METHODOLOGY
3.1 Introduction
This chapter is an account of the methods and procedures adopted in
this research work on the effect of industrial accident on employee’s morale in
Guinness Nigerian Breweries PLC Ikeja Lagos. Specifically, this chapter
explains the rationale for the design adopted, the population and sample of the
study, source of as well as the instruments and techniques for data collection
and analysis.
3.2 Design Method
In the research design the
descriptive method of analysis is adopted. This entails the description of
phenomenon and characteristics associated with the subject population,. In the
words of Eboh (1998) descriptive studies can be carried out on small and large
scale, they involve a systematic collection and presentation of data with hope
that good picture of a particular situational will emerge.
3.3 Area of the study
The
study covers only Guinness Nigerian Breweries PLC, Ikeja Lagos
3.4
Population characteristics
The population size for the study
comprised of both management staff and employees (skill and unskilled) of
Guinness Nigerian Breweries PLC, Ikeja, Lagos.
This is because almost everybody is
prone to accident in an industrial setting. Because of the nature of work in
the company it was difficult to get accurate number of employees working in the
organization. Here, the population was estimated to be 600.
3.5 Sample size
The sample size was determined using the Yaro
Yamene formular, this is because the sample size cannot be guessed
n = N (e)2
1 + N
When
n = sample size
N = population size
e = level of significance
I = constant
Subsisting
for the above formula, we have
600 (0.05)2
1
+ 600
=
600
1
+ 600 (0.0025)
=
600
1 + 1.5
= 350
2.5
11 = 240
3.6 Research Instrumentation
A self-completion questionnaire was
used for the purpose of obtaining data from the respondents. The questionnaire
was grouped into two. The first one bordered on the issue of demographic
characteristics of the company such as Age, sex and academic qualifications
while the second one concentrated on obtaining data pertaining to the issue of
accident and moral.
3.7 Validity and Reliability of Research
instruments.
The questionnaire was subjected to
initial tests for validity and consistency before it was finally adopted.
According to Ukwuije (2003) validity is the extent which an instrument measures
what it is expected to measure, while reliability measures on the other hand
test the consistency of the instrument.
The questionnaire which was
constructed to achieve the above aims was tested by the expert in this field
before going out to the respondents.
3.8 Sources of Data
Data for this research were both
qualitative and quantitative, while qualitative data were obtained form
interviews and comments of key informants” quantitative data were got from
studies whose findings are mainly products of statistical surveys, summaries
and analysis.
Both the qualitative and
quantitative data for the study were obtained form two sources, ie primary and
secondary sources. Primary sources provides data in their raw and unused forms,
with the questionnaire and interview serving as the major instruments and
technique of data collection.
Secondary sources of data for this
study were textbooks handbooks, journals, magazines, dictionaries and internet
websites that were considered reliant to the study.
3.9 Analytical methods and techniques
Here, the
descriptive mode of analysis is made use of. Responses of the respondents are
presented in matrix tables with a calculation of their corresponding
Frequencies
Percentages
Mean
. 10
Decision Rule
Adopting the chi-square formula as
developed by Kal Pearson, Pertorious, (1995). The decision rule for the testing
of hypothesis is
Reject
Ho, if calculated X2 >critical value
Accept
Ho, if calculated X2 >critical value.
Reject
Hi, if calculated X2 < critical value.
Accept
Hi if calculated X2 < critical value.
