A Study on Quality of work life in it sector: Its Impact on Employee Productivity
Monika Sharma
Assistant Professor, Delhi Institute of Advanced Studies
ABSTRACT:
In modern era, it has been observed that stress management has become one of the most substantial concepts in the professional environment. It is also seen that working efficiency has degraded to some extent as professionals are unable to maintain a balance between their personal and professional lives. This difference has made organizations to formulate such policies that lead to better job performance which results in job satisfaction moreover employee satisfaction. This degree of satisfaction has been referred to as Quality Of Work Life. Quality of work life is a process in an organization which enables its members at all levels to participate actively and effectively in shaping organizational environment, methods and outcomes. This study focuses on the subjective matter of QWL i.e. its key elements like job security, job performance, employee satisfaction etc.
KEYWORDS: Quality of work life, job performance, employee satisfaction, job security.
INTRODUCTION:
In a highly competitive work environment, there is great pressure on professionals to not just perform, but excel. There is also excessive expectation from their organisations to increase productivity at any cost. This takes its toll on the physical and mental well-being of professionals. In fact, striking a right balance between work and life is better said than done.
Effective HR activities can help employees to enjoy their work as well as not neglect their personal life. The obvious benefits for the organisation are—higher productivity, lower staff turnover, reduction in absenteeism and better utilization of talent.
One of the more stressful professions today is in the Information Technology (IT) field. Not long ago, IT professionals were extremely well respected and in demand. As technology advanced rapidly, there was a high demand for programmers and engineers. Most had their choice of high-paying jobs as technology companies competed to recruit the best of them. Technological advances further help organizations to implement these programs successfully. Organizations are enjoying the fruits of implementing QWL programs in the form of increased productivity, and an efficient, satisfied, and committed workforce which aims to achieve organizational objectives. The future work world will also have more women entrepreneurs and they will encourage and adopt QWL programs.
LITERATURE REVIEW:
According to Walton (1975) proposed eight conceptual categories. They are as follows:
· Adequate and fair compensation
· Safe and healthy working conditions
· Immediate opportunity to use and develop human capacities
· Opportunity for continued growth and security
· Social integration in the work organization
· Constitutionalizing in the work organization
· Work and the total life span
· The social relevance of work life
QWL, refers to the level of satisfaction, motivation, involvement and commitment individuals experience with respect to their lives at work. (Bernardin) (VSP Rao, 2007)
According to Rethinam (2008), QWL is a multi-dimensional construct, made up of a number of interrelated factors that need careful consideration to conceptualize and measure. It is associated with job satisfaction, job involvement, motivation, productivity, health, safety and well-being, job security, competence development and balance between work and non-work life and also he concluded as QWL from the perspective of IT professionals is challenging both to the individuals and organizations.
“Quality of work life is the degree to which members of a work organization are able to satisfy important personal needs through their experiences in the organizations” (Lloyd Suttle).
Table 1. Components of QWL in the view of different researchers along with the type ofindustries
|
Author |
Component |
Type of the Industries |
Out comes |
|
|
|
||||
|
Walton (1975) USA |
1.Adequate and Fair Compensation, 2.Safe and Healthy Working Conditions, 3.Immediate Opportunity to use and Develop Human 4. Capacities, Opportunity for Continued Growth and Security, 6. Social Integration in The WorkOrganization, 7. Constitutionalism in The Work Organization, 8. Work and Total Life Space And 9. Social Relevance Of Work Life. |
Service |
All |
these |
|
|
industries |
components |
||
|
|
are |
the |
||
|
|
associated with |
|||
|
|
QWL |
|
||
|
Levine, Taylor and Davis (1984) Europe |
1. Respect from supervisor and trust on employee’s capability; 2. Change of work; 3. Challenge of the work; 4. Future development opportunity arising from the current 5. work; 6. Self esteem; 7. Scope of impacted work and life beyond work itself; 8. Contribution towards society from the work |
Insurance Company |
QWL Policies may vary as per the size of the organization and employees group |
|
|
Mirvis and Lawler (1984) UK |
1. Safe work environment, 2. Equitable wages, 3. Equal employment opportunities and 4. Opportunities for advancement |
Corporation service |
QWL was associated with satisfaction, wages, hours and working condition |
|
|
Baba and Jamal (1991) UK |
1. Job satisfaction, 2. Job involvement, 3. Work role ambiguity, 4. Work role conflict, 5. Work role overload, 6. Job stress, 7. Organizational commitment and 8. Turn-over intentions |
Nurses in Hospital |
Monotony in the job due to routine work activities can affect QWL Negatively |
|
|
Lau and Bruce (1998) US |
1. Job security 2. Reward systems 3. Training 4. Carrier advancements opportunities 5. Participation in decision in decision making |
Manufacturing industries |
QWL is workplace strategies, operations and environment that promote and maintain employees satisfaction |
|
|
Ellis and Pompli (2002) Canberra |
1. Poor working environments, 2. Resident aggression, 3. Workload, inability to deliver quality of care preferred, 4. Balance of work and family, |
Nurses in Hospital |
All these factors associated with Job dissatisfaction |
|
OBJECTIVES:
· To study the relationship between Quality of work life and Employee Productivity for the purpose of understanding importance of QWLprogrammes.
