Expressions such as ‘there are not enough hours in the day’ and ‘the 25 h workday’ or cliché statements such as ‘working 24/7’ have become common overtones in the way employees feel about time at work. Because of this ‘lack of time’ feeling, alternative work arrangements such as flexitime, telecommuting and practices such as work–life balance have emerged as popular topics for researchers, employees, organisations and the like in the past few decades.
Setting
Women are still the main caregivers of family members and households, and compared to men, they are less likely to be granted flexitime by their employers. It therefore seems realistic to imagine that women would suffer more from work–life conflict. Women still earn, on average, less than men and are more likely to have part-time jobs. This has an impact on the financial well-being of women. These issues have yet to be investigated in an institution of higher learning in South Africa.
Aim
This study was aimed at determining: (1) the relationship between flexi work, financial well-being and work–life balance, productivity and job satisfaction, (2) the role of flexible work, financial well-being and work–life balance in productivity and job satisfaction, and (3) the mediating effect of productivity (job satisfaction in the alternative model) in the relationship between flexible work, financial well-being and work–life balance and job satisfaction (productivity in the alternative model).
Methods
A cross-sectional survey was used with a convenience sample (n = 252) of female support employees, employed in a higher education institution in the North West province of South Africa.
Results
Findings of the study indicated a statistically significant relationship between the variables. Results indicated that financial well-being, work–life balance and productivity were statistically significant predictors of job satisfaction, and in addition, subjective experiences of productivity serve as partial mediators in the relationship between financial well-being and work–life balance on the one hand, and job satisfaction on the other hand.
Conclusion
It seems like financial well-being and work–life balance play a more important role in job satisfaction and that financial well-being and work–life balance are more important for job satisfaction through subjective experiences of productivity. It would therefore make sense to increase experiences of financial well-being and work–life balance to address experiences of low levels of job satisfaction and subjective experiences of productivity.
Introduction
Work–life balance (WLB) and work–life satisfaction may have an impact on productivity in the workplace (Mušura, Korican & Krajnovic 2013). Chimote and Srivastava (2013) concluded that reducing absenteeism and turnover, improving productivity and image, and ensuring loyalty and retention are the benefits of WLB according to the organisational perspective, whereas the employees’ perspective highlighted job satisfaction, job security, autonomy, stress reduction and improving health as the benefits of WLB. Many organisations explore the various alternative work arrangements (AWA) to capitalise on the benefits of WLB.
Grobler and De Bruin (2011) noted that despite the benefits of AWA, very few companies in South Africa have more than 20% of their staff utilising flexi work practices at present. Employees’ use of flexitime is, however, not solely dependent on preference, but is also influenced by leader or manager perceptions (Bianchi & Milke 2010; Cooke 2005; Downes & Koekemoer 2011). A recent South African qualitative study (Downes & Koekemoer 2011) noted that work pressures and workload, client needs and expectations, leader or manager support or lack thereof, nature and scope of work, inherent job requirements, personal choice or working style, personal commitments and responsibilities, and supportive infrastructure, such as childcare that is flexible to adjust to changing work schedules, are the factors that restrict the use of flexitime. Downes and Koekemoer (2011) also revealed that frustration was evident in those participants whose access and use of flexitime were obstructed or reduced by such influencing factors. In addition, the Families and Work Institute’s 2008 ‘National study of the changing workforce’ reported that women are less likely to be granted flexitime by their employers compared to men.
The 2016 ‘Women at work report’ of the International Labour Organization (ILO) reported that among wage and salaried workers, gender wage gaps can be substantial but appear to be showing signs of a moderate reduction over time (International Labour Organization [ILO] 2016). Globally, the gender wage gap is estimated to be 23%; in other words, women earn 77% of what men earn (ILO 2011). Indeed, among 37 countries and territories with data for two periods, the gender wage gap has generally shown a reduction; this can be seen from the simple average of the gap in these countries, which has declined from 21.7% to 19.8%. The ILO has noted that, without targeted action, at the current rate, pay equity between women and men will not be achieved before 2086 (ILO 2016). Steyn and Jackson (2015) also reported evidence of gender-based wage differences in a selection of South African companies. They found evidence for higher post gradings and salary for males compared with those of females. However, the differences that were observed were not statistically significant and this suggests a numerical but not a statistical or practical meaningful wage gap.
Productivity has become a driving force for flexibility in the workplace and because of that many employees and employers are interested in flexibility programmes (Avery & Zabel 2001; Bond et al. 2005). Organisations are constantly trying to improve employee productivity; therefore, implementing flexible working arrangements in the first place is a good incentive for doing so (Bond et al. 2005). Pinsonneault and Boisvert (2001) confirm that improved productivity associated with telecommuting is the most cited organisational benefit in the literature. In their research, they cited 24 studies about telecommuting and the positive impact it had on individuals and organisations. Flexitime scheduling allows for more job autonomy and, consequently, leads to higher job productivity and performance (Dodd & Ganster 1996; Hackman & Oldham 1976) and job satisfaction (Cao 2005; Neufeld 1997; Thomas & Ganster 1995). AWA such as flexitime and job satisfaction are a heavily researched relationship and one of the most commonly reported associations in the literature (Pinsonneault & Boisvert 2001). Several studies have found that employees who report high levels of work–family conflict had lower job satisfaction than their counterparts with low levels of conflict (Bedeian, Burke & Moffett 1988; Frone, Russel & Cooper 1997; Netemeyer, Boles & McMurrian 1996; Rice, Frone & McFarlin 1992). The productivity, job satisfaction, flexitime, work–life balance and financial well-being relationship in an institution of higher learning (IHL) in South Africa are, however, not such a common reported association in the literature and are in fact lacking.
