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Information Systems and Applied Computer Sciences

Information Systems and Energy Efficient Systems

  1.  University of bamberg
  2. Faculties
  3. Information Systems and Applied Computer Sciences
  4. Subject groups
  5. Information Systems
  6. Information Systems and Energy Efficient Systems
  7. Team
  8. Dr. Konstantin Hopf

Dr. Konstantin Hopf

Room: WE5/02.062

Phone: +49 951 863 2236

Fax: +49 951 863 5077

Email: konstantin.hopf(at)uni-bamberg.de

Consultation hours by appointment

Google Scholar | Researchgate | LinkedIn

Academic Career

  • 2019 - today: Lecturer and Senior Researcher (Akademischer Rat a.Z.) at the Chair of Information Systems and Energy Efficient Systems, University of Bamberg
  • April 2019: PhD defense with grade summa cum laude; topic of the dissertation: "Predictive Analytics for Energy Efficiency and Energy Retailing"
  • 2018 (Feb - Apr): Teaching and research stay at the Copenhagen Business School, Department of Digitalization
  • 2014 - 2019: Senior Analyst and PhD student at the Information Systems and Energy Efficient Systems Group, University of Bamberg and member of the Bits-to-Energy Lab, a joint research initiative of ETH Zurich, University of Bamberg, and the University of St. Gallen (www.bits-to-energy.ch)
  • 2014 - 2015: Information Systems (M. Sc.), University of Bamberg
  • 2012 - 2013: Foreign semester at University of Skövde, Sweden
  • 2010 - 2014: Information Systems (B. Sc.), University of Bamberg
    (The Bachelor's thesis received first place in the IT Cluster Oberfranken e.V. graduation award.)

Selected university activities

  • Development and responsibility of the master courses "Business Intelligence & Analytics" (EESYS-BIA-M, V/Ü, 6 ECTS, winter term), "Data-driven Decision Support" (EESYS-DDS-M, V/Ü, 6 ECTS, summer term), master seminar "Platforms of Human-AI Collaboration" (WS 2020/21, 3 ECTS)

  • Supervision of Bachelor and Master theses, as well as student project papers in in Information Systems programs at the University of Bamberg

  • Representative of the scientific staff of the Faculty WIAI in the Faculty Council and the Mittelbau-Konvent (2017-2019 and 2019-2021)

  • Lectureship for the course "Business Intelligence" for master programs Strategic Management and Consulting at CBS International Business School, Mainz (since summer term 2021)

Research Focus

  • Integration of data science, especially (explainable) machine learning techniques, in organizational decision-making processes

  • Field evaluation of predictive models based on corporate and behavioural data

  • Development of novel methods to exploit spatio-temporal data sources with machine learning algorithms (e.g. energy data, sensor data of user behaviour, open data, geographical information, data from social media)

Selected Research Projects

Scientific Contributions

Journal articles (peer-reviewed)

Hopf, K., Müller, O., Thiess, T., Shollo, A. (2023). Organizational implementation of AI: Craft and mechanical work. California Management Review (forthcoming).

Shollo, A., Hopf, K., Thiess, T., Müller, O. (2022). Shifting ML Value Creation Mechanisms: A process model of ML value creation. The Journal of Strategic Information Systems, 31(3), 101734. https://doi.org/10.1016/j.jsis.2022.101734, received JSIS 2022 Best paper award in March 2023

Weigert, A., Hopf, K., Günther, S. A., Staake, T. (2022). Heat pump inspections result in large energy savings when a pre-selection of households is performed: A promising use case of smart meter data. Energy Policy, 169, 113156. https://doi.org/10.1016/j.enpol.2022.113156

Hopf, K., Weigert, A., Staake, T. (2022). Value creation from analytics with limited data: a case study on the retailing of durable consumer goods. Journal of Decision Systems, published online April 07, 2022, DOI: 10.1080/12460125.2022.2059172

Hopf, K., Sodenkamp, M., Staake, T. (2018). Smart Meter Data Analytics for Enhanced Energy Efficiency in the Residential Sector. Electronic Markets, 28(4), DOI: 10.1007/s12525-018-0290-9, received the AIS SIGGREEN 2018 Best Journal Paper on Green IS award in December 2018

Hopf, K. (2018). Mining Volunteered Geographic Information for Predictive Energy Data Analytics. Energy Informatics, 1:4, DOI: 10.1186/s42162-018-0009-3

Monographs

Hopf, K. (2019). Predictive Analytics for Energy Efficiency and Energy Retailing. Dissertation, Contributions of the Faculty of Information Systems and Applied Computer Sciences of the Otto-Friedrich-University Bamberg (36), University of Bamberg Press, Bamberg, DOI: 10.20378/irbo-54833

Conference articles (peer reviewed)

