CHAPTER VI

INFLUENCE OF THE LABOUR WELFARE DIMENSIONS ON JOB

SATISFACTION IN INDIAN PHARMACEUTICAL COMPANIES AND

MULTINATIONAL PHARMACEUTICAL COMPANIES IN GOA

6.1 INTRODUCTION

6.2 INFLUENCE OF THE DIMENSIONS OF LABOUR WELFARE

ON THE LEVEL OF JOB SATISFACTION OF EMPLOYEES IN

INDIAN PHARMACEUTICAL COMPANIES AND

MULTINATIONAL PHARMACEUTICAL COMPANIES IN GOA

6.3 PREDICTORS OF JOB SATISFACTION IN INDIAN

PHARMACEUTICAL COMPANIES AND MULTINATIONAL

PHARMACEUTICAL COMPANIES IN GOA: STATUTORY

AND NON-STATUTORY LABOUR WELFARE FACILITIES

6.4 CONCLUSIONS

CHAPTER VI

INFLUENCE OF THE LABOUR WELFARE DIMENSIONS ON JOB

SATISFACTION IN INDIAN PHARMACEUTICAL COMPANIES AND

MULTINATIONAL PHARMACEUTICAL COMPANIES IN GOA

6.1 INTRODUCTION

Labour welfare implies the setting up of minimum desirable standards and the provision

of welfare facilities like health, food, clothing, housing, medical assistance, education,

insurance, job security, recreation and other such facilities that enable the employees to

lead a good work, family and social life.

According to Srivastava (2004) if the environment of the organization helps in satisfying

various needs of the employees, they develop pro or favourable attitude towards the job,

organization and finally towards the management. The provision of labour welfare

facilities develops a positive attitude among employees that not only enhances the

effectiveness of the organization, but also is desirable for their own sake. Thus providing

labour welfare facilities positively influences the job satisfaction of employees.

The proper organization and administration of labour welfare facilities can play a vital

role in promoting better working conditions and standard of living for industrial workers,

as well as enhance their job satisfaction, especially in developing countries.

In the previous chapter it was observed that labour welfare has a significant positive

correlation with job satisfaction. Implying that as labour welfare facilities increase the

240

level of job satisfaction of employees in pharmaceutical companies in Goa are likely to

increase. There may be some dimensions of labour welfare that could influence the job

satisfaction of employees, which employers may need to pay attention to. The researcher

was thus curious to study the influence of the dimensions in the labour welfare inventory

(LWI) that influence the job satisfaction of employees in the pharmaceutical companies in

Goa.

The present chapter intends to focus on:

> Investigating those dimensions of the LWI that influence the level of job

satisfaction of employees in Indian and multinational pharmaceutical companies

in Goa.

> Highlight the significant difference in the statutory and non-statutory labour

welfare facilities in the Indian and multinational pharmaceutical companies in

Goa.

> Examine the influence of the statutory and non-statutory labour welfare facilities

as predictors of job satisfaction in the pharmaceutical companies in Goa.

Accordingly the researcher, in this chapter has made an attempt to study and determine

the influence of the dimensions in the Labour Welfare Inventory on the level of job

satisfaction of employees in Indian and multinational pharmaceutical companies in Goa

and also to examine whether the statutory or non-statutory labour welfare facilities are a

predictor of job satisfaction in these companies.

241

The null hypotheses Ho4 and Ho5 were accordingly framed.

Ho4: The dimensions in the labour welfare inventory do not influence the job

satisfaction of employees in Indian pharmaceutical companies and

multinational pharmaceutical companies in Goa.

Ho5: The statutory labour welfare facilities are not a predictor of job satisfaction

than non-statutory labour welfare facilities in the pharmaceutical companies

in Goa.

The eight dimensions in the LWI include education/training, recreation, medical,

subsidized loans, canteen, housing, safety, and others (uniforms, water facilities, toilets,

retirement benefits, workman's compensation, rest rooms, bonus, travelling allowance,

leave facilities and crèche). These labour welfare dimensions were categorized into

statutory and non—statutory labour welfare facilities. In accordance with the Factories Act

(1948) the statutory labour welfare facilities includes medical facilities, canteen, safety

and others; and the non-statutory labour welfare facilities incorporates education/training,

recreation, subsidized loans, and housing.

