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Chapter-IV 133

DATA ANALYSIS AND INTERPRETATION

OF EMPLOYEES’ PERSPECTIVES ON HIGH ATTRITION

Analysis is the key element of any research as it is the reliable way to test the hypotheses

framed by the investigator. This chapter deals with the analysis of the primary data

collected through the administration of the questionnaire. The collected data has been

codified, tabulated and analysis has been conducted using the different statistical tools

such as Reliability Analysis, Factor Analysis, Multiple Regression analysis, and Testing

of the Hypotheses focusing on Analysis of Variance (One-way ANOVA), Chi-Square

test, t-test, pie-charts, averages, percentages graphs and bar diagrams.

The five major analyses conducted in the study focusing on the employee’s perspective

are listed as:

4.1 Reliability Analysis

4.2 Factor Analysis

4.3 Analysis of personal and other factors

4.4 Data Analysis based on Objectives

4.5 Multiple Regression Analysis

The above five analyses are conducted and the results of the different statistical

procedures are discussed below:

4.1 RELIABILITY ANALYSIS

A pilot study has been conducted for a sample of 50 respondents and reliability analysis

(scale- split) is done.

Three measures of reliability are given. The scale consists of 40 items, which measures

the attitude of the respondents on a Likert type five point scale. 50 respondents were

selected for reliability analysis.

Chapter-IV 134

Table: No.4.1 Analysis of Factor Variables

Statistics for Mean S.D No. of items

Part 1 59.9400 9.9476 20

Part 2 59.5200 11.9953 20

Scale 119.4600 20.1982 40

The scale items were divided into two parts (forms) each part containing 20 items

selected randomly. The correlation between two forms was found to be 0.6919, indicating

that the items between the two parts correlates well. Spearman-Brown and Guttman

split-half reliabilities are used to find reliability coefficients of the scale by dividing the

scale items into two halves in some random manner.

Table: No.4.2 Reliability coefficients

No. of Cases 50 No. of Items 40

20 Items in part 1 20 items in part 2

Correlation between forms 0.6919 Equal-length Spearman-Brown 0.8179

Guttman Split-half 0.8095 Unequal-length Spearman-Brown 0.8179

Alpha for part 1 0.7513 Alpha for part 2 0.8676

The correlation between forms is used to find the Spearman Brown reliability and the

variances of sum scale and forms are used to find Guttman reliability. Cronbach's

coefficient alpha (α) uses variances for the k individual items (40) and the variance for

the sum of all items. If there is no true score but only error in the items then the variance

of the sum will be the same as the sum of variances of the individual items. Therefore,

coefficient alpha will be equal to zero. If all items are perfectly reliable and measure the

same thing (true score), then coefficient alpha is equal to 1.

In all, the reliability of the three statistics namely, Spearman-Brown, Guttman and

Cronbach’s alpha show that the reliability of scale constructed for the General

Assessment is between 0.70 and 0.87, which makes the constructed scale fairly reliable.

Therefore the scale reliability is good. Since it was found that the reliability of the scale

was good, factor analysis was performed on all the 400 valid responses.

Chapter-IV 135

4.2 FACTOR ANALYSIS

The set of 40 items included in the Employee Attrition Scale was used to find the

underlying factors in it.

The Factor analysis conducted in this study proceeds in four steps:

Step 1

Correlation matrix for the variables, item 1 to item 40, was analyzed initially for possible

inclusion in Factor Analysis. (The results of the correlation between item1 to item40 are

given in Appendix).

Since one of the goals of the factor analysis is to obtain 'factors' that help explain these

correlations, the variables must be related to each other for the factor model to be

appropriate. A closer examination of the correlation matrix may reveal what are the

variables which do not have any relationship. Usually a correlation value of 0.3 (absolute

value) is taken as sufficient to explain the relation between variables. All the variables

from 1 to 40 have been retained for further analysis. Further, two tests are applied to the

resultant correlation matrix to test whether the relationship among the variables is

significant or not.

Table: No 4.3 KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .823

Bartlett's Test of Sphericity

Approx. Chi-Square 4629.369

df 780

Sig. **

One test is Bartlett's test of sphericity. This is used to test whether the correlation matrix

is an identity matrix. i.e., all the diagonal terms in the matrix are 1 and the off-diagonal

terms in the matrix are 0. In short, it is used to test whether the correlations between all

the variables is 0. The test value (4629.369) and the significance level (P<.01) are given

above.

Chapter-IV 136

With the value of test statistic and the associated significance level is so small, it appears

that the correlation matrix is not an identity matrix, i.e., there exists correlations between

the variables.

Another test is Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy. This test is

based on the correlations and partial correlations of the variables. If the test value, or

KMO measure is closer to 1, then it is good to use factor analysis. If KMO is closer to 0,

then the factor analysis is not a good idea for the variables and data. The value of test

statistic is given above as 0.823 which means the factor analysis for the selected variables

is found to be appropriate to the data.

Step 2

Next step is to determine the method of factor extraction, number of initial factors and the

estimates of factors. Here Principal Components Analysis (PCA) is used to extract

factors. PCA is a method used to transform a set of correlated variables into a set of

uncorrelated variables (here factors) so that the factors are unrelated and the variables

selected for each factor are related. Next PCA is used to extract the number of factors

required to represent the data. The results from principal components analysis are given

below.

To start with, in the correlation matrix, where the variances of all variables are equal to

1.0. Therefore, the total variance in that matrix is equal to the number of variables. In this

study, there are 40 variables (items) each with a variance of 1 then the total variability

that can potentially be extracted is equal to 40 times 1.

Chapter-IV 137

The variance accounted for by successive factors would be summarized as follows:

Table: No.4.4 Total Variance Explained

Component

Initial Eigen values Extraction Sums of Squared Loadings

Variance % of

Variance Cumulative % Variance

% of

Variance

Cumulative

%

1 6.863 17.158 17.158 6.863 17.158 17.158

2 3.835 9.587 26.745 3.835 9.587 26.745

3 2.230 5.576 32.320 2.230 5.576 32.320

4 1.875 4.686 37.007 1.875 4.686 37.007

5 1.612 4.031 41.038 1.612 4.031 41.038

6 1.368 3.419 44.457 1.368 3.419 44.457

7 1.247 3.117 47.574 1.247 3.117 47.574

8 1.109 2.772 50.346 1.109 2.772 50.346

9 1.089 2.722 53.068 1.089 2.722 53.068

10 1.061 2.652 55.720 1.061 2.652 55.720

11 1.027 2.567 58.287 1.027 2.567 58.287

12 1.013 2.533 60.820 1.013 2.533 60.820

13 1.000 2.501 63.320 1.000 2.501 63.320

14 .895 2.238 65.558

15 .850 2.125 67.684

16 .813 2.032 69.716

17 .790 1.975 71.691

18 .745 1.862 73.553

19 .702 1.754 75.307

20 .680 1.701 77.007

21 .678 1.695 78.702

22 .646 1.616 80.318

23 .607 1.517 81.835

24 .589 1.472 83.307

25 .564 1.410 84.717

26 .559 1.398 86.115

27 .528 1.319 87.435

28 .503 1.257 88.691

29 .493 1.232 89.924

30 .471 1.176 91.100

31 .445 1.112 92.212

32 .418 1.044 93.256

33 .403 1.006 94.263

34 .401 1.002 95.265

35 .363 .908 96.173

36 .352 .881 97.054

37 .345 .863 97.917

38 .311 .778 98.695

39 .273 .682 99.377

40 .249 .623 100.000

Chapter-IV 138

In the second column (Initial Eigen values) the column titled ‘Variance, we find the

variance on the new factors that were successively extracted. In the third column, these

values are expressed as a percent of the total variance. As we can see, factor 1 account for

about 17.16 percent of the total variance, factor 2 about 9.6 percent, and so on. As

expected, the sum of the eigen values is equal to the number of variables. The third

column contains the cumulative variance extracted. The variances extracted by the factors

are called the eigen values.

From the measure of how much variance each successive factor extracts we can decide

about the number of factors to retain. Retain only factors with eigen values greater than 1.

In essence, this is like saying that, unless a factor extracts at least as much as the

equivalent of one original variable, we drop it. This criterion is probably the one most

widely used and is followed in this study also. In this study, using the above criterion, 13

factors (principal components) have been retained.

The tableNo.4.5 shown below gives the Component Matrix or Factor Matrix where PCA

extracted 13 factors. These are all coefficients used to express a standardized variable in

terms of the factors. These coefficients are called factor loadings, since they indicate how

much weight is assigned to each factor. Factors with large coefficients (in absolute value)

for a variable are closely related to that variable. For example, Factor 1 is the factor with

largest loading (0.639) for the variable, Statement 33. These are all the correlations

between the factors and the variables, Hence the correlation between Statement 33 and

Factor 1 is 0.639. Thus the factor matrix is obtained. These are the initially obtained

estimates of factors.

Chapter-IV 139

Table No.4.5 Component Matrix

Statements Components

1 2 3 4 5 6 7 8 9 10 11 12 13

33 0.639 -0.100 -0.324 0.008 -0.003 0.095 -0.216 0.019 -0.075 0.001 -0.158 -0.017 0.295

31 0.638 0.113 -0.212 -0.041 -0.055 -0.217 0.043 -0.178 0.027 0.052 0.023 0.003 0.082

27 0.614 0.034 -0.156 0.024 -0.293 0.141 -0.007 -0.077 -0.104 0.013 0.189 -0.006 -0.173

29 0.611 0.107 -0.319 0.145 -0.016 -0.115 0.015 -0.165 -0.056 0.037 -0.062 -0.091 0.285

26 0.581 -0.008 -0.271 0.061 -0.267 0.094 0.107 0.105 0.153 0.178 0.133 -0.143 -0.201

24 0.579 0.032 -0.370 -0.163 -0.022 0.172 0.094 0.068 0.199 0.055 -0.149 -0.094 -0.122

25 0.570 -0.032 -0.321 -0.126 -0.296 0.049 -0.001 -0.004 0.168 0.100 0.072 -0.045 -0.359

19 0.569 -0.109 -0.039 0.187 -0.024 0.258 -0.263 -0.041 -0.094 -0.020 -0.287 0.028 0.112

38 0.561 -0.185 0.253 0.018 -0.001 -0.141 0.023 0.087 0.416 -0.071 0.098 0.226 0.187

32 0.543 -0.099 0.080 0.070 -0.138 0.161 0.118 0.181 0.053 -0.261 0.139 0.087 0.362

36 0.493 0.099 0.317 -0.156 0.024 -0.256 0.166 -0.057 0.339 -0.028 0.074 0.073 0.064

37 0.492 -0.207 0.241 0.108 0.086 -0.047 -0.070 -0.158 0.049 0.270 -0.186 0.379 -0.205

12 0.476 -0.061 -0.065 -0.110 -0.061 -0.158 -0.118 0.274 -0.338 0.078 -0.123 0.060 0.159

22 0.476 -0.133 -0.271 0.120 -0.157 0.062 0.058 -0.119 -0.255 -0.031 0.225 0.294 0.043

35 0.474 -0.133 0.370 -0.076 0.149 0.289 -0.183 -0.079 0.127 -0.078 0.053 -0.231 -0.195

1 0.465 0.099 0.360 0.130 -0.118 -0.121 -0.108 0.357 -0.249 0.225 0.026 -0.129 -0.024

14 0.453 -0.140 0.389 0.096 -0.067 0.344 -0.010 -0.181 0.120 0.157 -0.142 -0.085 0.055

23 0.421 -0.076 0.323 -0.144 -0.001 0.053 0.135 -0.094 -0.247 -0.256 0.268 -0.256 -0.142

20 0.419 0.246 -0.095 -0.190 0.099 -0.315 -0.143 0.105 -0.034 -0.285 -0.133 -0.179 -0.026

17 0.412 0.005 -0.036 -0.246 0.354 0.296 0.367 0.029 -0.120 0.083 0.103 0.057 0.016

34 -0.337 0.285 -0.180 -0.324 -0.257 -0.128 0.208 0.103 0.086 0.303 -0.106 0.252 -0.090

9 0.098 0.690 0.124 -0.017 0.103 0.176 -0.161 0.114 -0.039 -0.013 0.010 0.242 -0.197

4 0.020 0.664 0.002 -0.048 0.001 -0.156 0.029 -0.207 0.060 -0.059 0.056 -0.207 0.000

7 -0.026 0.622 0.035 -0.127 -0.304 0.125 -0.124 0.022 -0.026 -0.084 0.226 -0.034 0.101

21 0.021 0.599 0.155 0.004 0.237 0.238 -0.071 0.132 0.027 -0.040 -0.062 0.198 -0.034

28 0.081 0.585 0.101 -0.100 -0.129 0.122 -0.260 0.068 0.246 -0.139 -0.132 0.094 0.037

3 0.062 0.580 0.051 0.206 0.084 0.059 0.213 -0.125 -0.006 0.011 -0.191 0.080 0.172

