Deep Learning has had tremendous success in business and science (LeCun, 2015, Schmidhuber, 2015). The paper by (Krizhevsky, 2012) is widely accepted to be the key paper for this success, as they were able to substantially decrease the error on ImageNet Large Scale Visual Recognition Challenge 2012 (ILSVRC-2012), an image classification task, by using a convolutional neural network. As a consequence, deep learning has been applied to predictive problems in business process management as well – for example (Nguyen, 2020), (Taymouri, 2021), (Park and Song, 2019), (Tax, 2017), (Weinzierl, 2020) and (Obodoekwe, 2022).

The objective of this thesis is to conduct a comprehensive structured literature review (SLR) on the performance evolution of deep learning in business process management. Within this (SLR) we want to understand whether, and to which extend, deep learning leads to performance gains compared to other non deep learning methods. In other words, the comparison between deep learning and non deep learning is of particular interest. In the thesis, the student will systematically characterise the data sets used, the methods used for in-KG tasks, and how the performance has changed over time, and to which extend deep learning has improved, or not, the performance. The work of (Neu, 2021) is an excellent starting point for the thesis. The student might also be asked to give her/his opinion on the current state of the art.

Supervisor: Stefan Bachhofner

Resources

STAT 157, Introduction to Deep Learning, UC Berkley, courses.d2l.ai/berkeley-stat-157/index.html

6.S191, Introduction to Deep Learning, Massachusetts Institute of Technology, introtodeeplearning.com

Dive into Deep Learning, d2l.ai

CS231n, Convolutional Neural Networks for Visual Recognition, Stanford University, cs231n.stanford.edu

A collection of lecture on deep learning, Massachusetts Institute of Technology, deeplearning.mit.edu

References

LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444.

Schmidhuber, J. (2015). Deep learning in neural networks: An overview. Neural networks, 61, 85-117.

Neu, D. A., Lahann, J., & Fettke, P. (2021). A systematic literature review on state-of-the-art deep learning methods for process prediction. Artificial Intelligence Review, 1-27.

Nguyen, A., Chatterjee, S., Weinzierl, S., Schwinn, L., Matzner, M., & Eskofier, B. (2020, October). Time matters: time-aware LSTMs for predictive business process monitoring. In International Conference on Process Mining (pp. 112-123). Springer, Cham.

Taymouri, F., La Rosa, M., & Erfani, S. M. (2021). A deep adversarial model for suffix and remaining time prediction of event sequences. In Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) (pp. 522-530). Society for Industrial and Applied Mathematics.

G. Park and M. Song, "Prediction-based Resource Allocation using LSTM and Minimum Cost and Maximum Flow Algorithm," 2019 International Conference on Process Mining (ICPM), 2019, pp. 121-128, doi: 10.1109/ICPM.2019.00027.

Park, G., & Song, M. (2020). Predicting performances in business processes using deep neural networks. Decision Support Systems, 129, 113191.

Tax, N., Verenich, I., La Rosa, M., Dumas, M. (2017). Predictive Business Process Monitoring with LSTM Neural Networks. In: Dubois, E., Pohl, K. (eds) Advanced Information Systems Engineering. CAiSE 2017. Lecture Notes in Computer Science(), vol 10253. Springer, Cham. doi.org/10.1007/978-3-319-59536-8_30

Weinzierl, S., Zilker, S., Brunk, J., Revoredo, K., Matzner, M., & Becker, J. (2020, September). XNAP: making LSTM-based next activity predictions explainable by using LRP. In International Conference on Business Process Management (pp. 129-141). Springer, Cham.

Obodoekwe E, Fang X, Lu K. Convolutional Neural Networks in Process Mining and Data Analytics for Prediction Accuracy. Electronics. 2022; 11(14):2128. doi.org/10.3390/electronics11142128

Knowledge graphs (KG) are means to model a domain of interest via relationships between objects, where the objects are the nodes and the relationships are the edges of a graph (Hogan, 2020). See (Rotmensch, 2017) for an example from medicine. After construction, a KG can be used for downstream tasks, which are grouped into In-KG and Out-of-KG tasks - sometimes also called applications, but we stick with tasks for now - (Wang, 2017). The In-KG tasks are link prediction, triple classification, entity classification, and entity resolution. In the thesis, we are interested in these In-KG tasks and which methods of the past 10 to 12 years have lead to performance gains on these tasks. Within this, we are particularly interested in comparing methods which use knowledge graph embeddings and those which do not. Knowledge graph embeddings are graph embeddings, in other words, the nodes and edges of the knowledge graph are mapped into a continuous vector space – which is referred to as embedding a knowledge graph (Wang, 2017). Embeddings are, however, not limited to nodes and edges but are also done for substructures (subset of nodes and/or edges) and even the whole-graph (Cai, 2018).

The objective of this thesis is to conduct a comprehensive structured literature review (SLR) on the performance evolution of in-KG tasks. Within this (SLR), we are particularly interested in knowledge graph embeddings. We want to understand whether, and to which extend, knowledge graph embeddings lead to performance gains for in-KG tasks. In other words, the comparison between methods that use embeddings and those that do not is of particular interest. In the thesis, the student will systematically characterise the data sets used for in-KG tasks, the methods used for in-KG tasks, and how the performance on in-KG has changed over time, and to which extend embeddings have improved, or not, the performance. The student might also be asked to give her/his opinion on the current state of the art.

Supervisor: Stefan Bachhofner

Resources

CS 520, Knowledge Graphs, Stanford University, https://web.stanford.edu/class/cs520/, web.stanford.edu/~vinayc/kg/notes/Table_Of_Contents.html

References

Hogan, A., Blomqvist, E., Cochez, M., d'Amato, C., de Melo, G., Gutierrez, C., ... & Zimmermann, A. (2020). Knowledge graphs. arXiv preprint arXiv:2003.02320.

Rotmensch, M., Halpern, Y., Tlimat, A., Horng, S., & Sontag, D. (2017). Learning a health knowledge graph from electronic medical records. Scientific reports, 7(1), 1-11.

Wang, Q., Mao, Z., Wang, B., & Guo, L. (2017). Knowledge graph embedding: A survey of approaches and applications. IEEE Transactions on Knowledge and Data Engineering, 29(12), 2724-2743.

Cai, H., Zheng, V. W., & Chang, K. C. C. (2018). A comprehensive survey of graph embedding: Problems, techniques, and applications. IEEE Transactions on Knowledge and Data Engineering, 30(9), 1616-1637.

Knowledge graphs (KG) are means to model a domain of interest via relationships between objects, where the objects are the nodes and the relationships are the edges of a graph (Hogan, 2020). See (Rotmensch, 2017) for an example from medicine. After construction, a KG can be used for downstream tasks, which are grouped into In-KG and Out-of-KG tasks - sometimes also called applications, but we stick with tasks for now - (Wang, 2017). The Out-of-KG tasks are relation extraction, question answering, and recommender systems. In the thesis, we are interested in these Out-of-KG tasks and which methods of the past 10 to 12 years have lead to performance gains on these tasks. Within this, we are particularly interested in comparing methods which use knowledge graph embeddings and those which do not. Knowledge graph embeddings are graph embeddings, in other words, the nodes and edges of the knowledge graph are be mapped into a continuous vector space – which is referred to as embedding a knowledge graph (Wang, 2017). Embeddings are, however, not limited to nodes and edges but are also done for substructures (subset of nodes and/or edges) and even the whole-graph (Cai, 2018).