Given the above-mentioned factors, women are less likely to be granted the permission to use flexitime at work, experience more work–life conflict and pro-male gender wage inequalities and, therefore, being in a disadvantaged position regarding their financial well-being. In this study, we were interested in the role of flexi work, work–life balance and financial well-being in job satisfaction through subjective experiences of productivity of women in an IHL. As job satisfaction has been studied, there is a debate whether it is utilitarian as a concept or whether anything productive is necessarily a result of the satisfaction. A quantitative review of the literature suggested that the true correlation between job satisfaction and performance was quite small (0.17) (Iaffaldano & Muchinsky 1985). However, more recent evidence reveals that the relationship is larger than what was previously thought. A comprehensive review of 300 studies determined that when the correlations are corrected for the effects of sampling error and measurement error, the average true score correlation between overall job satisfaction and job performance is 0.30 (Judge et al. 2001). Therefore, it appears that a happy worker is more likely to be a productive one. Of course, the relationship between satisfaction and performance may be reciprocal. Not only may employees who are happy with their jobs be more productive, but performing a job well may lead to satisfaction with the job, especially if good performance is rewarded (Judge & Klinger 2009). Given the possible reciprocal nature of the job satisfaction–productivity relationship, we were rather interested in the productivity–job satisfaction relationship. Given the happy worker–productive worker hypothesis and in order to gain a comprehensive picture, we also tested the alternative job satisfaction–productivity relationship. More specifically, we investigated the mediating role of subjective experiences of productivity (job satisfaction in the alternative model) in the relationship between flexi work, work–life balance and financial well-being on the one hand, and job satisfaction (productivity in the alternative model) on the other hand.
Literature review
This research project proposes a model that depicts flexible work, financial well-being and work–life balance as important antecedents for subjective productivity and job satisfaction. In addition, it is argued that flexible work, financial well-being and work–life balance increase the subjective experiences of productivity and job satisfaction. More specifically, it is maintained that productivity (job satisfaction in Model 2) serves as a mediator in the relationship between flexible work, financial well-being and work–life balance and job satisfaction (productivity in Model 2). Mediators are variables that provide additional information on how or why two variables (dependent and independent) are strongly associated with each other. According to Wu and Zumbo (2008), for a mediation model, the independent variable (in this case, flexible work, financial well-being and work–life balance) is presumed to cause the mediator (e.g. productivity in Model 1 and job satisfaction in Model 2), and, in turn, the mediator causes the additional influence of the independent variable on the dependent variable (e.g. job satisfaction in Model 1 and productivity in Model 2). The hypothetical model illustrating the mediating effect of productivity (job satisfaction in the alternative model), as suggested, is depicted in Figure 1. (Fransman 2015)
The hypothetical model.
Independent variables (flexible work, financial well-being and work–life balance)Flexible work
Business leaders continue to adopt non-traditional work–life benefit policies, including virtual work programmes, in response to the financial savings realised and the unique flexibility these programmes offer (Purvanova 2014). Workplace flexibility as defined by Hill et al. (2008:152) is ‘the ability of workers to make choices influencing when, where, and for how long they engage in work-related tasks’. They explain further that it is a multi-faceted concept that includes discretion over where work is performed (e.g. telecommuting), the duration of individual and collective sessions of work-related tasks (e.g. part-time employment), as well as options for multiple points of entry and departure from paid work, for example, career flexibility (Hill et al. 2008) (Fransman 2015).
Flexibility is referred to by Costa, Sartori and Akerstedt (2006) as the level of individual discretion and autonomy. Literature classifies flexible work practices as office-based practices and flexi-place practices (Grobler & De Bruyn 2011); as well as flexitime and flexi-place (Munsch, Ridgeway & Williams 2014). Kelly, Moen and Tranby (2011) refer to flexibility as schedule control, because flexible work options can include contingent work, contract work and just-in-time staffing. The extent to what employees experience as flexible working hours requires supportive organisational culture (Galea, Houkes & De Rijk 2014), and it is important that management within organisations acknowledges the fact that employees go through different phases during careers and specific requirements can change (Fransman 2015).
Results indicated that job flexibility, such as flexi-place (telework) and flexitime, has a positive effect on WLB (Hill et al. 2001). Research by Moen et al. (2011) argues that greater employee work-time control and flexibility by means of an organisational policy initiative can reduce employee turnover. Increased competitive advantage, higher productivity, attraction and retention of top talent are also some of the benefits for employers, while they list improved employee morale and quality of life, as well as decreased unscheduled absences as benefits for employees (Grobler & De Bruyn 2011). Most employers adopt flexible work practices as a means to achieve greater operational efficiency (Appiah-Mfodwa et al. 2000). Flexible work has the potential to benefit employees and organisations alike by supporting positive job attitudes such as organisational commitment, motivation and job satisfaction and high levels of job performance (Fransman 2015; Leslie et al. 2012; Nadeem & Henry 2003).
Financial well-being
Originally, financial well-being was understated as simply happiness or general satisfaction with the financial situation. Based on the results of Census 2011, the official unemployment rate among men was 25.6%, while among women it was 34.6%, where the average female-headed household income was just more than half the annual income less than their male counterparts (Statistics South Africa 2012). Economic pressures over the past 20 years have challenged the traditional role of men at work and women at home (Crompton & Lyonette 2007). With more than 40% of households headed by women, and many of the rest dependent on the financial contribution women make (Van Rooyen 2014), it is unfortunate that many women are not as financially healthy as they could or should be (Fransman 2015).
Basic needs are closely linked to a physiological interpretation of those things that are vital to human survival (Quellette et al. 2004), specified as food, clothing, shelter, water and sanitation that are necessary to prevent ill-health and under-nourishment. Quellette et al. (2014) explain further that relative material needs are needs that may vary depending on circumstances or norms such as social wealth and context. As a society gets richer, the relative standard of needs changes to reflect societal wealth. Within contextual terms, a basic need, such as food, may be set in relative terms far above the physiological minimum, but may correspond to a view as to what people ‘should’ have (Fransman 2015).
