Master’s thesis
Graduate School of Communication, University of Amsterdam
2014-2015
The underlying mechanisms of the effect of New Ways of Working on
wellbeing unraveled
A quantitative research by means of a survey among employees and managers of a prominent Dutch organization in the banking and insurance sector
Master Communication Science, Corporate Communication track Celine Jellema
10765484
Supervisor: Claartje ter Hoeven
Abstract
New Ways of Working (NWW) has been studied extensively, however existing studies of the effects of NWW are inconclusive. Advantages as well as disadvantages are reported. This study aims to use the contrasting findings on the effects of NWW to explain the relationship with wellbeing. On the basis of the Job Demands-Resources model it is proposed that NWW can either increase or decrease the wellbeing of employees due to underlying processes like work-life balance, work intensification, and social cohesiveness.
Data were collected in a Dutch organization operating in the banking and insurance sector, using an online survey (N = 751). The organization started the implementation of NWW in 2006 and it is now part of their organizational culture and collaborative labor agreement. A conceptual model was tested using bootstrapping.
Consistent with predictions, the relationship between NWW and the wellbeing of employees was positively mediated by work-life balance. It was hypothesized that performing technology-assisted supplemental work (TASW) would negatively moderate the paths from NWW to work-life balance and from work-life balance to wellbeing. This was only the case for the path from work-life balance to wellbeing. Moreover, contrary to what was
hypothesized, NWW was not positively associated with work intensification, and did not cause a loss in social cohesiveness.
Overall, it appears that having a satisfactory work-life balance has the strongest effect on the positive relationship of NWW with wellbeing. However, only one organization was investigated which makes it hard to generalize these finding to organizations with different organizational cultures and from other sectors.
The underlying mechanisms of the effect of New Ways of Working on wellbeing unraveled
The world has become more technologically advanced, virtual, and global and employees are expected to be connected anywhere possible (Perlow & Kelly, 2014). New Ways of Working (NWW) stimulates people to share expertise at anytime, anywhere, and with anyone. NWW consists of the following elements: flexibility in time, place, and communication technology and can be defined as “a work design in which employees can control the timing and place of their work, while being supported by electronic
communication” (Ten Brummelhuis, Bakker, Hetland, & Keulemans, 2012, p. 114).
Flexibility in time implies that employees have more freedom in scheduling their work, it is no longer fixed from 9AM to 5PM. This provides more autonomy (Kelliher & Anderson, 2008; Gajendran & Harrision, 2007) and control (Kelliher & Anderson, 2008). Furthermore, employees have more flexibility in where they work; they can work from home or while they are traveling. Lastly, new media technologies facilitate NWW by offering multiple options for employees to communicate with colleagues, e.g. e-mail, smartphones, and videoconferences. Individuals can differ in their engagement with NWW on all three aspects.
The early adopters in The Netherlands were among others Interpolis and Shell and later Rabobank. SNS Reaal and Microsoft followed in their footsteps, with success. Microsoft for example reports an increase of productivity and work-life balance among their employees because of the implementation of this new job design (De Pous & Van der Wielen, 2010). However, negative effects of NWW have also been reported in the literature (e.g. Perlow & Kelly, 2014; Mazmanian, 2013; Kelly, Moen, & Tanby, 2011).
Starting with the advantages of NWW, Baltes et al. (1999) report that flexibility in time has positive effects on the productivity, job satisfaction, satisfaction with the work schedule, and that it decreases the absenteeism of employees. People feel like they have autonomy over their own affairs by being able to make decisions about their working hours and adapting them to their demands (Costa et al. 2004). Employees who have flexibility in work place stated that it reduced stress, because of not having the demands of the office all the time, and not having to commute (Kelliher & Anderson, 2008). Furthermore, flexibility in work is found to be important for improving work-life balance of employees (Gajandran & Harrison, 2007). Flexibility can also improve the wellbeing of employees (e.g. Almer & Kaplan, 2002). Mostly, the favorable effects of flexibility on wellbeing were associated with less work-family conflict and higher employee control (De Menezes & Kelliher, 2011).
Another characteristic of NWW is communication technology which can also provide advantages. The use of new media leads to more effective and efficient communication (Ten Brummelhuis et al., 2012). A few examples: work-related calls can be made while traveling, working from home prevents informal face-to-face interruptions, less office meetings need to be arranged since tasks can be distributed by e-mail (Ten Brummelhuis et al., 2012). And, because of the enhanced connectivity that NWW provides and the more effective and efficient communication, it fosters work engagement and lowers levels of exhaustion in employees (Ten Brummelhuis et al., 2012).
Nevertheless, there is also a negative side to NWW (Perlow & Kelly, 2014; Wright et al., 2014; Kossek & Lautsch, 2012; Boswell & Olson-Buchanan, 2007). Flexibility in place can reduce stress, but it can also create stress, because of a conflict between the demands from work and home (De Menezes & Kelliher, 2011). Social cohesiveness and the informal
interaction between colleagues on the work floor can get lost when people are no longer at the office every day (Kurland & Cooper, 2002). The employee is furthermore expected to be constantly connected for professional reasons. This feeling of constantly being and needing to be connected can cause work intensification (Green, 2004), which is often reported among flexible workers (Kelliher & Anderson, 2010). It can lead to employees finding it harder to disengage from their work (Mazmanian, 2013; Kossek & Lautsch, 2012; Boswell & Olson-Buchanan, 2007), employers having more hold on their employees outside of work
(Cavazotte, Lemos, & Villadsen, 2014), and working more overtime (Gajandran & Harrison, 2007). A particular form of distributing work after regular working hours is technology-assisted supplemental work (TASW), which entails full-time employees performing work-related tasks at home after working hours using communication technologies (Fenner & Renn, 2010). This use of communication technologies outside of work can increase work-life
conflict, stress, burnout, and employee turnover intentions (Kelly et al., 2011; Fenner & Renn, 2010; Kossek, Lewis, & Hammer, 2010; Kreiner, Hollensbe, & Sheep, 2009). Occupational stress, especially burnout, causes more sickness absence among employees (Borritz, Rugulies, Christensen, Villadsen & Kristensen, 2006). So, the wellbeing of employees can be affected by a job design like NWW, which makes it an important issue for organizations.
