy development design and analysis (including Business and Strategy Consulting tools and special attention to sustainability aspects, e.g. stakeholder management and outside-in strategy development) Approach to strategy implementation with focus on the development of a digital development path Course outcome: At the end of this module students are able to: illustrate the difference between standard and agile strategy development approaches, carry out a selected business analysis and strategy development methods, illustrate how to bring sustainability aspects into the process of strategy development and business analysis, apply a suitable approach to assess a company’s business capabilities and especially digital maturity and digitization potential (customer value or cost advantages derived from digitization), develop a transformation strategy and plan.
Digital Economy & Business Models
Digital Economy & Business Models	3	6
Digital Economy & Business Models Module: Digital Economy & Business Models Root module: Digital Business & Process Management Semester: 1 Course code: DEBM1ILV Contact hours per week: 3 ECTS: 6 Course Content: Knowledge and understanding of key theoretical and practical approaches in the context of the digital economy, digital markets, digitalised businesses and effects on value creation and value co-creation mechanis Evaluating the transition and transformation of business models to digitised business models Transformation of markets and industrial value chains at global scale as a result of digitalisation." Triple bottom line considerations (economic, social and environmental) The transformation of value creation: theories, concepts and processes including digitalisation of conventional value chains: primary and secondary value creation, industrial and company value chains Digitalisation of conventional value chains: primary and secondary value creation, industrial and company value chains Business Model Innovation methods such as Canvas-based models and methods Discussing incremental and disruptive factors and examples in the context of digitalisation of intra-company and industrial value chains, triggered or supported by digital technologies, such as blockchain, artificial intelligence, software robotics, cloud, business intelligence and mining, etc. Network economics of multi-sided networks, platforms and digital ecosystems Course outcome: At the end of this module students are able to: classify and discuss different business model types, business logics and value creation mechanism, identify and discuss key drivers for business model innovation and performance including trends and expectations at the societal level such as the UN Sustainable Development Goals, explain the influence of new technologies on business models and their effects on business strategies, value creation and business ecosystems, apply and evaluate central concepts and terminology within the field of digital economy, digitalised businesses and digital markets, analyse and compare digial ecosystems by consideration power distribuion and rules, roles and hierarchies, user participation, potentials in data driven businesss modelling and predictions, analyse and apply business model innovation concepts and examine the transformation of value creation machanism in the context of digital technologies and processes, analyse and evaluate digitalisation of business processes along the industrial value chains, Identify and critically evaluate the economic, ecologic and social impact of different business models.
Innovation
Innovation Management
Innovation Management	3	6
Innovation Management Module: Innovation Management Root module: Innovation Semester: 1 Course code: IM1ILV Contact hours per week: 3 ECTS: 6 Course Content: Dynamics of the economy (Schumpeter, Kirzner, Knight) Types and degrees of Innovation and Sources of Innovation Disruptive Innovation (Chistenssen) and its implications House of Innovation (Innovation Strategy, System, Portfolio and Projects) Diffusion of Innovation (Everett Rogers and Geoffrey A. Moore) Foresight and trend research methods (scenario techniques, forecasting techniques, Delphi method, roadmapping, cross-impact analysis) Innovation evaluation models for cost-benefit/investment analysis and decisions (e.g. return on investment calculations, NPV, BCR, sensitivity analyses) and KPIs Designing innovation controlling systems (Innovation accounting, metrics and levels) Triple bottom line considerations (economic, social and environmental) Business model innovation, Blue Ocean Strategy, Frugal Innovation Course outcome: At the end of this module students are able to: categorise different types of innovation, and evaluate the demands they place on the innovation process, explain the central elements of an innovation process, apply foresight methods to identify future opportunities and risks, analyse a variety of approaches to developing innovation strategies, determine the efficiency and effectiveness of innovation activities using controlling instruments, Identify and critically evaluate the social and environmental impact of innovations.
Data & Innovation Technology
Digital Technologies
Digital Technologies	3	6
Digital Technologies Module: Digital Technologies Root module: Data & Innovation Technology Semester: 1 Course code: DT1ILV Contact hours per week: 3 ECTS: 6 Course Content: Introduction to Information and Communication Technologies and their role in corporate environment Current technical trends and the foundation of the technologies behind them (VR, BC, IoT, AI, Cloud, 3DP…) Models and theories related to the rise and dissemination of digital trends and their practical application Method of trend assessment and prognoses as well as suitable infomation sources Method of designing user experience and their application Definition of sustainability and methods for assessing the sustainability of technologies and technical trends Principles of business and organizational ethics from a humanistic sociotechnical systems perspective Course outcome: At the end of this module students are able to: explain the emergence of technologicall trends and identify suitable means of measuring them, identify current technological trends, present key technologies behind them, and describe their possible impact on businesses, evaluate and forecast the development of technologies in connection to specific business areas based on suitably chosen methods, apply basic techniques of evaluating user experience to technology-driven innovations, generate and apply a suitable approach for assessing the sustainability of trends, explain human and sociotechnical systems (STS) principles and practically apply them in assessing the short and long term impact of digital technology applications in business and workplace settings, communicate and discuss analysis findings.
Business Statistics and Data Science
Business Statistics & Data Science	3	5
Business Statistics & Data Science Module: Business Statistics and Data Science Root module: Data & Innovation Technology Semester: 1 Course code: BSDS1ILV Contact hours per week: 3 ECTS: 5 Course Content: Computational Thinking (Introdoction to R) Statistical Thinking Probabilities Descriptive and Inferential Statistics Variables Experiments Research questions and Hypothesis testing Decision making under risk and uncertainty, Managerial economics Pay-off table decision trees Opportunity Loss EMV EVPI Utility Risk Aversion and Prospect Theory Revising Information with Bayes' Theorem Data Science Applications Exploratory Data Analysis (Decriptive statistics and visualization) Statistical Experiments and Significance Testing (Hypothesis Tests, A/B Testing) Regression and Prediction (Simple and Multiple Linear Regression) Classification (Logistic Regression, Discriminant Analysis and Naive Bayes) Statistical Machine Learning (KNN, Trees, Random Forests) Unsupervised Learning (Clustering: K-means & Hierarchical, PCA) Course outcome: At the end of this module students are able to: apply the data analytics methods and processes to solve business problems, apply tools to assist in decision-making in different circumstances (e.g. high uncertanty), solve business problems using statistics by hand and by using a programming language (ex. R), define data requirements based on an application problem statement, apply Exploratory Data Analysis, analyse datasets using the right Classification, Regression and Clustering models.
Research & Scientific Methods
Self-directed Learning I
Self-directed Learning I: Learning agreement	1	1
Self-directed Learning I: Learning agreement Module: Self-directed Learning I Root module: Research & Scientific Methods Semester: 1 Course code: SDLI1WK Contact hours per week: 1 ECTS: 1 Course Content: At the end of this module students are able to: students can choose and apply suitable methods and models for the purpose of self-analysis and goal setting, critically asses professional context and carreer development, identifying own knowledge gaps or lacking foundations for further development, reflect and describe personal strength and weaknesses in context of a concrete professional field, business area, and technical development, define and operationalise learning goals, and create a trackable learning plan. Course outcome: Self-assessment techniques Career assessment and prognosis techniques Goal-setting and goal-monitoring techniques Techniques for efficient information search and content identification Learning, leanring goals, and learning monitoring Learning agreement and learning controlling

