Volume 3, No. 9
September 2024 (1971-1981)
p-ISSN 2980-4868 |
e-ISSN 2980-4841
https://ajesh.ph/index.php/gp
The Influence of
Safety Leadership and Safety Climate on Safety Behavior is Mediated by Safety
Motivation in Sugar Factory Employees
Mochammad Iqbal Velayati Fajrin
Politeknik
Perkapalan Negri Surabaya, Indonesia
Email: iqbalavel97@gmail.com
ABSTRACT
The sugar industry has complex production
processes and involves various risks, including the high potential for employee
accidents. To reduce this risk, the implementation of an effective work safety
programme is required. This reserach aims to analyse the effect of safety
leadership and safety climate on safety behaviour mediated by safety motivation
in sugar factory employees. The method used is quantitative with data
collection through questionnaires. The population of this study were all sugar
factory employees in Indonesia, with a sample of 100 respondents selected using
random sampling technique. Data analysis was carried out using Path Analysis in
the SEM-PLS programme. The results showed that Safety Leadership and Safety
Climate positively influence the Safety Behaviour of sugar factory employees.
In addition, Safety Motivation mediates the influence of Safety Leadership and
Safety Climate on Safety Behaviour, which indicates that Safety Motivation can
strengthen the influence of these two factors on the safety behaviour of sugar
factory employees. This reserach provides important implications for sugar
factory management to pay more attention to aspects of motivation and safety
climate to improve safety behaviour in the workplace.
Keywords: Safety
Leadership , Safety Climate , Safety Behavior , Safety Motivation
INTRODUCTION
In an industry, employees are
considered a very valuable asset because they are responsible for the
implementation of the production process, which is the main activity for the
company. Without a smoothly running production process, the company will not be
able to achieve its operational goals and will experience a decline in
performance (Riniwati,
2016). Employees act as the main driving
force that ensures organizational goals can be achieved, and the success or
failure of an organization depends heavily on employee contributions and
performance (Indahsari
& Damayanti, 2020). Thus, human resource management is
crucial in ensuring that the factors influencing employee performance are
properly managed, enabling the production process to operate effectively and
efficiently. According to (Astuti
& Zaenab, 2020), one of the key factors affecting
employee productivity is the work environment and occupational safety and
health insurance. If employees feel safe and work in a conducive environment,
employees will be more productive (Azizah
& Faras, 2024). So employee safety must be a top
priority for the industry because work accidents can not only endanger
employees, but can also reduce work productivity.
Meanwhile, the sugar industry has a
complicated and dangerous production process, so employees involved in sugar
factory production face a high risk of occupational accidents. Employees in the
production and installation departments of sugar factories often work directly
with mechanized machinery. Each stage in the production process is assisted by
modern equipment, which although increases efficiency, also brings risks to
workers' safety and health (Astuti
& Zaenab, 2020). To minimize these risks, sugar
factories require the implementation of an effective work safety program. One
important element of a safety program is creating a strong safety culture among
employees, which can trigger safety behaviors. Safety behavior refers to
actions that employees take to protect themselves and others from hazards in
the workplace. Safety behavior will help employees avoid the risk of accidents
and create a sense of security at work, thereby increasing productivity (Rahman
et al., 2023).
To achieve employees who understand
safety behaviors, various factors can influence, including safety leadership,
safety climate, and safety motivation. A leader is an individual who is able to
influence the behavior of others to achieve a specific goal. Safety leadership
refers to leader behaviors that encourage and support employee safety behaviors
(Ningtias
et al., 2020). Leaders who are effective in
workplace safety will demonstrate a commitment to safety, set a good example in
following safety procedures, and be actively involved in workplace safety
activities. In addition, the safety climate can influence workers' behavior and
engagement in safety practices. Safety climate refers to employees' perceptions
of the priority of safety in the workplace. Zohar (1980) in (Ningtias
et al., 2020) defines safety climate as employee
perceptions of policies, procedures, practices, and overall safety interests
and priorities. A positive safety climate is characterized by the perception
that workplace safety is valued and prioritized by management and co-workers,
which then influences individual safety behavior.