· To analyze the criterias for quality of work life in IT Industry & its impact on productivity.
· To enhance areas of improvement for better productivity.
· To provide suggestions on why it is important for conducting a QWL programme in an IT industry.
· To interpret and document the findings of the pilot test and to provide suggestions and recommendations for further analysis.
HYPOTHESIS:
HO= The Quality of work life does not affect the employee productivity
Ha= The Quality of work life affects the employee productivity
The research type used is exploratory research and the sample taken is employees of IT sector. Convenience sampling is being used picking up the sample for research.
METHODS OF DATA COLLECTION:
Primary Data:
The data which is collected in the raw form. And it is directly form the respondents. These are mainly the findings of the study.
The primary data used for this project are:
Questionnaire-A questionnaire has been designed, wherein the respondents were asked to answer. It contained 3 sections. It has been answered by 100 employees of different designations corresponding to 20 quality of work life factors.
SPSS-It is software used for statistical analysis and interpretation of the data. The SPSS version 16.0 was used for this project.
SECONDARY DATA:
The data which is not in the raw form and is collected from some sources. These sources have some ideas about the study. Here neither the respondents nor the analysis is directly involved.
The secondary data used for this project are:
· Books
· Journals
· Newspapers
· Magazines
· Websites
STATISTICAL TOOL USED:
Correlation:
Correlation analysis tries to measure the magnitude and direction of relationship between two variables. Multiple and partial correlation analysis extend the same notion between a single variable and a set of variables. Measurement of relationship or association between two or more variables is carried out by correlation analysis. If we have data on two variables we are said to have a bivariate sample and in cases where we have data for more than two variables, we call it multivariate sample.
There are different methods for studying bivariate and multivariate samples. For bivariate samples we usually apply the following methods:
· Cross Tabulation
· Spearman’s coefficient of correlation
· Karl Pearson’s coefficient of correlation
Karl Pearson’s coefficient of correlation is considered as a better alternative. Under this method, coefficient of correlation is determined by the following formula:
∑XY
r = ----------
Nσxσy
∑XY= product of deviations
N = No. of observations (pair of items)
σx=Standard deviation of X
σy= Standard deviation of Y
r = Coefficient of correlation
But instead of representing the same in above in above order, for simple understanding, we can restate it as follows:
∑XY
r= ------------
√∑X2√Y2
The following steps are necessary to compute Pearsonian coefficient of correlation.
i. Calculation of mean deviations of individual pair (X and Y)
ii. Squaring of mean deviations of individual pairs
iii. Multiplying the mean deviations of individual pairs to find out the product of deviations
The Pearson correlation coefficient measures the degree of linear association between two variables.it varies between
· 1.00 and 1.00, with 0 representing absolutely no association between the two variables.
· 1.00 or 1.00 representing a perfect link between two variables.
The higher the correlationcoefficient, the stronger the level of association between two variables. The correlation coefficient can be either positive or negative, depending on the direction of the relationship between two variables.
If there is a negative correlation coefficient between X and Y, that means that increase in the value of Y are associated with decrease in the value of X, and vice versa.