The reality is that women do face more financial risks than men do. Women, who earn less, are expected to live 7 years longer in retirement and the majority of mothers are single breadwinners. Women remain the main caregivers in the South African society, with a high rate of single mothers; therefore, children’s well-being depends on their mother’s financial stability (Liberty Advisory Services 2014) (Fransman 2015). Pay and perceptions seem therefore important for financial well-being. Although pay level is not an important issue for global job satisfaction, pay fairness can be very important. People are not concerned if those in other jobs make more money, but they are concerned if people in the same job earn more. Pay satisfaction is affected by how an individual’s salary compares to the others in the same rather than people in general jobs, according to the equity theory of motivation (Jawahar & Stone 2011; Judge et al. 2010; Spector 1997; Williams, McDaniel & Ford 2007; Williams et al. 2008). Rice et al. (1990) found a significant practically large correlation (0.50) between pay and job satisfaction in a sample of mental health professionals who all had the same jobs. Mitchell, Lewin and Lawler (1990) estimate that the proper use of piece-rate plans leads to performance gains in 10% – 15%.
Work–life balance
Work–life balance is described by Jyothi and Jyothi (2012) as achieving a balance between the demands of employees’ family life and work lives. Satisfaction with the work–life balance is defined by Valcour (2007:1513) as ‘an overall level of contentment resulting from an assessment of one’s degree of success at meeting work and family role demands’ (Fransman 2015). The traditional South African household (where the man was the sole earner and the woman took care of the children) is being replaced by working couple families (Schreuder & Theron 2001). Globally, the traditional role of a woman as the main caretaker of the family has also changed dramatically. Women nowadays strive to contribute as both paid worker and as productive family caretaker (Sekaran & Leong 1992). While the work responsibility is perceived to be a man’s primary area, women are still mainly responsible for the home and children (Doucet 2000; Windebank 2001). As such, employed women have to manage with the demands from work, together with family roles, to a greater extent than employed men (Coetzer 2006). Duxbury and Higgins (2001) found that women are more likely than men to report high role overload, and men more likely to report high levels of work-to-family conflict. Studies done by Galea et al. (2014) explored flexible working hours as a win-win situation for both employers and employees, and found that flexible working hours appeared to be a tool to facilitate the flow of transition between work and personal life. Making use of flexible working hours enables employees to manage priorities on hand, either family or personal needs or organisational needs. (Fransman 2015)
Providing flexible working arrangements can be mutually beneficial to both workers and employers. When combined with regular childcare measures, flexible work arrangements can contribute to work–family harmonisation. With AWA, workers, primarily mothers, do not have to take a career break or leave the workplace entirely to provide care (ILO 2016). For employers, even small and medium-sized enterprises, these schemes improved staff retention, motivation and engagement without detrimental costs or implementation challenges for businesses (Chartered Institute of Personnel and Development 2012). In addition, the work–life balance and job satisfaction link was confirmed by Malik, Saleem and Ahmad (2010). Chimote and Srivastava (2013) concluded that WLB reduces absenteeism and turnover, and improves productivity.
Job satisfaction
Job satisfaction is described in the literature as an important attitude of employees and managers to their jobs (Oplatka & Mimon 2008) and one’s feelings about a job (Bogler 2005). Any person with a high degree of job satisfaction will in comparison display a positive attitude towards his or her career (Pirbasti et al. 2014). McShane and Von Glinow (2010) describe job satisfaction as a person’s evaluation of his or her job and work context – it is an appraisal of their perceived job characteristics, work environment and emotional experiences at work. Job satisfaction represents the well-being of employees and is predictive of higher job tenancy and lower counterproductive behaviours and withdrawal (Grandey, Cordeiro & Crouter 2005) (Fransman 2015). High rates of employee job satisfaction are associated with high commitment levels and elevated productivity (Rama Devi & Nagini 2013).
According to the perceived organisational supportiveness (POS) theory of Eisenberger et al. (1986), if workers perceive that their organisation shows concern and sensitivity to its personnel and their needs and values, including work–family needs, they will respond by showing positive job-related outcomes, such as job satisfaction and organisational commitment. Employees engaged in more effective and flexible workplaces are more likely to have greater engagement in their jobs and higher levels of job satisfaction (Bond et al. 2005). Cross-sectional research done by Booth and Van Ours (2008) indicated that women were less satisfied with their jobs if it was full time. If supervisors of firms tend to not concern themselves about the quality of subordinates’ work–family lives (Kim, Lee & Sung 2013), employees may not appreciate the firms’ efforts towards work–family obligations, which can provide damaging effects on their job attitudes (Fransman 2015).
A variety of research findings have shown that poor work–home and home–work interaction is linked with serious consequences for the individual (including poor self-rated, negative emotions and depression, low energy and optimism, fatigue, sleep disorders – stress, stress-related illness, family strife, violence, divorce, reduced life satisfaction and substance abuse, increased stress and burnout) and the organisation (withdrawal behaviour, including turnover and non-genuine sick absence and escalated absenteeism, and healthcare costs, as well as reduced productivity, employee satisfaction, commitment and loyalty towards the organisation), all of which negatively impact the organisational performance and, consequently, organisational profits (Allen et al. 2000; Anderson, Coffey & Byerly 2002; Hämmig & Bauer 2009; Hughes & Bozionelos 2007; Thomas & Ganster 1995). Green and Heywood (2011) suggested that flexible work had a general positive influence of job satisfaction (Fransman 2015). In addition, the AWA–job satisfaction relationship seems to be leaning towards a positive, albeit small-to-medium effect size. Reasons for positive attributes of the alternative work arrangement (flexi work and telecommuting) and job satisfaction relationship entail increased flexibility, job autonomy, control of work schedule and circadian rhythms (Sukal 2009). Pay, wage rate, income, salary or the perceptions of fairness thereof (Kreitner & Kinicki 2008; Okpara 2004; Rad & Yarmohammadian 2006; Viera 2005) are significantly related to job satisfaction. Based on the above-mentioned factors, it can therefore be expected that perceptions of access to flexi work arrangements, financial well-being and work–life balance would be related to job satisfaction.