Furthermore, effective safety
leadership and a positive safety climate can encourage safety motivation among
employees. Safety motivation is the
drive that makes employees want to behave safely at work. A good work environment
acts as a motivation for employees, making employees feel comfortable and
excited at work, which in turn improves their performance. An unhealthy work
environment can be an additional burden for employees, reducing productivity.
In contrast, a clean and hygienic environment not only reduces the additional
burden but also increases work enthusiasm and motivation, which is reflected in
better safety behavior (Ningtias
et al., 2020). Therefore, understanding factors
such as safety leadership, safety climate, and safety motivation and their
interactions can help companies design effective safety programs.
Previous research by (Rahman
et al., 2023) demonstrated a significant
relationship between safety leadership and safety climate on safety behavior.
The study revealed that safety leadership has a path effect of 0.550 on safety
behavior, while safety climate has a path effect of 0.447. Additionally, a
study by (Heryati
et al., 2019) found that safety climate impacts
safety behavior both directly and indirectly. The direct effect shows that
safety climate directly influences employee safety behavior, and part of this
influence is mediated by safety motivation.
This research introduces a novel focus
on the sugar industry, examining variables such as safety leadership, safety
climate, and safety motivation in relation to employee safety behavior, which
have not been previously studied. The objective of this study is to analyze how
safety leadership and safety climate impact employee safety behavior, with
safety motivation acting as a mediator. Through understanding this
relationship, it is hoped that sugar companies can implement more effective
strategies to improve safety and create a positive safety culture throughout
their production.
RESEARCH
METHODS
The method in the study uses
quantitative methods, which is a scientific method that emphasizes data
collection in the form of numbers or numerical data to be tested, analyzed, and
presented statistically. This approach aims to measure phenomena, relationships,
or certain variables objectively and measurably. Quantitative methods utilize
statistical techniques to analyze data and produce findings that can be
scientifically accounted for (Priadana
& Sunarsi, 2021). The data collection technique used
in the study was through a questionnaire. The study population included all
sugar factory employees in Indonesia, with a sample of 100 respondents selected
using random sampling techniques. Sample criteria include permanent employees
of sugar factories who work in production and have at least one year of work
experience in sugar factories. The collected data were analyzed using Path
Analysis with the SEM-PLS program. This method was chosen to test the complex
relationship between the variables studied.
RESULTS AND
DISCUSSION
Measurement Model
(Outer Model)
The Outer Model or Outer Measurement
is also known as the measurement model. The outer model test aims to determine
the relationship between latent variables and their indicators. This outer
model test was carried out using the PLS Algorithm procedure. The stages of
analysis on the outer model are measured by validity and reliability testing (Sholihin
& Ratmono, 2021).
Table 1. Outer Loading
|
|
Safety
Motivation |
Safety Behavior |
Safety Climate |
Safety
Leadership |
|
SL1 |
0.726 |
|
|
|
|
SL2 |
0.789 |
|
|
|
|
SL3 |
0.816 |
|
|
|
|
SL4 |
0.819 |
|
|
|
|
SL5 |
0.794 |
|
|
|
|
SL6 |
0.718 |
|
|
|
|
SC1 |
|
0.842 |
|
|
|
SC2 |
|
0.895 |
|
|
|
SC3 |
|
0.785 |
|
|
|
SC4 |
|
0.784 |
|
|
|
SC5 |
|
0.791 |
|
|
|
SC6 |
|
0.747 |
|
|
|
SB1 |
|
|
0.826 |
|
|
SB2 |
|
|
0.801 |
|
|
SB3 |
|
|
0.752 |
|
|
SB4 |
|
|
0.787 |
|
|
SM1 |
|
|
|
0.910 |
|
SM2 |
|
|
|
0.837 |
|
SM3 |
|
|
|
0.732 |
|
SM4 |
|
|
|
0.761 |
From table 1 above, it can be seen
that all indicators that make up each variable have met the requirements of
convergent validity. This can be seen from the loading factor value which is
greater than 0.70 for each indicator. Convergent validity indicates that the
indicators consistently measure the variable in question, with a high loading
factor value indicating a strong relationship between the indicator and the
latent variable being measured.
