Developing And Implementing a Perception- And Experience-Based Measurement of Corruption: Facilitating And Hindering Factors, And the Construction of Multi-Layered Measurement Tools

Within the framework of the Hungarian Integrity Authority, the newly established Integrity Academy aims to design and deliver evidence-based services and training programmes that respond directly to the needs of various societal groups, including youth, business leaders and civil servants. Data-driven educational initiatives are essential in a context where reliable information on corruption and integrity remains scarce, and they enable the Authority to complement its reactive investigative functions with proactive, prevention-oriented societal engagement. The Tiszta Úton (“Clean Path”) research programme brings together social scientists with the objective of producing a comprehensive and accurate picture of corruption- and integrity-related perceptions and experiences among the Hungarian general population and two key professional subgroups: Hungarian business leaders and civil servants. Beyond these core thematic areas, the already completed large-scale representative population survey also captures several related key dimensions, including trust, civic and political participation, transparency, access to services, safety, subjective well-being and media consumption. The conceptual foundation of the research is strengthened by Alfred Schütz’s theory of the social distribution of knowledge, which provides a partial theoretical framework for integrating the findings from the population survey with the forthcoming data collections targeting business leaders and civil servants. This multi-layered approach creates a genuinely comprehensive measurement instrument capable of reflecting corruption across a broader spectrum. Moreover, results from these surveys can be linked to a parallel study investigating corruption-related red flags in the Hungarian public procurement system, offering an integrated, system-level view of corruption risks that based on different type of corruption data. The population survey was conducted between June and September 2025 using a multimode (hybrid) data-collection technique, alternating between online (CAWI) and face-to-face (CAPI) interviewing. A multi-stage, random-probability sampling design ensured representativeness. The innovative multimode technique, the careful construction of question blocks and survey flow, and an extended, precisely conceptualised set of corruption and integrity definitions—significantly broader than conventional ones—collectively enhance the validity and reliability of the dataset. The aim of the new definitional framework is to move beyond the limitations of perception-based indicators and capture corruption as a multi-level phenomenon. Despite the sensitive nature of the topic, the methodological design resulted in a 42% response rate (n = 1,254). Preliminary analyses indicate that corruption perception significantly affects subjective well-being in Hungary. Respondents identified corruption as the third most pressing national problem, following inflation and the state of public healthcare. Perceived institutional trust correlates strongly with perceived corruption prevalence: trust was highest toward local administrative service providers and lowest toward the Hungarian government and the healthcare system. Regression models suggest that institutional trust and perceptions of others’ ethical behaviour are the strongest predictors of subjective organisational integrity—an effect that remains notable even alongside indications of moral self-enhancement. The processing of the population survey data is nearing completion, while the two specialised subgroup surveys and the proxy indicators are scheduled for the 2nd-3rd quarter of 2026.