CHAPTER FOUR
DATA PRESENTATION AND ANALYSIS
4.1 INTRODUCTION
Relevant data collected for this
study were recorded, edited and coded, and were presented as follows;
A = Agreed
SA = Strongly Agreed
D = Disagreed
SD = Strongly Disagreed
TPR = Total positive Response
TNR = Total negative Response
TR = Total Response
%TPR = Percentage
of total positive response
%TNR = Percentage
of total negative response
Table
4.1
Distribution
Distribution as to the effect of industrial accident on employee’s morale
Distribution as to the effect of industrial accident on employee’s morale
|
|
A
|
SA
|
D
|
SD
|
TPR
|
TNR
|
TR
|
%TPR
|
%TNR
|
|
Question
11
|
37
|
65
|
41
|
29
|
102
|
70
|
172
|
42
|
29
|
|
Question
9
|
42
|
69
|
53
|
34
|
111
|
87
|
198
|
46
|
36
|
|
Question
11
|
38
|
51
|
37
|
42
|
89
|
79
|
168
|
37
|
33
|
|
Total
|
117
|
185
|
131
|
105
|
302
|
236
|
538
|
125
|
98
|
Source: Fieldwork
Table 4.1 above
shows that total of 302 respondents or 125% agreed that industrial accident has
effect on employee’s morale whereas total of 236 respondents or 98% from
various questionnaires disagreed that industrial accident has effect on
employee’s morale.
Table
4.2
Distributions
as to the extent of which training reduces industrial accident rate.
|
|
A
|
SA
|
D
|
SD
|
TPR
|
TNR
|
TR
|
%TPR
|
%TNR
|
|
Question
12
|
92
|
65
|
13
|
27
|
157
|
157
|
40
|
65
|
17
|
|
Question
14
|
68
|
57
|
25
|
27
|
125
|
52
|
52
|
52
|
22
|
|
Total
|
160
|
122
|
38
|
54
|
282
|
92
|
374
|
117
|
39
|
Source:
Field work
From the table above, a total
position response of 282, representing 117% agreed with the fact that training
reduces industrial accident rate whereas a total of 92 respondents representing
39% disagreed.
Table
4.3
|
|
A
|
SA
|
D
|
SD
|
TPR
|
TNR
|
TR
|
%TPR
|
%TNR
|
|
Question 18
|
41
|
29
|
65
|
37
|
70
|
102
|
172
|
29
|
42
|
|
Question 19
|
37
|
42
|
38
|
51
|
79
|
89
|
168
|
37
|
33
|
|
Total
|
78
|
71
|
103
|
88
|
149
|
191
|
340
|
66
|
75
|
Distribution
as to control measures to reduce industrial accident in the company.
Source: Fieldwork
The table above shows that a total
of 149 or 66% respondents agreed that Guinness
Nigreian breweries, PLC Ikeja Lagos, have control measures to reduce industrial
accident in the company while a total of 191 respondents or 75% disagreed that
the company have control measures.
Table
4.4
Distribution
as to the cost effect of industrial accident in the company.
|
|
A
|
SA
|
D
|
SD
|
TPR
|
TNR
|
TR
|
%TPR
|
%TNR
|
|
Question
8
|
62
|
57
|
35
|
41
|
119
|
76
|
195
|
50
|
32
|
|
Question
10
|
57
|
65
|
42
|
37
|
172
|
79
|
201
|
72
|
33
|
|
Question
13
|
48
|
45
|
42
|
43
|
93
|
85
|
178
|
39
|
35
|
|
Question
20
|
37
|
42
|
38
|
51
|
79
|
89
|
168
|
33
|
37
|
|
Total
|
204
|
209
|
157
|
172
|
463
|
329
|
792
|
194
|
137
|
Source: Fieldwork
Table 4.4 shows that 463 respondents or 194% shows
that there are cost effect of industrial accident whereas 329 respondents representing
137% disagreed that there are cost effect of industrial accident in Guinness Nigerian
breweries PLC, Ikeja Lagos.
4.2 Test of hypotheses
In view of the available and relevant data for this study provided by
the fieldwork, the researcher decided to test both hypotheses in section 1.
Re-statement
of Hypothesis 1
Null
Hypothesis (H0):
Industrial accident has no effects
on employee morale.
Null
Hypothesis (H2):
Industrial accident has effects on
employee morale.
Decision
Rule:
Reject
H0, if calculated X2 > critical value
Accept
H0, if calculated X2 < critical value
Reject
H1, if calculated X2 < critical value
Accept
H1, if calculated X2 > critical value
Degree
of freedom = (R – 1) (c-1)
(4-1) (3-1)
3 x 2 = 6df
Critical
value of 6df at 5% significance level 12.59.
