Estimating the loss of economic predictability from aggregating firm-level production networks.

To estimate the reaction of economies to political interventions or external disturbances, input-output (IO) tables-constructed by aggregating data into industrial sectors-are extensively used. However, economic growth, robustness, and resilience crucially depend on the detailed structure of nonaggregated firm-level production networks (FPNs). Due to nonavailability of data, little is known about how much aggregated sector-based and detailed firm-level-based model predictions differ.

Communication between Autonomous Vehicles and Pedestrians: An Experimental Study Using Virtual Reality.

One of the major challenges of autonomous vehicles (AV) is their interaction with pedestrians. Unofficial interactions such as gestures, eye contact, waving, and flashing lights are very common behavioral patterns for drivers to express their intent to give priority. In our research we composed a virtual reality experiment for a pedestrian crossing in an urban environment in order to test pedestrians' reactions on an LED light display mounted on a virtual AV.

A Creative Concept to empower office workers addressing work-related health risks.

Among office workers, the sedentary work-related health challenges are mainly associated with the fact that they often sit for up to 10 hr a working day. Members of the Research Group conducted a research program to assist the office workers of an international telecommunication company's affiliate in Budapest to enhance comfort levels in the office work environment. The data collection included a Comfort Survey to reveal employees' sense of comfort related to Indoor Environmental Quality (IEQ) components and the characteristics of employees' feelings and behavior during working hours.

Quantifying firm-level economic systemic risk from nation-wide supply networks.

Crises like COVID-19 exposed the fragility of highly interdependent corporate supply networks and the complex production processes depending on them. However, a quantitative assessment of individual companies' impact on the networks' overall production is hitherto non-existent. Based on a unique value added tax dataset, we construct the firm-level production network of an entire country at an unprecedented granularity and present a novel approach for computing the economic systemic risk (ESR) of all firms within the network.

Application of Bivariate Extreme Value models to describe the joint behavior of temporal and speed related surrogate measures of safety.

Limitations of historical crash data and the advantages of surrogate measures of safety have already been stressed by various authors. To describe nearness-to-collision, mostly time-based indicators are applied, and there is a consensus among researchers that speed-related indicators are needed to account for the severity dimension. There have been attempts to fit bivariate Extreme Value models to predict the number of crashes, however modeling crash frequency together with severity has received much less attention.