242

6.2 INFLUENCE OF THE DIMENSIONS OF LABOUR WELFARE ON THE

LEVEL OF JOB SATISFACTION OF EMPLOYEES IN INDIAN

PHARMACEUTICAL COMPANIES AND MULTINATIONAL

PHARMACEUTICAL COMPANIES IN GOA

The null hypothesis Ho4 states that the dimensions of the labour welfare inventory do not

influence the job satisfaction of employees in Indian pharmaceutical companies and

multinational pharmaceutical companies in Goa. To test the null hypotheses, a correlation

matrix between job satisfaction and labour welfare dimensions, and within the labour

welfare dimensions was constructed as shown in Table 24. This was followed by running

the multiple regression analysis. The findings in the correlation matrix would explain

those dimensions in the LWI that are significantly correlated with job satisfaction of

employees in the pharmaceutical companies in Goa. The multiple regression analysis

would identify those labour welfare dimensions that influence job satisfaction.

The results of the correlation matrix are reported in Table 20.

243

• • • Table 20

• correlation Matrix of JOD Sausracnon ana Lanour Welfare uimensions •

JS

Total

Education &

Training Recreation Medical

Subsidised

Loans Canteen Housing Safety Others MNC Staff Age Sex Experience

JS Total Pearson Correlation 1

- .610

.. .512

.. .506 .462

.. .571

.. .510" .509 .. .571 .. .541

. .556 . .345.. .041 .263

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .566 .00(

N 201 201 201 201 201 201 201

.598

201 201 201 201 201 201 20

Education &

Training

Pearson Correlation .- 610 1

. . .886 .652** .420** .583- .716

.. .679

.. .593

.. .. .423

.. .263

. .179 .064 .06!

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .011 .367 .33

N 201 201 201 201 201 201 201 201 201 201 201 201 201 20

Recreation Pearson Correlation - .512 .886 1 .697** .548** ** .757..

. .612

. .. .608

. .351 .215 .157 .078 .03

Sig. (2-tailed) , .000 .000 .000 .000 .000 .000 .000 .000 .000 .002 .026 .272 .66:

N 201 201 201 201 201 201 201 201 201 201 201 201 201 20

Medical Pearson Correlation .506-

.. .652

.. .697 1

.. .540

.. .555

.. .620

.. .644

.. .583

.. .387 .200

.. .158 .030 .0S

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000 .004 .025 .670 .41

N 201 201 201 201 201 201 201 201 201 201 201 201 201 20

Subsidised

Loans

Pearson Correlation .462- .420** .54-e .540 1 .580** .575** ** .357 ** .486 ** .418 .234- .214** .061 .16z

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000 .001 .002 .393 .02 ,

N 201 201 201 201 201 201 201 201 201 201 201 201 201 20

Canteen Pearson Correlation

.. .571

.. .583

.. .598

.. .555

.. .580 1

. .583

.. .425

.. .582

.. .547

.. .265 .138 .077 .08

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .051 .279 .25:

N 201 201 201 201 201 201 201 201 201 201 201 201 201 20

Housing Pearson Correlation - .510

.. .716

.. .757

- .620

.. .575

- .583 1 ** .504

.. .565 .390

.. .220 .072 .117 -.03'

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000 .002 .312 .099 .58:

N 201 201 201 201 201 201 201 201 201 201 201 201 201 20

JS

Total

Education &

Training Recreation Medical

Subsidised

Loans Canteen Housing Safety Others MNC Staff Age Sex Ex p eriencE

Safety

N

Pearson Correlation .509 .679" .612 .644.. .357.. .425- .504 1 .626 .316 .325.. .160. -.035 .06 ,

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .023 .619 .35

201 201 201 201 201 201 201 201 201 201 201 201 201 20

Others

N

Pearson Correlation .571 .. .593- .608- .583.. .486 .582.* .565.. .626- 1 .354 .313.. .272.. -.009 .195

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .903 .001

201 201 201 201 201 201 201 201 201 201 201 201 201 20

MNC

N

Pearson Correlation .541 .. .423 .351" .387.. .418 .547 .390- .316 .354- 1 .223.. .051 -.095 .09.

