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Publikation A concept for team development and team optimisation(2024) Aeschbacher, Marc; Legena, Valeria; Smuts, Hanlie; Hinkelmann, Knut04B - Beitrag KonferenzschriftPublikation A tool guide for teaching law to business students – with an eye on AI(2024) Nicol Brogle, Anja06 - PräsentationPublikation Academic or vocational education? A comparison of the long-term wage development of academic and vocational tertiary degree holders(Springer, 2024) Kriesi, Irene; Sander, FabianEducation is a key determinant of wage development. The relationship between education and wages is particularly strong in countries with vocationally oriented educational systems and a clear distinction between general and vocational education, such as Germany and Switzerland. However, whether general and vocational education offer the same returns to education is an ongoing debate. Previous findings from international research are still inconclusive. Against this background and based on theoretical arguments from human capital and signalling theory and the task-specific learning-by-doing approach, our paper examines the long-term wage development of Swiss university and professional education degree holders from the time they obtain their tertiary degree until their late career. It asks how differences between the two groups in wage development may be explained. Our results, produced with regression decomposition methods, show that within the first 20 years after graduation, university degree holders experience steeper wage growth. An important reason for this difference is that university graduates move more often than vocational tertiary degree holders into well-paid labour market positions endowed with formal authority, management responsibility, and a large proportion of cognitive nonroutine tasks.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Phenological patterns of flowering across biogeographical regions of Europe(Springer, 2017) Templ, Barbara; Templ, Matthias; Filzmoser, Peter; Lehoczky, Annamária; Bakšienè, Eugenija; Fleck, Stefan; Gregow, Hilppa; Hodzic, Sabina; Kalvane, Gunta; Kubin, Eero; Palm, Vello; Romanovskaja, Romanovskaj; Vucˇetic´, Višnja; žust, Ana; Czúcz, BálintLong-term changes of plant phenological phases determined by complex interactions of environmental factors are in the focus of recent climate impact research. There is a lack of studies on the comparison of biogeographical regions in Europe in terms of plant responses to climate. We examined the flowering phenology of plant species to identify the spatio-temporal patterns in their responses to environmental variables over the period 1970–2010. Data were collected from 12 countries along a 3000-km-long, North–South transect from northern to eastern Central Europe. Biogeographical regions of Europe were covered from Finland to Macedonia. Robust statistical methods were used to determine the most influential factors driving the changes of the beginning of flowering dates. Significant species-specific advancements in plant flowering onsets within the Continental (3 to 8.3 days), Alpine (2 to 3.8 days) and by highest magnitude in the Boreal biogeographical regions (2.2 to 9.6 days per decades) were found, while less pronounced responses were detected in the Pannonian and Mediterranean regions. While most of the other studies only use mean temperature in the models, we show that also the distribution of minimum and maximum temperatures are reasonable to consider as explanatory variable. Not just local (e.g. temperature) but large scale (e.g. North Atlantic Oscillation) climate factors, as well as altitude and latitude play significant role in the timing of flowering across biogeographical regions of Europe. Our analysis gave evidences that species show a delay in the timing of flowering with an increase in latitude (between the geographical coordinates of 40.9 and 67.9), and an advance with changing climate. The woody species (black locust and small-leaved lime) showed stronger advancements in their timing of flowering than the herbaceous species (dandelion, lily of the valley). In later decades (1991–2010), more pronounced phenological change was detected than during the earlier years (1970–1990), which indicates the increased influence of human induced higher spring temperatures in the late twentieth century.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Student-mediated knowledge exchange in Switzerland(Springer Cham, 2024) Barjak, Franz; Heimsch, Fabian; Hinkelmann, Knut; Smuts, HanlieThe majority of the academic work on knowledge and technology transfer has been on two types, knowledge commercialization and academic engagement. Mechanisms which involve students have been neglected though they are as common and potentially as beneficial. This neglect harbours several risks with regard to the economic and social valorisation of research results. We define and typify the construct of student-mediated knowledge exchange and review the literature which has reported multiple benefits for the involved parties, students, universities and companies, but also some costs. We then use survey data on three selected measures generated in a survey of the institutes of 18 Swiss higher education institutions (HEIs) for multivariate regression analyses at institute level to explain the differences for the student-mediated knowledge exchange metrics with structural characteristics of the institutes (university type, size, academic discipline) and variables on their activities (teaching focus, cooperation and commercialisation orientation). The results show that student-mediated transfers capture knowledge exchange with companies that is not covered by the common metrics for knowledge commercialization and academic engagement. In sum, we argue that the scope of knowledge and technology transfer metrics should be expanded to include measures that capture student-mediated forms.04B - Beitrag KonferenzschriftPublikation Visualization and imputation of missing values. With applications in R(Springer, 2023) Templ, MatthiasThis book explores visualization and imputation techniques for missing values and presents practical applications using the statistical software R. It explains the concepts of common imputation methods with a focus on visualization, description of data problems and practical solutions using R, including modern methods of robust imputation, imputation based on deep learning and imputation for complex data. By describing the advantages, disadvantages and pitfalls of each method, the book presents a clear picture of which imputation methods are applicable given a specific data set at hand. The material covered includes the pre-analysis of data, visualization of missing values in incomplete data, single and multiple imputation, deductive imputation and outlier replacement, model-based methods including methods based on robust estimates, non-linear methods such as tree-based and deep learning methods, imputation of compositional data, imputation quality evaluation from visual diagnostics to precision measures, coverage rates and prediction performance and a description of different model- and design-based simulation designs for the evaluation. The book also features a topic-focused introduction to R and R code is provided in each chapter to explain the practical application of the described