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Eduvest � Journal of Universal Studies Volume 4 Number 8, August, 2024 p- ISSN 2775-3735- e-ISSN 2775-3727 |
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Assessing the Influence of
Safety Culture to Employee Safety Performance Mediated by Safety Communication
in Coal-Fired Power Plant |
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Bambang
Jiwantoro Universitas
Bunda Mulia, Master of Management, Jakarta, Indonesia Email: [email protected] |
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ABSTRACT |
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This study analyzes the effect
of safety culture on employee safety performance at a Coal Fired Power Plant
(CFPP) in Java, as well as the mediating role of safety communication and
moderating role of service years. This study aims to investigate the direct
and indirect effects between the variables of safety culture, safety
communication and employee safety performance. In addition, the study also
explored the moderating role of service year in the relationship between
safety culture and employee safety performance. Data was obtained from
distributing questionnaires to CFPP employees using a stratified sampling
method. SmartPLS SEM. The findings reveal that safety culture does not have a
significant direct effect on employee safety performance. However, safety
communication significantly mediates the relations between safety culture and
employee safety performance. The service year does not moderate the
relationship between safety culture and employee safety performance This
indicates that other factors such as continuous training, reward system, and
work environment may be more influential in this context. |
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KEYWORDS |
Safety
Culture, Safety Communication, Employee Safety Performance, Service Year |
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This work is
licensed under a Creative Commons Attribution-ShareAlike
4.0 International |
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INTRODUCTION
The demand for electricity in Indonesia continues to
increase from year to year in line with the pace of economic development and
the increasing population, with the average electricity consumption per capita
in 2023 reaching 1,285 kWh up from 1,173 kWh in 2022. However, amidst the
development of the power industry, workplace safety is still a major concern in
Indonesia.
Work accidents are very costly for companies,
employees and state agencies.� The costs
caused by work accidents can be likened to an iceberg. Direct costs can be
easily calculated, including medical expenses, costs incurred to repair damaged
facilities, and wages paid to workers during the period they are unable to
work.
Based on the Liberty Mutual Workplace Safety Index
2023 (Doyle, 2023) According to the Liberty
Mutual Workplace Safety Index 2023 (Doyle, 2023), in 2020, industries in the
United States incurred $58.61 billion in direct costs due to injured workers,
of which 82.2 percent ($48.15 billion) was for the top 10 causes of injuries
and illnesses. The 10 most costly causes of workplace injuries and illnesses
are presented below:
Table 1 Accident Cost Data
|
Causes |
�Cost (Billion USD) |
�Percentage |
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�Excessive exertion involving outside sources |
$12.84 |
21.9% |
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�Fall at the same rate |
$8.98 |
15.3% |
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�Falling at a lower level |
$6.09 |
10.4% |
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�Falling on objects or equipment |
$5.14 |
8.8% |
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�Exertion or other bodily reactions |
$3.67 |
6.3% |
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�Exposure to other harmful substances (Including COVID-19) |
$3.35 |
5.7% |
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�Road incidents involving motorized land
vehicles |
$2.58 |
4.4% |
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�Trapped or compressed by equipment or
objects |
$1.98 |
3.4% |
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�Slips or trips without falling |
$1.92 |
3.3% |
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Pedestrian
vehicle incidents |
$1.61 |
2.7% |
One of the factors that contribute to work safety is
safety culture. Safety culture refers to the values, beliefs and norms held by
the company and its employees related to work safety. A strong safety culture
can encourage employees to prioritize safety, follow safety procedures and
report potential hazards.
This research was conducted at one of the Coal Fired
Power Plant (CFPP) in Java to analyze the company's efforts to improve safety
culture and the factors that influence it. In 2019, the Company began measuring
the Safety Culture Maturity Model using the Bradley Curve. Initially, a Safety
Perception Survey was conducted in 2019 which showed that the Company was in a
Dependent position (see Figure 1).
Figure 1 Safety Perception Survey 2019
The survey was targeted only at permanent CFPP
employees and did not involve employees of partners / contractors, especially
contractors who are fix services and serve the company for a long period of
time.
Since 2019, the company has implemented an Employee
Observation program to enhance work safety communication, allowing employees to
identify safe and unsafe conditions. While the program's data serve as leading
indicators of employee performance, participation from 2021 to 2023 has
stagnated, averaging 210 participants monthly, which is significantly lower
than expected given the total workforce. This underreporting of unsafe
conditions could potentially lead to safety incidents, with recurring issues related
to Personal Protective Equipment, Person Position, and Person Reaction.
Research indicates that a positive safety culture,
which influences employee safety performance, significantly reduces workplace
incidents across various industries. However, safety performance is also
affected by other factors, such as communication, knowledge, engagement, and
leadership, with employee tenure playing a crucial role in safety practices.
Further studies are needed to explore the relationship between safety culture,
communication, and employee tenure in improving safety performance.
Based on the explanation above, the problem
identification in this study is to investigate the effect of safety culture on
employee safety performance and investigate the direct and indirect
relationship between safety culture variables, safety communication, and
employee safety performance and the moderating role of employee tenure. This
research involves more employees of partners / contractors.