Course	SWS	ECTS
Digital Business & Process Management
Digital Business Development
Digital Business Development	3	5
Digital Business Development Module: Digital Business Development Root module: Digital Business & Process Management Semester: 2 Course code: DBD2ILV Contact hours per week: 3 ECTS: 5 Course Content: Growth strategies Difference between traditional and digital business model growth and startegies Ansoff's growth model Greiner's organizational growth model Market Penetration: Sales, Marketing and Channel development Digital marketing (4P), performance marketing and analytics CRM and marketing automation (in-bound, outbound) Ecommerce automation (4C) Omnichannel marketing and Digital Customer Experience Management Market Development & Internationalisation Motives and I/R Framework (Bartlett & Goshal), Ghemawat’s “AAA” Global Strategy Framework Theories and Models (Uppsala, Network, Eclectic, Int'l Entrepreneurship) EPRG Orientation and CAGE distance model, Culture, cultural dimensions (Hofstede) International 4P marketing mix policies and international STP strategies Foreign market entry strategies and modes of operation Product Development & Diversification Commercialization and Scaling of Innovations Diffusion of Innovation model Hightech B2B Marketing: Strategies for crossing the chasm Launching and scaling SaaS businesses Igniting and scaling multi-sided digital platforms Course outcome: At the end of this module students are able to: develop a growth strategy plan exploiting digital opportunities, plan global digital marketing activities to achieve a range of objectives and outline how they can be implemented, illustrate how new digital technologies can be applied in developing the business to increase reach and revenue, evaluate the digital marketing and sales maturity of companies, interpret marketing and sales analytic data and derive actions to optimize processes, customer experience and product development, develop actionable KPIs for business growth and explain how to implement and manage them, apply the theories of persuasion and communication in written.
Digital Process Management & Automation
Digital Process Management	2	3
Digital Process Management Module: Digital Process Management & Automation Root module: Digital Business & Process Management Semester: 2 Course code: DPMA2ILV Contact hours per week: 2 ECTS: 3 Course Content: Principles of process management and process lifecycle Process modelling with formal language(s) Methods for process analysis and innovation Approaches and methods to process monitoring and process mining Technologies in process automation Course outcome: Upon completion of this course students are able to: apply a formal modelling language to complex processes, analyse processes using structured methods, plan process improvement using structured methods, develop suitable indicators for process monitoring, describe currently available technologies for process automation and process analysis, explaining their application context, advantages and disadvantages.
Process Automation	1	3
Process Automation Module: Digital Process Management & Automation Root module: Digital Business & Process Management Semester: 2 Course code: PA2WK Contact hours per week: 1 ECTS: 3 Course Content: New forms of value creation and value chain in the digital age (e.g. the on-demand economy and the sharing economy) Digitalisation of conventional value chains: primary and secondary value creation, industrial and company value chains Current trends in process innovation and automation Course outcome: Upon completion of this course students are able to: analyse and evaluate digital complex business processes along the value chain, selecting and applying suitable methods and evaluating findings from them, determine unused potential that could be leveraged using alternative digital processes and structures, design a suitable digitalisation approaches and plan their implementation, communicate and discuss analysis findings.
Leadership
Project & Change Management
Project & Change Management	3	6
Project & Change Management Module: Project & Change Management Root module: Leadership Semester: 2 Course code: PCM2ILV Contact hours per week: 3 ECTS: 6 Course Content: Classic versus Agile Project Management Different project methodes (ex. Waterfall, Hybrid, Scrum, Kanban, Scrumban, SAFE, Nexus, LESS, OKR) Tools for virtual collaboration and project management (ex. Jira, Confluence, MS Teams, …) Individual Change Theories, Emotional Intelligence, Transactional Analysis, Process Communication Model Organizational Change Theories and Models (ex. Lewin, Kotter, Otto Schramer Theory U, ...) People management, Stakeholder management, Project Communication and Marketing Cultural aspects, Diversity and Intercultural Management, Conflict Management Leading Corporate Transformation Course outcome: At the end of this module students are able to: define, distinguish between and apply traditional and agile project management, and describe the attributes of each, select and apply modern management techniques suited to a particular situation to support strategy development, strategy communication and successful performance improvement, describe the core aspects of a transformation process and analyse various change management approaches, identify and critically evaluate sustainability and ethical issues pertaining to organisational transformations, develop actionable strategies to master the challenge of a dynamic environment and to drive change at different levels of the organisation, apply change and transformation models to digital transformation, name conflicts and contribute constructively to clarification as well as give constructive critique to team members and stand by their own mistakes, apply persuasion techniques in role plays.
Innovation
Innovation Lab
Innovation Lab	3	6
Innovation Lab Module: Innovation Lab Root module: Innovation Semester: 2 Course code: IL2WK Contact hours per week: 3 ECTS: 6 Course Content: Human-cetred Innovation (Design Thinking) Team-building (T-shaped) The holistic innovation process (Design Thinking, Lean Startup, Agile Development) Design Challenge Creativity techniques Course outcome: At the end of this module students are able to: apply and adapt the iterative human centred process to innovation projects, select, evaluate, adapt and apply the appropriate methods related to the stages of innovation projects, evaluate the market desirability, the technical feasibility and business viability of the innovation, evaluate sustainable as well as ethical, legal and security implications of digitalization and innovation, plan and distribute work in the course of the capstone project among the group, manage their working time effectively.
Data & Innovation Technology
IT, Data & Security Management
IT, Data & Security Management	3	6
IT, Data & Security Management Module: IT, Data & Security Management Root module: Data & Innovation Technology Semester: 2 Course code: ISCM2ILV Contact hours per week: 3 ECTS: 6 Course Content: At the end of this module students are able to: illustrate the fundamental technical approaches to data generation, data analysis and data integration, analyse diverse nature and states of data (such as data at rest, data in use and data in motion) in an organization and critically evaluate their roles in the corporate big picture, explain the advantages, disadvantages and areas of application of big data technology, architectures and analysis tools, explain the enterprise IT architecture and how to orchestrate the functions for a digital transformation, perform a capability-based plan and fit-for-purpose analysis, explain the Cloud paradigm, its advantages, disadvantages and how to build organization specific cloud migration context, explain the role of “digital security” in meeting strategic objectives, explain common security risks, threats and countermeasures, perform a risk assessment and an impact analysis for digital security threats on a firm. Course outcome: Business Layer· Business drivers, goals and objectives Capability-Based Planning Operational excellence, enhance customer/user experience and new business models Data Layer Types of Data (structured/unstructured, master/transactional, historical/real-time, internal/external) – Data in use, at rest and in transit Data Value Chain & Life-cycle (CRISP-DM). The Data Value Map Databases (relational, non-relational), Enterprise data hubs: Data warehouse, Data lake The concept of BIG Data (areas of applicability, storage & analysis architectures and technologies) Data Governance, Data Management and Data Protection Data availability, consistency, integrity and lifecycle management Intellectual property management and data loss prevention Application Layer Application Design (Front-end, Back-end/Service Layer, Database/Data Layer) Application interfaces, integration and standardization DevSecOps Technology Layer Libraries, Frameworks and Technology Stacks (Ex. MEARN, MERN, Flutter) Enterprise Architecture (EA) Best practice frameworks (ITIL, COBIT, TOGAF) Security Layer ISO OSI-Layers of Communication POPIT Security Framework and CIA (Confidentiality, Integrity, Availability) Organizational and operational security Information security guidelines, governance & protocols (ISO 27001) Typical security threats in IoT, Cloud, Mobiloe, AI, eCommerce… Enterprise digital resilience
Research & Scientific Methods
Self-directed Learning II
Self-directed learning II: Learning methods	1	1
Self-directed learning II: Learning methods Module: Self-directed Learning II Root module: Research & Scientific Methods Semester: 2 Course code: SDLII2WK Contact hours per week: 1 ECTS: 1 Course Content: At the end of this module students are able to: describe cognitive processes related to learning, analyse their progress with relation to learning goals, create an operative learning plan that takes into account not only the learning goals but also physcial, mental, and social needs,· choose and apply suitable techniques to maintain motivation and learning drive, choose and apply suitable techniques for effective and efficient learning. Course outcome: Theory of cognition and learning Evidence-based learning methods Evidence-based note-taking methods Techniques for motivation and self-assessment Techniques for tracing and monitoring (esp. in context of learning and personal development)