methodology. Addressed to researchers, practitioners and students who work with incomplete data, the book offers an introduction to the subject as well as a discussion of recent developments in the field. It is suitable for beginners to the topic and advanced readers alike.02 - MonographiePublikation General approach to coordinate representation of compositional tables(Wiley, 2018) Facevicova, Kamila; Hron, Karel; Todorov, Valentin; Templ, MatthiasCompositional tables can be considered a continuous counterpart to the well-known contingency tables. Their cells, which generally contain positive real numbers rather than just counts, carry relative information about relationships between two factors. Hence, compositional tables can be seen as a generalization of (vector) compositional data. Due to their relative character, compositions are commonly expressed in orthonormal coordinates using a sequential binary partition prior to being further processed by standard statistical tools. Unfortunately, the resulting coordinates do not respect the two-dimensional nature of compositional tables. Information about relationship between factors is thus not well captured. The aim of this paper is to present a general system of orthonormal coordinates with respect to the Aitchison geometry, which allows for an analysis of the interactions between factors in a compositional table. This is achieved using logarithms of odds ratios, which are also widely used in the context of contingency tables.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Evaluation of robust outlier detection methods for zero-inflated complex data(Taylor & Francis, 2019) Templ, Matthias; Gussenbauer, Johannes; Filzmoser, PeterOutlier detection can be seen as a pre-processing step for locating data points in a data sample, which do not conform to the majority of observations. Various techniques and methods for outlier detection can be found in the literature dealing with different types of data. However, many data sets are inflated by true zeros and, in addition, some components/variables might be of compositional nature. Important examples of such data sets are the Structural Earnings Survey, the Structural Business Statistics, the European Statistics on Income and Living Conditions, tax data or – as in this contribution – household expenditure data which are used, for example, to estimate the Purchase Power Parity of a country. In this work, robust univariate and multivariate outlier detection methods are compared by a complex simulation study that considers various challenges included in data sets, namely structural (true) zeros, missing values, and compositional variables. These circumstances make it difficult or impossible to flag true outliers and influential observations by well-known outlier detection methods. Our aim is to assess the performance of outlier detection methods in terms of their effectiveness to identify outliers when applied to challenging data sets such as the household expenditures data surveyed all over the world. Moreover, different methods are evaluated through a close-to-reality simulation study. Differences in performance of univariate and multivariate robust techniques for outlier detection and their shortcomings are reported. We found that robust multivariate methods outperform robust univariate methods. The best performing methods in finding the outliers and in providing a low false discovery rate were found to be the generalized S estimators (GSE), the BACON-EEM algorithm and a compositional method (CoDa-Cov). In addition, these methods performed also best when the outliers are imputed based on the corresponding outlier detection method and indicators are estimated from the data sets.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Habitat-dependency of transect walk and pan trap methods for bee sampling in farmlands(Apicultural Research Association, 2019) Templ, Barbara; Mozes, Edina; Templ, Matthias; Földesi, Rita; Szirák, Ádám; Báldi, András; Kovács-Hostyánszki, AnikóBees are the most important group of flower visitors providing an essential ecosystem service, namely pollination. Due to the worldwide decline of bees, there should be standardized sampling methods in place to ensure consistent and comparable results between studies. We compared the two commonly used sampling methods of yellow pan traps and transect walk to determine (i) which habitat variables affect the species composition, abundance and species richness of sampled bee communities, (ii) which method potentially contains sampling bias towards some individuals or groups of bees and (iii) the efficiency of sampling in various habitats. We conducted fieldwork in different agricultural habitats distributed along landscape heterogeneity and topography gradients. Our results showed that the height of vegetation, the average number of flowers and the amount of woody vegetation had the greatest influence on the sampling efficiency. Our survey also demonstrated that sampling by transect walk captured less bees in general, especially in stubble, maize, and cereal fields. We found that Apis mellifera and Bombus spp. were well represented in samples collected by the transect walk method, while the abundance of other genera, especially Dasypoda, Hylaeus and Panurgus was higher in pan traps. Based on the results, we suggest (i) the transect walk method to compare samples of flower-visiting wild bee communities from various habitats of different vegetation and flower characteristics, (ii) application of the transect walk or pan traps to compare similar habitats and (iii) adoption of a comprehensive method which would incorporate both sampling techniques to gain a more complex insight into wild bee species composition.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Feedback-based integration of the whole process of data anonymization in a graphical interface(MDPI, 2019) Meindl, Bernhard; Templ, MatthiasThe interactive, web-based point-and-click application presented in this article, allows anonymizing data without any knowledge in a programming language. Anonymization in data mining, but creating safe, anonymized data is by no means a trivial task. Both the methodological issues as well as know-how from subject matter specialists should be taken into account when anonymizing data. Even though specialized software such as sdcMicro exists, it is often difficult for nonexperts in a particular software and without programming skills to actually anonymize datasets without an appropriate app. The presented app is not restricted to apply disclosure limitation techniques but rather facilitates the entire anonymization process. This interface allows uploading data to the system, modifying them and to create an object defining the disclosure scenario. Once such a statistical disclosure control (SDC) problem has been defined, users can apply anonymization techniques to this object and get instant feedback on the impact on risk and data utility after SDC methods have been applied. Additional features, such as an Undo Button, the possibility to export the anonymized dataset or the required code for reproducibility reasons, as well its interactive features, make it convenient both for experts and nonexperts in R—the free software environment for statistical computing and graphics—to protect a dataset using this app.01A - Beitrag in wissenschaftlicher Zeitschrift