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000 .001 .471 .178 .19(

201 201 201 201 201 201 201 201 201 201 201 201 201 20

Staff

N

Pearson Correlation .556- .263- .215 .200 .234 .265- .220- .325.* .313- .223.. 1 .326- .000 .275

Sig. (2-tailed) .000 .000 .002 .004 .001 .000 .002 .000 .000 .001 .000 .990 .00 ,

201 201 201 201 201 201 201 201 201 201 201 201 201 20

Age

N

Pearson Correlation .345.. .179. .157. .158. .214 .138 .072 .160. .272 .051 .326 1 -.204 .894

Sig. (2-tailed) .000 .011 .026 .025 .002 .051 .312 .023 .000 .471 .000 .004 .00(

201 201 201 201 201 201 201 201 201 201 201 201 201 20

Sex

N

Pearson Correlation .041 .064 .078 .030 .061 .077 .117 -.035 -.009 -.095 .000 -.204- 1 -.303

Sig. (2-tailed) .566 .367 .272 .670 .393 .279 .099 .619 .903 .178 .990 .004 .00,

201 201 201 201 201 201 201 201 201 201 201 201 201 20

Experience Pearson Correlation .263.. .069 .031 .058 .164. .081 -.039 .066 .195.. .093 .275.. .894.. -.303..

Sig. (2-tailed) .000 .331 .662 .417 .020 .252 .582 .355 .006 .190 .000 .000 .000

N 201 201 201 201 201 201 201 201 201 201 201 201 201 20

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

From the above Table it can be observed that all the eight labour welfare dimensions are

positively and significantly correlated with job satisfaction at the 0.01 level. This implies

that an increase in any of the labour welfare dimensions is likely to significantly increase

job satisfaction of employees (N=201) in the pharmaceutical companies in Goa. For

instance an increase in education/training will significantly increase the job satisfaction of

the employees. Similarly any increase in recreation facilities, medical facilities,

subsidized loans, canteen, safety, housing, safety, and others would have a significant

influence on the job satisfaction of employees (N=201) in these companies in Goa. Thus

any effort made by the management of pharmaceutical companies in Goa to increase any

labour welfare measure would significantly increase the job satisfaction of their

employees.

Though these eight labour welfare dimensions are significantly correlated to job

satisfaction, it does not mean that all of them are independent of each other. This can be

observed from the correlation matrix, where the eight dimensions of labour welfare are

highly correlated with each other. For example education/training is significantly

correlated with the other seven labour welfare dimensions at the 0.01 level. Likewise

recreation has a significant correlation with the rest of the dimensions of labour welfare.

This could be said for all the labour welfare dimensions that they are highly correlated to

each other at the 0.01 level of significance.

This is but natural because each of these eight dimensions is indeed a composite labour

welfare measure. These are the labour welfare facilities that employers provide and that

employees expect to receive. An employee who receives good education/training would

also like to acquire better recreation facilities, medical facilities, more subsidized loans,

246

improved canteen facilities, housing, safety measures and others. This goes for each of

the other labour welfare dimensions as well, which reveals that each of the labour welfare

dimensions are significantly correlated with one another. These are very strongly

correlated and so they are not independent variables by themselves. It means that the so-

called independent variables are not really independent.

This is an indication of a multi-collinearity problem, which could make the findings of

the study unreliable and lead to large standard errors of the estimators. The problem of

multi-collinearity was further realized when a multiple regression was run with job

satisfaction as the dependent variable and the dimensions of labour welfare as the

independent variables. The results of which are revealed in Table 21. A glance at the

Table confirms that there is a multi-collinearity problem, since the value of the R 2 is very

high (R2 = 0.67) but quite a few of the coefficients of labour welfare are not statistically

significant at the 0.05 level (medical facilities, subsidized loans, canteen, housing and

safety). The rule of thumb is that if the correlation between the regressors is significant,

and if the R2 is high but quite a few of the coefficients are not statistically significant, it is

a sign of a multi-collinearity problem (Gujarati, 2004).

Table 21

Multiple Regression Analysis for Multi-collinearity

Model Summary

Model R R Square Adjusted R

Square Std. Error of the Estimate

1 .823 a .678 .656 10.308 a. Predictors: (Constant), StaffMPCs, Gender, Age, Staff, MPCs, Recreation, Subsidised Loans, Safety, Canteen, Others, Medical, Housing, Education / Training

247

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression

Residual

Total

41822.148

19868.847

61690.995

13

187

200

3217.088

106.251

30.278 .000a

a. Predictors: (Constant), StaffMNC, Gender, Age, Staff, MPCs, Recreation, Subsidised Loans, Safety, Canteen, Others, Medical, Housing, Education/Training

b. Dependent Variable: JS Total

Coefficient?