8 0.007 0.544 0.195 0.056 0.164 -0.082 0.047 -0.171 0.072 0.355 0.117 -0.244 0.163

40 0.003 -0.511 0.098 -0.352 0.065 -0.182 0.095 0.155 0.173 -0.209 0.089 0.103 0.079

5 0.393 0.445 -0.264 -0.034 0.002 -0.125 0.239 -0.120 0.098 -0.335 -0.253 -0.043 -0.080

16 0.474 -0.106 0.541 0.219 -0.166 -0.007 0.161 -0.006 0.035 0.085 0.028 0.028 0.075

13 -0.087 0.133 -0.176 0.704 0.185 0.013 -0.091 0.092 0.058 -0.114 0.048 -0.014 -0.139

15 -0.039 0.168 -0.326 0.501 0.181 0.023 0.013 0.387 0.253 0.045 0.406 0.030 0.056

10 0.352 0.171 -0.065 -0.397 0.304 0.046 0.021 0.166 -0.152 0.030 0.061 0.233 -0.042

6 0.474 0.106 -0.004 -0.186 0.570 0.028 -0.010 0.119 -0.108 -0.033 0.074 -0.061 -0.107

30 0.289 -0.286 -0.153 0.333 0.449 -0.113 0.332 -0.022 0.041 0.037 -0.200 -0.067 -0.126

39 0.321 0.157 -0.068 -0.090 0.259 -0.366 -0.289 -0.260 -0.051 0.301 0.300 0.037 0.093

18 -0.324 -0.005 -0.176 -0.303 0.073 0.366 0.182 0.199 0.121 0.291 -0.058 -0.285 0.300

11 -0.014 0.400 0.204 0.206 -0.216 -0.004 0.539 0.004 -0.291 -0.053 0.005 0.095 -0.001

2 0.307 0.112 0.252 0.093 -0.141 -0.349 0.034 0.448 -0.024 0.114 -0.238 -0.220 -0.112

Chapter-IV 140

Table No.4.6 Communalities

Items Initial Extraction Items Initial Extraction

Statement-2 1.000 .653 Statement-27 1.000 .592




















The Table No.4.6 titled ‘Communalities’ is given above. This provides communalities for

each variable calculated from the factor matrix described above. The proportion of

variance explained by the common factors is called Communality of the variable. For

example the proportion of variance explained by the 13 factors in the variable, that is the

statement-1 is 0.653. That is 65.3% of the variance in Statement 3 is explained by all the

13 factors. So the communality of the variable Item 1 is 0.653. Further, the table titled

‘Total Variance Explained’ gives the proportion of total variance explained by all the

factors. The column '% of Variance' explains how much variance is attributed to each

factor and the next column is the cumulative percent of variance. So, Factor 1 is the one

which accounts for maximum proportion of total variance. These eigen values are

calculated from the factor matrix described above. Thus for any factor, its corresponding

Chapter-IV 141

highest factor loading will contribute much to that factor. By looking at the last column it

is understood that the 13 factor model explains 63.32% of the variance in the selected

variables.

Step 3

Although the factor matrix (Table No.4.5 titled Component Matrix) obtained in the

extraction phase indicates the relationship between the factors and the individual

variables, it is usually, difficult to identify meaningful factors based on this matrix. Since

the idea of factor analysis is to identify the factors that meaningfully summarize the sets

of closely related variables, the Rotation phase of the factor analysis attempts to transfer

initial matrix into one that is easier to interpret. It is called the rotation of the factor

matrix.

The Rotated Factor Matrix (Table titled Rotated Component Matrix) using Oblique

rotation is given in Table: No 4.7 where each factor identifies itself with a few set of

variables. The variables which identify with each of the factors were sorted in the

decreasing order and are highlighted against each column and row.

Chapter-IV 142

Table No.4.7 Rotated Component Matrix

1 2 3 4 5 6 7 8 9 10 11 12 13

25 0.838 0.028 -0.035 -0.026 -0.003 -0.075 -0.125 0.027 -0.002 -0.035 -0.072 0.043 -0.064

26 0.765 -0.053 0.014 0.154 -0.031 0.087 0.018 0.131 0.047 0.019 0.020 0.000 0.012

27 0.605 0.086 0.152 -0.024 0.025 -0.178 0.124 -0.001 -0.035 0.022 0.080 -0.046 0.141

24 0.578 -0.012 -0.031 0.002 0.181 0.201 -0.110 0.000 0.036 -0.087 -0.260 0.102 0.157

28 0.004 0.707 -0.031 0.007 -0.070 0.036 -0.084 0.021 0.117 -0.011 -0.211 0.072 0.050

9 0.014 0.647 -0.025 0.134 0.305 -0.139 0.096 0.063 -0.125 0.039 -0.039 0.156 -0.110

30 0.008 -0.641 0.064 0.271 0.206 -0.002 0.080 0.044 0.015 -0.025 -0.281 0.285 0.010

7 0.114 0.617 0.016 -0.015 -0.080 0.044 0.157 -0.021 -0.030 0.150 0.030 -0.293 0.010

21 -0.171 0.542 0.012 0.166 0.328 0.035 0.108 0.010 -0.030 -0.003 -0.079 0.177 -0.039

34 0.184 0.148 -0.675 -0.190 0.027 0.127 0.116 0.026 -0.040 0.005 0.027 0.049 -0.252

35 0.175 0.125 0.642 -0.093 0.115 0.040 -0.206 0.043 0.092 -0.008 0.019 0.179 -0.093

23 0.126 -0.078 0.577 -0.211 0.181 -0.145 0.198 0.080 0.038 0.014 -0.010 -0.256 -0.141

15 0.137 0.039 -0.110 0.895 0.055 0.082 -0.045 0.013 0.146 0.057 0.148 -0.181 -0.052

13 -0.032 -0.033 0.110 0.690 -0.142 -0.185 0.030 0.010 -0.171 -0.044 -0.091 0.098 0.009

10 0.027 0.151 -0.110 -0.099 0.659 -0.043 -0.047 0.034 0.047 0.024 0.005 -0.020 0.045

6 -0.020 -0.055 0.246 0.090 0.652 -0.002 -0.143 0.100 -0.012 0.137 -0.144 0.005 0.003

17 0.129 -0.146 0.122 -0.051 0.647 0.209 0.224 -0.126 0.074 0.008 0.033 0.048 0.031

18 0.007 -0.043 -0.108 -0.050 0.123 0.790 -0.057 -0.050 -0.093 -0.012 0.127 -0.112 0.068

11 -0.045 0.006 -0.083 -0.018 0.018 -0.070 0.802 0.123 -0.035 -0.059 -0.053 -0.051 -0.114

3 -0.182 0.193 -0.086 0.087 0.029 0.088 0.421 -0.042 0.005 0.169 -0.265 0.185 0.144

2 0.061 -0.055 -0.071 0.036 -0.093 0.041 0.032 0.792 0.056 -0.050 -0.140 0.018 -0.077

1 0.060 0.070 0.131 0.035 0.055 -0.037 0.101 0.691 -0.006 0.099 0.243 0.011 0.090

38 0.034 0.046 0.016 0.100 -0.007 -0.082 -0.092 0.045 0.780 0.012 0.016 0.124 0.064

36 0.060 0.039 0.027 -0.099 0.047 -0.047 0.048 0.081 0.626 0.213 -0.172 0.080 -0.161

32 0.031 0.110 0.171 0.113 0.054 0.043 0.196 0.012 0.500 -0.195 0.053 -0.190 0.389

40 -0.126 -0.214 -0.051 -0.160 0.129 -0.022 -0.233 -0.038 0.462 -0.241 0.018 -0.194 -0.140

16 0.013 -0.046 0.244 -0.058 -0.131 -0.060 0.311 0.266 0.393 0.041 0.180 0.219 0.014

39 -0.006 -0.055 -0.054 0.000 0.162 -0.220 -0.251 -0.023 0.059 0.736 0.118 -0.015 0.095

8 -0.099 0.096 0.062 0.057 -0.017 0.274 0.149 0.094 -0.017 0.649 -0.006 0.067 -0.099

4 0.027 0.258 0.051 -0.017 -0.072 0.024 0.147 -0.023 -0.069 0.402 -0.356 -0.137 -0.129

31 0.304 -0.100 -0.069 -0.070 0.036 -0.126 0.041 0.006 0.181 0.304 -0.206 -0.009 0.263

5 0.201 0.078 -0.049 -0.025 0.063 -0.088 0.214 -0.063 0.052 -0.037 -0.707 -0.031 0.086

20 0.010 0.092 0.074 -0.076 0.127 -0.141 -0.179 0.265 0.036 0.065 -0.487 -0.221 0.131

37 0.109 -0.083 -0.058 -0.122 0.116 -0.312 -0.028 0.074 0.178 0.060 0.143 0.624 0.036

14 0.122 0.046 0.393 -0.178 -0.104 0.171 0.087 0.026 0.169 0.024 0.133 0.411 0.160

33 0.152 -0.010 0.027 -0.013 0.075 0.052 -0.162 0.037 0.045 0.030 -0.081 0.013 0.709

19 0.085 0.096 0.219 -0.033 -0.019 -0.043 -0.077 0.071 -0.054 -0.117 -0.027 0.286 0.588

29 0.173 -0.159 -0.014 0.044 -0.037 -0.002 0.091 -0.001 0.078 0.295 -0.222 -0.032 0.550

12 -0.004 -0.040 -0.141 -0.134 0.207 -0.089 -0.015 0.420 -0.022 -0.024 0.071 -0.096 0.443

22 0.296 -0.082 -0.058 0.045 0.138 -0.337 0.222 -0.188 0.045 -0.007 0.192 -0.067 0.348

Chapter-IV 143

Step 4

Normally, from the factor results arrived above, factor score coefficients can be

calculated for all variables (since each factor is a linear combination of all variables)

which are then used to calculate the factor scores for each individual. Since PCA was

used in extraction of initial factors, all methods will result in estimating same factor score

coefficients. However, for the study, original values of the variables were retained for

further analysis and factor scores were thus obtained by adding the values (ratings given

by the respondents) of the respective variables for that particular factor, for each

respondent.

Result

Thus the 40 variables considered in the primary data were reduced to 13 factors model

and each factor was given a name which associated with the corresponding variables. The

factor names and descriptions of the factors are given in the following Table No.4.8.

Table No.4.8. 13 Factors Model

Item

No. Statement Factor Name

25 Unclear performance goals causes high attrition

1. Lack of integration and

goal setting

26 Missing of personal touch in the organization leads to

high attrition

27 Lack of scientific goal setting process causes high

attrition

24 Lack of integration of people in the company leads to

high attrition

28 This company’s location is good and it makes my work

easier

2. Work atmosphere

09 The culture of this company is such that it creates a very

positive work environment

30 Salary hike in every six months can be a better option to

reduce high attrition

07 I feel that I get self-respect and dignity in this

organization

21 This company’s infrastructure is good and makes my

work easier

34 Introduction of family benefit plans will reduce high

attrition

3. Work and family conflict 35 Social isolation is a major cause for high attrition

23 Family issues and influence of family members leads to

high attrition

Chapter-IV 144

15 My organization provide hygiene and timely food to the

employees 4. Food and relaxation

13 This organization conduct stress reduction programs like

yoga, meditation etc.

10 This company is not very open to ideas and suggestions

given by employees 5. Motivation and

appreciation 06 This organization does not conduct effective

motivational programs

17 Internal job rotation will lead to high attrition

18 “Work from home option” will reduce high employee

attrition 6. Work from home

11 This organization provides sufficient holidays for

employees 7. Dissatisfaction with

salary and perks 03 I am paid enough for the work I do in this company

02 Odd working hours causes high employee attrition 8. Maximum hours worked/

abnormal working hours 01 Lengthy working hours leads to high attrition

38 Absence of counseling and medical health checkups

causes high attrition 9. Occupational health

problems 36

Lack of spiritual sessions organized in the company

leads to high attrition

32 Eye fatigueness and vision deterioration leads to high

attrition

40

This organization has a logical, bias free promotion

policy

16 Sleeping disorders causes high employee attrition

39 This organization do not provide labour welfare

measures like housing schemes, health club etc.

10. Labour welfare and

corporate governance

08 This company has high standards of corporate

governance

04 I believe that the company’s leadership is doing what is

required for its growth

31 Low perceived equity of rewards system leads to high

attrition

05 I am not satisfied with the kind of salary hikes I get 11. Dissatisfaction with

rewards and hikes 20 Reward systems in this organization are not transparent

37 Lack of talent management in the organization leads to

high attrition 12. Miscellaneous-lack of

transportation and talent 14

Lack of safe and good transportation facility leads to

high attrition

33 Lack of communication around total value causes high

attrition

13. Lack of work ethics

19 Lack of work value and ethics causes high attrition

29 Absence of performance-based bonus causes high

attrition

12 Constant pull of higher salaries leads to high attrition

22 Mismatching of job expectations creates the problem of

attrition

Chapter-IV 145

4.3 ANALYSIS OF THE PERSONAL AND OTHER FACTORS

The personal factors included in the study are gender, location, age, designation,

qualification, area of work, salary, and global position.