Subjective experiences of productivity
Productivity is the ability to carry out a duty or job that sustains the profitability of the organisation. It is a comparison of the amount of effectiveness (ratio of inputs and outputs) that results from a certain level of cost associated with that effectiveness (Sukal 2009). Productivity indicates the extent to which a firm’s human capital is efficiently creating output (Guthrie 2001) (Fransman 2015). It is important to note that we are looking at the role of subjective productivity at work and therefore in line with Guthrie (2001) and Sukal (2009), we are here dealing with employees’ subjective views of their ability to carry out a duty, job or task that sustains profitability through the organisation and efficiently creating output. The basis of productivity management should be the aim of management to provide appropriate conditions to achieve the highest performance (Nazem & Seifi 2014). The workforce will be remembered as one of the most important resources in achieving organisational productivity (Pirbasti et al. 2014). Companies can increase their productivity by increasing the well-being of personnel (Pietilä, Lahdensaari-Nätt & Tuure 2011). Flexible working hours enhance staff productivity and lower overheads, while staff members have a significantly better work–life balance, higher satisfaction and motivation (Fransman 2015; Symanowitz 2012). Many employers have discovered that increasing work schedule flexibility does not interfere with maintaining acceptable levels of productivity (Reese, Rowings & Sharpley 2007). Pay influences perceptions of financial well-being. At the individual level, there are three major types of pay-for-performance systems: traditional incentive systems, variable pay configurations and merit pay plans. Traditional incentive plans include piece-rate plans and sales commissions. With piece-rate incentive plans, an employee is paid a specified rate for each unit produced or each service provided. Mitchell et al. (1990) estimated that the proper use of piece-rate plans leads to performance gains in 10% – 15%. Based on their review of the literature, Locke et al. (1980) concluded that the median productivity improvement from piece-rate plans is 30%.
Contextualising the study
The promotion of well-being should be connected to management and the structure of personnel administration, and should be taken into account in strategies and processes, as well as be included in daily activities (Pietilä et al. 2011). The institution, from which the sample was taken, has an employee wellness policy in place where the aim is to improve employees’ work, psychological and physical wellness needs. The objective of the wellness programme is to improve the institution’s health and wellness strategy in order to contribute to the morale, productivity and the quality of life of employees. The programme provides services such as personal or financial counselling, managerial services, help with planning of a vacation, car emergencies, trauma counselling, buying of a house, relocation and even help with employees’ children’s homework. The idea is that employees make use of trained consultants to help manage the time-consuming pressures and stressors of daily life, instead of carrying the burden all by themselves. Despite services rendered by the wellness department to employees, aiming to enhance well-being, very little is known about the role of flexi work, financial well-being and work–life balance in subjective experiences of productivity and job satisfaction by women employed by the IHL where this study was conducted. In addition, scientifically speaking, the link between flexi work, financial well-being, work–life balance, productivity and job satisfaction is still very vague in the South African context (and more specifically in IHL) (Fransman 2015).
Mediators are variables that provide additional information about how or why two variables (dependent and independent) are strongly associated with each other. In the case of this project, a mediation model is proposed where the independent variable (flexible work, financial well-being and work–life balance) is presumed to cause the mediator (productivity and job satisfaction in the alternative model), and, in turn, the mediator causes the additional influence of the independent variable on the dependent variable (job satisfaction and productivity in the alternative model) (Fransman 2015). Given the above-mentioned role of flexi work, work–life balance and perceptions of financial well-being, it can be expected that the independent variables in this study would influence productivity and job satisfaction in this sample. Not only may employees who are happy with their jobs be more productive (in the alternative model), but performing a job well may lead to satisfaction with the job (Judge & Klinger 2009). Given the reciprocal nature of the job satisfaction–productivity relationship, we were rather interested in the productivity–job satisfaction relationship. However, to gain a comprehensive view, we also tested the alternative model production–job satisfaction model. More specifically, we investigated the mediating role of subjective experiences of productivity (job satisfaction in the alternative model) in the relationship between flexi work, work–life balance and financial well-being on the one hand, and job satisfaction (subjective experiences of productivity in the alternative model) on the other hand.
This project was aimed at filling this void. Therefore, the aim of the study was to test the following hypotheses:
H1: The independent variables (flexi work, work–life balance and financial well-being) are significantly positively related to subjective experience of productivity.
H2: The independent variables (flexi work, work–life balance and financial well-being) are significantly positively related to job satisfaction.
H3a: Subjective experiences of productivity mediate the relationship between the independent variables (flexi work, work–life balance and financial well-being) and job satisfaction (the hypothesised model).
H3b: Job satisfaction mediates the relationship between the independent variables (flexi work, work–life balance and financial well-being) and subjective experiences of productivity (the alternative model: Model 2).
Research objectives
The main goal of the study was to investigate the role of flexible work, financial well-being and work–life balance in the productivity and overall job satisfaction in a sample of women employed in an IHL. More specifically, this study was aimed at determining: (1) the relationship between flexi work, financial well-being and work–life balance, productivity and job satisfaction, (2) the role of flexible work, financial well-being and work–life balance in productivity and job satisfaction, and (3) the mediating effect of productivity (job satisfaction in the alternative model) in the relationship between flexible work, financial well-being and work–life balance and job satisfaction (Fransman 2015) (productivity in the alternative model).
Research methodResearch approach
A quantitative research approach with a cross-sectional design was used. Web-based questionnaires, accompanied by a covering e-mail, explaining the aim of the project, the anonymity and voluntary nature of the research and an invitation letter with contact information of the researchers were distributed to most female employees in support departments of the IHL (Fransman 2015). Participation in the study was entirely optional.
Sampling
Participants for the study were female support staff of a South African IHL, employed both full time (permanent and fixed-term appointments) and part-time (temporary). A small convenient sample was taken from female employees in all support divisions of an IHL in the North West province. The respondents each completed a web-based questionnaire divided into two parts, which included items concerning the respondent’s biographical details. Table 1 represents the demographic characteristics of the participants (n = 252) (Fransman 2015).
Participant characteristics.