Course	SWS	ECTS
Leadership
Leadership in the Digital Age
Human Development and Leadership in the Digital Age	3	4
Human Development and Leadership in the Digital Age Module: Leadership in the Digital Age Root module: Leadership Semester: 3 Course code: HDLD3WK Contact hours per week: 3 ECTS: 4 Course Content: New Work environments in the digital age (People, Place, Technology) with special focus on leadership in dispersed work environments Employee workstyles and needs in the digital age (Point of reference: 'Make people flourish and live up to their full potential') Relevant leadership skills, traits, methods and instruments in the digital age Self-analysis and envisioning as a future leader in the digital age Course outcome: Upon completion of this course students are able to: illustrate and exemplify new work environments and their implication explain organisational and people development concepts, judge core HR models and concepts, as well as their applicability in agile, digitized work environments develop a leadership vision (role model) which adresses the needs of people in an organization (structure, processes, infrastructure, etc.). apply persuasion techniques in role plays name conflicts and contribute constructively to clarification as well as give constructive critique to team members and stand by their own mistakes.
Ethics in Leadership	1	2
Ethics in Leadership Module: Leadership in the Digital Age Root module: Leadership Semester: 3 Course code: EIL3WK Contact hours per week: 1 ECTS: 2 Course Content: Changes in managerial professional responsibilities due to digitalisation in business along the value chain Ethical responsibilities of all workplace participants—leaders, workforce, business partners, and supply chain members Principles of business and organizational ethics from a humanistic sociotechnical systems perspective Information and AI ethics in theory and practice Ethical critical reflection and decision making processes Practical ethical problem analysis and solution building (simulation/case study) Course outcome: Upon completion of this course students are able to: explain the duties of a manager to act in a socially responsible manner, explain ethical issues related to digital applications in companies, compare and contrast ethical models, values, reasoning, and processes related to managerial decision making in the contemporary business enterprise, identify and critically evaluate ethical problems linked to digitalisation and design potential solutions.
Risk & Legal Issues
Corporate Risk Management	2	3
Corporate Risk Management Module: Risk & Legal Issues Root module: Leadership Semester: 3 Course code: CRM3ILV Contact hours per week: 2 ECTS: 3 Course Content: International risk management standards Types of risk, risk assessment and classification Risk control, risk mitigation and risk treatment methods Roles and activities in Risk Management Risk management methods, processes and roles Risk management in agile and highly innovative organisations Agile Risk Management and Innovation Risk Management Risk vs Uncertainty, Foresight and Scenarios Course outcome: Upon completion of this course students are able to: plan exemplarily the implementation of proactive, company-wide risk management systems, use practical tools for identifying and assessing corporate risks arising from innovation and digitalisation, identify and analyse the role of risk management in value-based management, planning and reporting, explain optimisation processes and timely consideration of a risk/opportunity profile.
Legal Awareness	2	3
Legal Awareness Module: Risk & Legal Issues Root module: Leadership Semester: 3 Course code: LAW3VO Contact hours per week: 2 ECTS: 3 Course Content: Legal aspects of digitalisation: copyright, intellectual property, labour law, data protection Political and ethical dimensions of the digitalisation of environments Labour law topics, patent protection and protection of ideas Course outcome: Upon completion of this course students are able to: interpret the legal framework in areas of decision-making that are important for digital business, explain how to make practical use of intellectual property rights in order to protect innovations, intellectual achievements, patents, copyright, etc., evaluate the importance of intellectual property as an asset in a business context, evaluate the legal implications of technical solutions and organisational changes.
Data & Innovation Technology
Software Engineering and Quality Management
Software Engineering and Quality Management	3	6
Software Engineering and Quality Management Module: Software Engineering and Quality Management Root module: Data & Innovation Technology Semester: 3 Course code: SEQM3ILV Contact hours per week: 3 ECTS: 6 Course Content: At the end of this module students are able to: evaluate the quality of software projects, elicit, interpret and prioritize requirements for software-intensive systems, analyse and evaluate the architecture of software-intensive systems, select multiple design alternative and evaluate design decisions, systematically plan software development projects in agile and devops context, analyze the software landscape in an organisation, use appropriate software engineering methods and processes to deal with questions from the field of enterprise software architectures and document the results. Course outcome: Requirements Engineering - elicitation and management of requirements Software Engineering Process Models Software Architecure - Styles, Patterns and Best Practices Modeling Notations and Languages, e.g., UML Documentation of Design Decisions Cost Estimation Test and Deployment Starategies, Operational Concepts
Data Analytics
Data Analytics	3	6
Data Analytics Module: Data Analytics Root module: Data & Innovation Technology Semester: 3 Course code: DA3ILV Contact hours per week: 3 ECTS: 6 Course Content: Evaluating a business questions with respect to the required data and the suitable analysis method Defining data quality criteria and checking data quality Exploring the data in a visual and descriptive way Using advanced analytic models and machine learning techniques like decision trees, regression analyses, gradient boosting, and cluster analysis Preparaing results for further development of digitalization strategies Utilizating and evaluating results for error reduction, cost optimization and process optimization Vertical hands-on application examples in Industry, Marketing, Healthcare, Finance Information and AI ethics in theory and practice Tools: utilisation of open source and commercial data analytic tools (like SAS Software) Course outcome: At the end of this module students are able to: apply data management and data analysis on a case-by-case basis, interpret the results and findings from analytical models and decide which actions should be derived from them, draw appropriate conclusions and develop strategic planning steps, plan integration of data use within the organisational context, develop data-based business plan for process optimisation and cost reducion, explain information and artificial intelligence (AI) ethics principles applied to specific business technology applications.
Research & Scientific Methods
Research Methods
Research Methods	3	5
Research Methods Module: Research Methods Root module: Research & Scientific Methods Semester: 3 Course code: RM3ILV Contact hours per week: 3 ECTS: 5 Course Content: Literature search and lieterature review Research Methodologies Research design and research question & hypotheses Quantitative research: surveys, experiments Qualitative research: interviews, case studies, focus groups, delphi Writing research proposals and scientific papers (citation) Course outcome: At the end of this module students are able to: describe the empirical research process, select and implement qualitative and quantitative research designs according to the requirements of the given problem, identify suitable data sources and evaluate their quality, use software applications to assist with qualitative and quantitative data analysis, contrast suitable data collection methods, formulate a research question and hypotheses, test hypotheses using statistical methods and discuss findings.
Self-directed Learning III
Self-directed Learning III: Learning portfolio	1	1
Self-directed Learning III: Learning portfolio Module: Self-directed Learning III Root module: Research & Scientific Methods Semester: 3 Course code: SDLIII3WK Contact hours per week: 1 ECTS: 1 Course Content: Presentation options for skills/learning Content preparation for a skill/learning portfolio Communicating technical content with innovative methods Course outcome: At the end of this module students are able to: analyse and communicate their learning achievements, evaluate and present complex technology-related topics, create a skill porfolio.

