CHAPTER -v ORGANISATIONAL FACTORS …shodhganga.inflibnet.ac.in/bitstream/10603/61108/12/12_chapter 5.pdfCHAPTER -v ORGANISATIONAL FACTORS CAUSING ABSENTEEISM IN CPCL This chapter

CHAPTER -v

ORGANISATIONAL FACTORS CAUSING

ABSENTEEISM IN CPCL

This chapter completely explores the factors directly incidental over CPCL

employees causing absenteeism. The stress creating factors at the work environment,

different interpersonal relationship among different levels of employees and nature

of work are playing vital role in this chapter. To ascertain the real causes of

absenteeism among the employees the nature of work and inter-personal relationships

create awartion and uninteresting approaches among the employees, the behavioural

aspects of top level management people and the behaviour of middle level employees

to execute the comments of the top level management create enormous amount of

stress among the lower level executives. In fact this leads to high rate of absenteeism

among the lower level executives. This chapter also explores the external factors like

family commitment and various health problem and their respective impact over

absenteeism

Factor Analysis by principle component analysis method is applied on the

level variables of interpersonal relationship among top, middle and lower level

executives.

The following variables are considered for the analysis in this study:

• Do you get on well with your co-workers?

• Do you let others know how you are feelings?

• Do you get jealous of your co-workers?

• Do you often get angry with others?

135

. Do you avoid social contacts in the recent past?

• Do you have difficulty saying 'no' to others?

• Do you have time for your hobbies, pastime?

• Do you confide your personal matters to your friends?

• Do you avoid people whose ideas are different from yours?

• Do you react defensively to constructive criticism?

. Do you look to others to make things happen to you?

The following results are obtained through factor analysis

Table 5.1

Factors of absenteeism due to inter-personal relationship

Rotation Sums of SquaredInitial Eigen values

ComponentLoadings

% of Cumulative Total% of Cumulative

Total

Variance Variance

1 3.788 34.439 34.439 2.798 25.440 25.440

ff

1.424 12.943 47.381 2.053 18.663 44.102

1.251 11.377 58.758 1.612 14.656 58.758

.937 8.522 67.279

5 .886 8.055 75.335

6 .718 6.529 81.863

7 .591 5.375 87.238

8 .487 4.431 91.669

9 .454 4.125 95.794

10 .262 2.378 98.172

11 .201 1.828 100.000

Extraction Mettioa: inncipai imiwiJ

From the above Table, it is found that the eleven variables are converted into

three major factors. These eleven variables explain 58.75% of the total variance.

Table presents the variable loadings of each factor.

- 136

VARIABLE LOADINGS OF FACTORS OF INTER-PERSONALRELATIONSHIP

Tih1e 5.2Component

1 2 3

q5 .804

q3 .760

q6 .744

q4 .689

qlO .787

q9 .784

qi -.618

qil .454

q7 .813

qa8 .683

q2 .619

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with

Kaiser Normalization, a Rotation converged in 5 iterations.

From the above Table, it is inferred that factor one consists of the variables

1. Do you avoid social contacts in the recent past? (0.804)

2. Do you get jealous of your co-workers ?(0.760)

3. Do you have difficulty in saying "No" to others (0.744)

4. Do you often get angry with others? (0.689)

Hence the first factor is named as social contact and non-co operation.

The Second factor consists of the following variables:

Do you react defensively to constructive criticism? (0.787)

Do you avoid people whose ideas are different from yours? (0.784)

Do you get on well with your co-workers? (-0.618)

Do you look to others to make things happen to you? (0.454)

137

Therefore the second factor can be suitably named as (Cordial) relationships and

openness.

The Third factor emerges from the variables

Do you have time for your hobbies? (0.813)

Do you confide personal matters to your friends? (0.683)

Do you let others know your feelings? (0.619)

Therefore this factor can be called as leisure time and sharing the views.

So, it is concluded that CPCL, the absenteeism due to interpersonal

relationships is evolved in the form of factors; lack of social contacts and non-co

operation", "cordial relationships and openness" and "leisure time and sharing of

views".

THE PREDOMINANT FACTORS OF INTER-PERSONAL RELATIONSHIP

CAUSING STRESS:

Factor analysis extracted three factors of interpersonal relationships among the

employees of the CPCL namely:

. Social contacts and non co-operation (SCNON)

Cordial relationships and openness (OPCOR)

. Leisure time and sharing of views (LTS HARE)

The one sample "t" test with test value 3 is applied on eleven variables of

absenteeism due to interpersonal relationships and the following results are obtained.

138

Table 5.3

One-Sample Statistics for variables of absenteeism due to inter-personalrelationship

Table 5.4

One-Sample Test for variables of absenteeism due to inter-personal relationship

Test Value = 395% Confidence

t Df Sig. (2-tailed) Mean Difference Interval of the Difference

Lower Upper

qi 7.391 599 .000 .80000 .5852 1.0148

q2 4.075 599 .000 .45000 .2309 .6691

q3 -3.562 599 .001 -.51000 -.7941 -.2259

q4 -2.730 599 .008 -.35000 -.6044 -.0956

q5 -2.394 599 .019 -.33000 -.6035 -.0565

q6 .152 599 .880 .02000 -.2415 ;2815

q7 -.527 599 .599 -.07000 -.3334 .1934

qa8 -.414 599 .680 -.05000 -.2899 .1899

j

-2.478 599 .015 -.34000 -.6123 -.0677

-1.205 599 .231 -.13000 -.3441 .0841

.386 599 .701 .21000 -.8703 1.2903

The value 4.3 revealed that the mean values of variables of absenteeism due to

inter-personal relationship range from 2.49 - 3.80.

139

The 't' test significance is displayed in Table 5.4 This shows that the

employees in the CPCL agree with absenteeism due to cordial relationship with co-

workers, understanding others feelings and maintaining a smooth relationship to

achieve things at work. The employees remain undecided to express their opinion in

difficulty in saying "No" to others, confiding the personal matters and having time for

their hobbies. They disagree with absenteeism due to jealousy of co-workers, getting

angry with others, avoiding social contacts, avoiding ideas from others and reaction to

constructive criticism. One sample "t" test is applied on the above-mentioned three

factors and the following results are obtained.

Table 5.5

One-Sample Statistics for factors of inter-personal relationship

Factors N Mean Std. Deviation Std. Error Mean

SCNON 600 2.7075 1.06307 .10631

OPCOR 600 3.1875 1.49468 .14947

LTSHARE 600 3.1200 .88321 .08832

Table 5.6

One-Sample Test for factors of inter-personal relationship

Test Value 3

Sig. (2- Meantailed' Difference

-2.751 599 .007 -.29250

1.254 599 .213 .18750

1.359 599 .177 .12000

95% Confidence Intervalof the Difference

Lower Upper

-.5034 -.0816

-.1091 .4841

-.0552 .2952

Factors

SCNONOPCORLTSHARE

t I df

140

Table revealed that the mean value of factors ranging are from 2.71 - 3.18.