The null hypothesis for the Pearson correlation states that there is no association between the two variables in the population and the correlation coefficient is zero. Elation coefficient can be either positive or negative, depending on the direction of the relationship between two variables.
If there is a negative correlation coefficient between X and Y, that means that increase in the value of Y are associated with decrease in the value of X, and vice versa.
The null hypothesis for the Pearson correlation states that there is no association between the two variables in the population and the correlation coefficient is zero.
Research Type
Exploratory research
Sample Procedure:
Universe: The employees of IT sector.
Population: The employees of who have attended the Quality of Work life (QWL) programmes earlier.
Sample Frame:
· Sample unit–100 employees
· Sample design–Convenience sampling.
ANALYSIS:
FREQUENCIES:
|
Statistics |
|||||
|
|
|
Dsgntn |
Gender |
Exprenc |
Age |
|
N |
Valid |
100 |
100 |
100 |
100 |
|
Missing |
0 |
0 |
0 |
0 |
|
|
Mean |
3.14 |
1.47 |
1.37 |
1.43 |
|
|
Median |
3.00 |
1.00 |
1.00 |
1.00 |
|
|
Mode |
3 |
1 |
1 |
1 |
|
|
Std. Deviation |
1.155 |
.502 |
.747 |
.891 |
|
|
Sum |
314 |
147 |
137 |
143 |
|
DESIGNATION:
|
Dsgntn |
|||||
|
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
Valid |
Sr. consultant |
9 |
9.0 |
9.0 |
9.0 |
|
Consultant |
20 |
20.0 |
20.0 |
29.0 |
|
|
Technical Analyst |
32 |
32.0 |
32.0 |
61.0 |
|
|
Programmer Analyst |
26 |
26.0 |
26.0 |
87.0 |
|
|
Programmer Analyst Trainee |
13 |
13.0 |
13.0 |
100.0 |
|
|
Total |
100 |
100.0 |
100.0 |
|
|
EXPERIENCE:
|
Exprenc |
|||||
|
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
Valid |
1-5yrs |
76 |
76.0 |
76.0 |
76.0 |
|
6-10yrs |
13 |
13.0 |
13.0 |
89.0 |
|
|
10-15yrs |
10 |
10.0 |
10.0 |
99.0 |
|
|
16 and above |
1 |
1.0 |
1.0 |
100.0 |
|
|
Total |
100 |
100.0 |
100.0 |
|
|
GENDER
|
Gender |
|||||
|
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
Valid |
male |
53 |
53.0 |
53.0 |
53.0 |
|
female |
47 |
47.0 |
47.0 |
100.0 |
|
|
Total |
100 |
100.0 |
100.0 |
|
|
AGE
|
Age |
|||||
|
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
Valid |
20-29 |
74 |
74.0 |
74.0 |
74.0 |
|
30-39 |
16 |
16.0 |
16.0 |
90.0 |
|
|
40-49 |
6 |
6.0 |
6.0 |
96.0 |
|
|
50 and above |
4 |
4.0 |
4.0 |
100.0 |
|
|
Total |
100 |
100.0 |
100.0 |
|
|
DESCRIPTIVE STATISTICS:
|
Descriptive Statistics |
|||||
|
|
N |
Minimum |
Maximum |
Mean |
Std. Deviation |
|
Benefits |
100 |
3 |
5 |
4.26 |
.733 |
|
JobSec |
100 |
2 |
5 |
4.31 |
.813 |
|
Flexitime |
100 |
2 |
5 |
4.18 |
.857 |
|
WLBal |
100 |
1 |
5 |
4.14 |
.841 |
|
PrcptMgt |
100 |
2 |
5 |
3.73 |
.941 |
|
Recgn |
100 |
2 |
5 |
4.13 |
.825 |
|
Funatwrk |
100 |
1 |
5 |
3.50 |
1.176 |
|
Prsnlgrth |
100 |
2 |
5 |
4.20 |
.853 |
|
CarGrth |
100 |
1 |
5 |
4.12 |
1.066 |
|
FairCmpn |
100 |
2 |
5 |
4.08 |
.992 |
|
OrgInv |
100 |
2 |
5 |
3.85 |
.892 |
|
TrngOpp |
100 |
2 |
5 |
3.95 |
.880 |
|
SupvSprt |
100 |
1 |
5 |
3.87 |
.872 |