Course	SWS	ECTS
Research & Scientific Methods
Academic Coaching Colloquium
Academic Coaching Colloquium	1	3
Academic Coaching Colloquium Module: Academic Coaching Colloquium Root module: Research & Scientific Methods Semester: 4 Course code: ACC4WK Contact hours per week: 1 ECTS: 3 Course Content: Coaching in writing the master thesis in order to obtain a second opinion, in addition to the supervisor’s input Clarification of content-related and formal academic issues Rehearsal of Thesis presentation and defense in fron of a committee Course outcome: At the end of this module students are able to: identify individual problems in connection with the preparation of the master's thesis, to clarify the identified problems and to develop a solution, present and defend a thesis.
Master Thesis
Master Thesis	0	22
Master Thesis Module: Master Thesis Root module: Research & Scientific Methods Semester: 4 Course code: MT4DA Contact hours per week: 0 ECTS: 22 Course outcome: At the end of this module students are able to: examine and critically discuss literature related to the topic or research problem, compile and evaluate data for the purpose of addressing the research problem/s, discuss and critically reflect on findings, independently produce their master thesis.
Master Exam
Master Exam	0	5
Master Exam Module: Master Exam Root module: Research & Scientific Methods Semester: 4 Course code: ME4AP Contact hours per week: 0 ECTS: 5 Course outcome: At the end of this module students are able to: present their Master Thesis appropriately to the target audience, and defend the question they addressed, the research design they used and the results reached before an expert committee, work through a case study related to their degree programme, applying the content of the programme, and develop and justify possible solutions.

