Internal Research Seminars

Our cleantech startup strategy research examines how cleantech start-ups cope with resource constraints while pursuing both economic and environmental objectives. We focus on how firms can achieve balanced growth without mission drift. Building on bricolage theory, we conceptualize firms’ responses as configurations of hybrid harvesting strategies, including partnerships, networking, local resource utilisation, customer empowerment, and inclusive employment. Using fuzzy-set Qualitative Comparative Analysis (fsQCA) on data from a questionnaire survey and qualitative interviews with cleantech start-ups, we explore how different strategy configurations perform under varying resource constraints. The research is conducted within the project “Resilience and impact of clean-tech start-ups in Bavaria and the Czech Republic” in collaboration with the Technical University of Munich. Preliminary findings suggest multiple pathways to balanced growth, but also configurations associated with mission drift, indicating that outcomes depend on both strategy combinations and the context in which they are applied.

We consider the problem of identifying the optimal subset of past observations to be used for estimating the covariance matrix of asset returns when computing the global minimum variance portfolio. While the usual approach simply employs either all the available past returns or a rolling window of fixed size, we argue that such solutions are inefficient, and we instead propose to dynamically adjust the estimation window. To this end, we employ the PELT changepoints detection algorithm to identify outdated observations. We then set up a cross-validation procedure to determine the minimum number of upto-date observations that individual assets must have to be considered when estimating the covariance matrix. Assets that do not reach the selected threshold are excluded from the optimization and assigned equal weights. In an empirical application, our solution achieves a higher Sharpe ratio compared to both an expanding and rolling window estimation of the global minimum variance portfolio, and it also compares well with other benchmarks.

In 2025, a survey of 8,000 students and employees at ten Czech universities analysed commuting behaviour using a logit model of mode choice. Public transport dominated (47%), followed by car (32%) and walking or cycling (21%), with higher car use among employees and higher-income respondents. Distance, age (non-linear effect), and children significantly increased the likelihood of car use, particularly beyond 10 km. Differences across universities reflected urban size and topography, with higher public transport shares in large agglomerations. Key barriers to sustainable mobility were habits, distance, and public transport quality, while faster connections, lower costs, improved cycling infrastructure, and limited parking were identified as main drivers of modal shift.

Do people think enough before acting? We study this in a first laboratory experiment where participants can either use a known but tedious method or search for a more efficient strategy whose existence they are made aware of, but whose nature is not disclosed. We exogenously induce early search through a "Freeze" intervention, where participants must spend 90 seconds studying solved example sequences from which the efficient strategy can be inferred. In the "No Freeze" condition, participants see the same examples but are free to move on to the task immediately. We find that Freeze significantly increases discovery rates, however not uniformly across specifications, and leads to more efficient task performance conditional on discovery. At the same time, given our calibration of time horizon and task difficulty, Freeze does not improve overall performance, as the gains from discovery are insufficient to offset the time spent searching. Conditional on discovery, outcomes are similar between the two conditions, while unsuccessful search reduces the overall output in "Freeze" due to lost time. These results highlight a trade-off between exploration and exploitation: forcing individuals to think before acting can backfire when the probability of discovering a better strategy is low or when too little time remains to exploit the discovery. The talk concludes with follow-up ideas on why individuals fail to search and how to better target efficient exploration.

Optimism—the expectation that future events will be better than they actually are—is a widely spread cognitive bias. How can this bias survive? Previous studies have mostly claimed that it survives because it benefits the optimist. However, I show that optimism may have evolved not to benefit the optimist but her family or community, who share her genes. I present an agent-based simulation model in which optimism serves as a proactive/pro-exploratory bias, leading the optimist to explore more opportunities than an unbiased individual. This may harm the optimist herself, but it benefits her relatives who can learn from, imitate, or benefit from her explorations in other ways. In this way, kin selection can explain the origin and persistence of optimism.

The predictive power of the variance risk premium (VRP) for realized volatility depends critically on aligning the maturity of the option-implied variance measure with the forecast horizon. We exploit the CBOE's progressive expansion of the SPY option expiration calendar — from weekly Friday expirations through Wednesday and Monday additions to daily expirations in 2022 — as a natural experiment. Using SPY options from 2013 to 2025, we construct two VRP measures: one restricted to Friday-expiring weekly options (replicating the pre-expansion constraint) and one using the best-available expiration. Within a nested HAR framework evaluated across one-, five-, and ten-day horizons, we find that VRP inclusion reduces out-of-sample mean squared prediction error by 12–18%, with additional significant gains from maturity alignment concentrated at short horizons and in the post-2022 daily-expiry regime. Statistical improvements are corroborated by realized utility gains. Our findings establish a direct link between exchange design decisions and forecast quality.

