INTRODUCTION:

Greenhaus and Parasuraman (1999) found that traditionally the work-to-nonwork studies ignored the positive effect of interaction between work and nonwork domain (as cited in Greenhaus and Powell, 2006). During the last decade of 20^th century researchers started focusing on positive side of work/nonwork interactions (Frone M. R., 2003). It was only in the 21^st century, the research world widely recognised that the positive interaction between work and nonwork is capable of producing an enhanced effect in various life domain of an individual. However, a thorough review of the literature proves that the positive impact of work has been empirically validated even during 1980s.

Empirical studies have reported the positive impact of work on other non-work domains (e.g., Gary, 1983; Yogev, 1981; Piotrkowski, 1979), and number of non-work roles positively correlated with satisfaction as well as wellbeing in the work and personal life (e.g., Pietromonaco, Manis, andFrohardt-Lane, 1986; Cooke and Rousseau, 1984) (Kirchemeyer, 1993). Staines (1980) based on literature found that spillover-the positive correlation between work and non-work activities occours more frequently than compansation-the negative association between work and non-work activities. To describe the work and non-work domain is benefited each other several terms such as positive spillover, enhancement, facilitation and enrichment were used, which are of disparate in nature (Shein and Chen, 2011). Enrichment isthe concept came in to existence as a latest addition to the stock of such construct used to describe the benefit of work and non-work interaction (Brough, Siu, O'Driscoll, and Timms, 2015).

The concept of enrichment was formalised by Jeffrey H. Greenhaus and Gary N. Powell in the year 2006 with the introduction of ‘Work-family enrichment theory’. According to Greenhaus and Powell (2006) work/family enrichment is the extent to which experience in one role improve the quality of life in the other role. That is the enrichment occurs only if either the gain or the resource obtained from one domain enables an individual to improve the performance and quality of life in another domain. Though Greenhaus and Powell (2006) introduced the theory of enrichment as a domain specific concept focused on work and family domain specifically, they pointed out the need of expanding the bandwidth of the concept beyond the family (e.g., community, religion, volunteer etc.,) in order to reflect the true effect of life as a whole.

Different researchers defined the positive effect of work/non-work interactions using different terminology such as positive spillover, enhancement, facilitation and enrichment. All these terminologies were similar to each other in such a way that, it intends to explain how the participation and engagement in one domain (either work or nonwork) either improve or benefit the functioning and experience of other domain (either work or nonwork). However, on the basis of magnitude and dimension of the positive impact each construct (positive spillover, enhancement, facilitation and enrichment) were independent to each other. Positive spillover can be considered as the forerunner among the construct and it simply implies the transfer of benefits (resources/emotions/skills) from one domain to another. Whenever there is a beneficial transfer of resources/emotions/skills from one domain to another, the same can be considered as positive spillover. Positive spillover refers to the situation at which the work and family domain function in such a way that promote the transfer of resources in between each domain which makes two domains similar in nature(Edwards and Rothbard, 2000). Enhancement is the positive outcome of multiple role engagement (Sieber, 1974). That is multiple role engagement increase the access to skills and resources, which in turn enable an individual to perform various life roles more effectively. Enhancement focuses on how the benefit acquired as a result of multiple role engagement benefit an employee silently in the successful functioning of the life as a whole (Carlson, Kacmar, Wayne, and Grzywacz, 2006). Enrichment is different from enhancement on the sense that the enhancement focuses on the overall benefit that arise as a result of multiple role engagement. Whereas the enrichment focuses on how a particular life domain is benefited as a result of transfer of positive effect or benefit from another life domain. Work-family facilitation is the extent to which an individual’s engagement in one life domain provide gains which contribute to the enhanced functioning of another life domain (Wayne, Grzywacz, Carlson, and Kacmar, 2007). Facilitation occurs when the gain acquired as a result of engagement in one life domain resulted in the enhanced functioning of another life domain. On the other hand, enrichment is said to be happened when the benefit acquired from one life domain resulted in the enhanced performance of the any of the individual role in another domain. Wayne et.al, (2004) enrichment focus on the improvement in individual role or quality of life whereas facilitation focus on improvement in system functioning (as cited in Carlson, Kacmar, Wayne, and Grzywacz, 2006).

