The relevance of individual and motivational factors for consequences of blended working.

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Master Thesis:

The relevance of individual and motivational factors for consequences of blended working.

R. den Hollander S2453553

r.den.hollander@student.rug.nl

June 7, 2020

Master Thesis Human Resource Management

Faculty of Economics and Business Rijksuniversiteit Groningen

Supervisor: dr. S. Täuber s.tauber@rug.nl

Second Supervisor: dr. P.H. van der Meer

p.h.van.der.meer@rug.nl

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Abstract

IT possibilities and world-wide access to internet have resulted in a new way of working; blended working. But how and for whom blended working results in certain consequences remains unclear.

The literature describes many possible explanations but has failed to report consistent results. In this thesis, we combine individual and motivational factors to explain the effect of blended working on work-life balance, stress and social isolation. Basic psychological needs and motivational factors were measured through a survey-study, resulting in three models that describe the relationship on possible consequences. Due to the corona-crisis another questionnaire was distributed to include contextual factors in our research. The relationship between blended working and its consequences can be explained through autonomy and flexibility, employees’ need for autonomy positively interacted with these relationships and contextual factors are at the foundation of these effects.

Keywords: blended working, work-life balance, individual factors, motivational factors,

contextual factors

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The relevance of individual and motivational factors for consequences of blended working.

The work environment is changing. Technological possibilities have revolutionized the way we work. The shift from working in a conventional office towards autonomously working- employees is emerging (Gschwind & Vargas, 2019). Work is no longer an office you go to, work for 40 hours a week, and then leave behind. It is becoming a bigger part of our private lives.

Therefore, work-life balance is becoming an increasingly important research topic. This new way of working, enabled by technological innovation (i.e. connectivity through widely available internet), is generally described in two (overlapping) definitions. While extensive research has been conducted on the topic ‘telework’, referring to the fact that information technology (IT) enables remote working (Huws, Korte, & Robinson, 1993). Van Yperen, Rietzschel and De Jonge (2014) have introduced a new definition: Blended Working (BW). This refers to time- and location independent working and being able to decide how, when and where one works (e.g. working at home in the morning, get the kids from school at noon and work at the office in the afternoon).

Since the overlap between the topics is much greater than the (minor) differences between them, they are considered referring to the same concept and blended working will be used as the terminology in this study.

About 17,5% of Dutch workforce engages in blended working for at least half a day per

week (CBS, 2018). The greatest share of blended working is found among employees that do

knowledge work. This can be defined as creative production of, dealing with or conveying

knowledge in a network with activities facilitated by information and communication technologies

(as cited in Vesala & Tuomivaara, 2015). In contrast, the lowest share of blended working is found

among industry-based plant and machine operators, elementary jobs and craft related work (CBS,

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2015). A main reason for the increase of blended working is the underlying assumption that it has a positive impact on work-life balance. But is this really the case? Research finds mixed results.

Blended working has been found to enhance employees’ work-life balance (Huws et al., 1996;

Morganson, Major, Oborn, Verive, & Heelan, 2010). Other research show that blended working increases work-life conflict and interference from work to family (Byron, 2005; Song & Gao, 2019). This suggests that third variables play a role that affect the relation between blended working and work-life balance. The importance of research into work-life balance antecedents is supported by recent work that suggests it might serve as a proxy for many important job-outcomes (McCarthy, Darcy, & Grady, 2010). A lack of balance has been linked to increased report of burnouts (CBS, 2018). Furthermore, work-life balance affects important outcomes such as job satisfaction, productivity, stress and employee turnover (Bloom, Freeman, Shaw, Kretschmer, & van Reenen, 2013; Cooper & Kurland, 2002; Frone, 2003). These job outcomes are extremely relevant for organizations. Increasing productivity and job satisfaction and reducing employee stress and turnover is beneficial for companies. It will likely result in happier employees and consequently better performance.

To date, a reason for why blended working outcomes are sometimes positive, sometimes

negative has not been established. However, several researchers have found evidence that

motivational factors (e.g. autonomy) influence the effects of blended working (Chen et al., 2015; Van

den Broeck et al., 2010; Van Yperen et al., 2014). Furthermore, Van Yperen et al. (2014) found

evidence supporting the influence of individual factors. According to them, psychological needs play

a role in how effectiveness of blended working is perceived. These needs predict for who blended

working might work, and for whom it may not. However, their research was limited to the perceived

effectiveness. In order to find out how blended working leads to certain outcomes, an explanation is

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sought by combining both topics. The current research tries to answer two questions: How does blended working affect work-life balance? and for who do these effects apply? To answer the first, we ought to find these ‘third variables’ that explain the inconsistent relationship between blended working and work-life balance. The former question is answered by exploring the effects of psychological needs, similar to Van Yperen et al., (2014).

Contribution

The contribution of this thesis concerns finding moderators and mediators reconciling prior mixed findings in the literature. The goal is to combine past findings into one model to understand the effects of blended working on work-life balance. Although this research is not the first to explore potential mediators or investigate the influence of basic psychological needs on blended working consequences, it will likely contribute to existing literature. By combining individual and motivational factors this research will clarify the influence of both. The configurational approach that is used in this thesis is making the contribution even stronger.

The practical relevance in this research lies in the exploratory aspects. Since managers throughout the knowledge-work field face choices regarding blended working, understanding not only outcomes of blended working but also potential explanations are very relevant for them.

When deciding if and possibly how to implement blended working into a firm, it is advised to consider both individual workers’ characteristics (which cannot be altered) and motivational factors (which can be influenced). The insights this research will generate can increase knowledge of these factors and will likely improve the success of blended working implementation.

Theoretical Background

The concept of blended working comprises two aspects; time-independent and location-

independent working. Time-independency refers to flexibility concerning when and how long

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employees are engaged in work-related tasks, location-independency refers to flexibility concerning where one chooses to work (Van Yperen et al., 2014). The term blended working is used because there is no clear border between working at work or elsewhere. According to Van Yperen (2017, p. 157), “the term blended working unambiguously refers to a work arrangement in which workers alter between traditional office working and working from home or another location at any time.”. Though the term telework is used more (in research) than blended working, the latter provides a more comprehensive explanation.