Table 2. Average Variances Extracted
|
Safety
Motivation |
0.622 |
|
Safety Climate |
0.524 |
|
Safety
Leadership |
0.520 |
|
Safety Behavior |
0.702 |
From table 2, it is known that all
indicators that make up each variable have met the discriminant validity
requirements. This is evidenced by the square root value of the average
variance extracted (AVE) which is greater than 0.50. This shows that each
indicator is able to explain more than half of the variability, thus ensuring
that the indicators are valid in measuring the intended construction. Good discriminant
validity ensures that the latent variables being measured differ from each
other sufficiently.
Table 3. Discriminant Validity
|
|
Safety Motivation |
Safety Behavior |
Safety Climate |
Safety Leadership |
|
0.662 |
|
|
|
|
|
Safety Behavior |
0.530 |
0.792 |
|
|
|
Safety Climate |
0.514 |
0.566 |
0.612 |
|
|
Safety Leadership |
0.484 |
0.558 |
0.558 |
0.646 |
Based on table 3 above, it can be seen
that all indicators that make up each variable in this study have met
discriminant validity, because the cross loading value shows that the
correlation value between the construct and its indicator is greater than the
correlation value between the construct and other indicators.
Table 4. Composite Reliability
|
|
Cronbach’s Alpha |
Composite Reliability |
|
Safety Motivation |
0.621 |
0.711 |
|
Safety Climate |
0.764 |
0.771 |
|
Safety Leadership |
0.730 |
0.807 |
|
Safety Behavior |
0.802 |
0.871 |
The data in the table above shows that
all variables are declared reliable because the composite reliability value is
greater than 0.70 and the Cronbach's alpha value is greater than 0.60.
Structural Model
(Inner Model)
Inner model evaluation is carried out
to assess the influence between latent variables and is used to test
hypotheses. The influence between latent variables can be seen from the
R-square value. The greater the R-square value, the greater the influence of
exogenous latent variables on endogenous latent variables and the significance
of the structural path parameter coefficient (Jamu,
2018).
Based on data processing with SEM-PLS
3.0 Professional, the following R-square values are generated:
|
|
R Square |
R Square Adjusted |
|
Safety Behavior |
0.454 |
0.437 |
From the table above, it is known that
safety factors that affect safety behavior; safety leadership, safety climate,
safety motivation have a significant influence on the safety behavior of sugar
factory employees with an R-square value of 0.454 or 45.4%.
Hypothesis
Testing
Hypothesis testing is a process or
step in research in which proposed hypotheses are tested to see if the data
obtained support or reject the hypothesis. Hypothesis testing is evaluated
using the t-statistic and p value.
Table 6. Path Coefficients
|
|
Original Sample (O) |
Sample Mean (M) |
Standard Deviation (STDEV) |
T Statistics (|O/STDEV|) |
P Values |
|
Safety Climate
-> Safety Behavior |
0,275 |
0,297 |
0,099 |
2,780 |
0,005 |
|
Safety
Leadership -> Safety Behavior |
0,295 |
0,292 |
0,083 |
3,531 |
0,000 |
The Path
Coefficients test will serve as a reference for conducting hypothesis testing
in this study, with the established criterion that the hypothesis is accepted
if the P value is less than 0.05, and rejected if the P value is greater than
0.05. The test results for the hypotheses proposed in this study are as
follows:
1.
