Development and standardization of the work-life balance scale for the insurance sector employees

Abstract

The nature of work and working habits are changing in this modern era, making work more demanding and impacting personal life. This creates work-life balance. A work-life balance (WLB) is an ability to manage both the spheres of life, such as work and personal life. The various factors, such as personal, social, and work-related aspects, broadly influence an individual’s work-life balance. Based upon the nature of the work study has been conducted in the Insurance sector. The study aimed to construct and standardize the work-life balance scale using validity and reliability; this study used the stratified random technique of three hundred employees from eighteen private Insurance sector companies. Responses were collected using a structured work-life balance questionnaire with six contributory factors. The research intention behind the study was to standardize the work-life balance tool by ensuring its reliability and validity. A reliability test was conducted using Cronbach’s alpha. Factors have been derived based upon segmentation theory, spill over theory, ladder theory, resource drain theory, compensation theory, congruence theory and enrichment theory. It showed 0.81; in composite reliability, all the factors of work-life balance, such as nature of work, work flexibility, workload, compensation, organizational support, and personal life, were more than 0.7. The tool was validated using construct, content, and exploratory and confirmatory factors. This study will be helpful to further researchers to use the validated tool, especially in Insurance and related sectors, to measure the level of WLB.

Keywords:

• Work life balance
• Insurance sector
• reliability
• exploratory factor analysis
• confirmatory factor analysis
• validity test

1. Introduction

Indian insurance market liberalization has made it more open to private competition. Numerous foreign insurance companies have partnered with various asset management firms and opened representative offices in India. The insurance companies now have to compete due to all these changes. Technology, clever ideas, expert strategy, and tool utilization are all critical, but what makes a company the best is that they have the best employees.

45% of the overall GDP is made up of the service sector. Thus, the degree of contentment and the balance between work and life is crucial. Today we have reached such a phase where most employees across the sectors are spending their maximum hours in the organization, leaving very little time for our time. Today’s generation has lost sight of the importance of spending time with family and self-care. Man has become more ambitious due to increased commitment in life and never-ending wants, and time dedicated to personal life becomes negligibly less without his knowledge. All of this strains a person’s physical and mental health.

Businesses are more focused on meeting employee demands and attracting better employees who are more motivated to perform effectively (Waterman, 1994). Maintaining a work-life balance is a problem for both individuals and employers in the face of growing competition.

A vital feature of work-life balance is the sum of stint an individual devotes to the workplace. Prolonged work hours may damage individual health, increase stress levels and imperil safety. Researchers opined that the arena of work-life balance study is itself “unbalanced.” Most of the survey on work-life balance has focused on individuals’ multiple roles. Keeney et al. (2013), Haar et al. (2014), Casper et al. (2017), and Casper et al. (2017) examined the scholarly literature for conceptual definitions of balance and found that around sixty-six definitions focused on family and work.

Clark (2000) defined work-life balance as “Satisfaction and good functioning at work and home with a minimum of role conflict,” it can be called a state of steadiness where the demand equates an individual’s personal life with work life. Torrington et al. (2011) argued that work-life balance enlightens the capability to gratify three simple areas. Jobs, family, and personal life are all aspects of life. Working hours, job speed, and the proportion of working hours spent in work were loads of work areas of life. In that case, the disparity could result in exhaustion, anxiety, and other physiological effects that would be detrimental to both the work and family domains of life.

Organizational culture and workplace behaviors often control a person’s working life and prioritize the organization’s goals over the individual’s. However, as time passes, it tends to squat efficiency and productivity, as shown by the workers at work.

In the Insurance sector, 24 life Insurance companies and 27 Non-life Insurance companies work in India. Work is an integral part of our everyday life. However, tough competition exists among companies which will eventually impact the employees in the field of sales and marketing. These department people have to work hard to find prospective agents, recruit them, train them, convert them into Insurance advisors/agents and get the business through them. In order to complete the whole set of processes, employees need to spend their whole time, which may create conflict between personal and professional goals; this will lead to work-life balance issues among employees and lead to high attrition in the organization.

The researcher is focusing on issues of the work-life balance of employees in the Insurance sector keeping is steadily growing to be a significant problem in India. This study focuses on creating a scale to assess professionals’ work/life balance while considering their extremely demanding and precarious job profiles and the requirement to determine their work/life balance.

The paper’s main aim is to standardize the work-life balance tool through reliability and validity by having the respondents from Private Insurance Sectors. This tool will help measure the level of WLB among the employees.