Theoretical Background
Safety culture, a
key element of organizational culture, reflects workplace safety norms and is
linked to improved operational results. Edgar Schein's concept of
organizational culture, divided into three levels�artifacts, espoused values,
and basic assumptions�helps explain how organizational culture influences
safety culture. Through factors like work environment, leadership, and
communication, organizational culture shapes employee safety practices. The
relationship between organizational structure and safety culture is complex,
requiring cultural norms to support roles, rules, and authority.
Safety Culture
Safety culture
gained prominence after the Chernobyl disaster, leading to enhanced safety
measures and labor protection. It is multifaceted,
involving organizational policies, leadership actions, and individual
responses. Safety culture includes roles, rules, leadership, communication, and
human factors. Maturity models, such as Hudson's five-stage model, assess
safety culture development, ranging from a pathological stage�where safety is
secondary to business priorities�to a generative stage, where safety is
ingrained in the company culture.
Safety
Communication
Safety
communication involves the exchange of information about well-being and risk
management in the workplace. Effective safety communication is crucial in
reducing risks and ensuring a safe environment. It includes conveying safety
threats, regulations, and progress through various media, which contributes to
building a safer workplace.
Employee Safety
Performance
Employee safety
performance is vital in high-risk industries like construction, utilities, and
manufacturing. Companies use leading (proactive) and lagging (reactive)
indicators to measure safety performance. Key factors influencing safety
performance include management commitment, employee engagement, and safety
communication. Effective safety management strategies can improve overall
safety outcomes in various industries.
Hypothesis
H1: Safety culture has a positive and significant
influence on employee safety performance at the Steam Power Plant (CFPP).
H2: Safety culture has a positive and significant
influence on safety communication at the Steam Power Plant (CFPP).
H3: Safety Communication has a positive and
significant influence on employee safety performance at the Steam Power Plant
(CFPP).
H4: Safety communication acts as a mediator of the
relationship between safety culture and employee safety performance in Steam
Power Plants (CFPP).
H5: Service Years acts as a moderator of the
relationship between safety culture and employee safety performance at the
Steam Power Plant (CFPP).
RESEARCH METHOD
Research Design
This study uses a quantitative design. Research data
will be collected at one time from a sample of employees at the Steam Power
Plant. This design was chosen because it allows researchers to analyze the
relationship between research variables simultaneously.
Figure 3 Research Model
Variable
& Measurement Scale
This study examines five types of variables:
independent, dependent, intervening, moderator, and control variables. The
independent variable, Safety Culture, influences the dependent variable,
Employee Safety Performance, by causing positive or negative changes. Safety
Communication acts as the intervening variable, explaining the relationship
between the independent and dependent variables. Service Years serve as the
moderating variable, potentially altering the strength or direction of the
relationship between the independent and dependent variables. All variables are
measured using a 5-point Likert Scale, which captures participants' agreement
or disagreement with various statements.
Population
and Sample
The population determined in this study are permanent
employees of the company totaling 431 people and employees of partners /
contractors who are fixed contracts with a duration of more than 1 year
totaling 200 people. This research uses Stratified Random Sampling where the
population is divided into several subpopulations or strata, and random samples
are then drawn from each stratum (Sekaran, 2016). This method was chosen
because it can ensure adequate representation of all segments of the population
in the sample and allow comparisons between different strata or subpopulations.
The samples taken were mainly from employees of
partners/contractors and a small portion from permanent employees of the
company.
�Most respondents, 42%, had a tenure with the
company between 6 and 10 years, followed by respondents with a tenure between
11 and 15 years at 25%. Only a small number of respondents had a tenure of less
than 5 years (14%) or more than 20 years (12%). This data shows that the
majority of respondents have a long working experience in the company, which
can provide deep insights into workplace safety culture and practices.
Table 3 Respondents' Period of Service
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Length of Service in the Company |
Frequency |
Percent |
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Less than 5 years |
14 |
14% |
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6 - 10 years |
42 |
42% |
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11 - 15 years |
25 |
25% |
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16 - 20 years |
7 |
7% |
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More than 20 years |
12 |
12% |
RESULT AND DISCUSSION
Outer
Model Evaluation
Evaluation
of the outer model or measurement model is carried out to calculate and test
the validity and reliability or reliability of the model. Outer models with
reflective indicators are evaluated through convergent validity and
discriminant validity of the indicators (Ghozali,
2016). In this research stage, an SEM model diagram is developed which aims to
make it easier to see the causal relationships to be tested.
Validity Test
Outer
loading testing is used to determine how far an indicator is able to reflect
the variables in the study. In the partial least square test, the
standardization for the outer loading assessment is 0.70, so all indicators
that have a loadings value> 0.70 mean that they have been able to reflect
the latent variable. (Hair et al., 2019).
Figure 5 Outer Loading Graphical Output
Figure
51 shows the Outer Loading Graphical Output which illustrates the relationship
between latent variables and their indicators in this study. The Safety Culture
latent variable has a number of indicators such as CO-01 to OL-04, with high
outer loading values, indicating a strong correlation between the indicators
and the latent variable. Safety Communication also has several indicators
(SCO-1 to SCO-5) with high outer loading values, indicating that these
indicators are very good at measuring their latent variables.
