Mediator or Moderator? The Influence of Flow at Work on the Relationship between Resources and Organizational Outcomes

TABLE OF CONTENTS

1. Introduction

2. Theoretical Background
2.1. The Flow Phenomenon in the Working Context: A Short-Term Peak Experience
2.2. Job Resources and the Job Demands-Resources Model
2.3. The Influence of Job Resources on Work Processes and Outcomes
2.4. Do Resources Lead to Flow?
2.5. The Influence of Flow on Work Processes and Outcomes
2.6. The Role of Flow: Mediator or Moderator?

3. Hypotheses

4. Methods
4.1. Participants and Sampling Procedure
4.2. Measures
4.2.1. Demographical Information
4.2.2. Flow at Work
4.2.3. Task Variety
4.2.4. Social Support from Colleagues & Social Support from Supervisors
4.2.5. Autonomy
4.2.6. Feedback (from the Job itself)
4.2.7. Feedback (from Agents)
4.2.8. Occupational Self-efficacy
4.2.9. Subjective Well-being
4.2.10. Health
4.2.11. Work Performance

5. Results
5.1. Descriptive Analyses
5.2. Construct Validity of the Measurements
5.3. Resources and Organizational Outcomes (F1)
5.4. Resources and Flow (F2)
5.5. Flow and Organizational Outcomes (F3)
5.6. The Mediating Effect of Flow (F4)

6. Discussion
6.1. Results Regarding the Hypotheses
6.2. Excursus: Further Calculations

7. Limitations and Further Research

8. Practical Implications

9. References

10. List of Tables

11. List of Figures

12. Appendix

ABSTRACT

Within the scope of positive psychology one main construct is optimal experience or flow. Flow is a state in which people are so involved in an activity that nothing else seems to matter. Although Maslow introduced the term 'positive psychology' more than 70 years ago the research in this field is still sparse and conceptualizations as well as implications of flow are fragmentary and inconsistent. Therefore the present study among 117 white-collar employees investigates the relationships between flow at work, job resources (feedback, task variety, social support, autonomy and self-efficacy) and organizational outcomes (subjective well-being, work performance and health). In this concept it was assumed that resources and flow are predictors of organizational outcomes and that resources are also predictors of flow. Additionally, flow was studied as a mediator of the resources-outcomes relationship. Subjects completed online and paper-pencil-surveys including resources, flow and organizational outcomes. Analyses revealed that higher levels of job resources lead to higher levels of flow at work, as well as predicting well-being and work performance. In addition, employees who report frequent flow experience also report high levels of well-being and work performance. Furthermore, flow was found to be a mediator in the relationship of resources with subjective well-being and work performance. It is recommended that organizations should care more about resources and flow, since they predict well-being and work performance.

Keywords: Flow at work, job resources, work performance, well-being, health

Correspondence should be addressed to Univ.-Prof Dr. Christian Korunka, Institute of Applied Psychology; Work, Education & Economy, Faculty of Psychology; University of Vienna; Universitätsstrasse 7, 1010 Vienna, Austria. Email: Ch ristian.ko ru nka@ ..univie.ac. at

* The form of the reference selected shall apply to both genders.

1. INTRODUCTION

In recent decades, psychologists have almost exclusively focused on problems and mental illnesses. This exclusive attention to pathology concentrates on repairing damage and removal of negative states (Seligman & Csikszentmihalyi, 2000). Doing a web research Luthans (2002b) found about 375 000 articles on negative concepts like mental illness or depression but only about 1000 articles on positive concepts and capabilities of people. This shows a publication ratio of 375 to 1 between negatively and positively connoted publications.

Maslow (1954) introduced the term ‘positive psychology’ more than 70 years ago and stated that the behavior of a healthy person is less determined by negative emotions like anxiety or fear, and more by positive constructs like truth and fairness (Wright, 2003). However, the turn to a science of human strengths and optimal functioning gained no increasing interest until Martin Seligman’s call for a positive psychology (Luthans, 2002b; Seligman & Csikszentmihalyi, 2000). The so-called father of positive psychology stated that the major tasks of psychotherapy are less the fixing of negative states but rather the reinforcement of positive properties (Flowinstitute, n.d.). “Psychology is not just the study of pathology, weakness and damage; it is also the study of strength and virtue” (Seligman & Csikszentmihalyi, 2000, p. 7). He stated that the field of positive psychology is more about subjective experiences like well­being, contentment and satisfaction (relating to the past); hope and optimism (relating to the future); and flow and happiness (relating to the present) (Seligman & Csikszentmihalyi, 2000).