Since the border between work and private life is diminishing, seeking a balance becomes increasingly important (Matthaei, 2010). Trying to find a balance between both is regarded a general part of life (Lewis & Beauregard, 2018). Many definitions have been reported, but in this thesis, “Satisfaction and good functioning at work and at home, with a minimum of role conflict”

(Clark, 2000, p. 751) is considered the definition of work-life balance. Work-life balance has been linked to several positive outcomes. A large study (N = 1416) of Haar, Russo, Suñe, and Ollier- Malaterre (2014) found strong support for work-life balance being beneficial for employees.

Among these benefits are higher job satisfaction, organizational performance and lower reports of anxiety, depression, turnover and burnout (Cegarra-Leiva, Eugenia Sánchez-Vidal, & Cegarra- Navarro, 2012; Frone, 2003; Haar et al., 2014; Malik, Saleem, & Ahmad, 2010; Shanafelt et al., 2012). As the name implies, work-life balance is regarded to have primarily positive consequences for individuals.

According to Sullivan and Lewis (2001) blended working is used to cope with the demands of work and family (i.e. increased flexibility will facilitate managing work and family demands).

The flexibility that comes with blended working is considered beneficial for the family through

improving communication and reducing costs of food and transportation (Hill, Ferris, &

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Märtinson, 2003). The impact on commuting, in costs and in time, are viewed as an attractive aspect of blended working. Working from home enables employees to better cope with family demands (e.g. doing groceries, taking kids from school) and thus finding a better balance (Tremblay, 2003). The possibility for blended working provides people the opportunity to strengthen family relationships and optimize time management (Hilbrecht, Shaw, Johnson, &

Andrey, 2008). Furthermore, Hill et al. (2003) found a strong positive relationship between working at home and work-life balance.

However, downsides of blended working on work-life balance have been reported.

According to Kurkland and Bailey (1999), the reduced travel time has a negative impact on employees. The period they normally commute is needed to prepare for- and cool down from work.

Employees need this transition time to change their mindset from work-oriented to home-oriented.

They consider transition as disrupting the balance between work and home. Another consequence of working at home might be distraction. When working at home, workers are more prone to be held off work by family members (Van Yperen, Wörtler, & De Jonge, 2016). Despite the notion of these apparent negative outcomes, the meta-analytic study from Gajendran and Harrison (2007) has shown the general positive consequences of blended working on work-life balance. It is thus expected that:

H1: There is a positive relationship between blended working and work-life balance.

Underlying processes: motivational factors

In order to explain the complex relationship between blended working and work-life

balance we first need to find out why there are effects. As mentioned before, past research has not

found clear results. Some report blended working increases work-life balance, some find it

decreases balance. This suggests third variables being at play. Several factors have been examined

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to explain positive as well as potentially negative effects of blended working on work-life balance.

The current research focuses on the most prominent (potential) mediators which are discussed below:

Autonomy. Autonomy is considered closely related to blended working. By providing workers

with a choice (i.e. they decide where and when to work), blended working enhances employee autonomy (Weinert, Maier, & Laumer, 2015). “Developments in IT have enabled qualitatively new working arrangements that offer more opportunities for teleworkers to exercise greater autonomy.” (Sewell & Taskin, 2015, p. 1509). Multiple studies have reported the autonomy that comes with blended working is related to several positive outcomes (Bélanger & Allport, 2008;

Gajendran, Harrison, & Delaney-Klinger, 2015; Sardeshmukh, Sharma, & Golden, 2012).

According to Moore (2007), autonomy serves as a condition to achieve balance. An explorative qualitative study of Annink and den Dulk (2012) investigated the role of autonomy on work-life balance. They found autonomy does not always lead to improvements in work-life balance.

Furthermore, a positive relationship between autonomy and work-life balance has been found in several quantitative studies (Emre & De Spiegeleare, 2019; Fotiadis, Abdulrahman, & Spyridou, 2019). Benz and Frey (2008) found that autonomy mediates the relationship between self- employment and work-life balance. Self-employment is similar to blended working in the way self-employed people decide when and where they work too. Therefore, it is expected that:

H2: There is a positive indirect effect of blended working on work-life balance via autonomy.

Flexibility. The general use of smartphones and widely available internet has led to employees

carrying work tasks with them wherever they go, thereby facilitating work flexibility (Van

Laethem, van Vianen, & Derks, 2018). By engaging in blended working, employees are granted

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the freedom to decide where and when they work, thereby increasing their flexibility (Allen, Johnson, Kiburz, & Shockley, 2013; Van Yperen et al., 2014).

There is a discrepancy found in results regarding flexibility and work-life balance.

According to Higgins, Duxbury and Johnson (2000), the flexibility that comes with blended working enables employees to achieve a better balance, but in practice this is not always the outcome. Flexible workers might even struggle to achieve a balance between work- and family demands (Warren, 2004). Though seemingly negative, a quantitative meta-analysis found that flexibility decreases interference (Byron, 2005). Furthermore, flexible employees were generally satisfied with their work-life balance (Kelliher & Anderson, 2010). As for autonomy, flexibility mediated the relationship between self-employment and work-life balance (Benz & Frey, 2008).

Therefore, it seems plausible that flexibility increases work-life balance and it is expected that:

H3: There is a positive indirect effect of blended working on work-life balance via flexibility.

Stress. The relationship between blended working and stress has been researched extensively.