The current literature is inconsistent in reporting advantages and disadvantages of NWW (De Menezes & Kelliher, 2011). Work-life balance for example is reported as an advantage (e.g. Gajandran & Harrison, 2007), while other studies name work-life conflict as a disadvantage (e.g. Perlow & Kelly, 2014; Wright et al., 2014). Furthermore, in current studies often not all three aspects of NWW are taken into consideration. Most of the time it is focused
on just one or two aspects. Telecommuting (e.g. Gajendran & Harrison, 2007; Fonner & Roloff, 2012), which is a combination of the elements flexibility in place and communication technology, and flexible working arrangements (FWAs) (De Menezes & Kelliher, 2011), which consists of flexibility in time and place, are also common concepts.
Job designs like NWW change the organizational environment and culture, which can have a strong effect on employee wellbeing. Organizations have to make sure that the
wellbeing of the employees is vouched for in this change. It is therefore interesting to examine how NWW influences wellbeing. Does NWW elicit engaged employees, or does it mainly cause stress or even a burnout? Literature on the effect of NWW on wellbeing is inconsistent. Negative, positive, and even no links are reported (De Menezes & Kelliher, 2011; Kattenbach, Demerouti, & Nachreiner, 2010; Kelliher & Anderson, 2008; Almer & Kaplan, 2002). The question then remains which aspects of NWW result in these positive and negative effects on the wellbeing of employees? On the basis of the Job Demands-Resources model, it can be expected that both the advantages, like work-life balance, and disadvantages, like work intensification, and a loss of social cohesiveness, can affect the wellbeing of
employees (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001). The central aim of this study is to investigate the underlying processes of the relationship between NWW and the wellbeing of employees. Work-life balance, work intensification, and social cohesiveness hereby serve as the underlying mechanisms of the effects of NWW onto outcomes on the individual level, in this case the wellbeing of employees. Promoting the wellbeing of employees contributes to a successful organization and it allows for more satisfaction and commitment, which
consequently reduces absenteeism and turnover intentions (Baptiste, 2008). Furthermore, based on Fenner and Renn (2010), it is expected that TASW can decrease the positive mediating effect of work-life balance on the relationship between NWW and wellbeing.
Since the results of previous studies are so ambiguous, for this study a survey was sent out within an organization that integrated NWW in their collective labor agreement. They started the implementation in 2006 and it is now integrally implemented at almost all
locations. Their main reason for implementing this job design was to generate more employee satisfaction. Employees can choose where, when, and with what technological medium they want to work. In this manner they can work in a way that suits their current activity best. Arrangements on availability and reachability are made in agreement with their manager. The organization’s systems and processes are adapted so that people can work effectively from home. By giving the employees this kind of freedom, work and private life get more
their own space or office. If employees work at the office, they can choose the workspace that fits their activity. There are a lot of communal spaces where people can work together, but individual work spaces are also available.
This research is an addition to the current literature on the positive and negative effects of NWW. The positive processes, work-life balance and social cohesiveness, and the negative process, work intensification, were investigated together in one model. This way, determining the specific effect of one of the mediator variables conditional on the others present in the model is possible. Therefore, it provides better insight in the processes that lead to the proposed relationship between NWW and the wellbeing of employees. This can help organizations to implement it more effectively by mitigating the negative effects and
strengthening the advantages of NWW. By unraveling the underlying processes, organizations get a better perspective on which mechanisms exert the biggest effect on wellbeing and
therefore have a better view on what to prioritize.
Theoretical framework
Every organization strives to be successful and in a healthy state (Baptiste, 2008). The wellbeing of the employees contributes to this. Wellbeing at work also contributes to the overall sense of happiness of people, which is consequently outed through their attitude and behavior, and shapes the work environment and culture (Baptiste, 2008). The promotion of employee wellbeing at work allows for employees who are more committed and satisfied, which helps to enhance performance and reduce turnover intentions and absenteeism (Baptiste, 2008). Studies showed that flexible working arrangements can contribute to this, and are therefore good for business (De Menezes & Kelliher, 2011; Costa et al., 2004; Almer & Kaplan, 2002). It has been reported that flexibility in time can relieve stress (De Menezes & Kelliher, 2011; Halpern, 2005), and is negatively related to burnout (Kattenbach et al., 2010; Grzywacz, Carlson, & Shulkin, 2008). However, the existing evidence for a link between NWW and wellbeing is inconclusive. There are also studies that show that NWW can be a source of stress and therefore has a negative effect on wellbeing (Kelliher & Anderson, 2008; Tietze & Musson, 2005; Ashford, Kreiner, & Fugate, 2000). NWW gives employees more autonomy in scheduling their time. This increases their demands and
responsibilities and employees can have difficulty coping with this, as it makes them feel like they are always in between tasks or people and this can therefore cause stress (Tietze & Musson, 2005).
Job Demands-Resources model
How different aspects of NWW influence wellbeing will be examined with help of the Job Demands-Resources model ( JD-R model). This model describes how working conditions can affect the development of burnout symptoms, which is related to health outcomes, and can be used to predict this (Bakker, Demerouti, & Sanz-Vergel, 2014). Burnout is represented as a combination of exhaustion and disengagement. The working conditions are classified into two categories: job demands and job resources. Job demands are associated with
physiological and psychological costs, because of the intense physical or mental effort they require (Demerouti et al., 2001) e.g. bad environmental conditions and high work pressure (Bakker, Demerouti, & Verbeke, 2004). Job resources are the physical, psychological, social, or organizational aspects that are functional in attaining work goals, reduce job demands and the physiological and psychological costs linked to them, and stimulate personal development and growth (Demerouti et al., 2001), e.g. the opportunity to learn, social support, and
autonomy (Schaufeli, Bakker, & Van Rhenen, 2009).
On the basis of this model it can be expected that both the advantages and
disadvantages of NWW affect the wellbeing of employees (Demerouti et al., 2001). The basis of the conceptual model that was developed tests the mediating effects of both an advantage and a disadvantage of NWW, depicted in Figure 1. Work-life balance and social cohesiveness can be seen as job resources, and work intensification as a job demand. These are the
underlying mechanisms that possibly cause the effect of NWW on wellbeing. On the one hand, because of a possible increase in work intensification and a possible decrease in social cohesiveness, there can be a negative influence of NWW on wellbeing. On the other hand, because of a better work-life balance due to NWW, the wellbeing of employees might be positively affected. Because employees can differ in their engagement on all three elements of NWW, the model will be tested separately for each element.