Even researchers in the field of occupational psychology have become increasingly more interested in optimizing positive emotions and experiences and therefore the study of positive psychology has drawn attention in many organizations (Llorens, Salanova, & Rodríguez, 2013; Luthans, 2002b; Schaufeli & Bakker, 2004). The ‘Continentale Studie 2013’ (Eng. Continentale study 2013) inspected the expectations and requests of employees in Germany and found that well-being and satisfaction move to the center of attention. Physical and mental health at work, as well as work-life-balance are getting more important and gain 6 increasing influence in a person’s decision for a workplace. Employees want to be supported in balancing their private and working lives, the working day should be flexible and relievingly designed and the health of the employees moves into focus (Continentale Krankenversicherung a.G., 2013). In addition, another trend forces the companies to be active. The term ‘war of talents’ is a prevalent topic in the media regarding the current labor market situation. Companies face a major challenge to find and keep qualified employees. For them, non-monetary incentives and soft factors are gaining importance (Bartscher & Stöckl, 2011). As a result, companies turn to occupational health management to address potential candidates or to keep qualified employees (Continentale Krankenversicherung a.G., 2013).

These trends are not solely prevalent in practice and are expanding into scientific theory. Luthans (2002a, 2002b) noted the need for a more concrete approach to positive psychology in organizational research, which he termed positive organizational behavior (POB). He defined POB as “the study and application of positively oriented human resource strengths and psychological capacities that can be measured, developed and effectively managed for performance improvement in today’s workplace”. (Luthans, 2002a, p. 59). The focus of positive organizational behavior is on strengths and values that are measurable and contribute to better performance. Constructs that are able to contribute to POB should be positive, measurable, capable of being developed, and associated with optimal performance. He identified five variables that fulfil the criteria for POB: self-efficacy, hope, optimism, subjective well-being, and emotional intelligence (Luthans, 2002a).

One of the positive phenomena receiving increasing attention is flow (Seligman & Csikszentmihalyi, 2000). Flow is a term first coined by Csikszentmihalyi (1975), and defined as a state in which people are so involved in an activity, that nothing else seems to matter. The experience is so enjoyable, that people will do it even at great costs. The concept of flow also seems to be in line with the earlier mentioned criteria for constructs that are able to contribute to POB. Flow is positive, measurable, capable of being developed as well as associated to 7 optimal performance (Fullagar & Kelloway, 2009). Researchers have identified this optimal experience in a wide range of activities, including sports (Jackson, Thomas, Marsh, & Smethurst, 1998, 2001), school (M. M. Wong & Csikszentmihalyi, 1991) or work settings (Bakker, 2005; Demerouti, 2006; Salanova, Bakker, & Llorens, 2006). For the organizational setting the Psychologist Arnold Bakker defined flow at work as a short-term peak experience that is characterized by absorption, work enjoyment and intrinsic motivation (Bakker, 2005, 2008). Previous research with regard to flow at work focused, among other things, on the influence of resources. Several empirical studies showed, that flow has a connection to resources like autonomy, social support, self-efficacy, clarity of goals, task variety or to the motivational potential score from Hackman and Oldham (1980) (Bakker, 2005; Demerouti, 2006; Fullagar & Kelloway, 2009; Salanova et al., 2006) as well as to organizational resources like well-being, satisfaction, work performance, health-related life quality or physical health (Bakker, 2008; Bryce & Haworth, 2002; Csikszentmihalyi & LeFevre, 1989; Fave & Massimini, 1988; Haworth & Hill, 1992; Hirao, Kobayashi, Okishima, & Tomokuni, 2012; Kobayashi et al., 2008).

Although organizational psychologists did a lot of research on resources, aspiring work outcomes and their effect in one’s working life, they did not reveal the influence of flow or other psychological states on this connection (Behson, Eddy, & Lorenzet, 2000). Studies that tried to combine the resource-outcome relation with flow are rare. Only one study tried to explain why and how the connection between resources and outputs is influenced by flow (Fullagar & Kelloway, 2009). Nevertheless, knowledge of its predictors and outcomes at work is important for the flow concept and its’ added value in a work setting (Demerouti, 2006).