Though some negative effects have been found, the majority of studies found that blended working

increases stress. Because workers are constantly connected with their work – enabled by blended

working – they cannot take a break, consequently increasing stress (Day, Scott, & Kelloway,

2010). The research of Hartig, Kylin, and Johansson (2007) was aimed at explaining the blended

working-stress relationship. They theorize that though blended working is increasing work-related

stressors it has a mitigating effect on non-work-related ones. Their research seems like an advocate

for the stress-reducing effects of blended working. However, multiple studies investigated the

effects of stress on work-family conflict and found that stress adds work demands (Chang, Zhou,

Wang, & Heredero, 2017). Lastly, Podsakoff, Lepine, and Lepine (2007) found evidence that the

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strain which comes with stress is associated with problematic investment of resources in family, which results in more conflict. These work demands lead to stress, which then results in conflict.

Even though work demands will not be measured, there still seems to be an indirect effect between blended working and work-life balance via stress. It is expected that:

H4: There is a negative indirect effect of blended working on work-life balance via stress.

Social Isolation. It is imaginable that blended workers have less face-to-face contact with

colleagues when working remotely. By choosing not to work at the office, social isolation is considered a consequence of blended working (Sewell & Taskin, 2015). The lack of office environment was associated with developmental issues, making workers feel professionally isolated (Charalampous, Grant, Tramontano, & Michailidis, 2019). A quantitative study from Morganson, Major, Oborn, Verive, and Heelan (2010) showed that office-based workers experience higher levels of inclusion compared to remote-workers. Furthermore, social isolation has been linked to job-outcomes such as decreased job satisfaction and lower performance (Cooper

& Kurland, 2002; Golden, Veiga, & Dino, 2008). When office-workers show resentment towards blended workers, contact between them becomes more difficult (Tietze & Nadin, 2011). However, not all remote-workers experience isolation, which indicate possible mediation or moderation (Bentley et al., 2016). The degree to which isolation is experienced is, among other things, dependent on the intensity and frequency of which workers engage in blended working activities (Wilton & Scott, 2011). When employees feel isolated, they usually also feel less relevant. To compensate for this, they use strategies that signal their presence (e.g. sending an excessive number of messages to signal availability to colleagues) (Sewell & Taskin, 2015). Overall, many studies have found evidence that blended working increases social isolation (Golden et al., 2008; Mulki

& Jaramillo, 2011).

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Little to no research has examined the relationship between social isolation and work-life balance. We expect that, when workers feel socially isolated, they experience a lack of social connection (with colleagues). They will likely spend more time away from work (i.e. at home) and will spend more time around their family members. Though isolation implies negative effects, the upside of this might be the improvement of private relationships. The question if these isolating feelings affect the balance between work and private life remains unanswered. Because there is less time spend at the office - which means the balance point being more on the private side than the work side - the construct does imply imbalance. It is thus expected that:

H5: There is a negative indirect effect of blended working on work-life balance via social isolation.

Moderating effects of psychological needs

According to the Self Determination Theory (SDT, Deci & Ryan, 2000) people have three basic needs; these concern their need for autonomy (NfA), need for competence (NfC) and need for relatedness (NfR). These needs are intrinsic to human motivation. Usually, the needs are treated as individual difference variables, meaning that their strength differs between individuals (Gagné

& Deci, 2005). Blended working does not work for everyone. In research from Van Yperen et al.

(2014), they have combined literature on SDT from Deci and Ryan (2000) and (Thompson,

Naccarato, Parker, & Moskowitz, 2001). They found evidence for a fourth need, need for structure

(NfS), which is related to blended working effectiveness: “Indeed, our findings suggest that

blended working is most suitable for workers who are high in need for autonomy, low in need for

relatedness, and low in need for structure.” (Van Yperen et al., 2014, p. 5). Though they have not

found significant indicating a relationship with need for competence, its influence will be

investigated in this research.

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Since it is assumed these are basic human needs (with the addition of need for structure), all four needs probably influence the relationships in their own way. It is plausible some needs are relevant for certain mediators, but irrelevant for others. Given these uncertain outcomes this research will explore the influence of psychological needs on the suggested relationships. This will enhance our understanding of the interplay between contextual factors (blended working), motivational factors (mediators) and individual factors (needs). The combination of these factors will determine how blended working affects work-life balance and for whom this applies.

Method Participants and procedure

The aim of this thesis was to enhance knowledge about the blended working – work-life balance relationship. A quantitative survey-study was designed in order to test the hypotheses.

This questionnaire enabled us to investigate many variables in a relatively short period.

Furthermore, the same questions are presented to all participants, making for better comparison.

The questionnaire was open for one month and available via Qualtrics. Within this period, 703 people participated in the study. The survey was open to everyone and participants were sourced via the personal network of the author. In addition to this convenience sample, the survey was posted on participant-exchange websites (SurveySwap and SurveyCircle). Participants with missing data and those working less than 8 hours per week were deleted data-gathering was complete. This resulted in complete data of 526 respondents. Age ranged from 18 to 70 (M = 32.27, SD = 12.29, 55.5% male, 44.5 % female). Hours worked per week ranged from 8 to 90 hours (M

= 35.82, SD = 11.57). Thirty-five percent of the sample worked part-time (< 34 hours per week);

65% worked full time (> 35 hours per week). Participants had an average work experience of 9.28

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years (SD = 11.71). The predominant sectors they worked in were IT (22.2%), B2B (10.6%), marketing (10.5%) and healthcare (10.3%).

Measurements

Blended working. Blended working was measured with an altered version of the questionnaire from Van Yperen et al. (2014). From the scores of all six items that measured blended working, an average score was conducted. In this average, a higher score represented more opportunity for blended working (M = 3.62, SD = 0.88, α = .83). Items were rated on a 5-point Likert scale, ranging from 1 (completely disagree) to 5 (completely agree). In addition, the amount of blended working was measured, too. Participants reported the percentage of blended working (%BW) per week (0%

– 100%). This measure ensures a less biased and less abstract indication of how much blended working participants engage in. %BW will be used as the IV in hypothesis testing and will be referred to as ‘BW’.

Unless indicated otherwise, all variables were assessed on 5-point Likert-scales ranging from1 (completely disagree) to 5 (completely agree). A complete overview of all items can be found in the Appendix.