The objective of this thesis is to conduct a comprehensive structured literature review (SLR) on the performance evolution of Out-of-KG tasks. Within this (SLR), we are particularly interested in knowledge graph embeddings. We want to understand whether, and to which extend, knowledge graph embeddings lead to performance gains for Out-of-KG tasks. In other words, the comparison between methods that use embeddings and those that don’t is of particular interest. In the thesis, the student will systematically characterise the data sets used for Out-of-KG tasks, the methods used for Out-of-KG tasks, and how the performance of Out-of-KG tasks has changed over time, and to which extend embeddings have improved, or not, the performance. The student might also be asked to give her/his opinion on the current state of the art.

Supervisor: Stefan Bachhofner

Resources

CS 520, Knowledge Graphs, Stanford University, https://web.stanford.edu/class/cs520/, web.stanford.edu/~vinayc/kg/notes/Table_Of_Contents.html

References

Hogan, A., Blomqvist, E., Cochez, M., d'Amato, C., de Melo, G., Gutierrez, C., ... & Zimmermann, A. (2020). Knowledge graphs. arXiv preprint arXiv:2003.02320.

Rotmensch, M., Halpern, Y., Tlimat, A., Horng, S., & Sontag, D. (2017). Learning a health knowledge graph from electronic medical records. Scientific reports, 7(1), 1-11.

Wang, Q., Mao, Z., Wang, B., & Guo, L. (2017). Knowledge graph embedding: A survey of approaches and applications. IEEE Transactions on Knowledge and Data Engineering, 29(12), 2724-2743.

Cai, H., Zheng, V. W., & Chang, K. C. C. (2018). A comprehensive survey of graph embedding: Problems, techniques, and applications. IEEE Transactions on Knowledge and Data Engineering, 30(9), 1616-1637.

Background            

Open Data has increased in popularity and many private and public stakeholders want to promote transparency and enable new business models: this access is provided by different means. The purpose is to provide direct machine readable access to the information and foster democracy and innovative reuse of publicly available data [1]. 

This movement has already many years, therefore the organisations have already an history on how to treat its access. The work from Neumair and Polleres, 2018 [2], analysed the Open Data Portals measuring its quality and proposing metrics, assessing “the goodness” of these Open Data sources.  This represents a “generic formal model to represent data and metadata in web portals”[2]. This project has been implemented in Portal Watch https://data.wu.ac.at/portalwatch.

This project has been interrupted after the work of Thomas Weber in 2020 https://aic.ai.wu.ac.at/~polleres/supervised_theses/Thomas_Weber_BSc_2020.pdf [3]. It requires to be monitored again. The research aims to continue and extend the work analysing the new sources of data and integrate into a new version of dashboard in the https://data.wu.ac.at/ website.

Research problem        

In this Master thesis, you will investigate questions such as:

RQ: What are the open data sources that are present on these archives? What is the best way to visualise the quality of data and its availability?

RQ: What is the evolution of source of open data in the portal and what are the characteristics of such development 

RQ: What is the complete panorama of Open Data Software Provider? 

The goal is to consolidate the previous work and to provide ways to communicate open data portals to different stakeholders. This project suits people who are interested and willing to deepen knowledge in data analysis and data management techniques: foster their knowledge of SQL/Python, visualisation techniques. Further questions must be created from the student according to their interests.

Meet the supervisor – Shahrom Sohi

Shahrom, is a transport engineer that loves combine data techniques to solve international mobility challenges. Feel free to book a meeting if you’re willing to have a quick chat about the topic.

You can use his Calendly https://calendly.com/shahrom-sohi/30min.

Industry Possibility with ÖBB

WU is collaborating with ÖBB on multiple projects (Press) – Shahrom Sohi, is one of the two Pre-Docs associated to this cooperation. This project can be implemented into a ÖBB vision on how catalogue data for transport and mobility operations and their organisations. Further development can be jointly design with the industry partner.

The project can provide direct connection with ÖBB and its industry challenges.

Reference

[1] Gurstein, 2011 “Open data: Empowering the empowered or effective data use for everyone?”

https://firstmonday.org/article/view/3316/2764

[2] Neumair and Polleres, 2018 “Enabling Spatio-Temporal Search in Open Data”

https://research.wu.ac.at/en/publications/enabling-spatio-temporal-search-in-open-data-15

[3] Weber, 2020 “Open Dataset Archive”, Bachelor Thesis

https://aic.ai.wu.ac.at/~polleres/supervised_theses/Thomas_Weber_BSc_2020.pdf

Background            

Raising the population in urban areas challenges transportation practitioners to design more efficient mobility solutions. At the same time new forms of mobility are emerging accessible digitally [1]. Transport mode choice analysis takes care of the core factors that affect a user when they are planning to move such as Comfort, Time and Cost [2]. The growth of access to transport via digital interfaces is representing a transport need, these information need to take into account factors affecting usage of mode of transport.

At the same time Open Data increased in popularity and many private and public stakeholders want to promote transparency and enable new business models: this access is provided by different means. The purpose is to provide direct machine readable access to the information and foster democracy and innovative reuse of publicly available data [3]. 

Accessibility such as of the information can be explained with modern data quality assessments [4]

Research problem        

In this Master thesis, you will investigate questions such as:

RQ: What is the transport planning related information accessible as open data?

RQ: Can this information be categorised according to factors affecting mode of transport choice and how? 

RQ: What are the benefits for transport stakeholders?

RQ: How to connect the information found and what are the benefits for transport operations?

At the beginning you navigate into the basics of the mobility domain: Why do people/goods move in this way? After gathering the essential information about Transport Planning and understanding what can be useful for transport info. You collect information about availability datasets and analyse them. Additionally, you can propose a new use case of your choice in the mobility domain selecting one of the Austrian Mobility providers o. The thesis will be ideal for people who are curious about the mobility world and would like to dig into Data Management Specialisations. Further questions must be created from the student according to their interests.

Meet the supervisor – Shahrom Sohi

Shahrom, is a transport engineer that loves combine data technologies to solve international mobility challenges. Feel free to book a meeting if you’re willing to have a quick chat about the topic.

You can use his Calendly https://calendly.com/shahrom-sohi/30min.

Industry Possibility with ÖBB

WU is collaborating with ÖBB on multiple projects (Press) – Shahrom Sohi, is one of the two Pre-Docs associated to this cooperation. This thesis can be implemented into a ÖBB vision on how use data for transport and mobility operations. Further development can be jointly design with the industry partner.

The project can provide direct connection with ÖBB and its industry challenges.

Reference

[1] Shaheen et al 2020 “Mobility on Demand Planning and Implementation: Current Practices, Innovations, and Emerging Mobility Futures”

URL : https://rosap.ntl.bts.gov/view/dot/50553

[2] Geurs and van Wee 2004 “Accessibility evaluation of land-use and transport strategies: review and research directions“

https://www.sciencedirect.com/science/article/pii/S0966692303000607?via%3Dihub

[3] Gurstein, 2011 “Open data: Empowering the empowered or effective data use for everyone?”

https://firstmonday.org/article/view/3316/2764

[4] Neumair and Polleres, 2018 “Enabling Spatio-Temporal Search in Open Data”

https://research.wu.ac.at/en/publications/enabling-spatio-temporal-search-in-open-data-15

Processes deliver value to customers through a repetitive execution of its activities. However,

every good process eventually becomes a bad process due to numerous factors such as changing

environment (e.g. climate change, pandemic), increased competition and rising customer

expectations which influence how a company operates. In order to keep up with all these

changes, organizations have to continuously change their business processes. One of the biggest

enablers of process change nowadays are the emerging digital technologies.