Our research focuses on the area of brownfield revitalisation, examining its potential impact on surrounding residential areas as reflected in property price changes and residential preferences and expectations. The crucial research objective of our study is to determine whether the relevant brownfield neighbouring inhabitants are rationally anticipating property price changes determined by brownfield regeneration, as reflected in real property transactions, and furthermore whether the residents consider the property price increase as a decrease in accessibility of residential housing. We use the data on 63 brownfield revitalisation levels in the city of Brno in Czechia from 2013 to 2025 with an a minimum area of the brownfield larger than 0.5 ha. We accompany these data with property price transactions from 2013 to 2024, comprising 38,418 property transactions. Consequently, we have surveyed the residential expectations via a field survey including 251 residential respondents. Using the hedonic pricing model, our results show that the property prices in the neighbourhood of brownfields are strongly affected by the brownfield site, but the level of brownfield revitalisation has a significant positive impact on property prices in the residential neighbourhood. The positive impact on prices is potentially strengthened by future brownfield use for offices, not for residential areas. Most residents anticipate a property price increase, but even more, they expect a higher level of accessibility to housing. Thus, the existence of new available flats is a stronger expectation compared to a price increase that affects housing accessibility oppositely. Thus, the residents show relatively ambivalent expectations on revitalisation of the long-term effects.

Inaccurate inference about economic policy uncertainty affects international investment returns, and investment decisions made with imperfect information result in financial losses for all market participants. The classic widely used Baker et al. (2016) index of economic policy uncertainty (EPU) suffers from methodological imperfections in construction due to (1) neglecting semantics, (2) data quality fluctuations, and (3) ignoring tonality/emotion in the data. In this paper, we introduce a novel emotion-based economic policy uncertainty index that (i) improves the semantic identification of economic policy by extracting a large set of tokens from RoBERTa, (ii) uses a vast CC-News media dataset, and (iii) identifies uncertainty by a finetuned emotion recognition model.

This study examines whether bid advantages can stimulate innovation by comparing bonus-based incentives with prize-and-penalty schemes. We conduct a controlled laboratory experiment with two sequential stages. In the innovation stage, participants choose an R&D investment level; in the auction stage, they compete for a procurement contract in a second-price auction. We implement three treatments: a benchmark with no incentive, bonus scheme, and prize-and-penalty scheme designed to be payoff-equivalent to the bonuses. While bonuses operate within the auction stage by rewarding the innovator and disadvantaging the non-innovator, prize-and-penalty schemes shift these incentives to the innovation stage, thereby removing auction distortion and reducing uncertainty. We test whether these mechanisms generate different levels of innovation and whether the timing and framing of incentives affect behavior, particularly through sunk-cost bias.

This study evaluates the impact of the 2018 mandatory transition to electronic prescribing in the Czech Republic. Leveraging administrative registry data on medical prescriptions and dispensations, we analyze the reform’s influence on the spatial relationship between prescribing physicians and dispensing pharmacies-specifically focusing on changes in patient travel time. Furthermore, we examine potential heterogeneous effects across different age cohorts and regions.

Systematic reviews show that multinationality is measured in many ways, yet these measures are often treated as equivalent. This study conducts a systematic literature review of multinationality metrics used since the 1960s and maps their operationalizations across empirical, theoretical, and review articles. Building on and extending Vaněk’s (2024) framework, the metrics are classified by construct, dimension, indicators, segmentation, and format, revealing substantial conceptual and structural differences behind similar-looking measures. Selected metrics are then empirically compared using Taiwanese firm data to show how they lead to conflicting assessments of internationalization. The study explains why multinationality is difficult to measure consistently and offers a structured basis for selecting and interpreting metrics in future research.

Using household-level survey data on 22 European countries collected in four waves between 2010 and 2022, we document the distributional effects of borrower-based macroprudential measures (BBM). We find that the tightening of the BBM significantly reduces the availability of mortgages for lower-income households, leading to increased reliance on renting. Regulation works not only through the extensive margin by cutting off risky borrowers from the mortgage market, but also through the intensive margin by reducing the average loan amount of households with lower incomes. This reduction in risk has the positive side effect of lower borrowing costs, benefiting mainly households with above-average incomes. The easing of BBM, observed in several countries, does not yet fully reverse these effects.

