The role of high performance work practices, work-family conflict, job stress and personality in affecting work life balance

Article history: Received: July 10, 2020 Received in revised format: October 18 2020 Accepted: November 4, 2020 Available online: November 4, 2020 The purpose of this research was to identify the role of high performance work practices of banks, work-family conflict, job stress, and personality of bank employees in affecting their work-life balance. To accomplish this goal, self-administered structured questionnaires were distributed to those bank employees who were either married, divorced, or separated, had children, and at least one year working experience in that bank. Final sample was comprised of 726 employees from 277 banks of South Punjab. The results revealed that high performance work practices of banks, family to work conflict, and personality type B behavioral patterns of bank employees increase their worklife balance, and work to family conflict of bank employees decreased their work-life balance. However, job stress and personality type A behavioral patterns of bank employees did not affect their work-life balance. Contrary to previous studies, these results suggest that moderate family to work conflict is actually good for work-life balance, and job stress and personality type A behavioral patterns are inherently not bad for work-life balance. Hence, State Bank of Pakistan should consider developing policies to enhance employee friendly high performance work practices in banks. Banks should also consider taking personality tests prior to recruiting and selecting employees for hectic posts. © 2021 by the authors; licensee Growing Science, Canada


Introduction
Work-life balance (WLB) is a notion to explain the balance between any individual's personal life and work (Dizaho & Othman, 2013). The term originated from the dichotomy of work-leisure which was invented in 1850s in Europe. Afterwards a great deal of research was carried out on work-leisure during 19 th and 20 th century (Burke, 1995). Although the concept of WLB balance existed long ago but the practice of WLB policies was first solidified in 1990s. Since then reputable companies are focusing on introducing WLB policies. But recently, the public's interest in work-life policies has enhanced tremendously (Lewis, 2009) because of its challenges and importance. WLB is important both for organizations and their employees. Because, it determines job satisfaction, mental health (Haar et al., 2014;Guest, 2002), life satisfaction, wellbeing, stress level, their behavior, and performance of employees both at work and home (Guest, 2002). Employees having better WLB can manage their personal and professional life much efficiently, which in turn facilitates organizational culture (Susi & Jawaharrani, 2011) and performance as well (Guest, 2002). WLB is becoming challenging due to increased workload, technological advancement, availability of younger workforce and globalization (Dizaho & Othman, 2013). Due to this rapid change in the labor market, it's becoming nearly impossible to balance the work and life (Lewis, 2009). As work and life are inseparable, so there is always a tug war situation while balancing the work and family. This situation creates pressure on the individual and hence work-family conflict arises (Jamadin et al., 2015) and stress generates (Gulzar & Khalid, 2016;Lewis, 2009). Situation becomes more critical in case of married people (Herman & Gyllstrom, 1977) especially those who have young children (Beutell & Greenhaus, 1980;Pleck, 1977), and have to look after their families (Hays, 1996;Reskin & Padavic, 1994).
To overcome these challenges, researchers identified several factors which can influence the WLB and can create conflict. These factors can be grouped into; family and personal life related, work related, and others. Family and personal life factors could be increased participation of women, child bearing women, dual career couples, single parent employees, dependents' care. Work related factors could be long working hours, unpaid overtime, increased part-time workforce, time squeeze, stress, and intensified work load. Whereas other factors could be aging, increased service sector, technological complexity, shortage of skills, loss of social support, demographic shift, and workforce globalization (Naithani & Jha, 2009). These factors not only influence the work and life but also makes the WLB challenging (Dizaho & Othman, 2013).
Challenges of WLB are increasing with every passing day. Because, labor market is changing dramatically and employees have to adjust themselves according to the market demands (Lewis, 2009). So, individuals are experiencing increasing levels of job demands. Because job responsibilities and working hours has been increased to cover the broader job scopes (Chang et al., 2017) in order to maintain high performing work system. These increased job demands are yielding job stress (JS). But how anyone will manage the stress is dependent upon the personality of that person (Hobfoll, 1989). So, in this research some of these factors were observed which can influence work-life balance. These factors are high performance work practices (HPWP) (Carvalho & Chambel, 2016;Macky & Boxall, 2008;Ronda et al., 2016), work-family conflict (Pattusamy & Jacob, 2016a, 2016b, JS (Bell et al., 2012;Karkoulian et al., 2016;Malun, 2011), and personality (Devadoss & Minnie, 2013;Devi & Rani, 2012;Wickramaaratchi & Perera, 2016). In short, objective of this research was to identify the role of HPWP of banks, work-family conflict, JS, and personality type behavior patterns (PTBP) of bank employees in managing their WLB.