Work/life enrichment has positive association with marital satisfaction, family functioning, work engagement, family engagement, work satisfaction, family satisfaction, family functioning, family performance and work performance; Whereas it is negatively associated with psychological distress, tension, (Kacmar, Crawford, Carlson, Ferguson, and Whitten, 2014). Future research on should focus on heterogenous demographics in terms of age, gender, occupation, social class, income, etc., in order to have a refined understanding on the enrichment concept (Kacmar, Crawford, Carlson, Ferguson, and Whitten, 2014; see also Wayne, Grzywacz, Carlson, and Kacmar, 2007). The direct effect of work-life enrichment with other constructs such as work-life balance, work satisfaction, family satisfaction and demographic were well documented; however, lack of consistency among research findings explaining the relationship of work-life enrichment should not be ignored (Brough, Siu, O'Driscoll, and Timms, 2015). Here in this study one of such spectrum (demographics) of ambiguity associated with work-life enrichment is explored in detail. That is the objective of this study is to explore the relationship between demographics (work, family and personal) and work-life enrichment.

Demographics and Work-Life Enrichment:

Demographics (work, family and personal) is considered as a dominant force that has very significant effect in shaping perception, emotion, attitude and behaviour of an individual (Pjesivac, 2016; see also Klein, 2015; Loshin, 2013; Amina, 2007). Which postulates that the demographics is a potential factor that has the ability to influence the physical as well as psychological level of an individual. Therefore, it is very essential to explore and understand the demographic dimensionality of a construct for the successful interpretation of the construct. Furthermore, knowledge about the underlaying demographic dimensionality of work-life enrichment enables the employer to formulate tailor made policies focused on each demographic class so as to enhance the morale and satisfaction of the employees. The purpose of this study is to explore and understand the relationship if any that exist in between demographics (work, family and personal) and work-life enrichment of employees.This study clusters the employee demographics in to three viz., work demographics, family demographics and the personal demographics. The work demographics comprises of variables such as occupation, designation, experience and salary. Whereas the family demographics of variables such as family type, marital status and child status. And the personal demographics comprises of variable such as age, gender and educational qualification. The general supposition about demographics is that the demographics has the potential to influence employee perception, preference and attitude (e.g., Pjesivac, 2016; see also Klein, 2015; Joseph and Devasia, 2015; Loshin, 2013; Amina, 2007). Based on the supposition about demographics following hypothesis were framed in relation with each of the demographic domain viz., work family and personal.

H1: Employee work demographics and work-life enrichment are related.

H1a: There is relationship between employee occupation and work-life enrichment.

H1b: There is relationship between employee designation and work-life enrichment.

H1c: There is relationship between employee experience and work-life enrichment.

H1d: There is relationship between employee salary and work-life enrichment.

H2: Employee family demographics and work-life enrichment are related.

H2a: There is relationship between marital status of the employee and work-life enrichment.

H2b: There is relationship between employee family type and work-life enrichment.

H2c: There is relationship between child status of the employee and work-life enrichment.

H3: Employee personal demographics and work-life enrichment are related.

H3a: There is relationship between employee age and work-life enrichment.

H3b: There is relationship between employee gender and work-life enrichment.

H3c: There is relationship between employee qualification (education level) and work-life enrichment.

MATERIAL AND METHODS:

Measures Used:

Work-life enrichment- Work-life enrichment was measured with the help of work/personal life enrichment scale developed by Jeremy Hayman in the year 2005. Jeremy Hayman’s scale of work-life enrichment was a modified version of Fisher McAuely’s scale of work-life enrichment which was published in the year 2003. Hyman’s scale of work/personal life enrichment is unidimensional four itemised seven-point scale frequency rating scale (7 = All the time, 6 = Almost every time, 5 = A moderate amount, 4 = Sometimes, 3=rarely, 2 = All most never, 1 = Not at all). The Cronbach alpha reliability of the scale was .863. A sample item of the scale was ‘Job gives me energy to pursue personal activities’. High value on the scale indicates high level of work-life enrichment. whereas low score indicates low level of work-life enrichment.