This study explores the spatial logic behind the distribution of grocery retail chains in urban environments, with a particular focus on spatial clustering, accessibility, and the structural influence of the street network. Using Brno, Czech Republic, as a case study, the research examines the location patterns of national and multinational grocery chains through Geographic Information Systems and advanced spatial analytical methods. The findings demonstrate that grocery stores exhibit significant clustering shaped by population density and the urban structure. Clear differences in spatial organisation emerge: national chains are primarily concentrated in central and inner-city neighbourhoods, while multinational chains display a broader spatial reach, particularly along highly connected transportation corridors. Multinational stores also show a stronger dependence on street network centrality, highlighting the role of urban connectivity and mobility flows in their location strategies. The study contributes to a deeper understanding of urban retail dynamics and offers insights for municipal planning, retail development, and commercial investment decisions.

Prejudice and social distance have long been the topic of research in the social sciences and are significantly linked to the majority's relationship with various minorities, particularly ethnic groups. In this study, we explore how the attitudes of the majority population towards the Roma differ according to the intensity (degree) and types of contact with Roma individuals. The theoretical framework is grounded in contact theory, which emphasizes the role of intergroup interactions in reducing prejudice. Recent research shows the importance of the context and the type or form of contact, which can significantly influence prejudiced attitudes. Based on these research findings, we analyze whether the acceptability of interactions with the Roma in the Czech context differs depending on various types of interethnic contacts. Descriptive analysis reveals a slight correlation between the intensity of contacts and its acceptability. However, advanced latent class analysis (LCA) indicates that this relationship is not uniform (one-dimensional). We identified four distinct social groups differing in both their interethnic contact patterns and affective attitudes toward the Roma. These results emphasize that when testing the contact hypothesis, it is important to consider not only the intensity but also the types of interethnic interactions.

We examine parental willingness to pay (WTP) and willingness to accept (WTA) for human papillomavirus (HPV) vaccination in a survey experiment conducted with 3,694 parents in the Czech Republic. Respondents indicated the maximum payment they would make, or the minimum compensation they would require, to state an intention to vaccinate their 14-year-old daughter in a hypothetical decision scenario. In a between-subjects design, we varied (i) the stated population-level effectiveness of the vaccine across three levels and (ii) the rules governing a bonus payment, comparing unconditional rewards with rewards paid only if overall vaccination uptake surpassed a predefined threshold. We find no significant effect of bonus-payment rules on either WTA or WTP. Relative to a baseline effectiveness level, the lowest vaccine effectiveness significantly reduces willingness to pay, whereas a moderate increase in effectiveness yields no significant change. Even in the highest-effectiveness condition, 16% of parents would not vaccinate their daughter even when offered a hypothetical reward exceeding the equivalent of two average monthly wages. These results point to substantial residual resistance to HPV vaccination and motivate further investigation—planned in follow-up data collection—into whether reluctance is heightened when decisions are made on behalf of others rather than for oneself. 

Exogenous shocks pose critical challenges for incumbent firms, necessitating strategic adaptations to ensure survival and subsequent performance recovery. This paper investigates the strategic responses of U.S. airlines to seven significant exogenous shocks that occurred between 1979 (the Second Oil Crisis) and 2020 (Covid-19). Using Coincidence Analysis (CNA), a configurational comparative method, we identify causal patterns linking response strategies to short-term and long-term performance success. Specifically, we found that Perseverance (keeping status quo) is a strategy that generally pays off in the short term. However, this early success does not translate into long-term success. Airlines that were successful in the long term instead pursued Retrenchment strategy (in high impact shocks) or Innovation strategy (in low impact shocks).

Geographic disclosure practices of multinational enterprises (MNEs) are shifting from vague, management-driven segment reporting under standards such as IFRS 8 to the emerging system of standardized, mandatory public Country-by-Country Reporting (CbCR). Driven primarily by initiatives in the European Union (EU) and Australia, the shift promises a breakthrough for International Business (IB) research by providing unprecedented, country-level data on revenues, employees, and taxes. Using the Five Key Aspects framework of measuring firm-level multinationality, it is argued that public CbCR will reshape how we measure multinationality, test key IB concepts such as the relationship between multinationality and performance, and define geographic regions. However, limitations persist, including the limited geographic coverage of the EU directive and the absence of a centralized data repository.