The "t" test value used for these mean values and the test value 3 show that the

employees CPCL disagree with the absenteeism due to social contacts and non-

cooperation from the employees. In the case of other factors like "openness and

cordial relationships" and "leisure time and sharing view" the employees are not able

to decide absenteeism due to openness and sharing of views. So, it is concluded that

CPCL absenteeism due to interpersonal relationships is not significant among the

employees.

ABSENTEEISM AND WORK ENVIRONMENT

Work environment is one of the crucial factors for stress, many public and

private sector organizations acknowledge the un-acceptance costs of absenteeism and

have resorted to providing a better place of work. There are many macro and micro

factors at work, which leads to stress. They are: (a) Organisational culture: Building a

supportive and open climate and culture and ensuring that the style of management is

compatible with the goals and aims which are important in reduction of stress. It means

developing a culture that encourages staff to be more supportive of each other. This will

facilitate team working and good inter-personal relationships in the work place. b) Work

overload: A high work overload leads to long hours of working either as paid to as paid

or unpaid overtime. Re-analysis of staffing levels, task redesign helps reduce work

overload. (c) Safety: physical and psychological safety is a basic human need and having

a predictable and non-threatening environment is fundamental to this need. (d)The

absenteeism can be associated with uncertainty and ambiguity about the future and

career potential. (e) Absenteeism can be caused if there is no participative decision-

making which need to be a part of their job. (f) Absenteeism if there is discrimination on

141

the basis of race, colour, sex or creed (g) Absenteeism from work could be in the form

of pay and associated fringe benefits, allowances if they are lesser than what the

employee actually deserves or expects (h) The constructs of role conflict are also

acknowledged as a potent source of absenteeism in work environment that has negative

attitudinal and behavioral outcomes (i) the nature of leadership, the policies and

procedures of organization, job insecurity, organisational change and uncertainty, targets

and deadlines, authoritarian culture and poor work relationship are some major causes of

absenteeism of work.

These when increased further in magnitude will alleviate the problems associated

such as low work motivation and job dissatisfaction. Thus employees are more attached

to organization with good policies and family friendly atmosphere which causes job

enrichment and reduction in stress, and greater turnover.

Factor analysis is applied on the twenty-eight variables on absenteeism due to

work environment and the following results are obtained

142

Table 5.7

Factors of absenteeism due to work environment

Corn- Initial EigenvaluesRotation Sums of Squared

ponent ____________ Loadin u,,s

Total% of Cumulative Total

% of Cumulative.

Variance % Variance %

1 14.337 51.203 51.203 6.074 21.693 21.693

2 2.147 7.668 58.871 6.049 21.603 43.296

3 1.778 6.350 65.221 5.934 21.193 64.489

4 1.578 5.635 70.856 1.704 6.085 70.574

5 1.312 4.686 75.542 1.391 4.968 75.542

6 .984 3.513 79.055

7 .845 3.018 82.073

8 .694 2.477 84.551

9 .632 2.258 86.809

10 .545 1.946 88.755

11 .472 1.684 90.439

12 .443 1.583 92.022

13 .417 1.488 93.509

14 .320 1.143 94.652

15 .263 .939 95.591

16 .216 .770 96.361

17 .173 .619 96.980

18 .137 .490 97.470

19 .127 .453 97.923

20 .117 .419 9 8.3 42

21 .093 .333 98.674

22 .081 .289 98.963

23 .068 .244 99.207

24 .061 .217 99.424

25 .050 .179 99.603

26 .045 .162 99.765

27 .037 .131 99.896

28 .029 .104 100.000

Extraction Method: I-'rinclpal component i-uLu1y1.

From the above Table, it is found that the twenty eight variables are converted

into five major factors with 75.542 per cent of total variance, the variable loadings of

each factor is presented in the Table 4.11

143

Table 5.8

Variable loadings of factors of absenteeism due to work environment

1 2 3 4 5

q27 .783

q21 .767

q20 .723

q29 .697

q22 .693

q26 .692

q28 .657

q30 -.578

q25 .553

q35 .836

q32 .823

q33 .803

q36 .796

q37 - .775

q40 - -.700

q34 .595

q31 - .581

q18 .877

q13 .840

q14 .830

q17 .828

q15__ .809

q12 .710

q16 _________ _________ .654

q39 ________ .769 ________

q38 .702

_________ ___________________ .739q24 q19

Extraction Method: Principal Component Analysis. Rotation

Method: Varimax with Kaiser Normalization, a Rotation converged in 21 iterations.

From the above Table it is derived that factor one consists of the variables

27. I receive additional allowances and facilities besides my salary (0.783)

144

21. I have job security (0.767)

20. The demands of my job does not interfere with my family (0.723)

29. The management takes personal interest in my well being (0.697)

22. Conditions on my job allow me to be as productive I can be (0.693)

26. Promotions are handled fairly at work (0.692)

28. I keep learning new things at work (0.657)

30. In the past 12 months I have had pain in hands, arms, shoulders, wrist, back (-

0.578)

25. There is no age, race, gender discrimination at work (0.553)

Hence the first factor is called management policy.

The second factor consists of the following variables:

35. I do not feel I am always under pressure (0.836)

32. I am able to meet deadlines (appointments, chores, promises) (0.823)

33. I do not have conflicts and disagreements with peer's, superior's often (0.803)

36. I do not have difficulty in concentrating at work (0.796)

37. All in all I am satisfied at work (0.775).

40. I feel tired at the beginning of the day (-.400).

34. I do not feel I am always under pressure (0.595).

31. My main satisfaction in life comes from work (0.58 1).

Therefore the second factor is suitably called as work performance.

The Third factor consists of the following variables.

18. I have sufficient time to get the work done (0.877).

145

13. My job lets me use the best of my abilities and skills (0.840).

14. Management has taken necessary steps to ensure safety at work (0.830).

17. I receive necessary equipments to get my work done (0.828).

15. I have enough people or staff to get all the work done (0.809).

6. I know what is expected of me at work (0.710).

16. The chances of promotion are good at work (0.654).

Therefore the third factor is named as promotion and facilities.

The Fourth factor consists of the following variables.

39. My fringe benefits are good (0.769).

38. I feel lonely (0.702).

Hence the fourth factor is suitably called as benefits and seclusiveness.

The fifth factor consists of the following variables.

24. I have too much work to do everything well (0.739).

19. My job requires me to do lifting, pulling, pushing, bending (0.448)

So this factor is called work load.

Hence it is concluded that in the CPCL the absenteeism due to work environment is

evolved in the form of

1. Management policy (MP)

2. Work performance (WP)

3. Promotion and facilities (PROFACT)

4. Benefits and seclusiveness (BFSECLUS)

5. Work load (WL)

One sample "t" test is applied on the above-mentioned five factors and the

following results are obtained.