Employee
Safety Performance (ESP-1 to ESP-8) and Service Years (SY-1 and SY-2) also have
high outer loading values, indicating a strong correlation between the
indicators and their latent variables. Arrow lines between latent variables
indicate the relationship between variables, with coefficient values describing
the strength and direction of the relationship. For example, Safety Culture has
a direct influence on Safety Communication, which in turn affects Employee
Safety Performance. The moderating relationship by Service Years is also
illustrated, albeit with a smaller influence. The figure as a whole shows the
strength and direction of the relationship between the research variables as
well as the reliability of the indicators in measuring their respective latent
variables.
Average Variance
Extracted (AVE) Test
The
Average Variance Extracted (AVE) test is a method for measuring convergent
validity in research models. AVE shows how much the latent variable is able to
explain the variance of its indicators. A high AVE value indicates that the
indicators have good internal consistency and are valid in measuring the latent
variable. Generally, an AVE value greater than 0.5 is considered adequate,
indicating that more than 50% of the indicator variance can be explained by the
latent variable.
Table 4 Average Variance Extracted (AVE)
Test Results
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Variables |
Average Variance Extracted (AVE) |
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Employee Safety Performance |
0.820 |
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Safety Communication |
0.679 |
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Safety Culture |
0.649 |
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Service Years |
0.807 |
The
AVE test results in Table 4 show that all variables in this study have AVE
values higher than 0.5, signaling good convergent validity. Employee Safety
Performance has the highest AVE value of 0.820, followed by Service Years at 0.807,
indicating that the indicators for this variable are highly consistent in
measuring their latent variable. Safety Communication and Safety Culture also
have adequate AVE values of 0.679 and 0.649, respectively, signifying that
these variables are valid in measuring the concepts they represent. Overall,
these AVE values indicate that the research model has strong convergent
validity.
Composite
Reliability Test
The
Composite Reliability test results in Table 5 show that all variables in this
study have a Composite Reliability value higher than 0.7, indicating excellent
internal consistency. Employee Safety Performance has the highest Composite
Reliability value of 0.973, indicating very high consistency between its
indicators. Safety Culture also has a very high value of 0.972, indicating that
the indicators are very reliable in measuring their latent variables. Safety
Communication and Service Years have Composite Reliability values of 0.913 and
0.893, respectively, which are still above the recommended threshold,
indicating that the indicators for this variable are also consistent in their
measurement. Overall, these Composite Reliability values indicate that the
research model has excellent internal consistency.
Table 5 Composite Reliability Test Results
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Variables |
Composite Reliability |
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Employee Safety Performance |
0.973 |
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Safety Communication |
0.913 |
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Safety Culture |
0.972 |
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Service Years |
0.893 |
Cronbach's Alpha
Test
The
Cronbach's Alpha test results in Table 6 show that all variables in this study have
Cronbach's Alpha values higher than 0.7, indicating excellent internal
consistency. Employee Safety Performance has the highest Cronbach's Alpha value
of 0.968, indicating that the indicators are very consistent in measuring the
latent variable. Safety Culture and Safety Knowledge also show very high
internal consistency with values of 0.970 and 0.958 respectively. Safety
Communication has a Cronbach's Alpha value of 0.881, which is also in a very
good range. Service Years had a Cronbach's Alpha value of 0.771, which showed
adequate internal consistency although not as high as the other variables.
Overall, these values indicate that all indicators in the study have strong
internal consistency, supporting the measurement reliability of the research
model.
Table 6 Cronbach's Alpha Test Results
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Variables |
Cronbach's Alpha |
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Employee Safety Performance |
0.968 |
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Safety Communication |
0.881 |
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Safety Culture |
0.970 |
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Service Years |
0.968 |
Discriminant
Validity Test
The
Discriminant Validity test using the Fornell-Larcker Criterion is a method for
assessing the extent to which the constructs or latent variables in the model
differ from one another. Discriminant validity is considered adequate if the
square root of the AVE (Average Variance Extracted) for each construct is
greater than the correlation between that construct and other constructs.
Table 7 Discriminant Validity Test Results
(Fornell-Larcker Criterion)
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Employee Safety
Performance |
Safety Communication |
Safety Culture |
Safety Knowledge |
Service Years |
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Employee Safety Performance |
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Safety Communication |
0.905 |
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Safety Culture |
0.842 |
0.824 |
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Service Years |
0.899 |
0.819 |
0.607 |
0.909 |
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Service Years |
0.100 |
0.042 |
0.069 |
-0.016 |
0.898 |
The
discriminant validity test results in Table 7 show that the square root of the
AVE (bold diagonal values) for each construct is greater than the correlation
between the construct and other constructs (off-diagonal values). Employee
Safety Performance has an AVE square root of 0.905, which is greater than the
correlation with other constructs. Safety Communication has a value of 0.824,
which is also greater than the correlation with other constructs. Safety
Culture has a value of 0.805, which indicates good discriminant validity as
these values are greater than the correlations between constructs. Service
Years has an AVE square root of 0.898, which is greater than the correlation
with other variables. These results indicate that each construct in this model
has adequate discriminant validity, signaling that the constructs are measuring
clearly distinct concepts.
Inner
Model Evaluation (Structural Model)
Inner
model or inner measurement is a model that connects latent variables. According
to Ramayah et al, (2018) the model feasibility test is used to determine how
far the panel data regression has succeeded in forming a good regression model
to interpret the research results. There are three stages in testing the feasibility
of the model, namely including the Determinant Coefficient (R2
), Q Squere, and F Squere.