Work-life balance
Work and life influence each other (Putnam, Myers, & Gailliard, 2014; Geurts & Demerouti, 2003), which makes that “[…] employers, societies and individuals cannot ignore one sphere without potential peril to the other” (Clark, 2000, p. 749). There is
interdependence between life and work and this interaction has become a practical and
theoretical concern (Clark, 2000). A lot of employees seem to have difficulty combining work and domestic obligations (Geurts & Demerouti, 2003). According to the work/family border theory from Clark (2000), people are able to determine their own work and home
Figure 1. The proposed influence of NWW on wellbeing through work-life balance, work
intensification, and social cohesiveness.
environment, yet they are also being determined by these same environments. A balance between work and home needs to be created. Balance is in this case defined as “satisfaction and good functioning at work and at home, with a minimum of role conflict” (Clark, 2000, p. 751). For employees to be able to obtain work-life balance, flexibility is important (Cowan & Hoffman, 2007). The elements of NWW can affect the balance between work and life.
However, in the empirical research on this topic there is a debate going on about the effects of flexibility and communication technologies on work-life balance (Gajendran & Harrison, 2007). Positive as well as negative effects are reported.
On the one hand, a negative influence on work-life balance can occur because of the possibility of intensified conflict by making the work and life boundaries more permeable (Wright et al., 2014; Igbaria & Guimaraes, 1999; Standen, Daniels, & Lamond, 1999). That the boundaries are blurring is especially due to communication technologies, like smartphones and laptops. These technologies allow employees to self-manage work (Wright et al., 2014), and provide enhanced connectivity between colleagues, which increases the permeability of work-life boundaries (Perlow, 1998). Furthermore, employee benefits, like child transport services, on-site child care or fitness offered by the organization, bring personal activities into the workspace, and personal activities, like personal calls or emails, are also done during working hours (Geurts & Demerouti, 2003). Moreover, communication technologies are increasingly used by employees for work-related tasks outside of work, since they support flexibility in place (Gajendran & Harrison, 2007), which can cause a conflict between work and life (Perlow & Kelly, 2014; Wright et al., 2014; Kelly et al., 2011; Kossek et al., 2010; Kreiner et al., 2009). Employees might also find it harder to disengage from their work, and
stress from issue at work can interfere with their personal life (Mazmanian, 2013; Kossek & Lautsch, 2012; Boswell & Olson-Buchanan, 2007).
On the other hand, positive effects of flexibility and communication technology on work-life balance have also been repeatedly reported (McNall, Masuda, & Nicklin, 2010; Kattenbach et al., 2010; Hayman, 2009; Raghuram & Wiesenfeld, 2004; Duxbury, Higgings, & Neufeld, 1998; Kirchmeyer, 1995). These researchers state that the increased flexibility in place and timing of work can reduce work-life conflict by helping employees to balance the demands between work and family. The flexibility allows for hours that can be scheduled to match those of family members which reduces time-based conflict, and work that can be scheduled optimally which can minimize interruptions by family (Gajendran & Harrison, 2007). Also, if people can work more from home, the commuting hours to and from work will be reduced, which can be used for family activities (Greenhaus & Beutell, 1985). In the meta-analysis of Gajendran and Harrison (2007), flexibility in place and communication technology were negatively related to work-family conflict.
According to the border theory, there are a few organizational tools for balance (Clark, 2000). The culture should be changed according to the changes to the borders (like adding flexibility in time and place), and supportiveness of supervisors and the central participation of employees are both important. The latter can be facilitated by organizations. This can make it easier for people to cross the border from work to private life and vice versa. In case of the investigated organization in this study, the organizational culture is adapted to the needs of its employees. The NWW design is implemented not to serve the organization’s own interests, but to generate more employee satisfaction. Employees are supported in their transition to the NWW design by their managers. They are allowed to indicate how they believe to be able to obtain the best results and are flexible in when and where they would like to work. This is established in agreement with their manager. This led to the following hypothesis:
H1. The effect of (a) flexibility in time, (b) flexibility in place, and (c) communication
technology on the wellbeing of employees is positively mediated by work-life balance.
Work intensification
Due to globalization, changes in technology and how people work together, the expectation arises that employees should be constantly connected. There is an intensification of work, which “is felt keenly by growing numbers of dual-earner couples, single parents, elder caregivers, and fathers who are involved in day-to-day caregiving” (Perlow & Kelly,
2014, p. 112). It is shown that giving employees more autonomy and freedom in scheduling their work could result in work intensification (Perlow & Kelly, 2014; Kelliher & Anderson, 2010). Work intensification regards the effort that is put into a job, which can be the time spent working, but also mental and physical input (Kelliher & Anderson, 2010). Kelliher and Anderson (2010) established that intensification may take place by one of three means. First, the identification may be imposed, this might happen for example if the working hours are reduced, but the workload is not. Second, it may be enabled by flexible working
arrangements, because these make it easier for people to work more or harder. Third, it might be an employees’ reciprocal act or exchange, caused by the ability to exploit flexible working arrangements. They sometimes make sacrifices in exchange for being able to adopt flexible time schedules.
Work intensification can negatively influence employee wellbeing and job satisfaction (Kelliher & Anderson, 2010). Employees who experience greater work intensity leads to poorer wellbeing, in terms of more fatigue, stress, and work-life conflict (Boxall & Macky, 2014). The 24/7 connectedness that comes along with communication technologies intensifies the demands of an employee (Chesley, 2014). They are expected to be available all the time, which can cause stress because weekends and holidays become less relaxing (Towers,
Duxbury, Higgins, & Thomas, 2006). Because of smartphones and laptops work-related calls and emails can be received anywhere. This results in organizations having more hold on employees outside of work (Cavazotte et al., 2014). Flexibility provided by communication technologies consequently leads to employees working more overtime (Gajandran & Harrison, 2007; Geurts & Demerouti, 2003). This led to the following hypothesis:
H2. The effect of (a) flexibility in time, (b) flexibility in place, and (c) communication
technology on the wellbeing of employees is negatively mediated by work intensification.