To support further research of the concept and the connections of flow, the present study primarily aims to describe how the connection between resources and organizational outcomes is influenced by flow at work. In addition this paper will evaluate the direct relations between flow, resources and outcomes, as there already has been some research but with contrary 8 findings. Despite the advances in the research of flow, more empirical research is needed in order to clarify the influence of resources on flow at work. Existing studies already examined these connection but most of them only report correlations between flow and resources, which do not allow to tell if resources predict flow. In addition the relation of flow to organizational outcomes needs to be evaluated due to the fact that the work context needs more attention and to see if flow predicts these outcomes. The main objective of this study is to clarify if flow at work influences the relation between job resources and organizational outcomes in the role of a moderator or a mediator.

2. THEORETICAL BACKGROUND

2.1. The Flow Phenomenon in the Working Context: A Short-Term Peak Experience

The study of flow is a relatively new trend evolved from research in the field of positive psychology. Originally studied with artists, athletes, composers or dancers studies of the experience of flow have also been extended to the work context (Catley & Duda, 1997; Csikszentmihalyi, 1990, 1997; Csikszentmihalyi & LeFevre, 1989).

Csikszentmihalyi (1975) introduced the concept of flow and defined it as a state of mind or experience in which people are so involved in an activity that nothing else seems to matter. The experience itself is so enjoyable that people will do it even at great cost, for the sheer sake of doing it. It is a condition people feel in moments they describe as the best of their life, a condition where time flies by (Csikszentmihalyi, 1997; Flowinstitute, n.d.). According to Csikszentmihalyi (2001) some conditions need to be met to achieve flow. Nine core elements have been proposed in literature. The most important element that has been proposed is the balance between perceived high challenges for action and high personal skills. Other core elements are: a) the clarity of goals; b) a direct and unambitious feedback; c) a merging of action and awareness; d) an intense and focused concentration on action; e) a sense of control; f) the loss of reflective self-consciousness; g) a distortion of temporal experience and h) an autotelic

experience (Bryce & Haworth, 2002; Ceja & Navarro, 2012; Csikszentmihalyi, 1990; Jackson & Marsh, 1996; Llorens et al., 2013). This definition shows that the flow experience itself and its prerequisites are mixed together (Llorens et al., 2013). Additionally, Csikszentmihalyi’s studies have shown that people experience flow more often in their work than during their free time, where they spend most of the time with passive activities like watching TV or listening to music (Csikszentmihalyi, 2001).

illustration not visible in this excerpt

In Csikszentmihalyi's (1975) originalflow model of optimal experience or three channel model flow occurs when the actor perceives a balance between challenge and skill, regardless of whether the context was one of high or of low perceived challenge and skill. Experiences outside this channel are characterized by anxiety, when challenges exceed skills, or boredom, when skills exceed challenges (Clarke & Haworth, 1994; Ellis, Voelkl, & Morris, 1994; Engeser & Rheinberg, 2008). Figure 1 shows the original flow model of optimal experience. Based on

many experience sampling reports this model was reformulated by Csikszentmihalyi and Csikszentmihalyi (1988). The revised four channel model proposes, that flow is experienced only when challenge and skills are high and when they exceed the level that is typical for the day to day experiences of the individual (Ellis et al., 1994; Engeser & Rheinberg, 2008). Figure 2 shows the reformulated flow model of optimal experience.

Other theoretical models of flow, like the experience fluctuation or 16 channel model by Massimini and Carli (1988), the nine channel model by Clarke and Haworth (1994) or the eight channel model by Llorens, Salanova, and Rodriguez (2013) exist, too. While differing in some aspects they all have the common assumption that flow is experienced in the channel where challenge and skill are both high (Clarke & Haworth, 1994; Delle Fave & Bassi, 2000; Ellis et al., 1994; Engeser & Rheinberg, 2008; Llorens et al., 2013; Massimini & Carli, 1988).

