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Intro

All seminars will take place in room 4.02 in Pohligstraße 1, 50969 Cologne, starting at 12.00 unless noted otherwise.

Talks are organized as brown bag seminars, so please join us for catered sandwich lunch and cold beverages. Everybody interested is welcome to attend the sessions! If you have questions, please send an email to werder(at)wiso.uni-koeln.de.

Currently planned seminar talks (speakers and order may change on short notice):

Talks

Research Seminar Series Winter 23/24
Date Speaker Title & Abstract

Sept, 19th 2023

Thursday

Brian Pentland

(University of Michigan

Title: From points to paths: Two papers about path theory

Abstract:  Paths are coherent, temporally ordered sequences of actions or events. In this talk, I plan to discuss two papers that use the concept of paths. The first paper is a quantitative analysis about the tendency of paths to form and persist after a disruption. In that paper, we use data from an Electronic Health Record system to show that coherent paths are up to 14 times more likely to persist and up to 40 times more likely to form than less coherent paths in the narrative networks that represent outpatient clinical routines.  We argue that path networks have implications for inertia and resilience. The second paper is a theoretical discussion of the systemic nature of temporal structuring in practice.  The central idea is simple: when paths intersect, it creates temporal interdependence, which has a powerful influence on the timing of activities along a path and therefore, the Eigenzeit of the path. To theorize about this process, we introduce the concept of a path network, which emerges from intersections between paths as they are enacted.  It is useful to discuss these papers together because they fit in a larger perspective on paths, path networks and path theory.

Oct, 19th 2023

Tuesday

Christoph Schneider (IESE Business School)

Title: Contextualizing Collective Efficacy in Virtual Team Research: The Essential Role of Collaborative Technologies in the Virtual Team Efficacy Conceptual Framework

Abstract: Collaboration among geographically dispersed individuals has proven effective in solving organizational and societal challenges; following the increase in virtual teamwork during the COVID-19 pandemic, the use of virtual teams has become permanent. While collaborating virtually offers many opportunities for organizations, challenges remain in fostering optimal performance of virtual teams. One factor that has a strong influence on the performance of teams (across a variety of settings) is collective-level efficacy, i.e., a team’s shared belief in its collective abilities to work effectively. However, research on collective-level efficacy in traditional teams does not consider the crucial role of collaboration technologies in virtual teams. Conversely, research on virtual teams in information systems largely ignores the impact of collective-level efficacy. To this end, we seek to gain a deeper understanding of the impact of virtual team efficacy (VTE)—a collective-level efficacy measure that incorporates the role of technology—on virtual team outcomes. Analyzing data from a field study involving 42 virtual teams from Hong Kong, Taiwan, and the United States, we found that VTE positively influences virtual team effectiveness by increasing team members’ trust and decreasing their perceptions of problems associated with common collaboration inhibitors, in particular time difference, geographical separation, and cultural differences. Our results 1) contribute to the virtual team literature by providing a deeper understanding of how VTE influences virtual team outcomes and 2) inform managers about the crucial need for considering the role of collaboration technologies in fostering virtual team efficacy to maximize outcomes of virtual teams.

Oct, 31st 2023

Tuesday

Philipp Staudt (University of Oldenburg)

Title: The Effect of Digital Monitoring Technology on the Energy Efficiency Gap

Abstract: Households often underestimate the impact of investments in energy efficiency relative to the potential of behavioral change. This might be caused by low energy literacy, i.e., a lack of understanding of the personal energy consumption behavior. It is therefore plausible that digital monitoring technology that affords access to real-time consumption data changes the attitude towards energy efficiency. In an exploratory study, we conduct an online experiment to measure the effect of salient consumption information on the willingness to invest in energy efficiency. The results can support policy makers in designing programs to promote energy efficiency in households.

Nov, 14th 

Tuesday

John Collins (University of Minnesota

Title: Storing energy, from hours to months: from batteries to hydrogen

Abstract: If we are going to transition our electric power grid away from fossil fuel power plants, we will need to either (a) quickly ramp up our investments in hydro and nuclear power, or (b) fundamentally change the way we think about ?keeping the lights on?. We will discuss the various storage technologies, including various types of flexible demand in homes and businesses. It is becoming increasingly clear that we need energy storage that can deliver stored energy over minutes, hours, days, and months. We will survey the options and their characteristics, with a focus on using hydrogen for months-long ?seasonal? storage. We will also briefly discuss the problem of deciding when to add energy to the various types of storage available on the grid, a rich source of open research questions.

Jan, 9th

Tuesday

Kai Nagel (TU Berlin)

Title: Full decarbonization of Berlin's traffic: simulation studies and political reality

Abstract: Electrification of taxis would not have caused any additional costs even 10 years ago.  Electrification of waste collection would lead to approx. 20% higher waste collection charges.  A significant improvement of local public transport would (only) reduce the number of car journeys by around 10%.  Based on these and other results, we are developing possible scenarios for CO2-free transport in Berlin.   The results are transferable to other urban areas; we also have results for rural areas.  We then discuss these scenarios with a citizens' council.  This results in feasible decarbonization paths for transport subsystems.  However, there is little consensus in the area of private passenger transport.

Jan, 23th 2024

Tuesday

Aaron Schecter (University of Georgia)

Title: The Role of Uncertainty in Algorithmic Decision Making

Abstract: Humans are increasingly making decisions with the aid of algorithms for tasks such as forecasting, price estimation, and text generation. In some cases, people have exhibited algorithmic aversion, or a tendency to disregard potentially accurate advice from an algorithm. In other cases, the reverse is true, and humans display algorithmic appreciation, accepting algorithmic advice even if it is sub-optimal. Prior work has focused on the role of task type in determining aversion or appreciation or has considered an individual's agency in the decision-making process. In this workshop, we present the results of two experimental studies designed to highlight the role of uncertainty in shaping these preferences. In the first study, we explore how individuals react to AI when they are part of human-agent hybrids, namely groups of multiple humans and potentially multiple AI. These hybrid forms are unique in that advice is often given simultaneously, i.e., a human decision maker evaluates advice from other humans and algorithms at the same time. The decision maker must then differentiate between the human and AI sources and render a judgement. In the second study, we posit that certain latent preferences can explain these decisions, i.e., that algorithmic aversion and appreciation are not purely behavioral tendencies. We introduce two constructs related to individuals' tolerance for uncertainty and sensitivity to the source of uncertainty and measure them across three different experimental tasks. Collectively, the studies point to the role of uncertainty in human decision-making with AI and suggest that both individual preferences and situational context can drive the observed behaviors.