This paper examines the paradoxical role of the Czechoslovak secret police (Státní bezpečnost, StB) as a “toothless watchdog” in the socialist economy. Using unique archival records from the StB’s surveillance of the industrial enterprise ZVVZ Milevsko (1975–1989), it reveals how the StB uncovered extensive economic fraud, plan manipulation, and corruption—but consistently refrained from enforcement. The analysis reframes the classic principal–agent problem by adding a third actor, the monitor, and shows that political priorities rather than information deficits shaped outcomes. The StB’s inaction reflected a deliberate policy of “knowing non-enforcement,” serving the Communist Party’s goal of maintaining the façade of plan fulfillment and stability. This case exposes how the institutions of control became instruments of systemic dysfunction, normalizing deviance as part of everyday governance. The findings offer new insight into the political economy of late socialism and the logic of authoritarian monitoring.

We study how targeted educational incentives shape human capital formation, educational trajectories, and labor market outcomes. Exploiting a nationwide reform in Norway that removed bonus credits from university admission scores for taking science and advanced specialization courses in high school, we provide novel evidence of how marginal changes in course-level incentives affect students’ academic decisions and long-run career paths. Using population-wide register data and a dose-response difference-in-differences design, we show that students respond by dropping science and specialization courses in favor of easier subjects. This shift leads to slightly higher high school grades but lowers overall admission scores, reducing access to selective college programs. Affected students are subsequently less likely to complete STEM college degrees and pursue master’s degrees. We also find moderate but economically meaningful reductions in expected earnings at age 35. To understand behavioral responses, we conducted a novel survey of high school students, which reveals that decisions about courses are shaped by perceived difficulty and information gaps, with the strongest responses among high-achieving students. Our findings demonstrate how seemingly small changes in education policy can alter the supply of skills, shape long-run labor market outcomes, and affect inequality in access to opportunity.

We examine the determinants of zombie firms in Slovakia using almost 500,000 firm–year observations. Zombie status is identified under two definitions (Favara and Storz), and we apply cost-weighted logistic regression, double machine learning, and heterogeneity analysis by sector and firm size. We find that financial performance is decisive – low returns on assets, low efficiency, low effective tax rates, and high reliance on tangible collateral significantly increase the probability of zombification. Governance factors play a secondary but still relevant role. Foreign ownership and multiple directors raise zombie risk, while owner–director overlap consistently lowers it. These effects are concentrated in small firms, particularly in manufacturing and services sectors, whereas large firms show weaker patterns. Finally, the choice of definition matters – under Favara, governance effects are largely absent, but under Storz, they become substantial and policy-relevant. Our findings suggest that regulators and lenders should monitor both financials and governance, especially in small firms with high collateral, to limit resource misallocation and reduce zombie survival.

Standard fairness preference measures involve spectators redistributing between workers whose inequality stems from merit or luck. We show that these measures are influenced by participants’ prior redistributive decisions. In a laboratory experiment, we vary whether participants first make their redistributive decision in the merit-based or luck-based setup. On a representative UK sample (N = 1418) we find that measured merit premia — the extent by which inequality is tolerated more when generated by merit as opposed to luck — is 55% higher when the first decision is in the luck-based setup. We argue that anchoring to previous choices is unlikely to be the primary explanation for this effect. The effect implies that the same participant can appear more or less tolerant of inequality depending on the sequence of their decisions. Beyond shifts in measured inequality tolerance, choices influence participants’ measured ideological stance. Specifically, the treatment changes the share of participants appearing libertarian by one-third of the estimated US-Norway difference in the literature. In addition to offering valuable insights for experimental design, our aim is to bolster further research on how prior experiences shape fairness perceptions.

Human papillomavirus (HPV) infections are estimated to cause over 600,000 cancers annually worldwide. Our study aims to identify the effect of the monetary subsidy on HPV vaccination uptake. Although we cannot manipulate the public insurance contribution directly, we provide information on the out-of-pocket price of the vaccine to correct misconceptions and generate exogenous variation in perceived vaccination costs. We conducted a survey experiment with two treatment arms. In the control group, participants were asked about their intentions to vaccinate their child against HPV. In the information treatment group, participants were informed that the out-of-pocket price is zero for children aged 11 to 14 years before being asked about their vaccination intentions. We collect data from a representative sample of 3,693 mothers of children aged 0 to 14. Our results indicate that approximately 50\% of the participants believe that they would need to pay a positive out-of-pocket cost for HPV vaccination. Providing information on free vaccination substantially increases vaccination intentions. The treatment effect was particularly pronounced for sons and for parents with positive attitudes towards vaccination.