Some researchers postulated slightly different definitions of flow. Ellis, Voelkl, and Morris (1994) defined flow as an optimal experience that is the consequence of a situation in which challenges and skills are equal. Such a situation also facilitates the occurrence of phenomena associated with flow-like positive affect, arousal and intrinsic motivation. Ghani and Deshpande (1994) focus on the total concentration in an activity and the enjoyment which one derives from an activity during flow. They postulated an optimum level of challenge in relation to a certain skill level that is important for the flow experience. Strongly inspired by Csikszentmihalyi, Lutz and Guiry (1994, cited by Bakker, 2005, p. 27) stated that flow is a state of mind experienced by people who are deeply involved in an event, object, or activity. They are totally immersed in this activity, time seems to stand still and nothing else seems to matter. These definitions indicate that the central aspects of flow might be enjoyment, intrinsic motivation and total involvement (Mäkikangas, Bakker, Aunola, & Demerouti, 2010).

Bakker (2005, 2008) took these three aspects into account and applied them to the work situation. He defined flow at work as a “short-term peak experience at work that is characterized by absorption, work enjoyment and intrinsic work motivation. Absorption refers to a state of 11 total concentration in which employees are totally immersed in their work. Time flies, and they forget everything else around them (Csikszentmihalyi, 1990, cited by Bakker, 2008, p. 401). Employees who enjoy their work and feel happy give a positive judgment about the quality of their working life (Veenhoven, 1984, cited by Bakker, 2008, p. 401).(...) Finally, intrinsic work motivation refers to the need to perform a certain work-related activity with the aim of experiencing the inherent pleasure and satisfaction in the activity (Deci & Ryan, 1985, cited by Bakker, 2008, p. 401). Intrinsically motivated employees are continuously interested in the work they are involved in (Harackiewicz & Elliot, 1998, cited by Bakker, 2008, p. 401)” (Bakker, 2008, p. 401).

As mentioned previously, one of Csikszentmihalyi’s core elements of flow is the balance between high challenges and high personal skills. Applied to the work situation this means that employees should experience flow particularly when their job demands match their professional skills (Bakker, 2005).

2.2. Job Resources and the Job Demands-Resources Model

One of the models used in this study is the job demands-resources (JD-R) model. The JD-R model has gained high popularity and can be used as a framework in research of employee well-being and performance in different types of occupations and organizations. Along with Karasek’s (1979) job demand-control model and Siegrist's (1996, 2002) effort-reward imbalance model, it is one of the leading job stress models (Schaufeli & Taris, 2014). Initially applied to burnout (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001), Schaufeli and Bakker (2004) presented an extended version of the JD-R model that includes work engagement as the positive counterpart of burnout.

At the heart of the original JD-R model lies the assumption that conditions at work can be classified into two broad categories: job demands and job resources (Demerouti et al., 2001). These work characteristics evoke two different processes. High job demands exhaust mental 12 and physical resources and hence may lead to health problems and burnout (exhaustion). Poorness or a lack of job resources prevent the accomplishment of goals, which may result in failure and frustration. The employee is not able to meet and reduce the negative influence of high job demands. This could lead to withdrawal from work, reduced motivation or reduced commitment (Disengagement) (Bakker, Demerouti, de Boer, & Schaufeli, 2003 a; Demerouti et al., 2001). Demerouti et al. (2001) defined job demands as physical, psychological, social, or organizational aspects of a job that require sustained physical or psychological effort and therefore stand in connection with physical and psychological costs. Examples are high work pressure, role overload or time pressure. Job resources refer to those physical, psychological, social, or organizational aspects of a job that help to achieve work goals, reduce job demands and associated costs, stimulate personal growth or development. Resources can be located at different levels. For example at the level of the organization, the personal level or the task level (Bakker et al., 2003a). Examples of job resources are social support from colleagues and supervisors, performance feedback, skill variety or job control (Demerouti et al., 2001).

As illustrated in figure 3, the revised job demands-resources model includes work engagement in addition to burnout and considers burnout as a mediator of the relation between job demands and health problems, and work engagement as a mediator of the relation between job resources and turnover intention (Schaufeli & Taris, 2014). Schaufeli and Bakker (2004) added a positive psychological state in the model. Similar to the earlier model, the revised model assumes that burnout results from high job demands and low job resources, but now burnout is treated as uni- instead of two-dimensional. The revised model emphasizes the motivational character of job resources. Following the effort-recovery theory from Meijman and Mulder (1998), job resources play an extrinsic motivational role, because they initiate the willingness to spend compensatory effort and thereby reduce job demands and foster goal attainment. Job resources also play an intrinsic motivational role, because they satisfy basic human needs for autonomy, relatedness and competence (Deci & Ryan, 2000). Through the achievement of goals or the satisfaction of basic needs job resources stimulate a positive work- related state of mind. This state fosters positive organizational outcomes like organizational commitment and performance. Therefore engagement is assumed to mediate the relation between job resources and organizational outcomes (Schaufeli & Taris, 2014).