This thesis should explore the different ways digital technologies such as the Internet of Things

affect the business processes of organizations. This should be done by means of a systematic

literature review of published scientific papers and/or industry case studies, or by collecting and

analysing empirical data on the role of digital technologies on the business processes in

organizations.

This thesis topic could be divided into multiple thesis topics, each focusing on a specific digital

technology (e.g. AI, VR, AR, Robotics, Automation, Cloud Computing, Data Analytics, etc.).

References:

Mendling, J., Pentland, B. T., & Recker, J. (2020). Building a complementary agenda for business

process management and digital innovation. European journal of information systems, 29(3),

208-219.

Bilgeri, D., Gebauer, H., Fleisch, E., & Wortmann, F. (2019). Driving process innovation with IoT field

data. MIS Quarterly Executive, 18, 191-207.

Kamalaldin, A., Sjödin, D., Hullova, D., & Parida, V. (2021). Configuring ecosystem strategies for

digitally enabled process innovation: A framework for equipment suppliers in the process

industries. Technovation, 105, 102250.

Sjödin, D. R., Parida, V., Leksell, M., & Petrovic, A. (2018). Smart Factory Implementation and

Process Innovation: A Preliminary Maturity Model for Leveraging Digitalization in Manufacturing

Moving to smart factories presents specific challenges that can be addressed through a structured

approach focused on people, processes, and technologies. Research-Technology Management,

61(5), 22-31.

Shi, Zhan, et al. "Smart factory in Industry 4.0." Systems Research and Behavioral Science 37.4

(2020): 607-617.

Processes deliver value to customers through a repetitive execution of its activities. One company can outperform another company that sells the same products and/or services by executing their

processes better. Nowadays, companies take advantage of the different digital technologies such

as AI and Data Analytics in order to serve their customers better. For example, companies use

technologies such as AR to enable customers to try products virtually, which in turn increases the

customer’s convenience as well as experience. Also, digital technologies facilitate better patient

care by making it possible to monitor the health of people without hospitalization. This also has an

effect on the customer convenience.

This thesis should explore the different ways digital technologies can be used to enhance the

customer convenience and experience.

References:

Petersen, J. A., Paulich, B. J., Khodakarami, F., Spyropoulou, S., & Kumar, V. (2022). Customer-based

execution strategy in a global digital economy. International Journal of Research in Marketing,

39(2), 566-582.

Hoyer, W. D., Kroschke, M., Schmitt, B., Kraume, K., & Shankar, V. (2020). Transforming the

customer experience through new technologies. Journal of Interactive Marketing, 51(1), 57-71.

Lee, S. M., & Lee, D. (2020). “Untact”: a new customer service strategy in the digital age. Service

Business, 14(1), 1-22.

Jamkhaneh, H. B., Tortorella, G. L., Parkouhi, S. V., & Shahin, R. (2022). A comprehensive

framework for classification and selection of H4. 0 digital technologies affecting healthcare

processes in the grey environment. The TQM Journal.

Recent years have seen an increasing availability of process execution data from several sources. Process mining offers different analysis techniques to extract business insights from these data, known as event logs. An event log is a set of the executed process instances, i.e., cases. Each event in the event log represents an execution of a process activity. The event's primary attributes carry the control-flow information as execution timestamp, executed activity, and case identifier. Additionally, an event has different data attributes that describe business objects used for the process execution and environment, e.g., resources, project name, location, cost..., etc.

In some circumstances, event logs do not include a case identifier. Such logs are called uncorrelated event logs. This problem occurs mainly when event logs are extracted from non-process-aware information systems, which do not keep track of case identifiers. In this case, the event log has to be pre-processed by grouping events into cases -- an operation known as event correlation.

A few approaches have investigated the issue of reasoning about uncorrelated events. 

The existing approaches use different forms of the domain. There are three categories:

1. Approaches depend on the process models only.

2. Approaches rely on data rules over the event data context attributes only.

3. Approaches combine the process model and the data rules to correlate the events.

 

However, the approaches in the second and third categories do not provide a measure to evaluate the impact of the data rules on the correlation decision.  

The thesis's objective is to formulate a set of measures that evaluate the impact of the different data rules over the correlation process and build a tool that computes these measure during an event correlation process, and shows how these measures improve the selection of the rules for further correlation analysis.

Programming skills are required to be able to create a software prototype.

Mathematical and statistical knowledge are required to be able to formulate the new measures.

References:

[1] Pentland, B. T., Recker, J., Wolf, J. R., & Wyner, G. (2020). Bringing context inside process research with digital trace data. Journal of the Association for Information Systems, 21(5), 5.

[2] Bayomie, D., Di Ciccio, C., La Rosa, M., Mendling, J. (2019). A Probabilistic Approach to Event-Case Correlation for Process Mining. In: Laender, A., Pernici, B., Lim, EP., de Oliveira, J. (eds) Conceptual Modeling. ER 2019. Lecture Notes in Computer Science(), vol 11788. Springer, Cham.

[3] Reguieg, H., Toumani, F., Motahari-Nezhad, H.R., Benatallah, B. (2012). Using Mapreduce to Scale Events Correlation Discovery for Business Processes Mining. In: Barros, A., Gal, A., Kindler, E. (eds) Business Process Management. BPM 2012. Lecture Notes in Computer Science, vol 7481. Springer, Berlin, Heidelberg. 

[4] Motahari-Nezhad, H.R., Saint-Paul, R., Casati, F. et al. Event correlation for process discovery from web service interaction logs. The VLDB Journal 20, 417–444 (2011). doi.org/10.1007/s00778-010-0203-9

[5] Polyvyanyy, Artem, and Anna Kalenkova. "Conformance checking of partially matching processes: An entropy-based approach." Information Systems 106 (2022): 101720. https://doi.org/10.1016/j.is.2021.101720

The concept of phronesis (i.e., practical wisdom), dating back to Aristotle, has recently been “rediscovered” and has entered the stage of knowledge management (Nonaka & Takeuchi, 2019, 2021). In essence, it is about doing the right thing in a particular context to promote the common good. However, the concept remains theoretically elusive and empirically difficult to test. In a recent attempt to address this shortcoming, Rocha et al. (2021a, 2021b, in prep.) propose the Organizational Phronesis Scale (OPS). This proposed master thesis consists of two parts:

First, you will investigate if phronesis has a positive influence on (organizational) performance as indicated in the literature. The newly proposed OPS allows for investigating this relationship empirically. In this thesis, you will theoretically relate organizational phronesis to concept(s) of organizational performance and are among the first to use the OPS in combination with another/other scale(s) you identify in the literature. You will perform statistical analysis of empirical data, that you will need to obtain, and discuss your findings.

Second, you will identify sources of practical wisdom based on a structured review of the state-of-the-art literature. Based on your findings, you will reflect on possible pathways to practical wisdom and provide practical advice for leadership education.

Nonaka, I., & Takeuchi, H. (2021). Humanizing strategy. Long Range Planning, 102070.

Nonaka, I., & Takeuchi, H. (2019). The wise company: How companies create continuous innovation. Oxford University Press.