146

Table 5.9

One-Sample Statistics for factors of absenteeism due to work environment

Factors N Mean Std. Deviation Std. Error Mean JMP 600 3.2722 .86318 .08632

TWP 600 3.5186 1.13210 .113211

[IOFACIL 600 3.4143 1.07797 .107

[BFSECLUS 600 2.9500 1.07895 .107

WL 600 3.0350 .91081 .091

Table 5.10

One-Sample Test for factors of absenteeism due to work environment

Test Value = 3

t I dfFactors

MP 3.154 599WP 4.581 599

PROFACIL 3.843 599BFSECLUS -.463 599WL .384 599

Sig. (2-tailed)

.002

.000

.000

.644

.702

MeanDifference

.27222

.51857

.41429-.05000.03500

95% Confidence Intervalof the Difference

Lower Upper

.1009 .4435

.2939 .7432

.2004 .6282

-.2641 .1641

-.1457 .2157

Table ascertained that the mean values of the factors are varying from 2.95 to

3.51. The "t" test of significance shows that the factors, "Management policy", "Work

performance", "Promotion and facilities", "Benefits and seclusiveness" and "Work

overload" are significantly higher than the test value three, whereas work load

benefits and seclusiveness are not statistically significant. This shows that the

employees CPCL agree with absenteeism due to management policies, work

performance and promotional facilities. They are not able to express any opinion

about absenteeism due to "benefits and seclusiveness" and "Work load".

147

ABSENTEEISM AND HEALTH

Absenteeism can cause a toll on health prolonged periods of stress, where body

does not return to a homeostatic state, can result in chronic exhaustion and illness.

Under such constant stress, the body continues to manufacture increased quantities of

absenteeism chemicals, which depresses the immune system.

When absenteeism occurs, the signs and its effects on body are increased heart

rate, high blood pressure, difficulty in breathing, difficulty in swallowing, feelings of

nausea, hyperventilation, contracted muscles, backache, hot and cold t'lushes, blushing,

sweating, skin dryness, rashes, numbness, stinging, sensation, increased blood sugar

levels, dilation of pupils, dry mouth and frequent urination; these are caused when there

is an imbalance between the demands of everyday life and the ability of cope.

The effects are broadly categorized into behavior, thoughts, emotions, and

health. Behavior difficulty sleeping, loss of appetite, avoidance of particular situations,

inactivity. Thoughts difficulty in concentrating, in making decisions, forgetfuliness,

distorted ideas, emotions anxiety, moodiness, apathy, fatigue, tension, panic, phobias,

nervousness and health stomach ulcers, migraine, diarrhoea, skin rashes, strokes and

coronary heart diseases. Physical exercise can boost the immune system and increase the

activity of the body. The ability to cope absenteeism depends on how the balance

between demands in life, operates everyday.

Thus it can be seen that absenteeism and health are closely linked. The life skills

such as assertiveness and rational thinking can equip an individual to cope with the

demands of everyday life.

148

I find myself confused or restless, jittery, nervous

1. I lack fulfillment, joy, and peace in life

2. Ineglect my diet

3. I neglect my network of friends.

4. I have difficulty maintaining a healthy weight.

5. I spend a lot of time thinking about the past.

6. I feel my leave turnover has been increasing in the recent past.

7. I have difficulty in remembering things.

Therefore this factor can be called as physiological Psychological changes

(PPFACTO).

Factor analysis revealed that the employees in CPCL have classified the

absenteeism due to health as psychological and physiological features. One sample

"t" test is applied on this factor and the following results are obtained.

Table 5.11

One-Sample Statistics for absenteeism due to health

Factor N Mean Std. Deviation Std. Error Mean

PPFACTO 600 2.8170 1.20270 .12027

Table 5.12

One-Sample Test for absenteeism due to health

Test Value = 3

Factor Tdf Sig. (2- Mean 95% Confidence Interval

tailed) Difference of the Difference

Lower Upper

-.18300 -.4216 .0556PPFACTO

149

From the Table it is known that the mean values of the effect of absenteeism

are 2.81, which is not, statistically significant w.r.t the test value three. This shows

that the employees in the CPCL are not able to express their opinion about

physiological and psychological changes due to absenteeism in their organisation

significantly.

One-way analysis of variance for absenteeism due to interpersonal relationship

with respect to Age

One-way analysis of variance is applied for three factors of interpersonal

relationship namely "non-cooperation", "Openness and cordial relationship", "leisure

time and sharing of views" with respect to the age groups 18-30, 31-40 and 40-50,

respectively.

Table 5.13

ANOVA for factors absenteeism due to inter-personal relationship with respect

to AGE

From the above Table it is found that the factor social contact and non-co

operation differ significantly with respect to age. The report Table 4.19 revealed that

150

the employees in the age group 18-30 are in an undecided mood about absenteeism

due to social contact and non - co operation, followed by the age group 40-50 and 31-

40.


with respect to gender

One-way analysis of variance is applied for three factors of inter-personal

relationship namely " non-cooperation and social contacts" "Openness and Cordial

Relationship", "leisure time and sharing of views" with respect to gender male and

female.

Table 5.14


to GENDER

Factors Sources Sum of Squares Mean Square F Sig.

[SCNON Between Groups .272 .272 .239

Within Groups 111.610 1.139

L Total 111.882

LOPCOR Between Groups 2.010 2.010 .899 .345


Total 221.172

SHARE Between Groups 1.807 1.807 2.348 .129

Within Groups 75.420 .770

Total 77.227

From the above Table it is found that none of the factors of inter-personal

relationship differ significantly with respect to gender. So it is concluded that both

male and female employees CPCL are the same in their opinion about absenteeism

due to interpersonal relationship.

151


with respect to job status.

One-way analysis of variance is applied for three factors of interpersonal relationship

namely "Social contacts and non-co-operation", "Openness and Cordial relationship",

"leisure time and sharing of views" with respect to job status lower, middle, top level

respectively.

Table 5.15


to JOB


SCNON Between Groups 53.456 26.728 44.374 .000


Total 111.882

OPCOR Between Groups 12.390 6.195 2.878 .061


Total 221.172 ______

LTSHARE Between Groups 11.451 5.725 8.443 .000

Within Groups 65.776 .678 ____

Total 77.227

From the above Table it is found that the factors "social contact and non-

cooperation", and "leisure time and sharing of views" differ significantly with respect

to job status.

The report Table revealed that the employees in the job status of lower level

and middle level are in an undecided mood about absenteeism due to "social contact

and non-co-operation" and "leisure time and sharing of views", followed by the job

status of employees who are at a higher level.

152


with respect to salary.

One-way analysis of variance is applied for three factors of interpersonal

relationship namely "social contacts and non-co-operation", "openness and cordial

relationship", "leisure time and sharing of views" with respect to salary 3000-5000,

5000-10000, and above 10,000.

Table 5.16

ANOVA for factors absenteeism due to inter-personal relationship with respectto SALARY

Factors SourcesSum of Mean Square F Sig. I

L Squares

çNON Between Groups 50.277 25.138 39.582 .0001


Total 111.882

LQCOR Between Groups 13.830 6.915 3.235 .044


L Total 221.172

JJSHARE Between Groups 13.235 6.618 10.031 .000


Total 77.227

From the above Table it is found that the factors "social contact and non-

cooperation", "Openness and cordial relationships" and "leisure time and sharing of

views" differ significantly with respect to salary.

The report Table revealed that the employees whose salaries are in between

3000-5000 are in an undecided mood about absenteeism due to "social contacts and

non-cooperation", followed by employees whose salaries are between 5000-10,000

and above 10,000.