1.1. Background and theoretical framework of work-life balance

According to reports, the phrase “work-life balance” dates back to the 1970s in the UK. It was popularised in the US starting in the middle of the 1980s. However, the issue began to receive more attention in the US and UK in the 1960s, particularly as more women entered the workforce. Employers in the 1960s and 1970s saw work-life balance as primarily a problem for mothers who had to juggle the demands of their careers and raising children. Pioneering companies like Merck, Deloitte & Touche, and IBM started changing their internal workplace rules, processes, and benefits in the 1980s to realize the worth and requirements of their female employees. Among the modifications were the modifications of maternity leave, employee assistance programs (EAPs), flexitime, home-based work, and child-care referrals. Men started expressing concerns about work-life balance in the 1980s as well. By the decade’s end, it was recognized that work-life balance affected men, families, organizations, cultures, and women. Work-life balance became widely acknowledged in the 1990s as a crucial issue for everyone, including men, women, parents and non-parents, singles, and couples (Bird, 2006). Many ideas have been put out throughout the discipline’s history to explain this occurrence. These are some of the theories that have been put forth:

Segmentation theory was the first to suggest that since each has been divided into its unique entity, the relationship between work and home is unaffected by the other (Edwards & Rothbard, 2000; Kanter, 1977; Staines, 1980; Zedeck, 1992). According to segmentation theory, each domain operates independently. As a result, spillover theory is the complete opposite of this idea. Additionally, it holds that a person’s home and work settings are always independent and do not affect one another in any way.

Spill-Over Theory strategy makes the jobs identical by affecting the proficiencies in one role. It is the degree to which there are connections between work and family, whether those connections are horizontal or vertical (Sirgy et al., 2001), favorable or unfavorable (Morris & Madsen, 2007), and where adverse family experiences are related to adverse work experiences and vice versa (Staines, 1980). This is when fulfillment and success in one area may lead to fulfillment and success in another and vice versa (Xu, 2009). According to Edwards and Rothbard (2000), spillover can be interpreted in one of two ways: either as a transfer of the entirety of skills and behaviors from one field to another or as a result of the positive relationship between life and work ethics and contentment (Zedeck, 1992). When examining the relationship between work and family life, this hypothesis is the most frequently applied in work-life balance research (Rincey & Panchanatham, 2014; Zedeck & Mosier, 1990).

In Compensation Theory, people go for fulfillment in other areas when they are unfulfilled in their current ones. According to this notion, family and work coexist in the same environment and have a balancing influence on one another (Mathew, R & Natarajan, 2014). It has been said that compensation is a conflict between a job and a family. Because bad experiences in one domain lead to favorable perceptions in another, it has been labeled as unfavorable. Alternately, a person may seek incentives in another domain in response to discontent in one. Rewards are those activities that satisfy people’s desires and can raise their level of enjoyment.

Ladder theory says that the most fundamentally balanced approach to WLB is provided by the theory proposed by Bird (2006). (Rincey & Panchanatham, 2014). According to the idea, every story has two sides, which is also the position taken by WLB.

In Enrichment Theory, Seiber’s (1974) enrichment perspective, playing several or accruing roles gives people access to a variety of resources that they can use when playing other parts. According to Marks (1977), human energy is not limited. Participation in one position may result in energy expansion, allowing individuals to find energy for their favorite activities. According to Frone (2003), WLB encompassed more than only the conflict between work and family. It also includes the beneficial spillover effects from one position to another (Repetti, 1987).

Border Theory says that Clark’s (2000) idea takes a fresh perspective on WLB. This theory is predicated on the idea that humans only play a part inside specific life domains divided by borders that might be either temporally, physically, or emotionally (Clark, 2000). One of the challenges the theory addresses is crossing borders, particularly between the home and the workplace.

Resource drain theory: According to Frone (2003), WLB encompassed more than only the conflict between work and family. It also includes the beneficial spillover effects from one position to another (Repetti, 1987).

According to the conflict theory, which was first put forth by Greenhaus & Beutell in 1985, sacrifice in one area of life results in fulfillment and achievement in another. According to the boundary theory, some limits define the job and non-work components of an individual’s life as being different and separate from one another on a psychological, bodily, and behavioral level (Allen et al., 2014).

The congruence theory is based on the similarity or congruence between work and family. This similarity is mediated by other variables such as hereditary characteristics, personality qualities, and sociocultural pressures (Zedeck, 1992). Congruence theory postulates that a third element, such as genetics or community cohesion, could favor work and family domains (Mathew, R & Natarajan, 2014). The early conception of how work and home are related was that they are separate, independent, and unrelated to one another as shown in Figure 1. The pioneers of this concept are Blood and Wolfe (1960).

Figure 1. Conceptual framework.

