Management & Society

Digital Transformation

Digital Transformation

The research area "Digital Transformation" complements the study programs of Management, Communication & IT and Digital Business & Software Engineering respectively in the fields of applied research and development of practice-oriented solutions for digitization and their comprehensive integration into practice. We work on technical, social, organisational and individual aspects in an interdisciplinary way.

In the context of digital transformation, the secure, analytical handling of data, the interaction of people with technical systems, the design of new work environments, and the adaptation of work and production processes and their control in real as well as virtual worlds are essential for us.

 

Data & Analytics

Large amounts of data generated from a wide variety of data sources (e.g. IoT, etc.) can be used as a basis for decisions, improvement of products and processes and for the development of new business models. Data & Analytics deals with the storage, preparation, analysis and visualization of data using suitable system architectures.

  • Implementation of concrete projects and tasks in companies
  • Integration of the Internet of Things as an essential data source
  • Visualization of data (e.g. dashboards)
  • Application of modern tools (e.g. from the field of artificial intelligence, for decision making)
  • Further development of existing IT system architectures

IT Security & Privacy

IT security and privacy make a contribution to the secure handling of data and information systems, which are becoming increasingly relevant in the course of increasing digitalization.

  • Security of machine learning
  • Network security
  • Encryption technologies
  • Multimedia security

Technology Interaction & Innovation

Technology Interaction & Innovation deals with the interaction of people and technology in the professional and private environment. In the field of innovation research, the focus is on the methodology of Design Thinking.

  • Experience and usability of social and web-based services
  • Evaluation of the acceptance of assistance technologies
  • Study of trust in intelligent systems

Operational Excellence & Agile Governance

The improvement of business decisions and the establishment of stable processes in the company - taking into account rapidly changing technologies, frameworks and the regulatory environment - are essential design fields of operational excellence.

  • Internet of Things
  • Smart production
  • Data evaluation of large amounts of data
  • Audits
  • Compliance and IT governance of agile action

Next World of Work / Virtual & Augmented Reality

Next World of Work / Virtual & Augmented Reality unites different topics in the context of a changing world of work.

  • Creation and agility of jobs
  • Life-long learning
  • Talent diversity & innovativeness
  • Organizational design
  • Leadership
  • Innovative technologies e.g. Virtual Reality (VR) & Augmented Reality (AR)
Contact
Prof. Dr. Peter J. Mirski | Head of Department & Studies Bachelor's program Management, Communication & IT
Prof. Dr. Peter J. Mirski Head of Department & Studies

If you have any questions regarding this research area, please contact us:
digitaltransformation@mci.edu