An analysis of the respondents based on gender, location, age, designation, qualification,

area of work, salary, and global position have been conducted and the findings are

discussed as follows:

4.3.1 Gender-wise distribution of the sample: Analysis of the respondents based on

the gender is conducted and the results are given as follows:

Table No.4.9 Gender-wise distribution of the sample

Gender No. of respondents Percentage of the total

sample

Male 236 59

Female 164 41

Total 400 100 Source: Survey Data

Table No.4.9 indicates the classification of data according to their gender as male and

female. There are 236 male respondents and 164 female respondents included in the

sample.

Chart No.4.1 Percentage distribution of the gender

59% 41%

0% 50% 100%

Percentage

Male

Female

Gen

der

Chapter-IV 146

The Chart No.4.1 reveals that there are 59% male respondents and 41% female

respondents in the selected sample.

Inference: From the above chart, it is inferred that approximately 60% of the respondents

selected for the study are male and nearly 40% of the respondents are female. It shows

that the selected number of male and female respondents in the study is moderate.

4.3.2 Location-wise distribution of the sample: Analysis of the respondents based on

location is conducted and the results are given as follows:

Table: No.4.10 Location wise distribution of the respondents

Location No. Percentage

Karnataka 285 71.3

Kerala 115 28.7

Total 400 100

Source: Survey Data

Table 4.10 shows the location-wise distribution of the sample. There are 285 respondents

from Karnataka state and 115 respondents from Kerala state in the sample. Also the

percentages of the two groups are tabulated along with their numbers.

Chart No.4.2 Percentage-wise distribution of the location

71.3%

28.7%

0%

10%

20%

30%

40%

50%

60%

70%

80%

Perc

en

tag

e

Karnataka Kerala

Location

Karnataka

Kerala

Chapter-IV 147

The chart No.4.2 shows that 71.3% of the respondents in the sample belong to Karnataka

State and 28.7% of the respondents are from Kerala.

Inference: From the percentage distribution, it is inferred that approximately 70% of the

respondents are from Karnataka and approximately 30% of the respondents are from

Kerala which shows that the selection of respondents from Karnataka and Kerala are

moderate for the present study.

4.3.3 Global position-wise distribution of the sample: Analysis of the respondents

based on global position is conducted and the results are given as follows:

Table No.4.11 Distribution of the sample based on global position (national/

multinational)

Global Position Number of respondents Percentage

National 212 53

Multinational 188 47

Total 400 100

Source: Survey Data

Table No.4.11 shows the grouping of the respondents under national and multinational

BPO employees. 212 respondents belong to national BPO’s and 188 respondents belong

to multinational BPO companies.

Chart No. 4.3: Percentage wise distribution of Global position

53%47%

0%

10%

20%

30%

40%

50%

60%

Perc

en

tag

e

National Multinational

Global Position

National

Multinational

Chapter-IV 148

Chart No.4.3 indicates the grouping of the respondents in the sample under national and

multinational BPO employees. It shows that 53% of the sample belongs to national BPO

employees and 47% of the sample belongs to multinational BPO employees.

Inference: From the chart No.4.3 , it is inferred that 53% of the respondents are selected

from national BPO’s and 47% of the respondents are selected from multinational BPO’s

which shows that there is almost equal representation from national and multinational

BPO’s.

4.3.4 Age-wise distribution of the sample: Analysis of the respondents based on age is

conducted and the results are given as follows:

Table: No.4.12 Age-wise distribution of the sample Age No. of respondents Percentage of the total sample

< 18 yrs. 04 01.0

18 – 20 yrs. 27 06.8

21 – 25 yrs. 260 65.0

Above 25 yrs. 109 27.3

Total 400 100

Source: Survey data

Table No. 4.12 shows the grouping of the respondents under different age groups as ’less

than 18 years’ group, 18 – 20 years, 21 – 25 years and’ Above 25 years group.260

respondents belong to 21-25 years group, 109 respondents belong to above 25 years

group, 27 respondents under 18-20 years group and 4 respondents belong to less than 18

years group.

Chart No 4.4 Percentage distributions of the age groups

27.30%1%

65%

6.80%

< 18 yrs.

18 – 20 yrs.

21 – 25 yrs.

Above 25 yrs.

Chapter-IV 149

From the chart No. 4. 4, it is found that 65% of the respondents fall in the age group of

‘21-25 years’ and 27.3% of the respondents fall in ‘above 25 years’ category. Also,

06.8% of the respondents belong to ‘18-20 years’ group and 01% of the respondents

belong to ‘less than 18 years’ category.

Inference: From the chart it is observed that among the respondents 65% of them are in

the age group of ‘21-25 years’ and 27.3% of the respondents are above 25 years. Also,

06.8% of the respondents are in 18-20 years’ group and only 01% of the respondents are

less than 18 years. It is found that majority of the respondents (65%) are in the entry level

age group of ‘21-25 years’ which accounted for the highest employee attrition in BPO

sector.

4.3.5 Experience-wise distribution of the sample: Analysis of the respondents based on

experience groups is done and the results are given as follows:

Table: No. 4.13 Distribution of Experience groups in the organization

Experience Groups No. of Respondents Percentage of the total

sample

< 6 months 39 9.8

6 months – 1 year 80 20.0

1 – 2 years 191 47.8

3 – 5 years 78 19.5

> 5 years 12 3.0

Total 400 100

Source: Survey Data

Table No. 4.13 gives the classification of the respondents as per their experience in the

present organization. Five groups have been formed to include the experience groups

ranging from ‘less than 6 months to above 5 years’ groups.

Chart: No.4.5 Percentage distribution of Experience groups

9.8%

20.0%

47.8%

19.5%

3.0%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Pe

rce

nta

ge

< 6 months 6 months – 1 year 1 – 2 years 3 – 5 years > 5 years

Experience

Chapter-IV 150

Chart No. 4.5 indicates that 47.8% of the respondents belong to ‘1-2 years’ group and

20% of the respondents belong to ‘6 months – 1 year’ group. Also 19.5% of the sample

belong to ‘3-5 years’ category, 09.8% of the sample belong to ‘less than 6 months’ group

and 03% of the sample fall in ‘above 5 years’ group.

Inference: It is observed that among the respondents, approximately half of them are in

the experience group of ‘1-2 years’ and an equal number of them are either in ‘6 months

– 1 year’ group, or ‘3-5 years’ experience group.

4.3.6 Salary-wise distribution of the sample: Analysis of the respondents based on

salary groups is done and the results are given as follows:

Table No. 4.14 Salary-wise distribution of the respondents Salary groups (per month) No. of respondents Percentage

<Rs. 5,000 07 1.8

Rs. 5,000 – 10,000 82 20.5

Rs. 10,000 – 15,000 160 40.0

Rs. 15,000 – 20,000 94 23.5

Above Rs. 20,000 57 14.2

Total 400 100

Source: Survey Data

Table No. 4.14 exhibits classification of respondents as per their salary per month. There

are five salary groups included in the sample as ‘less than Rs. 5000’,’Rs.5000-10000

‘group, ’Rs.10000-15000 ‘group, ‘Rs. 15,000 – 20,000’and above Rs. 20,000 group.

Chart No. 4.6: Percentage-wise distribution of salary groups

1.8%

20.5%

40%

23.5%

14.2%

0% 5% 10% 15% 20% 25% 30% 35% 40%

Percentage

< Rs. 5,000 Rs. 5,000 – 10,000 Rs. 10,000 – 15,000 Rs. 15,000 – 20,000 Above Rs. 20,000

Sala

ry

Chapter-IV 151

Inference: From the chart, it is observed that among the respondents 40% of them are in

the salary group of ‘Rs.10, 000–15,000’ and 23.5% of the respondents are in ‘Rs.15, 000–

20,000’ salary group. Also 20.5% of the samples are in Rs. 5,000 – 10,000’ salary group,

14.2% of the samples are in ‘above Rs. 20,000’ group and 1.8% of the samples fall in

‘less than Rs. 5,000’ category. Thus analysis shows that majority of the respondents

salary is above Rs. 10000 which accounts to higher salary drawers group.

4.3.7 Designation-wise distribution of the sample: Analysis of the respondents based

on designation groups is done and the results are given as follows:

Table No.4.15 Designation-wise distribution of the sample

Designation No. Percentage

Process Analyst 246 61.5

Senior Process Analyst 95 23.8

Team Leader 34 8.5

Supervisor 15 3.8

Manager 10 2.5

Total 400 100

Source: Survey Data

Table: No. 4.15 gives an account of the designation groups and their numbers and

percentages in the sample. The groups included are process analyst, senior process

analyst, team leader, supervisor and manager. The process analysts group has 246

respondents, senior process analyst group has 95 respondents, team leader has 34

respondents, supervisor has 15 numbers and manager has 10 respondents.

Chart: No.4.7 Percentage distribution of Designation groups

61.50%

23.80%

8.50%3.80%

2.50%

0%

20%

40%

60%

80%

Pe

rcen

tag

e

Process Analyst

Senior Process Analyst

Team Leader

Supervisor

Manager

Chapter-IV 152

Inference: From the chart, it is observed that among the respondents 61.5% of them are

in the designation group of ‘process analyst’ (entry level), and from the total sample

23.8% of the sample are in ‘senior-process analyst’ group. Also, 08.5% of the sample

belongs to ‘team leader’ category, 03.8% of the sample belong to ‘supervisor’ group and

02.5% of the sample belong to ‘manager’ category. Thus it is concluded that from the

total sample, majority (61.5%) of them are from ‘process analyst’ (entry level) group,

where employee attrition is highest which further justifies the sample selection.

4.3.8 Qualification-wise distribution of the sample: Analysis of the respondents based

on qualification groups is done and the results are given as follows:

Table: No.4.16 Qualification wise distribution of the sample

Qualification No. of respondents Percentage

ITI/Diploma 15 3.8

Undergraduate 21 5.3

Graduate 217 54.3

Postgraduate 147 36.8

Total 400 100

Source: Survey Data

Table No. 4.16 gives an account of the qualification groups, the number of respondents in

each group and their percentage distribution. The four qualification groups included are

ITI/Diploma, undergraduate, graduate and postgraduate. The ‘graduate’ group has 217

respondents, ‘post graduate’ group has 147 respondents, and under graduate group have

21 respondents and ITI/Diploma group have 15 respondents.

Chart: No. 4.8 Percentage distribution of Qualification groups

3.80%

5.30%

54.30%

36.80%

0% 10% 20% 30% 40% 50% 60%

Percentage

ITI/Diploma

Undergraduate

Graduate

Postgraduate

Qu

ali

ficati

on

Chapter-IV 153

Inference: From chart No. 4.8 it is observed that among the respondents 54.3 % of them

are in graduate group and from the total sample, 36.8 % of the sample is in postgraduate

group. Also, 05.3% of the sample belongs to’ under graduate group and 03.8% of the

sample belong to ‘ITI/Diploma’ group. Thus it is concluded that from the total sample

more than half of them (54.3%) are from graduate group. Also 36.8 %of the respondents

are in ‘postgraduate group. Therefore minimum qualification of majority of the

respondents is graduation which implies BPO jobs seekers must start their search after

graduation.

4.3.9 Distribution of the sample as per area of work groups: Analysis of the

respondents based on area of work groups is done and the results are given as follows:

Table: No. 4.17 Distribution of the sample as per Area of work groups

Area of work Number of respondents Percentage

Financial Accounting 126 31.5

Customer Services 125 31.3

Procurement 14 3.5

Human Resources 41 10.3

Application Process 67 16.8

Others 27 6.8

Total 400 100

Source: Survey Data

Table No. 4.17 gives the grouping of the respondents as per their area of work groups.

The six areas of work groups included in the sample are Financial Accounting, Customer

Services, and Procurement, Human Resources, Application Process and Others. The

number of respondents in each category is tabulated with their percentages.

Chart: No. 4.9 Percentage distribution of Area of work groups

31.5%

31.3%

3.5%

10.3%

16.8%

6.8%

0% 5% 10% 15% 20% 25% 30% 35%

Percentage

Financial Accounting

Customer Services

Procurement

Human Resource

Application Process

Others

Are

a o

f w

ork

Chapter-IV 154

Inference:

From chart No.4.9, it is observed that among the respondents31.5 % of them are in

‘financial accounting’ group and from the total sample 31.3% of the sample is in

‘customer services’ group. Also 16.8 % of the sample is from application processes

group, 10.3% of the sample is in human resource group, 06.8% belong to ‘Others ’group

and 03.5% of the respondents is in ‘procurement’ category. Thus it is concluded that from

the total sample, majority (63%) of the respondents are chosen from the two important

areas namely financial accounting and customer services groups.