Rocha G. R., Pinheiro, P., D‘Angelo, M., & Kragulj, F. (2021) Organizational Phronesis Scale Development. 22nd European Conference on Knowledge Management - ECKM 2021

Rocha G. R., Pinheiro, P., Kragulj, F., & Nunes C. (2021) There remains much to learn about organizational phronesis. Theory and Applications in the Knowledge Economy - TAKE 2021

Rocha G. R., Pinheiro, P., Kragulj, F., & Nunes C. (in prep.) ONE STEP TOWARDS RECOGNIZING THE PRACTICALLY WISE COMPANY: MEASUREMENT AND VALIDITY

The automotive industry is being massively transformed through connectivity, autonomous driving, and shared mobility trends. There is great potential in enabling various vehicles to share information between each other and the infrastructure, or to use the computation services on the edge or in the cloud. Data sharing can be beneficial, both for the end user by improving driving experience and service quality, but also for companies developing novel use cases and innovative business models. However, security and privacy issues and unclear benefits hinder individuals and companies from participating in the data-sharing process.

Distributed ledger and blockchain as disruptive technologies could potentially solve these issues. The goal of this master thesis is to explore the possibilities and application of distributed ledger technologies in the context of connected and cooperated mobility. The student should identify the applicability and feasibility of the technology and associated frameworks and propose a suitable system architecture. Depending on the student's preferences and background, the focus of the work will be more on use cases and user benefits, stakeholder identification, business models and the potential for economic exploitation, or on the software-technical concepts and prototype implementation.

Collaboration with an Austrian corporate partner is possible (details will be given in the process).

Initial References:

1. McKinsey and Company, "The future of automotive computing: Cloud and edge", https://www.mckinsey.com/industries/semiconductors/our-insights/the-future-of-automotive-computing-cloud-and-edge?cid=eml-web

2. Y. Lu, X. Huang, K. Zhang, S. Maharjan and Y. Zhang, "Blockchain Empowered Asynchronous Federated Learning for Secure Data Sharing in Internet of Vehicles," in IEEE Transactions on Vehicular Technology, vol. 69, no. 4, pp. 4298-4311, April 2020, doi: 10.1109/TVT.2020.2973651.

 

Potential Publication Venue: IEEE Transactions on Industrial Informatics, IEEE Transactions on Vehicular Technology

Many of today's and future internet-based applications are distributed across IoT, Edge, and Cloud computing infrastructures. In addition, such applications involve more and more legal and organizational entities and are not centraly organized or managed. So, the question of how data is shared and stored, how people and devices collaborate, and how to guarantee security are fundamental challenges. The traditional centralized cloud/edge architecture cannot meet digital business infrastructure requirements. Blockchain is considered an adaptable technology for inaugurating a trustful decentralized platform with characteristics such as interoperation, tamper-resistance, decentralization, etc. Recently, progress has been made in blockchain-based decentralized cloud/edge computing. However, multiple challenges remain to be addressed, such as scalability, decentralization vs. centralization, and, most importantly, energy consumption and climate impact. 

The thesis should explore the field through a systematic literature review of published scientific or industrial papers and should identify use cases (particularly related to energy systems and environmental challenges), architectures, stakeholders, and future technological and organizational challenges. 

Collaboration with an Austrian corporate partner is possible (details will be given in the process).

Initial References:

1. D. C. Nguyen, P. N. Pathirana, M. Ding and A. Seneviratne, "Integration of Blockchain and Cloud of Things: Architecture, Applications and Challenges," in IEEE Communications Surveys & Tutorials, vol. 22, no. 4, pp. 2521-2549, Fourthquarter 2020, doi: 10.1109/COMST.2020.3020092.

2. Alliance for the Internet of Things Innovation, “AIOTI Report on DLT-IoT Convergence”, https://aioti.eu/wp-content/uploads/2022/07/AIOTI-DLT-IoT-Convergence-Final.pdf

 

Potential Publication Venue: IEEE Transactions on Industrial Informatics

Metaverse is created through virtualizing and digitalizing the real world using artificial intelligence, blockchain, cloud computing, and digital twin technologies. Currently, the most popular Metaverse applications are coming from social media, online games, or retail. However, the most significant potential of the Metaverse will lie with industries that make up the backbones of our economies such as manufacturing, energy, or transportation. The industrial Metaverse would be a network of digital twins connecting physical systems and the digital world. It would enable different industrial stakeholders to connect their digital twins with partners (customers and suppliers) to work together and get insights based on accurate and timely data.

The goal of this thesis is to create an overview of the industrial Metaverse ecosystem, including stakeholders and technologies. The focus should be put on the strategies and technologies, such as Distributed Ledger Technologies and smart contracts that enable seamless collaboration while preserving control over data management in such a decentralized environment.

Initial References:

1. Deloitte, “Metaverse report—Future is here”, https://www2.deloitte.com/cn/en/pages/technology-media-and-telecommunications/articles/metaverse-whitepaper.html

2. Siemens, “What is the Industrial Metaverse – and why should I care?”, https://new.siemens.com/global/en/company/insights/what-is-the-industrial-metaverse-and-why-should-i-care.html

3. Zhiyu Lin, Peng Xiangli, Zhi Li, Fuhe Liang, and Aofei Li. 2022. Towards Metaverse Manufacturing: A Blockchain-based Trusted Collaborative Governance System. In The 2022 4th International Conference on Blockchain Technology (ICBCT'22). Association for Computing Machinery, New York, NY, USA, 171–177.

4. McKinsey, “Digital twins: The foundation of the enterprise metaverse”, https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/digital-twins-the-foundation-of-the-enterprise-metaverse

 

Potential Publication Venue: IEEE Transactions on Industrial Informatics

Public and permissionless blockchains like Bitcoin and Ethereum are of transparent nature. This enables observers to trace money flows throughout the network. Privacy-enhancing technologies are on the rise to tackle this problem. In this thesis, we are investigating the most prominent privacy-enhancing technologies on Bitcoin and Ethereum. We move from centralized and trust-required services to decentralised and trustless operating application and highlight the differences between the. Furthermore we quantitatively show how privacy-enhancing technologies have been exploited in the past by malicious actors to launder money or finance terrorism.

Highlight the current state of the art including the following technologies:

Cenralized mixers - Blender.io (is already down)

Decentralised mixers - Wasabi Wallet, Samurai Wallet, Tornado Cash

Stealth Addresses

Initial References:

1. B. Tao, H.-N. Dai, J. Wu, I. W.-H. Ho, Z. Zheng, and C. F. Cheang, “Complex network analysis of the bitcoin transaction network,”IEEE Transactions on Circuits and Systems II: Express Briefs, 2021.

2. A. Kumar, K. Abhishek, P. Nerurkar, M. R. Khosravi, M. R. Ghalib, and A. Shankar, “Big data analytics to identify illegal activities on bitcoin blockchain for iomt,” Personal and Ubiquitous Computing

3. D. Vassallo, V. Vella, and J. Ellul, “Application of gradient boosting algorithms for anti-money laundering in cryptocurrencies,” SN Computer Science, vol. 2, no. 3, pp. 1–15, 2021.

 

Potential Publication Venue: IEEE Transactions on Dependable and Secure Computing

While a number of large organizations that were responsible for managing their users’ crypto assets blew up for different reasons, decentralized finance (DeFi) remained stable over the years.

In this thesis, we analyze the individual cases and investigate the total money lost in cryptocurrency exchange hacks vs DeFi. We categorize the individual risk of traditional crypto-finance organizations and DeFi and determine the main risks involved.

We show that, while traditional crypto-exchanges often become victims of fraud that originates from within the company, DeFi has more to deal with Smart Contract exploits. We further propose safety measures to tackle the identified problems.