Demographics- In order to explore the demographic (work, family and personal life) profile of respondents direct questions were asked with regard to occupation, designation, year of experience, and salary-work demographics; marital status, family type and child status-family demographics; age, gender and educational qualification-personal demographics.

Data and Sample:

The study is based on primary data collected. And the data required for the study was retrieved form the data base created by Miss Kavia A.G in the year 2016 as the part of her post graduate dissertation. Where the data belongs to a random sample of 78 professionals from banking and education sector who were employed with in the Viakom Thaluk of the Kottayam District in the state of Kerala. The data (i.e., the post graduate dissertation work) was collected with the help of questionnaire distributed randomly identified professionals, fifty each from the banking (employees of commercial banks) and education (professionals employed with the collegiate education) sector. Out of hundred questionnaires distributed only 78 found valid and therefore the final sample size of the study become 78.

ANALYSIS AND DISCUSSION:

Profile of Respondents:

Table 1 shows the distribution of respondent’s profile on the basis of variables such as age, gender, marital status, educational qualification, occupation, designation and salary.

Table: 1 Distribution of Respondents Profile

Dimension	Dimension category	N	%
Age	</= 30	31	39.7
	31-45	27	34.6
	> 45	20	25.6
	Total	78	100
Gender	Male	41	52.6
	Female	37	47.4
	Total	78	100
Marital status	Single	17	21.7
	Married	61	78.2
	Total	78	100
Educational qualification	Below graduation	4	5.1
	Graduation/equalling	18	23.1
	Post-graduation/above	56	71.8
	Total	78	100
Occupation	Banking	30	38.5
	Education	48	61.5
	Total	78	100
Designation	Managerial	23	29.5
	Non-managerial	55	70.5
	Total	78	100
Salary	< 25000	26	33.3
	25000-60000	38	48.7
	> 60000	14	17
	Total	78	100

As perage breakdown of respondent’s profile shown in the table 1, 39.7 percent of the respondents were below the age of 31, 34.6 percent of respondents were in between the age of 31-45, and 25.6 percent of the respondents were above the age of 45. While considering the respondents gender, table 1 shows that 52.6 percent of the respondent were male and 47.4 percent of the respondents were female. When it comes to marital status majority of the respondents were married (78.2 percent). Only minority (21.7 percent) remained single. The distribution of respondent’s profile based on educational qualification illustrates that, 71.8 percent of the respondents had qualification equalling or above post-graduation, it was followed by graduate’s 23.1 percent and only 5.1 percent of the respondents had qualification below graduation. The occupation wise distribution of respondent’s profile shows that 61.5 percent of the respondents belong to academic professionals and the remaining 38.5 percent of the respondents belongs to banking sector. Table 1 further shows the designation wise distribution of the respondents; 70.5 percent of the respondents were engaged with non-managerial task. Whereas 29.5 percent of the respondents were entrusted with managerial task. According to the salary distribution illustrated by table 1; 48.7 percent of the respondents have monthly earnings between ₹ 25000-₹ 60000, 33.3 percent having earnings below ₹ 25000, and the remaining 17 of the respondents have monthly earnings above ₹ 60000.

Work-life Enrichment Level of Respondents:

Table 2 shows the work-life enrichment level of the respondents. As per the data shown in the table 2, respondents were experiencing high level of work-life enrichment (mean = 4.83 > 4).

Table 2 Work-life Enrichment Level of Respondents

Item	N	Mean	Std. Deviation	Skewness	Kurtosis
WLE	78	4.83	1.31	-.333^NS	-.543^NS

(WLE = Work-life enrichment; NS = Not Significant)

Demographics and Work-Life Enrichment:

Work demographics and work-life enrichment- Table 3 shows the relationship between work demographics of the respondents and its relationship with work-life enrichment. Occupation, designation, experience and salary were the work demographic related variables considered.