4.3.10 Ranking of reasons for stress in the sample: Analysis of the reasons based on

the ranks they scored in the survey is done and the results are given as follows:

Table No.4.18 Ranking of reasons for stress

Reasons Rank

Long working hours 3.25

Working timings 3.75

Repetitive nature of work 4.06

Pressure to perform on metrics 4.80

Social isolation 6.24

Lack of quality of sleep 4.57

Lack of transportation 5.54

Stress due to verbal abuse 6.12

Travel time 6.67

Source: Survey Data

Table No.4.18 gives the list of the reasons for stress to employees in BPO sector with

their corresponding ranking.

Chart No.10: Ranking of reasons for stress to BPO employees

3.253.75 4.06

4.8

6.24

4.57

5.546.12

6.67

0

1

2

3

4

5

6

7

Ra

nk

Long w orking hours

Work timings

Repetitive nature of w ork

Pressure to perform on metrics

Social isolation

Lack of quality of sleep

Lack of transportation

Stress due to verbal abuse

Travel time

Chart No.4.10 shows that the reason ‘long working hours’ holds the rank – 1, ‘work

timings’ is given rank – 2 followed by the ‘repetitive nature of work in the 3rd

rank

position. The other ranks given by the respondents are 4th

rank ‘pressure to perform on

Reasons

Chapter-IV 155

metrics’, 5th

rank – social isolation, 6th

rank – lack of quality sleep, 7th

rank – lack of safe

and good transportation facility, 8th

rank – stress due to verbal abuse and 9th

rank is travel

time of respondents.

Inference: It is inferred that ‘long working hours’ is the primary reason for stress to BPO

employees. Work timing is the second reason identified for stress to BPO employees. The

third reason for stress is ‘repetitive nature of work’ .The fourth reason identified for stress

is ‘pressure to perform on metrics’. Social isolation stands as the fifth reason. The sixth

reason identified is ‘lack of quality sleep’. Lack of safe and good transportation’ occupies

the seventh position, eighth reason has been found as ‘stress due to verbal abuse’ and

finally ‘travel time of respondents’ is identified as the ninth reason for stress to BPO

employee.

4.3.11 Distribution of the respondents’ undergone training: Analysis of the

respondents based on number of respondents undergone training and the results are given

as follows:

Table No.4.19 Distribution of respondents’ undergone training

Opinion Number of respondents Percentage

Yes 366 91.5

No 34 8.5

Total 400 100.0

Source: Survey Data

Table No.4.19 gives an account of number of respondents’ undergone training and their

percentage. It also gives the number of respondents who have not undergone training.

Chart No: 4.11 Percentage distribution of Respondents undergone training

91.50% 8.50%

85% 90% 95% 100%

Opinion

Pe

rce

nta

ge

Yes

No

Chapter-IV 156

Chart No. 4.11 indicates that 91.5% of the respondents have undergone training and

08.5% of the respondents have not undergone training.

Inference: It is found that majority of the respondents have undergone training programs.

4.3.12 Distribution of number of training programs undergone: Analysis of the

respondents based on number of trainings undergone and the results are given as follows:

Table: No.4.20 Distribution of number of training programs undergone

Training groups No. of Respondents Percentage

1 - 2 143 35.8

3 – 4 196 48.9

5 & Above 61 15.3

Total 400 100.0

Source: Survey Data

Table No.4.20 shows the distribution of number of training programs undergone by

respondents in the sample. It gives three numbers of training groups, the number of

respondents in each category and their percentage.

Chart: No.4.12 Percentage of training program undergone by respondents

35.80%

48.90%

15.30%

1 - 2

3 – 4

5 & Above

Inference:

From the chart, it is found that15.3% of the respondents have undergone more than five

training programs and 48.9% of the respondents have undergone 3-4 training programs.

Also 35.8% of the respondents have undergone 1-2 training programs. Thus it is observed

that nearly 84% of the respondents have undergone at least one training program, which

Chapter-IV 157

shows that the BPO companies have made training programs mandatory for their

employees.

4.3.13 Rating of the training programs undergone: Rating of the training programs

effectiveness has been done and the results are given as follows:

Table: No.4.21 Rating of training program effectiveness

Grade/Opinion Number of respondents Percentage

Poor 10 2.7

Average 99 27.0

Good 232 63.4

Excellent 25 6.8

Total 400 100.0

Source: Survey Data

Table No.4.21 gives an account of the rating of training programs effectiveness using the

four grades namely excellent, good, average and poor. The number of respondents in

each group has been tabulated with the percentage values.

Chart No.4.13 Percentage distribution of rating of training program effectiveness

2.70%

27.0%

63.40%

6.80%

0%

10%

20%

30%

40%

50%

60%

70%

Perc

en

tag

e

Poor Average Good Excellent

Opinion

Inference: From the survey it is found that 63.4% of the respondents have rated the

training program effectiveness as ‘Good’. 27% of the respondents have rated the training

program effectiveness as ‘Average’ and 02.7% of the respondents rated it as ‘Poor’.

Chapter-IV 158

Since only 63 % of the respondents are happy with the effectiveness of the training

programs, the quality of training programs is to be improved.

4.3.14 Distribution of maximum number of worked: Analysis of the respondents

based on maximum number of hours worked is done and the results are given as follows:

Table No.4.22 Distribution of maximum number of hours worked

Number of hours –

groups Number of respondents Percentage

0 – 8 hrs. 80 20.0

8 – 12 hrs. 243 60.8

Above 12 hrs. 77 19.3

Total 400 100.0

Source: Survey Data

Table No.4.22 shows the distribution of number of hours worked by employees

(respondents) and their percentage. There are 3 ‘number of hours worked’ groups as “0 –

8 hours”, “8-12 hours “and “above 12 hours” group.

Chart: No.4.14 Percentage distribution of the maximum number of hours worked

20.0%

60.80%

19.30%

0%

10%

20%

30%

40%

50%

60%

70%

Pe

rce

nta

ge

0 – 8 hrs. 8 – 12 hrs. Above 12 hrs.

No. of hours

0 – 8 hrs.

8 – 12 hrs.

Above 12 hrs.

Inference: From the chart, it is found that19.3% of the respondents have worked more

than 12 hours and 60.8% of the respondents have worked for a period of ‘8-12 hours’.

Also 20% of the respondents have worked for a period of ‘0–8 hours’.

Chapter-IV 159

Therefore it can be found that maximum number of respondents has worked for a period

of ‘8-12 hours’. Therefore on an average the maximum number of hours worked by a

BPO employee is more.

4.3.15 Distribution of opinion on level of satisfaction for strength factors: Analysis of

the respondents based on opinion on level of satisfaction for the strength factors: high

standards of corporate governance, exciting growth opportunities and company’s work

value and ethics is done and the results are given as follows:

Table No.4.23 Distribution of opinion on level of satisfaction for strength factors

Strength factors

Opinion

Very

strongly

agree

Agree Partially

agree Disagree TOTAL

High standards of

corporate

governance

Number of

respondents 101 218 71 10 400

% 25.3 54.5 17.8 2.4 100.0

Exciting growth

opportunities

Number of

respondents 63 153 152 32 400

% 15.8 38.3 38.0 7.9 100.0

Company’s work

value and ethics

Number of

respondents 108 197 84 11 400

% 27.0 49.3 21.0 2.7 100.0

Source: Survey Data

Table No. 4.23 shows the distribution of opinion on level of satisfaction for the strength

factors: high standards of corporate governance, exciting growth opportunities and

company’s work value and ethics.

Chart No.4.15: Percentage distribution of level of satisfaction for strength factors

25.3%

54.5%

17.8%

2.5%

15.8%

38.3% 38.0%

8.0%

27.0%

49.3%

21.0%

2.8%

0%

10%

20%

30%

40%

50%

60%

Pe

rce

nta

ge

High standards of

corporate governance

Exciting growth

opportunities

Company’s work value and

ethics

Strength Factors

Chapter-IV 160

Chart No.4.15 indicates the percentage distribution of opinion on the level of satisfaction

for each strength factor.

For the factor high standards of corporate governance, it indicates that 25.3% of the

respondents very strongly agree that there are high standards of corporate governance and

54.5% of the respondents agree that there are high standards of corporate governance

For the factor, exciting growth opportunities, the chart indicates that 15.8% of the

respondents very strongly agree that there are exciting growth opportunities and 38.3% of

the respondents agree that there are exciting growth opportunities. Also, 38% of the

respondents partially agree that there are exciting growth opportunities. For the factor,

company’s work value and ethics, the chart shows that 27% of the respondents very

strongly agree that there is respect for company’s work value and ethics and 49.3% of the

respondents agree that there is respect for company’s work value and ethics.

Inference:

From the opinion on ‘high standards of corporate governance’, it is found that overall

97.6% of the respondents agree that there are high standards of corporate governance in

the organizations where they were working. Again for the same factor only 2.4% of the

respondents have disagreed on there is ‘high standards of corporate governance’ in the

organization for which they are working.

From the opinion on exciting growth opportunities, it is observed that overall 92.1% of

the respondents agree that there are exciting growth opportunities in the organizations

where they are working. Again for the same factor only 7.9% of the respondents have

disagreed on ‘there are exciting growth opportunities’ in the organization for which they

are working.

From the opinion on company’s work value and ethics, it is observed that overall 97.3%

of the respondents agree that there is work value and ethics in the organizations where

they are working. Again for the same factor only 2.7% of the respondents have disagreed

on ‘there is work value and ethics’ in the organization for which they are working.

Chapter-IV 161

4.3.16 Rating of Human Resource Management Practices:

Rating of the Human Resource Management Practices has been conducted and the results

are given as follows:

Table No.4.24 Rating of Human Resource Management Practices

Grade/Opinion Number of respondents Percentage of the total

sample

Excellent 32 8.0

Good 180 45.0

Average 129 32.2

Satisfactory 43 10.8

Poor 16 4.0

Total 400 100.0

Source: Survey Data

Table No. 4.24 gives an account of the human resource management practices rating

using the grades: Excellent, Good, Average, Satisfactory and Poor. The group ‘Excellent’

has 32 respondents, ‘Good’ has 180 respondents, ‘Average’ has 129 respondents,

’Satisfactory’ has 43 respondents and the ‘Poor’ group has 16 respondents.

Chart No. 4.16 Percentage distribution of human resource management practices

rating

8.0%

45.0%

32.30%

10.80%

4.0%

0%

10%

20%

30%

40%

50%

Pe

rce

nta

ge

Excellent Good Average Satisfactory Poor

Opinion

Excellent

Good

Average

Satisfactory

Poor

Chart No. 4.16 shows that 45% of the respondents belong to the grade ‘Good’, 32.3% of

the respondents belong to ‘Average’ group, 10.8% of the respondents belong to the

‘satisfactory’ group, 08% of the sample belong to the ‘Excellent’ group and 04% of the

sample belong to the ‘Poor’ group.

Chapter-IV 162

Inference: From the HRM practices rating, it is found that 08% of the respondents have

rated HRM practices of their organizations as ‘Excellent’ and 45% of the respondents has

rated HRM practices of their organizations as ‘Good’. Therefore the HRM practices of

the organizations have to improve for reducing high employee attrition.

4.4 DATA ANALYSIS BASED ON OBJECTIVES

This section includes the testing of the hypotheses that were framed based on the set

objectives and the results obtained. The analysis of the primary data obtained from

questionnaire is conducted based on the set objectives and framed hypotheses and the

results are summarized as follows:

4.4.1 Objective: Variation in factors among different BPO areas

The following hypotheses were framed to study the association between different BPO

areas and proposed attrition factors : lack of integration and goal setting, motivation and

appreciation, work atmosphere, labor welfare and corporate governance, maximum

number of hours worked, dissatisfaction with rewards and hikes, human resource

management practices, dissatisfaction with salary and perks, food and relaxation, lack of

transportation and talent, work and family conflict, work from home and lack of work

ethics. In each combination of BPO area and attrition factor, suitable hypotheses were

framed and testing (ANOVA) of the hypotheses were done and the results are discussed

as given below:

Chapter-IV 163

Hypothesis 1.1: Lack of Integration and Goal Setting Vs BPO areas

H0:1.1. There is no significant difference among the BPO areas in the average scores

of lack of integration and goal setting.

H1:1.1. There is significant difference among the BPO areas in the average scores of

lack of integration and goal setting.

Table: No. 4.25 Lack of Integration and Goal Setting Vs BPO areas

Lack of integration and goal setting

Mean S.D No.

Area of work

Financial Accounting 12.52 3.22 126

Customer Services 11.75 3.03 125

Procurement 12.43 2.59 14

Human Resource 12.24 3.01 41

Application Process 12.70 3.18 67

Others 10.56 4.10 27

Total 12.15 3.21 400

Table: No.4.26 ANOVA for Lack of integration and goal setting

Sum of

Squares df

Mean

Square F Sig.

Between Groups 127.871 5 25.574 2.526 *

Within Groups 3988.427 394 10.123

Total 4116.298 399

Result: One way ANOVA was applied to find whether there is significant difference

among the area of work groups in the average lack of integration and goal setting scores.

Since the calculated F-ratio value 2.526 is higher than the table value 2.237 at 5% level of

significance, we reject the null hypothesis.