Initial References:

1. Financial Stability Board (2020).Addressing the regulatory, supervisory and oversight challenges raised by ”global stablecoin” arrangements.(April). www.fsb.org/wp-content/uploads/P140420-1.pdf

2. Chen, W., Zhang, T., Chen, Z., Zheng, Z., and Lu, Y. (2020). Traveling the token world: A graph analysis of ethereum erc20 token ecosystem. In Proceedings of The Web Conference 2020, WWW ’20, page 1411–1421, New York, NY, USA.

3. Mertzanis, C. (2020). Financial supervision structure, decentralized decision-making and financing constraints. Journal of Economic Behavior & Organization, 174:13–37. doi.org/10.1016/j.jebo.2020.03.004

 

Potential Publication Venue: IEEE Transactions on Dependable and Secure Computing

One of the main constraints of public blockchain applications such as Bitcoin and Ethereum is their limited scalability. Over the past 10 years, multiple different scaling solutions have been proposed by both the Bitcoin and Ethereum community. In the following work, we first demonstrate the scaling bottleneck of public blockchains. Second, we analyze the proposed scaling solutions and compare them in quantitative manners. The goal of this work is to compare the different scaling solutions and assess the advantages and disadvantages they come with. Doing, so we shed light onto the current state of blockchain scalability. This includes Lightning Network, Ethereum Layer 2 solutions such as Arbitrum, Polygon, Optimism, Boba, etc., Bridges to other blockchains, Sharding, and more.

Initial References:

1. https://blog.chain.link/blockchain-scalability-approaches

2. https://ethereum.org/en/developers/docs/scaling/

 

Potential Publication Venue: IEEE Transactions on Dependable and Secure Computing

Owing to its inherent characteristic of security and computational requirements, classical blockchains are assumed to be secure against different attacks. However, the advancements toward quantum computing pose a significant threat to the attack-resistant nature of classical security mechanisms adopted by the existing blockchains. Due to that, this research aims to investigate the impacts of quantum computing on blockchain and propose new solutions to overcome these impacts.

Initial References:

1. X. Sun, M. Sopek, Q. Wang, P. Kulicki, Towards quantum-secured permissioned blockchain: Signature, consensus, and logic, Entropy 21 (2019) 887. URL: http://dx.doi.org/10.3390/e21090887. Doi:10. 3390/e21090887

2. D. A. Bard, J. J. Kearney, C. A. Perez-Delgado, Quantum advantage on proof of work, Array 15 (2022) 100225. URL: https://www.sciencedirect.com/science/article/pii/S2590005622000650. doi:https://doi.org/10.1016/j.array.2022.100225

3. J. Chen, W. Gan, M. Hu, C.-M. Chen, On the construction of a post-quantum blockchain, in: 2021 IEEE Conference on Dependable and Secure Computing (DSC), 2021, pp. 1–8. doi:10.1109/DSC49826.2021. 9346253

 

Potential Publication Venue: IEEE Transactions on Quantum Engineering, IEEE Transactions on Dependable and Secure Computing

Technology improvements have led to social media sites becoming news providers. Users from social media frequently have no hesitation in sharing anything that comes their way. These online platforms do not offer a way to verify the accuracy of the material that has been submitted due to their flexibility. The truthfulness of the news and maintaining online civility on online platforms are now top priorities. Due to that, this research aims to improve the traceability of fake news using blockchains. The main goal is to improve the maintenance and truthfulness of news spread through a publicly distributed ledger where everyone can check and track the information spread.

Initial References:

1. Farooq, M., Ashraf Makhdomi, A., & Altaf Gillani, I. (2022). Crowd Sourcing and Blockchain-Based Incentive Mechanism to Combat Fake News. In Combating Fake News with Computational Intelligence Techniques (pp. 299-325). Springer, Cham.

2. Qayyum, A., Qadir, J., Janjua, M. U., & Sher, F. (2019). Using blockchain to rein in the new post-truth world and check the spread of fake news. IT Professional, 21(4), 16-24.

3. Paul, S., Joy, J. I., Sarker, S., Ahmed, S., & Das, A. K. (2019, June). Fake news detection in social media using blockchain. In 2019 7th International Conference on Smart Computing & Communications (ICSCC) (pp. 1-5). IEEE.

 

Potential Publication Venue: IEEE Transactions on Engineering Management, IEEE Transactions on Network Science and Engineering,  IEEE Transactions on Dependable and Secure Computing

In a variety of data-based environments, several devices continuously generate, process, and transfer enormous volumes of data among themselves in a complex environment. Correctly identifying the devices that are producing the data, assessing the dependability of these devices and the data they offer, identifying aberrant activity, and limiting access to the data are some issues in this situation. The retention of information about the data's location of origin, the operations it has undergone, and its history of processing from creation to the present is made possible by data provenance. In this view, this research aims to purpose a blockchain-based architecture for data provenance management. This architecture could be used for different environments, including the Internet of Things (IoT), supply chains, etc. The main goal is to provide the provenance of data using a distributed ledger architecture.

Initial References:

1. Liang, X., Shetty, S. S., Tosh, D., Njilla, L., Kamhoua, C. A., & Kwiat, K. (2019). ProvChain: Blockchain‐based Cloud Data Provenance. Blockchain for Distributed Systems Security, 69.

2. Celik, Y., Petri, I., & Barati, M. (2023). Blockchain supported BIM data provenance for construction projects. Computers in Industry, 144, 103768.

3. Vieira, M. A., & Carvalho, S. T. (2021, August). Towards a Blockchain-based Architecture for Data Provenance Management in the Internet of Things. In Anais do IV Workshop em Blockchain: Teoria, Tecnologias e Aplicações (pp. 94-99). SBC.

 

Potential Publication Venue: IEEE Transactions on Engineering Management

Unlike the physical world, the creation of contents, applications and scenarios requires behavioral data of users and enterprises. At present, a number of AI algorithms have been deployed to enhance user experience in a number of metaverse projects. However, sharing such data may result in various privacy and security related issues. Federated learning/Distributed learning emerge as a promising solution to various security and privacy related issues in the centralized learning environment. In this thesis/project, the aim is to exploit various security and privacy related issues in the existing AI based metaverse projects using a state-of-the-art threat modeling method and to develop use cases or application scenarios as to how Federated learning can solve such issues.

1)           Trust/privacy and security related issues in the existing AI applications of Metaverse.

2)           Attacks/defense mechanisms in Metaverse (AI/Machine or deep learning)

3)           Applications of blockchain in metaverse.

4)           Privacy preserving federated learning in Metaverse.

Initial References:

1. Huynh-The, Thien, Quoc-Viet Pham, Xuan-Qui Pham, Thanh Thi Nguyen, Zhu Han, and Dong-Seong Kim. "Artificial intelligence for the metaverse: A survey." Engineering Applications of Artificial Intelligence 117 (2023): 105581.

2. Yang, Qinglin, Yetong Zhao, Huawei Huang, Zehui Xiong, Jiawen Kang, and Zibin Zheng. "Fusing blockchain and AI with metaverse: A survey." IEEE Open Journal of the Computer Society 3 (2022): 122-136.

3. Wang, Yuntao, Zhou Su, Ning Zhang, Rui Xing, Dongxiao Liu, Tom H. Luan, and Xuemin Shen. "A survey on metaverse: Fundamentals, security, and privacy." IEEE Communications Surveys & Tutorials (2022).