High Performance Work Practices and Work-Life Balance
Previous studies on HPWP mainly focused on the firm level output rather than employees. Now researchers are focusing on the employee level outcomes as well (Fan et al., 2014;Ronda et al., 2016). Mostly observed the relationship of HPWP with employee's mental health (Jensen et al., 2013;Topcic et al., 2016), physical health (Ogbonnaya et al., 2017), well-being (Carvalho & Chambel, 2016;Fan et al., 2014;Macky & Boxall, 2008;Ogbonnaya et al., 2017), and work-family balance (Appelbaum et al., 2000;Berg et al., 2003;Carvalho & Chambel, 2016;Ronda et al., 2016). White et al. (2003) analyzed the linkage between HPWP and WLB, but they measured the WLB as work to home spillover. Because previously WLB was considered as absence of work-life conflict (Frone, 2003). Also, most of these studies concentrated on the work domain and family domain only and ignored the aspect of personal life, as in the studies of; Appelbaum et al. (2000), Berg et al. (2003), Carvalho and Chambel (2016), and Ronda et al. (2016). Results of these studies are still useful for this research because they still provide the insights on effects of HPWP on work and family aspects of WLB. Because WLB is the extension of the work-family construct (McNamara et al., 2013;Rantanen et al., 2011). These studies suggest that HPWP enhance work-family balance (Appelbaum et al., 2000;Berg et al., 2003;Ronda et al., 2016) by reducing the conflict and increasing the enrichment (Carvalho & Chambel, 2016). Furthermore, contrary to the common belief, White et al. (2003) suggested that there is no variance in work to home spillover of dual earning and single earning families. Because in dual earning families, females tend to join fewer demanding jobs. Also, young children are no longer important in defining it as well.
Moreover, Macky and Boxall (2008) analyzed the relationship between HPWP and work-life imbalance. Contrary to the above discussed studies which suggest that HPWP increase work-family balance (Carvalho & Chambel, 2016;Ronda et al., 2016), Macky and Boxall (2008) suggest that HPWP increase the work-life imbalance through long working hours, work overload and pressurizing work demands. They also affirmed these results by suggesting that HPWP and long working hours increase negative work to home spillover. However, incentives and bonuses reduce the negative spillover between work and home (Berg et al., 2003;White et al., 2003). Based on results of these studies, relationship between HPWP and WLB was hypothesized as: H1: High performance work practices of banks increase work-life balance of their employees.

Work-Family Conflict and Work-Life Balance
Work-family conflict is one of the widely studied topics in organizational behavior (Netemeyer et al., 1996). Both work and family are integral parts of any working person's life. But sometimes due to role incompatibility, work-family conflict arises. This work-family conflict can further result into several negative outcomes including; job dissatisfaction (Lu et al., 2017), JS (Jamadin et al., 2015;Lu et al., 2017), and dissatisfaction with personal and married life (Gareis et al., 2009;Pattusamy & Jacob, 2016a, 2016b. Managing the work-family conflict is all about keeping the boundaries between work and family responsibilities. Because, work-family conflict generates whenever the spillover across the boundaries of the work and family occurs. Hence, there must be balance between work demands and family resources, and also between family demands and work resources, in order to keep the work-family balance (Baltes et al., 2009). This theoretical assumption could be extended to the WLB as well.
Although there are many studies on work-family conflict but its relationship with WLB is not much explored. There are studies on the relationship of the work-family conflict and work-family balance. These studies suggest that work-family conflict decreases the work-family balance (Pattusamy & Jacob, 2016a, 2016b. Because work-family conflict can affect both quality of work life and non-work life (Md-Sidin et al., 2010). These studies focused only on the work and family domains. Many researchers still use the terms of work-family balance and WLB interchangeably (Bell et al., 2012). Because WLB is the extension of the work-family construct (McNamara et al., 2013;Rantanen et al., 2011). Results of a current study conducted on the linkage of work-family conflict and WLB also affirms this by suggesting that work-family conflict reduces WLB (Taşdelen-Karçkay & Bakalım, 2017). Hence, considering the results of previous studies, work-family conflict and WLB relationship was hypothesized as: H2a: Work to family conflict of bank employees decreases their work-life balance.
H2b: Family to work conflict of bank employees decreases their work-life balance.