Item description
Category
Frequency
%
Gender
Female
252
100.00
Age
21–25
50
19.84
26–35
82
32.54
36–45
50
19.84
46–55
43
17.06
56–65
27
10.71
Ethnicity
Black people
23
9.13
Mixed race people
18
7.14
Indian people or Asian people
1
0.40
White people
210
83.33
Marital status
Married
135
53.57
Divorced
29
11.51
Single
83
32.94
Widowed
5
1.98
Highest qualification
Senior certificate
35
13.89
Higher certificate
10
3.97
Advanced certificate
4
1.59
Diploma
14
5.56
Advanced diploma
10
3.97
Bachelor’s degree
47
18.65
Bachelor honours degree
71
28.17
Master’s degree
50
19.84
Doctoral degree
11
4.37
Employment status
Permanent
184
73.02
Fixed-term
22
8.73
Temporary
46
18.25
Management level
Executive
1
0.40
Senior
11
4.37
Middle
60
23.81
Not in management
180
71.43
Source: Fransman, E.I., 2015, ‘Determining the impact of flexible work hours on women employed in a higher education institution’, Unpublished MBA dissertation, North-West University, Potchefstroom.
Table 1 indicates that the sample represented only female employees. The respondents (n = 252) consisted mainly of employees between the ages of 26 and 35 years (32.54%), with white people being major participants (83.33%). Married participants were the most (53.57%), followed by singles (32.94%). Almost half of the participants were either in possession of a bachelor honours degree (28.17%) or a bachelor’s degree (18.65%), were employed in permanent positions (73.02%) and not in management (71.43%) (Fransman 2015).
Measuring instruments
The measuring instruments consisted of six sections: flexibility, financial well-being, work–life balance, job satisfaction, productivity and demographics. All scales (except for the demographics section) followed a five-point Likert format ranging from strongly disagree (1) to strongly agree (5) and negatively phrased item scores were reversed before the analyses so that positive scores could reflect the targeted construct. The Cronbach’s alpha coefficients (which is used to determine the internal consistency and reliability) that were obtained in this study for the instruments used are reported in Table 2. Instruments that were used include in the study were the following (Fransman 2015):
Flexible work: A seven-item measure, developed for the project, was used to determine the support for flexibility in the workplace and the use of flexi work by the participants. Of the four items, one item was adapted from Thomas and Ganster’s (1995) control scale (e.g. control over hours worked each day or week) (Fransman 2015).
Financial well-being: This instrument, developed for the project, was a seven-item measure of the extent to which employees are satisfied with their current financial situation, that is, the household is able to secure necessities, being fairly compensated, being satisfied with their basic living standards and receiving a certain level of income to be able to live a safe and healthy life. A typical item was ‘My level of income enables me to live a safe and healthy life’ (Fransman 2015).
Work–life balance: This instrument, developed for the project, consisted of seven negatively phrased items where participants had to measure the current work–life balance support of their organisation, energy levels at the end of the workday, doing work at home and workload. A sample item included ‘I am too involved with my work and hardly have time for family responsibilities’. Scores of the negative phrased items in this scale were reversed before analysis (Fransman 2015).
Job satisfaction: A seven-item scale was adapted from Cammann et al. (1979) and measured the level of job satisfaction of respondents. This measure assesses aspects such as looking forward to going to work, feeling positive about your work on a Monday morning, feeling valued and affirmed at work, having an opportunity to do what you do best at work and whether your manager cares about you. ‘I feel positive about my job’ is a sample item of this scale (Fransman 2015).
Subjective experiences of productivity: This eight-item instrument was developed for the study and measures subjective experiences of productivity of respondents. It focuses on issues such as whether respondents are productive, give their best at work, complete planned weekly tasks, the quality of their work, whether managers acknowledge the work done by them and whether team members appreciate their efforts. One of the items in the scale was ‘My quality of work is high’. (Fransman 2015).
A biographical questionnaire was also included, dealing with biographical questions such as age, ethnicity, marital status and employment status (Fransman 2015).
Descriptive statistics (n = 252) and correlation analysis.
Variables
Α
Mean
SD
1
2
3
4
1. Flexible work
0.80
3.87
0.72
-
-
-
-
2. Financial well-being
0.88
3.13
0.86
0.11
-
-
-
3. Work–life balance
0.84
3.10
0.83
0.05
0.35*
-
-
4. Job satisfaction
0.89
3.48
0.81
0.06
0.39*
0.36*
-
5. Productivity
0.77
3.88
0.57
0.04
0.24*
0.25*
0.69*
, Correlation is significant at the 0.01 level (2-tailed).
Source: Fransman, E.I., 2015, ‘Determining the impact of flexible work hours on women employed in a higher education institution’, Unpublished MBA dissertation, North-West University, Potchefstroom.
Data analysis
The statistical analysis was completed with the aid of the SPSS program (SPSS Inc. 2010). Descriptive statistics including means, standard deviations, skew and kurtosis were used to analyse the data. The Cronbach’s alpha coefficients were used to determine the internal consistency. Pearson’s product–moment correlation coefficients were used to stipulate the practical relationship between the variables in terms of statistical significance. A stepwise multiple regression analysis was conducted to determine the proportion of variance in the dependent variable of productivity that was predicted by the independent variables, namely, flexible work, financial well-being, work–life balance and job satisfaction (Fransman 2015).
A multiple regression analysis was also conducted to determine the proportion of variance in the dependent variable of job satisfaction that was predicted by the independent variables, namely, flexible work, financial well-being, work–life balance and productivity. The parameters 0.10 (small effect), 0.30 (medium effect) and 0.50 (large effect) were set for practical significance of R2 (Steyn 1999). A cut-off point of 0.30 (medium effect) was set for the practical significance of correlation coefficients (Cohen 1988). The effect size in the case of multiple regressions is given in the formula f2=R21−R2 (Steyn 1999), to indicate whether obtained results were practically important. The parameters 0.01 (small effect), 0.09 (medium effect) and 0.35 (large effect) were set for practical significance of f2 (Steyn 1999). Structural equation modelling (SEM) was performed using AMOS 21 (Arburkle 2014) program to investigate the mediating role of productivity in the relationship between flexible work, financial well-being, work–life balance and job satisfaction (Fransman 2015).