illustration not visible in this excerpt

Figure 3. The revised Job Demands-Resources (JD-R) model (Schaufeli & Bakker, 2004)

The present study uses the motivational part of the job demands-resources model to explain the connection between job resources and organizational outcomes. According to Schaufeli and Bakker (2004) the availability of job resources stimulates a positive state of mind independently of job demands. In their reformulated JD-R model this positive state is work engagement. The present study explores if another positive state of mind such as flow can be evoked by job resources and foster positive organizational outcomes, too.

The next chapters will give an overview over the connection between job resources and organizational outcomes and the influence of flow in this connection.

2.3. The Influence of Job Resources on Work Processes and Outcomes

Researchers have long been interested in the preconditions of work motivation (Hackman & Oldham, 1980). Likewise, in the scope of positive psychology appears a renewed interest in the role of job resources in an employees work motivation process. As mentioned before, it is assumed that job resources have a motivational role. A considerable amount of studies have provided evidence for this motivational potential and showed the positive relationship between job resources and aspired positive work outcomes, like work engagement, well-being, health, or performance.

As already mentioned Demerouti et al. (2001) argued that according to the JD-R model high work resources increase motivation and lead to positive well-being and better performance at work. In their study with employees from three different occupations (human services, industry and transport workers) they could show this connection. Salanova, Llorens, Cifre, MartÍNez, and Schaufeli (2003) and Salanova, Agut, and Peiró (2005) also reported that organizational resources are important antecedents of work engagement, which in turn predict service climate, subjective well-being and group performance.

In their study among human service professionals, Bakker, Demerouti, and Verbeke (2004) showed that resources foster work engagement. On the one hand organizational demands are an important predictor of in-role performance, on the other hand organizational resources are an important predictor of extra-role performances. Similarly, Tierney and Farmer (2002) stated that organizational resources like task variety and supervisor support induce better working performance. Other researchers demonstrated the positive connection between organizational resources and performance at work. So Hackman and Oldham (1980) as well as De Jonge and Schaufeli (1998) revealed that job resources have a positive influence on performance and buffer the effect of job demands in stress situations.

In contrast, a lack of organizational resources has the opposite effect on motivation and performance (Wong, Hui, & Law, 1998) and impairs goal accomplishment and learning (Kelly, 1992). The absence of organizational resources also has some effects on health. Low social support (Leiter, 1991), low work control (De Jonge & Schaufeli, 1998) and poor performance feedback (Maslach & Jackson, 1986) result in burnout.

The last studies are in line with Hobfoll's (1989) Conversation of Resources (COR) theory. The model’s basic principle tells that people seek to obtain, retain, and protect resources. Stress occurs when resources that are threatened with loss, are lost, or when individuals fail to gain resources after resource investment. A central aspect of this theory is that individuals desire to acquire and sustain resources. In his surveys around COR-theory, Hobfoll, Johnson, Ennis & Jackson (2003) examined two types of resources: personal and psychosocial resources.

The present study will, in addition to organizational resources, focus on the personal resource self-efficacy. Personal resources are aspects of oneself that are linked to resilience. Self-efficacy showed his power as buffer against stress situations in many studies (Salanova et al., 2006). It has also a connection to better health, self-development, positive well-being and work performance (Bandura, 1999, 2001; Grau, Salanova, & Peiró, 2001; Tierney & Farmer, 2002). Tierney and Farmer (2002) showed in their study, that not only organizational resources like task variety and supervisor support result in better work performance but also that high self-efficacy beliefs lead to better performance at work. Another example that self-efficacy stands in connection to work outcomes is presented by Grau et al. (2001). In their study they showed that high levels of efficacy beliefs have a positive correlation with the employee’s well­being.

The connection between resources, especially organizational resources and health, are not quite clear. To take into account the job demands-resources model a second time (figure 3), it can be seen that the model does not support the connection between job resources, engagement and health. Empirical studies also focused on the effect of job demands on health and burnout. Demerouti, Bakker, Nachreiner, and Schaufeli (2000) explained that according to the JD-R model high job demands result in burnout and health problems.