Prof. Dr. Peter J. Mirski | Head of Department & Studies Bachelor's program Management, Communication & IT
Prof. Dr. Peter J. Mirski Head of Department & Studies
Mag. Gundula Glowka | Lecturer Bachelor's program Management, Communication & IT
Mag. Gundula Glowka Lecturer +43 512 2070 - 3534
 Susann Kruschel, MSc | Teaching & Research Assistant Bachelor's program Management, Communication & IT
Susann Kruschel, MSc Teaching & Research Assistant +43 512 2070 - 3530
Prof. Dr. Stephan Schlögl | Human-Centered Computing Bachelor's program Management, Communication & IT
Prof. Dr. Stephan Schlögl Human-Centered Computing +43 512 2070 - 3535
Prof. Dr. Reinhard Bernsteiner | Information Systems & Smart Technologies Master's Program Management, Communication & IT
Prof. Dr. Reinhard Bernsteiner Information Systems & Smart Technologies +43 512 2070 - 3532
 Aleksander Groth, PhD | Lecturer Bachelor's program Management, Communication & IT
Aleksander Groth, PhD Lecturer +43 512 2070 - 3523
Prof. Dr. Christian Ploder | Operational Excellence Bachelor's program Management, Communication & IT
Prof. Dr. Christian Ploder Operational Excellence +43 512 2070 - 3536
Prof. Dr. Pascal Schöttle | IT Security & Machine Learning Bachelor's program Digital Business & Software Engineering
Prof. Dr. Pascal Schöttle IT Security & Machine Learning +43 512 2070 - 4332
 Andrea Corradini, PhD | Senior Lecturer Bachelor's program Digital Business & Software Engineering
Andrea Corradini, PhD Senior Lecturer +43 512 2070 - 4333
Assoc. Prof.  Matthias Janetschek, PhD | Software Engineering Bachelor's program Digital Business & Software Engineering
Assoc. Prof. Matthias Janetschek, PhD Software Engineering +43 512 2070 - 4331
 Magdalena Posch, BA MA MA | Assistant & Project Manager Bachelor's program Management, Communication & IT
Magdalena Posch, BA MA MA Assistant & Project Manager +43 512 2070 - 3524
Prof. Dr. Teresa Spieß | Organizational Psychology & Change Management Bachelor's program Management, Communication & IT
Prof. Dr. Teresa Spieß Organizational Psychology & Change Management +43 512 2070 - 3525
 Thomas Dilger, BA MA | Senior Lecturer Bachelor's program Management, Communication & IT
Thomas Dilger, BA MA Senior Lecturer +43 512 2070 - 3537
Prof. Dr. Dietmar Kilian | Digitalization & Sales Bachelor's program Business & Management
Prof. Dr. Dietmar Kilian Digitalization & Sales +43 512 2070 - 3533
 Arno Rottensteiner, BA MA | Doctoral Student Bachelor's program Management, Communication & IT
Arno Rottensteiner, BA MA Doctoral Student +43 512 2070 - 3526
Dr. Willemijn van Kooten | Teaching & Research Assistant Bachelor's program Digital Business & Software Engineering
Dr. Willemijn van Kooten Teaching & Research Assistant +43 512 2070 - 4322

Smart Inclusion - supporting the independence of people with disabilities using Smart Glasses
Duration:
2022 - 2023

Project Lead:
Magdalena Posch, BA MA MA

Team:
Michael Freudenthaler

Anna-Karina Sailer

Franziska Scheele

Description:
In the "Smart Inclusion" project, augmented reality is used in the form of smart glasses. It is evaluated to what extent these can be used by people with disabilities to strengthen their individual skills and resources for activities of daily living. The research process will be cooperated and supported by Lebenshilfe Tirol, which is a social institution that offers its residents the opportunity to live and work independently in shared apartments.

AI4VET4AI - AI-powered Next Generation of VET
Duration:
2023 - 2027

Project Lead:
FH-Prof. Dr. Stephan Schlögl

Team:
FH-Prof. Dr. Peter J. Mirski

FH-Prof. Dr. Christian Ploder

Annika Gnädinger, B.Sc.

FH-Prof. Dr. Reinhard Bernsteiner

Description:
Science is clear: Artificial Intelligence will be the defining development of the 21st century. Experts estimate that due to the rise of AI within only 2 decades aspects of daily human life will be unrecognizable. The influence of AI is about to challenge the very organizing principles of our economic and social order. It can generate unprecedented wealth, revolutionize medicine and education, but it can bring existential perils for life as we know it. This makes the EC2020 report that the EU is lagging behind USA and Asia in AI-adoption and development all the more worrying. Among many reasons behind that, the lack of skilled work force is definitively one of the more prominent ones. The objective of AI4VET4AI is to contribute to the digital transformation of the EU labor market by adding new innovative teaching content and methods to VET curricula across 11 European countries and 18 EU NUTS2 regions, in order to support the growth of AI-skilled workers. We start from the ground up: we investigate the most potent sectors for AI-deployment in our 17 regions, and for those sectors, in close cooperation with enterprises and their cluster organizations we create 14 MOOCs and TT materials that can easily be implemented in VET programs (IVET and CVET). We organize 11 innovative AI VET campuses and 7 VET innovation AI incubators, in which VET learners hone their creative and entrepreneurial skills. We use project activities to connect partners closely and to raise awareness of the AI potential in our regions among representatives of public and private sector, as well as civil society. In turn, this helps us to create a joint and active platform of concerned EU citizens and institutions, interested, informed and motivated in supporting AI development further -- this being the basis of our ambitious CoVE - Center of Vocational Excellence, which aims to attract many more institutions (HEIs, VETs, companies, agencies, individuals) in its pursuit of sustainable, inclusive and just AI-powered future for all.

