Supervisory data are typically not conceived for statistical purposes or considered "official statistics", but they are disclosed to the public, either directly by the supervised institutions or indirectly by the competent authorities. This disclosure is required under Pillar 3 of the Basel...

The outbreak of COVID‐19 has sparked a sudden demand for fast, frequent and accurate data on the societal impact of the pandemic. This demand has highlighted a divide in survey data collection: Most probability‐based social surveys, which can deliver the necessary data quality to allow valid...

Since the conceptualization of bounded rationality, management scholars started investigating how people-managers and entrepreneurs-really make decisions within (and for) organizations. The aim of this eBook is to deeply investigate trends that have flourished within this pivotal research area...

Data quality is critical to adequately perform management accounting (MA) tasks, and information systems (IS) provide the data for the MA domain. However, IS can vary vastly across firms, which may influence the basis for rational decision making (i.e., data quality). This study therefore aims...

The rapid development of e-commerce has led to a swiftly increasing number of competing providers in electronic markets, which maintain their own, individual data describing the offered items. Recommender systems are popular and powerful tools relying on this data to guide users to their...

Declining participation in voluntary establishment surveys poses a risk of increasing non‐response bias over time. In this paper, response rates and non‐response bias are examined for the 2010–2019 IAB Job Vacancy Survey. Using comprehensive administrative data, we formulate and test...

Existing time series of the returns on German stocks are either short or have weaknesses. We discuss the problems of creating such a time series and then report our monthly series based on all stocks in the top segment of the Frankfurt Stock Exchange. We compare our return series with the...

This volume presents the results of the Cohort '18 Hungarian Birth Cohort Study as the third output in the research series. The first contained the theoretical, methodological and organizational tasks preceding the prenatal data collection wave. The second volume presented the theoretical...

Supervised machine learning methods, in which no error labels are present, are increasingly popular methods for identifying potential data errors. Such algorithms rely on the tenet of a 'ground truth' in the data, which in other words assumes correctness in the majority of the cases. Points...

In the field of nuclear magnetic resonance imaging, diffusion tensor imaging (DTI) has proven an important method for the characterisation of ultrastructural tissue properties. Yet various technical and biological sources of signal uncertainty may prolong into variables derived from diffusion...