Ethical consideration
Ethical clearance was first obtained from the research unit and thereafter faculty management provided approval to conduct the study.
Results
The results of the study are presented in three parts: firstly, the exploratory factor (factorial validity) analysis; secondly, descriptive statistics and correlational analyses of all the measures in the study; thirdly, the regression analysis with subjective experience of productivity and job satisfaction as dependent variables; and lastly, testing for the mediating effect of productivity (job satisfaction in the alternative model) in the relationship between flexible work, financial well-being, work–life balance and job satisfaction (subjective experience of productivity in the alternative model) of female employees in an IHL (Fransman 2015).
Factorial validity
All items used in the study were subjected to an exploratory factor analysis to determine if items loaded on the intended scales. The results of the exploratory factor analyses and inspections of the screen plots and eigenvalues showed that eight factors that explained 66.60% of the variance could be extracted. However, difficulty in interpreting the multi-factorial solutions because of double loadings, loading of items on unintended factors and a sharp decline of the eigenvalues after the fifth factor, as well as closer inspection of the screen plot, led us to the decision to subject the individual items of separate scales to separate exploratory factor analysis.
The results of the separate exploratory factor analyses and inspections of the screen plots and eigenvalues of the factors indicated that all scales used to assess the variables were unidimensional. The choice for one factor was based on difficulties in interpreting multi-factorial solutions as well as on the significant decrease of the eigenvalue after the first factor. The unifactorial solutions extracted explained 52.65% of the variance in flexible work (with item loadings ranging from 0.32 to 0.89); 54.74% of the variance in financial well-being (with item loading loadings ranging from 0.74 to 0.83); 52.29% in work–life balance (with item loading loadings ranging from 0.46 to 0.85); 60.51% in job satisfaction (with item loading loadings ranging from 0.73 to 0.84); and 40.68% of the variance in productivity (with item loading loadings ranging from 0.44 to 0.75) (Fransman 2015).
Descriptive statistics and correlational analyses
The descriptive statistics and correlation results for the variables in the study are presented in Table 2. An assessment of Table 2 indicates that all the alpha coefficients were higher than the guideline of an acceptable alpha coefficient larger than 0.70 (Nunnally & Bernstein 1994) (Fransman 2015).
Table 2 reveals that flexible work and financial well-being were statistically positively related to one another (small effect sizes). Financial well-being was practically significantly related (medium effect) to work–life balance and job satisfaction, and statistically significantly related to productivity (small effect). Work–life balance was also positively related to both job satisfaction (medium effect) and productivity (small effect). Job satisfaction was statistically significantly related to productivity (large effect) (Fransman 2015).
Regression analysis to determine the impact of flexible work, financial well-being and work–life balance as predictors of productivity and job satisfaction
The study also covered the impact of flexible work, financial well-being, work–life balance and productivity as predictors of job satisfaction for female employees. On the other hand, the impact of flexible work, financial well-being, work–life balance and job satisfaction as predictors of productivity also needed to be determined. Regression analyses with flexible work, financial well-being and work–life balance as predictors of productivity and job satisfaction are presented in Table 3 (Fransman 2015).
Regression analysis with flexible work, financial well-being and work–life balance as predictors of productivity and job satisfaction.
Variable
Productivity: Standardised β
Job satisfaction: Standardised β
Step 1
Step 2
Step 1
Step 2
1. Flexible work
0.03
0.00
0.04
0.02
2. Financial well-being
0.17*
−0.03
0.29**
0.19**
3. Work–life balance
0.19*
−0.01
0.25**
0.14**
4. Productivity
–
–
–
0.61**
5. Job satisfaction
–
0.70**
–
–
R
0.30
0.69
0.45
0.74
R2
0.09
0.47
0.21
0.54
F2
0.10
0.89
0.27
1.17
Practical significance: Effect size
Medium effect
Large effect
Medium effect
Large effect
f2 parameters set for practical significance: 0.01 ≥ small effect/0.09 ≥ medium effect/0.35 ≥ large effect/ *p < 0.05. **p < 0.01.
Source: Fransman, E.I., 2015, ‘Determining the impact of flexible work hours on women employed in a higher education institution’, Unpublished MBA dissertation, North-West University, Potchefstroom.
Closer inspection of Table 3 shows that flexible work, financial well-being and work–life balance account for 9% (medium practical significance) of the variance in productivity, with financial well-being (β = 0.17/t = 2.66) and work–life balance (β = 0.19/t = 2.91) proving to be statistically significant predictors of productivity. However, with the inclusion of job satisfaction in the second model, the variance explained in productivity increased from 47% (large practical significance) with job satisfaction (β = 0.70/t = 13.52), proving to be the only statistically significant predictor of subjective experience of productivity (Fransman 2015).
Flexible work, financial well-being and work–life balance also explain 21% (medium practical significance) of the variance in job satisfaction, with financial well-being (β = 0.29/t = 4.79) and work–life balance (β = 0.25/t = 4.16), proving to be statistically significant predictors of job satisfaction. However, with the inclusion of productivity in the second model, the variance explained in job satisfaction increased from 21% to 54% (large practical significance) with financial well-being (β = 0.19/t = 3.97), work–life balance (β = 0.14/t = 2.94) and productivity (β = 0.61/t = 13.52) proving to be the statistically significant predictors of job satisfaction (Fransman 2015).
The mediating effects of productivity in the relationship between flexible work, financial well-being and work–life balance on the one hand, and job satisfaction on the other hand
Structural equation modelling was performed using AMOS 20 (Arburkle 2013) to test for mediating effects of productivity (job satisfaction in the alternative model) in the relationship between flexible work, financial well-being and work–life balance on the one hand, and job satisfaction (productivity in the alternative model) on the other hand. The hypothesised model was a mediation model in which flexible work, financial well-being and work–life balance influenced perceived productivity (job satisfaction in the alternative model), which, in turn, had an impact on job satisfaction (productivity in the alternative model). A closer examination of the direct and indirect effects was made to evaluate their relative sizes. The result of the hypothesised model and the alternative (Model 2) mediation model is presented in Figures 2 and 3 and the results of the mediation analysis are presented in Table 4.