2. Review of literature

Research on this topic used to be known as “work-family conflict,” It was frequently discussed in modern organizational behavior literature (Frone et al., 1992; Williams & Alliger, 1994). Compared to work-family conflict, a more encompassing word for work/non-work conflict has recently developed in the literature: “work-life balance.” This concept gives a more comprehensive approach to work/non-work conflict research. Work-life balance impacts various employee outcomes (Adams et al., 1996; Burke, 1988; Frone et al., 1992; Greenhaus & Beutell, 1985; Netemeyer et al., 1996; Thomas & Ganster, 1995). Job satisfaction and job dissatisfaction, job burnout, life, and marital satisfaction and dissatisfaction are all employee-related outcomes. Turnover, absenteeism, presenteeism, and work performance are organizational outcomes. Allen et al. (2014) divided employee outcomes into three main categories when reviewing the research on how work affects family conflict:

1. Work-related outcomes (such as job satisfaction, organisational commitment, intention to leave, absenteeism, job performance, and career services)

2. Nonwork-related outcomes (such as life satisfaction, marital satisfaction, family performance, and leisure satisfaction)

3. Stress-related outcomes

The area of work-life balance research has struggled to come up with a universally accepted description of the WLB, Kalliath and Brough (2008). Parasuraman and Simmers (2001) type of employment and gender has a greater impact on job involvement, job engagement and conflict between personal and work life. Thornthwaite (2004), due to a lot of work pressure nowadays employees are fond of a part-time job, work flexibility and work from home options irrespective of gender. Employees seek work flexibility, work flexibility includes sharing the job, career breaks (maternity/paternity absences), part-time and term-time employment, and varying the workplace’s time and location (Torrington et al., 2011). The flexible working condition may increase workplace morale (Tipping et al., 2012). A hectic schedule reduces the flexibility of the workplace. One sign of employee stress at work is their workload. The volume of work assignments is also alleged to be the root of workers’ mental stress (Shah et al., 2011).

Wise (2003) mentioned that the awareness level of work-life balance policies of the organization is significantly less, every individual must know about such policies. Voydanoff (2004), strain from office to work and vice versa creates much mental stress, especially for women who carry office strain to home because their role will be more than men. Drew and Murtagh (2005), employees in a senior manager post always face work-life balance issues because they are expected to do a lot of work; Mesmer-Magnus and Viswesvaran (2006) study says that those who get family support can do better in the work place, Bhargava and Baral (2009), self-evaluation of an individual, superior support and family support make work and life happier, healthier and through individual as well as organizational performances can also be enriched. Jim said that work-life strategy should be implemented effectively in the organization; it should be implemented in such a way as to get employee commitment, involvement, and ROI.

Understanding the line and the connection between an employee’s job and non-work lives has become more critical due to several changes in the workplace and employee demographics over the past few decades (Hayman, 2005). The life insurance sector in India is struggling with significant sales force attrition; roughly 30% of newly hired salespeople quit their jobs during the first year of employment, and the retention rate after four years is as low as 13% . An organization loses its knowledge when employees leave. This information loss may negatively impact an organization’s competitive advantage (Omotayo, 2015; Sarra et al., 2013). Losing highly talented workers can result in both physical sunk costs linked to hiring, training, and recruiting and intangible costs related to decreased productivity, knowledge loss, and employee morale (Kantor & Crosser, 2016). Rita Goyal (2012), conducted a study on “Quality of working life in the Insurance sector “having 400 employees and found out that Poor work-life balance leads to many disastrous things like tardiness, bad performance, lack of motivation, more errors, absence of work and so on. Employees of the Insurance sector reported that many personal and professional life spillovers impact their quality of work life (Muthukumaran, 2016) and intention to quit the job due to work life balance issues has reduced the work performance (Vigneshwaran et al., 2022). Singh Akankshi (2018) did a study titled “Stress management: A comparative study of insurance and banking sector firms in MP” to determine the difference in employee stress levels between the two industries. The result showed that stress level is higher in the insurance sector based on work target, client meeting, and role overload. However, this study looks at how sound employees of a few insurance companies in Lagos State combine their professional and personal lives. According to the study, work-life balance, role conflict, flexible work arrangements, and job autonomy greatly influenced employees’ performance. It is advised that organizations have well-defined policies regarding work-life balance that will serve as a guide for both managers and employees. Management should also conduct training and development on this topic annually, biannually, or quarterly. Finally, management should work to implement flexible work arrangements in order to boost employee performance.

There is a significant difference in the work-life balance between male and female employees. The difference is based on a break from work, compressed working hours, self-roasting, teleworking, child care, flexi-time, paid leave, and job sharing (Fapohunda, 2014). Work-life balance will be better in people of growing age than young age (Kaźmierska et al., 2106). According to Panisoara & Serban (2013), work-life balance will differ based on marital status and with and without child state. Married women experience work stress due to multiple family responsibilities, which affect the work-life balance at a greater level. Compensation is one factor that influences and motivates employees to work in the organization and impacts the personal and professional life front. Irrespective of the sector, the workload is one such aspect that creates issues in fulfilling personal and professional requirements (Ashfaq et al., 2013).