Social cohesiveness
One of the biggest worries that is named by employees who have adopted NWW, is the loss of social cohesiveness (Van Heck et al., 2012; Kurland & Cooper, 2002). Since employees of organizations who have implemented NWW are more often working from home or other places than the office, the social cohesiveness at work could become less. Employees miss the informal interaction with colleagues (Kurland & Cooper, 2002). Social cohesiveness at work can be seen as the degree to which employees believe that their coworkers are
attracted to one another, wanting to work together, and are committed to reaching the goals of their department (Riordan & Weatherly, 1999).
Social cohesiveness is an important factor in organizations that can make employees feel a stronger commitment with the organization (Duyvendak & Veldboer, 2001). It is also positively associated with psychological outcomes like work satisfaction (Peters, de Bruijn, Bakker, & van der Heijden, 2001). A lack of social cohesion can lead to social isolation (Rajulton, Ravanera, & Beaujot, 2007), which is not desirable for organizations. The
professional development of flexible workers who feel socially isolated for some time might suffer when they do not have the opportunity to get ideas from other employees, which is “[…] a process of informal, interactive learning and a benefit of team synergy and
intraorganizational, interpersonal networking” (Kurland & Cooper, 2002, p. 122). When there is less social cohesiveness because of NWW, this could negatively influence wellbeing. The third hypothesis is therefore as follows:
H3. The effect of (a) flexibility in time, (b) flexibility in place, and (c) communication
technology on the wellbeing of employees is negatively mediated by a loss of social cohesiveness.
The moderating role of TASW
To make it possible for employees to work more flexible, communication technologies are needed. Laptops and smartphones make it possible for them to have flexibility in time and place. Through these technologies employees are constantly connected and can reach each other at any time, which can be convenient during working hours. However, it also facilitates performing work-related tasks after regular working hours (Fenner & Renn, 2010). The term used for performing supplemental work tasks at home after working hours by using
communication technology is called technology-assisted supplemental work (TASW) (Fenner & Renn, 2010). Fenner and Renn (2010) name three characteristics of TASW:
a) The work is supplemental and done after working hours at home by full-time employees.
b) Most of the time a contract or other compensation agreement does not cover it and it is performed discreetly by professionals.
c) Information and communication technologies, like laptops and smartphones, are being used to perform the tasks.
TASW can have consequences for employees. It can contribute to a conflict between work and family, because it makes it harder for them to disconnect from work when not at the work place, it can spontaneously interrupt people while enacting either role, and it can be confusing as to when to enact which role (Fenner & Renn, 2010). It can also cause stress (Fenner & Renn, 2010), and thus affect the wellbeing of employees. It was therefore hypothesized that the positive effect of NWW on wellbeing through work-life balance decreases when employees engage in TASW.
H4. The mediating effect of work-life balance on the relationship between (a)
flexibility in time, (b) flexibility in place, and (c) communication technology and wellbeing is negatively moderated by TASW.
Figure 2. The proposed influence of NWW on wellbeing through work-life balance, work
intensification, and social cohesiveness and the moderating role of TASW.
Method
Sample and procedure
The study was done by means of an online survey and the design was cross-sectional. Data were collected in 2015 in a Dutch company that operates in the financial service
industry. The organization started the implementation of NWW in 2006 and now almost all locations have fully adopted the design. The employees are flexible in when, where, and with what communication technology they want to work. Agreements with managers are made as
to which circumstances would be most suitable for the employee. The organization is very informal and transparent in their processes, tasks and communication.
The survey was sent out to employees working at three different locations. Each of these locations integrally adopted the design by now. In total 2,264 employees were invited to participate in the survey by email. They were informed that participation was voluntary. To increase the response rate, after one week a reminder was sent out. Of the 2,264 employees, 751 completed the survey (a 33 per cent response rate).
Of the participants in the sample, 62.3 per cent was male (versus 57,9 per cent in the total population of the three locations). The mean age was 42.6 years (SD = 8.96, N = 748), comparable to the average of 42 per cent in the total population of the three investigated locations. 72.4 per cent of the employees in the sample have one or more children and 58 per cent currently lives together with their partner and child(ren). Most employees had a higher vocational degree (45.3 per cent) or university degree (33.4 per cent), whereas 20.9 per cent had a middle and 0.4 per cent a lower vocational degree. 63.9 per cent of the participants where knowledge workers, and 12.8 per cent held a managerial position (versus respectively 33.8 per cent and 9.2 per cent in the total population of the three locations). On average respondents worked 35.30 hours weekly as per their contracts (SD = 4.46, N = 745), however according to their own indication of the actual hours they said to work on average 37.81 hours per week (SD = 6.83, N = 724).
Measures
To measure to what extent the participants adopted the NWW design in their work, a scale from Ten Brummelhuis et al. (2011) was used. The scale consisted of 20 items and represented the three elements flexibility in time, flexibility in place, and communication technology. Flexibility in time consisted of 3 items, for example “I can decide the time slots I work in” (α = .92). Flexibility in place also consisted of three items, for example “I can choose at which location I work” (α = .77). The element communication technology consisted of 14 items. Examples were “I can determine what communication technologies I use for my work”, and “I use my laptop for work-related communication” (α = .71). Five-point Likert-scales were used ranging from 1 (totally disagree) to 5 (totally agree).
The wellbeing of employees was measured by the UBOS-A scale from Schaufeli & van Dierendonck (2000). This scale serves to distinguish between healthy employees and the ones with burnout symptoms and consists of three sub scales, namely emotional exhaustion, mental distance, and competence (Schaufeli & van Dierendonk, 2000). A high score on
emotional exhaustion and mental distance, and a low score on competence are an indication for an employee with a possible burnout. The scale consisted of 15 items, such as “I feel mentally exhausted because of my work” and “I reached a lot of valuable goals within this job” (α = .86). Answer categories ranged from 1 (never) to 5 (always). Negative items were recoded so that the scale indicated wellbeing and not burnout symptoms.
