Occupational Health and Safety Management Systems.
Statement SD
D U A
SA
F % F % F % F % F %
Risk assessment
measures
143 44.5 95 29.6 15 4.7 40 12.5 28 8.7
Monitoring of the working
environment and its
impact on the
general environment
142 44.2 115 35.8 10 3.1 48 15.0 6 1.9
Regular medical check
ups
4 1.2 35 10.9 9 2.8 90 28.0 183 57.0
Record-keeping and
notification of injuries and
diseases
172 53.6 96 29.9 10 3.1 37 11.5 6 1.9
Preventive and
protective measures
148 46.1 119 37.1 12 3.7 38 11.8 4 1.2
Environmental
protection measures
192 59.8 94 29.3 35 10.9
Employers' and 35 10.9 29 9.0 99 30.8 158 49.2
workers participation
The results on occupational health and safety management systems in flower farms are presented
on Table. It shows that majority (143, 44.5%) employees strongly disagreed with the statement
that their organization had put in place risk assessment measures, (95,29.6%) employees
disagreed with the statement while (68,21.2%) employees were in disagreement with the
statement. The study finding showed that majority (80.0%) of the employees believed that their
organization had not put in place risk assessment measures to reduce on the likely of hazards
occurring in the farm. This implies that for improved safety of the employees, the flower farm
management need to consider the use of risk assessment as a hazard control tool.
According to Griffeth et al. (2000) pay and pay-related variables have a modest effect on
turnover. Their analysis also included studies that examined the relationship between pay, a
person’s performance and turnover. They concluded that when high performers are insufficiently
rewarded, they quit. If jobs provide adequate financial incentives the more likely employees
remain with organisation and vice versa. There are also other factors which make employees to
quit from organizations and these are poor hiring practices, managerial style, lack of recognition,
lack of competitive compensation system in the organization and toxic workplace environment.
Further, (142, 44.2%) employees strongly disagreed with the statement that there was monitoring
of the working environment and its impact on the general environment, (115,35.8%) employees
disagreed with the statement while (54,16.9%) employees were in agreement with the statement.
From the responses, it emerged that the flower farms were not doing environmental monitoring
to understand the health and safety issues affecting both the environment and the employees.
This implies that flower farms need to adhere to EMCA (1999) regulations on environmental
monitoring.
However, (183, 57.0%) employees strongly agreed with the statement that there were regular
medical checkups in the organization, (90, 28.0%) employees agreed with the statement while
(39, 12.1%) employees were in disagreement with the statement. The study showed that
regular medical checkups were conducted by the management of the flower farms and this
assisted in understanding the health needs of the employees and preventing their exit from the
organization.
Data analysis shows that (Natural Resource Institute, 2006) study supports that approximately
96% of the workers reported that their employer provided medical care for them. However, only
in about two thirds of the cases did this medical care include family members. Some workers did
not know whether medical care was extended to their families or not, because nobody had
informed them about it. The type of care provided included out-patient (57%); in- and out-patient
(15%); out-patient and first aid (14%); in- patient (9%); and a combination of in- and out-patient,
plus first aid.
Most of the outpatient treatment was received from the company facility. However, in some
cases, the employers paid for medical services in public health facilities because the company
did not have a health facility. A small number of workers reported that they received medical
care from private or mission facilities. Over 90% of the workers reported that they were
contributing towards the National Hospital Insurance Fund (NHIF) which caters for part of the
in-patient cost for health care. A few were not contributing, either because they had spouses who
contributed or they were casual employeeers. A small number of workers did not know whether
they contributed or not. this contradicts this study findings which shows that farm owners
provided medical check-ups for the employees in flower farms.
Further (192, 59.8%) employees strongly disagreed with the statement that the organization had
put in place environmental protection measures, (94, 29.3%) employees disagreed with the
statement while (35, 10.9%) employees were in agreement with the statement. Majority
(89.1%) employees believed that there were no environmental protection measures put in place
by the management of flower farms in North Rift Region and this contravenes the EMCA Act
(1999).
According to Muinde (2012), Health and safety practices include workplace health and safety,
occupational health programs, health and safety training, health and safety management, and
health and safety inspection. By implementing proper health and safety standard in the
workplace improves the performance of the organization through employees by avoiding and
reducing costs related disabilities, accidents, absenteeism and illness (Bratton & Gold, 2000).
This result more employee retention. Similarly occupational health programs allows
organizations to minimize the stress level of employees with higher productivity, less absence to
work improve staff determination (Armstrong, 2006) causing to reduce employee turnover.
Health and safety training among employees provided special courses to deal with the health and
safety areas to be careful and have safety problems. This builds the confidence and commitment
of the employee towards and organization (Armstrong, 2006) resulting further improvement in
employee retention. Also safety and health management helps the organization to reduce costs,
reduce risk in for employees at the workplace increasing their productivity because this practice
motivates employees and keeps them in good health (Health and Safety Executive, 1997) thereby
reducing employee turnover. Health and safety inspection prevents injury illness and property
dame in the workplace and builds a positive health and safety culture, which enhances employee
productivity, commitment and performance (Armstrong, 2010) causing to reduce employee
turnover.