According (to Alianto & Anindita, 2017), this study aimed to ascertain how compensation and work-life balance affected work satisfaction that was mediated by stress at work. The findings indicate that while work happiness impacts remuneration, stress at work is unaffected. Consequently, pay has no effect on work stress, work-life balance has no impact on job satisfaction, and compensation has no impact on work stress. Women employees are not finding much work pressure until they are satisfied with their compensation (Kar et al., 2019). Mentoring and other forms of support are less significant when evaluating employee commitment than organizational support. Positive employment status and emotional commitment are related to perceived organizational support. Turnover, absenteeism, presenteeism, and work performance are organizational consequences.

2.1. Review on reliability and validity

Work-life balance level or individual perception of work-life balance can be measured statistically by standardizing tools using reliability and validity. According to Razak et al. (2016), reliability and validity tests have been conducted. A healthy and harmonious work environment is crucial to retain and promoting employees’ high-quality work and life. Reducing stress, job burnout, and the imbalance between work and family obligations is critical.

The ability of a measuring device to produce precise and reliable results is known as reliability. It assesses the relative lack of mistakes in a measuring device; the lower the error, the more accurate and reliable the data are (DeVon et al., 2007). Testing an instrument’s validity entails seeing if it can measure the things it is designed to measure. According to (Siratirakul et al., 2022), this study aimed to evaluate the reliability and validity of a work-life balance measure created specifically for the operative field population of the Indonesian military. This study uses confirmatory factor analysis to examine the hypnosis model to confirm the underlying characteristics of work-life balance (CFA). There are 100 Indonesian soldiers among the participants. The findings demonstrate the work-life balance scale’s good reliability (= 0.889). According to (Nanjundeswaraswamy, 2021), this project is an organized effort to design, develop, and verify a tool for measuring nurses’ Quality of work life (QWL) and identify its essential elements. Design/methodology/approach: In this rigorous study, Pareto analysis is used to pinpoint key aspects of nurses’ Quality of life. Data and information were gathered from 474 nurses using a standardized questionnaire. The number of dimensions and items decreased using exploratory factor analysis (EFA). Nine predominate dimensions—work environment, working conditions, work-life balance, compensation, relationships and collaboration, stress at work, job satisfaction, career development, and organizational culture—by confirmatory factor analysis (CFA) using the SPSS 21 software. The proposed nine-component nurses’ QWL instrument was validated using a variety of statistical tests, including reliability, content validity, construct validity, convergent, divergent, and multicollinearity. The suggested measurement model explained 73.18% of the total variance, and the instrument’s Cronbach’s alpha value is 0.902, indicating high reliability. The following model fit indices meet the required standards: Tucker-Lewis index (TLI) = 0.921, comparative fit index (CFI) = 0.931, goodness-of-fit index (GFI) = 0.965, adjusted goodness-of-fit index (AGFI) = 0.937, parsimony goodness-of-fit index (PGFI) = 0.918, incremental fit index (IFI) = 0.933, and root mean square error of approximation. The QWL assessment tool for nurses using the nine parameters is accurate and statistically valid. A 19-item scale created by Fisher-McAuley et al. (2003) that was intended to gather employee perceptions on WLB had been modified into a 15-item measure. The 15-item scale measured the three dimensions of WLB as Work Interference with Personal Life (WIPL), Personal Life Interference with Work (PLIW), and Work Personal Life Enhancement (WPLE). To evaluate scale unidimensionality, EFA was conducted.

Bartlett’s test of sphericity yielded a factor analysis-appropriate p-value of 0.000. Scale validity and reliability were further evaluated using CFA. All scales’ GFI indices were more significant than 0.90, indicating that they were all one-dimensional. Indicator reliability and scale reliability were the two types of reliability estimations. With LISREL for this study, the Bentler Bonett Normed Fit Index (NFI) was used to assess the convergent validity of all five measures. It was determined to be 0.90, suggesting strong convergent validity for this investigation, and clear correlations between all three scales were discovered using nomological validity (Agha et al., 2017). To assess the WLB of IT professionals in Chennai, a tool made up of 46 statements, and five criteria were created. Three hundred and eighty-seven IT specialists from top Chennai IT companies provided the information needed to create the scale. The data were tested for sample adequacy and sphericity using the Kaiser-Meyer Olkin and Bartlett tests, and factor analysis supported the five-component solution.

The WLB measuring scale was determined to have sufficient reliability and validity (Banu, 2014). According to (Smita Singh, 2014), the current study aims to create a valid and reliable scale to assess work-life balance among working professionals in north India. Five industries were selected: banking, insurance, education, public health, and telecommunications. After analysis, the information gathered from a sample of 114 service industry professionals produced a 24-item scale with a Cronbach alpha value of 0.908 and subscale reliability ranging from 0.968 to 0.798. The four operationalized dimensions of the validated instrument are Work Spillover in Personal Life, Work Spillover in Personal Life, Work/Life Behavioural Enhancers, and Work/Life Behavioural Constrainers. Content, convergent, and discriminant validity contribute to the scale’s construct validity. The report also addresses the scale’s application concerns.