Work-life balance was measured using a scale of Valcour (2007) with five items asking the participant to what extent they were satisfied with for example “The way in which you divide your attention between work and home?” and “How well your working life and your personal life collide?” (α = .93). A five-point Likert-scale was used with answer categories ranging from 1 (very dissatisfied) to 5 (very satisfied).
Work intensification was measured using a six-item scale from Boxall and Macky (2008). Example items were “There is too much work to do everything well” and “Employees are often expected to work overtime or take work home at night and/or weekends” (α = .76). All items were rated on a five-point Likert-scale ranging from 1 (totally agree) to 5 (totally disagree).
Social cohesiveness was measured by the eight-item scale of work group cohesiveness from Riordan and Weatherly (1999). In this research the cohesiveness was measured at the department level, as not every employee in the organization belongs to a specific work group. Examples were “At the department where I work, there is a lot of team spirit among
colleagues” and “At the department where I work, individuals pitch in to help one another” (α = .94). A five-point Likert-scale ranging from 1 (totally agree) to 5 (totally disagree) was used.
TASW was measured by the scale from Fenner & Renn (2010). It consisted of 5 items, for example “When I fall behind in my work during the day, I work hard at home at night or on weekends to get caught up by using my smartphone or laptop” and “I feel my smartphone, or laptop is helpful in enabling me to work at home at nights or on weekends” (α = .93). The items were rated on a five-point Likert-scale ranging from 1 (totally agree) to 5 (totally disagree).
The control variables were gender, age, having children, level of education (high or low), contractual hours, actual working hours, and function level (operational level,
knowledge worker, or manager). It was not obligatory for the participants to answer these questions. This resulted in some missing cases which were excluded pairwise from the analysis.
Analysis
Bootstrapping was used to test whether work-life balance and work intensification mediated the relationship between the predictor variable (NWW) and the outcome variable (wellbeing). “Bootstrapping is a computationally intensive method that involves repeatedly sampling form the data set and estimating the indirect effect in each resampled data set” (Preacher & Hayes, 2008, p. 880). It provides very accurate confidence intervals of indirect effects (X M Y) and is useful when testing a model with multiple mediators (Preacher & Hayes, 2008).
Results
Table 1 shows the descriptive statistics as well as the internal consistency of the multiple-item measures for each of the eight study variables, and displays the inter-correlation among study and control variables.
The significance of the proposed mediators on the relationships between each of the three independent variables and the outcome variable was tested. First, separate regression analyses were executed to see if each of the independent variables were significantly associated with the mediators and if the mediators were significantly associated with the outcome variable. The independent variable flexibility in time was positively related to work-life balance (b* = .10, p < .001), negatively related to work intensification (b* = -.06, p = .010), but not significantly related to social cohesiveness (b* = .02, p = .485). The
independent variable flexibility in place was positively related to work-life balance (b* = .11,
p < .001), but not significantly related to work intensification (b* = -.02, p = .577), and social
cohesiveness (b* = .03, p = .183). The independent variable communication technology was positively associated with work-life balance (b* = .16, p < .001) and social cohesiveness (b* = .12, p = .001), and negatively with work intensification (b* = -.09, p = .011). The mediators work-life balance (b* = .38, p < .001), work intensification (b* = -.33, p < .001), and social cohesiveness (b* = .36, p < .001) were all significantly associated with wellbeing.
In a second step, the direct effect of the three independent variables on the outcome variable wellbeing was tested. Of the three independent variables, only communication technology was significantly associated with the outcome variable wellbeing (b* = .24, p < .01). Flexibility in time (b* = .06, p = .112) and flexibility in place (b* = .06, p = .116) appeared to be not significantly associated with wellbeing. In spite of these direct effects not being significant, the mediation model was still tested. In models with multiple mediators,
finding a significant direct relationship between X and Y is not always possible, as a net of X on Y can be outweighed by the opposite effects of two mediators (Preacher & Hayes, 2008). The model was tested for all three elements of NWW separately. To test the multiple mediator models, the PROCESS macro written by Hayes was used. 5,000 bootstrap samples were drawn and a level of confidence of 95 per cent was used for the analyses. By testing all mediators together as a set in one model, the specific indirect effects represent the ability of a mediator to mediate the effect controlling for the other mediators in the model (Preacher & Hayes, 2008). It represents the unique ability of a mediator to mediate above other mediators or covariates in a model (Preacher & Hayes, 2008).
Starting with flexibility in time, although the direct effect was not significant, the total indirect effect of this model appeared to be significant, 95% CI [.013, .048]. This is the case when the confidence interval does not contain zero. This effect remained significant
controlled for gender, age, having children, level of education (high or low), contractual hours, actual working hours, and function level 95% CI [.019, .058]. Looking at the specific indirect effects, displayed in Figure 3, hypothesis 1a was accepted. Work-life balance
positively mediates the relationship. Hypothesis 2a was rejected, work intensification was no significant mediator 95% CI [-.004, .008]. However not significantly, flexibility in time was negatively related to work intensification, which is opposite to what was expected. Hypothesis 3a was also not accepted, social cohesiveness was no significant mediator 95% CI [-.011, .007]. Test statistics can be found in Table 2.
Note. N = 751; pathways represent unstandardized regression coefficients; * pathway
significant at .05 level; ** pathway significant at .01 level.