Job Stress and Work-Life Balance
Although WLB is a progressing research construct, but there are few studies on the relationship between JS and WLB (Bell et al., 2012;Huang et al., 2017;Karkoulian et al., 2016;Malun, 2011;Meenu et al., 2016;Zaheer et al., 2016). Studies on the relationship of JS and WLB show different results. Some shows negative relationship (Bell et al., 2012;Meenu et al., 2016;Zaheer et al., 2016) whereas other shows positive relationship Karkoulian et al., 2016;Malun, 2011). The reason behind varying results lies in the operationalization of WLB by these researchers. Bell et al. (2012) measured the WLB as the equilibrium between work, family, and personal life. However, Meenu et al., (2016) reviewed the previous literature on WLB and identified that JS is the major contributor in decreasing WLB. Bell et al. (2012) identified that both perceived job pressure stress and job threat stress decrease the WLB. Whereas, the negative impact was much higher in case of job threat stress than job pressure stress. They suggested that quality of work experience matters more than the job demands in determining WLB.
Contrarily, Huang et al. (2017), Karkoulian et al. (2016), and Malun (2011) measured the WLB on the basis of work interference with personal life and personal life interference with work. Results of these studies suggested that JS increase work to personal life interference Karkoulian et al., 2016) and personal to work life interference (Karkoulian et al., 2016). However, Malun (2011) analyzed the relationship between JS and WLB inversely. Research suggests that worklife interference increases JS but the impact is not that significant. Karkoulian et al. (2016) suggested that the direction of interference is gender dependent. In case of females, relationship of JS with work interference with personal life was much stronger than the personal life interference with work. However, in case of males, JS was much stronger predictor of personal life interference with work, than work interference with personal life. Because, mostly employers are more understanding towards females to fulfill their family demands and relax them from work. Furthermore, Sarwar and Aftab (2011) analyzed the relationship between JS and family imbalance in the banking sector of Pakistan. They suggested that JS significantly increases the family imbalance. This research is being quoted because WLB construct also focuses on family along with work and personal life (McNamara et al., 2013;Rantanen et al., 2011). Zaheer et al., (2016) also affirmed that JS increase work-life imbalance. Hence, based on results of above discussed studies, relationship between JS and WLB was hypothesized as:
A study based on fuzzy relation mapping suggested that all of the big five personality traits have positive impact on the workfamily balance except neuroticism (Devadoss & Minnie, 2013). Contrary to these results, a study conducted on Indian females revealed that openness, extroversion, conscientiousness and emotional stability does not have any significant relationship with WLB. Only agreeableness was found to have positive relationship with WLB (Devi & Rani, 2012). However, a study conducted on banks in India, identified that extroverts are better at managing WLB as compared to people who are agreeable, conscientious and open minded. Because extroverts are better at managing stress as compared to others (Kundnani & Mehta, 2014). Another Indian study also supported that extroverts have higher WLB as compared to people who possess other traits (Kaur, 2013). But an African study found that only agreeableness, emotional stability and conscientiousness enhance WLB (Moshoeu, 2017).
The reason behind contradictory results of these studies could be the respondent's profile. As, Wickramaaratchi and Perera (2016) studied married employees and also proved that relationship between personality and WLB is significant for married employees. Whereas, Devi and Rani (2012) analyzed both single and married employees. So, this could be the reason behind varying nature of results. However, Kundnani and Mehta (2014) conducted the study on a very small sample of 42 bank professionals through a self-developed scale. Kaur (2013) targeted both male and female college teachers. And Moshoeu (2017) collected the data through a web-based survey without adhering to any specific target population.
Apart from big five personality, Myers-Briggs Type Indicator has also been used in the studies of personality and WLB. In a Sri Lankan study, relationship between personality and WLB was analyzed among academics. However, personality was measured through Myers-Briggs Type Indicator (MBTI). The results revealed WLB among Myers-Briggs personality types varies slightly but none of these personality types contribute towards work-life imbalance (Padmasiri & Mahalaekamge, 2013).
Considering the results of these studies, this research also focused on identifying the relationship between personality and WLB of bank employees. But personality was analyzed through personality Type A (PTA) and Type B (PTB) behavioral patterns rather than Big Five personality or Myers Briggs Personality. Because, focus of this research was on behavioral aspects of personality rather than personality traits. Previous literature suggests that people with PTA are hostile in nature, focus on competing and material acquisition. Whereas, people with PTB exhibit relaxed behavior and don't focus much on competing (Friedman & Rosenman, 1977;Strube, 2007). Therefore, PTA negatively influence, and PTB positively influence health and overall quality of life (Bortner, 1969;Friedman & Rosenman, 1977;Strube, 2007). Based on the characteristics of both PTBP and their possible outcomes, the relationship between personality and WLB was hypothesized as:

H4a: Personality Type A decreases work-life balance of bank employees.
H4b: Personality Type B increases work-life balance of bank employees.

Research framework
After analyzing the previous literature, a framework was developed to test hypotheses of this research, which is presented in

Instrumentation
Self-administered structured questionnaires were distributed to conduct survey. Questionnaire was consisted of 7 sections. Section 1 contained questions to screen those employees who were married, had children, and at least one year working experience in the current bank. Section 2 was based on demographic profile of respondents, including; age, gender, education, job level, working experience, marital status, working status of spouse, and number of children. Section 3 to 7 were based on items to measure variables of this research. Items of section 3 to 7 were measured on 6 point forced choice scale ranging from "strongly disagree" to "strongly agree". Forced choice scale was used to avoid any neutral response especially in negatively sounding questions. HPWP were measured from employees' perspective, based on their experience. They were operationalized as; performance management and evaluation practices, career management practices, training and development practices, team working practices, communication practices, and employee involvement practices. Measurement scale of Jensen et al., (2013) comprised of 15 items, was adopted to measure HPWP. Work-family conflict was measured from the inter role conflict between work and family (Greenhaus & Beutell, 1985). It was measured in both directions; from work to family, and from family to work. Measurement scale of Netemeyer et al., (1996) was adopted to analyze the work-family conflict in this study. The scale consists of 10 items, 5 related to work to family conflict (WFC), and 5 related to family to work conflict (FWC). JS was measured from the feelings of employees towards their job because of job demands and job environment (Ayuningrum, 2014;Karasek, 1979). Measurement scale of Ayuningrum (2014) consisting of 15 items, was adapted to measure JS in this study.
Personality was measured on the basis of PTBP. There are two major distinct categories of personality on the basis of behavioral patterns, PTA and PTB (Pervin, 2003). So, in this study personality was measured on the basis of these two types. In this study, PTA was operationalized as time observant, competitive, impatient, multitasker, fast, pushes oneself, and ambitious. Whereas, PTB was operationalized as casual, not very competitive, good listener, easy going, patient, have many interests, focus one thing at a time, unexpressive, and self-satisfied (Bortner, 1969). Measurement scale of Bortner (1969) was adapted to measure PTBP. Items of original scale were rephrased to specifically describe behavioral patterns in job environment. For this purpose, 11 items on PTA, and 3 items on PTB were taken from personality scale of Ayuningrum (2014). Ayuningrum (2014) adapted the scale from Wong (1991), Bortner (1969), and Friedman and Rosenman (1974). So, only those items were taken from the scale which fit to the personality characteristics of Bortner's (1969) scale. To balance out the scale, 7 more items of PTB were added based on Bortner's (1969) scale. So, final scale was comprised of 21 items, 11 on PTA and 10 on PTB.
WLB was analyzed from employee's view point based on its new definition, which states that WLB is about balancing the work, family, and personal life (Dizaho & Othman, 2013). Measurement scale of Valcour (2007) was adapted to measure WLB in this study. Slight changes were made in the sentence structure of original items to keep the rating scale format consistent, and to fit items on rating scale of strongly disagree to strongly agree.