Hence, it is inferred that there is significant difference among the area of work groups in

the average lack of integration and goal setting scores.

Chapter-IV 164

Hypothesis 1.2: Motivation and Appreciation Vs BPO areas


of motivation and appreciation.


motivation and appreciation.

Table No. 4.27 Motivation and Appreciation Vs BPO areas

Motivation and appreciation

Mean S.D No.

Area of

work






Others 8.00 3.35 27

Total 7.95 2.57 400

Table No. 4.28 ANOVA for Motivation and appreciation

Sum of

Squares df Mean Square F Sig.

Between Groups 45.426 5 9.085 1.381 NS

Within Groups 2591.574 394 6.578

Total 2637.000 399

Result

One way ANOVA was applied to find whether there is significant difference among the

area of work groups in the average motivation and appreciation scores.

Since the calculated F-ratio value 1.381 is lower than the table value 2.237 at 5% level of

significance, we accept the null hypothesis.

Hence, it is inferred that there is no significant difference among the area of work groups

in the average motivation and appreciation scores.

Chapter-IV 165

Hypothesis 1.3: Work Atmosphere Vs BPO areas


of work atmosphere.


work atmosphere.

Table No.4.29 Work Atmosphere Vs BPO areas

Work atmosphere

Mean S.D No.

Area of work






Others 14.00 3.67 27

Total 14.57 3.01 400

Table No. 4.30 ANOVA for Work atmosphere

Sum of

Squares df

Mean

Square F Sig.

Between Groups 99.971 5 19.994 2.246 *

Within Groups 3508.207 394 8.904

Total 3608.178 399

Result


area of work groups in the average work atmosphere scores.




the average work atmosphere scores.

Chapter-IV 166

Hypothesis 1.4: Labor welfare and corporate governance Vs BPO areas


of labor welfare and corporate governance.


labor welfare and corporate governance.

Table No. 4.31 Labor welfare and corporate governance Vs BPO areas

Labour welfare and corporate governance

Mean S.D No.

Area of

work






Others 11.22 3.03 27

Total 11.76 2.70 400

Table No. 4.32 ANOVA for Labor welfare and corporate governance

Sum of Squares df Mean

Square F Sig.

Between Groups 159.727 5 31.945 4.591 **

Within Groups 2741.750 394 6.959

Total 2901.477 399

Result


area of work groups in the average labour welfare and corporate governance scores.




the average labour welfare and corporate governance scores.

Chapter-IV 167

Hypothesis 1.5: Maximum number of hours worked Vs BPO areas


of maximum number of hours worked.


maximum number of hours worked.

Table No. 4.33 Maximum number of hours worked Vs BPO areas

Maximum hours worked

Mean S.D No.

Area of

work






Others 6.19 2.13 27

Total 6.69 1.91 400

Table No.4.34 ANOVA for Maximum hours worked

Sum of

Squares df

Mean

Square F Sig.

Between Groups 42.632 5 8.526 2.388 *

Within Groups 1406.545 394 3.570

Total 1449.178 399

Result


area of work groups in the average maximum hours worked scores.




the average maximum hours worked scores.

Chapter-IV 168

Hypothesis 1.6: Dissatisfaction with rewards and hikes Vs BPO areas


of dissatisfaction with rewards and hikes.


dissatisfaction with rewards and hikes.

Table No. 4.35 Dissatisfaction with rewards and hikes Vs BPO areas

Dissatisfaction with rewards and hikes

Mean S.D No.

Area of

work






Others 4.78 1.42 27

Total 6.05 1.96 400

Table No. 4.36ANOVA for Dissatisfaction with rewards and hikes

Sum of


Between Groups 89.548 5 17.910 4.885 **

Within Groups 1444.550 394 3.666

Total 1534.097 399

Result


area of work groups in the average dissatisfaction with rewards and hikes scores.




the average dissatisfaction with rewards and hikes scores.

Chapter-IV 169

Hypothesis 1.7: Human Resource Management Practices Vs BPO areas

Ho: 1.7. There is no significant difference among the BPO areas in the average scores

of human resource management practices.

H1: 1.7. There is significant difference among the BPO areas in the average scores of

human resource management practices.

Table No. 4.37 Human Resource Management Practices Vs BPO areas

Human Resource Management practice

Mean S.D No.

Area of work

Financial Accounting 2.45 .81 126

Customer Services 2.52 .90 125

Procurement 2.79 .80 14

Human Resource 2.24 .92 41


Others 2.81 .83 27

Total 2.58 .93 400

Table No.4.38 ANOVA for Human Resource Management practices

Sum of Squares df Mean Square F Sig.

Between Groups 20.206 5 4.041 4.924 **

Within Groups 323.392 394 .821

Total 343.597 399

Result


area of work groups in the average human resource management practices scores.

Since the calculated F-ratio value, 4.924 is higher than the table value 03.064 at 1% level

of significance, we reject the null hypothesis.

Hence, it is inferred that there is significant difference among the area of workgroups in

the average human resource management practices scores.

Chapter-IV 170

Hypothesis 1.8: Dissatisfaction with salary and perks Vs BPO areas

H0: 1.8 There is no significant difference among the BPO areas in the average scores

of dissatisfaction with salary and perks.

H1:1.8 There is significant difference among the BPO areas in the average scores of

dissatisfaction with salary and perks.

Table No.4.39 Dissatisfaction with salary and perks Vs BPO areas

Dissatisfaction with Salary and perks

Mean S.D No.

Area of

work






Others 5.63 1.90 27

Total 6.00 1.83 400

Table No.4.40 ANOVA for Dissatisfaction with Salary and perks

Sum of

Squares df

Mean

Square F Sig.

Between Groups 16.071 5 3.214 .961 Ns

Within Groups 1317.919 394 3.345

Total 1333.990 399

Result


area of work groups in the average dissatisfaction with salary and perks scores.

Since the calculated F-ratio value 0.961is lower than the table value 2.237 at 5% level of



in the average dissatisfaction with salary and perks scores.

Chapter-IV 171

Hypothesis 1.9: Food and relaxation Vs BPO areas

H0: 1.9 There is no significant difference among the BPO sectors in the average scores

of food and relaxation.

H1: 1.9 There is significant difference among the BPO sectors in the average scores of

food and relaxation.

Table No.4.41 Food and relaxation Vs BPO areas

Food and relaxation

Mean S.D No.

Area of

work






Others 7.78 2.34 27

Total 6.82 2.12 400

Table No. 4.42 ANOVA for Food and relaxation


Between Groups 78.712 5 15.742 3.620 **

Within Groups 1713.598 394 4.349

Total 1792.310 399

Result


area of work groups in the average food and relaxation scores.




the average food and relaxation scores.

Chapter-IV 172

Hypothesis 1.10: Lack of transportation and talent Vs BPO areas

H0: 1.10 There is no significant difference among the area of work groups in the

average lack of transportation and talent scores.

H1: 1.10 There is significant difference among the area of work groups in the average

lack of transportation and talent scores.

Table No. 4.43 Lack of transportation and talent Vs BPO areas

Miscellaneous-lack of transportation and talent

Mean S.D No.

Area of

work






Others 5.81 2.24 27

Total 6.45 1.83 400

Table No. 4.44 ANOVA for Miscellaneous-lack of transportation and talent



Within Groups 1319.528 394 3.349

Total 1332.790 399

Result


area of work groups in the average lack of transportation and talent scores.




in the average lack of transportation and talent scores.

Chapter-IV 173

Hypothesis 1.11: Work and family conflict Vs BPO areas

H0:1.11 There is no significant difference among the area of work groups in the

average work and family conflict scores.

H1:1.11 There is significant difference among the area of work groups in the

average work and family conflict scores.

Table No. 4.45 Work and family conflict Vs BPO areas

Work and family conflict

Mean S.D No.

Area of

work






Others 8.30 2.13 27

Total 8.68 1.64 400

Table No.4.46. ANOVA for Work and family conflict


Between Groups 20.167 5 4.033 1.504 Ns

Within Groups 1056.873 394 2.682

Total 1077.040 399

Result


area of work groups in the average work and family conflict scores.




in the average work and family conflict scores.

Chapter-IV 174

Hypothesis 1.12: Work from home Vs BPO areas

H0:1.12 There is no significant difference among the area of work groups in the

average work from home scores.



Table No.4.47 Work from home Vs BPO areas

Work from home

Mean S.D No.

Area of

work






Others 2.93 1.30 27

Total 2.57 1.13 400

Table No 4.48 ANOVA for Work from home



Within Groups 500.122 394 1.269

Total 507.898 399

Result


area of work groups in the average work from home scores.




in the average work from home scores.

Chapter-IV 175

Hypothesis 1.13: Lack of work ethics Vs BPO areas

H0 : 1.13 There is no significant difference among the area of work groups in the

average lack of work ethics scores.



Table No.4.49 Lack of work ethics Vs BPO areas

Lack of Work ethics

Mean S.D No.

Area of

work






Others 15.22 5.37 27

Total 15.58 3.60 400

Table No 4.50 ANOVA for Lack of Work ethics



Within Groups 5116.008 394 12.985

Total 5183.750 399

Result


area of work groups in the average lack of work ethics scores.




in the average lack of work ethics scores.

Chapter-IV 176

4.4.2 Variation in factors between the states of Karnataka and Kerala

The following hypotheses were set to study the relationship between different BPO

locations and proposed attrition factors : lack of integration and goal setting, motivation

and appreciation, work atmosphere, labor welfare and corporate governance, maximum


management practices, dissatisfaction with salary and perks, food and relaxation, lack of

transportation and talent, work and family conflict, work from home and lack of work

ethics.

In each combination of location and attrition factor, suitable hypotheses were framed and

testing (t-test) of the hypotheses were done and the results are discussed as given below:

Hypothesis 2.1: Dissatisfaction with salary and perks Vs location

H0: 2.1. There is no significant difference between the employees of Karnataka and

Kerala in the average scores of dissatisfaction with salary and perks.

H1: 2.1. There is significant difference between the employees of Karnataka and

Kerala in the average scores of dissatisfaction with salary and perks.

Table No.4.51 Dissatisfaction with salary and perks Vs location


Mean S.D No.

Location Karnataka 6.25 1.79 285

Kerala 5.37 1.77 115

Total 6.00 1.83 400

Table No.4.52 t-test for Equality of Means

t df Sig.

4.414 398 **

Chapter-IV 177

Result

The t-test was applied to find whether there is significant difference between Karnataka

and Kerala employees in the average dissatisfaction with salary and perks scores.

The calculated value is 4.44 which is higher than the table value of 2.588 at 1% level of


Hence, it is inferred that there is significant difference between Karnataka and Kerala

employees in the average dissatisfaction with salary and perks scores.

Hypothesis 2.2: Lack of integration and goal setting Vs employee’s location

H0:2.2. There is no significant difference between the employees of Karnataka and

Kerala in the average scores of lack of integration and goal setting.

H1:2.2. There is significant difference between the employees of Karnataka and

Kerala in the average scores of lack of integration and goal setting.

Table No. 4.53 Lack of integration and goal setting Vs employee’s location


Mean S.D No.


Kerala 11.53 3.48 115

Total 12.15 3.21 400

Table No.4.54 t-test for Equality of Means

t df Sig.

2.456 398 *

Result


and Kerala employees in the average lack of integration and goal setting scores.

Since the calculated t-test value 2.456 is higher than the table value 1.966 at 5% level of


Chapter-IV 178


employees in the average lack of integration and goal setting scores.

Hypothesis 2.3: Work atmosphere Vs Employee’s location


Kerala in the average scores of work atmosphere.


Kerala in the average scores of work atmosphere.

Table No. 4.55 Work atmosphere Vs Employee’s location.

Work atmosphere

Mean S.D No.


Kerala 13.90 3.52 115

Total 14.57 3.01 400

Table No. 4.56 t-test for Equality of Means

t df Sig.

2.864 398 **

Result


and Kerala employees in the average work atmosphere scores.

Since the calculated t-test value 2.864 is higher than the table value 2.588 at 1% level of



employees in the average work atmosphere scores.

Chapter-IV 179

Hypothesis 2.4: Food and relaxations Vs employee’s location


Kerala in the average scores of food and relaxation.


Kerala in the average scores of food and relaxation.

Table: No. 4.57 Food and relaxations Vs employee’s location

Food and relaxation

Mean S.D No.


Kerala 7.40 2.22 115

Total 6.82 2.12 400

Table: No. 4.58 t-test for Equality of Means

t df Sig.

3.557 398 **

Result


and Kerala employees in the average food and relaxation scores.

Since the calculated t-test value 3.557 is higher than the table value of 2.588 at 1% level

of significance, we reject the null hypothesis.


employees in the average food and relaxation scores.

Chapter-IV 180

Hypothesis 2.5: Dissatisfaction with rewards and hikes Vs employee’s location


Kerala in the average scores of dissatisfaction with rewards and hikes.


Kerala in the average scores of dissatisfaction with rewards and hikes.

Table: No. 4.59 Dissatisfaction with rewards and hikes Vs employee’s location


Mean S.D No.