Table 1
Means (of five-point scales), standard deviations, and correlations for study and control variables
Variables M SD 1 2 3 4 5 6 7 8 N 1 Wellbeing 4.03 .49 α = .80 751 2 Work-life balance 3.90 .66 .38** α = .93 751 3 Work intensification 2.61 .67 -.33** -.45** α = .76 751 4 Social cohesiveness 3.73 .63 .36** .23** -.13** α = .94 751 5 TASW 3.60 .99 .09** -.13** .23** .00 α = .93 751 6 Flexibility in time 3.42 1.08 .06 .17** -.09* .03 .10** α = .92 751 7 Flexibility in place 3.39 .94 .06 .16** -.02 .05 .18** .55** α = .77 751 8 Communication technology 3.35 .44 .24** .16** -.09* .12** .29** .30** .36** α = .71 751 Gender .38 .49 .04 .01 -.04 .04 -.16** -.42 -.12** -.07 751 Age 42.64 8.96 .12** -.02 .06 -.04 -.00 .08* .06 .01 748 Having children .72 .45 .11** -.02 .01 .03 .10** .06 .06 .15** 751 Level of education 1.79 .41 -.12** .00 .13** -.06 .25** .04 .16** .10** 751 Contractual hours 35.30 4.46 -.03 -.12** .15** -.04 .32** .01 .13** .12** 745
Actual working hours 37.81 6.83 .01 -.25** .26** -.01 .47** -.03 .08* .12** 724
Function level 1.90 .59 .01 -.09* .15** -.02 .48** .11** .20** .23** 750
Table 2
Specific indirect pathways using bootstrapping
Bootstrapping BC 95 per cent CI
Effect SE Lower Upper
Indirect effect X M Y
Flexibility in time work/life balance wellbeing
.0183 .0050 .0099 .0301
Flexibility in time work intensification wellbeing
.0001 .0003 -.0043 .0077
Flexibility in time social cohesiveness wellbeing
-.0018 .0047 -.0113 .0070
TOTAL .0294 .0089 .0125 .0477
Flexibility in place work-life balance wellbeing
.0190 .0057 .0093 .0318
Flexibility in place work intensification wellbeing
-.0050 .0034 -.0127 .0010
Flexibility in place social cohesiveness wellbeing
.0022 .0057 -.0088 .0138
TOTAL .0280 .0109 .0074 .0506
Communication technology work/life balance wellbeing
.0374 .0122 .0171 .0661
Communication technology work intensification wellbeing
.0045 .0068 -.0076 .0195
Communication technology social cohesiveness wellbeing
.0249 .0124 .0029 .0522
TOTAL .0911 .0218 .0510 .1372
Note. N = 751; BC, bias corrected; CI, confidence interval; if CI does not include zero the effect is considered
statistically significant and is displayed in bold; SE, standard error; entries represent unstandardized regression coefficients.
In the mediator model with flexibility in place as independent variable, the total indirect effect on the relationship with wellbeing was significant, 95% CI [.01, .05]. This effect remained significant controlled for gender, age, having children, level of education (high or low), contractual hours, actual working hours, and function level, 95% CI [.02, .07]. Looking at the specific indirect effects of the mediators, depicted in Figure 4, hypothesis 1b was accepted. Also in this model work-life balance was a significant mediator, 95% CI [.01,
.30]. Hypothesis 2b was not accepted, work intensification was no significant mediator, 95%
CI [-.01, .00]. Flexibility in place was in this case positively related to work intensification,
however not significantly. Hypothesis 3b was rejected as well, social cohesiveness was no mediator of the relationship between flexibility in place and wellbeing, 95% CI [-.01, .01]. Flexibility in place was positively associated with social cohesiveness, which is the opposite of what was hypothesized, however this was not significant. Test statistics are displayed in Table 2.
Note. N = 751; pathways represent unstandardized regression coefficients; * pathway
significant at .05 level; ** pathway significant at .01 level.
Figure 4. Mediation model with flexibility in place as independent variable.
For the last independent variable, communication technology, the total indirect effect of the mediation model was significant, 95% CI [.05, .14]. This effect remained significant controlled for gender, age, having children, level of education (high or low), contractual hours, actual working hours, and function level, 95% CI [.09, .18]. The specific indirect effects are displayed in Figure 5. Based on these effects, hypothesis 1c was accepted. The relationship between communication technology and wellbeing was positively mediated by work-life balance, 95% CI [.02, .07]. Hypothesis 2c was rejected, communication technology was no significant mediator, 95% CI [-.01, .02]. Opposite to what was expected, it was
negatively associated with work intensification, although not significantly. Hypothesis 3c was also rejected. Communication technology appeared to be a significant mediator, 95% CI [.00, .05], however contrary to what was expected. Communication technology was positively related to social cohesiveness. Test statistics can be found in Table 2.
To conclude, all mediators taken together as a set, work-life balance, work
intensification, and social cohesiveness do mediate the effect of each of the three elements of NWW on wellbeing. As for the examination of the specific indirect effects in the mediation
models with flexibility in time and flexibility in place as independent variables, neither work intensification nor social cohesiveness contributes above and beyond work-life balance. Therefore, in case of these elements of NWW, only hypotheses 1a and b were accepted. In the mediation model with communication technology as independent variable, the specific
indirect effects of work-life balance and social cohesiveness were both significant.
Consequently, hypotheses 1c and 3c were accepted. Nevertheless, also for this element work-life balance had the strongest effect.
Note. N = 751; pathways represent unstandardized regression coefficients; * pathway
significant at .05 level; ** pathway significant at .01 level.
Figure 5. Mediation model with communication technology as independent variable.
Moderated mediation
To test for moderated mediation, the SPSS macro PROCESS was used as well. It was tested if TASW negatively moderated the path from each of the three independent variables to the mediator work-life balance and/or the path from work-life balance to the outcome variable wellbeing. To be able to probe a significant interaction, bootstrapping was used to test the significant direct and indirect effect for TASW. 5,000 samples were drawn for this analysis and a level of confidence of 95 per cent was used. The test with flexibility in time as
independent variable showed that, surprisingly, the path from flexibility in time to work-life balance was positively moderated by TASW (b* = .05, p =.009), and the path from work-life balance to wellbeing was negatively moderated, however this was only marginally significant (b* = -.05, p =.053). Test statistics can be found in Table 3. The confidence intervals of the conditional indirect effect of flexibility in time (X) on wellbeing (Y) at different values of the moderator TASW overlapped. The effect of flexibility in time on wellbeing through work-life balance did not significantly change when TASW was added as a moderator. Table 3 shows that the first path was, unexpectedly, positively moderated by TASW and the second path
negatively. It seems that the moderating role of TASW was neutralized because of this and therefore did not exert a significant effect. Hypothesis 4a was rejected.
Table 3
Bootstrap results for moderated mediation with flexibility in time as independent variable Flexibility in time work-life balance b* (SE) Work-life balance wellbeing b* (SE) Direct effect
flexibility in place wellbeing
b* (SE) TASW (CI) .0516** (.0196) (.0132, .0900) -.0466 (.0240) (-.0936, .0005) -.0108 (.0154)
Note. N = 751; CI = 95 per cent confidence interval for all intervals; if CI does not include zero the effect is
considered statistically significant; * p < .05; ** p < .01.