 

Potential Publication Venue: IEEE Transactions on Dependable and Secure Computing

Due to its decentralized nature, blockchain technology has revolutionized the finance industry. However, most of its applications and use cases of are only limited to storage and transfer of tokens within a single blockchain or across cross chain transactions between multiple chains. With the introduction of various chains such as Cosmos, Polkadot etc. cross chain asset or token transfer can be achieved. However, data transfer across multiple chain has not been investigated. In this thesis, we aim to investigate the applications and use case of the following in data transfer across multiple chains:

1)    Incentive mechanisms

2)    Authentication mechanism

3)    Security and privacy issues data

4)    Machine learning/deep learning models

Initial References:

1. Lohachab, Ankur, Saurabh Garg, Byeong Kang, Muhammad Bilal Amin, Junmin Lee, Shiping Chen, and Xiwei Xu. "Towards interconnected blockchains: a comprehensive review of the role of interoperability among disparate blockchains." ACM Computing Surveys (CSUR) 54, no. 7 (2021): 1-39.

2. Belchior, Rafael, André Vasconcelos, Sérgio Guerreiro, and Miguel Correia. "A survey on blockchain interoperability: Past, present, and future trends." ACM Computing Surveys (CSUR) 54, no. 8 (2021): 1-41.

3. Khan, Sajjad, Muhammad Bilal Amin, Ahmad Taher Azar, and Sheraz Aslam. "Towards interoperable blockchains: A survey on the role of smart contracts in blockchain interoperability." IEEE Access 9 (2021): 116672-116691.

 

Potential Publication Venue: IEEE Transactions on Dependable and Secure Computing

Decentralized Federated learning emerged as a promising solution to the privacy preserving demand of machine learning models. However, recent works have suggested that DFL are confronted with various threats and vulnerabilities as malicious participants can deliberately launch various types of attacks in model training. In this thesis, we investigate various threats or vulnerabilities in the DFL ecosystem and their defense strategies.

1)           Incentive mechanisms for clients’ contributions in DFL.

2)           Federated transfer learning

3)           Attacks and defense strategies in DFL

Initial References:

1. Rodríguez-Barroso, Nuria, Daniel Jiménez-López, M. Victoria Luzón, Francisco Herrera, and Eugenio Martínez-Cámara. "Survey on federated learning threats: Concepts, taxonomy on attacks and defences, experimental study and challenges." Information Fusion 90 (2023): 148-173.

2. Mothukuri, Viraaji, Reza M. Parizi, Seyedamin Pouriyeh, Yan Huang, Ali Dehghantanha, and Gautam Srivastava. "A survey on security and privacy of federated learning." Future Generation Computer Systems 115 (2021): 619-640.

 

Potential Publication Venue: IEEE Transactions on Dependable and Secure Computing

Multiple students may select the same topic and write their thesis on a different sub-topic/research question

The performance of (unsophisticated) retail investors

Many individual investors trade actively, speculate, maintain poorly diversified portfolios, and chase trends. In sum, households often make costly investment decisions which depart from traditional portfolio theory. This thesis uses aggregate data from Robinhood (Robintrack) to investigate the portfolio choices and returns of unsophisticated retail investors. Potential focus can be on important questions such as how did the COVID crisis, government stimulus, and the introduction of fractional shares affect trading and returns. Interest in lottery stocks, and if investors buy the dip or follow momentum based strategies.

Suggested Literature:

• Welch, Ivo, Retail Raw: Wisdom of the Robinhood Crowd and the Covid Crisis (September 2020). NBER Working Paper No. w27866, Available at SSRN: ssrn.com/abstract=3700694

•  Barber, Brad M. and Huang, Xing and Odean, Terrance and Schwarz, Christopher, Attention Induced Trading and Returns: Evidence from Robinhood Users (November 24, 2020). Available at SSRN: ssrn.com/abstract=3715077 or dx.doi.org/10.2139/ssrn.3715077

• Grinblatt, M. and Keloharju, M., 2001. What makes investors trade?. The Journal of Finance, 56(2), pp.589-616.

• Giglio, S., Maggiori, M., Stroebel, J. and Utkus, S., 2019. Five facts about beliefs and portfolios (No. w25744). National Bureau of Economic Research.

• Greenwood, R. and Shleifer, A., 2014. Expectations of returns and expected returns. The Review of Financial Studies, 27(3), pp.714-746.

• Barber, B.M. and Odean, T., 2000. Trading is hazardous to your wealth: The common stock investment performance of individual investors. The journal of Finance, 55(2), pp.773-806.

Note: Basic knowledge in statistical analysis and data processing (in R, Stata, or similar) is

required. If you have no experience in this area, the willingness to acquire the necessary skills is

expected

Multiple students may select the same topic and write their thesis on a different sub-topic/research question

The exceptional growth of exchange-traded funds (ETFs) since the mid-nineties has undoubtedly revolutionized the investment landscape. ETFs have “democratized” financial market participation, offering low-cost access to well diversified portfolios. However, the market has evolved significantly with the advent and adoption of actively managed ETFs. These products cater to investor sentiment and bias particularly with new types new types of specialized, leveraged, and inverse ETFs.  These products charge higher fees and focus on small market segments (decrease diversification), are debt-financed (amplify risk), or even allow betting against the market. This thesis should aim to document the growth of such products, which investors use them, and how they are used. The thesis may also use natural language processing and text analysis to investigate the prospectus’ and marketing of these financial products. The thesis may also choose to focus on other related ETF products such as those related to the ESG preferences of investors.

Suggested Literature:

• Ben-David, Itzhak and Franzoni, Francesco A. and Kim, Byungwook and Moussawi, Rabih, Competition for Attention in the ETF Space (October 3, 2022). Fisher College of Business Working Paper No. 2021-03-001, Charles A. Dice Center Working Paper No. 2021-01, Swiss Finance Institute Research Paper No. 21-03, Review of Financial Studies, forthcoming , Available at SSRN: https://ssrn.com/abstract=3765063 or http://dx.doi.org/10.2139/ssrn.3765063

• Ben-David, I., Franzoni, F. and Moussawi, R., 2017. Exchange-traded funds. Annual Review of Financial Economics, 9(1), pp.169-189.

Note: Basic knowledge in statistical analysis and data processing (in R, Stata, or similar) is

required. If you have no experience in this area, the willingness to acquire the necessary skills is

expected

Trace data from online activities can help diagnose underlying behavioral states and traits. However, fine-tuning such models requires mixed-methods approaches. This topic is open for students interested in applied algorithmic approaches to understanding human behavior.

See: Am I who I say I am? Unobtrusive self-representation and personality recognition on Facebook | PLOS ONE and Utilizing Twitter data for analysis of chemotherapy - ScienceDirect

This topic can be split into multiple theses

Mentoring is a proven approach for assuring a healthy talent pipeline while at the same time it is unevenly valued in different sectors of the tech workforce. In conjunction with partners at Micro Focus, IBM, and others, this topic takes a qualitative approach to understanding trends, barriers, and opportunities of mentoring offers in engineering teams working in web app development, legacy computing, and others.

See: AIS Electronic Library (AISeL) - ICIS 2022 Proceedings: Towards Learning at Scale for Everybody: Applying Action Research to Design an Upskilling Platform for Marginalized Adults (aisnet.org) or Finding optimal mentor-mentee matches: A case study in applied two-sided matching - ScienceDirect

Phishing requests are targeting a broad and heterogeneous “audience”. They focus on exploiting trust and carelessness of their victims. Some of which are more susceptible, and some more resilient to this kind of manipulation. This thesis should focus on personality factors influencing the acquiescence with phishing requests/attacks.

