Suchergebnisse

PurposeBased on social exchange theory (SET), the current research aims to investigate the relationship between illegitimate tasks (ITs) and employees' knowledge-hiding behavior (KHB), incorporating the mediating role of psychological contract violation (PCV) and the moderating role of optimism.Design/methodology/approachA two-wave time-lagged survey was conducted to collect data from 196 adult Chinese full-time employees.FindingsITs were positively related to KHB, and this relationship was mediated by PCV. Furthermore, optimism buffered the connection between ITs and PCV as well as the mediating effect of PCV on the relationship between ITs and KHB.Practical implicationsFor managers, this study made them aware of the hidden costs of ITs; that is, employees may respond by concealing knowledge in the organization.Originality/valueThis study provides a more nuanced understanding of the relationship between ITs and employees' subtle deviant behavior, KHB and hitherto unspecified mediating and moderating factors that explain this process.

We examined the effect of social connections of public servants in China on citizens' perception of promotion fairness. We conducted a survey with 401 citizens employed in various different sectors in China, who were provided with a vignette involving the social connections/lack of
social connections of public servants as the manipulated variable. The results showed that having social connections was significantly and negatively correlated with citizens' perception of public servants' promotion fairness. Our findings offer new insight into the importance of an informal
factor in citizen perceptions of fairness, contribute to the literature on promotion fairness, and generate managerial implications for public servants' promotion process in regard to increasing citizen trust in the government. Study limitations are discussed and directions for future research
are presented.

The extant pieces of literature on discretion has mainly focused on its effect on policy implementation and public service delivery, but few studies have looked at its influence on street-level bureaucrats' work behavior, such as taking charge behavior (TCB), which is of great importance for government reforms, especially in developing and transitional countries. Based on the self-determination theory, this study examines whether and how discretion promotes street-level bureaucrats' TCB. Two studies were conducted among street-level bureaucrats in China. First, a survey experiment (n = 355) suggests that discretion positively predicts street-level bureaucrats' TCB. Then, a survey questionnaire study (n = 442) shows that discretion is positively related to TCB through the mediator of public service motivation (PSM). We concluded with implications for theory and practice.

Abstract. Sea ice disasters seriously threaten the structural safety of oil platforms in the Bohai Sea. Therefore, it is necessary to carry out a risk assessment of sea ice disasters on oil platforms in the Bohai Sea. In this study, a risk assessment of sea ice disasters on fixed jacket platforms in Liaodong Bay, in the Bohai Sea, was performed in five steps. Firstly, the formation mechanisms of sea ice disasters were analyzed and the sources and modes of sea ice risks were summarized. Secondly, according to the calculation formulas of extreme ice force, dynamic ice force, and accumulated force, several ice indices such as thickness, motion, strength, period, and concentration were proposed as the hazard indices, and corresponding values were then assigned to the proposed indices based on ice conditions in the Bohai Sea. Thirdly, based on four structural failure modes – structural overturning by extreme ice force (Mode 1), structural fracture failure caused by dynamic ice force (Mode 2), the damage of facilities caused by dynamic ice force (Mode 3), and structural function failure caused by accumulated ice (Mode 4) – the structural vulnerability index, overturning index, dynamic index, ice-induced vibration index, and function index were proposed, and corresponding values were assigned to the structural vulnerability index of fixed jacket platforms in Liaodong Bay. Fourthly, the weight of each risk index was determined according to previously recorded sea ice disasters and accidents, and the sea ice risk was then calculated with the weighted synthetic index method. Finally, with the above index system and risk assessment methods, the risk assessment of sea ice disasters on 10 jacket platforms in three sea areas in Liaodong Bay was carried out. The analysis results showed that efficient sea ice prevention strategies could largely mitigate the sea ice-induced vibration-related risks of jacket platforms in Liaodong Bay. If steady-state vibration occurs (usually in front of the vertical legged structure) or the structural fundamental frequency is high, the structural vulnerability is significantly increased and the calculated risk levels are high. The sea ice risk assessment method can be applied in the design, operation, and management of other engineering structures in sea ice areas.