Work-life balance. Work-life balance was measured through the question of Fisher, Matthews and Gibbons (2016). The single question measures the extent to which the participant feels their work and private life in balance (M = 3.73, SD = 0.90).

Stress. Stress was measured using the six-item scale of (Houtman et al., 1995) (M = 2.51, SD = 0.82, α = .89). Items were rated on a 5-point Likert scale, ranging from 1 (never) to 5 (very often).

Social isolation. Social isolation was measured with the 7-item questionnaire from (Golden et al.,

2008) (M = 2.14, SD = 0.82, α = .90).

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Social Determination index. The psychological preference of the participants was measured with the questionnaire from Van Yperen et al. (2014). The three original psychological needs with the added scale for Need for Structure were tested with four items for each need. NfA (M = 3.97, SD

= 0.69, α = .84), NfR: (M = 3.32, SD = 0.86, α = .85) NfC: (M = 4.22, SD = 0.63, α = .87) NfS: (M

= 3.10, SD = 0.84, α = .82). Items were rated on a 5-point Likert scale, ranging from 1 (not at all) to 5 (to a large extent).

Mediators. To measure the two mediating variables, a combination of multiple questionnaires was used. Autonomy was measured using the 4-item scale of (Chen et al., 2015) (M = 3.73, SD = 0.65, α = .78). Flexibility was measured using the 3-item scale from Yucel (2018) (M = 3.74, SD = 0.82, α = .78).

Results Descriptive data

Means, standard deviations, correlations and Chronbach’s alphas are presented in Table 1.

As shown, multiple demographic variables correlate with the three dependent variables.

Significant correlations were found between Age and Stress (r = -.25, p < .01) and Social Isolation (r = -.10, p < .05). Furthermore, the number of hours participants worked per week significantly correlated with work-life balance (r = -.15, p < .01) and Social Isolation (r = -.09, p < .05).

Additionally, blended working significantly correlated with work-life balance (r = .16, p < .01) and stress (r = -.09, p < .05). Based on these relationships, Age, blended working, and Hours, with the addition of Gender and the Sector participants worked in (not reported in Table 1) were included as covariates in further analysis.

As can be seen from the correlation table, only weak correlations of blended working with

stress and social isolation were found. Instead, the latter two variables showed relatively high

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Table 1. Correlations

correlations with autonomy and flexibility. This indicated that stress and social isolation might function as dependent variables on the same level as work-life balance, rather than as mediators. Reflecting this finding, we decided to restrict the mediators to autonomy and flexibility and extend the dependent variables to include work-life balance, stress, and social isolation. All three models were significant and results of all are reported below.

Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1. Blended Working (.83) 2. Work-life Balance .16** -

3. NfA .29** .14** (.84)9

4. NfR -.0899 .0799 -.0399 (.85)9

5. NfC .15** .09*9 .33** .13** (.87)

6. NfS -.0599 -.0799 -.0799 .17** .24** (.82)9

7. Autonomy .26** .34** .40** .0399 .20** .0199 (.78)9

8. Flexibility .26** .56** .29** .0199 .0499 -.09*9 .37** (.78)9

9. Stress -.09*9 -.45** -.12** .0199 .0499 .31** -.33** -.42** (.89)9

10. Social Isolation .0399 -.25** -.12** .0599 -.0499 .28** -.24** -.25** .49** (.90)9 11. Age .11*9 .0699 .12** -.25** -.0599 -.28** .0899 .12** -.25** -.10*9 -

12. Hours .23** -.15** .20** -.12** .09*9 -.17** .18** -.07 .0199 -.09*9 .19** -

13. Experience .0999 .0699 .0699 -.25** -.09*9 -.28** .0499 .10* -.23** -.10*9 .91** .15** -99 9 14. Percentage BW .26** .11** .16** -.13** -.0199 .0099 .21** .28** -.0299 .0999 .0899 .0499 -.0799 -99

M 3.6299 3.7399 3.9799 3.3299 4.2299 3.1099 3.7399 3.7499 2.5199 2.1499 32.2799 35.8299 9.2999 26.7299 SD 0.8899 0.9099 0.6999 0.8699 0.6399 0.8499 0.6599 0.8299 0.8299 0.8299 12.2999 11.5799 11.7199 28.4499 Note. N = 526. * p < .05; ** p < .01

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Model testing

To test the models, the PROCESS macro by Hayes (2020; model 7; 5000 bootstrap samples; CI = 95%) was used. The effect of blended working on work-life balance, stress and social isolation was tested, its mediation by autonomy/flexibility and its moderation by Need for autonomy. Mediator results are reported in Table 2. Given the explorative nature of the psychological needs study, all four needs were tested. A significant interaction between Need for autonomy and blended working was found on both autonomy (b = .11, CI

95%

= .03; .19) and flexibility (b = .11, CI

95%

= .03; .19). These interactions indicate that the positive effect of blended working on both autonomy and flexibility was stronger among employees with a high need for autonomy.

Table 2. Mediation Results

DV = Autonomy, R²=22.04%

Predictor b SE t 95% CI

Constant -.02 .04 -.44 [-.09; .06]

Percentage Blended Working .11 .04 2.73 [.03; .19]

Need for Autonomy .34 .04 8.11 [.25; .42]

NfA x Percentage Blended Working .11 .04 2.70 [.03; .19]

Age -.03 .04 -.61 [-.11; .06]

Blended Working .12 .04 2.88 [.04; .21]

Gender -.04 .04 -1.05 [-.13; .04]

Hours .07 .04 1.61 [-.02; .13]

Sector .06 .04 1.38 [-.02; .13]

DV = Flexibility, R²=20.86%

Constant -.02 .04 -.45 [-.10; .06]

Need for Autonomy .24 .04 5.72 [.16; .32]

NfA x Percentage Blended Working .11 .04 2.77 [.03; .19]

Age .08 .04 1.93 [.00: .16]

Blended Working .17 .04 3.99 [.09; .26]

Gender -.04 .04 -.98 [-.12; .04]

Hours -.20 .04 -4.72 [-.28; -.12]

Sector -.02 .04 -.44 [-.10; .06]

Note. IV = Percentage Blended Working, Moderator = Need for Autonomy (NfA), Control variables = Age;

Blended Working; Gender, Hours, Sector.

