The system dynamics encoding method – development of a research methodology for the exploration of complex models

Die Zunahme an Komplexität innerhalb biologischer, sozialer oder psychologischer Felder führt in der heutigen Zeit zu einem Defizit von Perzeptions- und Steuerungsmöglichkeiten. Bedingt wird diese Problematik durch erhöhte Wechselbeziehungen sowie die zeitliche und räumliche Trennung von Ursache und Wirkung. Demnach ist die Entstehung von Komplexität durch enge Kopplungen, Rückkopplungsprozesse, Nicht-Linearität, Selbstorganisation und Kontraintuitivität gekennzeichnet, welche durch cartesianisch-lineare Analysen zumeist nicht aufzulösen ist. Diese sind determiniert durch die Zerlegung von Problemen in Einzelteile und eine Erklärung des Gesamtphänomens durch anschließende Summierung, welches zur Bekämpfung von Einzelsymptomen und linear-sequenziellen Problemlösungsstrategien führt. Konträr zur analytischen Vorgehensweise bedarf es bei der Erkennung generischer Strukturmuster eines systemdynamischen Ansatzes. Basierend auf dem primär quantitativen System-Dynamics-Ansatz können, durch die modellbasierte Konstruktion generischer Strukturen, Wahrscheinlichkeitsaussagen über das Systemverhalten getroffen und potentielle Lösungshebel identifiziert werden. Jedoch existieren für systemdynamische Untersuchungen diverse Probleme, welche die Güte des Ansatzes beeinträchtigen. Als wesentlichste Probleme kann die Willkürlichkeit und die Subjektivität der Modellkonstruktion angeführt werden, welche auf das Fehlen einer wissenschaftlich fundierten Methode zurückzuführen sind. Zudem bezweckt die quantitative Fokussierung die Negierung des Primats der Offenheit gegenüber Neuentdeckungen, die jedoch durch ein qualitatives Forschungsvorgehen gefördert werden. Zur Überwindung dieser Probleme wird durch die Verknüpfung qualitativer Forschungsvorgehen sowie systemdynamischer Komponenten und Ansätze (Allgemeine Systemtheorie und Kybernetik) eine Systemdynamische Kodiermethode (SDKM) entwickelt, die in einen systemdynamischen Untersuchungsprozess (SDU) eingebettet und anhand der Stakeholderbeziehungen von H&M expliziert wird. Diese integrative Verfahrensweise ermöglicht die Förderung systemischen Denkens und die Optimierung einer ganzheitlichen Untersuchung, welche zur Verbesserung der Hebelidentifikation, Formulierung von Entscheidungsregeln sowie langfristigen Perzeptionszunahme für komplexe Probleme führt.The increase of complexity within biological, social or psychological fields leads nowadays to a deficit of perception and control possibilities. This problem is determined by accelerating interdependences as well as temporal and spatial separation of cause and effect. Accordingly, the origin of complexity is distinguished by tight couplings, feedback loops, non-linearity, self-organization and counter-intuitiveness, which mostly cannot be dissolved by Cartesian-linear analysis. These are determined by the decomposition of problems into separated parts and an explanation of the overall phenomenon by subsequent summation, which leads to symptom control and linear-sequential problem-solving strategies. Contrary to the analytical procedure the detection of generic structural patterns requires a system dynamical approach. Based on the predominant quantitative system dynamics approach, the model-based construction of generic structures allows to make probability statements about the system behavior and to identify potential levers of problem-solving. Though, there are various problems of system dynamical investigations, which compromise the quality of the approach. The main problems are the arbitrariness and the subjectivity of model construction, which is due to the lack of a scientifically based method. Furthermore, the quantitative focus purposes the negation of the primacy of openness to new discoveries, which will be facilitated by a qualitative research approach. To overcome these problems it is necessary to combine qualitative research approaches as well as system dynamical investigation components and approaches (General Systems Theory and Cybernetics) to develop a system dynamical coding method, which is integrated in a system dynamical investigation process and explained by the stakeholder relations from H&M. This integrative procedure allows the facilitation of systems thinking and the optimization of a holistic investigation, which leads to an improvement of the lever identification, the formulation of decision policies as well as a long-term increase of perception for complex problems