Kerala 5.73 2.01 115

Total 6.05 1.96 400


t df Sig.

2.063 398 *

Result


and Kerala employees in the average dissatisfaction with rewards and hikes scores.

Since the calculated value is 2.063, which is higher than the table value of 1.966 at 5%

level of significance, we reject the null hypothesis.


employees in the average dissatisfaction with rewards and hikes scores.

Chapter-IV 181

Hypothesis 2.6: Lack of work ethics Vs employee’s location


Kerala in the average scores of lack of work ethics.


Kerala in the average scores of lack of work ethics.

Table: No. 4.61 Lack of work ethics Vs employee’s location

Lack of Work ethics

Mean S.D No.


Kerala 15.35 4.41 115

Total 15.58 3.60 400


t Df Sig.

0.800 398 Ns

Result


and Kerala employees in the average lack of work ethics scores.

Since the calculated value is 0.800, which is less than the table value of 1.966 at 5% level

of significance, we accept the null hypothesis.

Hence, it is inferred that there is no significant difference between Karnataka and Kerala

employees in the average lack of work ethics scores.

Chapter-IV 182

Hypothesis 2.7: Motivation and appreciation Vs employee’s location

H0: 2.7 There is no significant difference between the employees of Karnataka and

Kerala in the average motivation and appreciation scores.

H1: 2.7 There is significant difference between the employees of Karnataka and

Kerala in the average motivation and appreciation scores.

Table: No. 4.63 Motivation and appreciation Vs employee’s location


Mean S.D No.


Kerala 8.28 2.42 115

Total 7.95 2.57 400


t df Sig.

1.626 398 Ns

Result


and Kerala employees in the average motivation and appreciation scores.

Since the calculated value 1.626 is lower than the table value of 1.966 at 5% level of



employees in the average motivation and appreciation scores.

Chapter-IV 183

Hypothesis 2.8: Work from home Vs employee’s location


Kerala in the average work from home scores.

H1:2.8 There is significant difference between the employees of Karnataka and

Kerala in the average work from home scores.

Table: No. 4.65 Work from home Vs employee’s location

Work from home

Mean S.D No.


Kerala 2.55 1.24 115

Total 2.57 1.13 400


t df Sig.

0.278 398 Ns

Result


and Kerala employees in the average work from home scores.

Since the calculated value is 0.278, which is lower than the table value of 1.966 at 5%

level of significance, we accept the null hypothesis.


employees in the average work from home scores.

Chapter-IV 184

Hypothesis 2.9: Work and family conflict Vs employee’s location


Kerala in the average work and family conflict scores.

H1 : 2.9 There is significant difference between the employees of Karnataka and

Kerala in the average work and family conflict scores.

Table: No. 4.67 Work and family conflict Vs employee’s location


Mean S.D No.


Kerala 8.39 1.91 115

Total 8.68 1.64 400


t df Sig.

.244 398 *

Result


and Kerala employees in the average work and family conflict scores.

Since the calculated value 2.244 is higher than the table value of 1.966 at 5% level of



employees in the average work and family conflict scores.

Chapter-IV 185

Hypothesis 2.10: Labour welfare and corporate governance Vs employee’s location

H0 : 2.10 There is no significant difference between the employees of Karnataka and

Kerala in the average labor welfare and corporate governance scores.

H1: 2.10 There is significant difference between the employees of Karnataka and Kerala

in the average labor welfare and corporate governance scores.

Table No. 4.69 Labour welfare and corporate governance Vs employee’s location.


Mean S.D No.


Kerala 11.35 2.93 115

Total 11.76 2.70 400


t df Sig.

1.937 398 Ns

Result


and Kerala employees in the average labour welfare and corporate governance scores.




employees in the average labour welfare and corporate governance scores.

Chapter-IV 186

Hypothesis 2.11: Occupational health problems Vs employee’s location

H0:2.11 There is no significant difference between the employees of Karnataka and

Kerala in the average occupational health problems scores.

H1: 2.11 There is significant difference between the employees of Karnataka and

Kerala in the average occupational health problems scores.

Table: No. 4.71 Occupational health problems Vs employee’s location

Occupational health problems

Mean S.D No.


Kerala 14.98 3.84 115

Total 14.69 3.38 400


t df Sig.

1.119 398 Ns

Result


and Kerala employees in the average occupational health problems scores.




employees in the average occupational health problems scores.

Chapter-IV 187

Hypothesis 2.12: Human resource management Practices Vs employee’s location

H0: 2.12 There is no significant difference between Karnataka and Kerala employees in

the average scores of human resource management practices.

H1:2.12 There is significant difference between Karnataka and Kerala employees in

the average scores of human resource management practices.

Table No. 4.73 Human resource management Practices Vs employee’s location


Mean S.D No.

Location Karnataka 2.55 .92 285

Kerala 2.63 .96 115

Total 2.58 .93 400


t df Sig.

0.784 398 Ns

Result


and Kerala employees in the average human resource management practices scores.

Since the calculated t-test value 0.784 is lower than the table value 1.966 at 5% level of



employees in the average human resource management practices scores.

Chapter-IV 188

Hypothesis 2.13: Average strength factor scores Vs employee’s location

H0: 2.13 There is no significant difference between Karnataka and Kerala employees in

the average strength factors scores.

H1: 2.13 There is significant difference between Karnataka and Kerala employees in the

average strength factors scores.

Table: No. 4.75 Average strength factor scores Vs employee’s location

Strength Factor Score

Mean S.D No.


Kerala 8.86 1.96 115

Total 8.65 1.90 400


t df Sig.

1.432 398 Ns

Result


and Kerala employees in the average strength factor scores.

Since the calculated t-test value 01.432 is less than the table value 1.966 at 5% level of



employees in the average strength factor scores.

Chapter-IV 189

4.4.3 Variation between national and multinational BPOs

The following hypotheses were set to study the relationship between two global positions

(national/ multinational) and the attrition factors: lack of integration and goal setting,

motivation and appreciation, work atmosphere, labor welfare and corporate governance,

maximum number of hours worked, dissatisfaction with rewards and hikes, human

resource management practices, dissatisfaction with salary and perks, food and

relaxation, work and family conflict, and work from home. In each combination of

global position (national/multinational) and attrition factor suitable hypotheses were

framed and testing (t-test) of the hypotheses were done and the results are discussed as

given below:

Hypothesis 3.1: Global position Vs Lack of integration and goal setting

H0: 3.1. There is no significant difference between national BPO employees and

multinational BPO employees in the average scores of lack of integration and

goal setting.

H1: 3.1. There is significant difference between national BPO employees and

multinational BPO employees in the average scores of lack of integration and

goal setting.

Table: No. 4.77 Lack of integration and Goal setting Vs Global position


Mean S.D No.

Global

position

National 11.81 3.04 212

Multinational 12.53 3.36 188

Total 12.15 3.21 400


t df Sig.

2.234 398 *

Chapter-IV 190

Result

The t-test was applied to find whether there is significant difference between national and

multinational BPO employees in the average lack of integration and goal setting scores.

Since the calculated value 2.234 is higher than the table value 1.966 at 5% level of


Hence, it is inferred that there is significant difference between national and multinational

BPO employees in the average lack of integration and goal setting scores.

Hypothesis 3.2 Global position Vs Dissatisfaction with salary and perks

H0:3.2. There is no significant difference between national BPO employees and

multinational BPO employees in the average scores of dissatisfaction with

salary and perks.

H1:3.2. There is significant difference between national BPO employees and


salary and perks.

Table: No. 4.79 Dissatisfaction with salary and perks Vs Global position


Mean S.D No.

Global

position

National 5.73 1.78 212


Total 6.00 1.83 400


t Df Sig.

3.154 398 **

Result

The t-test was applied to find whether there is significant difference between National

and Multinational BPO employees in the average dissatisfaction with salary and perks

scores.

Chapter-IV 191




BPO employees in the average dissatisfaction with salary and perks scores.

Hypothesis 3.3: Global position Vs Dissatisfaction with rewards and hikes

H0:3.3. There is no significant difference between national BPO employees and


rewards and hikes.



rewards and hikes.

Table: No. 4.81 Dissatisfaction with rewards and hikes Vs Global position


Mean S.D No.

Global

position

National 5.85 1.83 212


Total 6.05 1.96 400


t df Sig.

2.159 398 *

Result


multinational BPO employees in the average dissatisfaction with rewards and hikes

scores.



Chapter-IV 192


BPO employees in the average dissatisfaction with rewards and hikes scores.

Hypothesis 3.4: Global position Vs Human resource management practices

H0: 3.4. There is no significant difference between national and multinational BPO

employees in the average scores of human resource management practices.

H1: 3.4. There is significant difference between national and multinational BPO

employees in the average scores of human resource management practices.

Table: No. 4.83 Human Resource Management Practices Vs Global position


Mean S.D No.

Global position National 2.57 .92 212

Multinational 2.59 .94 188

Total 2.58 .93 400


t df Sig.

0.154 398 Ns

Result


multinational employees in the average human resource management practices scores.

Since the calculated t-test value 0.154 is less than the table value 1.966 at 5% level of


Hence, it is inferred that there is no significant difference between national and

multinational employees in the average human resource management practices scores.

Chapter-IV 193

Hypothesis 3.5: Global position Vs Work atmosphere

H0: 3.5. There is no significant difference between national BPO employees and

multinational BPO employees in the average scores of work atmosphere.


multinational BPO employees in the average scores of work atmosphere.

Table: No. 4.85 Work atmosphere vs global position.

Work atmosphere

Mean S.D No.

Global

position

National 14.45 3.19 212


Total 14.57 3.01 400


t df Sig.

0.810 398 Ns

Result


and Multinational BPO employees in the average work atmosphere scores.

Since the calculated value 0.810 is lower than the table value 1.966 at 5% level of


Hence, it is inferred that there is no significant difference between National and

Multinational BPO employees in the average work atmosphere scores.

Chapter-IV 194

Hypothesis 3.6: Global position Vs Work and family conflict

H0:3.6 There is no significant difference between national BPO employees and

multinational BPO employees in the average scores of work and family

conflict.

H1:3.6 There is significant difference between national BPO employees and

multinational BPO employees in the average scores of work and family

conflict.

Table: No. 4.87 Work and Family Conflict Vs Global position


Mean S.D No.

Global

position

National 8.58 1.75 212


Total 8.68 1.64 400


t df Sig.

1.353 398 Ns

Result


and Multinational BPO employees in the average work and family conflict scores.




Multinational BPO employees in the average work and family conflict scores.

Chapter-IV 195

Hypothesis: 3.7 Global position Vs Food and relaxation

H0: 3.7 There is no significant difference between national BPO employees and

multinational BPO employees in the average scores of food and

relaxation.

H1: 3.7 There is significant difference between national BPO employees and

multinational BPO employees in the average scores of food and

relaxation.

Table: No. 4.89 Food and relaxation Vs Global position

Food and relaxation

Mean S.D No.

Global

position

National 6.94 2.12 212


Total 6.82 2.12 400


t df Sig.

1.240 398 Ns

Result


and Multinational BPO employees in the average food and relaxation scores.




Multinational BPO employees in the average food and relaxation scores.

Chapter-IV 196

Hypothesis 3.8: Global position Vs Motivation and appreciation


multinational BPO employees in the average scores of motivation and

appreciation.

H1: 3.8 There is significant difference between national BPO employees and

multinational BPO employees in the average scores of motivation and

appreciation.

Table: No. 4.91 Motivation and appreciation Vs Global position


Mean S.D No.

Global

position

National 8.04 2.48 212


Total 7.95 2.57 400


t df Sig.

0.763 398 Ns

Result


multinational BPO employees in the average motivation and appreciation scores.




multinational BPO employees in the average motivation and appreciation scores.

Chapter-IV 197

Hypothesis 3.9: Global position Vs Labor welfare and corporate governance

H0: 3.9 There is no significant difference between national BPO employees and

multinational BPO employees in the average scores of labor welfare and

corporate governance.

H1:3.9 There is significant difference between national BPO employees and

multinational BPO employees in the average scores of labor welfare and

corporate governance.

Table: No. 4.93 Labour welfare and corporate governance Vs Global position


Mean S.D No.

Global

position

National 11.68 2.47 212


Total 11.76 2.70 400


t Df Sig.

0.579 398 Ns

Result


multinational BPO employees in the average labour welfare and corporate governance

scores.




multinational BPO employees in the average labour welfare and corporate governance

scores.

Chapter-IV 198

Hypothesis 3.10: Global position Vs Maximum number of hours worked

Ho: 3.10 There is no significant relationship between maximum number of hours

worked and the global position of the company.

H1:3.10 There is significant relationship between maximum number of hours worked

and the global position of the company.

Table: No. 4.95 Maximum number of hours worked Vs Global position

Global position TOTAL

National Multinational No. %

No. % No. %

Maximum no. of hours

worked

0 - 8 hrs 63 29.7 17 9.0 80 20.0

8 - 12 hrs 120 56.6 123 65.4 243 60.8

Above 12 hrs 29 13.7 48 25.5 77 19.3

Total 212 100.0 188 100.0 400 100.0

Table: No. 4.96 Chi-Square Test

Value df Sig.