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The other three psychological needs (NfC, NfR, NfS) consistently showed no interactive effects in all models. They were not included in further analysis and are not reported. A significant effect was found between blended working and autonomy (b = .11, CI

95%

= .03; .19) as for flexibility (b = .18, CI95% = .10; .26), indicating that more blended working results in more experienced autonomy and flexibility.

A significant effect was found between blended working and autonomy (b = .11, CI

95%

= .03; .19) as for flexibility (b = .18, CI95% = .10; .26), indicating that more blended working results in more experienced autonomy and flexibility.

Effects of Blended Working on Work-life Balance. Blended working did not significantly

affect work-life balance (b = -.07, CI

95%

= -.15; .00). However, work-life balance significantly affected autonomy (b = .20, CI

95%

= .12; .28) and flexibility (b = .48, CI

95%

= .40; .56), indicating that more autonomy and flexibility result in greater Work-life balance (Figure 1).

Figure 1. Moderated mediation model for Work-Life Balance.

Note. Indices for moderated mediations presented in bold, * p < .05, ** p < .01, *** p < .001.

The indirect effect of blended working on work-life balance via autonomy was significant, as shown in Table 3. The moderated mediation index was significant (b = .02, CI

95%

= .00; .04), which is reflected in the finding that blended working affects work-life balance

through autonomy for employees with moderate (b = .02, CI

95%

= .00; .05) and high (b = .04,

CI

95%

= .02; .08), but not with low NfA (b = .00, CI

95%

= -.03; .03). Thus, the positive indirect

effect of blended working on work-life balance via autonomy is stronger when people have

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a higher need for autonomy.

Table 3. Results for Work-life Balance

DV = Work-life Balance, R²=36.00%

Constant .00 .04 .00 [-.07; .07]

Percentage Blended Working -.07 .04 -1.93 [-.15; .00]

Autonomy .20 .04 5.01 [.12; .28]

Flexibility .48 .04 11.88 [.40; .56]

Age .03 .04 .75 [-.05; .10]

Blended Working .05 .04 1.16 [-.03; .12]

Gender .04 .04 1.03 [-.04; .11]

Hours -.16 .04 -4.07 [-.23; -.08]

Sector .00 .04 -.10 [-.07; .07]

Moderated mediation model

Index of moderated mediations Index BootSE 95% CI

Autonomy .02 .01 [.00; .04]

Conditional effects Effect BootSE 95% CI

Low need for autonomy (-1 SD) .00 .02 [-.03; .03]

Moderate need for autonomy (M) .02 .01 [.00; .05]

High need for autonomy (+1 SD) .04 .01 [.02; .07]

Index of moderated mediation Index BootSE 95% CI

Flexibility .05 .02 [.01; .10]

Moderate need for autonomy (M) .09 .02 [.05; .13]

High need for autonomy (+1 SD) .14 .03 [.09; .21]

Note. IV = Percentage Blended Working, Moderator = Need for Autonomy (NfA), Mediator = Autonomy;

Flexibility, Control variables = Age; Blended Working; Gender, Hours, Sector

A similar pattern was found for flexibility. The indirect effect of blended working on

work-life balance via flexibility was significant, as shown in Table 3. The moderated mediation

index was significant (b = .05, CI

95%

= .01; .10), which is reflected in the finding that blended

working affects work-life balance through flexibility for employees with moderate (b = .09,

CI

95%

= .05; .13) and high (b = .14, CI

95%

= .08; .21), but not with low NfA (b = .03, CI

95%

= -

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.03; .09). Thus, the positive indirect effect of blended working on work-life balance via flexibility is stronger when people have a higher (+1 SD) need for autonomy.

Effects of Blended working on Stress. Blended working significantly affected stress (b = .13,

CI

95%

= .05; .21). Furthermore, autonomy and flexibility significantly and negatively affected stress (b = -.23, CI

95%

= -.31; -.27 and b = -.35, CI

95%

= -.44; -.27, respectively), indicating that more autonomy and flexibility result in less stress (see Table 4).

Table 4. Results for Stress

DV = Stress, R²=28.12%

Constant .00 .04 .00 [-.07; .07]

Autonomy -.23 .04 -5.50 [-.31; -.15]

Flexibility -.35 .04 -8.24 [-.44; -.27]

Age -.20 .04 -4.98 [-.27; -.12]

Blended Working .05 .04 1.26 [-.03; .13]

Gender .09 .04 2.16 [.01; .16]

Hours .07 .04 1.63 [-.01; .15]

Sector .00 .04 .07 [-.07; .08]

Autonomy -.03 .01 [-.05; .00]

Moderate need for autonomy (M) -.03 .01 [-.05; -.01]

High need for autonomy (+1 SD) -.05 .02 [-.09; -.02]

Flexibility -.04 .02 [-.08; -.01]

Low need for autonomy (-1 SD) -.02 .02 [-.07; .02]

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The indirect effect of blended working on stress via autonomy was significant, as shown in Table 4 and Figure 2. The moderated mediation index was not significant (b = -.03, CI

95%

= -.05; .00), which is reflected in the finding that blended working affects stress through autonomy for employees with moderate (b = -.03, CI

95%

= -.05; -.01) and high (b = -.05, CI

95%

= -.08; -.02), but not with low Need for autonomy (b = .00, CI

95%

= -.04; .03). Thus, the positive indirect effect of blended working on work-life balance via autonomy is stronger when people have a higher need for autonomy.

