Translating cross-lagged effects into incidence rates and risk ratios: The case of psychosocial safety climate and depression

Longitudinal studies are the gold standard of empirical work and stress research whenever experiments are not plausible. Frequently, scales are used to assess risk factors and their consequences, and cross-lagged effects are estimated to determine possible risks. Methods to translate cross-lagged effects into risk ratios to facilitate risk assessment do not yet exist, which creates a divide between psychological and epidemiological work stress research. The aim of the present paper is to demonstrate how cross-lagged effects can be used to assess the risk ratio of different levels of psychosocial safety climate (PSC) in organisations, an important psychosocial risk for the development of depression. We used available longitudinal evidence from the Australian Workplace Barometer (N?=?1905) to estimate cross-lagged effects of PSC on depression. We applied continuous time modelling to obtain time-scalable cross effects. These were further investigated in a 4-year Monte Carlo simulation, which translated them into 4-year incident rates. Incident rates were determined by relying on clinically relevant 2-year periods of depression. We suggest a critical value of PSC?=?26 (corresponding to ?1.4 SD), which is indicative of more than 100% increased incidents of persistent depressive disorder in 4-year periods compared to average levels of PSC across 4 years.     

The neglected mediating role of self-efficacy in the goal setting process in local public administrations

To analyse the role of self-efficacy in goal setting in public administrations, this study combines goal-setting theory, public service motivation literature and cognitive theory. Using partial least squares structural equation modelling (PLS-SEM), survey data from 105 German civil servants are analysed. The results underline the role of goal setting (represented by goal difficulty and specificity) in determining the self-efficacy of public servants. Public service motivation and goal specificity both increase public servants’ work performance; however, the effects of goal difficulty are negatively mediated by the employee’s self-efficacy. That finding reflects the central role of self-efficacy, which should not be ignored in the goal-setting processes of public administrations.     

The effects of leadership change on team escalation of commitment

Although teams benefit from developing plans and processes that boost efficiency and reduce uncertainty, they may become too attached to these plans and escalate commitment when an alternative response is needed. Drawing on theories of team leadership, team processes and escalation of commitment, we propose that a change in leadership can help the team reduce commitment to outdated plans and avoid further escalation over time. Across two studies, we tested and found support for our hypotheses and provide evidence that leadership change can break the cycle of escalation by enhancing leader-driven team reflection and refocusing the team on error correction instead of additional investment. We discuss how the results of these studies extend existing theory and add to our understanding of the important role leaders play in enhancing team adaptation and preventing team escalation.     

The impact of acquisitions on firm performance: A review of the evidence

This paper presents a review of empirical research on the impact of acquisitions on firm performance. The evidence suggests that, in the short run, acquisitions have at best an insignificant impact on shareholder wealth. Long‐run performance analysis reveals overwhelmingly negative returns, while the evidence using accounting performance measures is mixed. The review also examines the impact of bid characteristics on performance. The acquisition of hostile targets, transactions that are paid for with cash and acquisitions of larger targets are associated with superior (or at least less negative) performance, while there is mixed evidence on the benefits of related acquisitions. A number of recent studies find that acquirers with superior pre‐bid performance tend to experience significant underperformance in the post‐bid period.     

Dynamic Global Games of Regime Change: Learning,Multiplicity, and the Timing of Attacks

Global games of regime change—coordination games of incomplete information in which a status quo is abandoned once a sufficiently large fraction of agents attack it—have been used to study crises phenomena such as currency attacks, bank runs, debt crises, and political change. We extend the static benchmark examined in the literature by allowing agents to take actions in many periods and to learn about the underlying fundamentals over time. We first provide a simple recursive algorithm for the characterization of monotone equilibria. We then show how the interaction of the knowledge that the regime survived past attacks with the arrival of information over time, or with changes in fundamentals, leads to interesting equilibrium properties. First, multiplicity may obtain under the same conditions on exogenous information that guarantee uniqueness in the static benchmark. Second, fundamentals may predict the eventual fate of the regime but not the timing or the number of attacks. Finally, equilibrium dynamics can alternate between phases of tranquility—where no attack is possible—and phases of distress—where a large attack can occur—even without changes in fundamentals.     

Research and development project selection and resource allocation: a review of quantitative modelling approaches

This paper reviews the literature on quantitative modelling for research and development (R&;D) project selection and resource allocation. The topic has been a subject of operations research for about four decades. Its importance stems from the fact that R&D projects are a core element of corporate renewal, heavily influence a firm's market success and, if not properly chosen and trimmed, may waste large amounts of resources or even ruin the enterprise. Our survey classifies and characterizes the various modelling approaches.     

Detecting mean increases in Poisson INAR(1) processes with EWMA control charts

Processes of serially dependent Poisson counts are commonly observed in real-world applications and can often be modeled by the first-order integer-valued autoregressive (INAR) model. For detecting positive shifts in the mean of a Poisson INAR(1) process, we propose the one-sided s exponentially weighted moving average (EWMA) control chart, which is based on a new type of rounding operation. The s-EWMA chart allows computing average run length (ARLs) exactly and efficiently with a Markov chain approach. Using an implementation of this procedure for ARL computation, the s-EWMA chart is easily designed, which is demonstrated with a real-data example. Based on an extensive study of ARLs, the out-of-control performance of the chart is analyzed and compared with that of a c chart and a one-sided cumulative sum (CUSUM) chart. We also investigate the robustness of the chart against departures from the assumed Poisson marginal distribution.