Chi-Square 29.843 2 **

Result

Chi-square test was applied to find whether there is significant relationship between

maximum number of hours worked and the global position of the company.

Since the calculated chi-square value, 29.843 is higher than the table value of 09.210 at

1% level of significance, we reject the null hypothesis.

Hence, it is inferred that there is significant relationship between maximum number of

hours worked and the global position of the company.

Chapter-IV 199

Hypothesis 3.11: Global position Vs Work from home


multinational BPO employees in the average work from home scores.

H1 :3.11 There is significant difference between national BPO employees and


Table: No. 4.97 Work from Home Vs Global position

Work from home

Mean S.D No.

Global

position

National 2.66 1.16 212


Total 2.57 1.13 400


t df Sig.

1.658 398 Ns

Result







Chapter-IV 200

4.4.4 Relationship between Age groups and Attrition factors

Following hypotheses were set to study the relationship between age groups and

proposed attrition factors: lack of integration and goal setting, motivation and

appreciation, work atmosphere, labor welfare and corporate governance, maximum


management practices, dissatisfaction with salary and perks, food and relaxation, work

and family conflict, strength factor and work from home.

In each combination of age groups and attrition factors, suitable hypotheses were framed

and testing (ANOVA) of the hypothesis were done and the results are given below:

Hypothesis4.1: Lack of integration and goal setting Vs Age

H0:4.1. There is no significant difference among the respondent’s age groups in the

average scores of lack of integration and goal setting.

H1: 4.1. There is significant difference among the respondents’ age groups in the

average scores of lack of integration and goal setting

Table: No. 4.99 Lack of integration and goal setting Vs Age


Mean S.D No.

Age of the

respondent

< 18 yrs 12.25 3.10 4

18-20 yrs 14.04 3.29 27

21-25 yrs 12.13 3.16 260

Above 25 yrs 11.72 3.19 109

Total 12.15 3.21 400

Table: No. 4.100 ANOVA for Lack of integration and goal setting


Between Groups 116.847 3 38.949 3.856 **

Within Groups 3999.450 396 10.100

Total 4116.297 399

Chapter-IV 201

Result


age of the respondent groups in the average lack of integration and goal setting scores.



Hence, it is inferred that there is significant difference among the age of the respondent

groups in the average lack of integration and goal setting scores.

Hypothesis 4.2: Work and family conflict Vs Age

H0: 4.2. There is no significant difference among the respondent’s age groups in the

average scores of work and family conflict.

H1:4.2. There is significant difference among the respondent’s age groups in the


Table: No. 4.101 Work and family conflict Vs Age


Mean S.D No.

Age of the respondent

< 18 yrs 9.00 .82 4

18-20 yrs 8.74 1.16 27

21-25 yrs 8.85 1.60 260

Above 25 yrs 8.25 1.80 109

Total 8.68 1.64 400

Table: No. 4.102 ANOVA for Work and family conflict


Between Groups 28.393 3 9.464 3.574 *

Within Groups 1048.647 396 2.648

Total 1077.040 399

Result


age of the respondent groups in the average work and family conflict scores.

Chapter-IV 202

Since the calculated F-ratio value 3.574 is higher than the table 2.628 at 5% level of



groups in the average work and family conflict scores.

Hypothesis 4.3: Strength factor Vs Age

H0: 4.3. There is no significant difference among the respondent’s age groups in the

average scores of strength factor.

H1: 4.3. There is significant difference among the respondent’s age groups in the

average scores of strength factor.

Table: No. 4.103 Strength factor Vs Age


Mean S.D No.


< 18 yrs 11.00 1.41 4

18-20 yrs 8.30 2.30 27

21-25 yrs 8.53 1.78 260

Above 25 yrs 8.93 2.00 109

Total 8.65 1.90 400

Table: No. 4.104 ANOVA for Strength Factor Score

Sum of


Between Groups 37.501 3 12.500 3.546 *

Within Groups 1395.796 396 3.525

Total 1433.298 399

Result


age of the respondent groups in the average strength factor scores.

Since the calculated F-ratio value, 03.546 is higher than the table value 02.628 at 5%


Chapter-IV 203


groups in the average strength factor scores.

Hypothesis 4.4: Maximum number of hours worked Vs Age

H0: 4.4 There is no significant relationship between maximum number of hours

worked and the age group of the respondents.

H1: 4.4 There is significant relationship between maximum number of hours

worked and the age group of the respondents.

Table: No. 4.105 Maximum number of hours worked Vs Age

Maximum hours worked

Mean S.D No.


< 18 yrs 5.75 .96 4

18-20 yrs 6.63 2.00 27

21-25 yrs 6.63 1.84 260

Above 25 yrs 6.88 2.06 109

Total 6.69 1.91 400

Table: No. 4.106 ANOVA for Maximum number of hours worked.

Sum of Squares df Mean

Square F Sig.


Within Groups 1440.784 396 3.638

Total 1449.178 399

Result


age of the respondent groups in the average scores of maximum hours worked.

Since the calculated F-ratio value 0.769 is lower than the table 2.628 at 5% level of


Hence, it is inferred that there is no significant difference among the age of the

respondent groups in the average scores of maximum hours worked.

Chapter-IV 204

Hypothesis 4.5: Human Resource Management Practices Vs Age

H0: 4.5 There is no significant difference among the respondents age groups in the

average human resource management practices scores.

H1: 4.5 There is significant difference among the respondent’s age groups in the

average human resource management practices scores.

Table: No. 4.107 Human Resource Management Practices Vs Age


Mean S.D No.


< 18 yrs 2.75 1.26 4

18-20 yrs 2.59 .80 27

21-25 yrs 2.62 .90 260

Above 25 yrs 2.48 1.02 109

Total 2.58 .93 400

Table: No. 4.108 ANOVA for Human Resource Management practices

Sum of Squares df

Mean

Square F Sig.

Between Groups 1.598 3 .533 .617 Ns


Total 343.598 399

Result


age of the respondent groups in the average human resource management practices

scores.

Since the calculated F-ratio value, 0.617 is lower than the table value 2.628 at 5% level of



respondent groups in the average human resource management practices scores.

Chapter-IV 205

Hypothesis 4.6: Lack of work ethics Vs Age

H0: 4.6 There is no significant difference among the respondents age groups in the


H1: 4.6 There is significant difference among the respondents age groups in the


Table: No. 4.109 Lack of work ethics Vs Age

Lack of Work ethics

Mean S.D No.

Age of the

respondent

< 18 yrs 15.00 .00 4

18-20 yrs 16.19 4.39 27

21-25 yrs 15.43 3.61 260

Above 25 yrs 15.79 3.45 109

Total 15.58 3.60 400

Table: No. 4.110 ANOVA for Lack of Work ethics



Within Groups 5161.975 396 13.035

Total 5183.750 399

Result


age of the respondent groups in the average lack of work ethics scores.




respondent groups in the average lack of work ethics scores.

Chapter-IV 206

Hypothesis 4.7: Dissatisfaction with rewards and hikes Vs Age

H0: 4.7 There is no significant difference among the age of the respondent groups

in the average dissatisfaction with rewards and hikes scores.

H1: 4.7 There is significant difference among the age of the respondent groups in

the average dissatisfaction with rewards and hikes scores.

Table: No. 4.111 Dissatisfaction with rewards and hikes Vs Age


Mean S.D No.


< 18 yrs 7.00 1.83 4

18-20 yrs 6.85 1.68 27

21-25 yrs 6.05 1.96 260

Above 25 yrs 5.82 2.00 109

Total 6.05 1.96 400

Table: No. 4.112 ANOVA for Dissatisfaction with rewards and hikes



Within Groups 1507.184 396 3.806

Total 1534.098 399

Result


age of the respondent groups in the average dissatisfaction with rewards and hikes scores.




respondent groups in the average dissatisfaction with rewards and hikes scores.

Chapter-IV 207

Hypothesis 4.8: Labour welfare and corporate governance Vs Age

H0:4.8 There is no significant difference among the age of the respondent groups

in the average labour welfare and corporate governance scores.

H1:4.8 There is significant difference among the age of the respondent groups in

the average labour welfare and corporate governance scores.

Table: No. 4.113 Labour welfare and corporate governance Vs Age


Mean S.D No.


< 18 yrs 11.75 .96 4

18-20 yrs 12.59 2.29 27

21-25 yrs 11.65 2.62 260

Above 25 yrs 11.82 2.99 109

Total 11.76 2.70 400

Table: No. 4.114 ANOVA for Labour welfare and corporate governance



Within Groups 2879.045 396 7.270

Total 2901.477 399

Result


age of the respondent groups in the average labor welfare and corporate governance

scores.




respondent groups in the average labor welfare and corporate governance scores.

Chapter-IV 208

Hypothesis 4.9: Dissatisfaction with salary and perks Vs Age

H0:4.9 There is no significant difference among the age of the respondent groups in the

average dissatisfaction with salary and perks scores.

H1:4.9 There is significant difference among the age of the respondent groups in the

average dissatisfaction with salary and perks scores.

Table: No. 4.115 Dissatisfaction with salary and perks Vs Age


Mean S.D No.


< 18 yrs 5.75 .50 4

18-20 yrs 5.85 1.43 27

21-25 yrs 6.10 1.94 260

Above 25 yrs 5.80 1.66 109

Total 6.00 1.83 400

Table: No. 4.116 ANOVA for Dissatisfaction with Salary and perks



Within Groups 1326.313 396 3.349

Total 1333.990 399

Result


age of the respondent groups in the average dissatisfaction with salary and perks scores.




respondent groups in the average dissatisfaction with salary and perks scores.

Chapter-IV 209

Hypothesis 4.10: Work from Home Vs Age

H0:4.10 There is no significant difference among the respondents age groups in the


H1:4.10 There is significant difference among the respondents age groups in the


Table: No. 4.117 Work from Home Vs Age

Work from home

Mean S.D No.


< 18 yrs 3.75 .96 4

18-20 yrs 2.30 .91 27

21-25 yrs 2.56 1.12 260

Above 25 yrs 2.62 1.18 109

Total 2.57 1.13 400

Table: No. 4.118 ANOVA for Work from home



Within Groups 499.973 396 1.263

Total 507.897 399

Result


age of the respondent groups in the average work from home scores.




respondent groups in the average work from home scores.

Chapter-IV 210

Hypothesis 4.11: Motivation and Appreciation Vs Age

H0:4.11 There is no significant difference among the respondents age groups in the

average motivation and appreciation scores.

H1:4.11 There is significant difference among the respondents age groups in the

average motivation and appreciation scores.

Table: No. 4.119 Motivation and Appreciation Vs Age


Mean S.D No.


< 18 yrs 8.75 2.22 4

18-20 yrs 8.74 2.58 27

21-25 yrs 7.94 2.62 260

Above 25 yrs 7.74 2.44 109

Total 7.95 2.57 400

Table: No. 4.120 ANOVA for Motivation and appreciation



Within Groups 2612.877 396 6.598

Total 2637.000 399

Result


age of the respondent groups in the average motivation and appreciation scores.




respondent groups in the average motivation and appreciation scores.

Chapter-IV 211

Hypothesis 4.12: Work Atmosphere Vs Age

H0: 4.12 There is no significant difference among the age of the respondent groups

in the average work atmosphere scores.

H1: 4.12 There is significant difference among the age of the respondent groups in

the average work atmosphere scores.

Table: No. 4.121 Work Atmosphere Vs Age

Work atmosphere

Mean S.D No.


< 18 yrs 16.00 1.41 4

18-20 yrs 15.07 2.32 27

21-25 yrs 14.59 3.11 260

Above 25 yrs 14.34 2.95 109

Total 14.57 3.01 400

Table: No. 4.122 ANOVA for Work atmosphere

Sum of



Within Groups 3587.258 396 9.059

Total 3608.178 399

Result


age of the respondent groups in the average work atmosphere scores.




respondent groups in the average work atmosphere scores.

Chapter-IV 212

4.4.5 Relationship between maximum number of hours worked and

Attrition

The following hypotheses were set to study the relationship between maximum number

of hours worked groups and proposed attrition factors namely area of work, gender,

location and monthly salary. In each combination of maximum number of hours worked

groups and attrition factors, suitable hypotheses were framed and testing (Chi-Square

Test) of the hypothesis were done and the results are given below:

Hypothesis 5.1: Maximum number of hours worked Vs Gender

Ho: 5.1. The maximum number of hours worked is independent of the employee’s

gender.

H1: 5.1. The maximum number of hours worked is dependent on the employee’s

gender.

Table No. 4.123 Maximum number of hours worked Vs Gender

Gender TOTAL

Male Female No. %

No. % No. %

Maximum no. of hours

worked

0 - 8 hrs 43 18.2 37 22.6 80 20.0

8 - 12 hrs 138 58.5 105 64.0 243 60.8

Above 12 hrs 55 23.3 22 13.4 77 19.3

Total 236 100.0 164 100.0 400 100.0


Value df Sig.