The test with flexibility in place as independent variable showed that the moderating effect of TASW on the path from flexibility in place to work-life balance was negative, however not significant (b* = -.00, p = .929). The path from work-life balance to wellbeing was significantly moderated by TASW (b* = -.05, p = .044). Hypothesis 4b was therefore partly accepted. Test statistics are displayed in Table 4. The plot of the effect is depicted in Figure 6. The negatively moderated effect of TASW becomes higher when work-life balance decreases. However, the lowest indicated scores of wellbeing and work-life balance can still be deemed satisfactory. Surprisingly, the score on wellbeing was the highest when TASW was high.
For the independent variable communication technology, the first path from communication technology to work-life balance was positively moderated, however not significantly (b* = -.02, p = .743), and the second path from work-life balance to wellbeing was negatively moderated (b* = -.05, p = .049). Table 5 shows the test statistics. The same holds here as for the independent variable flexibility in time. The confidence intervals of the conditional indirect effect of communication technology (X) on wellbeing (Y) at different values of the moderator TASW overlapped. The effect of communication technology on wellbeing through work-life balance did not significantly change when TASW was added as a moderator. Table 5 shows that also for this element the first path was positively moderated by TASW and the second path negatively. The moderating role of TASW could have been neutralized because of this and therefore did not exert a significant effect. Hypothesis 4c was rejected.
Table 4.
Bootstrap results for moderated mediation with flexibility in place as independent variable. Flexibility in place work-life balance b* (SE) Work-life balance wellbeing b* (SE) Direct effect
flexibility in place wellbeing
b* (SE) TASW (CI) -.0021 (.0236) (-.0485, .0443) -.0485* (.0240) (-.0955, .-0014) -.0194 (.0179)
Note. N = 751; CI = 95 per cent confidence interval for all intervals; if CI does not include zero the effect is
considered statistically significant; * p < .05; ** p < .01.
Table 5
Bootstrap results for moderated mediation with communication technology as independent variable Communication tech work-life balance b* (SE) Work-life balance wellbeing b* (SE) Direct effect
communication tech wellbeing
b* (SE) TASW (CI) .0167 (.0509) (-.0833, .1167) -.0467* (.0237) (-.0936, -.0002) .1727** (.0391)
Note. N = 751; CI = 95 per cent confidence interval for all intervals; if CI does not include zero the effect is
considered statistically significant; * p < .05; ** p < .01.
Figure 6. Plot of the moderating effect of TASW on the relationship between work-life
Discussion
The aim of the study was to unravel the underlying mechanisms that could explain the relationship between NWW and the wellbeing of employees. Existing literature on the
association of NWW with wellbeing is inconsistent (De Menezes & Kelliher, 2011;
Kattenbach et al., 2010; Kelliher & Anderson, 2008; Almer & Kaplan, 2002). Examining the underlying processes that could explain the association with wellbeing can help to explain these inconsistent outcomes. NWW consists of three elements: flexibility in time, flexibility in place, and communication technology. Because employees can differ in their engagement on these elements, the mediation model was tested for all three independently.
Consistent with the first hypothesis, work-life balance positively mediated the relationship between NWW and wellbeing. Of all three elements, work-life balance was the strongest contributor to the mediation effect on the relationship with wellbeing. In the investigated organization, the NWW job design seemed to enhance the work-life balance of their employees and therefore also wellbeing in general. The results were consistent with existing literature stating that flexibility helps employees to balance work and life (McNall et al., 2010; Kattenbach et al., 2010; Hayman, 2009; Gajendran & Harrison, 2007; Raghuram & Wiesenfeld, 2004; Duxbury et al., 1998; Kirchmeyer, 1995; Greenhaus & Beutell, 1985). Work-life balance being a positive mediator was also consistent with the border theory from Clark (2000).
In all three mediation models, work intensification led to less wellbeing among employees, which was consisted with what was predicted and with current literature (Boxall & Macky, 2014; Kelliher & Anderson, 2010). Opposite to what was predicted, flexibility in time and communication technology led to less work intensification. This result was
inconsistent with studies that showed that work intensification can be a consequence of NWW (Perlow & Kelly, 2014; Kelliher & Anderson, 2010), especially of the element
communication technology (Towers et al., 2006; Chesley, 2014). One of the causes given for this intensification of work is a conflict between work and life, which is a stressor that
negatively effects the family life of employees (Perlow & Kelly, 2014). Possibly work-life balance and work intensification are connected, and less work intensification is felt when employees indicate to have a satisfactory balance between work and life. An overall positive work-life balance was indicated by the employees who participated in the study, which could explain why a result opposite to what was expected was found. However, flexibility in place was found to be positively related with work intensification. A possible explanation is that
people who indicate having high flexibility in place, probably work more from home. Working from home can possibly increase work intensity because of fewer work place distractions, which makes working harder and/or longer is easier (Kelliher & Anderson, 2010). It is also reported that flexibility in place can cause stress (De Menezes & Kelliher, 2011).
Social cohesiveness only contributed significantly to the mediation model with communication technology as independent variable. In this model the relationship between communication technology and wellbeing was positively mediated by social cohesiveness, which was opposite to what was hypothesized, which was that due to work designs like NWW people miss the informal interaction which can result in less social cohesiveness (Kurland & Cooper, 2002). An explanation for the opposite result found in this study can be that due to communication technology there is more effective and efficient communication and there is an enhanced availability of colleagues due to continuous connectivity (Ten Brummelhuis et al., 2012). This could explain why there was no loss of social cohesiveness found for this element of NWW and why social cohesiveness contributed the most in this mediation model compared to the other elements.