Project homepage:
https://www.ai4vet4ai.eu/

Prototypical Implementation of an intelligent tutoring system for introductory programming courses
Duration:
2022 - 2024

Project Lead:
Assoz. FH-Prof. Matthias Janetschek, PhD

Description:
The shortage of skilled workers in the field of software development is damaging competitiveness in Austria as a business location. For this reason, universities are targeting offerings at working professionals, often using blended learning concepts. This involves integrating online and face-to-face teaching in order to offer students increased flexibility. Although blended learning concepts have already proven to be effective, students are confronted with challenges arising from the online component of blended learning approaches on the one hand and the subject matter of programming on the other hand. An Intelligent Tutoring System that provides students with individualized, immediate, and instructive feedback is proposed as a solution.

Smartify TT
Duration:
2022 - 2024

Project Lead:
FH-Prof. Dr. Stephan Schlögl

Team:
Assoz. FH-Prof. Matthias Janetschek, PhD

Andrea Corradini, PhD

Description:
The TensionTerminator (TT) is a certified medical device that helps users relieve tension pain in the back, arm/shoulder belt and neck area effectively and sustainably in a short time by means of self-application. The TT is specially developed for workplace contexts to offer a low-threshold opportunity for employees to relieve their tension pain directly at the workplace. The "smartification" of the TT is intended to allow for an additional level of interaction with users, both on an individual and an organizational level. Thus, the following data will be collected via sensors: (1) force impacts and movement speeds, (2) component function checks, and (3) tracking of the type and frequency of use. Furthermore, in connection with a smartphone app, the patophysiological categorization of the tension situation and its change through the use of the TT will be recorded. The collected data will be processed on the device using a machine learning (ML) based system in order to recognize the type of application, misapplication, sensor errors, etc., to increase the quality of the data obtained, and thus to make subsequent correction loops unnecessary. In real time, this should provide users feedback on optimal and thus effective self-therapy. The aim is to achieve the best possible improvement in the pain and tension situation. Furthermore, the safety of use is to be increased when, for example, indications and warnings are issued in the event of excessive force application, excessive rolling speed, unfavorable force application or improper use. Gamification concepts based on this should encourage employees to use the equipment correctly and prophylactically. Self-motivation is to be increased in connection with notifications, individual leaderboards, linkage with the perceived tension situation, or proof of the improvement in mobility, etc. Furthermore, the sustainable use of the TT provided and its effect on the health and well-being of the employees will be evaluated through ongoing monitoring.

Game Over Eva(sion): Securing Deep Learning with Game Theory
Duration:
2019 - 2023

Project Lead:
FH-Prof. Dr. Pascal Schöttle

Team:
Florian Merkle, BSc MA

Description:
The project "Game Over Eva(sion): Securing Deep Learning with Game Theory" aims to protect deep learning classifiers against targeted attacks. Deep learning classifiers are not only popular in scientific research but are also more and more adapted to the daily life, as self-driving cars, smartphones, and digital personal assistants use these kind of algorithms. Unfortunately, recent research has shown that almost all deep learning classifiers are vulnerable to so-called evasion attacks. In an evasion attack, an attacker can slightly modify a benign object and by this achieves a misclassification with a very high probability. The robustness of deep learning classifiers to these attacks is an open problem. We will model the competition of an attacker who is able to launch an evasion attack and the defender who wants to train a deep learning classifier that is robust against such an attack with means of game theory. In a first step, we will analyze which concepts of other research areas, such as adversarial classification, can be translated to the domain of secure deep learning. Then, we will develop a game-theoretic model that captures all relevant aspects and dependencies between the attacker's and the defender's strategies. In the course of the project, we expect the first theoretically well-founded results on the achievable security of deep learning classifiers in the presence of evasion attacks. Furthermore, we will evaluate existing countermeasures against evasion attacks to gain insights about their optimality when facing a strategic attacker. Finally, we want to implement the key properties from out theoretical models in a practical deep learning classifier. We will compare our classifier against other state-of-the-art classifiers in terms of robustness against evasion attacks and accuracy on benign input objects. By this, we can validate if it is possible to make deep learning classifiers robust against evasion attacks. The expected results of the project will enable us to judge if deep learning classifiers are suitable for scenarios where an attacker has incentives to explicitly fool them, i.e., security-critical areas and widespread consumer products.