With the help of the above studies, the investigator formulated a hypothesis.

2.2. Hypothesis

The work-life balance scale possesses all reliability and validity required for a standardized tool. From the above hypothesis, the researcher has framed an objective.

• To construct and standardize the work-life balance Scale using reliability and validity tests.

2.3. Research methodology

The study focused on eighteen private-sector insurance company employees in India. The researcher surveyed the employees of private sector life and general insurance firms. The report included eighteen private Insurance firms in various parts of India. In order to identify the samples from the study population, the researcher adopted the Krejcie and Morgan (1970) table. At a confidence level of 95% and a 5% margin of standard error. The study population was 1200, and 291 is the sample size per the Morgan table, and in that, 300 sample size was finalized. The data were collected via a simple random sampling technique. The respondents who are being polled are from the Sales department. With the help of a systematic questionnaire, researchers gathered data from insurance industry employees. The following questions make up the questionnaire:

1. The socio-demographic characteristics of the respondents, including their type of insurance, location, age, gender, educational background, job title, years of experience, monthly income, and family structure.

2. The work-life balance scale assesses how flexible people in the insurance industry are in balancing their job and personal obligations. It consists of 34 items measuring various aspects of work-life balance on a five-point Likert scale: strongly agree, agree, neutral, disagree, and strongly disagree.

The entire questionnaire was divided into two sections and used a five-point scale. Section A is concerned with categorizing data based on respondents’ demographic characteristics, and section B deal with work-life balance factors.

Three hundred people participated in a pilot study to determine the feasibility of the research and the suitability of the questionnaire’s questions. By doing this, the questionnaire’s construct will be guaranteed to collect the information required for research (Malhotra, 2005). A few of the questionnaire’s items were slightly modified in light of the pilot study results. Further data collection was conducted using this modified questionnaire.

2.4. Construction of instrument

This study used a questionnaire called the Work-Life Balance Scale (WLB-scale), created by the researchers (Avadhani & Menon, 2021), to assess a person’s work-life balance. The level of work-life balance is determined by higher or lower ranking. The investigators (Avadhani & Menon, 2021) conducted validation and reliability tests on 300 employees in the private insurance sector using the original item of the 38-item questionnaire, which was reduced to 34 items for the report.

Hypothesis:

3. Reliability test

The capacity of a measuring instrument to provide reliable and consistent results is referred to as reliability. It assesses a measuring instrument’s relative lack of errors; the lower the error, the more reliable and precise the data (DeVon et al., 2007).

Internal consistency is one of the approaches to quantify scale reliability by evaluating the normalness of a set of items that measure a particular construct. Here, the researcher used Cronbach’s alpha to test the internal consistency in measuring the scale. If the alpha value is more than 0.7, then the scale is considered to be reliable.

The Cronbach’s alpha is identified as 0.816 from the above table constructs of work-life balance , which shows an internal consistency among the items in the scale. So, it is reliable and fit for further analysis.

4. Validity test

Validity testing means checking whether the instrument can measure what it aims for. There are two forms of Validity testing: 1) Content validity and 2) Construct Validity.

5. Content validity

The research tool is made up of a large number of objects and structures. These objects and structures were created based on a literature review that was already accessible.

Following the development of the necessary variables, ensure that the statements used in the research instrument are easily understandable and command the required material validity (Yaghmale, 2003). A thorough validation process was used for this. The instrument was first offered to three research scholars, who provided feedback on the questionnaire.

Three professors then examined the instrument with expertise in statistics, management, and commerce, and their recommendations were reported. These suggestions were considered, and variables in the questionnaire were inserted, omitted, and appropriately updated.

As a result, the questionnaire’s content validity was validated based on subject experts’ opinions and suggestions. Some adjustments were made to make the questionnaire clearer, more understandable, and more purposeful.

The adjustments were made after thorough consultations with subject experts and due diligence to ensure that the study goals could be met effectively and efficiently through data collection and administration of the tool.

6. Construct validity

1. Clustering the constructs using Exploratory Factor Analysis

2. Convergent Validity ensuring through Confirmatory Factor Analysis

7. Clustering constructs using exploratory factor analysis

“It is a data reduction tool that reduces a huge numeral of variables to a lesser number of fundamental aspects that summarise the important information contained in the variables.” (Fabrigar et al., 1999). Lawley (1940) defined “factor loadings as numerical values that indicate the strength and direction of a factor’s influence on a measured variable as shown in Table 1.

Table 1. Description of factors

Factors	Description
Nature of work	The type of work that an employee does better defines the quality of his work.
Work Flexibility	When it comes to how work is completed, workplace flexibility refers to the ability and willingness to adapt to changing circumstances.
Work load	The amount of work to be done by employees in the working setup.
Compensation	Benefit which employer receives in financial and non-financial form through organsaition.
Organizational Support	The degree to which workers feel their company values their efforts, cares for their well-being, and meets their socio emotional needs is referred to as organizational support.
Personal Life	When an individual is critically ill and unable to breathe on their own, a system is used to keep them alive.