153


with respect to experience

One-way analysis of variance is applied to three factors of interpersonal

relationship namely "social contacts and non-co-operation", "openness and cordial

relationship", "leisure time and sharing of views" with respect to experience of 1-5, 5-

10 and above 10 years.

Table 5.17


to EXPERIENCE


SCNON Between Groups 31.484 15.742 18.993 .000


Total 111.882

OPCOR Between Groups 6.070 3.035 1.369 .259


Total 221.172 ______

LTSHARE Between Groups 5.650 2.825 3.829 .025


Total 77.227 I

From the above Table it is found that the factors "social contacts and non-co-

operation", "leisure time and sharing of views", differ significantly with respect to

experience.

The report Table revealed that the employees in the experience of 7-5 years

are in an undecided mood about absenteeism due to "social contacts and non co-

operation", "leisure time and sharing of views", followed by employees whose

experience are 5-10 and above 10 years.

154

Analysis of variance for absenteeism due to work environment

The five factors of work environment namely management policy, work

performance, promotion and facilities, benefits and seclusiveness and work load are

subject analysis of variance with respect to the demographic variables age, gender,

education and job status and the results are discussed here under:

01. Analysis of variance for absenteeism due to work environment with

respect to age:

Table 5.18

ANOVA for absenteeism due to work environment with respect to AGE


MP Between Groups 2.976 1.488 2.039 .136


Total 73.762

WP Between Groups 5.499 2.750 2.197 .117


Total 126.884

PROFACIL Between Groups 1.346 .673 .574 .565


Total 115.041

BFSECLUS Between Groups 1.003. .502 .426 .654


Total 115.250

WL Between Groups 4.739 2.369 2.970 .056


Total 82.128

From the above Table it is found that there is no significant difference in the

factors of absenteeism due to work environment with respect to age. The employees

155

in different age group CPCL expressed the same opinion about absenteeism due to

work environment.


respect to gender:

Table 5.19

ANOVA for absenteeism due to work environment with respect to GENDER




Total 73.762

WP Between Groups .146 .146 .113 .738

Within Groups 126.738 1.293 _

Total 126.884

PROFACIL Between Groups .176 .176 .151 .699


Total 115.041

BFSECLUS Between Groups .397 .397 .339 .562


______ Total 115.250 _____



82.127

From the above Table it is found that there exists significant difference in the

factors work load with respect to gender, other factors do not differ significantly. The

arithmetic mean analysis revealed that the female employees CPCL are very much

affected by absenteeism due to work load than male employees.

156


respect to job status:

Table 5.20

ANOVA for absenteeism due to work environment with respect to

JOB STATUS

Factors SourcesSum of Mean Square F Sig.Squares



Total 73.762 _



Total 126.884

PROFACIL Between Groups 35.727 17.863 21.847 .000


--Total 115.041 ______

BFSECLUS Between Groups 4.028 2.014 1.757 .178


Total 115.250



From the above Table, it is found that the factors management policy, work

performance, promotion and facilities differ significantly with respect to job status.

The mean analysis explained that the lower level executives are affected by

absenteeism due to management policies, work performance, promotion and facilities,

followed by middle level executives and top-level executives. So it is concluded that

absenteeism prevails more among lower level executives.

157


respect to salary:

Table 5.21

ANOVA for absenteeism due to work environment with respect to SALARY

Sum of MeanPFactors Sources F Sig.

Squares Square

Between Groups 11.808 5.904 9.243 .000


Total 73.762



Total 126.884



Total 115.041



Total 115.250



Total 82.128

From the above Table it is found that the factors of absenteeism due to work

environment namely management policy, work performance, promotion and facilities

and work load differ significantly at 5 percent level of significance. The mean

analysis ascertained that the employees in the income group above 10,000 are affected

by the absenteeism due to management policies, work performance, promotion and

facilities. But in the case of workload, the employees with salary less than 5000 are

affected by absenteeism more than others.

158

5. Analysis of variance for absenteeism due to work environment with respect to

experience:

Table 5.22

ANOVA for absenteeism due to work environment with respect to

EXPERIENCE

Factors

Sum of Mean Square F Sig.Squares



Total 73.762 _______ ______



Total 126.884



Total 115.041 ______



______ Total 115.250


Within Groups 76.705 .791 ____

82.128 __ ____ ^

From the above Table, it is inferred that the employees in the CPCL differ

significantly in their opinion about absenteeism due to management policies, work

performance, promotion facilities and work load. Based on their experience, the

arithmetic mean analysis revealed that the absenteeism due to management policies,

work performance, promotion facilities affect the employees with more than 10 years

of experience. As far as the work load is concerned, the employees with experience

5-10 years are very much affected by the work load than others.

159

Analysis of variance for absenteeism due to health:

The factors analysis on the variables of absenteeism due to health revealed the

existence of a unique major factor. Now One-way analysis of variance is applied on

the factor with respect to all the demographic variables.

01. Analysis of variance of absenteeism due to health factor with respect to

Age:

Table 5.23

ANOVA For absenteeism due to health factor with respect to AGE:

Sum of Squares Mean Square F Sig.

LIL 16.463 8.231 6.300 .003

s 126.738 1.307

143.201

Sources

BetweenWithin (Total

From the above Table it is inferred that the employees in the CPCL differ

significantly in their opinion about absenteeism due to health factor based on their

age. The employees in the age group between 30-40 are affected by absenteeism due

to health whereas others are not affected by the health stress.


Gender:

Table 5.24

ANOVA For absenteeism due to health factor with respect to GENDER

Sources Sum of Squares Mean Square F Sig.

Between Lps 4.951 4.951 3.509 .064

Within (

138.250 1.411

Total

143.201

160

From the above Table, it is found that there is no significant difference

between male and female employees in the CPCL in the opinion of absenteeism due

to health. It is concluded that both of them are equally affected by absenteeism due to

health.


job status:

Table 5.25

ANOVA for absenteeism due to health factor with respect to JOB STATUS


Between Groups 23.618 11.809 9.579 .000


Total 143.201

From the above table, it is ascertained that the employees of the CPCL differ

in their opinion about health absenteeism with respect to their status. The mean

analysis revealed that the top-level executives are very much affected by absenteeism

due to health whereas others are not at all affected by health stress.

161


salary:

Table 5.26

ANOVA Report for absenteeism due to health factor with respect to SALARY


Between Groups 34.557 17.279 15.427 .000


Total 143.201

The above table explains that the employees CPCL differ in their opinion

about health stress. Especially the employees CPCL with less than Rs. 5000 salary is

very much affected by health absenteeism and others are not affected by stress.


experience:

Table 5.27

ANOVA for absenteeism due to health factor with respect to EXPERIENCE


Between Groups 26.892 13.446 11.214 .000


Total 143.201

It is inferred that the employees CPCL differ in their opinion about health

absenteeism with respect to experience of the employees. It is also found that the

162

employees CPCL with experience 10-15 years are very much affected by health

absenteeism followed by employees with less than 5 years.