Model

Unstandardized Coefficients Standardized Coefficients

t Sig. B Std. Error Beta

1 (Constant) 30.766 6.476 4.751 .000

Staff 14.559 2.283 .408 6.376 .000

Gender 2.561 1.575 .072 1.626 .106

Age .271 .102 .127 2.649 .009

Education / Training 1.300 .341 .407 3.808 .000

Recreation -.789 .299 -.284 -2.639 .009

Medical .325 .312 .069 1.043 .298

Subsidised Loans .131 .215 .038 .612 .542

Canteen .272 .257 .068 1.061 .290

Housing .211 .225 .067 .938 .349

Safety -.016 .322 -.003 -.049 .961

Others .374 .151 .158 2.475 .014

MP Cs 11.650 2.433 .329 4.789 .000

StaffMPCs -7.468 3.213 -.179 -2.324 .021

a. Dependent Variable: JS Total

To alleviate this problem of multi-collinearity the researcher tried many specifications

with different combinations of the labour welfare dimensions. This finally led to selecting

248

education/training, and others (uniform, water facilities, toilets, retirement benefits,

compensation, rest-rooms, bonus, travelling allowance, crèche and leave facilities) as the

labour welfare dimensions, since their coefficients were highly significant at the 0.01

level and are thus indicative of influencing job satisfaction. Other independent variables

such as the dummy variables MPCs (Di), gender (D2), staff (D3) and age were also

selected because of their high significant coefficients (0.01 level), which are also

suggestive of them influencing job satisfaction. These independent variables together

would probably be able to explain the maximum variance in job satisfaction. The other

independent variables (recreation, medical, subsidized loans, canteen, housing, safety and

stsff MPCs) were dropped because their coefficients were not found to be significant in

influencing job satisfaction or were found to be highly correlated with education/training

and others. Similar method has been used by researchers in earlier studies (Joshi and

Sharma, 1997; Bhargava and Kelkar, 2000; Afza, 2005; and Randhawa, 2005).

After having selected the independent variables that were indicative of influencing job

satisfaction the researcher once again used the multiple regression analysis to test the null

hypothesis Ho4, the results of which unfold in Table 22.

249

Table 22

Influence of Labour Welfare Dimensions on Job Satisfaction of Employees in Indian

and Multinational Pharmaceutical Companies in Goa

Model Summary

Model R R Square Adjusted R

Square Std. Error of the

Estimate

I .807a .652 .641 10.524

a. Predictors: (Constant), MPCs, Age, Gender, Staff, Others, Education/Training

ANOVAb

Model Sum of Squares df Mean Square F Sig.

I Regression

Residual

Total

40203.393

21487.602

61690.995

6

194

200

6700.566

110.761

60.496 .000a

a. Predictors: (Constant), MPCs, Age, Gender, Staff, Others, Education /Training

b. Dependent Variable: JS Total

Coefficient?

Model '

Unstandardized Coefficients

Standardized Coefficients

t Sig. B Std. Error Beta

I (Constant) 37.530 4.636 8.095 .000

Education /Training .862 .177 .270 4.872 .000

Others .392 .130 .165 3.008 .003

Age .321 .101 .150 3.191 .002

MPCs 10.530 1.708 .297 6.165 .000

Gender 3.008 1.575 .084 1.910 .058

Staff 11.316 1.674 .317 6.761 .000

a. Dependent Variable: JS Total

250

Based on Table 22 the following multiple regression model emerges.

a+ x + 132 X 2 + 133 X 3+134 Di+ 135 D2+ 6 D3 +

Y = Dependent variable (job satisfaction)

a = Constant term

RI 132 • • 136 = Regression coefficient

X1 X2 = Dimensions of labour welfare

X1 = Education / training

X 2 = Others

X 3 = Age

Di = 1 for MPCs

0 for IPCs

D2 = 1 for Female 0 for Male

D3 = 1 for Manager 0 for Worker

c = Error term

The regression equation is

Y= 37.5 + .86 X1+ .39 X2+.32 X3+ 10.5 D1+ 3 D2+ 11.3 D3

( 1 ) Adjusted R2 = 0.64

N=201

For MPCs the regression equation is: (1.1)