But there also are some results that reveal that resources may play their part in health. Some researchers postulated that high job demands exhaust mental and physical resources which in turn leads to health problems and burnout (Demerouti et al., 2001). As mentioned 16 above, the absence of organizational resources has an effect on burnout (De Jonge & Schaufeli, 1998; Leiter, 1991; Maslach & Jackson, 1986). Bakker et al. (2003a) revealed that the organizational resources job control and participation are predictors of commitment and show a negative correlation to absence duration.

Nevertheless, the most promising results were published by Väänänen and his team. In their study they could prove that the organizational resources job autonomy, job complexity and coworkers’ support predicted sickness absenteeism. Job autonomy was found to be associated with long (4-21 days) and very long (>21 days) episodes of absence. Low job complexity was associated with long sickness absences and a lack of coworkers’ support increased the frequency of long sickness absenteeism (Väänänen et al., 2003).

2.4. Do Resources Lead to Flow?

Although the research on resources in connection with flow is limited, a couple of studies already pointed out that a positive association between work-related resources and flow does exist and that they strongly correlate with each other. Bakker (2008) showed that autonomy, social support and opportunities for professional development are positively associated with work-related flow. According to these findings, Demerouti (2006) revealed that motivating job characteristics are positively related to flow at work. In their study, motivating job characteristics were operationalized by the motivational potential score, a combined index including skill variety, task identity, task significance autonomy and feedback (Hackman & Oldham, 1980). A recent study from Mäkikangas et al. (2010) found a strong correlation between work resources and flow. In their longitudinal study they found a positive association between resources like autonomy, feedback, social support, opportunity for professional development, and coaching by the supervisor with flow.

Some researchers also stated that organizational and personal resources are significant antecedents of flow. Support for this assumption is shown by Bakker (2005). In his study among music teachers, organizational resources like autonomy, performance feedback, social support and supervisory coaching are important antecedents of flow experiences among teachers and their students. He found that teachers with high levels of autonomy, social support, supervisory coaching, and feedback at their workplace were most likely to experience flow. Fullagar and Kelloway (2009) postulated that task variety and autonomy are significant predictors of flow. An example that personal resources have an influence on flow was demonstrated by Salanova et al. (2006). Flow is facilitated over time when resources are sufficiently available. In their study personal resources like self-efficacy and organizational resources like social support and clear goals resulted in flow. In addition Salanova and her team hypothesized a reversed causal relationship between resources and work-related flow. They also stated that flow would predict future resources. Their data confirmed the reciprocal relationship between resources and flow and based on this the authors postulated an upward spiral of resources and flow.

2.5. The Influence of Flow on Work Processes and Outcomes

Considering that flow at work is a relatively new construct, only a limited number of studies have investigated the relationship with organizational outcomes. Existing studies have shown that flow and outcomes like health, performance and well-being are positively related.

There is constrained evidence that flow leads to better performance in domains like school or sports. Flow presented itself as a predictor of perceived success after competing in a match in a sample of older athletes (Jackson et al., 1998). Jackson et al. (2001) have shown a positive association between flow and perceived self-reported performance and an objective measurement of performance after a competitive event among athletes. In the school context Wong and Csikszentmihalyi (1991) published that flow is a predictor of progress in the school curriculum and intrinsic motivation has a positive impact on academic achievement with high school students.

Within the work context flow has been found to be positively related to in-role and extra­role performance (Bakker, 2008; Demerouti, 2006). According to Demerouti (2006) frequent flow experiences are beneficial for in-role and extra-role performances for employees high in conscientiousness. This is consistent with the later research of Bakker (2008). He showed that work-related flow is an important predictor for job performance. Accordingly, work enjoyment was significantly positively related to in-role performance, whereas intrinsic work motivation has significant correlations with extra-role performance. Studies of Eisenberger and his team published that positive moods are associated with better in-role performance of employees (Eisenberger, Armeli, Rexwinkel, Lynch, & Rhoades, 2001). In his later empirical study he could show that the balance between high skills and high challenges is related to positive mood, task interest and performance. Specifically, high skill and challenge were strongly associated to organizational spontaneity among achievement-oriented employees (Eisenberger, Jones, Stinglhamber, Shanock, & Randall, 2005).