In this study, EFA is used to discover the underlying factors of the work-life balance of the Insurance sector employees by applying the principal component method with varimax rotation.

7.1. EFA and CFA for work life balance

Table 2 reveals the results of two measures, the KMO sampling adequacy quantity and Bartlett’s Test of Sphericity to see if the relationship between the variables is meaningful.

The seven parameters of work-life balance include’ This job matches my skill set,’ ‘This job requires a lot of planning and skill. ‘The job needs interpersonal skills to achieve the targets,’ ‘The job does not give me the freedom to make my own decision to suggest apt investment plans. ‘I am happy with the nature of work assigned by the organization,’ ‘This organization helps me to grow professionally,’ and ‘I believe that my job has societal benefit’ were clustered together as factor 1 (Nature of work) with 21.37 percent variance. The other five parameters of work-life balance, such as ‘Strict login rules are followed in the workplace, ‘My superior is not empathetic to understand whenever I need time off, ‘I can share my work with my colleagues in case of emergency’, ‘The job provides me the option of work from home’, ‘Job rotation practice is not encouraged’ were grouped as factor 2 (Work flexibility) with variance of 17.91 percent variance. The other six parameters of work-life balance such as ‘I cannot complete any assigned work in the specified time, ‘I have unachievable deadlines at the workplace, ‘I do official work at home also,’ ‘I neglect some tasks because of too much work load’, ‘The work pressure makes it difficult for me to fulfill family responsibilities, ‘When dependents are sick at home I find it difficult to get leave’ were constituted as factor 3 (Workload) with 14.62 percent variance and then another five parameters of work-life balance such as ‘I get remuneration as per the Industrial standards,’ ‘I get compensated for my extra efforts in the organization’, ‘The organization provides medical benefit to me and my dependents’, ‘The organization does not take care of employee welfare schemes’, ‘I work in such a place that is supportive of my family commitments’ were clustered as factor 4 (Compensation) with 11.85 percent variance. The other 6 parameters of work-life balance such as ‘My casual leave is not easily sanctioned by my manager,’ ‘Medical leave is allowed when it is needed, ‘Organization provides paid paternity/maternity leave, ‘This organization does not encourage the employees to be physically fit, ‘The organization offers personal counseling for enhancing mental health, ‘On-site child care facility is not provided’ were clustered as factor 5 (Organizational support) with 9.88 percent variance and finally five parameters of work-life balance such as ‘I can have at least 8 hours of sleep, ‘I always manage to have food on time, ‘I cannot spend quality time with my loved once, ‘I can make myself free to attend the social gatherings, ‘My personal life is not moving according to my expectation’ were clustered as factor 6 (Personal life) with 4.52 Percent variance. It is identified that the loading patterns of the factors suggest a strong association among the parameters, and all these variables are found to contribute to the work-life balance among the insurance sector employees.

Table 2. Assessment of construct reliability

Construct	Cronbach’s alpha (α)
Work life balance	0.816

Source: Computed from primary data

In Figure 2, light of the CFA models used in the studies of Paré and Tremblay (2007) and Nasurdin et al. (2009)16, “it was determined that an item statement’s factor loading must be greater than.40 in order for it to be maintained in its respective scale, while insignificant and negatively significant/insignificant statements (.40) were omitted” as shown in Table 3 and 4.

Figure 2. CFA measurement model of work life balance.

Table 3. Reliability analysis of work-life balance

KMO and Bartlett’s Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.829
Bartlett’s Test of Sphericity	Approx. Chi-Square	20,334.898
	Df	561
	Sig.	.000