Lastly, on the relationship between the three elements of NWW with wellbeing mediated by work-life balance, the moderating effect of TASW was studied. This moderating role was not significant on the relationship of the elements flexibility in time and
communication technology with wellbeing, mediated by work-life balance. TASW did negatively moderate the path from work-life balance to wellbeing, with flexibility in place as the independent variable. When work-life balance decreased, the moderating role of TASW did lead to reduced wellbeing. This last found effect of TASW is consistent with the study of Fenner and Renn (2010). Their results indicated a positive association of TASW with work-family conflict. However, the findings of this study also suggest that although wellbeing decreases when work-life balance does, the wellbeing is still deemed highest when there is high TASW. Which seems contradictory. Nevertheless, even at the point representing low work-life balance, the mean work-life balance still represented a satisfactory balance. A possible explanation for this can also be found in Fenner and Renn (2010), who state that applying time management can diminish the conflict between work and life due to TASW. If someone performs TASW, but also knows how to apply time management effectively, this person engages in activities that contribute to both work and family responsibilities and ignores non-productive activities which do not help them to reach their goals (Fenner & Renn, 2010). So, if someone works more from home, engages a lot in TASW, but is also a time
manager, this person probably has more work-life balance and therefore a higher wellbeing. The more someone engages in TASW, the better time management should be needed to not let it affect their work-life balance and wellbeing. If people can lead themselves effectively, TASW does not have to decrease wellbeing. This could also be a possible explanation for the fact that no significant effect on wellbeing was found with flexibility in time and
communication technology as independent variables.
Limitations and future directions
There are some limitations that need to be taken into account when interpreting the results of this study. A consequence of testing a multiple mediator model is that specific indirect effects are most of the time attenuated as far as the mediators are correlated, which is a manifestation of collinearity (Preacher & Hayes, 2008). Preacher & Hayes (2008) state that this collinearity may lead to the conclusion that a specific mediator has no significant effect when in fact it does. This must be taken into account when interpreting the results of this study. Moreover, from the results of this study and current literature (Fenner & Renn, 2010) it seems like time management is important for creating a good work-life balance when working according to a NWW design. However, if the participants of this study actually engaged in time management was not investigated. Furthermore, the design was cross-sectional, so a causal relationship between NWW and the wellbeing of employees could not be verified. The locations of the organization investigated for this study integrally implemented NWW. To see if the wellbeing of employees improves by implementing NWW and integrating it in the culture of the organization, a longitudinal study should be conducted. The status of wellbeing before and after implementation can then be determined.
Moreover, only one organization was studied, which limits the generalization of the results to employees in other organizations. All organizations have different cultures which might affect outcome as well. If organizations are very formal or hierarchical it might be harder to work successfully according to a NWW design. Furthermore, in one sector NWW might be more suitable than in the other. For example, for governmental organizations like the police, surgeons, etcetera, this design is possibly less applicable. Even within organizations that are suitable for NWW, it might not be fitting for every employee. Receptionists for example cannot work according to this design.
In this study wellbeing of employees at work was measured. However, NWW not only affects the working life of people, it also affects their private life since they work more from home. So their perspective on wellbeing outside of work is also interesting to study.
Furthermore, wellbeing was measured by self-report from the perspective of the employees, but other family members can also be affected by someone who works according to a NWW design. The crossover effects of work and family can also be investigated (Cinamon, Weisel, & Tzuk, 2007; Hammer, Allen, & Grigsby, 1997).
Managerial implications
From a managerial standpoint, this study offers several suggestions. The relationship between NWW and wellbeing appeared to be positive, with work-life balance being the strongest mediator. To make it easier for employees to cross the borders between work and life, changing the organizational culture is needed besides adding flexibility in time and place (Clark, 2000). This is needed to create a workplace that is more accepting of NWW, since the permeability of boundaries due to more flexibility could cause work-life conflict (Perlow & Kelly, 2014). Engagement with a work design like NWW does not occur overnight. So, to be able to avoid work-life conflict among employees organizations have to take their time with implementing NWW, which depending on the size of the organizations could take years. The investigated company started implementing NWW in 2006. The implementation took years and was step by step integrated in their organizational culture. The three investigated locations integrally adopted the job design, which might have resulted in the positive association with work-life balance and wellbeing. Clark (2000) also points out that
supportiveness of supervisors and the central participation of employees are important for succeeding in creating a balance. The first to start working according to the NWW design in 2010, was the board of executives with the intention of setting an example for the rest of the employees. Managers were instructed to support their employees in the transition to NWW as from half a year before the complete switch to the new job design. This most likely
contributed significantly to a successful transition and minimalizing the conflict between work and life of the employees. If organizations decide to implement NWW, taking the time to carefully implement it and guiding the employees in finding their balance between work and life the change is important. It has to be made possible for employees to create this balance. What this balance looks like will be different for every individual. Attention should be given to the specific individual boundary management styles of the employees and how these enact in the context of the organization, moving away from a standardized work-family culture is important (Kossek & Lautsch, 2012). Consistently engaging in dialogue with the employees is also very important, managers should be open to this and guide their employees in the change. Managers should start the dialogue. If employees feel free to share their issues
about work and personal live, and frequently engage in dialogue about how to make changes happen, they are likely to gain more confidence in their ability to create this change, and consequently have a more satisfying work-life balance (Perlow & Kelly, 2014).
A consequence of employees working according to a NWW job design is being constantly connected through communication technologies, possibly also after work. For employees who are dealing with TASW, applying time management could help to avoid it getting in the way of their family life (Fenner & Renn, 2010). It would be helpful to guide these employees with setting clear goals and prioritizing as well as coaching on how to schedule and plan tasks and activities. Furthermore, because of flexibility offered by
communication technologies, knowledge workers might suffer from intensified expectations of their availability, resulting in performing more TASW and making it harder for them to disconnect form work (Mazmanian, Orlikowski, & Yates, 2013). In organization with a lot of knowledge workers, special attention should be paid to this. Clear agreements have to be made as to what extend employees and managers have to be flexible in responding to work-related issues after regular working hours. They could for example agree on a time after which no professional phone calls or emails will be answered anymore.
Organizations should at all times keep in mind that a transition to a job design like NWW is never only an instrumental change, it is a behavioral adjustment for the employees as well. Like Clark (2000) states, only adding flexibility in time and place is not enough. Being able to create a balance between work and life is not an easy change if employees are used to working only at the office and separating work and personal live. Having flexibility in time and place means that they have to be able to lead themselves. This is an important behavioral change that requires individual coaching by managers or for example by offering them a training.
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