Webinars

Date

Speaker

Topic

2025, October 25

Joern Hoppmann, University of Oldenburg

Joaquin Delgado Fernandez, University of Luxembourg

Theoretical contributions in sustainability management studies
In recent years, scholarly work in the field of sustainability management has grown significantly. As in other domains, one of the main challenges for sustainability scholars seeking to publish in leading academic journals is demonstrating a strong theoretical contribution. However, because sustainability research is also intended to address urgent societal challenges, such as climate change, an important question arises: how should researchers balance theoretical rigor with practical impact? In this talk, Joern Hoppmann will explore this dilemma. He will begin by providing an overview of what theories are and how they are applied in management research. Building on this foundation, he will discuss the value and limitations of theories and critically examine their implications for sustainability scholarship. For the Green IS community, this perspective from the management field offers valuable insights and raises key questions about how to reconcile rigorous theorizing with the field’s applied mission of tackling pressing environmental challenges.

Privacy-preserving use of smart meter data

Joaquín Delgado Fernández presents a large-scale smart meter data project in Luxembourg in which the University of Luxembourg was granted access to high-resolution energy consumption data for almost all households in Luxembourg. The core challenge was how to exploit this dataset for useful analysis (e.g., load forecasting, demand response, system optimization) while preserving privacy and security of individuals. He will explain the privacy-preserving and data governance design choices (e.g., differential privacy, aggregation, secure computation, anonymization protocols) and reflect on trade-offs between data utility and confidentiality. The discussion is particularly relevant to the Green IS community, as it exemplifies how information systems research can responsibly handle “big energy data” for sustainability applications.

2025, April 9

7am EDT

(1pm Central European Time; 9pm Australian Eastern Standard Time)

Dirk Hovorka, University of Sydney

Jiyong Park, University of Georgia 

Dirk Hovorka is engaged in the field of Future Studies and has promised to provoke a few thoughts on where Green IS might or should be heading next.

Jiyong Park has recently been awarded the SIG Green Best Paper Award and will present his paper on “Green cloud? An empirical analysis of cloud computing and energy efficiency”.

2024, October 28

2pm EDT

Julia Kotlarsky, University of Auckland 

Ali Y Shaheen, Dakota State University

Digital Sustainability: Julia Kotlarsky is a Professor of Information Systems at the University of Auckland Business School and is conducting research on digital sustainability. Building on her recent work and her engagement with the topic, Professor Kotlarsky will explore the critical role of digital technologies in advancing sustainability objectives across environmental, social, and economic dimensions. She argues that digital sustainability extends beyond the environmental impact of IT systems to include broader economic and social dimensions, emphasizing the role of digital artifacts, data, and AI in driving sustainability outcomes. Her analysis connects the fields of Green IS and Green IT with contemporary digital innovations, illustrating how digital solutions can address global sustainability challenges, from resource optimization to new business models. She will further discuss her current research projects in the field and give important insights on her perspective of the field.

Weed Detection using Lightweight DL models with Transfer Learning & Hyperparameter Optimization: Weeds significantly reduce agricultural yields. Professor Shaheen's study focuses on using artificial intelligence, specifically deep learning, for early-stage weed detection on edge devices, which have limited computational power. it proposes a three-part strategy to address this challenge: employing lightweight architectures (LWA's) to reduce the model size and computational demand; using transfer learning to overcome the limitations of small data sets; and applying Bayesian optimization to fine-tune model parameters. The results show that MobileNetV2 and EfficientNetV2B0 models achieve high accuracy (95.09% and 95.79% respectively) with MobileNetV2 being nearly as accurate but much smaller in size (13.96 MB compared to 23 MB). The lightweight architectures utilized in this study surpassed the previously best-performing state-of the-art ResNet152V2 model. This demonstrates LWA's suitability for computationally constrained edge devices, promoting energy efficient and resource saving methods for weed detection.

2021, June 29

Jason Dedrick (Syracuse University)

Information Technology Investment and Carbon Intensity: A Cross-National Study

2021, June 29

Petruska de Araújo Machado (Federal University of Campina Grande) and Roya Gholami (University of Illinois Springfield)

Green Information Systems Adoption: An Integrative Framework Based on Literature Review Grounded in Design Science and Future Research Directions

2021, March 29

Bo Nørregaard Jørgensen (University of Southern Denmark)

Smartgrid Integration of Commercial Greenhouses

2021, March 29

Roman Zeiss (University of Cologne)

Circular Coordination: Towards a Sociomaterial Theory on Information Systems for a Circular Economy