Bürgerversicherung — Die Wirkung von Kopfprämien auf den Arbeitsmarkt

Capitation fees are considered to be an option for a change in funding principles for statutory health care insurance. This paper discusses several models of capitation fees either to be introduced for a part of the population or for all citizens. It analyses the impact of a change in financing health care on the labour market. Therefore microeconomic theory and a QUERU-model is applied. It also considers the issue of presently co-insured dependents.     

Model selection in random effects models for directed graphs using approximated Bayes factors

With the development of an MCMC algorithm, Bayesian model selection for the p ₂ model for directed graphs has become possible. This paper presents an empirical exploration in using approximate Bayes factors for model selection. For a social network of Dutch secondary school pupils from different ethnic backgrounds it is investigated whether pupils report that they receive more emotional support from within their own ethnic group. Approximated Bayes factors seem to work, but considerable margins of error have to be reckoned with.     

Networked innovation and coalition formation: the effect of group-based social preferences

In this paper, we study the production and dissemination of public knowledge goods, such as technological knowledge, generated by a network of voluntarily cooperating innovators. We develop a private-collective model of public knowledge production in networked innovation systems, where group-based social preferences have an impact on the coalition formation of developers. Our model builds on the large empirical literature on voluntary production of pooled public knowledge goods, including source code in communities of software developers or data provided to open access data repositories. Our analysis shows under which conditions social preferences, such as ‘group belonging’ or ‘peer approval’, influence the stable coalition size, as such rationalising several stylized facts emerging from large-scale surveys of open-source software developers, previously unaccounted for. Furthermore, heterogeneity of social preferences is added to the model to study the formation of stable but mixed coalitions.     

The Multilevel Approach to Repeated Measures for Complete and Incomplete Data

Repeated measurements often are analyzed by multivariate analysis of variance (MANOVA). An alternative approach is provided by multilevel analysis, also called the hierarchical linear model (HLM), which makes use of random coefficient models. This paper is a tutorial which indicates that the HLM can be specified in many different ways, corresponding to different sets of assumptions about the covariance matrix of the repeated measurements. The possible assumptions range from the very restrictive compound symmetry model to the unrestricted multivariate model. Thus, the HLM can be used to steer a useful middle road between the two traditional methods for analyzing repeated measurements. Another important advantage of the multilevel approach to analyzing repeated measures is the fact that it can be easily used also if the data are incomplete. Thus it provides a way to achieve a fully multivariate analysis of repeated measures with incomplete data. This revised version was published online in June 2006 with corrections to the Cover Date.     

LEGAL KNOWLEDGE AND AGILITY IN PUBLIC ADMINISTRATION

To address agility in public administration, we have developed a knowledge acquisition infrastructure for legal knowledge, based on an implementation‐oriented conceptualization of the legal system. Our objective is to reframe legal knowledge as a knowledge source in a design‐oriented task ontology, building on insights from the CommonKADS methodology for intelligent system design. The main result is to make case law and legal expert knowledge of critical incidents in organizations, two diagnostic knowledge sources underutilized in modern management and engineering, more accessible as a resource for design of agile organizational structures and intelligent systems. Copyright © 2013 John Wiley & Sons, Ltd.     

Positive Accounting Theory as a Lakatosian Research Programme

‘Positive accounting theory’ fails to meet Popper's falsificationist criteria for scientific inquiry. This paper argues, however, that Lakatos' ‘methodology of scientific research programmes’ is superior to Popper's falsificationist methodology, and that ‘positive accounting research’ does meet Lakatos' criteria for ‘scientific' status. Within Lakatos’ philosophy of science, however, this claim does not necessarily represent an endorsement of positive accounting theory.     

Cost engineering and costing in Hawthorn Leslie Shipbuilders, 1886–1915

This research examines cost engineering and costing in a British shipbuilding firm in the late nineteenth – early twentieth century. The firm maintained separate systems of contract accounting, costing and reporting for directors and employed internal data from these systems in performance measurement, the development of managerial incentives and the enforcement of managerial accountability. An apparent gap in the information required to manage the firm in a cyclical and highly competitive industry during a period of rapid organisational and technological change was filled by an informal and personal cost engineering system developed by the shipbuilding manager. The shipbuilding manager's cost engineering system employed a wide range of both internal and external data for use in cost management and in cost estimation, pricing and tendering. Thus cost engineering and costing developed to serve different purposes and developed in different spheres and along different trajectories.     

Non-technical skills for managing risk and performance in financial trading

Recent large-scale failures in financial institutions have been found to be caused, in-part, by human factors-related issues in financial trading. In other environments where risk management and performance are intertwined, a human factors approach is often adopted to understand how the ‘non-technical skills (NTS)’ (leadership (LD), decision-making (DM), situation awareness (SA), teamwork) of organisational actors influence outcomes. Yet, to date, there has been minimal application of human factors research in financial trading. This study (i) identifies ‘real-world’ (i.e. non-laboratory) research studies investigating the NTS important for performance in financial trading, (ii) examines and synthesises data on the NTS found to underpin good or poor performance and (iii) considers the quality and coverage of research investigating NTS in financial trading, and identifies potential areas for future research. Nineteen studies were identified through a systematic literature search and then content-analysed for associations between NTS and performance in financial trading. The review found a range of decision-making (e.g. heuristics and biases, intuitive DM, emotional regulation) and LD skills (e.g. setting standards, monitoring behaviour, encouraging speaking-up) to have been identified as important for managing risk and performance in financial trading environments. Furthermore, SA (e.g. information search and assessment strategies, vigilance, identifying ‘noise’ data) and teamwork (e.g. avoiding ‘role’ conflict, communication between traders) were found to be important, yet remain less explored within the literature, and should be the focus of future research. NTS appear essential for effective risk management within the financial sector, yet further field research is required to examine the context-relevant behaviours that underpin safe activity. This will facilitate the development of evidence-based systems for assessing and training NTS competencies.