The fourth industrial revolution has significantly increased the adoption of Digital Twins (DTs) across various sectors, including intelligent manufacturing, automation, logistics, and medical analysis. Despite substantial progress in deploying DT projects, numerous challenges remain, such as managing distributed data flows, protecting commercial confidentiality, securing intellectual property, and ensuring privacy and security. This research introduces a novel approach to addressing these challenges by leveraging blockchain and Web3 technologies, including non-fungible tokens (NFTs) and Distributed Autonomous Organizations (DAOs). The study aims to develop a distributed, tamper-proof DT cooperation platform that facilitates traceable and trustworthy data sharing while preserving intellectual property rights and enabling decentralized governance. This platform enhances idea and invention ownership, promotes collective decision-making through consensus protocols, and explores innovative solutions like blockchain-based federated learning and efficient DT project fundraising tools. Relying on security models and analysis tools, this study addresses several important security analysis methods that are known as practical analysis methods. They can strongly prove every claimed security feature of DT projects. The proposed solutions set the stage for future academic and industrial advancements, supported by a comprehensive SWOT (Strongness - Weakness - Opportunity - Threat) analysis, and outline potential future research directions.

We investigate the effect of students’ age relative to their classmates on adolescents’ risky behaviors across European countries. Using data from the Health Behaviour in School-Aged Children survey and employing a two-stage least squares approach, we provide causal estimates that disentangle relative age effects from absolute age and season-of-birth effects. Our findings indicate that relatively younger students are generally more prone to risky behaviors. We explore two sets of mechanisms underlying these effects. First, causal mediation analyses reveal that academic self-concept, well-being, self-esteem, and peer support act as amplifiers of relative age effects on substance use. Second, additional analyses on European School Survey Project on Alcohol and Other Drugs data suggest that relatively younger students perceive lower risks associated with substance consumption and believe substance use is more prevalent among their peers.

The healthcare situation in many developed countries has become precarious due to limited supply and a steadily growing demand stemming from mandatory health cover for all. As a result, health resources may get allocated inefficiently with those with potentially serious conditions not getting treated in a timely manner. In this paper, we test measures to prevent such inefficiencies, including i) instituting a co-payment for using healthcare services, ii) creating a triage system based on self-reporting one's symptoms, and iii) receiving access to more accurate signals about one's health needs. Drawing on a game theoretic framework with other-regarding preferences, we conduct an online experiment with a large, representative sample of UK adults, where participants decide whether to extract resources from a limited common pool after receiving a noisy signal about their types. Our results suggest that all measures reduce unnecessary extractions from the common pool. While both the cost and self-report triage system have the highest impact on participants extraction choices, the accuracy treatment leads to the highest efficiency, as it reduces the errors stemming from noisy signals.

The integration of robotic services in the hospitality industry has gained significant attention, particularly in the context of safety and hygiene, which have become paramount concerns for tourists in the wake of global health crises. This study investigates the factors influencing tourists' intentions to use hotel service robots, with a focus on perceived safety, health awareness, and service assurance. Drawing on the Theory of Planned Behavior (TPB), the research examines how these factors shape personal engagement and, ultimately, the intention to adopt robotic services in hospitality settings.

Using a purposive sampling technique, data were collected from 275 participants with prior experience in robotic services via the Prolific platform. Structural equation modeling (SEM) was employed to analyze the data, revealing that perceived robotic safety and service assurance significantly positively impact personal engagement. Specifically, guests who perceive robots as safe and reliable are more likely to engage with them, leading to a higher intention to use robotic services. However, health awareness did not show a significant effect on personal engagement, suggesting that while safety and reliability are critical, health-related information may not be a primary driver of engagement with robotic services.

The findings also highlight the mediating role of personal engagement in the relationship between perceived safety, service assurance, and the intention to use robotic services. This underscores the importance of fostering trust and confidence in robotic systems through consistent performance and effective communication of safety features. Notably, female guests exhibited a higher preference for robotic services, indicating potential gender differences in the acceptance of technology in hospitality settings.

This study offers several implications for hoteliers. First, enhancing perceived robotic safety is crucial for increasing guest acceptance. Hoteliers should prioritize clear communication of the security features and capabilities of robots, ensuring guests feel safe and secure during their interactions. Second, investing in high levels of service assurance—such as reliability, responsiveness, and consistent performance—can foster trust and confidence in robotic systems. Regular maintenance, software updates, and staff training are essential to maintaining these standards. Third, hoteliers should implement strategies to enhance personal engagement with robotic services, such as providing interactive features, personalized assistance, and opportunities for guests to learn about and interact with robots. Training staff to effectively assist guests in using these systems can further enhance guest satisfaction and confidence.