FACTORS OF EMPLOYEES ABSENTEEISM AND ITS INFLUENCE ON

CPCL EMPLOYEES AND THEIR ORGANISATION

In a competitive and global business environment, converting challenges into

business opportunities needs a high degree of integration of resources and

competencies. It is essential to empower the people involved in converting the

opportunities with unstinted devotion. An absenteeism practice at all levels is

considered as a powerful tool to achieve the adequate outputs. The absenteeism

process for both men and employees in every organisation is congruent to

absenteeism practices and its implementation of its subsistence'. The outcomes and

their effectiveness of absenteeism emerge in the form of improvement in the

individual efficiency, organisational efficiency, productivity and creation of optimistic

atmosphere. One of the most successful strategies is employee absenteeism. As a HR

strategy, it indicates the tremendous faith reposed by the organisation in the abilities

of an employee to deliver the value chain2 . Recognition and respect for the

individual's potential is the very essence of absenteeism.

In this chapter the employee's absenteeism factors of organisation and external

influence are going to be found out microscopically. T-test is applied to study the

opinion of the CPCL Employees about various processes in the organisation. Factor

analysis is a multivariate tool applied to reduce the numerous number of variables

used in the study into major factors.

163

ABSENTEEISM RELATED FACTORS

Absenteeism related factors play a conscious and effective role in CPCL

Employees and their absenteeism. To be successful in today's business environment,

companies need the knowledge, ideas, energy, and creativity of every employee, from

front line workers to the top-level managers in the executive suite. Absenteeism

practices are implemented with the hopes of building employee commitment,

overcoming worker dissatisfaction, and reducing absenteeism, turnover, poor quality

work, and sabotage. Reservations are given more priorities in case of public sector.

Whereas the policies of the private and MNC the main concern is on improvement of

employees in the organisation. Accordingly, absenteeism related factors in all the

sectors prominence is on the employee's role in the organization.

In this study Absenteeism related factors on absenteeism of CPCL Employees

are identified through 5 statements (see appendix) regarding the prominent role of

absenteeism related factors in the organization. One Sample T-test is applied on five

variables of Absenteeism related factors on CPCL Employees. This test is performed

with the test value 3 and the following results are obtained.

Table: 5.28

One-Sample Statistics for Absenteeism related factors

N Mean Std. Deviation Std. Error Mean

SRF1 600 3.9475 .99252 .04461

SRF2 600 3.9515 .94036 .04227

SRF3 600 3.6424 .97510 .04383

SRF4 600 3.8364 .80954 .03639

SRF5 600 3.8081 .96996 I .04360

Source: Computed Data

164

From the above Table it is found that all the mean values are greater than 3 in

particular ranging from 3.64 to 3.95 with their respective standard deviation it is

observed that the standard deviation of these five variables are strictly less than 1, this

implies the consistency of the opinions of CPCL Employees

TABLE: 5.29

One-Sample Test for Absenteeism related factors

Test Value = 3

t dfSig. (2- Mean 95% Confidence Interval of

tailed) Difference the Difference

Lower Upper

SRF1 21.239 599 .000 .94747 .8598 1.0351

SRF2 22.512 599 .000 .95152 .8685 1.0346

SRF3 14.658 599 .000 .64242 .5563 .7285

SRF4 22.986 599 .000 .83636 .7649 .9079

SRF5 18.535 599 .000 .80808 .7224 .8937


From the above Table it is found that t-test values are significantly greater

than the test value 3 at 5% level of significance. So CPCL Employees agree with the

aggressive behaviour and extraction of best of service in the form of increased work

load. They profoundly believe that adoption of target reaching and offering long

working hours is the main strategy of the management to create absenteeism among

the employees. CPCL Employees also agree that, potentiality and emphasis on regular

breaks are the indication of absenteeism formation.

PHYSICAL RESPONSE TO STRESS

The influence of absenteeism on physical and psychological well being is well

documented. Absenteeism has been implicated in heart disease, eating disorders,

165

stroke, insomnia, ulcers, accident proneness, cancer, decreased immunity, chronic

headaches, diabetes, depression, substance abuse, chronic pain, irritable bowel

syndrome and chronic fatigue. In fact, estimates are that 50 to 80 percent of all

physical disorders have psychosomatic or absenteeism related origins. CPCL

Employees report high absenteeism are three times more likely than employees

reporting low absenteeism to suffer from frequent illness. In this study 9 statements

are (see appendix) prepared to identify the physical response to stress. One Sample T -

test is applied on these nine variables and the Table infers the following results.

Table: 5.30

One-Sample Statistics for Development of physical response to stress


PR1 600 4.0263 .87087 .03914

iR2 600 3.8808 .82222 .03696

[TR33 600 3.8162 .84685 .03806

r PR4 600 3.7596 .79011 .03551

PiR5 600 3.8263 2.04754 .09203

riR6 600 3.8990 1.25410 .05637

r PR7 600 3.5596 .96915 .04356

rR8 600 3.8364 .79440 .03571

600 3.7737 .82553 .03710


It is ascertained from the above Table that all the mean values are greater than

3 in ranging from 3.55 to 4.02 with their respective standard deviation. It is observed

that the standard deviation of eight variables out of nine variables are strictly less than

1, this implies the uniformity of the opinions of CPCL Employees .so the CPCL

Employees widely oscillate in their opinion about the variables of physical responses

to absenteeism and withstanding the future challenges.

Table 5.31

One-Sample Test for physical response to stress

Test Value = 3

t Df Sig. (2-tailed) Mean Difference95% Confidence

Interval of the Difference

Lower Upper

PR1 26.218 599 .000 1.02626 .9509 1.1032

PR2 23.834 599 .000 .88081 .8082 .9534

PR3 21.442 599 .000 .81616 .7414 .8909

PR4 21.389 599 .000 .75960 .6898 .8294

PR5 8.978 599 .000 .82626 .6454 1.0071

PR6 15.949 599 .000 .89899 .7882 1.0097

PR7 12.847 599 .000 .55960 .4740 .6452

PR8 23.424 599 .000 .83636 .7662 .9065

PR9 20.853 599 .000 .77374 .7008 .8466


From the above Table it is observed that t-test values are significantly greater

than the test value 3 at 5% level of significance. It is found that the CPCL Employees

agree with the effects of head aches and stomach ache. They get these aches due to

heavy work load and stressful climate. They often get backache and stiffness in the

shoulder, high blood pressure. The CPCL Employees rarely get palpitations and rapid

breath. The employees sometimes encounter with problem of diabetes and dizziness.

BEHAVIOURAL RESPONSE TO STRESS

Once the existence of absenteeism has been recognized and the stressors

identified, action to deal with absenteeism should be taken. Absenteeism is a misfit

between the demands of the environment and the individual's abilities, the imbalance

may be corrected, according to the situation, either by adjusting external demands to

fit the individual or by strengthening the individual's ability to cope, or both. One

167

Sample T-test is applied on nine variables (see appendix) of behavioral response of

employees to absenteeism and the following results are obtained.