Y(Dt= 1)=48+ .86 Xi+.39 X2+.32 X3+3 D2+11.3 D3

For IPCs the regression equation is: (1.2)

Y(D1=0)=37.5 +.86 X1+.39 X2+.32 X3+3 D2+11.3 D3

251

Table 22 and equation (1) emphasize that the coefficients education/training (X 1 ) and

others (X2) influence job satisfaction. The findings show that a one unit increase in

education/training is likely to increase the level of job satisfaction of respondents in IPCs

and MPCs by 86 percent, while a one unit increase in others is most likely to increase the

level of job satisfaction in these companies by 39 percent. Moreover the standardized

coefficient of education/training (0.27) is higher than that of others (0.16). This signifies

that education/training has a higher influence on job satisfaction than others. Furthermore

the coefficients of education/training (X i ) and others (X2) are statistically significant at

the 0.01 level as can be observed from their respective t-values. Thus the null hypothesis

Ho4, which states that the dimensions in the labour welfare inventory do not influence the

job satisfaction of employees in Indian pharmaceutical companies and multinational

pharmaceutical companies in Goa is not accepted.

Researchers have found labour welfare dimensions to influence the job satisfaction of

employees (Joshi and Sharma, 1997; KirissIi et. al., 1992; Khan and Robertson, 1992;

Rahman et. al., 1995; Sinha and Singh, 1995; Rao et. al., 2002)

Given that the labour welfare dimensions of education/training and others influence the

job satisfaction of respondents in the pharmaceutical companies in Goa, a glimpse at

regression equations (1.1) and (1.2) indicates that there is a difference in the level of job

satisfaction in IPCs and MPCs in Goa. The intercept of MPCs is much higher than that of

IPCs signifying that the respondents in MPCs enjoy a higher level of job satisfaction than

their counter parts in IPCs in Goa.

252

Moreover the adjusted R 2 is 0.64. This indicates that 64 percent of the variance in the

perceived level of job satisfaction is explained by the independent variables. This makes

the model a good fit.

It can be concluded from the above discussion that there is a difference in the dimensions

of the labour welfare inventory - education/training and others - that influence the job

satisfaction of employees in Indian pharmaceutical companies and multinational

pharmaceutical companies in Goa. The labour welfare dimension education/training has

more influence on job satisfaction than others.

6.3 PREDICTORS OF JOB SATISFACTION IN PHARMACEUTICAL

COMPANIES IN GOA: STATUTORY AND NON-STATUTORY LABOUR

WELFARE FACILITIES

Organizations are becoming more aware of the importance of providing labour welfare

facilities. The Government has enforced various labour welfare laws, so that the industrial

worker can enjoy better working and living conditions and is happy in the organization.

The labour welfare facilities provided in an organization are statutory and non-statutory in

nature. Which of these labour welfare amenities — statutory/non-statutory — is a predictor

of job satisfaction needs to be investigated. In this study the labour welfare dimensions in

the LWI have been classified into statutory and non-statutory labour welfare facilities.

Medical facilities, canteen, safety and others are the statutory welfare facilities and

education/training, recreation, subsidized loans, and housing are the non-statutory labour

welfare facilities.

253

The present research therefore is an attempt to examine whether the statutory labour

welfare facilities are a predictor of job satisfaction than the non-statutory labour welfare

facilities in the pharmaceutical in Goa. This lead to framing the null hypothesis Ho5,

which states that the statutory labour welfare facilities are not a predictor of job

satisfaction than non-statutory labour welfare facilities in pharmaceutical companies in

Goa.

To test this hypothesis, first the test of significance, t-test was done, which would

determine the existence of a significant difference between the statutory labour welfare

facilities (SLWF) and the non- statutory labour welfare facilities (NSLWF) in IPCs and

MPCs in Goa and then the regression analysis run that would specify whether the SLWF

or the NSLWF are a predictor of job satisfaction in these companies.

Table 23 illustrates the difference in the SLWF and NSLWF for IPCs in Goa.