Table
4.5
Value
Utilized In Testing Hypothesis
|
|
A
|
SA
|
D
|
SD
|
Total
|
Percentage
|
|
Q4
|
37
|
59
|
42
|
34
|
172
|
|
|
Q9
|
43
|
68
|
48
|
39
|
198
|
|
|
Q11
|
37
|
58
|
41
|
33
|
168
|
|
|
Total
|
117
|
185
|
131
|
105
|
538
|
|
Calculation
of the expected frequencies from the observed frequencies
37 =
172 x117 = 37
538
42 =
198 x117 = 43
538
38 = 168
x 117 = 37
538
65 =
172 x185 = 59
538
69 =
198 x 185 = 68
538
51 =
168 x 185 = 58
538
41 =
172 x 131 =42
538
53
= 198 x 131 = 48
538
37 =
168 x 131 = 41
538
29
= 172 x 105 =34
538
34
= 198 x 105 = 39
538
42 =
168 x 105 = 33
538
Table
4.6
|
Obs. Freq.
|
Exp. Freq
|
(O-e
|
(O-e)2
|
(O-e)2/e
|
|
37
|
37
|
0
|
0
|
0
|
|
42
|
43
|
-1
|
1
|
0.025
|
|
38
|
37
|
1
|
1
|
0.027
|
|
65
|
59
|
6
|
36
|
0.610
|
|
69
|
68
|
1
|
1
|
0.0147
|
|
51
|
58
|
7
|
49
|
0.844
|
|
41
|
42
|
-1
|
1
|
0.0238
|
|
53
|
48
|
5
|
25
|
0.520
|
|
37
|
41
|
-4
|
16
|
0.390
|
|
29
|
34
|
-5
|
25
|
0.735
|
|
34
|
39
|
-5
|
25
|
0.641
|
|
42
|
33
|
9
|
81
|
2.5
|
|
538
|
59
|
-1
|
198
|
6.33
|
Observed frequency expected frequency
Ex 2 = 6.33
x 2
=å (O-e) 2 =
6.33
e
Calculated
x 2 = 6.33
Critical
value = 2.4469
Since
the calculated x 2 (6.33) is greater than the critical value x 2
(24469), the null hypothesis is rejected
4.2
Test of hypothesis II
|
|
A
|
SA
|
D
|
SD
|
Total
|
Percent
|
|
Q48
|
54
|
55
|
41
|
45
|
195
|
|
|
Qus
10
|
55
|
57
|
43
|
47
|
201
|
|
|
Q13
|
49
|
50
|
38
|
42
|
178
|
|
|
Q20
|
46
|
47
|
36
|
39
|
168
|
|
|
|
204
|
209
|
157
|
172
|
742
|
|
62
= 195 x 204 = 54
742
57
= 201 x 204 = 55
742
48
= 178 x 204 = 49
742
37 =
168 x 204 = 46
742
57 =
195 x 209 = 55
742
65 =
201 x 209 = 57
742
45 =
178 x 209 = 50
742
42 =
168 x 209 = 47
742
35 =
195 x 157 = 41
742
42 =
201 x 157 = 43
742
42 =
178 x 157 = 38
742
38 =
168 x 157 = 36
742
41 =
195 x172 = 45
742
37 =
201 x 172 = -47
742
43 =
178 x 173 = 42
742
51 =
168 x 172 = 39
742
|
Obse.freq
|
Expect
freq (e)
|
O-e
|
(O-e)2
|
(O-e)
2/e
|
|
62
|
54
|
8
|
64
|
1.18
|
|
57
|
55
|
-2
|
4
|
0.072
|
|
48
|
49
|
-1
|
1
|
0.020
|
|
37
|
46
|
-9
|
81
|
1.8
|
|
57
|
55
|
2
|
4
|
0.072
|
|
65
|
51
|
8
|
64
|
1.12
|
|
45
|
50
|
5
|
25
|
0.5
|
|
42
|
47
|
-5
|
25
|
0.53
|
|
35
|
41
|
-6
|
36
|
0.878
|
|
42
|
43
|
-1
|
1
|
0.023
|
|
42
|
38
|
4
|
16
|
0.421
|
|
38
|
36
|
2
|
4
|
0.111
|
|
41
|
45
|
-4
|
16
|
0.355
|
|
37
|
47
|
-10
|
100
|
2.12
|
|
43
|
42
|
1
|
1
|
0.02
|
|
51
|
39
|
12
|
144
|
3.69
|
|
742
|
744
|
4
|
566
|
12.912
|
Ex2
= 12.912
X2
= å(o-e) 2 =
12.912
E
Calculated
x2 = 12.912
Critical
value = 1.8331
Decision
Rule:
Since the calculated x2
(12.912) is greater than the critical value x2 (1.8331),
