Modeling religion: bureaucratic reform and the transformation of popular piety in the 18th century

Zwischen 1750 und 1790 versuchten Maria Theresia und Joseph II. das religiöse Leben des Habsburger Landes von der traditionellen barocken Frömmigkeit in einen reformierten Katholizismus zu transformieren. Der vorliegende Beitrag untersucht die Reaktionen der Bevölkerung auf diese administrativ eingeleitete Kirchenreform und ihre ideologischen Elemente. Als Datenbasis zur Erfassung der Volksfrömmigkeit dienen Testamente. Die Interpretation der multivariaten Analyse zeigt, daß es zwischen 1770 und 1790 zu hoch signifikanten religösen Einstellungsänderungen gekommen ist. Der Mentalitätswandel wird nicht einfach aus dem Prozeß der Säkularisierung bzw. dem 'Absinken' des aufgeklärten Bewußtseins der Eliten in die Massen erklärt, sondern als autonomer Prozeß der 'Debarockisierung' des einst führenden Landes der Gegenreformation. (pmb

Economic growth and lower class investments in nineteenth century Austria

Die historische Studie untersucht das Investitionsverhalten der Unterschicht-Bevölkerung im alpinen Raum Österreichs zwischen 1820 und 1913. Nach einem kurzen Überblick über das Banken- und Kreditwesen zur Zeit der Habsburger Monarchie werden die Kapitalanlagen der Österreicher in Abhängigkeit von Familienstand, Alter, Gesamtvermögen und kulturellen/regionalen Merkmalen tabellarisch dargestellt. Besonderes Interesse gilt den Bestimmungsfaktoren für das jeweilige Investitionsverhalten und der Entscheidung zwischen den einzelnen Anlageformen. (ICI)'The paper examines investment behavior in the lower-class population in the Alpine lands of the Habsburg Monarchy between 1820 and 1913. In order to determine how the lowerclass population responded to institutional changes in the financial market, the paper distinguishes between investments in various kinds of assets and examines the specific preferences of the lower-class population for savings deposits, securities, private debt claims, cash, real estate and movable belongings. In addition to professional factors, the analysis uses overall wealth, family status, age, cultural and regional factors, and the time factor as independent variables. Finally, the article determines whether the structures of portfolios show any additional systematic variation that cannot be explained by the effect of those factors.' (author's abstract

Special Issue on: Awareness and Reflection in Technology Enhanced Learning. Vol.9, (2-3)

Awareness and reflection play a crucial role in the learning process, helping the involved actors to succeed in self-regulated learning and to optimise their learning experience. Whether in traditional education, workplace training or lifelong learning, appropriate feedback together with proper assessment of previous practices can bring benefits for all the participants and cultivate their reflective skills, which are essential for effective learning

The Data Product Canvas - A Visual Collaborative Tool for Designing Data-Driven Business Models

The availability of data sources and advances in analytics and artificial intelligence offers the opportunity for organizations to develop new data-driven products, services and business models. Though, this process is challenging for traditional organizations, as it requires knowledge and collaboration from several disciplines such as data science, domain experts, or business perspective. Furthermore, it is challenging to craft a meaningful value proposition based on data; whereas existing research can provide little guidance. To overcome those challenges, we conducted a Design Science Research project to derive requirements from literature and a case study, develop a collaborative visual tool and evaluate it through several workshops with traditional organizations. This paper presents the Data Product Canvas, a tool connecting data sources with the user challenges and wishes through several intermediate steps. Thus, this paper contributes to the scientific body of knowledge on developing data-driven business models, products and services

Supporting Data-Driven Business Model Innovations: A structured literature review on tools and methods

Purpose: This paper synthesizes existing research on tools and methods that support data-driven business model innovation, and maps out relevant directions for future research. Design/methodology/approach: We have carried out a structured literature review and collected and analysed a respectable but not excessively large number of 33 publications, due to the comparatively emergent nature of the field. Findings: Current literature on supporting data-driven business model innovation differs in the types of contribution (taxonomies, patterns, visual tools, methods, IT tool and processes), the types of thinking supported (divergent and convergent) and the elements of the business models that are addressed by the research (value creation, value capturing and value proposition). Research limitations/implications: Our review highlights the following as relevant directions for future research. Firstly, most research focusses on supporting divergent thinking, i.e. ideation. However, convergent thinking, i.e. evaluating, prioritizing, and deciding, is also necessary. Secondly, the complete procedure of developing data-driven business models and also the development on chains of tools related to this have been under-investigated. Thirdly, scarcely any IT tools specifically support the development of data-driven business models. These avenues also highlight the necessity to integrate between research on specifics of data in business model innovation, on innovation management, information systems and business analytics. Originality/value: This paper is the first to synthesize the literature on how to identify and develop data-driven business models, and to map out (interdisciplinary) research directions for the community. Keywords: Business model innovation, data-driven business models, research agenda.   Article classification: Literature revie

The Data-Driven Business Value Matrix - A Classification Scheme for Data-Driven Business Models

Increasing digitization is generating more and more data in all areas of business. Modern analytical methods open up these large amounts of data for business value creation. Expected business value ranges from process optimization such as reduction of maintenance work and strategic decision support to business model innovation. In the development of a data-driven business model, it is useful to conceptualise elements of data-driven business models in order to differentiate and compare between examples of a data-driven business model and to think of opportunities for using data to innovate an existing or design a new business model. The goal of this paper is to identify a conceptual tool that supports data-driven business model innovation in a similar manner: We applied three existing classification schemes to differentiate between data-driven business models based on 30 examples for data-driven business model innovations. Subsequently, we present the strength and weaknesses of every scheme to identify possible blind spots for gaining business value out of data-driven activities. Following this discussion, we outline a new classification scheme. The newly developed scheme combines all positive aspects from the three analysed classification models and resolves the identified weaknesses

Autophagy in the Thymic Epithelium Is Dispensable for the Development of Self-Tolerance in a Novel Mouse Model

The thymic epithelium plays critical roles in the positive and negative selection of T cells. Recently, it was proposed that autophagy in thymic epithelial cells is essential for the induction of T cell tolerance to self antigens and thus for the prevention of autoimmune diseases. Here we have tested this hypothesis using mouse models in which autophagy was blocked specifically in epithelial cells expressing keratin 14 (K14), including the precursor of thymic epithelial cells. While the thymic epithelial cells of mice carrying the floxed Atg7 gene (ATG7 f/f) showed a high level of autophagy, as determined by LC3 Western blot analysis and fluorescence detection of the recombinant green fluorescent protein (GFP)-LC3 reporter protein on autophagosomes, autophagy in the thymic epithelium was efficiently suppressed by deletion of the Atg7 gene using the Cre-loxP system (ATG7 f/f K14-Cre). Suppression of autophagy led to the massive accumulation of p62/sequestosome 1 (SQSTM1) in thymic epithelial cells. However, the structure of the thymic epithelium as well as the organization and the size of the thymus were not altered in mutant mice. The ratio of CD4 to CD8-positive T cells, as well as the frequency of activated (CD69+) CD4 T cells in lymphoid organs, did not differ between mice with autophagy-competent and autophagy-deficient thymic epithelium. Inflammatory infiltrating cells, potentially indicative of autoimmune reactions, were present in the liver, lung, and colon of a similar fraction of ATG7 f/f and ATG7 f/f K14-Cre mice. In contrast to previously reported mice, that had received an autophagy-deficient thymus transplant, ATG7 f/f K14-Cre mice did not suffer from autoimmunity-induced weight loss. In summary, the results of this study suggest that autophagy in the thymic epithelium is dispensable for negative selection of autoreactive T cells