Core topics

Re-imagine the business world! During your studies you'll ask yourself how you can advance digitalisation and innovation in your company based on basic economic principles.

Digital transformation

Where are we headed in this digitalised world? Get a holistic perspective of new technologies and work out how you can use digitalisation to add value to your business.

Opportunities of digitalisation

Developments such as automation, the sharing economy, prosumerisation – the growing professional demands of users on products and services – as well as smart services are only a few of the trends you'll deal with in depth. You'll also learn how to integrate digital processes into your corporate strategy and how your company can benefit from continuous improvement processes, right through to the development of innovative business processes.

On the other hand, you will also deal with the effects of digitalisation on society and the economy and learn to assess the associated opportunities and risks.

In this regard, you'll discuss how you can ensure that today's workforce meets tomorrow's needs. This means taking a close look at the conditions for digital work. For example, you'll deal with communication and collaboration among remote teams.

The power of data

During your studies you will come to realise the importance of data for the digitalisation of business models. You'll look at data generation, data management, data analysis and data visualisation. But data protection and governance play equally crucial roles, as do the appropriate tools and processes for optimal data management.

Let the data speak to you! You will naturally also learn how you can benefit from data – especially for Industry 4.0, the Internet of things (IoT) and digital services. Big data analysis and data mining are two terms that come up a lot.

Innovation 4.0

It will soon become obvious to you that digitalisation and innovation go hand in hand. That's why you'll also deal with the key well-established and new innovation models. You'll learn digital approaches that you can use to increase innovation in your company.

Digitalisation calls for change

You'll deal with organisational forms that promote innovation, and learn to transcend restrictive structures in traditional organisations. During your studies you'll acquire tools that will help you to successfully manage digital change processes. Because professional project and change management are indispensable when implementing a digitalisation process.

You'll also learn how to make the most of internal and external trends and developments. Based on your analyses, you'll design scenarios to ensure that your company is well-positioned to face the future.

Embedding innovation in your corporate culture

You'll also study human-centred innovation – especially design thinking – and learn about the underlying process in depth. Learn to walk the walk - that's the idea! It's a matter of identifying non-intuitive behaviour and reacting to it as quickly as possible with a prototype or a minimum viable product. Then you ask your users for feedback – and incorporate it immediately. This succinct process is then repeated several times.

In the Innovation Lab, you and your classmates will apply this approach to creatively, efficiently and effectively solve problems for real-world projects.

Newsletter & additional information

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Career options

After completing the Digital Business Innovation and Transformation master degree programme, you will have a solid understanding of the unique challenges and key success factors of digital business models.

You'll therefore be able to plan, direct, and drive production, service, or sales digital transformation processes.

After graduation, you'll enjoy new career opportunities because you'll be optimally positioned for an international career. You can use your newly acquired expertise to benefit your current company, or you can switch to another post in Austria or abroad.

The professional areas open to graduates include
change management with a focus on digital technologies
design and implementation of digital business models
digital supply chain management and logistics
big data analysis using digital technologies (e.g. optimisation of production lines by digital simulation of the production process)
project management
innovation management
business-oriented IT management
strategic management with a focus on digital business management
digital transformation consultancy
chief digital officer (CDO) responsibilities

10 good reasons

What makes us special? We are more than happy to tell you about the aspects of our university, which we are especially proud of.

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Krems

Friendly and cosmopolitan: The city attracts students from all over the world, who come to study, research and work together.

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Service centers

Our university has removed a host of administrative hurdles, leaving you free to concentrate fully on your studies.

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Advisory Service

Do you have questions regarding our degree programmes or the application? Contact our Prospective Student Advisory Service.

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Opinions: Digital Business Innovation and Transformation

Click through the videos of the degree programme.

Get to know our university of applied sciences from a new and very personal perspective.

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Our team

Get to know the core team of our master degree programme Digital Business Innovation and Transformation.

Prof.(FH) Dipl.-Ing. Dr. Roger Hage
Programme Director Digital Business Innovation and Transformation
Institute Digitalisation and Informatics
+43 2732 802 307
[email protected]
IMC Campus KremsIMC Campus Trakt G
Digital Transformation
International Business Development
R Programming
Informatics
Bachelor of Science in Engineering / full-time
Digital Business Innovation and Transformation
Master of Arts in Business / part-time
Digital Innovation Hub OST (DIHOST)
Department of Science & Technology
eMobSim - Elektromobilität im Alltag
Project Leader, Department of Business
Hage R., Lovasz-Bukvova, H., Hopp, M., Hölzl, M., Kormann-Hainzl G., Reiner, M., Dhungana, D. (2021): Agile Approach for E-Learning in Digital-Leadership Training for Small and Medium Enterprises. In Softic, S.K., Read, T. (Hrsg.), Proceedings of the EDEN Annual Conference: Lessons Learned from the Pandemic. Madrid: EDEN.
Lovazs-Bukova, H., Hage, R., Waiguny, M.K.J., Gruber-Mücke, T. (2020): ESTABLISHING AN AVATAR-BASED PRESENCE ON INSTAGRAM. In Doucek, P., Chroust, G., Oškrdal, V. (Hrsg.), IDIMT-2020 Digitalized Economy, Society and Information Management (245-252). Linz: Trauner Verlag.
Prof.(FH) Dipl.-Ing. Dr. Roger Hage
Programme Director Digital Business Innovation and Transformation
Programme Director Digital Business Innovation and Transformation
Prof.(FH) Dipl.-Ing. Dr. Roger Hage
Core Competencies
- Digital Transformation
- International Business Development
- R Programming