Table 3 Work Demographics and Work-life Enrichment

Variable	Work-life Enrichment
Variable	Test	Value	df	Sig
Occupation	t	.394	76	.697^NS
Designation	t	.456	76	.719^NS
Experience	r	.080		.488^NS
Salary	F	4.87	2,75	.359^NS
(NS = Not Significant; t = t-test; r = correlation; F = ANNOVA)

According to the statistics shown in the table 3, occupation of the respondents does not have any significant relationship with the work-life enrichment, t (DF = 76) = .394, p > .05. Which postulates that occupation does not have the potential to influence the work-life enrichment level. Therefore, the hypothesis ‘H1a: There is relationship between employee occupation and work-life enrichment’ was rejected and concluded that work-life enrichment cannot be influenced by the occupation status. When it comes to employee designation, table 3 illustrates that there is no significant relationship between employee designation status and work-life enrichment, t (df = 76) = .456, p > .05. Hence the hypothesis ‘H1b: There is relationship between employee designation and work-life enrichment’ was rejected and clinched that employee designation does not have the potential to influence the work-life enrichment level. While considering the employee experience and work-life enrichment, table 3 shows that there is only very weak as well as statistically insignificant correlation between work-life enrichment and employee experience, r = .080, p > .05. Therefore, the hypothesis ‘H1c: There is relationship between employee experience and work-life enrichment’ was failed to accept and concluded that there is no relationship between employee experience and work-life enrichment. In the case of relationship between employee salary level and work-life enrichment level, table 3 illustrates that there is no significant relation between employee salary level and work-life enrichment, F (2,75) = 4.87, p > .05. Which indicates that work-life enrichment level is not influenced by the salary level of the employee. Therefore, the hypothesis ‘H1d: There is relationship between employee salary and work-life enrichment’ was rejected and clinched that there is no relationship between employee salary level and work-life enrichment.

The analysis of relationship between work demographics and work-life enrichment proved that all the all the work demographic related variables (employee occupation, designation status, employee experience and salary level) considered failed to exhibit any statistically significant relationship with the work-life enrichment. Hence, the hypothesis ‘H1: Employee work demographics and work-life enrichment are related’ was rejected and concluded that employee work demographics does not have the potential to influence the work-life enrichment level.

Family demographics and work-life enrichment-Table 4 shows the relationship between employeefamily demographics of the respondents and its relationship with work-life enrichment. Marital status, family status and child status were the variables used to measure the family demographics.

Table 4 Family Demographics and Work-life Enrichment

Variable	Work-life Enrichment
Variable	Test	Value	df	Sig
Marital Status	t	1.429	76	.157^NS
Family Status	t	1.541	76	.250^NS
Child Status	t	-1.748	76	.077^NS

(NS = Not Significant; t = t-test)

As per the statistics shown in the table 4, marital status of the employee does not have any significant relationship with the work-life enrichment, t (df = 76) = 1.429, p > .05. Which postulates that the marital status does not have the potential to influence the work-life enrichment level of the employee. Therefore, the hypothesis ‘H3a: There is relationship between employee age and work-life enrichment’ was rejected and concluded that work-life enrichment cannot be influenced by the age of the employee. When it comes to employee designation, table 4 illustrates that there is no significant relationship between employee familytype and work-life enrichment, t (df = 76) = 1.541, p > .05. Hence the hypothesis ‘H2b: There is relationship between employee family type and work-life enrichment’ was rejected and clinched that employee family type does not have the potential to influence the work-life enrichment. While considering the child status of the employee and work-life enrichment, table 3 further shows that there is no statistically significant relationship between work-life enrichment and child status of the employee, t (df = 76) = -1.748, p > .05. Therefore, the hypothesis H2c: There is relationship between child status of the employee and work-life enrichment’ was rejected and concluded that there is no relationship between child status of the employee and work-life enrichment.