The results of structural equation modelling analysis for the hypothesised model: Model 1.
The results of the structural equation modelling analysis for the alternative model: Model 2.
Direct, indirect and total standardised effects of flexible work, financial well-being, work–life balance and productivity (and job satisfaction in the alternative model).
Dependent variables
Flexible work
Financial well-being
Work–life balance
Productivity (job satisfaction)
Direct
Indirect
Total
Direct
Indirect
Total
Direct
Indirect
Total
Direct
Indirect
Total
Job satisfaction
0.00
0.02**
0.02**
0.19**
0.11**
0.30**
0.14**
0.12**
0.26**
0.61**
0.00
0.61**
(Productivity)
0.00
0.03
0.03**
−0.03
0.20**
0.17**
−0.01
0.18**
0.19**
0.70**
0.00
0.70**
, p< 0.05;
, p< 0.01.
Source: Fransman, E.I., 2015, ‘Determining the impact of flexible work hours on women employed in a higher education institution’, Unpublished MBA dissertation, North-West University, Potchefstroom.
A very good fit was obtained for the proposed hypothetical model (see Figure 2): χ2(3, N = 252) = 5.66, p = 0.13 (recommended p < 0.05); χ2/df = 1.89 (recommended ≤ 3.00), adjusted goodness of fit index (AGFI) = 0.99 (recommended ≥ 0.90), the Tucker–Lewis index (TLI) = 0.97 (recommended ≥ 0.90), the comparative fit index (CFI) = 0.99 (recommended ≥ 0.90), and the root mean square error of approximation (RMSEA) was 0.06 (recommended ≤ 0.05). However, a relative poor fit was obtained for the proposed alternative Model 2 (see Figure 3): χ2(2, N = 252) = 5.41, p = 0.07 (recommended p < 0.05); χ2/df = 2.71 (recommended ≤ 3.00), AGFI = 0.94 (recommended ≥ 0.90), TLI = 0.93 (recommended ≥ 0.90), CFI = 0.99 (recommended ≥ 0.90), and the RMSEA was 0.08 (recommended ≤ 0.05). In addition, all direct paths from the independent variables were insignificant, as well as the path from flexi work to the mediator (job satisfaction).
An inspection of Table 4 indicated that, in line with observations from Figure 2, financial well-being and work–life balance had total, direct and indirect effects on job satisfaction. In addition, the significance of the total, direct and indirect effects suggested that the link with job satisfaction was partially mediated by financial well-being and work–life balance. Financial well-being and work–life balance have, therefore, a salient influence on subjective experiences of productivity. Direct and indirect effects were all positive and reinforced each other to increase job satisfaction. It can be concluded that subjective experiences of productivity partially mediate the path from financial well-being and work–life balance to job satisfaction. This means that financial well-being and work–life balance and subjective experiences of productivity are important for the enhancement of job satisfaction in this sample. However, when we tested the alternative model where job satisfaction is assumed to mediate the relationship between the independent variables and productivity, a different picture emerged. It turns out that financial well-being and work–life balance had only indirect and total effects on productivity. In addition, the significance of the total and indirect effects suggested that the link between productivity and financial well-being and work–life balance is fully mediated by job satisfaction. This means that job satisfaction is needed for financial well-being and work–life balance to impact subjective experiences of productivity in this sample.
Discussion
The first aim of the study was to determine the relationship between flexible work, financial well-being, work–life balance, productivity and job satisfaction. Financial well-being and work–life balance were positive related to job satisfaction and productivity. This was also confirmed by Gupta (2011) who indicated that adequate remuneration had a positive relationship with employees’ satisfaction. Work–life balance was positively related to job satisfaction. This was also confirmed by Padmar and Reddy (2014), who found that work–life balance was a strong predictor of job satisfaction. Job satisfaction was positively related to productivity. In support of this finding are the studies by Halkos and Bousinakis (2010) and Wood et al. (2012), who found positive relationships between job satisfaction and productivity.
The second objective of the study was to determine the role of flexible work, financial well-being and work–life balance on productivity and job satisfaction. Regression analysis indicated that financial well-being and work–life balance prove to be statistically significant predictors of productivity and job satisfaction. This means that financial well-being and work–life balance are essential for subjective experiences of productivity and job satisfaction. Nazem and Seifi (2014) also found that the work–life quality significantly affected the productivity of staff. The findings also seem to concur with the findings of Richter et al. (2014), who indicated that employees with high subjective financial dependence were more satisfied with their jobs. Carlson, Grzywacz and Kacmar (2010) noted that work-to-family enrichment was strongly correlated with job satisfaction, suggesting that when workers recognise the benefits families receive from their work, they attribute those synergies to the source, which, in turn, benefits job satisfaction. Fung, Ahmad and Omar (2014) also confirmed a significantly strong relationship between work–family enrichment and job satisfaction. With the inclusion of productivity (job satisfaction in the alternative model) in the second step as predictor of job satisfaction (productivity in the alternative model), the variance explained in job satisfaction (productivity in the alternative model) significantly increased, suggesting that not only may employees who are happy with their jobs be more productive, but performing a job well may lead to satisfaction with the job (Judge & Klinger 2009).