Table 23

Difference in the Statutory and Non-Statutory Labour Welfare Facilities

in Indian Pharmaceutical Companies in Goa

Mean N Std. Deviation Std. Error Mean

Statutory 85.2870 115 12.83756 1.19711

Non-Statutory 44.7391 115 14.41617 1.34432

Paired Differences

t df

Sig. (2-

tailed) Mean SD

Std. Error Mean

95% Confidence Interval of the

Difference

Lower Upper

Statutory Non-Statutory

4.05478E1 10.58818 .98735 38.59189 42.50376 41.067 114 .000

254

From Table 23 it can be realized that for the IPCs in Goa there is a difference in the

provision of SLWF and NSLWF and this difference is statistically significant at the 0.01

level, as the t-value is 41.067 (P<0.01). It implies that the SLWF are provided to a

significantly greater extent than the NSLWF in IPCs in Goa.

Furthermore when the test of significance was extended to the MPCs in Goa the results

were found to be similar. The MPCs too demonstrated a significant difference in the

SLWF and NSLWF. This can be observed in Table 24.

Table 24

Difference in the Statutory and Non-Statutory Labour Welfare Facilities

in Multinational Pharmaceutical Companies in Goa.

Mean N Std. Deviation Std. Error Mean Statutory 1.0069E2 86 15.54520 1.67628

Non-Statutory 62.5000 86 20.50351 2.21095

Paired Differences

t df

Sig. (2- tailed) Mean SD

Std. Error Mean

95% Confidence Interval of the

Difference Lower Upper

Statutory Non- Statutory

3.81860E1 12.46124 1.34373 35.51435 40.85774 28.418 85 .000

The Table illustrates that in MPCs there is a statistically significant difference in the

SLWF and the NSLWF at the 0.01 level, the t-value being 28.418 (P<0.01). This means

that the SLWF are significantly better provided to the employees than the NSLWF in

MPCs in Goa.

Pr'

255

From the findings of the above two Tables 23 and 24 it can be concluded that in IPCs and

MPCs in Goa it is the SLWF that are significantly superior than the NSLWF. This could

perhaps be because these pharmaceutical companies take utmost care to provide those

labour welfare facilities that are mandatory and required by the law. They offer their

employees SLWF to a greater extent than NSLWF because they probably do not want to

get on the wrong side of the law and get into any litigation. Thus the SLWF are provided

to a greater extent than the NSLWF in IPCs and MPCs in Goa. The pharmaceutical

companies in Goa therefore follow the Policing theory of labour welfare, wherein the

management provides labour welfare facilities under the fear of punishment by the State.

The labour welfare facilities provided has become a legal /statutory responsibility of the

employer.

Having found that there is a statistically significant difference in the SLWF and NSLWF

in IPCs and MPCs in Goa, the researcher was curious to investigate whether the SLWF or

the NSLWF are a predictor of job satisfaction in pharmaceutical companies in. Goa. To

test the null hypothesis Ho5, which states that the statutory labour welfare facilities are

not a predictor of job satisfaction than non-statutory labour welfare facilities in

pharmaceutical companies in Goa, the multiple regression analysis was applied. The

results of the same are revealed in Table 25.

256

Table 25

Statutory and Non-Statutory Labour Welfare Facilities as Predictor of

Job Satisfaction of Employees in Pharmaceutical Companies in Goa

Model Summary

Model R R Square Adjusted R

Square Std. Error of the Estimate

I .802a .644 .633 10.646

a. Predictors: (Constant), Age, MPCs, Gender, Staff, Non-Statutory labour welfare facilities, Statutory labour welfare facilities.

ANOVAb

Model Sum of Squares df Mean Square F Sig.

I Regression

Residual

Total

39703.542

21987.453

61690.995

6

194

200

6617.257

113.337

58.385 .000a

a. Predictors: (Constant), Age, MPCs, Gender, Staff, Non-Statutory labour welfare facilities, Statutory labour welfare facilities

b. Dependent Variable: JS Total

Coefficient?

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig. B Std. Error Beta

I (Constant)

Non-Statutory

Statutory

Age

MPCs

Gender

Staff

33.296 5.794 5.746 .000

.143 .067 .158 2.131 .034

.276 .084 .251 3.293 .001

.335 .101 .157 3.320 .001

9.853 1.781 .278 5.533 .000

2.893 1.605 .081 1.802 .073

11.225 1.699 .315 6.607 .000

a. Dependent Variable: JS Total

257

Based on Table 25 the following multiple regression model emerges.