Figure 2. Moderated mediation model for Stress

The indirect effect of blended working on stress via flexibility was significant, as shown in Table 4 and Figure 2. The moderated mediation index was significant (b = -.04, CI

95%

= -.08;

-.01), which is reflected in the finding that blended working affects stress through flexibility for employees with moderate (b = -.06, CI

95%

= -.10; -.03) and high (b = -.10, CI

95%

= -.16; -.06), but not with low Need for autonomy (b = -.02, CI

95%

= -.07; .02). Thus, the negative indirect effect of blended working on stress via flexibility is stronger when people have a higher need for autonomy.

Effects of Blended Working on Social Isolation. A significant direct effect was found between

blended working and social isolation (b = .30, CI

95%

= .11; .28). However, significant negative

effects on social isolation were found for autonomy (b = -.18, CI

95%

= -.27; -.09) and flexibility

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(b = -.25, CI

95%

= -.35; -.16), indicating that more autonomy and flexibility result in less social isolation (see Table 5).

Table 5. Results for Social Isolation

DV = Social Isolation, R²=13.91%

Constant .00 .04 .00 [-.08; .08]

Autonomy -.18 .05 -3.98 [-.27; -.09]

Flexibility -.25 .05 -5.43 [-.35; -.16]

Age -.06 .04 -1.37 [-.14; .03]

Blended Working .05 .05 1.17 [-.04; .14]

Gender -.02 .04 -.37 [-.10; .07]

Hours -.09 .04 -1.92 [-.17; .00]

Sector -.04 .04 -.87 [-.12; .05]

Autonomy -.02 .01 [-.04; .00]

Moderate need for autonomy (M) -.02 .01 [-.04; .00]

Flexibility -.03 .01 [-.06; -.01]

Low need for autonomy (-1 SD) -.02 .02 [-.05; .02]

The indirect effect of blended working on social isolation via autonomy was significant, as shown in Table 5 and Figure 3. The moderated mediation index was not

significant (b = -.02, CI

95%

= -.04; .00), which is reflected in the finding that blended working

affects social isolation through autonomy for employees with high (b = -.04, CI

95%

= -.07; -

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.01), but not with moderate (b = -.02, CI

95%

= -.04; .00) and low Need for autonomy (b = .00, CI

95%

= -.03; .03). Thus, the positive indirect effect of blended working on social isolation via autonomy is only significant when people have a high need for autonomy.

Figure 3. Moderated mediation model for Social Isolation

The indirect effect of blended working on social isolation via flexibility was significant, as shown in Table 5 and Figure 3. The moderated mediation index was significant (b = -.03, CI

95%

= -.06; -.01), which is reflected in the finding that blended working affects social isolation through flexibility for employees with moderate (b = -.05, CI

95%

= -.07; -.02) and high (b = - .07, CI

95%

= -.11; -.04), but not with low need for autonomy (b = -.02, CI

95%

= -.05; .02). Thus, the negative indirect effect of blended working on social isolation via flexibility is stronger when people have a higher need for autonomy.

Contextual factors

In sum, these results show the relevance of individual needs and motivational factors

for predicting the effects of blended working on focal variables like work-life balance, stress

and social isolation. The corona-pandemic offered a unique possibility to include different

contextual factors into the study. Blended working is commonly considered something

voluntary, something an employee chooses to do. However, the coronavirus has forced many

to stop commuting and to work from home continuously. We took this change to repeat the

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same study during this contextual change. Data was collected in with similar methods and gathered in the first half of April 2020.

The findings from the first study were not repeated. The work-life balance, stress and social isolation models were non-significant in the second study. Because the percentage blended working was extremely skewed (due to almost everyone working from home) this measure could not be used and likely influenced the results. An independent t-test was used to compare pre- and post-corona data (see Table 6).

Table 6. Independent T-test results pre- and post-corona studies.

Mean SD t df p %-change

Blended Working Pre-corona 3.62 .88

-1.61 339 .00 +3.3 % Post-corona 3.74 .81

Work-life Balance Pre 3.73 .90

1.26 308 .21

Post 3.63 .93

Stress … 2.51 .82

1.31 365 .19

… 2.42 .71

Social Isolation 2.14 .82

-12.48 314 .00 +41.1 % 3.02 .82

NfA 3.97 .69

4.20 256 .00 -8.1 % 3.65 .92

NfC 4.22 .63

5.28 267 .00 3.88 .79

NfR 3.32 .86

-.19 308 .85 3.34 .89

NfS 3.10 .84

-4.04 320 .00 3.39 .83

Autonomy 3.73 .65

1.65 278 .10 3.62 .76

Flexibility 3.74 .82

-2.33 319 .02 +10.4 % 3.90 .81

Age 32.27 12.29

1.38 350 .17 30.92 11.04

Hours 35.82 11.57

1.82 324 .07 34.05 11.29

Experience 9.29 11.71

1.39 566 .10 7.67 10.61

Percentage Blended Working 26.72 28.44

-15.31 261 .00 +171.4 % 72.51 36.83

Note. Npre-corona = 526, Npost-corona = 183.

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After selection and elimination of incomplete data 183 people participated in the second survey. Eighty-one of these participants had participated in the initial survey. Since no identifying variables were used the data was not paired. A significant difference in the scores

%BW

pre-corona

(pre: M = 26.7%, SD = 28.4) and %BW

post-corona

(M = 72.5%, SD = 36.8, t(261)

= -15.3, p < .00) was found. Other interesting differences were found in Social Isolation

pre- corona

(pre: M = 2.14, SD = .82) and SI

post-corona

(M = 3.02, SD = .82, t(315) = -12.5, p < .00).

As mentioned, psychological needs are considered fairly stable within people. They are comparable with traits, which only vary slightly over time. However, significant

differences were noted between the two studies. A decrease in need for autonomy (pre: M = 3.97, SD = .69, post: M = 3.65, SD = .92, t(256) = 4.2, p < .00) was found. However, the SD in the second study was larger, likely because the smaller sample size. A decrease for need for competence was also found (pre: M = 4.22, SD = .63, post: M = 3.88, SD = .79, t(268) = 5.3, p < .00). The final significant difference is found for flexibility (pre: M = 3.74, SD = .82, post: M = 3.90, SD = .81, t(319) = -2.3, p < .05).