Determinant
Coefficient Test (R )2
The
Determinant Coefficient Test (R�) is used to assess how well the proposed model
explains the variability of the dependent variable. The R� value indicates the
proportion of variance in the dependent variable that can be explained by the
independent variables in the model. An R� value close to 1 indicates that the
model has a very good ability to explain the variance in the dependent
variable, or in other words, the independent variables in the model have a
strong influence on the dependent variable. R� can be expressed as strong if
the value is greater than 0.7, moderate if the value is greater than 0.5, and
weak if the value is greater than 0.25 ((Cepeda-Carrion
et al., 2019).
Table 8 Test Results of the Coefficient of
Determination
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R-square |
Adjusted
R-square |
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Employee Safety Performance |
0.857 |
0.849 |
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Safety Communication |
0.336 |
0.329 |
The
coefficient of determination test results in Table 8 show that the Employee
Safety Performance variable has an R-square value of 0.857 and an adjusted
R-square of 0.849. This means that 85.7% of the variability in Employee Safety
Performance can be explained by the independent variables in the model,
indicating that this model is very good at explaining these variables. Safety
Communication has an R-square value of 0.336 and an adjusted R-square of 0.329,
indicating that 33.6% of the variability in Safety Communication can be
explained by the independent variables, indicating moderate explanation.
Overall, these values indicate that the model is reasonably good at explaining
the variability of the Employee Safety Performance variable, but less powerful
at explaining the variability of Safety Communication.
Predictive
Relevance Test (Q )2
The
Predictive Relevance (Q�) test was used to assess the predictive ability of the
structural model in the study. Q� is measured using a blindfolding procedure
and indicates how well the observed values are reconstructed by the model. A
positive Q� value indicates that the model has good predictive ability. Q�
values greater than 0 indicate predictive relevance, with larger values
signaling better predictions.
Table 9 Predictive Relevance (Q�) Test
Results
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Variables |
Q� |
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Employee Safety Performance |
0.749 |
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Safety Communication |
0.288 |
The
Predictive Relevance test results in Table 9 show that all variables have
positive Q� values, indicating that the model has good predictive ability.
Employee Safety Performance has the highest Q� value of 0.749, indicating that
this model has excellent predictive ability for this variable. Safety
Communication has a Q� value of 0.288, indicating moderate predictive ability.
Overall, these Q� values indicate that the structural model used in this study
was able to accurately predict the observed values for the variables tested.
Effect Size Test
(F )2
The
Effect Size (F�) test is used to measure the influence or relative effect of
each independent variable on the dependent variable in the structural model.
The F� value indicates the size of the influence of the independent variable on
the dependent variable. Generally, an F� value of 0.02 is considered to have a
small effect, 0.15 has a medium effect, and 0.35 has a large effect.
Table 10 Effect Size Test Results (F2)
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Employee Safety Performance |
Safety Communication |
Safety Culture |
Service Years |
Service Years x Safety Culture |
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Employee Safety Performance |
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Safety Communication |
0.238 |
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Safety Culture |
0.019 |
0.506 |
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Service Years |
0.073 |
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Service Years x Safety Culture |
0.025 |
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The
effect size test results in Table 10 show that variables have various effect
sizes on Employee Safety Performance and other variables. Safety Communication
has an effect size of 0.238 on Employee Safety Performance, which indicates a
moderate influence. Safety Culture has a small effect size on Employee Safety
Performance (0.019) but has a large effect on Safety Communication (0.506).
Service Years shows a small effect size on Employee Safety Performance with a
value of 0.073. Finally, the interaction between Service Years and Safety
Culture shows a small effect size on Employee Safety Performance with a value
of 0.025. This data shows that Safety Communication has a significant influence
on Employee Safety Performance, while the influence of Safety Culture is
greater on Safety Communication than directly on Employee Safety Performance.
Test Path Coefficients
Bootstrapping
is a resampling technique used to estimate the accuracy (standard error,
confidence interval) of model estimates. Figure 6 shows the bootstrapping
results of the structural model analyzed in this study. In this figure, the
numbers displayed above the arrows represent the t-statistic values, which
indicate the statistical significance of the relationship between the latent
variables.
- Safety Culture to Safety Communication (0.336):
The relationship between Safety Culture and Safety Communication is
significant with a strong t-statistic value (0.000), indicating a
significant effect of Safety Culture on Safety Communication.
- Safety Communication to Employee Safety
Performance (0.857): The relationship between Safety Communication and
Employee Safety Performance is very significant with a t-statistic value
(0.000), indicating that Safety Communication has a very large and significant
influence on Employee Safety Performance.
- Service Years to Employee Safety Performance
(-0.070): The effect of Service Years on Employee Safety Performance has a
t-statistic value that shows significance (0.001), but the effect is
negative and small, indicating that length of service is not positively
related to employee safety performance.
- Service Years � Safety Culture to Employee Safety
Performance: The interaction relationship between Service Years and Safety
Culture with Employee Safety Performance shows a t-statistic value of
(0.456), which indicates moderating significance in the relationship.
The
structural model shown in Figure 6 shows that Safety Culture, Safety
Communication, and Safety Knowledge have a significant influence on Employee
Safety Performance. Service Years also has a significant but negative
influence, suggesting complex dynamics in this relationship. The use of
bootstrapping provides greater confidence in the model estimates and
demonstrates the statistical significance of the relationships tested in this
study.