TABLE: 5.32

One-Sample Statistics for Organization Development and Employees

Absenteeism


BR! 600 3.7455 1.01997 .04584

BR2 600 3.6768 .88199 .03964

BR3 600 3.7899 .93531 .04204

BR4 600 3.7919 .79671 .03581

BR5 600 3.8202 .80861 .03634

BR6 600 3.7131 .93651 .04209

BR7 600 3.8707 .86979 .03909

BR8 600 3.7111 .96044 .04317

BR9 600 3.8242 .83897 .03771


The above Table infers that all the mean values are greater than 3 in particular

ranging from 3.67 to 3.87 with their respective standard deviation. It is observed that

the standard deviation of 9 variables of Organisation Development and employees

Absenteeism are less than 1 implying the uniformity of the opinion of CPCL

Employees in these 9 variables. But the standard deviation of the variable consist of

changes done in favour of employees are found to be more than 1, this connotes that

CPCL Employees differ enormously in their opinion about the behavioral response to

stress.

168

Table 5.33

One-Sample Test for Organization Development and Employees Absenteeism

Test Value = 3

95% Confidence Interval of the

t dfSig. (2- Mean Differencetailed) Difference

Lower Upper

BR1 16.261 599 .000 .74545 .6554 .8355

BR2 17.072 599 .000 .67677 .5989 .7547

BR3 18.790 599 .000 .78990 .7073 .8725

BR4 22.115 599 .000 .79192 .7216 .8623

BR5 22.568 599 .000 .82020 .7488 .8916

BR6 16.942 599 .000 .71313 .6304 .7958

BR7 22.272 599 .000 .87071 .7939 .9475

BR8 16.473 599 .000 .71111 .6263 .7959

BR9 21.858 599 .000 .82424 .7502 .8983


The CPCL Employees agree with the compulsive food and smoking for

relaxation. They also strongly agree with alcohol consumption to create a situation

free from stress. They often grind their teeth; clench their fist to remove absenteeism

from their mind. Over work load for CPCL Employees often create the sleepless

nights and forces to show resentment on others and colleagues. The CPCL employees

agreed that they always possess to attention disorder.

EMOTIONAL RESPONSE TO STRESS.

The harmful physical and emotional responses always occur when the

requirements of the job do not match the capabilities, resources, or needs of the

worker. Job absenteeism can lead to poor health and even injury." It simply means

that workplace absenteeism generally arises when there is a mismatch between the

nature and magnitude of the job to be done and the employee's desire and capabilities.

169

Std. Deviation.89530.93478.95907.76108

Std. Error Mean.04024.04202.04311.03421

The following results are achieved on the four variables (see appendix) of goal

achieving on applying the one sample t-test.

Table 5.34

One-Sample Statistics for emotional response

N Mean

LiR1 600 4.0081

ER2 600 3.8869

ER3 600 3.7960

ER4 600 3.9010Source: Computed Data

The table above reveals that it is found that all the mean values are greater

than 3 ranging from 3.79 to 4.00 with their respective standard deviation. It is

observed that the standard deviations of these four variables are less than 1. This

implies the consistency of the opinion of the CPCL Employees.

Table 5.35

One-Sample Test for emotional response to stress

LIITest Value = 3


t dfSig. (2- Mean Differencetailed) Difference Lower Upper

ER1 25.051 599 .000 1.00808 .9290 1.0871

ER2 21.108 599 .000 .88687 .8043 .9694

ER3 18.465 599 .000 .79596 .7113 .8807

ER4 26.339 599 .000 .90101 .8338 .9682

Source: Computect uata

From the above table it is found that t-test values are significantly greater than

the test value 3 at 5% level of significance. So the CPCL Employees strongly feel the

depressed situations in their mind and sense of accomplishment. The CPCL

170

Employees sometimes share their feelings about the work environment with friends

and relatives. They often brood over incidents as the indication of emotional response

to stress. Thus it can be said that the organisation policies helps the CPCL Employees

in achieving their stressful domain.

ABSENTEEISM PREVENTION PROCESS

The job absenteeism prevention process does not end with evaluation. Rather,

job absenteeism prevention should be seen as a continuous process that uses

evaluation data to refine or redirect the intervention strategy. The following lines

provide examples of actions some organizations have taken to help prevent

absenteeism in their workplaces.

1. Behavioral Rehearsal

2. Cognitive Restructuring/Reframing

3. Absenteeism Inoculation

4. Systematic Desensitization

5. Anger Management

6. Thought Stopping Techniques

7. Control and Perception of Control

8. Self-Esteem Enhancement

9. Goal Setting

10. Active (Reflective) Listening

11. Strategies for Coping with Derivational Absenteeism (Lack of Stimulation and

Challenge)

12. Modification of Life-style (Nutrition, Sleep, etc.)

171

COPING WITH STRESS: REMEDIAL ACTIONS

Remedial action to control absenteeism falls into three categories:

1. Change your thinking

2. Change your behavior

3. Change your lifestyle

Change Your Thinking

Reframing

Positive thinking

Change Your Behavior

Be Assertive

Get Organized! Time Management

Ventilation

Humor

Diversion and Distraction

Change Your Lifestyle

Diet

Exercise

Drink Water

Pet Therapy

Meditation

Deep Breathing

Nature Walks and Imagery

Hydrotherapy: A Warm, Hot Bath

172

Music Therapy

Sleep

Leisure

Pacing

One sample t-test is applied on 6 variables (see appendix) of rewards and

facilities and the following results are obtained.

Table 5.36

One-Sample Statistics for Absenteeism


SM! 600 3.6525 1.13843 .05117

SM2 600 3.5475 1.08601 .04881

SM3 600 3.4202 1.15289 .05182

SM4 600 3.8465 .91139 .04096

SM5 600 3.6525 .96522 .04338

SM6 600 3.6283 2.57817 .11588


From the above Table it is found that all the mean values are greater than 3

ranging from 3.42 to3.84 with their respective standard deviation. It is observed that

the standard deviation of the 2 variables such as attending parties and Suitable

relaxation are less than 1. This implies that the opinions of the CPCL Employees with

regard to these variables are consistent. But the standard deviation of the other 4

variables is more than 1. Implying that in the opinion of CPCL Employees these

variables differ enormously.

173

Table 5.37

One-Sample Test for Absenteeism

Test Value = 3


t dfSig. (2- Mean Differencetailed) Difference

Lower Upper

SM1 12.752 599 .000 .65253 .5520 .7531

SM2 11.216 599 .000 .54747 .4516 .6434

5M3 8.109 599 .000 .42020 .3184 .5220

SM4 20.664 599 .000 .84646 .7660 .9269

SM5 15.041 599 .000 .65253 .5673 .7378

SM6 5.422 599 .000 .62828 .4006 .8560


From the above table it is clear that the t-test values are significantly greater

than the test value 3 at 5% level of significance. So the CPCL Employees often

practice yoga to remove absenteeism from their minds and they regularly attend

parties to cheer up. The employees of IT sometimes play their favorite sport to

achieve a absenteeism free atmosphere and they also agree that their company screens

the movies to create an optimistic mood. The IT organizations arrange absenteeism

work shops and periodically arrange tours and picnics for the employee's welfare.