Prof.(FH) Mag. Gerhard Kormann-Hainzl
Professor Department of Science and Technology
Institute Digitalisation and Informatics
+43 2732 802 381
[email protected]
IMC Campus KremsIMC Campus Trakt G
Digital Business Transformation such as digital business model innovation, digitalization processes innovation, digital leadership
Risk management, international trade and finance and alternative financial instruments such as crowd funding
Strategic Management and Internationalisation
Export-oriented Management
Bachelor of Arts in Business / full-time
Digital Business Innovation and Transformation
Master of Arts in Business / part-time
Informatics
Bachelor of Science in Engineering / full-time
Dataskop – Sensor-Based Data Economy in Niederösterreich
Project Leader, Department of Science & Technology
Digital Innovation Hub OST (DIHOST)
Project Leader, Department of Science & Technology
Mixed Reality Based Collaboration for Industry (MRBC4i)
Project Leader, Department of Science & Technology
Digitales Kompetenzmonitoring in Produktionsunternehmen
Department of Business
Enterprise 4.0 – Erfolg im digitalen Zeitalter
Project Leader, Department of Business
Digital Business Transformation
Project Leader, Department of Business
Hage R., Lovasz-Bukvova, H., Hopp, M., Hölzl, M., Kormann-Hainzl G., Reiner, M., Dhungana, D. (2021): Agile Approach for E-Learning in Digital-Leadership Training for Small and Medium Enterprises. In Softic, S.K., Read, T. (Hrsg.), Proceedings of the EDEN Annual Conference: Lessons Learned from the Pandemic. Madrid: EDEN.
Kormann-Hainzl, G., Lovasz-Bukvova, H., Hoelzl, M. (2021): Are smarts villages just smaller smart cities? Call for a region-type-specific approach to the smartification of communities. In Hemker, T., Müller-Török, R., Prosser, A., Sasvari, P., Scola, D., Urs, N. (Hrsg.), Central and Eastern European e/Dem and e/Gov days 2021. Conference Proceedings (115-126). virtual: Facultas.
Moser, T., Hohlagschwandtner, M., Kormann-Hainzl, G., Pölzlbauer, S., Wolfartsberger, J. (2019): Mixed reality applications in industry: challenges and research areas. Software Quality: The Complexity and Challenges of Software Engineering and Software Quality in the Cloud, 338: 95-105.
Doi: https://doi.org/10.1007/978-3-030-05767-1_7
Schwand, C., Kormann, G., Pacher, F., Bartz, M. (2018): Digitale Transformation: Mehrwert durch Vernetzung und Austausch in Multi-Projekt-Umgebungen durch strategische Partnerschaften. In Fachhochschule Salzburg GmbH (Hrsg.), Online Tagungsband FHK Forschungsforum 2018 (1-9). Salzburg: FFH.
Hammerschmid, S., Kormann, G., Moser, T., Reiner, M. (2017): A conceptual Mixed Realities (AR/VR) capability maturity model – with special emphasis on implementation. In Stolfa, J., Stolfa, S., O'Connor, R., Messnarz, R. (Hrsg.), Software and Services Process Improvement. EuroSPI 2017. Communications in Computer and Information Science, vol 748 (372-377). Ostrava: Springer, Cham.
Doi: https://doi.org/10.1007/978-3-319-64218-5_31
Kormann, G., Hanus, F., & Moser, T. (2016): Autonomisierung von Produktionsprozessen–Theorie, Anwendung und Werkzeuge. In Fachhochschule des BFI Wien (Hrsg.), Online-Tagungsband FHK Forschungsforum 2016 (eFFH2016-112-2). Wien: FFH.
Schwand, C., Kotek, K., Kormann, G. (2016): GW St. Pölten – Industriell. Integrativ. Innovativ. In Wagner, U., Reisinger, H., Schwand, C. (Hrsg.), Fallstudien aus der österreichischen Marketingpraxis 7 (99-108). Wien: Facultas.
Kormann, G., Andersson, S., Moser, R., & Wictor, I. (2015): Will Digital Transformation become a Game Changer in the Field of Internationalisation Research?. In Department of Management, Birkbeck, University of London (Hrsg.), 19th McGill International Entrepreneurship Conference. International Entrepreneurship in a Multi-Speed Global Economy: Opportunities and Challenges (50). London: McGill.
Kormann, G. (2013): Porsche - A company of its own?. In Wagner, U., Reisinger, H., Schwand, C. (Hrsg.), Fallstudien aus der österreichischen Marketingpraxis (67-74). Wien: Facultas.
Kormann, G., Schuneritsch, W., Bartz, M., Kotek, K., Schwand, C. (2011): Risikoadjustierte Entscheidungsmodelle im Servicebereich - ein Mythos trifft auf Best Practice. In FH Campus Wien (Hrsg.), Tagungsband 5. Forschungsforum der österreichischen Fachhochschulen, 27.-28. April 2011 (-). Wien: FFH.
Schwand, C., Berger, C., Hartbach, S., Kleiss, D., Kotek, K., Kormann, G., Schachner, M., & Neuherz, C. (2011): Grundelemente der Verkaufsraumgestaltung: Die Suche nach dem Stern. In FH Campus Wien (Hrsg.), Tagungsband 5. Forschungsforum der österreichischen Fachhochschulen, 27.-28. April 2011 (-). Wien: FFH.
Prof.(FH) Mag. Gerhard Kormann-Hainzl
Professor Department of Science and Technology
Dr. Rubén Ruiz Torrubiano
Professor Department of Science and Technology
Institute Digitalisation and Informatics
+43 2732 802 302
[email protected]
IMC Campus KremsIMC Campus Trakt G
Combinatorial optimization
Machine learning / data mining
Systems architecture
Unternehmensführung
Bachelor of Arts in Business / full-time
Informatics
Bachelor of Science in Engineering / full-time
Digital Business Innovation and Transformation
Master of Arts in Business / part-time
BRfit für Künstliche Intelligenz
Department of Business
VRWalk
Department of Science & Technology
Dataskop – Sensor-Based Data Economy in Niederösterreich
Department of Science & Technology