Günther, S. A., Haag, F., Hopf, K., Klose, M., Handschuh, P., Staake, T. (2022). A feedback component that leverages counterfactual explanations for smart learning support: First insights into its empirical evaluation. Proceedings of the DiKuLe Symposium 2022 (forthcoming)

Haag, F., Hopf, K., Menelau Vasconcelos, P., Staake, T. (2022). Augmented Cross-Selling Through Explainable AI – A Case From Energy Retailing. 30. European Conference on Information Systems (ECIS'22), Timișoara: Romania [Full-text]

Wastensteiner, J., Weiss, T. M., Haag, F., Hopf, K. (2021).  Explainable AI for Tailored Electricity Consumption Feedback – An Experimental Evaluation of Visualizations, 29. European Conference on Information Systems (ECIS'21), Marrakesh: Morocco / Virtual, June 14 – 12, [Full-text]

Fteimi, N., Hopf, K. (2021). Knowledge Management in the Era of Artificial Intelligence - Developing an Integrative Framework, 29. European Conference on Information Systems (ECIS'21), Marrakesh: Morocco / Virtual, June 14 – 12 Juni [Full-text]

Weigert, A., Hopf, K., Weinig, N., Staake, T. (2020) Detection of heat pumps from smart meter and open data, 9. DACH+ Conference on Energy Informatics, Sierre, Schweiz,  October 29 – 30, In: Energy Informatics, 3(Suppl 1):21, DOI: 10.1186/s42162-020-00124-6

Stingl, C., Hopf, K., Staake, T. (2018). Explaining and predicting annual electricity demand of enterprises – A case study from Switzerland, 7. DACH+ Conference on Energy Informatics, Oldenburg, Germany, October 11 – 12, In: Energy Informatics, 1:50, DOI: 10.1186/s42162-018-0028-0

Hopf, K., Riechel, S., Sodenkamp, M., Staake, T. (2017). Predictive Customer Data Analytics – The Value of Public Statistical Data and the Geographic Model Transferability.38. International Conference on Information Systems (ICIS), Seoul: South Korea, December 10 – 13.

Hopf, K., Kormann, M., Sodenkamp, M., Staake, T. (2017). A Decision Support System for Photovoltaic Potential Estimation. ACM International Conference on Internet of Things and Machine Learning 2017, Liverpool: UK, October 17 – 18, DOI: 10.1145/3109761.3109764.

Sodenkamp, M., Kozlovskiy, I., Hopf, K., Staake, T. (2017). Smart Meter Data Analytics for Enhanced Energy Efficiency in the Residential Sector. 13. Conference on Wirtschaftsinformatik 2017, St. Gallen: Switzerland, February 12 – 15.

Hopf, K., Sodenkamp, M., Kozlovskiy, I. (2016). Energy Data Analytics for Improved Residential Service Quality and Energy Efficiency. 24. European Conference on Information Systems (ECIS'16), Istanbul: Turkey, June 12 – 15.

Kozlovskiy, I., Sodenkamp, M., Hopf, K., Staake, T. (2016). Energy Informatics for Environmental, Economic and Societal Sustainability: A Case of the Large-Scale Detection of Households with Old Heating Systems. 24. European Conference on Information Systems (ECIS'16), Istanbul: Turkey, June 12 – 15.

Hopf, K., Sodenkamp, M., Kozlovskiy, I., Staake, T. (2015) Household Classification Using Annual Electricity Consumption Data, presented as poster at 4. D-A-CH+ Energieinformatik Konferenz, Karlsruhe: Germany, November 12 – 13.

Hopf, K., Dageförde, F., Wolter, D. (2015). Identifying the Geographical Scope of Prohibition Signs, 12. International Conference on Spatial Information Theory (COSIT), Santa Fe: NM, USA, October 12 – 16. Proceedings in Lecture Notes in Computer Science, DOI: 10.1007/978-3-319-23374-1_12

Hopf, K., Sodenkamp, M., Kozlovskiy, I., Staake, T. (2014). Feature extraction and filtering for household classification based on smart electricity meter data, 3. D-A-CH+ Energieinformatik Konferenz 2014, Zurich, Switzerland, November 13 – 14. In: Computer Science - Research and Development 31 (3), pp. 141-148, DOI: 10.1007/s00450-014-0294-4

Conference talks

Hopf, K., Haag, F. (2020), Explainable AI for enhanced human-AI interaction. Pre-ICIS Practice Development Workshop “AI Beyond the Hype”, Online, December 13

Hopf, K., Constantiou, I., Staake, T. (2020), Directing relationship marketing to the era of AI – How machine learning increases customer data richness. Work in the Age of Intelligent Machines Research Coordination Network Workshop, Online, Deceber 1

Weigert, A., Hopf, K. (2020). Design of cognitive computing systems to support the sales process for durable goods on the example of renewable energy systems, ECIS Workshop on Energy Informatics, Online, June 15