|
PeerSprt |
100 |
1 |
5 |
3.70 |
1.000 |
|
Involmnt |
100 |
1 |
5 |
3.59 |
1.093 |
|
WrkStres |
100 |
1 |
5 |
3.05 |
1.359 |
|
WrkCond |
100 |
1 |
5 |
3.81 |
.992 |
|
JobStcftn |
100 |
2 |
5 |
4.04 |
.887 |
|
LeaveOpt |
100 |
1 |
5 |
3.55 |
.947 |
|
WrkGrp |
100 |
1 |
5 |
3.34 |
1.007 |
|
Valid N (listwise) |
100 |
|
|
|
|
Correlations
Correlation Between Different QWL Factors And Employee Productivity
1. Correlation between Benefits and Employee productivity
|
Correlations |
|||
|
|
|
Benefits |
RELTN |
|
Benefits |
Pearson Correlation |
1.000 |
.349** |
|
Sig. (2-tailed) |
|
.000 |
|
|
N |
100.000 |
100 |
|
|
RELTN |
Pearson Correlation |
.349** |
1.000 |
|
Sig. (2-tailed) |
.000 |
|
|
|
N |
100 |
100.000 |
|
**. Correlation is significant at the 0.01 level (2-tailed).
Interpretation: Benefits and employee productivity are related with 0.349 correlation
2. Correlation between Job Security and employee productivity
|
Correlations |
|||
|
|
|
JobSec |
RELTN |
|
JobSec |
Pearson Correlation |
1.000 |
.126 |
|
Sig. (2-tailed) |
|
.212 |
|
|
N |
100.000 |
100 |
|
|
RELTN |
Pearson Correlation |
.126 |
1.000 |
|
Sig. (2-tailed) |
.212 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Job security and employee productivity are related with 0.126 correlation
3. Correlation between Flexitime and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
Flexitime |
|
RELTN |
Pearson Correlation |
1.000 |
.214* |
|
Sig. (2-tailed) |
|
.033 |
|
|
N |
100.000 |
100 |
|
|
Flexitime |
Pearson Correlation |
.214* |
1.000 |
|
Sig. (2-tailed) |
.033 |
|
|
|
N |
100 |
100.000 |
|
*Correlation is significant at the 0.05 level (2-tailed).
Interpretation: Flexitime and employee productivity are related with 0.214 correlation
4. Correlation between Work and life balance and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
WLBalance |
|
RELTN |
Pearson Correlation |
1.000 |
.194 |
|
Sig. (2-tailed) |
|
.053 |
|
|
N |
100.000 |
100 |
|
|
WLBalance |
Pearson Correlation |
.194 |
1.000 |
|
Sig. (2-tailed) |
.053 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Work and life balance and employee productivity are related 0.194 correlation
5. Correlation between Participative Management and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
PrcptMgt |
|
RELTN |
Pearson Correlation |
1.000 |
.224* |
|
Sig. (2-tailed) |
|
.025 |
|
|
N |
100.000 |
100 |
|
|
PrcptMgt |
Pearson Correlation |
.224* |
1.000 |
|
Sig. (2-tailed) |
.025 |
|
|
|
N |
100 |
100.000 |
|
|
|
|||
*Correlation is significant at the 0.05 level (2-tailed).
Interpretation: Participative Management and employee productivity are related 0.224correlation
6. Correlation between Recognition and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
Recgn |
|
RELTN |
Pearson Correlation |
1.000 |
.218* |
|
Sig. (2-tailed) |
|
.029 |
|
|
N |
100.000 |
100 |
|
|
Recgn |
Pearson Correlation |
.218* |
1.000 |
|
Sig. (2-tailed) |
.029 |
|
|
|
N |
100 |
100.000 |
|
*Correlation is significant at the 0.05 level (2-tailed).