Population and Sampling
Population of this research was employees of all public and private banks located in South region of Punjab Province of Pakistan. At the time of population identification, there were total 26 registered banks in South Punjab, which had 557 branches altogether. These banks and their branches were identified based on the information available on the official website of the State Bank of Pakistan (SBP). Because, SBP is central bank of Pakistan, and it regulates all other financial institutes of the country including banks (State Bank of Pakistan, 2016). Only those banks are included in this study which were categorized as banks by SBP (Pakistan Banks' Association; State Bank of Pakistan, 2016). Then, branches of each bank were identified through the official website of each bank, one by one. Lastly, those banks were omitted which were registered under SBP, but were not situated in South Punjab. There were total 35 banks registered under the SBP (State Bank of Pakistan, 2016), but only 26 banks were situated in the South Punjab, including government owned banks, privatized banks, and private banks. Foreign banks were excluded from the final list because they were not situated in South Punjab. Only those branches were targeted which are situated in the geographical boundaries of South Punjab. Hence, sample was extracted from these 557 branches of 26 banks.
Sample was extracted from the population through simple random purposive sampling. Banks were targeted through simple random sampling, and employees were targeted through purposive sampling. In this study, employees were screened purposively on the basis of following characteristics; (i) employee must be married, divorced or separated from their partner, (ii) employee must have children, and (iii) employee must have working experience of at least one year in the current bank. After randomly choosing a branch, Questionnaires were distributed systematically. Firstly, approval of the branch managers was taken for conducting the survey. Then, the managers were requested to identify those employees who meet preset criteria. After approval of the branch manager and identification of the required employees, questionnaires were distributed to employees. Consent of respondents was taken prior to the survey, in which anonymity of the collected data was assured.
Questionnaires were randomly distributed to 319 banks. Out of these banks, 14 (4.38%) refused to participate, 12 (3.76%) were inaccessible, and 16 (5.01%) did not returned questionnaires. So overall, out of 293 (91.84%) participating banks, 277 banks returned questionnaires, leading to a response rate of 86.83% at bank level. Total 1050 questionnaires were distributed after approval and identification of relevant employees by branch managers. Out of these questionnaires, 219 (20.85%) were not returned, 96 (9.14%) were purposively screened, and 9 (0.85%) were incomplete and improperly filled. So out of 1050 questionnaires, 726 were shortlisted for hypotheses testing, leading to a response rate of 69.14% at employee level. So, response rate at employee level was also good.

Demographic Profile
Fig. 2 presents demographic profile of respondents in terms of frequency and percentage of respondents in each demographic sub-category. These demographics were observed based on their highlighted importance in previous literature on work and life.

Descriptive and Normality Analysis
Descriptive analysis was performed to analyze the level of HPWP, work-family conflict, JS, PTBP, and WLB in banks of South Punjab. and maximum values of each variable indicate that cases with lowest possible and highest possible level of work-family conflict, JS, and WLB were part of sample. But in HPWP (Min= 1.53; Max= 6), and both PTA (Min= 1.9; Max= 6) and PTB (Min= 2; Max= 6) minimum value was slightly higher than 1. Conclusively these results suggest that bank employees in South Punjab exhibited more PTA and they experienced moderate levels of JS and FWC. But simultaneously, they experienced significant levels of WFC, HPWP, and WLB as well. The reason behind higher WLB in spite of higher WFC could be higher utilization of HPWP in banks of South Punjab. Regression analysis was performed further to understand this phenomenon better. Normality analysis was conducted to check normality of data symmetry and outliers through skewness and kurtosis statistics respectively (Pallant, 2013). Results of Table 1 indicate that skewness statistics of all variables are negatively skewed and less than 1, indicating that data distribution is symmetrical and normal (George & Mallery, 2010;Tabachnick & Fidell, 2007). Results of Table 1 (George & Mallery, 2010;Tabachnick & Fidell, 2007). But kurtosis values of HPWP (1.218), and PTA (2.000) lie within acceptable range of ±2 (George & Mallery, 2010;Tabachnick & Fidell, 2007). As none of kurtosis statistics are beyond 3, so data set is platykurtic and there is no issue of outliers in it. Furthermore, kurtosis statistics of PTBP, HPWP and WLB are positive, and kurtosis statistics of JS and work-family conflict are negative.