Source: Computed from primary data

Table 4. Clustering the factors of work-life balance using EFA

Factor	Parameters	Rotated factor loadings
Factor 1: Nature of work 21.37 % of Variance	This job is matching with my skill set (N1)	.870
	This job requires lot of planning and skill (N2)	.782
	The job needs interpersonal skills to achieve the targets (N3)	.766
	The job does not give me freedom to take my own decision to suggest apt investment plans (N4)	.656
	I am happy with the nature of work assigned by the organization (N5)	.651
	This organisation helps me to grow professionally (N6)	.649
	I believe that my job has societal benefit (N7)	.637
Factor 2: Work Flexibility 17.91 % of Variance	Strict login rules are followed in the work place (F1)	.801
	My superior is not empathetic to understand whenever I need time off (F2)	.796
	I can share my work with my colleagues in case of emergency (F3)	.754
	The job provides me the option of work from home (F4)	.741
	Job rotation practice is not encouraged. (F5)	.716
Factor 3: Work Load 14.62 % of Variance	I cannot complete any assigned work in the specified time (L1)	.796
	I have unachievable deadlines at workplace (L2)	.726
	I do official work at home also. (L3)	.657
	I neglect some tasks because of too much work load. (L4)	.570
	The work pressure makes it difficult for me to fulfil family responsibilities (L5)	.769
	When dependents are sick at home I find it difficult to get leave. (L6)	.861
Factor 4: Compensation 11.85 % of Variance	I get remuneration as per the Industrial standards. (C1)	.768
	I get compensated for my extra efforts in the organisation. (C2)	.743
	The organization provides medical benefit to me and my dependents. (C3)	.811
	The organization does not take care of employee welfare schemes. (C4)	.672
	I work in such a place that is supportive of my family commitments (C5)	.653
Factor 5: Organizational Support 9.88 % of Variance	My casual leave is not easily sanctioned by my manager. (S1)	.741
	Medical leave is allowed when it is needed (S2)	.701
	Organisation provides paid paternity/maternity leave. (S3)	.836
	This organisation does not encourages the employees to be physically fit (S4)	.777
	The organisation offers personal counselling for enhancing mental health (S5)	.632
	On-site child care facility is not provided (S6)	.601
Factor 6: Personal Life 4.52 % of Variance	I can have at least 8 hours of sleep (P1)	.877
	I always manage to have food on time. (P2)	.764
	I can’t spend quality time with my loved once. (P3)	.742
	I am able to make myself free to attend the social gatherings. (P4)	.666
	My personal life is not moving according to my expectation. (P5)	.598
Total Variance Explained: 80.15 % Variance

As a result, 34 statements of Work-Life Balance are maintained in their respective scales because their factor loadings are less than.40, whereas other statements that were considered to be negligible have been excluded as shown in Table 5.

Table 5. Results of goodness-of-fit test for work-life balance

Indices	CMIN/df	P	GFI	AGF1	NFI	TLI	CFI	RMSEA	RMR	AVE
Model Value	1.214	.302	.998	.983	.997	.998	.962	.019	.021	.59
Recommended Value	<3.0	>0.05	>0.90	>0.90	>0.90	>0.90	>0.95	<0.05	<0.05	>0.50

CFA model for work life balance yielded a good model fit with acceptable indices of GFI = .998, AGFI = .983, NFI = .997, TLI = .998, CFI = .962, RMSEA = .019, RMR = .021, chi-square = 44.601, CMIN/df = 1.214 and Probability level (p value) = .302 (Anderson & Gerbing, 1988 ¹⁷; Hair et al., 1995 ¹⁸; Kline, 2005 ¹⁹). The Average Variance Explained (AVE) of work-life balance is greater than 0.5, indicating convergence validity (Nunally & Bernstein, 1978)20. The variables loaded for work-life balance are found to be above the specified amount, indicating that the construct is unidimensional.

7.2. Framework analysis

The framework of research involves numerous methodological methods for data analysis that are in line with the study’s goals and aid in the development of concrete conclusions. Various statistical tests were used to authenticate and govern the reliability of the collected data.

The collected data was coded using the SPSS, and various relevant statistical methods, such as “percentage analysis, descriptive statistics, independent t-test, ANOVA, Chi-square analysis, exploratory factor analysis, and confirmatory factor analysis”.

7.3. Discussion

The present study considered six factors for the construction of tool. These factors were the result of the qualitative study conducted among the employees of Insurance sector. Around 45 employees participated in the interview and each one spent around 30 minutes of time. They had answered for what is work-life balance according to them and the factors affecting work-life balance. A detailed note was taken based on interview and with the support of review of literature questionnaire was prepared. As per the result of Interview and with the support of literature, WLB tool factors were identified. Factors were 1) Nature of work, 2) Work load, 3) Work flexibility, 4) Compensation, 5) organizational support and 6) Personal life.

Nature of work consists of seven statements, work flexibility has five statements, work load consists of six statements, compensation includes five statements, organizational support consists of six statements and personal life includes five statements. In total work-life balance has 34 statements. Each statement has followed Likert scale. Once the tool was ready, content validity and construct validity have been ensured. The content validity was performed through subject experts, industrial experts and research scholars. Necessary corrections have been made. During pilot study, total number of statements has been reduced from 38 to 34 with the help of content validity. Based on the inputs from pilot study, minor modifications were made to some of the questions included in the questionnaire. This modified questionnaire was used for further data collection. The questionnaire consists of the following questions:

1. Socio-demographic factors of respondents like type of insurance, locality, age, gender, educational qualification, designation, year of experience, monthly income, type of family of the respondents. (b) Work-life balance scale is used to measure the nature of work flexibility among the Insurance sector employees between their work and life.