Secure Machine Learning Applications with Homomorphically Encrypted Data
Duration:
2021 - 2024

Project Lead:
FH-Prof. Dr. Pascal Schöttle

Team:
Martin Nocker, MSc

Carina Kollmitzer

Description:
SMiLe examines the conditions under which solutions using homomorphic encryption are suitable for harnessing the potential of sensitive data for machine learning. The potential of the machine learning techniques is evaluated through two use cases, dealing with employee segmentation and predictive maintenance, respectively. SMiLe contributes to the establishment of a cooperative-creative ecosystem in which various actors interact trustingly, symbiotically, and independently and implement previously unimaginable solutions in which not only data protection and security are guaranteed, but also previously unused potential of data can be exploited. The project will extend existing platforms to provide solutions that enable the creation and use of machine learning models using homomorphically encrypted data.

Advancing careers in mathematics and computer science Heidelberg Laureate Forum Foundation Project 2022+ in cooperation with MCI
Duration:
2023 - 2025

Project Lead:
FH-Prof. Dr. Peter J. Mirski

Team:
Valentina Huter, BA

Susann Kruschel, MSc

FH-Prof. Dr. Dietmar Kilian

Description:
HLFF Inspiring Minds is a collaboration between the Heidelberg Laureate Forum Foundation and the MCI - The Entrepreneurial School® and is dedicated exclusively to supporting all HLF alumni in developing their personal career paths in mathematics and computer science. Through expert mentoring, coaching and amplified by other activities, bundled on the HLFF Inspiring Minds platform, some of the most aspiring young talents get the unique opportunity to interact and build meaningful relationships with laureates and experts from academia, business and industry.

Smart Technology Monitoring II
Duration:
2023 - 2024

Project Lead:
FH-Prof. Dr. Stephan Schlögl

Team:
Roman Blaas, BSc

Assoz. FH-Prof. Matthias Janetschek, PhD

FH-Prof. Dr. Oliver Som

Description:
The Smart Technology Monitoring II project will implement the prototype of an ontology for storing, processing and querying data from partially structured and unstructured data sources. The goal of this project is to test the feasibility of an innovative knowledge management platform that combines information from different technology data sources and must therefore be able to grow and change dynamically. The ontology prototyped in this project is intended to represent an MVP for the core of this software solution, on which future projects can be based.

Smart Villages / Regionalmanagement Wipptal
Duration:
2020 - 2025

Project Lead:
FH-Prof. Dr. Christian Ploder

Team:
Lukas Heschl, BA MA

Description:
In the course of an Interreg project "SMART VILLAGES Wipptal" set up for this purpose, a common understanding for a regional portal is to be developed for the communities located in the region (northern South Tyrol with 12 communities and southern South Tyrol with 6 communities). The sub-goal offered by MCI is to survey the logical structure, usability, possible integration options and a specification of the communication platform for the future according to scientific findings and to elaborate it together with the stakeholders.

Ready, Immerse, Go!
Duration:
2023 - 2025

Project Lead:
FH-Prof. Dr. Peter J. Mirski

Team:
Aleksander Groth, PhD

Description:
The project aims to experiment with virtual reality for the training and development of specific competences of students, trainees and apprentices who wish to undertake international mobility or who simply want to try out these experiences virtually. A planned VR platform will host immersive virtual scenarios and other virtual activities, which will allow users to acquire skills to face these new situations that may cause them fear and rejection, weighing negatively on their decision to leave.


