Systemic justice and burnout: A multilevel model

With the aim of extending organisational justice research to embrace significant and enduring aspects of the workplace context, this study examines organisational culture and human resource management (HRM) as constitutive dimensions of systemic justice and relates them to employee health. Bridging organisational justice, HRM, organisational culture, and occupational health research, we advance and test a multilevel model relating systemic justice to burnout. Data collected from 60 organisations; 89 employee groups; and 1,976 employees provide support for the hypothesised relationships between justice‐oriented culture, in terms of organisational values and group culture, and justice‐oriented HRM. In turn, justice‐oriented HRM related directly to employee burnout and indirectly through employee perceived job control and supervisor social support.     

On Measurement of Economic Growth

This article continues the discussion raised in the pages of the journal on the methodological problems of justifying economic policy [1]. Problems of measuring the inflationary component of economic growth and in product competitiveness in the internal market and external markets are considered. A procedure to measure economic growth, taking into account the balance of interests of the current and future generations, is proposed.     

Aufdeckung von Versicherungsbetrug bei Kfz-Schäden mit Hilfe des Benford-Tests

The German Insurance Association estimates a yearly amount of damage of € 1.5?bn to German motor vehicle insurance companies because of systematic fraud by insurance holders. It is supposed that about 10% of submitted claim applications contain manipulated data, therefore insurance companies are forced to complete a detailed and cost intensive case-by-case review of each single application. An alternative method to detect fraud in empiric data is the method of digital analysis based on Benford’s law. The Benford method uses a mathematical law of specific logarithmic distribution attributes of first digits. According to this approach, the data of a Benford set confirm with the expected digit distribution, if the data is not manipulated, whereas fraudulent interventions lead to a deviation from Benford’s law. Hence, until now there has not been any investigation whether the Benford method can also be applied on insurance data. The present article analyses a dataset consisting of more than 120,000 damage claim applications to answer this question as well as to identify the impact of specific characteristics on the probability of fraud contained in claim applications, such as the repair of the vehicle in a franchised or an independent workshop, the vehicle brand or the examination by insurance companies experts. Indeed it could be shown that Benford’s Law is only applicable on second digits of insurance data, but delivers very strong results here: All results of the considered characteristics could be verified by plausible arguments. For this reason insurance companies can benefit from making use of the Benford method to identify those claim applications with a high probability of fraud, which should then be reviewed in more detail so that resources can be allocated in a much more cost efficient way.     

An experimental analysis of tax avoidance policies

Policies to reduce aggressive tax avoidance are increasingly being implemented or discussed in many countries around the world. Tax authorities hope that such policies will generate new tax revenue by increasing overall tax compliance. We present an experimental design to investigate the effect of a stylized anti-avoidance tax policy on tax compliance behavior. We highlight that anti-avoidance tax policies that reduce tax avoidance can also induce an increase in tax evasion (“substitution effect”), which limits the additional tax revenue these policies will generate. We show that the degree of substitution depends crucially on behavioral factors such as tax morale. Policymakers therefore also need to consider behavioral features while designing such policies and estimating their potential effects.     

Exploring the learning problems and resource usage of undergraduate industrial design students in design studio courses

Design is a powerful weapon for modern companies so it is important to have excellent designers in the industry. The purpose of this study is to explore the learning problems and the resources that students use to overcome problems in undergraduate industrial design studio courses. A survey with open-type questions was conducted to collect data. Participants in this study were 189 undergraduate industrial design students from three universities, and two coding schema were formulated for analysing the data. The results demonstrated that the most difficult design tasks included concept generation, design presentation, and design research. The learning resources used to solve the learning problems included four categories: people, object, method, and environment. This information will increase the understanding of the learning process of students and provide a reference for teaching and the setting of learning resources in industrial design education.     

Technology‐push,market‐demand and the missing safety‐pull: a case study of American Airlines Flight 587

Through a critical case study of the crash of American Airlines Flight 587, this paper draws upon ‘the Social Shaping of Technology’ (SST) approach to offer a reconceptualisation of the technology‐push and market‐demand model for High‐Reliably Organisations (HROs), providing support for a third factor, called here a ‘safety‐pull’. A safety‐pull is defined as organisationally supported reflexivity in which technology innovators and frontline operators collaborate to consider the potential implications of adopting new technologies in HROs and the complex ways this change may impact human operators' work performance, often in risky and unanticipated ways. In contrast to accidents occurring solely as the result of individual operator error, analysing the safety‐pull provides a way to tease out the wide range of factors that can contribute to HRO failures and offers a new SST perspective through which to examine high‐risk operations.     

Applications of Statistics in the Field of General Insurance: An Overview

This is an expository paper on applications of statistics in the field of general insurance, also called non‐life insurance. Unlike life insurance where advanced statistical techniques have long been part of financial mathematics and actuarial applications, their use is only relatively recent in non‐life insurance. The business model of insurance companies, especially those active in non‐life insurance, has seen dramatic changes over the last 15 years. The aim of this paper is to convince the readers that especially today non‐life insurance is not only an exciting ground to apply existing modern statistical tools but also a fertile environment for new and challenging statistical developments. The activities of an insurance company can be viewed as an industrial process where data management and data analysis play a key role. That is why a fundamental understanding of data‐related issues (such as data quality, variability, analysis and correct interpretation) is so essential to the insurance business. These are exactly the tasks where professional statisticians excel. Also, a better understanding of the field of general insurance by statisticians will promote fruitful exchanges between actuaries and statisticians, thereby helping to bring actuarial and statistical professional societies closer to each other. Selected examples are used to cover the essential aspects of general insurance, and all of them are based on the author's experience. The paper concludes with some remarks on the role of statisticians working in general insurance.     

Does Accrual Management Impair the Performance of Earnings‐Based Valuation Models?

This study examines how accrual manipulations affect firm valuation in the years surrounding the passage of the Sarbanes‐Oxley Act (SOX). We compare the absolute percentage pricing errors of RIM and DCF valuation models for a group of US firms suspected to have engaged in accrual manipulations to avoid a small loss or a small earnings decline vs. ‘Normal’ firms matched on industry, year and size. We find that RIM can better estimate intrinsic value than DCF for the matched Normal firms in the pre‐SOX period, but not so for accrual manipulators, and that SOX mitigates the harmful effect of accrual manipulations, completely eliminating the difference in RIM's accuracy advantage over DCF between Normal firms and accrual manipulators. As a further analysis, we redefine Suspect firms as real‐activity manipulators and find a significant across‐group difference in accuracy wedge in both sample periods, implying that SOX has prompted firms to favor real‐activity manipulations over accrual manipulations.     

The European origins of economic development

Although a large literature argues that European settlement outside of Europe during colonization had an enduring effect on economic development, researchers have been unable to assess these predictions directly because of an absence of data on colonial European settlement. We construct a new database on the European share of the population during colonization and examine its association with economic development today. We find a strong, positive relation between current income per capita and colonial European settlement that is robust to controlling for the current proportion of the population of European descent, as well as many other country characteristics. The results suggest that any adverse effects of extractive institutions associated with small European settlements were, even at low levels of colonial European settlement, more than offset by other things that Europeans brought, such as human capital and technology.