Discussion

Over the past years, working from home, or blended working as van Yperen (2014)

labelled the subject, has gained a lot of attention. IT development and world-wide internet

access have made remote working possible for nearly everyone. However, the consequences

and theoretical implications have been ambiguous. Even though blended working is generally

considered as having positive consequences for employees (Sullivan & Lewis, 2001) and

(Tremblay, 2003), some negative aspects have been reported, too (e.g. by Kurkland and Bailey

(1999)). The initial interest of this study was to take individual and motivational concepts into

account to explain these mixed findings. The questions guiding this research were twofold: why

does blended working influence work life balance and when does this happen? Additionally,

an incredible opportunity was presented due to the coronavirus outbreak. As work situations

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changed drastically over the course of two weeks, many started blended working. This gave us the chance to include contextual factors into the study and expand the study to a three-part focus (motivational, individual and contextual).

Understanding the moderated-mediation models consists grossly of two parts (forming the model as a whole when combined). The first part, the mediation, describes the indirect effects of blended working on the dependent variables (work-life balance, stress, social isolation) via both autonomy and flexibility. These indirect effects answer the ‘why question’

and try to explain de relationship between blended working and the DVs by adding the mediators to the mix. The second part is the moderation of the mediation (hence a moderated mediation), answering the ‘when’ question. As discussed below, the indirect effects as a whole are conditional (i.e. in some situations the indirect effects occur, in others they do not). The basic psychological needs were used to answer this section. As mentioned before, only need for autonomy showed to be of significant influence in this study. The Social Determination index implies these basic psychological needs are rather fixed (Gagné & Deci, 2005), meaning they can be considered a personal characteristic (some having a low NfA, others having a high NfA).

This translates the ‘when’ question into a ‘for whom’ question. Since the need for autonomy is considered a fixed characteristic, its influence determines for whom the indirect effect is stronger and when it is significant.

Motivational factors

The relationship between blended working and work-life balance was examined in an

effort to reconcile inconsistent prior results. We found that blended working is associated with

positive consequences. These are explained by two mediating variables; autonomy and

flexibility. Employees experience more autonomy and more flexibility as a result from blended

working. These increases lead to less stress and social isolation, while increasing work-life

balance.

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Individual factors

We found empirical evidence that the need for autonomy influences the consequences of blended working. As the need for autonomy increases, employees experience more work- life balance and less stress and social isolation. Especially those having a high need for autonomy experience these benefits. However, blended working will likely not ‘work’ for employees with a low need for autonomy. No significant results were found for those participants.

Contextual factors

These results indicate the consideration of contextual factors is highly important. As discussed, the amount of blended working an employee engages is influences their work-life balance, stress and social isolation through autonomy and flexibility. The voluntary principle of blended working; deciding yourself when and where to work forms the fundament of our results. If this is the case, blended working works (better) for those with a high need for autonomy, resulting in more work-life balance and less stress and social isolation.

However, the corona crisis has changed the world drastically. The virus has spread throughout the world, resulting in extreme measures from governments. To stop the spread of the virus, social distancing is to be the ‘new normal’. Keeping physical distance, doing only necessary travels and most relevant in this research, working from home as much as you can.

The results are interesting; the percentage of blended working almost tripled. This difference was expected because offices are closed and people were forced to work from home.

Furthermore, the Dutch Travelpanel (NPV) has reported up to a 40% reduction of commuting

since the Coronavirus outbreak. This likely contributes to the change in this percentage. As

results from the first study imply, an increase in blended working is likely to result in more

autonomy and flexibility, which then result in more work-life balance, less stress and less social

isolation. However, these expectations were not supported in the post-corona data.

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The increase in social isolation is very large. Especially when you consider the second survey data was gathered in the beginning of the lockdown (first two weeks of April 2020).

Again, because people are ‘locked’ at home, they only have virtual contact with others. You can assume that if quarantine lasts longer, people feel more isolated. Lacking face-to-face contact with colleagues at work has likely resulted in this large increase. Furthermore, this increase is cause for concern since social isolation has been linked to negative outcomes such as depression (Hall-Lande, Eisenberg, Christenson, & Neumark-Sztainer, 2007).

As mentioned, psychological needs are considered fairly stable within people. They are comparable with traits, which only vary slightly over time. However, significant differences were noted between the two studies. We found differences for need for autonomy, need for competence and need for structure. We find the corona crisis a plausible explanation for this change. Since the day-to-day life changed so drastically, this might have influenced these

‘basic’ needs. The impact of the corona consequences are of such influence, it even influenced these stable characteristics.

We assume that the non-voluntary change of context has had prominent influence on the results. As mentioned before, blended working is considered a voluntary option for employees. This is also reflected in our findings; those needing autonomy are more likely to profit from blended working than others. Employees are forced to work from home during this crisis. Basically, taking away any autonomy or flexibility that was originally gained by this practice. Even though our models are not supported in the second study, the lack of results indicate a certain level of free will is a necessity for blended working to have positive consequences.

Theoretical implications

In contrast with original hypotheses and meta-analytic research from Gajendran and

Harrison (2007), no direct effect was found between blended working and work-life balance.

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However, the interactive indirect effects are explainable. When people engage in more blended working, they experience more autonomy and flexibility (Van Yperen et al., 2014; Weinert, Maier, & Laumer, 2015), especially when they have a moderate to high need for autonomy.

Through increased autonomy and flexibility, employees’ work-life balance increases, while stress and social isolation decrease. Having the freedom to combine work and private related tasks results in a better balance overall. Similar results have been found by Kelliher and Anderson, 2010. Furthermore, van Yperen et al., (2014) found a similar interactive effect.