Workforce ageing and the training propensity of Italian firms: cross-sectional evidence from the INDACO survey

In this paper, I provide a probit analysis in which the propensity of private Italian firms to offer on-the-job training is linked to the age and the gender of the employed workforce as well as to a set of relevant corporate characteristics such as size, sector, geographical location, innovation strategies, R&D investments and the use of social safety valves. Retrieving cross-sectional data from INDACO 2009, I find that the propensity of surveyed firms towards training provision follows an inverted u-shaped pattern with respect to the average age of incumbent workers. Furthermore, I show that larger firms are more willing to offer training and the same attitude holds for productive units that adopted innovation strategies and/or invested in R&D projects. By contrast, I find that the propensity to support training activities is negatively correlated to the percentage of employed women and the use of social valves

Megatrend Wissenskultur: Die Handlungsräume der Zukunft

Die Wissenskultur ist ein Megatrend, der durch internationale Entwicklungsinitiativen und Digitalisierung getrieben wird. Er hat weitreichende Auswirkungen auf Bildung, Arbeitsmarkt und Gesellschaft. Wichtig sind die Anpassung an neue Anforderungen, die Förderung von Kreativität und die Entwicklung von Strategien zur Bewältigung der Herausforderungen dieser Entwicklungen

A First Course on Time Series Analysis : Examples with SAS

The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS. Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first three chapters can be dealt within the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 4, 5 and 6 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. Chapter 7 (case study) deals with a practical case and demonstrates the presented methods. It is possible to use this chapter independent in a seminar or practical training course, if the concepts of time series analysis are already well understood. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific parts are highlighted. This book is an open source project under the GNU Free Documentation License

Estrogenic Activity of Mineral Oil Aromatic Hydrocarbons Used in Printing Inks.

The majority of printing inks are based on mineral oils (MOs) which contain complex mixtures of saturated and aromatic hydrocarbons. Consumer exposure to these oils occurs either through direct skin contacts or, more frequently, as a result of MO migration into the contents of food packaging that was made from recycled newspaper. Despite this ubiquitous and frequent exposure little is known about the potential toxicological effects, particularly with regard to the aromatic MO fractions. From a toxicological point of view the huge amount of alkylated and unsubstituted compounds therein is reason for concern as they can harbor genotoxicants as well as potential endocrine disruptors. The aim of this study was to assess both the genotoxic and estrogenic potential of MOs used in printing inks. Mineral oils with various aromatic hydrocarbon contents were tested using a battery of in vitro assays selected to address various endpoints such as estrogen-dependent cell proliferation, activation of estrogen receptor α or transcriptional induction of estrogenic target genes. In addition, the comet assay has been applied to test for genotoxicity. Out of 15 MOs tested, 10 were found to potentially act as xenoestrogens. For most of the oils the effects were clearly triggered by constituents of the aromatic hydrocarbon fraction. From 5 oils tested in the comet assay, 2 showed slight genotoxicity. Altogether it appears that MOs used in printing inks are potential endocrine disruptors and should thus be assessed carefully to what extent they might contribute to the total estrogenic burden in humans

A Critical Scoping Review of Pesticide Exposure Biomonitoring Studies in Overhead Cultures

The exposure of operators, workers, residents and bystanders to pesticides is of high potential concern. Yet, reports on pesticide residues in the environment and near treated fields often spark debates if such findings might indicate a health risk. Although the underlying models are considered conservative, there are only limited field data on systemic exposure available. As a first step to improve the situation, we conducted a scoping review of state-of-the-art pesticide exposure biomonitoring studies in operators, workers, residents or bystanders. In contrast to existing reviews, we focused on target cultures of potential high pesticide exposure such as tree-grown produce, vine or hops. The search was conducted in Web of Science, Scopus and PubMed. Out of 17 eligible articles, a total of 11 studies met our search criteria, and 6 of them quantified the systemic exposure of humans. The analysis revealed that exposure was mainly driven by application of pesticides and reentry work, resulting in a higher exposure of operators and workers than of residents and bystanders. In nearly all cases, the systemic exposure was below the relevant toxicological reference values. The studies were subsequently analyzed to identify key criteria for a reliable design of a biomonitoring study on pesticide exposure