Dhungana, D., Haselböck, A., Ruiz-Torrubiano, R., Wallner, S. (2022): Variability of safety risks in production environments. In Alexander Felfernig et. al. (Hrsg.), SPLC '22: Proceedings of the 26th ACM International Systems and Software Product Line Conference (178-187). Graz, Austria: Association for Computing Machinery.
Doi: https://doi.org/10.1145/3546932.3547074
Ruiz-Torrubiano, R., Suárez, A. (2015): A memetic algorithm for cardinality-constrained portfolio optimization with transaction costs. Applied Soft Computing, 36: 125-142.
Doi: https://doi.org/10.1016/j.asoc.2015.06.053
Ruiz-Torrubiano, R., Suarez, A. (2011): The TransRAR crossover operator for genetic algorithms with set encoding. In Ruiz-Torrubiano, R., Suarez, A. (Hrsg.), Proceedings of the 13th annual conference on Genetic and evolutionary computation (489-496). New York: Association for Computing Machinery.
Doi: https://doi.org/10.1145/2001576.2001644
Ruiz-Torrubiano, R., Suarez, A. (2010): Hybrid approaches and dimensionality reduction for portfolio selection with cardinality constraints. IEEE Computational Intelligence Magazine, 5(2): 92-107.
Doi: https://doi.org/10.1109/MCI.2010.936308
Ruiz-Torrubiano, R., García-Moratilla, S., Suárez, A. (2010): Optimization problems with cardinality constraints. In Ruiz-Torrubiano, R., García-Moratilla, S., Suárez, A. (Hrsg.), Optimization problems with cardinality constraints (105-130). Berlin Heidelberg: Springer.
Doi: https://doi.org/10.1007/978-3-642-12775-5_5
Ruiz-Torrubiano, R., Suárez, A. (2009): A hybrid optimization approach to index tracking. Annals of Operations Research, 166(1): 57-71.
Doi: https://doi.org./10.1007/s10479-008-0404-4
Ruiz-Torrubiano, R., Suárez, A. (2007): Use of heuristic rules in evolutionary methods for the selection of optimal investment portfolios. In IEEE (Hrsg.), IEEE. Singapore: IEEE.
Doi: https://doi.org/10.1109/CEC.2007.4424474
Moral-Escudero, R., Ruiz-Torrubiano, R., Suárez, A. (2006): Selection of optimal investment portfolios with cardinality constraints. In Moral-Escudero, R., Ruiz-Torrubiano, R., Suárez, A. (Hrsg.), 2006 IEEE International Conference on Evolutionary Computation (2382-2388). New York: IEEE.
Doi: https://doi.org/10.1109/CEC.2006.1688603
Hernández-Lobato, D., Hernández-Lobato, J., Ruiz-Torrubiano, R., Valle, A. (2006): Pruning adaptive boosting ensembles by means of a genetic algorithm. In Hernández-Lobato, D., Hernández-Lobato, J., Ruiz-Torrubiano, R., Valle, A. (Hrsg.), International Conference on Intelligent Data Engineering and Automated Learning (322-329). Berlin Heidelberg: Springer.
Doi: https://doi.org/10.1007/11875581_39
Dr. Rubén Ruiz Torrubiano
Professor Department of Science and Technology
Prof.(FH) Dipl.-Ing. Dipl.-Wirtsch.-Ing. Michael Bartz
Professor Department of Business
Institute International Trade and Sustainable Economy
+43 2732 802 392
[email protected]
IMC International Campus Piaristengasse
Digital Business Transformation
New World of Work
Agile Organisations and Project Management
Management von Gesundheitsunternehmen
Master of Arts in Business / part-time
Export-oriented Management
Bachelor of Arts in Business / full-time
Digital Business Innovation and Transformation
Master of Arts in Business / part-time
International Business and Economic Diplomacy
Master of Arts in Business / part-time
Management
Master of Arts in Business / part-time
Guide für Mobiles Arbeiten
Project Leader, Department of Business
MBIT New World of Work Erfolgsmessung
Project Leader, Department of Business
New World of Work: Erfolgsmessung Porsche Informatik GmbH
Project Leader, Department of Business
Bartz, M., Schwand, C. (2021): Spielregeln für Mobiles Arbeiten (ISBN 978-3950467628). Seattle: KDP.
Bartz, M., Borenich, J., Schmutzer, T. (2021): Hybrides Arbeiten & Digitalisierung. Warum Homeoffice erst der Anfang war und kein Stein auf dem anderen bleibt. Seattle: Amazon KDP.
Bartz, M. (2020): Leitfaden für die Entwicklung von organisatorischen Spielregeln für mobiles Arbeiten und ihre nachhaltige Implementierung. Wien: BMA.
Bartz, M., Danninger, O., Heidler, P., Hemetsberger, M., Kitzberger, D., Koren, K., Stampfl-Walch, D. (2020): Homeoffice & Videokonferenzen. Was bleibt nach der Krise und wie?. St. Pölten: Amt der NÖ Landesregierung.
Bartz, M. (2018): Digital Transformation Toolbox Part 1. Seattle: Amazon KDP.
Schwand, C., Kormann, G., Pacher, F., Bartz, M. (2018): Digitale Transformation: Mehrwert durch Vernetzung und Austausch in Multi-Projekt-Umgebungen durch strategische Partnerschaften. In Fachhochschule Salzburg GmbH (Hrsg.), Online Tagungsband FHK Forschungsforum 2018 (1-9). Salzburg: FFH.
Bartz, M., Schwand, C. (2017): Preis der Freiheit – Nutzen von Spielregeln für Mobil- Flexibles Arbeiten. In IMC Fachhochschule Krems GmbH (Hrsg.), Online Tagungsband FHK Forschungsforum 2017 (899-905). Krems: FFH.
Bartz, Michael, Gnesda, Andreas, Schmutzer, Thomas (Hrsg.) (2017): Unternehmen der nächsten Generation. Berlin: Springer.
Bartz, M., Schmutzer, T. (2014): New World of Work. Warum kein Stein auf dem anderen bleibt. Wien: Linde.
Kormann, G., Schuneritsch, W., Bartz, M., Kotek, K., Schwand, C. (2011): Risikoadjustierte Entscheidungsmodelle im Servicebereich - ein Mythos trifft auf Best Practice. In FH Campus Wien (Hrsg.), Tagungsband 5. Forschungsforum der österreichischen Fachhochschulen, 27.-28. April 2011 (-). Wien: FFH.
Prof.(FH) Dipl.-Ing. Dipl.-Wirtsch.-Ing. Michael Bartz
Professor Department of Business