López-Aguilar, P., & Solanas, A. (2021, July). Human Susceptibility to Phishing Attacks Based on Personality Traits: The Role of Neuroticism. In 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC) (pp. 1363-1368). IEEE.

Halevi, T., Memon, N., & Nov, O. (2015). Spear-phishing in the wild: A real-world study of personality, phishing self-efficacy and vulnerability to spear-phishing attacks. Phishing Self-Efficacy and Vulnerability to Spear-Phishing Attacks (January 2, 2015).

Online misinformation campaigns influence beliefs and behaviors of internet users. They are reliant on users who are spreading misinformation content on various digital channels. Some of them are sharing misinformation frequently and others are more reluctant to share dubious content. This thesis should explore the personality factors influencing tendencies to propagate misinformation content online.

Sampat, B., & Raj, S. (2022). Fake or real news? Understanding the gratifications and personality traits of individuals sharing fake news on social media platforms. Aslib Journal of Information Management.

Buchanan, T., & Benson, V. (2019). Spreading disinformation on Facebook: Do trust in message source, risk propensity, or personality affect the organic reach of “fake news”?. Social media+ society, 5(4), 2056305119888654.

Misinformation could potentially have severe consequences for a variety of domains, ranging from healthcare to politics. In order to address the negative impact of misinformation, there is a need for tools and technologies that can automatically identify misinformation. The goal of this thesis is to identify misinformation benchmarking criteria and use these criteria to benchmark state of the art misinformation detection approaches.

Reading material in order to get started: Krickl A. and Kirrane s., 2022. Misinformation Detection: Using Linguistic Cues. Proceedings of the Posters and Demos Track of the 18th International Conference on Semantic Systems.
https://penni.wu.ac.at/papers/Semantics%202022%20Misinformation%20Detection%20Using%20Linguistic%20Cues.pdf

Avilés Podgurski, L.V., Zaczynska, K. and Rehm, G., 2022. Evaluating Web Content Using the W3C Credibility Signals. In Towards a Knowledge-Aware AI (pp. 3-20). IOS Press.
https://ebooks.iospress.nl/volumearticle/60707

Görnemann, E. and Spiekermann-Hoff, S., 2020. Moments of truth with conversational agents-An exploratory quest for the relevant experiences of Alexa users. In Proceedings of the 28th European Conference on Information Systems (ECIS). AIS Association for Information Systems.
https://research.wu.ac.at/en/publications/moments-of-truth-with-conversational-agents-an-exploratory-quest--6

Popular virtual personal assistants (e.g. Siri, Axela, Google Assistant, Cortana) have different strengths and weaknesses (e.g., amazon shopping, restaurant booking, directions, setting reminders, general information). Additionally they often have problems detecting commands; rely on very specific terminology; their responses are not intuitive or helpful; and they are information vs task oriented. The goal of this thesis is to perform a hands on systematic analysis of virtual assistants in order to better understand their strengths and weaknesses.

Reading material in order to get started:

Norouzi, N., Kim, K., Hochreiter, J., Lee, M., Daher, S., Bruder, G. and Welch, G., 2018, November. A systematic survey of 15 years of user studies published in the intelligent virtual agents conference. In Proceedings of the 18th international conference on intelligent virtual agents (pp. 17-22). https://dl.acm.org/doi/pdf/10.1145/3267851.3267901

Adams, R., 2020. Helen A'Loy and other tales of female automata: a gendered reading of the narratives of hopes and fears of intelligent machines and artificial intelligence. AI & SOCIETY, 35(3), pp.569-579. https://repository.hsrc.ac.za/bitstream/handle/20.500.11910/14956/11027.pdf?sequence=1&isAllowed=y

Görnemann, E. and Spiekermann-Hoff, S., 2020. Moments of truth with conversational agents-An exploratory quest for the relevant experiences of Alexa users. In Proceedings of the 28th European Conference on Information Systems (ECIS). AIS Association for Information Systems
https://research.wu.ac.at/en/publications/moments-of-truth-with-conversational-agents-an-exploratory-quest--6

A third AI winter could be caused by inadequacies and biases in the AI algorithms leading to negative impacts from a societal perspective. According to [1] bias simply does not build value in business, particularly when it comes to credit and healthcare or increasing diversity through recruitment. The goal of this thesis is explores how existing bias detection and mitigation strategies work in a practical setting.

Reading material in order to get started:

[1] https://www.computing.co.uk/ctg/opinion/3073390/explainable-ai-should-help-us-avoid-a-third-ai-winter

Fighting AI Bias - Digital Rights are Human Rights, 2020
https://www.forbes.com/sites/insights-ibmai/2020/03/19/fighting-ai-bias-digital-rights-are-human-rights/#24985db9119a

Roselli, D., Matthews, J. and Talagala, N., 2019, May. Managing bias in AI. In Companion Proceedings of The 2019 World Wide Web Conference (pp. 539-544).
https://dl.acm.org/doi/pdf/10.1145/3308560.3317590

E. Ntoutsi, P. Fafalios, U. Gadiraju, V. Iosifidis, W. Nejdl, M.E. Vidal, S. Ruggieri, F. Turini, S. Papadopoulos, E. Krasanakis, I. Kompatsiaris, K. Kinder-Kurlanda, C. Wagner, F. Karimi, M. Fernandez, H. Alani, B. Berendt, T. Kruegel, C. Heinze, K. Broelemann, G. Kasneci, T. Tiropanis, S. Staab. Bias in Datadriven AI Systems--An Introductory Survey. 2020. arXiv preprint arXiv:2001.09762.
https://arxiv.org/pdf/2001.09762.pdf

The world’s largest user-generated content (UGC) platforms such as YouTube, Instagram, TikTok and Twitter have recently introduced online tipping. Several Chinese livestreaming platforms and Twitch have successful implemented online tipping systems to their platform generating large revenues for themselves and their content creators. However, research looking into the design requirements for an online tipping system have been lackluster. What does a sustainable online tipping system for UGC look like? What design elements do platforms need to implement such a system? Tipping leaderboards, virtual gifting and the use of virtual currencies have been widely used by mature online tipping systems. However, how should these elements be tailored to each platform and their UGC? Conduct primary research to identify distinctive design requirements that current platforms use for online tipping. Evaluate and discuss which design requirements are most effective at increasing tipping based on published studies.    

Literature to start with:
Lin, Y., Yao, D., & Chen, X. (2021). Happiness begets money: emotion and engagement in live streaming. Journal of Marketing Research, 58(3), 417-438.  
Lu, S., Yao, D., Chen, X., & Grewal, R. (2021). Do larger audiences generate greater revenues under pay what you want? evidence from a live streaming platform. Marketing Science, 40(5), 964-984. 

Overburdened public infrastructure due rapid urbanization in cities is a concern highlighted by the United Nations’ 2020 Sustainable Development Goals. Citizen reporting is a smart city solution that tackles this problem. Citizens can use a mobile app to easily submit a report about a public infrastructure issue rather than using a hotline for municipal services. However, many cities have observed a similar pattern of significantly lower reporting rates in low-income neighborhoods compared to high-income neighborhoods. Matthews and co-authors (2018) state that “high levels of reporting may suggest higher expectations on the part of individuals more than anything else. Conversely, low levels of reporting may in some areas reflect low expectations about neighborhood quality in the first place. These issues are things we think need to be investigated further” (p.18). Conduct a literature review to identify why there is a difference between high- and low-income neighborhoods in citizen reporting levels. Evaluate and discuss which factors would be the most important to address to increase citizen reporting levels for low-income neighborhoods.  