H1: Safety Leadership positively impacts Safety
Behavior among Sugar Factory Employees, with a t-statistic of 2.780 and a P
value of 0.000, indicating P < 0.05, thus the hypothesis is accepted.
2.
H2: Safety Climate positively impacts Safety
Behavior among Sugar Factory Employees, with a t-statistic of 3.531 and a P
value of 0.005, indicating P < 0.05, thus the hypothesis is accepted.
Mediation
Evaluation
Mediation analysis involves testing
the direct effect between the dependent variable and the mediating variable, as
well as the indirect effect between the independent variable and the dependent
variable through the mediating variable.
Table 7. Mediation Test
|
|
Original Sample (O) |
Sample Mean (M) |
Standard Deviation (STDEV) |
T Statistics (|O/STDEV|) |
P Values |
|
Safety Motivation -> Safety Leadership -> Safety Behavior |
0,246 |
0,237 |
0,111 |
2,227 |
0,026 |
|
Safety Motivation -> Safety Climate -> Safety Behavior |
0,354 |
0,370 |
0,116 |
3,044 |
0,002 |
According to Baron and Kenny, testing
for a mediation effect involves three stages. The first stage tests the impact
of the independent variable on the dependent variable, which must be
significant with a t-statistic greater than 1.96. The second stage examines the
effect of the independent variable on the mediating variable, which must also
be significant with a t-statistic greater than 1.96. The third stage evaluates
the impact of the mediating variable on the dependent variable, which must
again be significant with a t-statistic greater than 1.96 (Rapali
& Soelaiman, 2019). The mediation test results for the
hypotheses proposed in this study are as follows:
1. Based on the results of testing the
construct variable safety leadership on safety behavior through safety
motivation as a mediating variable which has a t-statistic value of 2.227 and a
p-value of 0.026, H3 is accepted because the t-statistic is greater than 1.96
and the p-value is smaller than 0.05.
2. Based on the results of testing the
construct variable safety climate on safety behavior through safety motivation
as a mediating variable which has a t-statistic value of 3.044 and a p-value of
0.002, H4 is accepted because the t-statistic is greater than 1.96 and the
p-value is smaller than 0.05.
Discussion
Safety Leadership
has a positive effect on Safety Behavior in Sugar Factory Employees
The hypothesis testing results
indicate that Safety Leadership positively affects Safety Behavior among Sugar Factory
Employees, thus the hypothesis is accepted. This signifies that leadership
practices emphasizing workplace safety significantly enhance employees' safety
behavior. It underscores the critical role and implementation of effective,
supportive safety policies by leadership in fostering a strong safety culture
within the sugar factory environment.
These findings align with previous
research by (Stiawan
& Faidal, 2024), which demonstrated that Safety
Knowledge, Safety Leadership, and Safety Citizenship Behavior significantly
positively impact Safety Behavior at Lombang Sumene Beach. Another study by (Afifah,
2021) also found that effective safety
leadership positively influences safety behavior, indicating that
well-implemented safety leadership practices lead to improved safety behavior
and a more comfortable work environment for employees. Similarly, research by (Rahman
et al., 2023) identified significant relationships
between safety behavior and work accident variables (path value of 0.889),
safety leadership and safety behavior variables (path value of 0.550), and
safety leadership and work accident variables (path value of 0.530).
Safety Climate
has a positive effect on Safety Behavior in Sugar Factory Employees
The results of hypothesis testing show
that Safety Climate has a positive effect on Safety Behavior in Sugar Factory
Employees which means the hypothesis is accepted. This means that employees'
perceptions of safety conditions in their work environment significantly affect
the safety behavior they show. The better the safety climate perceived by
employees, the higher the likelihood of them adopting the desired safety
behaviors in carrying out their daily tasks in the sugar factory. This shows
the importance of creating and maintaining a safe and supportive work
environment for employees so that they can actively participate in workplace
safety efforts.
