Abstract There is an increased relevance of non-routine creative work. The use of virtual teams within organizations comes along with communication and coordination challenges for the case of creative work in particular. We focus on the creative performance of newly formed virtual dyadic teams and investigate performance differences compared to individuals working virtually on a creative task. We conducted an online lab experiment, accounting for a work-from-home environment, comprising two working phases one week apart, extending the common focus on one-shot interactions. We make use of Unusual Uses Tasks (UUT) to assess creativity of dyadic teams and individuals. Given that this task is typically used at the individual level, our study contributes to the field of creative experimental tasks by implementing the UUT in a team setting with direct interaction and a virtual workplace. Our findings show that dyadic teams exhibit significantly higher creative performance than individuals across the two virtual phases hinting for the meaningfulness of the UUT approach on the group level. Additionally, we check for mechanisms exploring the performance differences between individuals and teams working on this creative task with regard to heterogeneity in performance, the role of errors next to productive performance as well as the role of trust and sympathy within teams.

Abstract Green hydrogen is a crucial component in the transition to a low-carbon economy. However, large-scale production is limited by geographical conditions in many regions, which requires hydrogen imports to meet demand. To ensure supply security and avoid dependence on singular exporters, sourcing from multiple regions within a diversified import network is essential. This study presents a mixed-interger linear programming (MILP) model that determines an optimal import network for green hydrogen, considering diversification constraints and liquid hydrogen losses during transport due to boil-off. Our case study, focusing on the diversified import of green hydrogen to Germany, reveals that production and conversion operating costs dominate the overall cost structure and transporting hydrogen as ammonia is the most cost-efficient option in most cases. Further analysis indicates that enforced diversification increases total costs and influences the structure of the import network. Lastly, we demonstrate that reducing the boil-off rate of liquid hydrogen during transport may lead to liquid hydrogen being a more cost-effective carrier than ammonia.

Abstract We investigate the behavior of stocks after the launch of Netflix’s scandal documentaries on the corresponding firms. We document a significant fall in prices after the release of the documentaries that is not reversed in the weeks following their launch, resulting in an average cumulative abnormal return of −15.34% three months after the event day. We also find a significant increase in stocks’ traded volumes and Google Search Volumes for the corresponding firms after the release of the documentaries. Moreover, we report a significant contemporaneous and lagged relation between stocks’ returns and traded volumes in the event window that is not seen before the release day. Taken together, these results suggest that the fall in stock prices is driven by investor attention. Our findings have significant implications for corporate misconduct and how market participants become informed and consequently price this behavior.

Abstract The rapid digitalization of organizations necessitates a re-evaluation of managerial competencies to effectively lead virtual and hybrid teams. This paper introduces the concept of Digital Managerial Competencies (DMC), a comprehensive framework delineating the specific skills and knowledge managers require to navigate the digital workplace successfully. Building on the DigComp framework and grounded in a systematic literature review of 48 peer-reviewed studies, the research identifies three core dimensions of DMC: Technological Knowledge, Soft Skills, and Management & Leadership Skills, comprising 18 specific competencies. The study employs inductive content analysis to develop and validate the model, further enriched through focus group feedback with practitioners. The findings contribute to theory by offering a multidimensional, context-dependent understanding of digital managerial effectiveness and practical guidance for developing targeted training programs. The DMC framework provides a valuable tool for scholars and organizations to assess, develop, and leverage managerial competencies in the evolving digital landscape, ultimately enhancing virtual team performance and organizational outcomes.

Abstract The global transition to hydrogen as a sustainable alternative fuel is ongoing, owing to its ability to decarbonize the hard-to-abate industries of mobility. However, barriers to adoption still exist, and enabling solutions are needed. This study explores barriers and enabling solutions, in terms of infrastructure development, operational requirements, and supply chain demands, to the large-scale adoption of hydrogen technologies in road, maritime, and aviation transport industries. By means of a systematic literature review, reinforced by industry perspectives gathered from a survey of Italian professionals, common barriers are identified together with those specific to each industry. These include barriers related to fuel (e.g., clean energy sourcing for production), infrastructure (e.g., location and geographical dispersion of refueling), vehicle (e.g., availability of low-cost components), and operations (e.g., availability of refueling). Potential enabling solutions to lower them are explored (e.g., innovations, economies of scale, development of pilot projects). One possible development of the industry is a gradual shift toward modes of transport that are considered better suited to hydrogen technologies. The study assists policymakers by outlining the next steps to take for decarbonizing transportation, with actions aligned with a prioritization that identifies infrastructure as the starting point.

Abstract The Eurosystem’s asset purchase programmes reduced the free float of German Bunds. We study the intended and unintended consequences of asset purchases in the repo market involving Bund collateral. Bunds that are eligible for purchases carry a repo specialness premium even when they are not purchased. This “eligibility premium” is larger than the actual flow effect of purchases. The Bundesbank’s securities lending operations have a flow effect. The effects of purchases and securities lending on repo specialness are relatively small compared to those caused by banks window dressing their balance sheets and by hedging pressure for Bund Futures.

Abstract Nowadays, choice modelling based on stated choice data is widely used for assessing consumer preferences, with the hierarchical Bayes multinomial logit (HB-MNL) model being typically embedded as choice model for preference estimation. The HB-MNL model accounts for individual preference heterogeneity and is therefore able to weaken the Independence of Irrelevant Alternatives property (IIA) the standard MNL model suffers from. The IIA property states that the ratio of choice probabilities of two alternatives remains constant independent of the availability of further alternatives and hence implies an often unrealistic proportional substitution pattern among alternatives. The IIA property can also be addressed by applying nested multinomial logit (NMNL) models, which explicitly allow for a representation of different degrees of similarity between subsets of alternatives (nests). In this paper, we consider a HB-NMNL model which combines both the idea of nested market structures and heterogeneous consumer preferences with the expectation to handle the IIA property even better. We propose an extensive simulation study in which we compare the performance of the established HB-MNL model to the HB-NMNL model under varying experimental conditions for model fit, prediction accuracy, and parameter recovery. Our findings from this Monte Carlo study are twofold: first, both types of models perform rather close with regard to predictive validity (and model fit). This result is quite surprising and provides strong support for the use of the less complex HB-MNL model. Second, as could be expected, the HB-NMNL model shows advantages in terms of parameter recovery which is an important criterion for product design decision-making. We further present results from applying and comparing both models in an empirical study for summer tires. Model estimation is carried out using the publicly available R software package RSGHB .