Table
4.9
Values
utilized for the test of hypothesis III
|
|
A
|
SA
|
D
|
SD
|
Total
|
|
Q12
|
87
|
64
|
20
|
|
194
|
|
Q14
|
76
|
58
|
18
|
|
177
|
|
Total
|
160
|
122
|
38
|
51
|
371
|
92 =
194 x 160 = 87
371
68
= 160 x 177 = 76
371
65
= 194 x 122 = 64
371
57
= 177 x 122 = 58
371
13 =
197 x 38 = 20
371
25
= 177 x 38 = 18
371
24 =
197 x 51 = 27
371
27 =
177 x 51 = 24
371
|
Obs.
Freq O
|
Exp.
Freq (e)
|
0-e
|
(o-e)2
|
(o-e)2/e
|
|
92
|
87
|
5
|
25
|
0.3
|
|
68
|
76
|
-8
|
64
|
0.84
|
|
65
|
64
|
1
|
1
|
0.015
|
|
57
|
58
|
-1
|
1
|
0.017
|
|
13
|
20
|
-7
|
49
|
2.45
|
|
25
|
18
|
7
|
49
|
2.8
|
|
24
|
27
|
-3
|
9
|
0.33
|
|
27
|
24
|
3
|
9
|
0.12
|
|
371
|
374
|
-3
|
207
|
6.872
|
Ex
2 = 6.9
X 2 = å( o - e ) 2 = 6.9
e
Calculated
value x 2 = 6.9
Critical
value = 2, 3534
Decision
Rule
Since the calculated x 2 (6.9)
is greater than the critical value x 2 (2.3534) the null hypothesis is
accepted. We there fore conclude that “Employee’s training has significant
impact in controlling accident in the organization..
Discussions
5.1 Discussion of Findings
From the above findings, the
researcher discovered that industrial accident is unavoidable in any industrial
establishment, from the result of the questionnaires distributed among staff or
Employees of Guinness Nigerian Breweries, plc Ikeja Lagos, it was discovered that
no matter the level of prevention of industrial accidents, we cannot stop its occurrence.
From the first hypothesis tested, the result shows that industrial accident has
significant effect on employee’s morale. The second hypothesis put it that
though industrial accident is unavoidable, the cost of reduce the accident has a significant effect
on the organization performance. Finally, the third hypothesis concludes that,
Employees training has significant impact on controlling accident in the organization.
This implies that expatriates are needed if industrial accidents are to be
minimized in any industry.
5.2 Implications of Review
A major service
sector that will improve the employee morale is the inclusion of global
diversity plan to help communicate, among others, all the departments in the industry.
This will help in the reduction of accidents as well as improve in the employee
services delivery.
Equally, from the literature, it was
reviewed that distrust among top-workers and their level of relationship to
their junior cadre affects the employee’s morale. To this end both sector
should endeavor to come together to rescue the problems. The implication is
that the industrial management should
endeavour to improve in managing their industrial hazard for greater efficiency.