Role of supervisor behavioral integrity for safety on the relationship between top management safety climate, safety motivation and safety performance

The relationship of Value dimensions in Turk Society with fatalistic tendencies, safety motivation, risk perception and safety performance

Understanding the role of people in occupational accidents is very difficult. It is always assumed that people perform the behaviour that feels right to them. This study's main topic is the relationship between values, which form the basis of human behaviour, and safety motivation, fatalistic tendencies, risk perception and safety behaviour. In this context, for the aim of the study, path analysis and partial correlation analysis were used to examine the relationship between variables, and tests were used to examine the relationship between demographic variables with 701 participants from NUTS-12 region of Turkey. According to the findings of the research, it was determined that most of the 19 value dimensions and the top values of self-protection and growth and the top value dimensions of conservation, self-enhancement, self-transcendence and openness to change affect fatalism tendencies, risk perception, safety motivation(SM) and safety performance(SP). While self-protection, conservation and self-enhancement top values have a negative effect on SP, openness to change, self-transcendence and growth top values have a positive effect on SP. Taking into consideration that individuals will exhibit behaviours based on the value dimensions they attach importance to, OHS trainings should be developed in accordance with the value dimensions given importance according to NUTS-12 regions. Furthermore, legal support should be provided to eliminate and reduce the negative aspects of value dimensions for OHS.

An interpretable clustering approach to safety climate analysis: Examining driver group distinctions

The transportation industry, particularly the trucking sector, is prone to workplace accidents and fatalities. Accidents involving large trucks accounted for a considerable percentage of overall traffic fatalities. Recognizing the crucial role of safety climate in accident prevention, researchers have sought to understand its factors and measure its impact within organizations. While existing data-driven safety climate studies have made remarkable progress, clustering employees based on their safety climate perception is innovative and has not been extensively utilized in research. Identifying clusters of drivers based on their safety climate perception allows the organization to profile its workforce and devise more impactful interventions. The lack of utilizing the clustering approach could be due to difficulties interpreting or explaining the factors influencing employees' cluster membership. Moreover, existing safety-related studies did not compare multiple clustering algorithms, resulting in potential bias. To address these problems, this study introduces an interpretable clustering approach for safety climate analysis. This study compares five algorithms for clustering truck drivers based on their safety climate perceptions. It also proposes a novel method for quantitatively evaluating partial dependence plots (QPDP). Then, to better interpret the clustering results, this study introduces different interpretable machine learning measures (Shapley additive explanations, permutation feature importance, and QPDP). The Python code used in this study is available at https://github.com/NUS-DBE/truck-driver-safety-climate. This study explains the clusters based on the importance of different safety climate factors. Drawing on data collected from more than 7,000 American truck drivers, this study significantly contributes to the scientific literature. It highlights the critical role of supervisory care promotion in distinguishing various driver groups. Moreover, it showcases the advantages of employing machine learning techniques, such as cluster analysis, to enrich the scientific knowledge in this field. Future studies could involve experimental methods to assess strategies for enhancing supervisory care promotion, as well as integrating deep learning clustering techniques with safety climate evaluation.

Safety climate and safety behaviors: Adapting and validating a positively worded safety climate scale through the time-lagged approach

BACKGROUND

Contemporary literature raises serious questions about the inclusion of negatively worded items in the safety climate scale. Despite these reservations, limited efforts have been made to address this shortcoming.

OBJECTIVE

The present study aims to adapt and empirically validate the ten-items group-level safety climate scale with the purpose of replacing negatively worded items with positively worded ones after a thorough validation process. The present study is one of the first to propose an empirically validated group-level safety climate scale that uses positive items to measure the safety climate construct.

METHODS

Study 1 was conducted using a sample of 135 participants. Study 2 used a time-lagged approach to validate the scale, with a sample of 173 production workers from six oil and gas organizations in Malaysia. The Partial Least Squares Structural Equation Modeling (PLS-SEM) method was used to test the hypothesized relationships.

RESULTS

In Study 1, the results of the exploratory factor analysis showed good reliability for the revised scale. In Study 2, the results of the PLS-SEM analysis demonstrated a positive relationship between safety climate and safety behaviors, thereby validating the revised and translated scale of safety climate.

CONCLUSION

The revised safety climate scale will not only improve data quality, but it will also increase response rates. Additionally, the revised scale will assist managers in understanding the true perceptions of safety climate in their organization, regardless of the cultural context in which the scale is used.

Healthcare workers' safety compliance behavior in times of COVID-19: The interaction model

BACKGROUND

Strengthening safety compliance behaviour can reduce the organizations' unexpected financial losses and prevent employees from continuous COVID-19. It drives this study to create a research framework involved by organizational, individual and social factors to predict employees' safety compliance behaviour.

OBJECTIVE

This study examines how risk perceptions of COVID-19, employee well-being, workplace health and safety training, safety motivation and safety related stigma impact safety compliance behavior in times COVID-19 pandemic.

METHODS

A self-administered questionnaire was disseminated to healthcare workers. In all, 344 acceptable questionnaires were derived for further analysis.

RESULTS

The results revealed that the risk perception of COVID-19 and employee well-being has no significant relationship with safety compliance behavior. Similarly, safety related stigma also has no moderating effect on safety motivation and safety compliance behavior. However, workplace health and safety training and safety motivation have significant relationships with safety compliance behavior.

CONCLUSION

This study contributes to the literature by illuminating on the importance of organizational, individual, social factors and how they can interact with safety compliance behaviour. Additionally, knowing the unique function of safety related stigma in building safety compliance behaviour may help guide future efforts and training initiatives to enhance workplace safety.

The effect of empowering leadership on miners' unsafe behavior: a cross-level chain mediation model

Miners' unsafe behavior has always been a key issue in coal mine safety management. Numerous studies have shown that leadership is an important factor influencing miners' unsafe behavior. A cross-level structural model was constructed based on social cognitive theory, using psychological safety and safety climate as intermediary variables, to analyze the effect of empowering leadership on miners' unsafe behavior. Data were gathered from 272 coal miners on 59 working teams. Multilevel regression analysis and the Monte Carlo method were employed to analyze the influence of the empowering leadership on miners' unsafe behavior. The results showed that empowering leadership was negatively related to miners' unsafe behavior. Psychological safety and safety climate mediated the relationship between empowering leadership and miners' unsafe behavior, and also jointly mediated in the chain. These findings enrich existing research results on miners' unsafe behavior and provide a beneficial enlightenment to coal mine safety management.

Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support

Rumination is a common problem and is associated with reduced psychological well-being. However, little is known about how rumination in the workplace is affected by interpersonal relationships. We propose that negative workplace behavior could serve as a potential influencing factor for rumination. Therefore, the current study constructed a multilevel moderated mediation model to investigate the relationship between workplace unit social undermining and interpersonal rumination. We also examined whether unit social support moderated that relationship and whether being the subject of envy mediated that relationship. Survey data were collected from 630 employees in China. The results indicate that: (1) a high level of unit social undermining by either a supervisor or co-workers has a significant positive influence on interpersonal rumination; (2) being the subject of envy exerts a mediating effect between unit supervisor social undermining and interpersonal rumination, as well as between unit co-worker social undermining and interpersonal rumination; and (3) unit social support moderates the associations between unit supervisor/co-worker social undermining and interpersonal rumination. These findings extend the research on rumination to the field of management and interpersonal relationships and emphasize the potential mechanisms of rumination, providing significant guidance for reducing staff rumination and improving psychological well-being.