Figure 6 Bootstrapping (Model Structure)
Hypothesis Test
Hypothesis
testing in this study was conducted to test the relationship between latent
variables that had been hypothesized. Table 11 displays the results of the Path
Coefficient test which includes the original sample, sample mean, standard
deviation, t-statistics, and p-values to determine the significance of the
relationship between these variables.
Table 11 Path Coefficient Test Results
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Original sample (O) |
Sample mean (M) |
Standard deviation (STDEV) |
T statistics (|O/STDEV|) |
P values |
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Safety Communication ->
Employee Safety Performance |
0.329 |
0.342 |
0.082 |
4.023 |
0.000 |
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Safety Culture ->
Employee Safety Performance |
-0.067 |
-0.069 |
0.088 |
0.766 |
0.444 |
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Safety Culture -> Safety
Communication |
0.579 |
0.586 |
0.099 |
5.864 |
0.000 |
|
Service Years ->
Employee Safety Performance |
0.103 |
0.097 |
0.052 |
1.984 |
0.047 |
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Service Years x Safety
Culture -> Employee Safety Performance |
-0.070 |
-0.096 |
0.094 |
0.746 |
0.456 |
- Safety Culture and
Employee Safety Performance
The
results of the path coefficient test show that safety culture has no
significant effect on employee safety performance with an original sample value
of -0.067, t-statistic 0.766, and p-value 0.444. This means that in the context
of this study, safety culture does not directly affect employee safety
performance at CFPP. Although previous literature suggests that safety culture
can influence safety performance, the results of this study do not support this
hypothesis. Hypothesis H1 is thus rejected.
- Safety Culture and
Safety Communication
Safety
culture has a positive and significant influence on safety communication with
an original sample value of 0.579, t-statistic of 5.864, and p-value of 0.000.
This shows that a strong safety culture in the organization can improve
effective safety communication. This is consistent with previous research which
shows that a good safety culture can strengthen the way safety information is
conveyed and understood in the organization. Therefore, hypothesis H2 is
accepted.
- Safety Communication
and Employee Safety Performance
Safety
communication has a positive and significant influence on employee safety
performance with an original sample value of 0.329, t-statistic of 4.023, and
p-value of 0.000. This indicates that effective safety communication plays an
important role in improving employee safety performance. This result is
consistent with previous findings which show that good safety communication can
improve employee safety behavior and attitudes, so hypothesis H3 is accepted.
- Interaction of
Service Years and Safety Culture on Employee Safety Performance
The
interaction between Service Years and safety culture has no significant effect
on employee safety performance with an original sample value of -0.070,
t-statistic 0.746, and p-value 0.456. This shows that tenure does not moderate
the relationship between safety culture and employee safety performance in the
context of this study. This result contradicts the proposed hypothesis and
suggests that other factors may play a greater role in moderating this
relationship. Therefore, hypothesis H5 is rejected.
Indirect
hypothesis testing is carried out to understand the mediating effect of
intermediate variables between independent and dependent variables. Table 12
displays the results of the path coefficient test for the mediating
relationship of safety communication and safety knowledge between safety
culture and employee safety performance.
Table 12 Indirect Hypothesis Test Results
|
|
Original sample (O) |
Sample mean (M) |
Standard deviation (STDEV) |
T statistics (|O/STDEV|) |
P values |
|
Safety Culture -> Safety
Communication -> Employee Safety Performance |
0.191 |
0.201 |
0.062 |
3.090 |
0.002 |
The
test results show that safety culture has a significant indirect effect on
employee safety performance through safety communication with an original
sample value of 0.191, t-statistic 3.090, and p-value 0.002. This means that
safety communication mediates the relationship between safety culture and
employee safety performance. In other words, a strong safety culture improves
safety communication, which in turn improves employee safety performance. This
hypothesis is supported by the literature which shows that effective safety
communication plays an important role in the implementation of a good safety
culture, thereby strengthening safety performance.
From
the results of hypothesis testing, it can be concluded that safety
communication has a positive and significant influence on employee safety
performance. Safety culture has a significant influence on safety communication
but not directly on employee safety performance. Years of service (Service
Years) has a significant moderating effect on employee safety performance, but
the interaction between Service Years and safety culture is not significant.
From
the results of the indirect hypothesis test, it can be concluded that safety
communication mediates the relationship between safety culture and employee
safety performance significantly. A strong safety culture improves safety
communication, which in turn improves employee safety performance at the power
plant. These results emphasize the importance of the mediating role of safety
communication and knowledge in the relationship between safety culture and
employee safety performance.
Discussion
Safety
Culture and Employee Safety Performance
The results showed that safety culture does not have a
significant influence on employee safety performance in CFPP (original sample
value -0.067, t-statistic 0.766, and p-value 0.444). This finding contradicts
many previous studies which show that safety culture has a positive influence
on employee safety performance. For example, (Bautista-Bernal
et al., 2024) and (Abeje & Luo, 2023)
found that a strong safety culture improves safety performance, which impacts
financial and operational performance. In addition, research (Naji et al., 2022) and (Setiawan
& Astutik, 2022) also support that safety
culture has a positive impact on safety performance by reducing psychosocial
hazards and through effective training and supervision. However, the results of
this study emphasize the importance of considering contextual and organization-specific
factors that may influence the relationship between safety culture and employee
safety performance.