Interpretation: Recognition and employee productivity are related with 0.218correlation
7. Correlation between Fun at workplace and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
Funatwrk |
|
RELTN |
Pearson Correlation |
1.000 |
.025 |
|
Sig. (2-tailed) |
|
.802 |
|
|
N |
100.000 |
100 |
|
|
Funatwrk |
Pearson Correlation |
.025 |
1.000 |
|
Sig. (2-tailed) |
.802 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Fun at workplace and employee productivity are related with 0.025correlation
8. Correlation between Personal growth opportunities and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
Prsnlgrth |
|
RELTN |
Pearson Correlation |
1.000 |
.029 |
|
Sig. (2-tailed) |
|
.772 |
|
|
N |
100.000 |
100 |
|
|
Prsnlgrth |
Pearson Correlation |
.029 |
1.000 |
|
Sig. (2-tailed) |
.772 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Personal growth opportunities and employee productivity are related with 0.025correlation.
9. Correlation between Career growth opportunities and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
CarGrth |
|
RELTN |
Pearson Correlation |
1.000 |
.189 |
|
Sig. (2-tailed) |
|
.059 |
|
|
N |
100.000 |
100 |
|
|
CarGrth |
Pearson Correlation |
.189 |
1.000 |
|
Sig. (2-tailed) |
.059 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Career growth opportunities and employee productivity are related with 0.189correlation.
10. Correlation between Fair Compensation and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
FairCmpn |
|
RELTN |
Pearson Correlation |
1.000 |
-.058 |
|
Sig. (2-tailed) |
|
.568 |
|
|
N |
100.000 |
100 |
|
|
FairCmpn |
Pearson Correlation |
-.058 |
1.000 |
|
Sig. (2-tailed) |
.568 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Fair compensation and employee productivity are not related with -0.058correlation.
11. Correlation betweenOrganizational Involvement and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
OrgInv |
|
RELTN |
Pearson Correlation |
1.000 |
.134 |
|
Sig. (2-tailed) |
|
.183 |
|
|
N |
100.000 |
100 |
|
|
OrgInv |
Pearson Correlation |
.134 |
1.000 |
|
Sig. (2-tailed) |
.183 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Organizational Involvement and employee productivity are related with 0.134 correlation
12. Correlation between Training oppurtunities and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
TrngOpp |
|
RELTN |
Pearson Correlation |
1.000 |
.292** |
|
Sig. (2-tailed) |
|
.003 |
|
|
N |
100.000 |
100 |
|
|
TrngOpp |
Pearson Correlation |
.292** |
1.000 |
|
Sig. (2-tailed) |
.003 |
|
|
|
N |
100 |
100.000 |
|
**Correlation is significant at the 0.01 level (2-tailed).
Interpretation: Training opportunities and employee productivity are related with 0.292 correlations.
13. Correlation between Supervisory support and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
SupvSprt |
|
RELTN |
Pearson Correlation |
1.000 |
.186 |
|
Sig. (2-tailed) |
|
.064 |
|
|
N |
100.000 |
100 |
|
|
SupvSprt |
Pearson Correlation |
.186 |
1.000 |
|
Sig. (2-tailed) |
.064 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Supervisory support and employee productivity are related with 0.186 correlations
14. Correlation between support from peers and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
PeerSprt |
|
RELTN |
Pearson Correlation |
1.000 |
.239* |
|
Sig. (2-tailed) |
|
.016 |
|
|
N |
100.000 |
100 |
|
|
PeerSprt |
Pearson Correlation |
.239* |
1.000 |
|
Sig. (2-tailed) |
.016 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: support from peers and employee productivity are related with 0.239 correlation