Further the IT companies in Chennai city have difference of opinion about the

absenteeism techniques followed in their organisation.

CLASSIFICATION OF CPCL EMPLOYEES BASED ON THE PERCEPTION

OF ABSENTEEISM

In a competitive environment the organisations must be faster, learner, provide

better service, be more efficient, and ultimately be profiTable 1 . Empowered and

proactive workforce is essential for this. The organisation follows different

absenteeism process to empower the CPCL employees' in the organisation. All the

174

CPCL employees do not perceive these processes in the same way. Perception is the

process of acquiring, interpreting, selecting, and organizing information. The

percepts shift on acquiring of new information. As the CPCL employees perceived

notions are influenced by their culture and academic background. Absenteeism is

understood as taking a greater responsibility and authority in the decision-making

process'. But some may feel threatened by absenteeism as they feel that it will expose

their vulnerabilities. The absenteeism process followed by various organisations

ranging from manufacturing to service sector inclusive of software companies, police

machinery and educational institutions is also not similar and varies according to the

organisation or institutions. So the CPCL employees opinion about the absenteeism

process within the organisation and among the organisations will differ according to

their own perception.

CLASSIFICATION OF CPCL EMPLOYEES BASED ON THEIR

PERCEPTION OF ORGANISATIONAL ABSENTEEISM

The CPCL employees have different perception level in understanding the

absenteeism policies of the organisation. The organisations expedite their absenteeism

process through rigorous absenteeism practices. The factor analysis in this study

revealed 13 factors namely trust and openness strategy, developmental policies,

persistent assessment, prospective enhancement, innovative climate, optimistic team

management, goal achieving, rewards and facilities, role of employees, performance

of CPCL employees, career development, versatile training measures and

technological training, are the major determinants in estimating the organisational

absenteeism of CPCL employees. The multivariate tool cluster analysis is applied on

these 13 factors of the organisational absenteeism and the following results are

obtained.

175

Table 5.38

Final Cluster Centers for Factors of Organisation Absenteeism

Clusters2 3

TAO 3.21 3.34 3.62

DP 2.58 3.54 4.16

PA 3.14 3.86 4.39

PE 2.45 3.20 3.85

IC 2.28 3.04 3.82

OTM 2.54 3.37 3.95

GA 3.27 3.61 4.19

RAF 2.88 3.24 3.91

ROW 3.51 3.73 4.16

PWE 3.86 3.49 3.42

CD 2.17 3.03 3.80

VTM 2.97 3.47 3.95

TT 2.54 3.22 3.80


From the above final cluster center Table it is found that these exist 3 types of

CPCL employees based on their perception of organisational absenteeism.

Table: 5.39

Classification of Executives based on their opinion of Factors of OrganisationAbsenteeism

176

The first cluster strong in performance of CPCL employees so it is called as

performance oriented cluster. The second cluster of CPCL employees is strong in

persistent assessment so it is known as assessment oriented cluster. The third cluster is

strong in trust and openness strategy, development policies, goal achieving, and role

of employees. Hence this cluster is named as development oriented cluster. The

frequency distribution of each cluster is presented below in Table.

Table 5.40

Number of Cases in each Cluster for Organisation Absenteeism

L 1 66.000

Clusters 2 214.000I 3 230.000 1

Valid 510.000


From the frequency distribution of the clusters it is ascertained that the first

cluster comprises of 1 2.92%of CPCL employees. These CPCL employees profoundly

believe that their absenteeism can be measured through their knowledge and skills in

performing their jobs.

The second cluster comprises 42.02% of CPCL employees. They have the

opinion that their performance appraisal system and assessment modules in their

organisation must exactly determine their performance in their work.

The third cluster with 45.05 % of CPCL employees with developmental

oriented views and this group of CPCL employees formidably believes that their

absenteeism is directly correlated to the development process in their organisation.

177

CLUSTER CLASSIFICATION AND FACTORS DISCRIMINATING THE

CLUSTERS

The classification of three groups of CPCL employees discriminate the 13

factors of employees absenteeism. The multivariate discriminate analysis by stepwise

approach is applied on three types of cluster and 13 independent factors of

organisational absenteeism. The results are stated as follows.

Table 5.41

Tests of Equality of Group Means for Factors of Organisation Absenteeism

Wilks' Lambda F dfl df2 Sig.

TAO .944 14.642 2 507 .000

DP .525 222.679 2 507 .000

PA .678 117.079 2 507 .000

PE .563 191.326 2 507 .000

IC .451 299.750 2 507 .000

OTM .534 214.260 2 507 .000

GA .703 103.877 2 507 .000

RAF .617 152.798 2 507 .000

ROW .723 94.017 2 507 .000

PWE .975 6.268 2 507 .002

CD .451 298.859 2 507 .000

VTM .744 84.445 2 507 .000

TT .560 193.290 2 507 .000 j


From the above Table it is ascertained that 13 factors of organisational

absenteeism perfectly discriminates the classification of CPCL employees. Among

these 13 factors 6 factors are being identified in the following Table that perfectly

predicts their absenteeism of CPCL employees and classification of them.

178

Table 5.42

Variables Entered/Removed for Factors of Organisation Absenteeism

I Entered Wilks' LambdaStatistic dli df2 d13 Exact F

Step - _______ Statistic dfl d12 Sig.

1 IC .451 1 2 507.000 299.750 2 507.000 .0002 507.000 184.394 4 982.000 .0002 CD .326 2 2 507.000 157.068 6 980.000 .0003 DP .260 3

4 RAF .241 4 2 507.000 126.871 8 978.000 .000

5 PWE .229 5 2 507.000 106.317 10 976.000 .000

6 OTM .223 6 2 507.000 90.821 12 974.000 00

7 PE .218 7 2 507.000 79.181 14 972.000 .000

8 PA .214 8 2 507.000 70.423 16 970.000 .000


From the Table, it is inferred that 8 factors innovative climate, career

development, development policies, rewards and facilities, performance of CPCL

employees, optimistic team management, prospective enhancement, and persistent

assessment are considered as important factors those predict the absenteeism of CPCL

employees. The predicted 8 factors have a Canonical Correlation with three groups

of CPCL employees. The significance of canonical correlation coefficient is presented

in Eigenvalues Table and Wilk' s lamda Table.

Table 5.43

Eigenvalues for Factors of Organisation Absenteeism

Function Eigenvalue %of Variance Cumulative % Canonical Correlation

1 3.411

98.3 98.3 .879

2 .059

1.7 100.0 .237


179

Table 5.44

Wilks' Lambda for Factors of Organisation Absenteeism

Test of Function(s) Wilks' Lambda Chi-square df Sig.

lthrough2 .214 753.126 16 .000

2 .944 28.164 7 .000


From the above Table it can be noted that Canonical Correlation between

groups of CPCL employees and the factors of organisational absenteeism and the

factors of organisational absenteeism are established by two discriminant functions

with Eigenvalues 3.411 and 0.059 respectively. The canonical correlation coefficient

for the discriminant function 0.879 and 0.237 are highly significant.