Safety
Culture and Safety Communication
Safety culture has a positive and significant
influence on safety communication (original sample value 0.579, t-statistic
5.864, and p-value 0.000). This is consistent with previous research which
shows that a strong safety culture can increase the effectiveness of safety
communication within the organization (Schulman, 2020). Research by (Naji et al., 2022) in the petrochemical industry
and (Mat Isa et al., 2021) in the context of
government-related companies show that effective safety communication mediates
the relationship between safety culture and safety performance. In the
construction field, (He et al., 2019) found
that two-way communication facilitated by a strong safety culture can reduce
work accidents. Therefore, the results of this study strengthen the evidence
that a good safety culture can create an environment where effective safety
communication can flourish, improving overall employee safety.
Safety
Communication and Employee Safety Performance
The test results show that safety communication has a
positive and significant effect on employee safety performance (original sample
value 0.329, t-statistic 4.023, and p-value 0.000). This is in line with the
findings of (Naji et al., 2022) in the
petrochemical industry and (Acheampong et al., 2024)
in the construction industry, which showed that effective safety communication
can improve employee safety behaviors and attitudes, leading to better safety
performance. However, (Sun et al., 2022) noted
that not all forms of safety communication have a positive impact; for example,
voice endorsement can have a negative effect on safety messaging. These
findings emphasize the importance of selecting and implementing appropriate
safety communication methods to improve employee safety performance.
Safety
Communication as a Mediator
This study shows that safety communication mediates
the relationship between safety culture and employee safety performance with an
original sample value of 0.191, t-statistic of 3.090, and p-value of 0.002.
This means that a strong safety culture improves safety communication, which in
turn improves employee safety performance. This result is consistent with
research (Zhang et al., 2022) in the mining
industry and (Mohd Nawi et al., 2023) in the
manufacturing industry, which showed that safety communication mediates the
relationship between safety culture and safety performance. These findings
confirm the importance of developing a strong safety culture to strengthen
safety communication, which will improve employee safety performance.
Service
Years as Moderator
Service Years has a significant moderating effect on
employee safety performance with an original sample value of 0.103, t-statistic
of 1.984, and p-value of 0.047. This suggests that longer tenure in the
organization is associated with better employee safety performance. Previous
research by (Ahmad et al., 2021) and (Opoku et al., 2019)� showed
that employees who have worked longer have a deeper understanding of safety
processes, which can improve their safety performance. However, the interaction
between Service Years and safety culture has no significant effect on employee
safety performance (original sample value -0.070, t-statistic 0.746, and
p-value 0.456). This finding suggests that tenure does not moderate the
relationship between safety culture and employee safety performance, indicating
that other factors may play a greater role in this relationship.
The results of this
study are largely consistent with the existing literature, but also show some
important differences. Although many previous studies have shown that safety
culture has a significant direct influence on safety performance (Bautista-Bernal
et al., 2024), the results of this study are largely consistent with the
existing literature. (Bautista-Bernal et al., 2024),
the results of this study do not support this hypothesis in the context of
CFPP. This may be due to specific contextual factors unique to this
organization, which requires further research.
In addition, the findings showing that safety
communication mediates the relationship between safety culture and employee
safety performance are consistent with previous studies (Zhang et al., 2022) (Mohd Nawi et al.,
2023). This confirms that improving safety communication through a
strong safety culture is an effective strategy to improve employee safety
performance. However, the results showing that service year does not moderate
the relationship between safety culture and employee safety performance are in
contrast to previous research which shows that experience and tenure contribute
to better safety performance. (Ahmad et al., 2021)(Opoku et al., 2019)This indicates that other
factors such as continuous training, reward system, and work environment may be
more influential in this context.
This study confirms the importance of safety
communication as a mediator in the relationship between safety culture and
employee safety performance in CFPP. Although safety culture does not have a
significant direct effect on employee safety performance, its influence on
safety communication shows that a strong safety culture remains an important
factor for improving employee safety. In addition, service year has a
significant moderating effect on safety performance, but does not moderate the
relationship between safety culture and safety performance. These results
emphasize the importance of a holistic approach that considers multiple factors
in an effort to improve workplace safety. Further research is needed to
identify specific contextual factors that may influence the relationship
between these variables across different organizations and industries.
REFERENCES
Abeje,
M., & Luo, F. (2023). The
Influence of Safety Culture and Climate on Safety Performance: Mediating Role
of Employee Engagement in Manufacturing Enterprises in Ethiopia.
Sustainability, 15(14), 11274. https://doi.org/10.3390/su151411274
Abiltarova, E. N. (2021). Safety Culture:
Historiography of Notion. IOP Conference Series: Materials Science and
Engineering, 1079(6), 062045. https://doi.org/10.1088/1757-899X/1079/6/062045
Acheampong, A., Adjei, E. K.,
Adade-Boateng, A., Acheamfour, V. K., Afful, A. E.,
& Boateng, E. (2024). Impact of construction workers informal safety
communication (CWISC) on safety performance on construction sites. Engineering,
Construction and Architectural Management. https://doi.org/10.1108/ECAM-09-2023-0906
Ahmad, A., Ambad,
S. N. A., Syed Mohd, S. J. A. N., & Lajuni, N.
(2021). The Moderation Effect of Job Tenure on Psychological Empowerment and
Employee Performance in Malaysia Public Sector. International Journal of
Academic Research in Business and Social Sciences, 11(4).
https://doi.org/10.6007/IJARBSS/v11-i4/9733
Ali, M.