Reliability and Factor Analysis
Cronbach Alpha was observed to check internal consistency reliability, and principal component analysis with varimax rotation was performed to check indicators' convergent validity (Sekaran & Bougie, 2016). Table 2 presents the results of reliability and factor analysis of constructs of this study. Results of Table 2 indicate that all constructs are reliable as the Cronbach alpha coefficient of all variables is above 0.7 (Hair et al., 2014;Sekaran & Bougie, 2016). To establish convergent validity between indicators, items with factor loadings below 0.4 were dropped (Pallant, 2013). Hence, one item (PTA1) was dropped in PTA, and one item (PTB1) was dropped in PTB. So, 10 items were retained in PTA, and 9 items were retained in PTB. In other constructs, all items were retained as they exhibited satisfactory factor loadings of 0.5 and above (Hair et al., 2014).

Correlation Analysis
Correlation analysis was performed to identify any possible issue of multicollinearity, and establish discriminant validity (Sekaran & Bougie, 2016). Table 3 presents results of one tailed Pearson correlation analysis between variables of this study. Results of Table 3 indicate that correlation coefficient values between all variables are less than 0.8. Hence, there is no serious issue of multicollinearity between variables (Cooper & Schindler, 2007) in observed model, and hence, discriminant validity is established. Hence, all variables were retained for further analysis. Results of Table 3 further indicate that all possible variable pairs have significant correlations between them, except HPWP and WFC (r=-0.041, p>0.05).

Regression Analysis
Regression analysis was conducted to identify nature of relationship between variables and to test hypotheses. Table 4 presents results of hierarchical regression analysis to identify relationship of all independent variables with WLB. Hierarchical regression analysis was conducted to analyze individual confounding effects of variables. Results of Table 4 indicate that HPWP have highly significant and strongly positive effect on WLB (β=0.573, p<0.001), even after inclusion of other variables. The strength of relationship is only reduced after inclusion of PTB (β=0.363, p<0.001) and A (β=0.352, p<0.001). These results suggest that any increase in HPWP of banks will increase WLB of their employees, but PTBP can affect the magnitude of this increase in WLB. Hence, H1 is accepted.
JS initially exhibited quite significant and positive effect on WLB (β=0.103, p<0.01), in presence of HPWP and work-family conflict. But this relationship became insignificant and much weaker after inclusion of PTB (β=0.075, p>0.05) and A (β=0.073, p>0.05). These results suggest that opposing to the common belief, JS does not decrease WLB. In presence of HPWP and work-family conflict, it increases WLB, but after inclusion of PTB and PTA it does not affect WLB, neither positively nor negatively. Hence, H3 is rejected. Results indicate that PTB has highly significant and strongly positive effect on WLB (β=0.475, p<0.001), and the relationship remains significant even after inclusion of PTA (β=0.433, p<0.001). Suggesting that PTB increases WLB of bank employees in presence of HPWP, work-family conflict, and even JS, and inclusion of PTA traits does not affect this positive effect. Furthermore, PTA exhibits insignificant and weakly positive effect on WLB (β=0.098, p>0.05). Suggesting that in presence of HPWP and PTB, PTA does not reduce WLB. Hence, H4a is rejected, and H4b is accepted.