The results of this study align with
previous research by (Abdillah
& Rumita, 2015), which found that various elements of
the safety climate—such as Communication & Support, Adequacy of Procedures,
Work Pressure, Personal Protective Equipment, Relationships, and Safety
Rules—have a significant collective impact on safety behavior. Additionally, (Sadili
& Faidal, 2024) showed that Safety Awareness, Safety
Climate, and Safety Citizenship Behavior significantly influence Safety
Behavior. This was evidenced by the t-test results in Equation II, which
reported a t-value of 1.473 and a significance level of 0.145 (greater than
0.05) with a regression coefficient of 0.142.
Similarly, research by (Setiawan
et al., 2017) found that the safety climate among
construction workers, across all seven dimensions, is negatively perceived and
associated with poor safety behavior. In the El-Centro Apartment project, the
safety climate was categorized as very low, with scores ranging from 1.30 to
1.59. The P values for the seven dimensions ranged from 0.017 to 0.047,
indicating a significant relationship between the safety climate and safety
behavior. Additionally, the odds ratios (OR) of 1.908 to 2.500 suggest that
workers with a negative perception of workplace safety are 1.908 to 2.500 times
more likely to exhibit unsafe behavior.
Safety Motivation
mediates the effect of Safety Leadership on Safety Behavior in Sugar Factory
Employees
Based on the results of testing the
construct variable safety leadership on safety behavior through safety
motivation as a mediating variable which has a t-statistic value of 2.227 and a
p-value of 0.026, H3 is accepted because the t-statistic is greater than 1.96
and the p-value is less than 0.05. This means that the presence and positive
influence of safety leadership on employees' safety behavior can be partially
explained through the increase in their perceived safety motivation. When
employees perceive leadership that supports and prioritizes safety in the
workplace (Safety Leadership), this increases their motivation to comply with
safety procedures and perform expected safety behaviors. This safety motivation
then positively influences how often employees demonstrate safety behaviors in
their daily activities at the sugar mill.
Safety Motivation
mediates the effect of Safety Climate on Safety Behavior in Sugar Factory
Employees
Based on the results of testing the
construct variable safety climate on safety behavior through safety motivation
as a mediating variable which has a t-statistic value of 3.044 and a p-value of
0.002, H4 is accepted because the t-statistic is greater than 1.96 and the
p-value is smaller than 0.05. That is, the safety climate perceived by
employees influences their safety behavior through increased safety motivation.
More specifically, this finding suggests that when employees perceive a good
safety climate in their work environment, such as management support for
safety, strong safety norms, and rewards for safety behavior, this increases
their motivation to follow safety procedures and behave safely (Setiono
& Andjarwati, 2019). This safety motivation then
contributes positively to employees' safety behavior in carrying out their
daily tasks in the sugar factory.
CONCLUSION
The results of hypothesis testing show
that safety leadership and safety climate have a positive influence on the
safety behavior of sugar factory employees. In addition, safety motivation
mediates the effect of safety leadership and safety climate on safety behavior,
which indicates that safety motivation can strengthen the influence of these
factors on the safety behavior of sugar factory employees. When management
demonstrates a strong commitment to safety and creates an environment that
supports safety, employees are likely to behave more safely. Safety motivation
plays an important role in strengthening the influence of leadership and safety
climate on safety behavior. When employees are highly motivated to work safely,
they tend to respond positively to good leadership and safety climate, which in
turn improves employee safety behavior. This research highlights the importance
of management's role in establishing a safe work environment and in motivating
employees to comply with safety practices. This is not only important for
individual safety but also for the sustainability of company operations.
However, the study has limitations as the sample used only includes employees
from sugar factories, so the results may not be generalizable to other industries.
Therefore, further research is needed to examine the factors that influence
safety behavior in the workplace.
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|
Copyright holder: Mochammad Iqbal Velayati
Fajrin (2024) |
|
First publication right: Asian Journal of Engineering, Social and Health (AJESH) |
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