  • Baumhauer, T., Schöttle, P., & Zeppelzauer, M. (2022). Machine unlearning: linear filtration for logit-based classifiers. Machine Learning. https://doi.org/10.1007/s10994-022-06178-9
  • Schadelbauer, L., Schlögl, S., & Groth, A. (2023). Linking Personality and Trust in Intelligent Virtual Assistants. Multimodal Technologies and Interaction, 7(6). https://doi.org/10.3390/mti7060054
  • Höller, S., Dilger, T., Spiess, T., Ploder, C., & Bernsteiner, R. (2024). Awareness of Unethical Artificial Intelligence and its Mitigation Measures. European Journal of Interdisciplinary Studies, 15(2), 67–89. doi: https://doi.org/10.24818/ejis.2023.17
  • Klocker, F., Bernsteiner, R., Ploder, C., & Nocker, M. (2023). A Machine Learning Approach for Automated Cost Estimation of Plastic Injection Molding Parts. Cloud Computing and Data Science, 4(2), 87–111. https://doi.org/10.37256/ccds.4220232277
  • Oberascher, L., Ploder, C., Spiess, J., Bernsteiner, R., & Van Kooten, W. (2023). Data Storytelling to Communicate Big Data Internally – a Guide for Practical Usage. European Journal of Management Issues, 31(1), 27–40. https://doi.org/10.15421/192303
  • Brinkschulte, L., Schlögl, S., Monz, A., Schöttle, P., & Janetschek, M. (2022). Perspectives on Socially Intelligent Conversational Agents. Multimodal Technologies and Interaction, 6(8). https://doi.org/10.3390/mti6080062
  • Amore, E., Dilger, T., Ploder, C., Bernsteiner, R., & Mezzenzana, M. (2023). Leverage the COBIT 2019 Design Toolkit in an SME Context: A Multiple Case Study. KnE Social Sciences, 8(1), 73–101. https://doi.org/10.18502/kss.v8i1.12636
  • Dilger, T., Bernardi, S., Ploder, C., Spieß, T., & Bernsteiner, R. (2023). Cash in the Trash? An Austrian Perspective on Mobile Payment Adoption. KnE Social Sciences, 8(1), 375–398. https://doi.org/10.18502/kss.v8i1.12657
  • Moedt, W., Bernsteiner, R. C., Hall, M., & Fruhling, A. L. (2022). Enhancing IoT Project Success through Agile Best Practices. ACM Trans. Internet Things. https://doi.org/10.1145/3568170
  • Khazanchi, D., Bernsteiner, R., Dilger, T., Groth, A., Mirski, P. J., Ploder, C., Schlögl, S., & Spieß, T. (2022). Strategies and best practices for effective eLearning: lessons from theory and experience. Journal of Information Technology Case and Application Research, 1–13. https://doi.org/10.1080/15228053.2022.2118992

  • Dilger, T. (2023, June 13). Awareness of unethical artificial intelligence and its mitigation measures [Conference presentation]. EBEEC 2023, Chios, Greece.
  • Corradini, A. (2023, November 22). A Machine Learning Approach to Predict Cyclists’ Functional Threshold Power [Conference presentation]. IDEAL 2023, Évora, Portugal.
  • Bernsteiner, R. (2023, November 28). Students’ Views on the Internet of Things in Engineering Education [Conference presentation]. ICL 2023, Madrid, Spain.
  • Mirski, P. J. (2023, March 15). The Value of a Skills-Based Approach for Education and Employability [Panel presentation]. D-DIALOGUES 2023, online.
  • Schöttle., P. (2023, October 10). Einblicke in KI Initiativen und Projekte bei INNIO [Invited talk]. Industriellen Vereinigung Tirol - KI in der Tiroler Industrie, Innsbruck, Austria.
  • Schlögl, S. (2023, September 21). Interacting with (Un)-Social Machines – The Challenge of Human-AI Companionship [Invited talk]. DISA 2023, Kosice, Slovakia.
  • Rottensteiner, A. (2023, September 13). Development and Evaluation of a Multi-Modal Mentoring Framework for Supporting Career Paths in Mathematics and Computer Science [Conference presentation]. SAP ACC 2023, Munich, Germany.
  • Ploder, C. (2023, September 13). How to Train and Experience IoT Implementation and Data Collection [Conference presentation]. SAP ACC 2023, Munich, Germany.
  • Bernsteiner, R. (2023, July 26). The Use of No-code Platforms in Startups [Conference presentation]. KMO 2023, Bangkok, Thailand.
  • Spieß, T. (2023, June 26). Learning Styles, Technostress & Blended Learning – Implications for the Educational Model of the Future [Conference presentation]. END 2023, Lisbon, Portugal.