15. Correlation between Involvement and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
Involmnt |
|
RELTN |
Pearson Correlation |
1.000 |
.303** |
|
Sig. (2-tailed) |
|
.002 |
|
|
N |
100.000 |
100 |
|
|
Involmnt |
Pearson Correlation |
.303** |
1.000 |
|
Sig. (2-tailed) |
.002 |
|
|
|
N |
100 |
100.000 |
|
**Correlation is significant at the 0.01 level (2-tailed).
Interpretation: Involvement and employee productivity are related with 0.303 correlation
16. Correlation between Stress at work and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
WrkStres |
|
RELTN |
Pearson Correlation |
1.000 |
.051 |
|
Sig. (2-tailed) |
|
.617 |
|
|
N |
100.000 |
100 |
|
|
WrkStres |
Pearson Correlation |
.051 |
1.000 |
|
Sig. (2-tailed) |
.617 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Stress at work and employee productivity are related with 0.051 correlation
17. Correlation between Working conditions and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
WrkCond |
|
RELTN |
Pearson Correlation |
1.000 |
-.162 |
|
Sig. (2-tailed) |
|
.106 |
|
|
N |
100.000 |
100 |
|
|
WrkCond |
Pearson Correlation |
-.162 |
1.000 |
|
Sig. (2-tailed) |
.106 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Working conditions and employee productivity are not related with-0.162 correlations
18. Correlation between Job satisfaction and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
JobStcftn |
|
RELTN |
Pearson Correlation |
1.000 |
-.094 |
|
Sig. (2-tailed) |
|
.354 |
|
|
N |
100.000 |
100 |
|
|
JobStcftn |
Pearson Correlation |
-.094 |
1.000 |
|
Sig. (2-tailed) |
.354 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Job satisfaction and employee productivity are not related with-0.094 correlation
19. Correlation between Adequate leave options and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
Leave Opt |
|
RELTN |
Pearson Correlation |
1.000 |
-.131 |
|
Sig. (2-tailed) |
|
.194 |
|
|
N |
100.000 |
100 |
|
|
LeaveOpt |
Pearson Correlation |
-.131 |
1.000 |
|
Sig. (2-tailed) |
.194 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Adequate leave options and employee productivity are not related with-0.131 correlations.
20. Correlation between Autonomous work groups and employee productivity
|
Correlations |
|||
|
|
|
RELTN |
WrkGrp |
|
RELTN |
Pearson Correlation |
1.000 |
.068 |
|
Sig. (2-tailed) |
|
.501 |
|
|
N |
100.000 |
100 |
|
|
WrkGrp |
Pearson Correlation |
.068 |
1.000 |
|
Sig. (2-tailed) |
.501 |
|
|
|
N |
100 |
100.000 |
|
Interpretation: Autonomous work groups and employee productivity are related with 0.68 correlations.
INTERPRETATION:
Interpretation is facilitated by correlating the various factors for QWL and relating it to employee productivity.QWL factors independently affects the employee productivity in an organization.
Following interpretations can be derived from the study:-
· Few QWL factors should be emphasized in an organization like Benefits, Job Security, Flexitime,Work and life balance etc. so that employee productivity increases.
· Fair compensation, working conditions, job satisfaction and adequate leave options though are very useful for improving quality of work life but are not an active player in increasing employee productivity.
Thus, Quality of work life has an impact on employee productivity and both of them have a correlation of 0.24092436 (Annexure)
Various other interpretations can be derived from the SECTION III of the questionnaire.
Are any Quality of work life (QWL) programmers conducted in your organization?
|
S_3 |
|||||
|
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
Valid |
No |
23 |
23.0 |
23.0 |
23.0 |
|
Yes |
77 |
77.0 |
77.0 |
100.0 |
|
|
Total |
100 |
100.0 |
100.0 |
|
|
Do you think QWL programmes, will help in bringing out change in productivity?
|
S_3_1 |
|||||
|
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
Valid |
Didn’t attend QWL programme |
23 |
23.0 |
23.0 |
23.0 |
|
Strongly Disagree |
2 |
2.0 |
2.0 |
25.0 |
|
|
Disagree |
1 |
1.0 |
1.0 |
26.0 |
|
|
No Opinion |
16 |
16.0 |
16.0 |
42.0 |
|
|
Agree |
35 |
35.0 |
35.0 |
77.0 |
|
|
Strongly Agree |
23 |
23.0 |
23.0 |
100.0 |
|
|
Total |
100 |
100.0 |
100.0 |
|
|
Here the respondents who have attended the QWL programme gave their response on their productivity level.
A large population of employees agrees that QWL programmes have enhanced their productivity.
This question was used as a variable for correlating the QWL factors which helps in employee productivity.
Do you find any usefulness after attending earlier QWL programs?
|
S_3_2 |
|||||
|
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
Valid |
Didn’t attend QWL programme |
23 |
23.0 |
23.0 |
23.0 |
|
Yes |
68 |
68.0 |
68.0 |
91.0 |
|
|
No |
9 |
9.0 |
9.0 |
100.0 |
|
|
Total |
100 |
100.0 |
100.0 |
|
|
Respondents who have attended the QWL programmes find that it has a great usefulness and they are quite satisfied with it.