Discussion
Results of this research are quite interesting, as various commonly believed effects of observed variables are negated by these results. Conforming to the previous studies of Carvalho and Chambel (2016), McNamara et al., (2013), and Ronda et al., (2016), this research also proved that HPWP of banks increase WLB of their employees. Furthermore, WFC was proved to decrease WLB, as suggested by previous studies of Pattusamy and Jacob (2016a), and Taşdelen-Karçkay and Bakalım (2017). But results of FWC were contradictory to the previous studies of Jacob (2016a, 2016b), and Taşdelen-Karçkay and Bakalım (2017). As results of this research suggest that FWC increase WLB instead of decreasing (Taşdelen-Karçkay and Bakalım, 2017), or do not affecting it Jacob, 2016a, 2016b).
Reason behind the positive effect of FWC on WLB could be moderate level of FWC experienced by bank employees of South Punjab. Which might made it easier for them to fulfill time demands of family. Because when someone spends time with family to fulfill their time demands, it actually boosts their WLB. As WLB is about balancing the time between work, family, and personal life (Dizaho & Othman, 2013). It has also been proved that if a person's work does not interfere in fulfilling their family demands, then they experience higher WLB (Pattusamy & Jacob, 2016a;Taşdelen-Karçkay & Bakalım, 2017). Bank employees of South Punjab are already experiencing moderate level of FWC, therefore it is easier for them to manage it. Hence, this moderate level of FWC experienced by bank employees of South Punjab is actually boosting their WLB satisfaction rather than decreasing it.
Results of JS are also contradictory to the previous studies of Bell et al., (2012), Huang et al., (2017), Karkoulian et al. (2016), andZaheer et al. (2016). As results of this research suggest that JS does not affect WLB, in fact it increases WLB if someone does not react to it. Because relationship between JS and WLB only became insignificant after inclusion of PTBP. These contradictory results could be because after inclusion of PTBP, the r square value significantly increased from 0.212 to 0.283, and the relationship became insignificant and weak. This phenomenon suggests that JS inherently is not bad for WLB. In fact there are some other factors which boost the negative effects of JS stress on WLB.
Results of PTB are in line with the common belief that PTB yields positive results (Bortner, 1969;Friedman & Rosenman, 1977;Strube, 2007). But results of PTA are contradictory to the common belief that PTA always yield negative outcomes (Bortner, 1969). As results of this research suggest that PTA does not affect WLB. There could be various reasons behind these contradictory results. Firstly, people with PTA experience higher stress due to their impatient and hostile nature (Friedman & Rosenman, 1977;Strube, 2007). Along with this they are also workaholic and push themselves to achieve their goals, therefore, they experience health issues (Bortner, 1969). Results of this research suggest that bank employees of south Punjab experienced moderate level of JS. So as the JS was not so high so there might be a chance that bank employees had not exhibited those behavioral patterns which enhance stress level. Secondly, workaholic people enjoy working and push themselves to achieve their work goals (Bortner, 1969;Friedman & Rosenman, 1977;Strube, 2007). So, even though they spend more time on work and lesser time with family, they can still experience higher WLB, because their preference is work not family or themselves.

Conclusion, implications and future recommendations
This research focused on identifying the role of HPWP of banks, work-family conflict, JS, and PTBP of bank employees in affecting their WLB. Results were based on 726 employees of 277 banks situated in South Punjab. Results revealed that WLB of bank employees in South Punjab was highly affected by HPWP of banks, work-family conflict experienced by them, and exhibition of PTB. However, JS and PTA, does not affect WLB of bank employees in South Punjab.
Based on these results, SBP should consider implementing policies to enhance employee friendly HPWP in banks. So that all banks try to implement at least those practices. Implementation of such policies will not only reduce he negative outcomes of JS and WFC of bank employees, it will also enhance their perceived WLB. Furthermore, banks should consider inclusion of a personality test during recruitment and selection of a specific post. Especially if it is hectic and time consuming. Because PTBP of employees determine their perceived JS, work-family conflict, and WLB (Hobfoll, 1989). Also a more relaxed person can better handle an emergent situation, rather than someone who panics. So, people with PTB are usually good at managing a stressful situation due to their relaxed and easy going nature (Friedman & Rosenman, 1977;Strube, 2007).
Considering these results, future researchers should focus on identifying the factors which could boost negative effects of JS on WLB, either directly or indirectly. Also, more studies are required to prove that FWC is not bad for WLB, when experienced in lower or moderate levels. Findings of this research could not be generalized, as the respondents of this research were either married, divorced or separated, and had children. So, more general studies are required with consideration of various other demographics. Researchers should also focus on other factors which could mediate or moderate the relationship between these variables.