Application and admissions – the next steps

You've found a course that's a perfect fit? Great – you’ve already taken the most important step! We’ve put together an overview to guide you through the next steps.

What are the admission requirements for master programmes?

To qualify for a master programme, you must have completed a bachelor degree – with a workload of at least 180 ECTS and lasting at least six semesters – in a related subject, or hold an equivalent degree from a recognised Austrian or foreign higher education institution.

If your undergraduate studies are not sufficiently relevant, for instance if you’ve completed a degree in an unrelated subject, your qualifications will be assessed after we have received your completed application.

Information about accepted previous academic qualifications

What kind of previous degrees are acceptable?

Basically, you need to have completed a business or technical undergraduate degree, or one which combined the two.

What proof of your language skills is required for our English-language master degree programme?

If English is your first language, or if you’ve already completed an undergraduate degree which was taught entirely in English, you don’t need any additional evidence of your English proficiency.

Otherwise, you’ll need to submit one of the following certificates:

IELTS Academic – minimum score of 7.0
Cambridge C1 Advanced (formerly CAE)

Language certificates must be no more than two years old and can be submitted by the start of the degree programme. If you submit it after your application, upload a copy of your proof of registration for the English language exam you are going to take along with your application.

Do you still need to earn a certificate? At the IMC University of Applied Sciences you can complete both an IELTS preparatory workshop as well as the IELTS certificate. If you are interested, please contact our language services or directly sonja.berger(at)fh-krems.ac.at.

Application interview

Everything revolves around the students on our Master degree programmes. That’s why we’d like to get to know you personally.

As part of the online application you will have to write a statement of motivation. Predefined questions about your motivation can be found in the online application. In your answers, which have to be entered in the provided input fields of the online application, you deal with the questions and explain your motivation to study the selected Master degree programme

Your statement of motivation and your CV (curriculum vitae) form the basis for your application interview. The admission interview is a one-to-one interview, usually with the degree programme director.
In addition to getting to know you personally, your motives for the Master degree programme will be discussed, as well as your professional background and the skillset you have acquired so far. Special attention will be paid to your previous academic and professional experience, your methodological and language skills and your general suitability with regard to your intended Master degree programme.

The application interview is held in the language of instruction of the degree programme and can take place online via Microsoft Teams or in presence.

Interview dates

There is usually a selection of dates to choose from, with quotas allocated for each date. You can select a preferred date and time slot for your admission interview during the online application process. In order to still benefit from the full selection of dates, we recommend that you submit your application in good time.

Get an overview of the dates for your programme.

No dates available at the moment.

After you have successfully completed your online application, your application will be checked for completeness and correctness. As soon as this process is completed, we will inform you by e-mail and confirm the date for your admission interview. We will send you the Microsoft Teams Meeting Link in a separate e-mail a few days before the application interview date.

Application for the next study year possible from 01/12/2022

Application deadline for EU nationals	15/05/2023
Application deadline for non-EU nationals	15/04/2023

You've decided for one of our degree programmes? First of all: congratulations and thank you for choosing us! We’ll be happy to guide you step-by-step through your online application.

Details

You would like to plan ahead and would like to know when your degree programme starts? Here you will find the answer!

Details

Questions about the degree programme?

Prospective Student Advisory Service

Do you have questions regarding the entry requirements, the admission procedure and more? Our Prospective Student Advisory Service is happy to help.

+432732802222

[email protected]

Ask a Student

Join our Facebook group: Direct your questions to our students and get first-hand accounts about studying at IMC Krems.

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Digital Business Innovation and Transformation master degree programme

Become a change agent! After your master degree, you'll lead your company into the future. You'll be able to coordinate and direct digital transformations, no matter what the industry. Because the future is digital.

Be the change you want to see in companies!

New: Optimal compatibility thanks to virtual component

Room for your individual interests

International orientation

Certifications

A formula for success: theoretical knowledge + practical experience

1. The business basics

2. The core topics

3. The practical training

Curriculum

Business Analysis & Strategy Development

Digital Economy & Business Models

Innovation Management

Digital Technologies

Business Statistics & Data Science

Self-directed Learning I: Learning agreement

Digital Business Development

Digital Process Management

Process Automation

Project & Change Management

Innovation Lab

IT, Data & Security Management

Self-directed learning II: Learning methods

Human Development and Leadership in the Digital Age

Ethics in Leadership

Corporate Risk Management

Legal Awareness

Software Engineering and Quality Management

Data Analytics

Research Methods

Self-directed Learning III: Learning portfolio

Academic Coaching Colloquium

Master Thesis

Master Exam

Core topics

Digital transformation

Opportunities of digitalisation

The power of data

Innovation 4.0

Digitalisation calls for change

Embedding innovation in your corporate culture

Newsletter & additional information

Newsletter & brochures

Career options

Opinions: Digital Business Innovation and Transformation

Our team

Prof.(FH) Dipl.-Ing. Dr. Roger Hage

Programme Director Digital Business Innovation and Transformation

Core Competencies

Prof.(FH) Mag. Gerhard Kormann-Hainzl

Dr. Rubén Ruiz Torrubiano

Prof.(FH) Dipl.-Ing. Dipl.-Wirtsch.-Ing. Michael Bartz

Application and admissions – the next steps

What are the admission requirements for master programmes?

What kind of previous degrees are acceptable?

What proof of your language skills is required for our English-language master degree programme?

Application interview

Interview dates

Questions about the degree programme?

Prospective Student Advisory Service

Ask a Student

Similar degree programmes

International Business and Economic Diplomacy

Marketing

Management

Umwelt- und Nachhaltigkeitsmanagement