This study contributes to the growing body of literature on human-robot interaction by emphasizing the role of perceived safety and service assurance in shaping user attitudes and behaviors. It also offers practical implications for hoteliers, suggesting that investments in reliable and safe robotic systems, coupled with strategies to enhance guest interaction, can significantly improve the adoption of robotic services. Future research should explore these dynamics in diverse cultural contexts and examine the long-term effects of robotic service integration on customer satisfaction and loyalty.

This paper examines the impact of participatory budgeting (PB) on voter turnout in local, regional, and parliamentary elections in the Czech Republic. Using panel data from over 6,200 municipalities between 2009-2022, we employ ordinary least squares regression with fixed effects and an array of control variables to analyze the relationship between PB initiatives and electoral participation. Our findings reveal that PB has a significant and positive effect on voter turnout in local and regional elections, but we found no effect in parliamentary elections. Specifically, PB implementation is associated with a 2.7-3.9 percentage point increase in local election turnout and a 1.5-2.6 percentage point increase in regional election turnout when conducted within two years prior to elections. These effects are most pronounced when PB occurs one year before elections, the effect size and significance decrease with a longer time interval from the election. Our robustness check, which is based on synthetic control method confirms the direction of these effects, albeit with smaller magnitudes and lower significance. The lack of impact on parliamentary elections suggests that PB's influence is primarily localized, while local elections turnout may be fostered by the implementation of PB initiatives to enhance voter participation in local and regional democratic processes.

Cryptocurrencies have experienced a tremendous growth in recent years, both in terms of market capitalization and number of existing digital assets. However, the extreme volatility and peculiar market behavior that characterize this asset class represent an obstacle for their adoption among mainstream investment instruments. In this study, we present a simple and effective way to optimize a portfolio of cryptocurrencies based on two conditioning variables whose value can predict the magnitude of price movements in the short-term. We show empirically that our strategy consistently delivers higher risk-adjusted returns and a more desirable wealth dynamics compared both to standard optimal portfolios and to a naive 1/N allocation.

Middle managers (MMs) implement intended strategy in both adaptive and obstructive outcomes, but prior studies have not fully examined why that happens. This paper investigates how agency and stewardship theories explain MM unintended strategy implementation, including adapted and obstructed strategy. We examined 92 unintended strategy implementations using data from interviews with 40 middle managers in 30 multinational companies. We find three explanations related to stewardship theory (lack of understanding, lack of slack, and autonomy from situational change) as well as four agency theory explanations (lack of agreement, lack of accountability, lack of incentive, and autonomy from temporary lack of top manager oversight). For practice, top managers should be aware of the many ways in which they may fall short in setting an appropriate context for MMs to implement intended strategy.

During the seminar I will share my experiences with writing the ERC proposal, describe the process and share insights into how to best plan, manage and execute the preparation process. The main focus of the presentation will be the core assumptions of the CONSPICIOUS project and discussion of alternative and available sources of funding for the research planned. The rise of the conspicious mindset at the centre stage of policy concerns has led to two major streams of research. First, research on conspiracy beliefs (CBs) has highlighted psychological risk factors and documented the extent of CBs negative behavioural consequences - e.g., fuelling violent extremism, vaccine hesitancy, support for autocrats and illiberal political parties. Second, the growing awareness of societal harms stemming from CBs has also generated a prolific research program focused on misinformation and mostly online and cognitive interventions to curb its prevalence. Contrary to research efforts to date, the current CONSPICIOUS project stems from the understanding of CBs as intergroup attitudes and hypotheses that anti-CBs interventions that focus on improving intergroup attitudes may prove more effective than the former cognitive approach. The overarching aim of CONSPICIOUS is thus to shift scholarly focus towards dealing with CBs directly as intergroup attitudes through fulfilling four specific objectives: (i) identify interventions aimed at improving intergroup attitudes and adapt them to CBs, (ii) test the effectiveness of these interventions in a large scale intervention tournament, (iii) explore generalizability of the most effective interventions in longitudinal trials across general population samples in ​​European and partner countries, and (iv) adapt the interventions to user-friendly, scalable, ready-to-deliver formats. CONSPICIOUS will rely on a large randomised controlled trial (megastudy, N≈10,000) and an international longitudinal study (N≈2,800 per country, first wave). By changing the research perspective, the current project offers an utterly new paradigm of scholarly approaches to curbing the CONSPICIOUS mindset