Y= a+ x + 132 X 2 + 133 X 3+ fit D i + 135 D2+ 6 D3 + E

Y = Dependent variable (job satisfaction)

a = Constant term

13 1 132 • • ••• = Regression coefficient

X = Non-statutory labour welfare facilities

X 2 = Statutory labour welfare facilities

X 3 = Age

Di = 1 for MPCs 0 for IPCs

D2 = 1 for Female 0 for Male

D3 = 1 for Manager 0 for Worker

= Error term

The regression equation is

Y= 33.2 +.14 X1+.27 X 2 +.33 X3+ 9.8131+ 2.8 D2 + 11.2 D3 (2)

Adjusted R2 = 0.63 N=201

For MPCs the regression equation stands as: (2.1)

Y(Di= 1)=43 + .14 Xl+.27 X2 +.33 X3 + 2.8 D2 +11.2D3

For 1PCs the regression equation is: (2.2)

Y (Di= 0) = 33.2 + .14 X 1+ .27 X 2 + .33 X 3 + 2.8 D2+ 11.2 D3

From Table 25 and regression equation (2) it is obvious that the SLWF (X 2) is a predictor

of job satisfaction than the NSLWF (Xi) in the pharmaceutical companies in Goa. This is

because a one unit increase in the SLWF is likely to increase the job satisfaction of the

respondents in the pharmaceutical companies by 27 percent, while a one unit increase in

the NSLWF is likely to increase the job satisfaction of the respondents in these companies

by 14 percent. Moreover in the pharmaceutical companies the SLWF have a better

influence on job satisfaction than the NSLWF, as the standard coefficient of SLWF (0.25)

is greater than the standard coefficients of NSLWF (0.15). This signifies that the SLWF

have a larger influence on job satisfaction than the NSLWF in the pharmaceutical

companies in Goa. Since the SLWF are a better predictor of job satisfaction than non-

statutory labour welfare facilities in pharmaceutical companies in Goa the null hypothesis

Ho5 is not accepted.

While comparing the IPCs and MPCs in Goa, the regression equations (2.1) and (2.2)

specify that the MPCs in Goa experience a higher level of job satisfaction than the IPCs,

given that the SLWF are a better predictor of job satisfaction than the NSLWF. This can

be noticed from the intercepts of the MPCs, which is higher than that of IPCs.

Moreover the adjusted R2 is 0.63, which makes the regression a good fit, since 63 percent

of the variance in the perceived level of job satisfaction is explained by the independent

variables.

To conclude it can be said that the SLWF are a predictor of job satisfaction than NSLWF

in pharmaceutical companies in Goa. It is thus important that if the employers of

pharmaceutical companies want to further increase the level of job satisfaction level of

q0„

their employees then they need to pay special attention to the SLWF which have emerged

as a predictor of job satisfaction of employees than NSLWF.

6.4 CONCLUSIONS

In this chapter the researcher analyzed the influence of the dimensions of labour welfare

on the job satisfaction of employees in IPCs and MPCs in Goa. The statutory/non-

statutory labour welfare facilities as a predictor of job satisfaction in pharmaceutical

companies was also observed. Based on the findings in this chapter the following

conclusions can be drawn:

■ The eight dimensions of labour welfare were positively and significantly

correlated with job satisfaction. An increase in any of the labour welfare

dimensions would significantly increase job satisfaction of employees in the

pharmaceutical companies in Goa. If the pharmaceutical companies improve the

welfare facilities for their employees then the job satisfaction of their employees

would greatly increase.

■ Two labour welfare dimensions - education/training, and others — were found to

be indicative of influencing job satisfaction. Education/training were more

influential in influencing the job satisfaction of employees than others in the IPCs

and MPCs in Goa.

■ There was a significant difference between the SLWF and NSLWF provided in

the IPCs and MPCs in Goa. The SLWF emerged as significantly better provided

than the NSLWF in both the IPCs and MPCs in Goa.

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■ The SLWF emerged as a better predictor of job satisfaction than NSLWF in the

pharmaceutical companies in Goa. The SLWF influenced the job satisfaction of

employees to a greater extent than NSLWF in these companies.

■ The employees in MPCs were found to experience a higher level of job

satisfaction that their fellow mates in 1PCs, given the labour welfare facilities,

including the SLWF and NSLWF. The IPCs need to therefore work towards

increasing the job satisfaction of their employees.

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