X. M., Arifin, K., Abas, A., Ahmad, M. A., Khairil, M., Cyio, M. B., Samad, M.
A., Lampe, I., Mahfudz, M., & Ali, M. N. (2022). Systematic Literature Review on Indicators
Use in Safety Management Practices among Utility Industries. International
Journal of Environmental Research and Public Health, 19(10), 6198.
https://doi.org/10.3390/ijerph19106198
Almost, J., Caicco
Tett, L., VanDenKerkhof, E., Par�, G., Strahlendorf, P., Noonan, J., Hayes, T., Van hulle, H., Holden, J., Silva e Silva, V., & Rochon, A.
(2019). Leading Indicators in Occupational Health and Safety Management Systems
in Healthcare. Journal of Occupational & Environmental Medicine, 61(12),
e486-e496. https://doi.org/10.1097/JOM.0000000000001738
Asad, M., Kashif, M., Sheikh, U. A., Asif,
M. U., George, S., & Khan, G. ul H. (2022).
Synergetic effect of safety culture and safety climate on safety performance in
SMEs: does transformation leadership have a moderating role? International
Journal of Occupational Safety and Ergonomics, 28(3), 1858-1864.
https://doi.org/10.1080/10803548.2021.1942657
Bautista-Bernal,
I., Quintana-Garc�a, C., & Marchante-Lara, M. (2024). Safety culture, safety performance and
financial performance. A longitudinal study. Safety Science, 172, 106409.
https://doi.org/10.1016/j.ssci.2023.106409
Cepeda-Carrion, G., Cegarra-Navarro,
J.-G., & Cillo, V. (2019). Tips to use partial least squares structural
equation modeling (PLS-SEM) in knowledge management. Journal of Knowledge
Management, 23(1), 67-89.
Churruca, K., Ellis, L. A., Pomare, C., Hogden,
A., Bierbaum, M., Long, J. C., Olekalns, A., &
Braithwaite, J. (2021). Dimensions of safety culture: a systematic review of
quantitative, qualitative and mixed methods for assessing safety culture in
hospitals. BMJ Open, 11(7), e043982.
https://doi.org/10.1136/bmjopen-2020-043982
Cooper, M. D. (2000). Towards a model of
safety culture. Safety Science, 36(2), 111-136.
https://doi.org/10.1016/S0925-7535(00)00035-7
Doyle, D. (2023). The 2023 Liberty Mutual
Workplace Safety Index.
Filho,
A. P. G., Andrade, J. C. S., & Marinho, M. M. de O. (2010). A safety culture maturity model for
petrochemical companies in Brazil. Safety Science, 48(5), 615-624.
https://doi.org/10.1016/j.ssci.2010.01.012
Hair, J. F., Risher, J. J., Sarstedt, M.,
& Ringle, C. M. (2019). When to use and how to report the results of
PLS-SEM. European Business Review, 31(1), 2-24.
https://doi.org/10.1108/EBR-11-2018-0203
Hammond, D. M., King, A. L., Joe, M.,
& Miller, J. R. (2023). Understanding the relationship between safety
culture and safety performance indicators in U.S. nuclear waste cleanup
operations. Safety Science, 166, 106241. https://doi.org/10.1016/j.ssci.2023.106241
He, C., Jia, G., McCabe, B., Chen, Y.,
& Sun, J. (2019). Impact of psychological capital on construction worker
safety behavior: Communication competence as a mediator. Journal of Safety
Research, 71, 231-241. https://doi.org/10.1016/j.jsr.2019.09.007
Hudson, P. (2007). Implementing a safety
culture in a major multi-national. Safety Science, 45(6), 697-722.
https://doi.org/10.1016/j.ssci.2007.04.005
Ismail, S. N., Ramli, A., & Aziz, H.
A. (2021). Influencing factors on safety culture in mining industry: A
systematic literature review approach. Resources Policy, 74, 102250.
https://doi.org/10.1016/j.resourpol.2021.102250
Liu, S., Nkrumah, E. N. K., Akoto, L. S., Gyabeng, E., & Nkrumah, E. (2020). The State of
Occupational Health and Safety Management Frameworks (OHSMF) and Occupational
Injuries and Accidents in the Ghanaian Oil and Gas Industry: Assessing the
Mediating Role of Safety Knowledge. BioMed Research International, 2020, 1-14.
https://doi.org/10.1155/2020/6354895
Mat Isa, A. A., Wahab, W. A., Omar, R. C.,
Mohd Nordin, M. Z., Taha, H., & Roslan, R. (2021). Factors influencing the
compliance of workplace safety culture in the government linked company (GLC).