From observation, most of the employees in flower farms did not have the right gear but other
has them and do not put them own. What was majority was missing are the boots that protect
them from thorny plants which could pick their feet gloves they had gloves but did not put them
own. Some had the masks but put them aside. It was observed the protection of natural
environment, cover use of fertilizers, water management, soil conservation, disposal of
hazardous waste and the protection of wildlife and water sources agrochemicals that is pesticides
and fertilizer were the major hazards exposed to the employees.
Employees working in the chemical stores had no masks that prevented them from inhaling the
chemical these exposed them to respiratory related problems. When the researcher visited green
houses it was realized that there was still some smell of chemicals this could suggest that the
time for entering these green houses after spraying was not observed. Most employees were
missing gloves when handling flowers yet they have them. This showed that employees
neglected the health and safety rules that they mat dress appropriately.
H04 There is no significant statistical relationship between health and safety practices and
employee turnover in flower farms which have human resource practices in place. The
hypothesis was tested using Pearson correlation analysis and the results are presented in Table
Table 4.30 Health and Safety Practices and Employee Turnover
Safety and Health
Practices
Employee Turnover
Attrition
Resignation Dismissal
Occupational safety and
health issues
r = -.820** r= -.185**
r = .023
p =.000 p=.001 p = .003
Accidents
r= -.895** r =.239** r=- -.529**
p =.000 p =.000 p =.000
Safety management
systems
r= -.770** r = -.406** r=.128*
p =.000 p =.000 p =.022
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
The findings on Table shows that safety and health issues had significant and negative
correlation at 0.05 significance level with all the indices of employee turnover (attrition,
resignation and Dismissal). The findings further showed that accidents had a negative
relationship with attrition and dismissal and a positive relationship with resignation. Finally
safety management systems had a negative correlation with all the indices of employee turnover
at a significance level of 0.01. This implies that there was a statistical significance but negative
relationship between health and safety practices and employee turnover in flower farms in North
Rift region.
To establish the relationship between Health and Safety practices and Employee turnover in
flower farm.
Table Model Fitting Information
Model Fitting Information
Model -2 Log Likelihood Chi-Square Df Sig.
Intercept Only 1023.595
Final 885.406 138.189 25 .000
The overall test of the model is shown in Table When there is a scale parameter, the null
hypothesis is that both the location parameters and the scale parameters are 0. Based on observed
significance level, the null hypothesis is rejected. According to DeCarlo (2003) proceeding to
examine the individual coefficients, check an overall test of the null hypothesis that the location
coefficients for all of the variables in the model are 0. It can be based on the change in 2log-
likelihood when the variables are added to a model that contains only the intercept. The change
in likelihood function has a chi-square distribution even when there are cells with small observed
and predicted counts. From Table 4.30, the results show the difference between the 2log-
likelihoods and the chi square has an observed significance level of less than 0.05. At α=0.05
chi-square statistic (p<.000) is significant which indicates that the model gives better predictions
based on the marginal probabilities for the outcome categories
Table Goodness-of-Fit
Results as shown in Table 4.32 implies that we accept the assumption of a good fit, p<.05, the
results for this analysis suggest the model does not fit well (p<.000) since the p value is small
the study conclude that the data and the model predictions are not similar. The Pearson
goodness-of-fit statistic is the deviation measure of the goodness-of-fit statistics and should be
used only for models that have reasonably large expected values in each cell. A continuous
independent variable or many categorical predictors or some predictors with many values, could
have many cells with small expected values. If the model fits well, the observed and expected
cell counts are similar, the value of each statistic is small, and the observed significance level is
large. The null hypothesis is rejected if the observed significance level for the goodness of-fit
statistics is small.
Table Pseudo R-Square
Pseudo R-Square
Cox and Snell .350
Goodness-of-Fit
Chi-Square df Sig.
Pearson 1045.390 600 .000
Deviance 685.765 600 .009
Nagelkerke .352
McFadden .083
In linear regression, R2 the coefficient of determination summarizes the proportion of variance in
the outcome that can be accounted for by the explanatory variables, with larger R2 values
indicating that more of the variation in the outcome can be explained up to a maximum of 1.
What constitutes a good R2 value depends upon the nature of the outcome and the explanatory
variables. Here, the pseudo R2 values Nagelkerke = 35.2%) indicates that health and safety
explains a low proportion of the variation between employee turnover. The low R2 indicates that
a model containing only health and safety is likely to be a poor predictor of employee turnover.
Note though that this does not negate the fact that there is a statistically significance.
Table Test of Parallel Lines
Test of Parallel Linesa
Model -2 Log Likelihood Chi-Square df Sig.