Construct validity was ensured through 1) Clustering the constructs using Exploratory Factor Analysis, 2) Convergent Validity ensuring through Confirmatory Factor Analysis, 3) Composite Reliability, 4) Divergent or Discriminate Validity. Unidimensionality explains whether all items are measuring a single theoretical variable or construct. Multiple goodness-of-fit index is used to test the unidimensionality. Thus, the goodness-of-fit is calculated through Confirmatory Factor Analysis (CFA) and the main measures for goodness-of-fit are explained. The Root Mean Square Error of Approximation (RMSEA), The Root Mean Square Residual (RMR), Parsimony Adjusted Fit indices such as Parsimonious Normed-Fit Index (PNFI) and Parsimonious Comparative Fix Index (PCFI), model fit the Goodness-of-Fit Index (GFI) and Adjusted Goodness-of-Fit Index (AGFI), NFI, and CFI have been ensured. Reliability test was run with the help of Cronbach’s alpha which is 0.816 and more than 0.7, the scale is reliable. In CFA, 34 statements about work-life balance are kept in their respective scales since their factor loadings are under.40, while other statements that were thought to be insignificant were eliminated. With appropriate indices of GFI = .998, AGFI = .983, NFI = .997, TLI = .998, CFI = .962, RMSEA = .019, RMR = .021, chi-square = 44.601, CMIN/df = 1.214, and Probability level (p value) = .302, the CFA model for work-life balance produced a strong model fit (Anderson & Gerbing, 198818; Hair et al., 199519; Kline, 200520). Work-life balance has an average variance explained (AVE) of more over 0.5, indicating converging validity (Nunally & Bernstein, 1978). It is concluded that the construct ensures unidimensionality because the elements loaded for work-life balance are above the permitted level.

As per the reliability and validity test, hypothesis has been accepted and shows that work-life balance tool possess all reliability and validity required for standardizing tool. This tool will help to check their level of work-life balance. This particular tool can be used by all the Insurance companies and related sectors for their study purpose.

7.4. Implications of the study

This research evaluation has several managerial and policy consequences. First and foremost, managers and decision-makers should try to gauge and track the degree of work-life balance periodically. Given that outcomes linked to work, non-work, and stress are significantly influenced by work-life balance. Managers and policymakers must create programs and policies to guarantee that employees maintain a high work-life balance.

The relative effectiveness of various organizational policies and initiatives (such as flexible work hours, part-time employment, job sharing, parental leave, childcare, eldercare, and social support) in promoting work-life balance should be assessed by managers and policymakers alike. It should aid managers and policymakers in choosing the best policies and initiatives.

Many organizational and human factors might influence work-life balance, and these factors can interact with one another. Because of this, managers (and occasionally policy officials) should allocate funds to create and implement work-life programs that are informed by our knowledge of how such programs and policies affect work-life balance. The same can be stated about the effects of work-life balance on outcomes linked to work, non-work, and stress. Understanding how programs and policies affect outcomes linked to work, non-work, and stress should serve as guidance.

7.5. Direction for future research

The WLB scale has now been given the green light by the study, giving the researchers the chance to use it. WLB tool can be used for relationship studies with other variables such as emotional intelligence, spiritual intelligence, attrition, job satisfaction, and other topics. The study can be conducted in the Insurance sector of different parts of the country and even in related industries. Additionally, the researchers might consider the limits of this study to improve the scale that would suit the working situations’ cultural aspects and other elements.

8. Conclusion

This work-life balance tool would be particularly useful in service industries where workers directly interact with clients or customers. This tool attempted to quantify aspects of work-life balance that can be considered significant. This tool helps to measure the level of work-life balance of employees. By checking the level of work-life balance of employee organization can take corrective measures to increase the welfare of employees this tool helps introspection for all the working people and work towards it to enhance their inner strength to increase the level of balancing their personal and work life.

Authors Contribution

Authors developed the tool for work-life balance for employees of Insurance sector and collected required number of data, standardized the tool with the help of statistical tools, wrote this manuscript by two authors and taken care of English grammar part and plagiarism. The work of tool validation is done as part of PhD under the guidance of thesis advisor.

Acknowledgements

The authors would like to thank all the respondents who cooperated with the investigators from Insurance sector.

Disclosure statement

The authors declare that they have no competing interests.

Additional information

Funding

Authors have not received funding.

Notes on contributors

Vidya D Avadhani

Vidya D Avadhani, MBA, (PhD). Social media links: vavadhani (Instagram). [email protected] (Facebook). Having 12 years of Teaching experience as an Assistant Professor at the department of Management and Commerce Amrita School of Arts and Sciences, Mysore, India having two years of Industrial Experience, Presently pursuing PhD, I have published several articles in Scopus and Non Scopus journals.

Rethy B Menon

Rethy B Menon Ph,D,Mcom,M.Ed. Presently serving as an Assistant Professor (Sr.G) at the Department of Management and Commerce, Amrita School of Arts and Sciences, Mysore, India. Contributor of several publications in both Scopus and UGC journals. Currently a thesis advisor for research scholors.