Literature to start with:
Abu-Tayeh, G., Neumann, O., & Stuermer, M. (2018). Exploring the Motives of Citizen Reporting Engagement: Self-Concern and Other-Orientation. Business and Information Systems Engineering, 60(3), 215–226.
doi.org/10.1007/s12599-018-0530-8

Berntzen, L., Johannessen, M. R., Böhm, S., Weber, C., & Morales, R. (2018). Citizens as sensors: Human sensors as a smart city data source. SMART 2018 : The Seventh International Conference on Smart Cities, Systems, Devices and Technologies, August, 11–18.
160.85.104.64/handle/11475/20031  

Matthews, P., Rae, A., Nyanzu, E., & Parsons, A. (2018). FixMyStreet! The Geography of Citizen Reporting on Neighourhood Issues in the UK. research.mysociety.org/html/fms-report/  
Huang, N., Burtch, G., Gu, B., Hong, Y., Liang, C., Wang, K., Fu, D., & Yang, B. (2019). Motivating user-generated content with performance feedback: Evidence from randomized field experiments. Management Science,
65(1), 327–345.
doi.org/10.1287/mnsc.2017.2944  

Wang, P., Lee, M., Hangen, F., & Brien, D. T. O. (2022). Social Justice & Technical Efficiency: The Role of Digital Technology in Boston’ s 311 System. ECIS 2022 Research Papers, 117.
aisel.aisnet.org/ecis2022_rp/117

References:
BMWi (2020). GAIA-X: A federated data infrastructure for Europe. https: //www.data-infrastructure.eu/GAIAX/Navigation/EN/Home/home.html.  

European Commission (2020). Communication from the commission to the european parliament, the council, the european economic and social committee and the committee of the regions: "A European strategy for data", Communication COM(2020) 66 final, European Commission, Brussels.

Nguyen, D., & Paczos, M. (2020). Measuring the economic value of data and cross-border data flows: A business perspective, OECD Digital Economy Papers, August 2020, No. 297

Krämer, J., Stüdlein, N., Zierke, O. (2021). Data as a Public Good: Experimental Insights on the Optimal Design of B2B Data Sharing Platforms. SSRN Working Paper. Available at SSRN:
ssrn.com/abstract=3970821

References:
Felfernig, A., Boratto, L., Stettinger, M., & Tkalčič, M. (2018). Group recommender systems: An introduction. Cham: Springer International Publishing.

Listokin, Y. (2015). The Vickrey-Clarke-Groves “Pivotal Mechanism” as an Alternative to Voting for Organizational Control. Theoretical Inquiries in Law, 16(1), 267-294.

Nisan, N. (2007). Introduction to mechanism design (for computer scientists). In: Nisan, N., Roughgarden, T., Tardos, E., & Vazirani, V. (Eds.). (2007). Algorithmic Game Theory. Cambridge: Cambridge University Press, 209-242.

Panoui, A., Lambotharan, S., & Phan, R. C. W. (2013). Vickrey-Clarke-Groves for privacy-preserving collaborative classification. In: IEEE 2013 Federated Conference on Computer Science and Information Systems, 123-128.  

Rothkopf, M. H. (2007). Thirteen reasons why the Vickrey-Clarke-Groves process is not practical. Operations Research, 55(2), 191-197.

This topic can be split into two theses

The output is to be used as a lecture case study within the Business Analytics part of the SCM Master Programme, for more details see https://www.wu.ac.at/erp/courses/course-02/

The filter is to be implemented in R (R Studio) using sentiment libraries available in R, ideally with a shiny interface. The libraries are to be exchangeable by the user, so are the parameters transferred to the interface, if any, and the necessary text pre-processing relative to the library used.

The case study provides 50 sample posts covering (i) real aggressive language, (ii) irony, (iii) referrals to other posts, (iv) other limiting cases for sentiment analysis; also parameter settings and/or pre-processing in R are to be implemented in an improvable way so that the recognition rate is to be increased by students as part of their course work. Programme functions and possible improvements are to be documented for the lecturer. An intro document ("storyline") has to be provided for the students. Students accepting this topic agree that their work will be published as case study material on above web site and used in university lectures, of course citing their authorship.

Description:

Municipal services of general interest (SGI) are a central feature of European societies. Against this backdrop, the global discourse on digitalisation currently highlights that one of the key challenges that local government actors must address is transforming SGI. As a result, both objectives and actual design of SGI are undergoing major changes. Despite this trend, there is still a lack of systematic knowledge about the extent to which and how digitalisation affects SGI, as well as about the outcomes of such changes in municipalities (for instance on an economic, societal and political level). Approaches to a systematic classification of how digitalisation affects SGI are still in their infancy, both in municipal practice and in the academic literature. Digital services of general interest (D-SGI) can be defined as the digital infrastructures, services and goods that are essential for a sustainable participation, for equality of living conditions and for sovereignty of citizens within a digital society. With this, D-SGI also have a considerable relevance to democracy. By mapping the current and future fields of activity, the dissertation is to shed light on the status quo of digitisation, digitalisation and digital transformation of public services in municipalities and to provide an outlook into the future by means of a systematic literature review.

References:

. Agostino, D./Arnaboldi, M./Lema, M.D. (2020): "New development: COVID-19 as an accelerator of digital transformation in public service delivery", in: Public Money & Management, Vol. 41, No. 1, pp. 69-72.

. Curtis, S. (2019): "Digital transformation—the silver bullet to public service improvement?", in: Public Money & Management, Vol. 39, No. 5, pp. 322-324.

. Mergel, I./Edelmann, N./Haug, N. (2019): "Defining digital transformation: Results from expert interviews", in: Government Information Quarterly, Vol. 36, No. 4, pp. 1-16.

Description:

The management of change is key to digital transformation projects. Focusing on the context of change in the public sector, the dissertation is to identify context, content, processes, leadership and outcomes of digital change initiatives through a structured literature review.

. Fitzgerald, G./Russo, N.L. (2005): "The turnaround of the London Ambulance Service Computer-Aided Despatch system (LASCAD)", in: European Journal of Information Systems, Vol. 14, No. 3, pp. 244-257.

. Kreutzer, R.T./Neugebauer, T./Pattloch, A. (2018): "Change Management: Shaping Change Successfully", in: Kreutzer, Ralf T./Neugebauer, Tim/Pattloch, Annette (eds.): Digital Business Leadership. Digital Transformation, Business Model Innovation, Agile Organization, Change Management. Berlin: Springer, pp. 197-218.

. Kuipers, B.S./Higgs, M./Kickert, W./Tummers, L./Grandia, J./van der Voet, J. (2014): "The Management of Change in Public Organizations: A Literature Review", in: Public Administration, Vol. 92, No. 1, pp. 1-20.

This master thesis looks into the requirements for trustworthy methodology design and applies these in a benchmarking study to various approaches now proposed for value-based/ethical system design; including e.g.  z-inspection, Value Sensitive Design, Ethical Canvas, etc.

//This master thesis project would need to be conducted by a non-German/Austrian student (ideally from Asia, Eastern Europe, USA, Middle East or Africa)//

A questionnaire-based study on our posthuman future would need to be conducted for this master thesis in the home-country of the student and results statistically analyzed and compared with the German/Austrian sample that is already collected.

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