The analysis of relationship between family demographics and work-life enrichment proved that all the all the family demographic related variables (marital status, family type and child status) considered failed to exhibit any statistically significant relationship with the work-life enrichment. Hence, the hypothesis ‘H2: Employee family demographics and work-life enrichment are related’ was rejected and concluded that employee family demographics does not have the potential to influence the work-life enrichment level.

Personal demographics and work-life enrichment- Table 5 shows the relationship between employee personal demographics of the employee and its relationship with work-life enrichment. Age, gender and education qualification were the variables used to measure the personal demographic of the employee.

Table 5 Personal Demographics and Work-life Enrichment

Variable	Work-life Enrichment
Variable	Test	Value	df	Sig
Age	F	1.869	2,75	.161^{NS ill}
Gender	t	-.789	76	.433^NS
Education	F	.560	2,75	.574^NS

(NS = Not Significant; t = t-test; F = ANNOVA)

According to the statistics shown in the table 5, employee age does not have any significant relationship with the work-life enrichment, F (2,75) = 1.869, p > .05. Which postulates that the employee age does not have the potential to influence the work-life enrichment level. Therefore, the hypothesis ‘H1a: There is relationship between employee occupation and work-life enrichment’ was rejected and concluded that work-life enrichment cannot be influenced by the occupation status. While considering the relationship between employee gender and work-life enrichment, table 5 illustrates that there is no significant relationship between employee gender and work-life enrichment, t (DF = 76) = -.789, p > .05. Hence the hypothesis ‘H3b: There is relationship between employee gender and work-life enrichment’ was rejected and clinched that employee gender status does not have the potential to influence the work-life enrichment level. In the case of relationship between employee education and work-life enrichment level, table 3 illustrates that there is no significant relation between education level of the employee and work-life enrichment, F (2,75) = 4.87, p > .05. Which in turn indicates that work-life enrichment level is not influenced by the educational qualification of the employee. Therefore, the hypothesis ‘H3c: There is relationship between employee qualification (education level) and work-life enrichment’ was rejected and clinched that there is no relationship between educational qualificationof the employee and work-life enrichment. The analysis of relationship between personal demographics and work-life enrichment proved that all the all the personal demographic related variables (age, gender and educational qualification) considered failed to exhibit any statistically significant relationship with the work-life enrichment. Hence, the hypothesis ‘H3: Employee personal demographics and work-life enrichment are related’ was rejected and concluded that employee personal demographics does not have the potential to influence the work-life enrichment level.

The result of the statistical analysis of relationship between demographics and work-life enrichment proved that the demographics viz., work demographics-occupation, designation, experience and salary (H1-H1a, H1b, H1c, and H1d); family demographics-marital status, family type and child status (H2-H2a, H2b and H2c); personal demographics-age, gender and educational qualification (H3-H3a, H3b and H3c); have no significant statistical relationship with work-life enrichment. Therefore, it can be concluded that employee demographics cannot be considered as a potential factor that influence the work-life enrichment.

CONCLUSION:

The study examined the relationship between employee demographics and work-life enrichment. Three dimensions of the employee demographics viz., work demographics-occupation, designation, experience and salary (H1-H1a, H1b, H1c, and H1d); family demographics-marital status, family type and child status (H2-H2a, H2b and H2c); personal demographics-age, gender and educational qualification (H3-H3a, H3b and H3c); were analysed in relation with work-life enrichment and fount that there is no relationship between employee demographics and work-life enrichment. That is work-life enrichment construct can be considered as less social as it was not influenced by the employee demographics. However further studies should be conducted in order to explore the psychometric characteristics of the work-life enrichment. Certain properties of the respondents make the findings confounding too, as the sample of the study tends to be homogeneous in terms of education (majority of the respondents were well educated-72 percent have education qualification above or equalling post-graduation), marital status (majority of the respondents were married-78 percent) and work-life enrichment level (high level of work-life enrichment). Hence it is necessary to replicate the study on a heterogenous population in order to validate the findings of the study.

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Received on 09.10.2017 Modified on 19.11.2017

Asian Journal of Management. 2018; 9(1):261-266.

DOI: 10.5958/2321-5763.2018.00039.2