Social and behavioral studies more and more often yield multi-block data, which consist of novel blocks of data (e.g., data from wearable devices) and traditional blocks of data (e.g., survey data) collected from the same sample. Multi-block data offer researchers valuable insights into complex social mechanisms, where several influences act together. Yet such mechanisms are likely to differ among subgroups. Hence, fully revealing the composite mechanisms underlying multi-block data is challenging, since proper clustering analysis of such data requires methods that simultaneously detect the covariation of variables underlying all data blocks and the group differences therein. Additionally, the methods should be able to handle high-dimensional datasets, which might include many irrelevant variables. Here, we present Clusterwise Sparse Simultaneous Component Analysis (CSSCA), a method that groups the subjects that are driven by the same mechanisms and, at the same time, extracts cluster-specific components that model these mechanisms. By imposing structure constraints, CSSCA further distinguishes common mechanisms that underlie all data blocks from distinctive mechanisms that only underlie one or a few data blocks. In extensive simulations, CSSCA delivered convincing results in recovering the clusters and their associated component structures across various conditions. More importantly, CSSCA showed a clear advantage over existing methods when substantial cluster differences in the component structure were present. We demonstrated the usefulness of CSSCA in an application to data stemming from a study on personality.

At present particulate matter (PM₂.₅) pollution represents a serious threat to the public health and the national economic system in China. This paper optimizes the whitening coefficient in a grey Markov model by a genetic algorithm, predicts the concentration of fine particulate matter (PM₂.₅), and then quantifies the health effects of PM₂.₅ pollution by utilizing the predicted concentration, computable general equilibrium (CGE), and a carefully designed exposure–response model. Further, the authors establish a social accounting matrix (SAM), calibrate the parameter values in the CGE model, and construct a recursive dynamic CGE model under closed economy conditions to assess the long-term economic losses incurred by PM₂.₅ pollution. Subsequently, an empirical analysis was conducted for the Beijing area: Despite the reduced concentration trend, PM₂.₅ pollution continued to cause serious damage to human health and the economic system from 2013 to 2020, as illustrated by various facts, including: (1) the estimated premature deaths and individuals suffering haze pollution-related diseases are 156,588 (95% confidence intervals (CI): 43,335–248,914)) and six million, respectively; and (2) the accumulated labor loss and the medical expenditure negatively impact the regional gross domestic product, with an estimated loss of 3062.63 (95% CI: 1,168.77–4671.13) million RMB. These findings can provide useful information for governmental agencies to formulate relevant environmental policies and for communities to promote prevention and rescue strategies.

At present particulate matter (PM(2.5)) pollution represents a serious threat to the public health and the national economic system in China. This paper optimizes the whitening coefficient in a grey Markov model by a genetic algorithm, predicts the concentration of fine particulate matter (PM(2.5)), and then quantifies the health effects of PM(2.5) pollution by utilizing the predicted concentration, computable general equilibrium (CGE), and a carefully designed exposure–response model. Further, the authors establish a social accounting matrix (SAM), calibrate the parameter values in the CGE model, and construct a recursive dynamic CGE model under closed economy conditions to assess the long-term economic losses incurred by PM(2.5) pollution. Subsequently, an empirical analysis was conducted for the Beijing area: Despite the reduced concentration trend, PM(2.5) pollution continued to cause serious damage to human health and the economic system from 2013 to 2020, as illustrated by various facts, including: (1) the estimated premature deaths and individuals suffering haze pollution-related diseases are 156,588 (95% confidence intervals (CI): 43,335–248,914)) and six million, respectively; and (2) the accumulated labor loss and the medical expenditure negatively impact the regional gross domestic product, with an estimated loss of 3062.63 (95% CI: 1,168.77–4671.13) million RMB. These findings can provide useful information for governmental agencies to formulate relevant environmental policies and for communities to promote prevention and rescue strategies.

Politicians are influential both in directing policies about refugees and in framing public discourse about them. However, unlike other host country residents, politicians' attitudes towards refugees and integration are remarkably understudied. We therefore examine similarities and differences between politicians' attitudes towards refugee integration and those held by citizens. Based on the stereotype content model, we expect that political ideology informs stereotypes about refugees, which subsequently shape attitudes towards refugee integration. Based on the Contact Hypothesis, we further argue that personal contact with refugees reduces negative stereotypes about them—in particular for those endorsing a right‐wing ideology. We draw on data collected via two surveys with 905 politicians and 8013 citizens in the Netherlands to show that (1) unlike those with a left‐wing orientation, residents (i.e., both politicians and citizens) with a right‐wing orientation hold more negative stereotypes about refugees, which in turn relate to more negative attitudes towards refugee integration; (2) personal contact with refugees is associated with less negative stereotypes among residents; and (3) politicians, compared to citizens, report less negative stereotypes and more positive attitudes towards refugee integration. The practical implication of fostering residents' contact with refugees as well as the implications for future research are discussed.