E3S Web of Conferences, 325, 06005. https://doi.org/10.1051/e3sconf/202132506005
Memon, M. A., Ting, H., Cheah, J.-H., Thurasamy, R., Chuah, F., & Cham, T. H. (2020). Sample
Size for Survey Research: Review and Recommendations. Journal of Applied
Structural Equation Modeling, 4(2), i-xx.
https://doi.org/10.47263/JASEM.4(2)01
Mohd Nawi, M. N., Zainol, N. A., Naim, F.,
Mamat, M. N., Hamzah, N. A., & Mohd Nawi, M. N. (2023). Employers'
Perceptions of the Manufacturing Industry on Workplace Safety Culture. Journal
of Energy and Safety Technology (JEST), 5(2), 78-86. https://doi.org/10.11113/jest.v5n2.123
Mrugalska, B., & Dovramadjiev,
T. (2023). A human factors perspective on safety culture. Human Systems
Management, 42(3), 299-304. https://doi.org/10.3233/HSM-220041
Naji, G. M. A., Isha, A. S. N., Alazzani, A., Saleem, M. S., & Alzoraiki,
M. (2022). Assessing the Mediating Role of Safety Communication Between Safety
Culture and Employees Safety Performance. Frontiers in Public Health, 10.
https://doi.org/10.3389/fpubh.2022.840281
Naji, G. M. A., Isha, A. S. N., Mohyaldinn, M. E., Leka, S., Saleem, M. S., Rahman, S. M.
N. B. S. A., & Alzoraiki, M. (2021). Impact of
Safety Culture on Safety Performance; Mediating Role of Psychosocial Hazard: An
Integrated Modeling Approach. International Journal of Environmental Research
and Public Health, 18(16), 8568. https://doi.org/10.3390/ijerph18168568
Ng, T. W. H., & Feldman, D. C. (2010).
Organizational Tenure and Job Performance. Journal of Management, 36(5),
1220-1250. https://doi.org/10.1177/0149206309359809
Nguyen, B. N., Le, H. N., & Nguyen, Q.
T. (2023). Safety communication in construction projects in Vietnam from
contractors' perspective. Science & Technology Development Journal -
Economics - Law and Management. https://doi.org/10.32508/stdjelm.v7i1.1150
Opoku, M. A., Choi, S. B., & Kang,
S.-W. (2019). Psychological Safety in Ghana: Empirical Analyses of Antecedents
and Consequences. International Journal of Environmental Research and Public
Health, 17(1), 214. https://doi.org/10.3390/ijerph17010214
Pahos, N., & Galanaki,
E. (2022). Performance Effects of High Performance
Work Systems on Committed, Long-Term Employees: A Multilevel Study. Frontiers
in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.825397
Peng, C., Xue, K., Tian, Y., Zhang, X.,
Jing, X., & Luo, H. (2022). Organizational Emotional Capability
Perspective: Research on the Impact of Psychological Capital on Enterprise
Safety Performance. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.854620
Ravi, D., Tawfik, D. S., Sexton, J. B.,
& Profit, J. (2021). Changing safety culture. Journal of Perinatology,
41(10), 2552-2560. https://doi.org/10.1038/s41372-020-00839-0
Reader, T. W. (2022). Stakeholder safety
communication: patient and family reports on safety risks in hospitals. Journal
of Risk Research, 25(7), 807-824. https://doi.org/10.1080/13669877.2022.2061036
Reason, J. (2016). Managing the Risks of
Organizational Accidents. Routledge. https://doi.org/10.4324/9781315543543
Schein, E. H. (2010). Organizational
culture and leadership (3rd Edition, Vol. 2). John Wiley & Sons.
Schulman, P. R. (2020). Organizational
structure and safety culture: Conceptual and practical challenges. Safety
Science, 126, 104669. https://doi.org/10.1016/j.ssci.2020.104669
Sekaran, U. & B. R. (2016). Research
Methods For Business: A Skill Building Approach (7th
ed.). John Wiley & Sons.
Setiawan, F., & Astutik,
M. (2022). The Effect of Training, Supervision and Occupational Safety and
Health (K3) Culture on Employee Performance. Indonesian Journal of Law and
Economics Review, 17. https://doi.org/10.21070/ijler.v17i0.821
Vinodkumar,
M. N., & Bhasi, M. (2010). Safety
management practices and safety behavior: Assessing the mediating role of
safety knowledge and motivation. Accident Analysis & Prevention, 42(6),
2082-2093. https://doi.org/10.1016/j.aap.2010.06.021
Westrum, R. (1993). Cultures with
Requisite Imagination. In Verification and Validation of Complex Systems: Human
Factors Issues (pp. 401-416). Springer Berlin Heidelberg.
https://doi.org/10.1007/978-3-662-02933-6_25
Wright, T. A., & Bonett, D. G. (2002).
The moderating effects of employee tenure on the relation between
organizational commitment and job performance: A meta-analysis. Journal of
Applied Psychology, 87(6), 1183-1190. https://doi.org/10.1037/0021-9010.87.6.1183
Xu, J., Cheung, C., Manu, P., & Ejohwomu, O. (2021). Safety leading indicators in
construction: A systematic review. Safety Science, 139, 105250.
https://doi.org/10.1016/j.ssci.2021.105250
Zakari Mustapha, Benjamin Boahene Akomah, & Benjamin Boahene Akomah.
(2023). Organizational culture and construction employee safety. Global Journal
of Engineering and Technology Advances, 16(2), 114-123.
https://doi.org/10.30574/gjeta.2023.16.2.0145
Zhang, S., Hua, X., Huang, G., & Shi,
X. (2022). How Does Leadership in Safety Management Affect Employees' Safety
Performance? A Case Study from Mining Enterprises in China. International
Journal of Environmental Research and Public Health, 19(10), 6187.
https://doi.org/10.3390/ijerph19106187