Hopf, K., Fteimi, N., Staake, T., Lehner, F. (2019). The Role of Human Cognition and Mental Capabilities in Setting Up Artificial Intelligence, Pre-ICIS Workshop on the JAIS-MISQE Special Issue on Artificial Intelligence in Organizations, Munich, December 14

Müller, O., Shollo, A., Hopf, K., Thiess, T. (2019) The Pursuit of Data Driven Value Creation in Organizations: A Typology of Data Science Projects and Facilitators in the Value Creation Process, Pre-ICIS Workshop on the JAIS-MISQE Special Issue on Artificial Intelligence in Organizations, Munich, December 14

Weigert, A., Hopf, K., Staake, T. (2019). A Cognitive Computing Solution to Foster Retailing of Renewable Energy Systems, SIGGreen Pre-ICIS Workshop, Munich, December 15

Software Libraries

Hopf, K., Weigert, A., Kozlovskiy, I., Staake, T. (2020). SmartMeterAnalytics: Methods for Smart Meter Data Analysis, Package for the Data Analytics Environment GNU R, https://cran.r-project.org/package=SmartMeterAnalytics

Hopf, K., Weigert, A., Weinig, N., Staake, T., (2020). ResidentialEnergyConsumption: Residential Energy Consumption Data, Package for the Data Analytics Environment GNU R, https://cran.r-project.org/package=ResidentialEnergyConsumption

Book chapters and technical reports

Weigert, A., Hopf, K., Staake, T., Rast, A., Marckhoff, J. (2020). SmartLoad – Smart Meter Data Analytics for Enhanced Energy Efficiency in the Residential Sector, Final project report. Bundesamt für Energie, Schweiz (Online)

Hopf, K., Staake, T. (2019). Methoden der Energiedatenanalyse, Final report for Eurostars Project „Energy Data Analytics: Steigerung der Servicequalität und der Energieeffizienz im Privatkundenbereich“ DOI: 10.2314/KXP:1687331642

Sodenkamp, M., Hopf, K., Kozlovskiy, I., Staake, T. (2016). Smart-Meter-Datenanalyse für automatisierte Energieberatungen ("Smart Grid Data Analytics"), Final project report. Bundesamt für Energie, Schweiz (Online)

Sodenkamp, M., Hopf, K., Staake, T. (2015). Using supervised machine learning to explore energy consumption data in private sector housing. In: Tavana, M. & Puranam, K. (Eds.): Handbook of Research on Organizational Transformations through Big Data Analytics. Hershey, USA: IGI Global, DOI: 10.4018/978-1-4666-7272-7.ch019

Awards and Honors

  • 03/2023: Journal of Strategic Information Systems 2022 Best paper award for the artticle "Shifting ML Value Creation Mechanisms: A process model of ML value creation"
  • 10/2020: Best Paper Nominee Award (9th DACH+ Energy Informatics 2020)
  • 12/2019: AIS 2018 SIGGREEN Best Journal Paper on Green IS für Beitrag "Enhancing Energy Efficiency in the Residential Sector with Smart Meter Data Analytics" in Electronic Markets 28(4)
  • 11/2015: Graduation award of the IT Cluster Oberfranken (first place) for Bachelor thesis

Invited talks and workshops

  • Support retailing of renewable energy systems with (interpretable) machine learning, Guest lecture at the University of Passau, July 07, 2021
  • Predictive Analytics for Energy Efficiency and Energy Retailing, Brown-Bag Seminar Information Systems, University of Passau, June 18, 2019
  • Data analytics with R, Management workshop for utility company representatives, University of Bamberg, April 2018
  • Mining Volunteered Geographic Information for Predictive Energy Data Analytics, PhD Workshop 'Energy Informatics' prior to the 6. D-A-CH+ Energy Informatics Conference in Lugano, Switzerland, October 04, 2017
  • Predictive Analytics in Energy Retail, Doctoral Consortium during the 25. European Conference on Information Systems (ECIS) in Guimarães, Portugal, June 05, 2017
  • Lifting the value of customer data for marketing – Predictive analytics in energy retail, 9. BarCamp Nürnberg, Germany, May 13, 2017
  • Das Internet der Dinge – Experimente mit intelligenten Stromzählern, Workshop at Girls and Technology Day of the University of Bamberg, October 28, 2014
  • Heimat ohne fossile Energieträger realisieren (H.o.f.E.r.) - Raus aus dem Energiestrudel, Neumarkter Nachhaltigkeitskonferenz 2010, June 25, 2010
  • Raus aus dem Energiestrudel, 17. Symposium der Deutschen Bundesstiftung Umwelt (DBU) und der Freunde und Förderer des Zentrums für Umwelt und Kultur, Benediktbeuern, September 29, 2009