In his papers about flow and positive psychology Csikszentmihalyi posted the assumption that flow leads to subjective well-being (Csikszentmihalyi, 1975, 1997). In fact several studies presented that the frequency of flow is associated with positive arousal in general. The more time people spend in the flow state, the more positive affect they experience (Fave & Massimini, 1988; LeFevre, 1988; Seongyeul, 1988). More specifically, Csikszentmihalyi and LeFevre (1989) postulated that people are happier and more satisfied when their skills match their demands. Positive affect and satisfaction are higher in persons who experience flow than in persons who do not. This is consistent with previous research that found flow to be associated with hedonic well-being, positive mood (Fullagar & Kelloway, 2009; Nakamura & Csikszentmihalyi, 2002) and long-term psychological well-being (Bryce & Haworth, 2002; Clarke & Haworth, 1994). In addition, Haworth and Hill (1992) showed that work enjoyment as a dimension of flow correlates with life satisfaction and enjoyment increases as the perceived skill-challenge-level increases.

Although literature of the influence of flow on health is sparse there are some studies, especially in Japanese surveys. Hirao, Kobayashi, Okishima, and Tomokuni (2011) discovered the relationship between flow experience and health-related quality of life. They demonstrated a significant correlation between the frequency of flow experience and both general health perception and social functioning. One year later Hirao and his team conducted a second study with elderly people at a nursing home and found that physical health was significantly higher in persons who experience flow while performing important daily activities. They suggested that ‘high-challenge-skilľ situations have a positive influence on physical health (Hirao et al., 2012). In addition, Kobayashi et al. (2008) reported a positive correlation of the frequency of absorption experience as a dimension of flow and the physical aspect of health-related quality of life.

Some European researchers explored the association between flow and health, too. By introducing the concept of flow, Csikszentmihalyi (1975) postulated that the withdrawal of flow enhances fatigue, somnolence, headaches and general reduced health. Accordingly, Young-Dal (2001) postulated an existing negative correlation between flow and indications of somatization like headaches, fainting and dizziness, spinal pain, sickness and shortness of breath. Pastor- Ruiz and his team (2012) also stated that flow has negative correlations with negative physical symptoms and positive associations to general health, emotional role functioning and vitality (Pastor-Ruiz, Benavides-Gil, Martinez-Zaragoza, Martin-del-Rio, & Solanes-Puchol, 2012).

Furthermore, the influence of positive states and emotions on health were examined. Salovey, Rothman, Detweiler, and Steward (2000) postulated that positive emotional states are associated with healthy patterns of response in cardiovascular activity and the immune system. They connote a direct relation between positive emotions and positive physiological states. In line with these findings Richman et al. (2005) found that frequent expression of positive emotions like hope and curiosity is associated with decreasing occurrence of diseases like high blood pressure, diabetes, or colds. Their results imply that positive emotions buffer illness.

2.6. The Role of Flow: Mediator or Moderator?

The main objective in this study is to examine the influence of flow in the complex cause-effect relationship between flow, resources and organizational outcomes. Is flow a mediator or moderator of the resource-outcome connection or does it have a different role? Before I start with a literature review of already conducted studies about the mediating or moderating effect of flow I want to precise the difference between a moderator and a mediator. This distinction is important to understand the applied analysis methods.

The properties of moderator and mediator variables are quite close but also distinguishable on many levels. A mediator variable accounts for the relation between a predictor or independent variable and a criterion or dependent variable. A mediator specifies how and why an effect or relation occurs and describes the psychological process that occurs to create the relation between two variables. Figure 4 shows the mediation model. A mediator analysis examines if the relation between a predictor and criterion variable is mediated by a third variable (Baron & Kenny, 1986).

A moderator variable is a qualitative or quantitative variable that has an influence on the direction or strength of the relation between two variables. So a moderator is a third variable that affects the correlation between an independent variable and a dependent variable. Figure 5 shows the model of an independent and dependent variable moderated by a third variable. Another characteristic of a moderator variable is that, unlike the predictor-mediator relation where the predictor is an antecedent of the mediator, moderators and predictors are on the same level. So moderating variables are independent variables, whereas mediator variables can be effects or causes, depending on the focus of the analysis. A moderator analysis examines the relationship between the predictor and the criterion variable affected by a third variable (Baron & Kenny, 1986).

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