According to you which programme should be given more attention?
|
S_3_3 |
|||||
|
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
Valid |
Didn’t attend QWL programme |
23 |
23.0 |
23.0 |
23.0 |
|
Training Programme |
19 |
19.0 |
19.0 |
42.0 |
|
|
QWL Programme |
45 |
45.0 |
45.0 |
87.0 |
|
|
Issue Oriented Programmes |
13 |
13.0 |
13.0 |
100.0 |
|
|
Total |
100 |
100.0 |
100.0 |
|
|
Respondents who have attended earlier QWL programmes agree with the fact and need of more and more QWL programmes in the organization as compared to Training programme and Issue oriented programme.
Thus, the alternate hypothesis is accepted, and the null hypothesis is rejected.
CONCLUSION:
To conclude we can say that the success of any organization is highly dependent on how it attracts, recruits, motivates, and retains its workforce. Today's organizations need to be more flexible so that they are equipped to develop their workforce and enjoy their commitment. Therefore, organizations are required to adopt a strategy to improve the employees’ ‘quality of work life'(QWL) to satisfy both the organizational objectives and employee needs.
Regular assessment of Quality of Working Life can potentially provide organisations with important information about the welfare of their employees, such as job satisfaction, general well-being, work-related stress and the home-work interface Employees in the future will likely be looking for corporations that have a new work environment, one that encourages each employee to work toward improvement in the product or service; gives employees the responsibility and authority to make decisions, provides timely feedback, and rewards employees based upon the quality of the product and efforts. Team effort will assume central importance, especially that of self-directed work teams. Employees will choose employers who have aims and values that match theirs and who value balance in their employees' lives. Employees want to learn and advance, so opportunities for professional growth will attract employees.
It is true that productivity is driven by several factors, but organizations have started realizing the significance of providing a culture that is more holistic. Unlike our counterparts in the West, we Indians are not really oriented towards striking that elusive work-life balance. It is heartening to observe that this consciousness has now started taking shape in our minds and has acted as a driver for corporates to design innovative and effective strategies for work-life balance.
A supportive and fun environment is must for any organisation to maintain the work-life balance in the lives of its employees, spending quality time is always more important than just spending time.
LIMITATIONS OF THE STUDY:
Even though it was very interactive and interesting part on my job but, a few limitations still exists.
The limitations to this project are:-
· All respondents were seldom not fair in their responses
· Some respondents were reluctant
· Sample size could have been increased
· The data collected sometimes deviate from the actual scenario or the actual picture may be totally different.
· It was a tedious process to explain the employees about the whole project and some of the Quality of work life factors and QWL programmes.
· In an IT sector to take few minutes from the employees was a challenging job.
Books:
1. Rao V.S.P;2007,2nd Ed; “Participation and Empowerment”; Human Resources Management; p 544-547
2. Carter c.c., 1994 Human Resources management and The Total Quality imperative, New York,AMACOM
3. Malhotra Naresh K,2007, ,5thEd“Correlation and Regression”, Marketing Research,p534-546
4. Foy nancy,1996, “The Empowering Organisation”, Empowering People at work,p3-9
5. Deb tapomoy,2006 “Quality of Work Life”,Human Resource Development,o 425-460
6. Chhabra T.N,2003, “Qualty of Working Life and quality Circles”, Human Resource Management,p 485-499
7. Bhatia S.K, Singh Nirmal, 2001,2nd Ed, “Quality of working life-Concept”, Personnel Management/ Human Resource Management,p 138-147
INTERNET SOURCES:
· http://www.scipub.org/fulltext/jss/jss2261-67.pdf
· http://www.eurojournals.com/ejss_7_1_05.pdf
· http://www.qowl.co.uk/
· http://users.ids.net/_brim/sdwtt.html
· www.workteams.unt.edu
· www.ssa.gov/ssa
· www.ipma-hr.org
Received on 07.01.2019 Modified on 16.02.2019
Accepted on 18.03.2019 ©AandV Publications All right reserved
Res. J. Humanities and Social Sciences. 2019; 10(2):471-478.
DOI: 10.5958/2321-5828.2019.00078.0