While testing the effectiveness of blended working, they found “particularly workers high in need for autonomy perceive blended working as highly personally effective.”. Eventhough the complexity and the scope of the current model have not been researched before, the essence of their findings is similar. When employees have a high need for autonomy they have the urge to divide their tasks and times themselves. Blended working fulfills these needs, giving employees the autonomy and flexibility they need, resulting in positive outcomes. When employees do not have those similar needs, they also lack these positive results (as shown in the non-significant effect for low NfA). Overall, the need for autonomy moderates the relationship between blended working and its consequences. Despite the fact a direct relationship was not found in this model, the positive effect on work-life balance is explained through an increase in autonomy and flexibility. Assuming this, these effects are stronger for people that need these results.

The stress model was not hypothesized in this study. However, similar results have been

found in previous research. As found by Song and Gao (2019), blended working does increase

stress, as reflected by the direct effect. However, the indirect effects of autonomy and flexibility

are negative. Similar results have been found by a study from Kalleberg, Nesheim and Olsen

(2009). They found that autonomy reduces job stress. Flexibility has been found to reduce

work-related health problems (like stress) in multiple studies (Butler, Grzywacz, Ettner, & Liu,

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2009; Halpern, 2005). However, no research has focused on the moderating role of the need for autonomy in this relationship. This need does not specifically moderate the effects of autonomy and flexibility on stress. Rather it moderates the model as a whole. The positive effects that result from blended working are stronger for people high in NfA because blended working works better for those people.

The implications of results from the third model are similar to the stress model. A positive effect between blended working and social isolation is found, implying more blended working results in more social isolation. When people engage in more blended working, they spend less time at work, resulting is less face-to-face contact with colleagues, resulting in more social isolation (Morganson et al., 2010). In line with results from Wilton and Scott (2011), the degree to which social isolation is experienced is dependent on the intensity and frequency one engages in blended working-activities.

Overall, the influence of the need for autonomy has been confirmed. In line with the social determination theory, an individual’s basic psychological need influences the effect of situational variables. It can be concluded that blended working works best for those having a high need for autonomy in line with Van Yperen et al. (2014). Compared to employees having a moderate need for autonomy, employees with a high need for autonomy are likely to benefit more from blended working. Though the scope of this study has only confirmed effects for work-life balance, stress and social isolation, it is expected the interactive effect can be found for other outcomes. In general, the higher one needs autonomy, the greater they experience the benefits resulting from blended working.

Practical implications

The results show blended working is a complex subject. It shows to be a considerable

option to implement because of the positive consequences employees experience. The main

finding of this research is that blended working does not work for all. Actually, individual

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differences are shown to be an important aspect to consider. Our results imply the reason blended working does not work for everyone can be explained by their basic needs. When employees do not feel the need for blended working (i.e. they have a low need for autonomy) they will likely not benefit from it (as much as employees with a high need for autonomy). It is advised for companies to take personal differences into account when implementing blended working practices. If an employee has a need for blended working, they will likely benefit from it, at least on a personal level. Similarly, if an organization decides to implement blended working practices for all employees, they should expect it will not work for everyone.

Strengths and limitations

The current research is based on correlational methods. It should be noted the results do not automatically imply causation. Furthermore, because the data was gathered via a convenience sample where multiple biases can form a threat. Among those is the self-report bias, those not willing to participate in a study will consequently not participate. So, these results only reflect those willing to participate in this study. It cannot be concluded this sample is representative for the whole population. Furthermore, the use of participant-gathering websites increases this effect. The platforms that were used are mainly used by other students, looking to recruit other participants. This results in a selection bias. An unknown proportion of the measures stems from these websites, inferring with generalizability of results. Again, this might have had an effect on the representativeness of the sample.

Lastly, the goal of the survey was to gather data from ‘knowledge workers’. However,

through the data-gathering strategies, no separation was made between ‘real’ knowledge

workers and others. Since everybody was able to fill in the survey, non-knowledge workers

likely participated too. In addition, the convenience sample has likely gained the attention of

students. Even though students might work more than eight hours per week (and were not

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eliminated from the data), they did not form the initial target group of the study. These might have had influence on the sample, resulting in less external validity.

A strength of the study is the large statistical power. Given the large sample size, sufficient power of results are assumed. Another aspect of the study contributing to this large power was the fact the survey was presented in Dutch and English. Even though for some questions, ‘official’ translations were used, interpretations of single questions might differ between languages. This might have had an influence in the answers reported.

Lastly, many significant results were found, contributing to existing knowledge. The variables in this study have not been combined in such extensive models before. The original goal of the study was to develop a model that combined both situational and personal characteristics. Not one model was found, but three. Even though the hypotheses were not answered, given the explorative scope of the research this is considered acceptable. Three models were developed in order to explain the complex field of blended working.

Future research

The current study has mainly focused on personal consequences of blended working.

Even though organizations have an increasing interest in employees’ private lives and their mental health, more research should be conducted towards the implications of blended working.

This study had formed a general image of how individual and motivational factors can and should be combined into explaining these effects. Future research should try to focus on specific aspects of this study, like the role of psychological needs.

Future research should also focus on organizational consequences of blended working.

Even if blended working would have only positive results for individual employees, if it does

not fit with business interests, it will likely not be implemented. To further expand our

knowledge of the effects blended working comes with, future research should focus on

variables like productivity and effectiveness. Especially because blended working is such a

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practical concept, more field-research should be conducted. If research will only focus on theoretical explanation of the concepts, it is not expected this will result in practical implementation.

Conclusion

The initial goal of this research was to explain the relationship between blended working

and work-life balance. After analysis, stress and social isolation were found to act more like

dependent variables than initially expected mediators. Consequently, the original hypotheses

were dropped, and focus shifted to development of new models. This resulted in three

moderated-mediation models were work-life balance, stress and social isolations were the

dependent variables. Significant indirect effects were found for autonomy and flexibility,

explaining the relationship between blended working and its consequences. Furthermore,

interactive effects of the need for autonomy were found. It can be concluded blended working

does not work for everyone. With a higher NfA come more positive consequences, implying

blended working works best for those having a high need for autonomy.

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