Null Hypothesis 885.406
General .000b885.406 600 .000
The null hypothesis states that the location parameters (slope coefficients) are the same across
response categories.
This test compares the ordinal model which has one set of coefficients for all thresholds labeled
Null Hypothesis, to a model with a separate set of coefficients for each threshold labeled
General. If the general model gives a significantly better fit to the data than the ordinal model if
p<.05 then we are led to reject the assumption of ordinal model. If the lines or planes are parallel,
the observed significance level for the change should be large as shown in the results, since the
general model does not improve the fit. The parallel model is adequate. The null hypothesis
may not be rejected since the lines are parallel.
From Table the assumption is reasonable for this problem. If the null hypothesis is not rejected,
it is possible that the link function selected is incorrect for the data or that the relationships
between the independent variables and logits.
General test for the four objectives and turnover
This study further sought to find out the relationship between the dependent variables and the
dependent variable.
Table Model Fitting Information
Model Fitting Information
The Model fitting Information table gives the 2 log-likelihood values for the baseline and the
final model. The significant chi-square statistic p<.000 indicates that the final model gives a
Model Fitting Information
Model -2 Log Likelihood Chi-Square df Sig.
Intercept Only 1670.878
Final 1266.311 404.566 133 .000
significant improvement over the baseline intercept-only model. This implies that the model
gives better predictions based on the marginal probabilities for the outcome categories. At
α=0.05 chi- square statistic p<.000 is significant which indicates that the Final model gives a
significant improvement over the baseline intercept-only model. This implies that the model
gives better predictions based on the marginal probabilities for the outcome categories.
Tabl
e
Goodness-of-Fit
Results as shown in Table 4.36 implies that we accept the assumption of a good fit, p<.05, the
results for this analysis suggest the model fits very well (p<.397) since the p value is small the
study conclude that the data and the model predictions are not similar. A continuous independent
variable or many categorical predictors or some predictors with many values, could have many
cells with small expected values. If the model fits well, the observed and expected cell counts are
similar, the value of each statistic is small, and the observed significance level is large. The null
hypothesis is rejected if the observed significance level for the goodness of-fit statistics is small.
Table Pseudo R-Square
Goodness-of-Fit
Chi-Square df Sig.
Pearson 7874.195 7842 .397
Deviance 1266.311 7842 1.000
Pseudo R-Square
Cox and Snell .716
Nagelkerke .720
McFadden .242
In linear regression, R2 the coefficient of determination summarizes the proportion of variance in
the outcome that can be accounted for by the explanatory variables, with larger R2 values
indicating that more of the variation in the outcome can be explained up to a maximum of 1. The
pseudo R2 values (Nagelkerke = 72%) implies that there is significant relationship between the
independent variables (Employee turnover, Management Styles, Intrinsic and Extrinsic rewards,
Work Life balance and Health and Safety practices) and the dependent (eployee turnover). The
independent variables explain the 72% of employee turnover in flower farms in the areas as
shown in Table.
This shows that there is need to improve on human resource management practices for reduced
turnover as past researchers concur with above view. They argue that if human resource
management practices are not implemented properly in an organization there are several negative
impacts. An organization with proper human resource management practices enjoys the firm’s
sustainable growth that will maximize the economic opportunities in order to meet the
organizational goals (Tanveer, et al., 2011). Similarly more significantly related to this research
will retain employees and improve their performance (Singh & Jain, 2014).
Table Test of Parallel Linesa
The
null
hypothesis states that the location parameters (slope coefficients) are the same across response
categories.
A large number of empirical studies verify a positive relationship between human resource
management practices on organizational performance mainly in relation to employee retention
(Tangthong, 2014). This studies have shown the results that are in line with this of the current
study, the general model gives a significantly better fit to the data than the ordinal (proportional
odds) model (that is p<.05) then we reject the assumption of proportional odds. This is the not
the conclusion that the study would draw for our example (Table 4.38), given the insignificant
value as shown below (p<1.0).
Muinde (2012), the objective of this study was to investigate the extent to which work life
balance practices are adopted by horticultural farms in Naivasha. The results of the study
indicate that horticultural farms in Naivasha have adopted practices relating to time and to the
job to a great extent while practices relating to the place and to the benefits have been adapted to
a moderate extent only. The study recommends that greater attention should be paid to practices
relating to the job as well as benefits as they are the ones with the lower ratings than practices
relating to time and place. In particular, the farms should introduce employee assistance
programs and study leave in order to empower the employees to make better use of the other
practices they have been provided. Further, the farms should consider introducing flexible
Test of Parallel Linesa
Model -2 Log Likelihood Chi-Square df Sig.
Null Hypothesis 1266.311
General .000b1266.311 3192 1.000
working hours and increased work autonomy so that the employee can schedule their work in a
manner that allows them to attend to non work matters during off peak working hours/seasons.
This could result to reduced turnover of employees in flower farms.
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