Table 5.45

Structure Matrix for Factors of Organisation Absenteeism


180

The full structured matrix identified key variables of employees absenteeism

in the organisations in two domains. The first domain consists of career development,

innovative climate, development policies, optimistic team management, prospective

enhancement, technological training, persistent assessment, and role of employees,

versatile training measures and trust and openness strategy.

The second domain comprises only three factors namely rewards and

facilities, goal achieving, and performance of CPCL employees. It is inferred that the

organisation concentrate on these two blocks of employees absenteeism process.

So the 8 factors namely innovative climate, career development, development

policies, rewards and facilities, performance of CPCL employees, optimistic team

management, prospective enhancement, and persistent assessment perfectly

discriminates the 3 groups of CPCL employees. The organisational employee's

absenteeism is highly effective when there is an innovative work climate in every

organisation, the CPCL employees and their career development plays a vital role in

the organisational absenteeism process. The proper commendations and facilities

along with the development policies of the employees in the organisations emerge as

a powerful absenteeism centers. When the CPCL employees are taught to perform

extraordinary and optimistic approaches always give a balanced approach towards

absenteeism. The organisational absenteeism is determined through prospective

infrastructure and management policies to assess the potentiality of CPCL employees.

181


PERCEPTION OF 'IMPACT OF ABSENTEEISM' ON THEM

The multivariate tool cluster analysis is applied on the 14 variables (see

appendix) of impact on individuals specifically self-confidence, capacity of hard

work, ability to communicate effectively, problem solving ability, organized way of

working, capacity for risk bearing, foresight and presence of mind, motivation,

determination, tenacity of purpose, knowledge about work area, innovative creativity,

honesty and emotional stability. The consequence of cluster analysis is presented

below in the Table

Table 5.46

Final Cluster Centers for the Variables of Impact on Individuals


From the above Table it is ascertained that two groups of CPCL employees

exists due to the variables of absenteeism impact on the individuals. The above Table

clearly presents the CPCL employees in the first cluster are moderate and in the

182

second cluster are strong in their opinion about the impact of absenteeism on them.

The frequency distribution of each cluster is presented in Table as follows.

Table 5.47

Number of Cases in each Cluster for Impact on Individuals

Cluster 1 252.000

I 2 258.000

IValid 510.000


From the Table the frequency distribution of the clusters it is ascertained that

the first clusters comprises of 49.49 % of CPCL employees. These CPCL employees

believe moderately that the organisational absenteeism and external factors have an

impact on them. The second cluster comprises of 50.51 % of CPCL employees

strongly believing that the factors of absenteeism make deep inroads on their

personality development. This shows that 50.51 % of CPCL employees profoundly

believe that the organisations are empowering them through absenteeism practices to

replete inward potentiality to accomplish the goals.


PERCEPTION OF 'IMPACT OF ABSENTEEISM' ON ORGANISATION

The multivariate tool cluster analysis is also applied on the 11 variables (see

appendix) of impact on organisation mainly Increase in Reputation Of Organisation,

Increased Productivity, Organisational Efficiency, Appreciable Customer Relation,

Increased Facilities, Flourished Inter-departmental Relationship, Job Involvement,

Constructive Inter Personal Relationship, And Achievement Of Organisational Goals.

The consequence of cluster analysis is presented below in the Table.

183

Table 5.48

Final Cluster Centers for the Variables and Impact on Organisation

Cluster

1 2

10098 3.57 4.32

10099 3.25 4.45

100100 3.24 4.51

00101 3.32 4.42

100102 3.20 4.47

00103 3.32 4.38

100104 3.15 4.43

100105 3.37 4.35

100106 3.44 4.54

100107 3.45 4.49

100108 3.54 4.49


From the above Table it is ascertained that two groups of CPCL employees

exists due to the variables of absenteeism impact on the organisation. The above

• Table clearly presents the CPCL employees in the first cluster are moderate and in the

second cluster are strong in their opinion about the absenteeism impact on

organisation. The frequency distribution of each cluster is presented in Table as

follows.

184

Table 5.49

Number of Cases in each Cluster for Impact on Organisation

Cluster 1 189.000

2 321.000

Valid 510.000


From the Table the frequency distribution of the clusters it is ascertained that

the first clusters comprises of 36.97 % of CPCL employees. These CPCL employees

believe moderately that the organisational absenteeism and external factors have an

impact on organisation. The second cluster comprises of 63.03 % of CPCL

employees strongly believing that the factors of absenteeism have an impact on

organisation.

ASSOCIATION BETWEEN ABSENTEEISM OF CPCL EMPLOYEES IN

THE ORGANISATIONS AND ITS IMPACT ON INDIVIDUALS

Cluster analysis has classified the absenteeism of CPCL employees in

organisations into three clusters and impact on individual CPCL employees into two

clusters as shown in the Table. So in this section correspondence analysis is used to

find the association between these two clusters reveals the following results.

Null Hypothesis: There is no association between clusters of organisation and

clusters of individual impact.

185

Table 5.50

Correspondence analysis for Organization absenteeism and Individual Impact

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 4.493 2 .106

Likelihood Ratio 4.535 2 .104

Linear-by-Linear Association 3.462 1 .063

of Valid Cases 510

From the above chi-square Table it is found that chi-square value is 4.493 and

P value is 0.106 with 2 degree of freedom. This implies that the probability value is

insignificant. So the null hypothesis is accepted at 5% level of significance and

concluded that there is no association between organisational absenteeism of CPCL

employees and its direct impact on CPCL employees. This shows that organisations

are practicing absenteeism only for the benefit of their organisation and not focus on

the absenteeism of the individual CPCL employees.

ASSOCIATION BETWEEN THE CLUSTERS OF ORGANISATION

ABSENTEEISM AND CLUSTERS OF ORGANISATION IMPACT

Cluster analysis has classified the absenteeism of CPCL employees in

organisations into three clusters and its impact on organisation into two clusters as

shown in the Table. The following results are obtained as a consequence by applying

the correspondence analysis to find the association between these two clusters. Null

Hypothesis: There is no association between clusters of organisation absenteeism of

CPCL employees and cluster of organisational impact.

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Table 5.51

Chi-Square Tests for Organization Absenteeism and Organization Impact

Asymp. Sig.Value df

(2-sided)

Pearson Chi-Square 5.034 2 .041

Likelihood Ratio 5.259 2 .072

Linear-by-Linear Association 4.204 1 .040

of Valid Cases 510


From the above chi-square Table it is found that chi-square value is 5.034 and

P value is 0.041 with 2 degree of freedom. This implies that the probability value is

significant. So the null hypothesis is rejected at 5% level of significance. It is

concluded that there is association between organisational absenteeism clusters and its

impact on organisation. This shows that organisational absenteeism is primarily aimed

at improving the organisational efficiency and its productivity. In this chapter on the

basis of the factors of absenteeism process in the organisation and external influence

the CPCL employees are clustered into three groups. And two groups of CPCL

employees are grouped on the basis of absenteeism impact on individuals and

organisations. Microscopic analysis was done for testing the association between

these clusters. In the next chapter the major findings of the study will be summarized

with conclusion and suggestion.

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