However, this study has demonstrated that flexible work does not necessarily enhance productivity and job satisfaction (Fransman 2015). McGuire and Liro (1986) concluded in their study that there were limited effects of flexitime on job productivity. Hartman, Stoner and Arora (1991) reported that family disruption is negatively correlated with telecommuting productivity. Their solution to this problem is to create a work schedule while working at home, one that is adequately communicated to family members to minimise disruptions. To ensure that productivity is maximised, there must be good productivity tools to coordinate and communicate with managers and co-workers. Good project management and coordination to allow remote work (as in the case of telecommuting) are also necessary (Hartman et al. 1991). Cooper and Kurland (2002) and McCloskey (2001) purport that social isolation and decreased social interaction as a result of being away from the office and from co-workers may have a negative effect on job satisfaction. Belanger (1999) mentions that the three most common reasons for not wanting to telecommute were the need to share information with others, being more productive at the office site and the need to socialise with colleagues. Another justification for specifically flexitime having a low effect on job satisfaction is that it limits on-the-job enrichment (Narayanan & Nath 1982).
The third objective of the study was to determine the mediating effects of productivity (Model 1) and job satisfaction (alternative: Model 2) in the relationship between flexi work, financial well-being and work–life balance on the one hand, and job satisfaction (Model 1) and subjective experience of productivity (alternative: Model 2) on the other hand. The results of this study seem to suggest that subjective experiences of productivity partially mediate the path from financial well-being and work–life balance to job satisfaction, while it fully mediates the path from flexi work to job satisfaction. The job satisfaction levels will and can only increase if female support staff experience subjective productivity, thereby confirming that performing a job well while using flexi work may lead to satisfaction with the job (Judge & Klinger 2009). Work–life balance and financial well-being on the other hand, have a direct and indirect link (through productivity) with job satisfaction. This means that financial well-being and work–life balance lead to subjective experiences of productivity (Fransman 2015), which in turn enhances the job satisfaction. When comparing the hypothesised and the alternative model 2 with job satisfaction as the mediator, it seemed that the variance explained in the mediator (job satisfaction) was much higher and that the variance explained was much lower in the dependent variable (subjective experience of productivity) in the alternative: Model 2. Another difference between models seems to relate to the statistical significance of the direct paths. All specified direct paths in the alternative model were insignificant, while only the direct path of flexi work was insignificant in the hypothesised model. This means that mediation effects were predominant partially in the hypothesised model (except for flexi work where productivity fully mediated the relationship with job satisfaction), while the mediations were predominant fully in the alternative model. We can therefore conclude that financial well-being and work–life balance lead to subjective experiences of productivity, which in turn enhances job satisfaction.
Managerial implications and recommendations
Research done by Perry-Smith and Blum (2000) suggested that organisations with more extensive work–family policies had higher perceived firm-level performance. If workers perceive that their organisation shows concern and sensitivity to its personnel and their needs and values, including work–family needs, they will respond by showing positive job-related outcomes, such as job satisfaction, organisational commitment (Eisenberger et al. 1986) and subjective experiences of productivity. Employees engaged in more effective and flexible workplaces are more likely to have greater engagement in their jobs and higher levels of job satisfaction (Bond et al. 2005) (Fransman 2015). This study has confirmed the significant impact of work–life balance and financial well-being on subjective experiences of productivity and job satisfaction. This means that management of this IHL should start to review and implement policies, procedures and practices that focus on assisting with work–life balance and address the issues of pay equality that influence perceptions of financial well-being to enhance the subjective experience of productivity and job satisfaction. It is therefore suggested that the organisation should experiment with strategies to promote greater work–life balance such as compressed workweeks, telecommuting, on-site childcare, part-time work and job sharing.
Limitations of the study
The common method variance because of self-report bias is a limitation of the study. Common method variance refers to the degree to which correlations are inflated, because of a methods effect (Meade, Watson & Kroustalis 2007; Podsakoff, MacKenzie, Lee & Podsakoff 2003). In this study, common method bias may have occurred because of the use of the same source to gather data on independent and dependent variables. Bias may lead to common method variance (i.e. variance attributable to a methods effect) (Podsakoff et al. 2003). It is suggested that future research should include other sectors and academic staff, which use more flexi work to firmly establish the impact of flexi work on job satisfaction and subjective experience of productivity. It is also suggested that future studies make use of longitudinal designs to establish cause and effect. No causal conclusions can be drawn from any cross-sectional design (Avey, Patera & West 2006).The use of bigger samples and the inclusion of staff from other IHLs could increase the generalisability of the findings of this study.
Conclusion
In conclusion, the study also explored the role of flexi work, financial well-being and work–life balance in job satisfaction (Model 1) and in subjective experience of productivity (alternative: Model 2). The findings indicate that in summary, financial well-being and work–life-balance are more important for both job satisfaction and subjective experiences of productivity (Fransman 2015). Financial well-being and work–life balance together explained less of the variance in subjective experiences of productivity (R2 = 0.09) compared to in-job satisfaction (R2 = 0.20). In addition, financial well-being and work–life balance explain more of the variance in-job satisfaction (R2 = 0.54) through subjective experiences of productivity compared to their role in subjective experiences of work success (R2 = 0.48). It therefore seems that financial well-being and work–life balance play a more important role in job satisfaction (compared to their role in subjective experiences of productivity) and that financial well-being and work–life balance are more important for job satisfaction through subjective experiences of productivity (compared to their role in subjective experiences of productivity through job satisfaction). I would, therefore, make sense to increase experiences of financial well-being and work–life balance to address experiences of low levels of job satisfaction and subjective experiences of productivity.
AcknowledgementsCompeting interests
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
Authors’ contributions
L.T.B.J. was the study supervisor and was responsible for the data analysis and refining of the literature. E.I.F. was a master’s student and was responsible for the data collection and initial data analysis and literature.
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How to cite this article: Jackson. L.T.B. & Fransman, E.I., 2018, ‘Flexi work, financial well-being, work–life balance and their effects on subjective experiences of productivity and job satisfaction of females in an institution of higher learning’, South African Journal of Economic and Management Sciences 21(1), a1487. https://doi.org/10.4102/sajems.v21i1.1487
Note: This article is partially based on one of the author’s unpublished work: Fransman, E.I., 2015, ‘Determining the impact of flexible work hours on women employed in a higher education institution’, Unpublished MBA dissertation, North-West University, Potchefstroom.