Chi-Square 6.319 2 *

Result

Chi-square test was applied to find whether the maximum number of hours worked is

dependent on the gender.

Since the calculated chi-square value, 6.319 is higher than the table value of 5.991 at 5%


Chapter-IV 213

Hence, it is inferred that the maximum number of hours worked is dependent on the

gender.

Hypothesis 5.2: Maximum number of hours worked Vs Location


location.

H1:5.2. The maximum number of hours worked is dependent on the employee’s

location.

Table: No. 4.125 Maximum number of hours worked Vs Location

Location TOTAL

Karnataka Kerala No. %

No. % No. %

Maximum no. of hours worked

0 - 8 hrs 36 12.6 44 38.3 80 20.0

8 - 12 hrs 189 66.3 54 47.0 243 60.8

Above 12 hrs 60 21.1 17 14.8 77 19.3

Total 285 100.0 115 100.0 400 100.0


Value df Sig.


Result


dependent on the employees location.



Hence, it is inferred that the maximum number of hours worked is dependent on the

location.

Chapter-IV 214

Hypothesis 5.3: Maximum number of hours worked Vs salary per month


salary per month.

H1:5.3. The maximum number of hours worked is dependent on the employee’s salary

per month.

Table: No. 4.127 Maximum number of hours worked Vs salary per month

Salary per month TOTAL

< Rs.5000 Rs.5000-

10000

Rs.10000-

15000

Rs.15000-

20000

Above

Rs.20000 No. %

No. % No. % No. % No. % No. %

Maximum

no. of

hours

worked

0 - 8 hrs 4 57.1 25 30.5 33 20.6 11 11.7 7 12.3 80 20.0

8 - 12 hrs 3 42.9 50 61.0 98 61.3 57 60.6 35 61.4 243 60.8

Above

12 hrs 7 8.5 29 18.1 26 27.7 15 26.3 77 19.3

Total 7 100.0 82 100.0 160 100.0 94 100.0 57 100.0 400 100.0


Value df Sig.


Result

Chi-square test was applied to find whether there is significant relationship between

maximum number of hours worked and salary per month.



Hence, it is inferred that there is significant relationship between maximum number of

hours worked and salary per month.

Chapter-IV 215

Hypothesis 5.4: Maximum number of hours worked Vs area of work

Ho: 5.4 The maximum number of hours worked is independent of the employee’s area

of work.

H1:5.4 The maximum number of hours worked is dependent on the employee’s area

of work.

Table: No. 4.129 Maximum number of hours worked Vs area of work

Area of work TOTAL

Financial

Accounting

Customer

Services Procurement

Human

Resource

Application

Process Others

No. %

No. % No. % No. % No. % No. % No. %

Maximum

no. of

hours

worked

0 - 8

hrs 21 16.7 29 23.2 2 14.3 10 24.4 13 19.4 5 18.5 80 20.0

8 - 12

hrs 83 65.9 78 62.4 8 57.1 23 56.1 38 56.7 13 48.1 243 60.8

Above

12 hrs 22 17.5 18 14.4 4 28.6 8 19.5 16 23.9 9 33.3 77 19.3

Total 126 100.0 125 100.0 14 100.0 41 100.0 67 100.0 27 100.0 400 100.0


Value df Sig.

Chi-Square 9.566 10 Ns

Result


dependent on the area of work.

Since the calculated chi-square value, 09.566 is lower than the table value of 18.307 at

5% level of significance, we accept the null hypothesis.

Hence, it is inferred that the maximum number of hours worked is independent on the

area of work.

Chapter-IV 216

4.4.6 Difference among the designation groups towards Attrition

factors The following hypotheses were set to study the relationship between designation groups

and proposed attrition factors namely: lack of integration and goal setting, motivation and

appreciation, work atmosphere, dissatisfaction with rewards and hikes, human resource

management practices, dissatisfaction with salary and perks, work and family conflict,

and strength factor. In each combination, suitable hypothesis were framed and testing

(ANOVA) of the hypothesis were done and the results are discussed as below:

Hypothesis 6.1: Designation groups Vs strength factor scores

H0: 6.1. There is no significant difference among the designation groups in the

average strength factor scores.

H1:6.1. There is significant difference among the designation groups in the average

strength factor scores

Table: No. 4.131 Designation groups Vs strength factor scores


Mean S.D No.

Designation

Process Analyst 8.41 1.90 246

Senior Process Analyst 8.91 1.80 95

Team Leader 9.15 1.73 34

Supervisor 9.27 2.09 15

Manager 9.50 2.17 10

Total 8.65 1.90 400

Table: No. 4.132 ANOVA for Strength Factor Score


Between Groups 42.102 4 10.526 2.989 *

Within Groups 1391.195 395 3.522

Total 1433.298 399

Result


designation groups in the average strength factor scores.

Chapter-IV 217

Since the calculated F-ratio value, 02.989 is higher than the table value 02.395 at 5%


Hence, it is inferred that there is significant difference among the designation groups in

the average strength factor scores.

Hypothesis 6.2: Work and Family Conflict Vs designation

H0:6.2. There is no significant difference among the designation groups in the


H1:6.2. There is significant difference among the designation groups in the average

scores of work and family conflict.

Table: No. 4.133 Work and Family Conflict Vs designation


Mean S.D No.

Designation





Manager 7.60 2.72 10

TOTAL 8.68 1.64 400

Table: No. 4.134 ANOVA for Work and family conflict

Sum of


Between Groups 45.810 4 11.453 4.387 **

Within Groups 1031.230 395 2.611

Total 1077.040 399

Result


designation groups in the average work and family conflict scores.



Chapter-IV 218


the average work and family conflict scores.

Hypothesis 6.3: Motivation and Appreciation Vs designation

H0:6.3 There is no significant difference among the designation groups in the

average scores of motivation and appreciation.

H1:6.3 There is significant difference among the designation groups in the average

scores of motivation and appreciation.

Table: No. 4.135 Motivation and Appreciation Vs designation


Mean S.D No.

Designation





Manager 6.30 2.79 10

Total 7.95 2.57 400

Table: No. 4.136 ANOVA for Motivation and appreciation


Between Groups 64.586 4 16.147 2.479 *

Within Groups 2572.414 395 6.512

Total 2637.000 399

Result


designation groups in the average motivation and appreciation scores.




the average motivation and appreciation scores.

Chapter-IV 219

Hypothesis 6.4: Lack of integration and goal setting Vs designation

H0:6.4 There is no significant difference among the designation groups in the average

scores of lack of integration and goal setting.

H1: 6.4 There is significant difference among the designation groups in the average

scores of lack of integration and goal setting.

Table: No. 4.137 Lack of integration and goal setting Vs designation


Mean S.D No.

Designation





Manager 12.90 3.54 10

Total 12.15 3.21 400

Table: No. 4.138 ANOVA for Lack of integration and goal setting



Within Groups 4040.093 395 10.228

Total 4116.297 399

Result


designation groups in the average lack of integration and goal setting scores.

Since the calculated F-ratio value 1.863 is less than the table value 2.395 at 5% level of


Hence, it is inferred that there is no significant difference among the designation groups

in the average lack of integration and goal setting scores

Chapter-IV 220

Hypothesis 6.5: Work Atmosphere Vs designation

H0: 6.5 There is no significant difference among the designation groups in the average

scores of work atmosphere.


scores of work atmosphere.

Table: No. 4.139 Work Atmosphere Vs designation

Work atmosphere

Mean S.D No.

Designation





Manager 13.20 3.16 10

Total 14.57 3.01 400

Table: No. 4.140 ANOVA for Work atmosphere

Sum of



Within Groups 3566.050 395 9.028

Total 3608.178 399

Result


designation groups in the average work atmosphere scores.

Since the calculated F-ratio value 1.167 is less than the table value 2.395 at 5% level of



in the average work atmosphere scores.

Chapter-IV 221

Hypothesis 6.6: Dissatisfaction with salary and perks Vs designation

H0: 6.6 There is no significant difference among the designation groups in the

average scores of dissatisfaction with salary and perks.

H1:6.6 There is significant difference among the designation groups in the

average scores of dissatisfaction with salary and perks.

Table: No. 4.141 Dissatisfaction with salary and perks Vs designation


Mean S.D No.

Designation





Manager 5.00 2.00 10

Total 6.00 1.83 400

Table: No. 4.142 ANOVA for Dissatisfaction with Salary and perks



Within Groups 1316.063 395 3.332

Total 1333.990 399

Result


designation groups in the average dissatisfaction with salary and perks scores.




in the average dissatisfaction with salary and perks scores.

Chapter-IV 222

Hypothesis 6.7: Dissatisfaction with rewards and hikes Vs designation

H0: 6.7 There is no significant difference among the designation groups in the

average scores of dissatisfaction with rewards and hikes.

H1: 6.7 There is significant difference among the designation groups in the

average scores of dissatisfaction with rewards and hikes.

Table: No. 4.143 Dissatisfaction with rewards and hikes Vs designation


Mean S.D No.

Designation





Manager 5.10 2.42 10

Total 6.05 1.96 400

Table: No. 4.144 ANOVA for Dissatisfaction with rewards and hikes



Within Groups 1520.973 395 3.851

Total 1534.097 399

Result


designation groups in the average dissatisfaction with rewards and hikes scores.




in the average dissatisfaction with rewards and hikes scores.

Chapter-IV 223

Hypothesis 6.8: Designation groups Vs Human Resource Management Practices

H0:6.8 There is no significant difference among the designation groups in the average

scores of human resource management practices.


scores of human resource management practices.

Table: No. 4.145 Designation groups Vs Human Resource Management Practices


Mean S.D No.

Designation

Process Analyst 2.64 .94 246

Senior Process Analyst 2.49 .85 95

Team Leader 2.38 .78 34


Manager 2.30 1.34 10

Total 2.58 .93 400

Table: No. 4.146 ANOVA for Human Resource Management practice


Between Groups 3.867 4 .967 1.124 Ns


Total 343.597 399

Result


designation groups in the average human resource management practices scores.

Since the calculated F-ratio value, 01.124 is less than the table value 02.395 at 5% level



in the average human resource management practices scores.

Chapter-IV 224

4.5 MULTIPLE REGRESSION ANALYSIS

Regression Analysis was applied to find the critical factors and non-critical factors or

variables which might affect the attrition of the employees. For this, overall attrition

score was considered as dependent variable. The other variables namely Gender (coded

as 1-M, 0-F), Location (coded as 1-Karnataka, 0-Kerala), Global Position (1-National, 0-

Multinational), Age of the respondent, Experience in the present organization, Salary per

month, Number of training programs attended, Maximum number of hours worked,

Strength factors and HRM Practices were selected as independent variables which might

affect the dependent variable namely Overall Attrition Score.

The result of the regression analysis is given below:

Table No. 4.147 Dependent Variable: Overall Attrition Score

Regression

Coefficients

(B)

Std. Error t Sig.

(Constant) 131.540 7.074

Gender .264 1.436 .184 Ns

Location .413 1.773 .233 Ns

Global position -.147 1.594 -.092 Ns

Age of the respondent -2.766 1.343 -2.060 *

Experience in the present organization -.450 .865 -.520 Ns

Salary per month 1.761 .861 2.045 *

No. of training programs attended -1.318 .892 -1.478 Ns

Maximum no. of hours worked 1.506 1.197 1.259 Ns

Strength Factor Score -1.942 .419 -4.633 **

Human Resource Management practice -3.217 .854 -3.765 **

Table: No.4.148 R and F-Ratio values

R R Square F Sig.

.423 .179 8.500 **

Chapter-IV 225

Result

The multiple correlation co-efficient (R) value was found to be 0.423 which shows that

there is moderate level of correlation between the dependent variable and the set of

independent variables taken together.

The F ratio value (8.500) shows that there is significant relationship between the overall

attrition score and the set of independent variables. The R square value indicates that

17.9% of variation in the overall attrition score is explained by the set of independent

variables included in the model.

Individually, looking at the regression co-efficient, it is seen that age, experience, number

of training programs attended, strength factor, HRM management practice have affected

the overall attrition score negatively. That is the employee’s attitude towards attrition

decreases when these variables are on the higher side. For example, respondents in the

older age group have lesser attitude towards attrition. Also, those who have given higher

scores or ratings for strength factor or HRM management practice, the attrition scores are

lesser.

Salary and number of hours worked affect the attrition score positively. That is, those

who draw higher salary and those who work longer hours have higher level of attrition

than those who draw lesser salary or work lesser hours.

Gender-wise, males have more attrition tendency than females.

Location-wise, Karnataka respondents are found to have more attrition scores than Kerala

employees.

Global position-wise, multinational employees are having higher level of attrition scores

than national employees.

Among all these regression co-efficients, it is found that age, salary, strength factor,

HRM practice significantly affect the attrition scores either at 1% or 5% level.

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