Promoting Flow at Work through Proactive Personality: A Sequential Mediation Model with Evidence from Italian Employees

Abstract

In recent years, organizations have increasingly become aware of the importance of employee happiness as well as the role of HRM practices and personal resources in promoting well-being at work. Based on the Job Demand–Resources model, we investigated ways in which proactive personality may predict flow at work through sequential mediation via job crafting and work engagement. A total of 362 Italian employees completed an online questionnaire. The results showed a positive correlation between proactive personality, job crafting, and work engagement and flow at work. Additionally, proactive personality had a positive total effect on work engagement and flow at work. However, the significant effect on flow at work disappeared in favor of the sequential indirect effect. These results suggest that proactive employees experience flow at work through the mediating role of job crafting and work engagement. This paper contributes to scientific knowledge by filling a gap in the literature around the mechanisms which underly the relationship between proactivity and flow at work. Furthermore, it provides new evidence and new insights about the role of personal resources in promoting flow in the workplace. Our results here can provide practical implications for organizations.

1. Introduction

In the ever-changing world of work, a profound change is being experienced in the way people work. The workforce is often unmotivated and unengaged [1]; For this reason, Positive Psychology is increasingly used within organizations. Positive psychology examines the optimal processes that lead people to a condition of complete well-being [2]. As evidenced by the HEalthy and Resilient Organizations (HERO) model, a healthy and resilient organization combines three key elements that interact with each other: organizational resources and practices, employee well-being, and organizational results [3]. In other words, organizations should provide their employees with job resources that can directly and indirectly address employee well-being and performance [4,5,6].

However, HRM practices are not always able to adequately meet each employee’s needs. Therefore, employees should motivate themselves by managing their personal resources to meet organizational demands. Among personal resources, proactivity may be playing an even more important role in recent times [7]. Consequently, the present study focuses on how and why proactive personality may promote job crafting, work engagement, and, flow at work. In other words, the present study aims to explain the positive effects of proactive personality on flow at work through sequential mediation via job crafting and work engagement. We expected that proactive people would model their work (job crafting) and feel fully immersed in their work (work engagement) in order to increase their state of harmony and control over their work (flow at work).

A graphical representation of the hypothesized model is depicted in Figure 1.

This study may contribute to previous research and literature in several ways. First, it could fill a literature gap around the relationship between proactivity and flow at work, providing new evidence and new insights. Second, it may expand the previous literature concerning the role of personal resources (proactive personality, job crafting and work engagement) in promoting flow at work, based on the Job Demands–Resources (JD-R) model. Third, it explains why proactive personality is related to flow at work via job crafting and work engagement in a sequential mediation model.

1.1. Proactivity and Flow at Work Dimensions

According to the JD-R model, all job characteristics can be categorized as either job demands or job resources [8] Specifically, job demands are generally the most important predictors of such outcomes as exhaustion, psychosomatic health, and strain [9,10]. Conversely, job and personal resources are generally the most vital predictors of work enjoyment, motivation, and engagement [11,12].

Among personal resources, proactivity has been studied extensively in the previous literature, as it is a resource capable of promoting effective lifelong self and relational management [13]. Proactive behavior is defined as “taking initiative in improving current circumstances or creating new ones” [14]. Proactive behaviors are self-initiated, future-oriented and involve taking control to bring about change [15]. Proactivity is particularly useful for predicting the behavior of workers who are able to change their work according to their resources [16]. An important facet of proactivity that emphasizes individual difference is proactive personality, i.e., a stable disposition to control a situation by the tendency to initiate change [17]. Proactive personality is a particularly useful resource for dealing with continuous work transitions, and such an individual will feel more responsible for developing their potential and their professional growth [18,19,20]. Thus, proactive personality may lead employees to feel more positive, i.e., that they are flourishing.

Applied to work, flow describes “the enjoyment inherent in the task that was intrinsically motivating” rather than deriving from an extrinsic reward [21]. More recently, Bakker and van Woerkom [22] defined flow at work as “a state of consciousness where people become totally immersed in an activity and enjoy it intensely”. Flow at work is a short-term peak experience and this “autotelic” state may change from moment to moment [21]. From an operationalization point of view, flow at work is composed of three dimensions [23]: absorption, i.e., concentration and immersion in the activity; enjoyment, i.e., a positive and happy state due to the quality of the activity; and intrinsic motivation, i.e., the personal and subjective fulfilment that leads workers to initiate or carry on with the activity. Individuals experiencing flow at work indicate that their sense of time disappears because they are completely focused on what they are doing. The experience is enjoyable, and thus people are intrinsically motivated to continue with what they are doing [24]. With their activity being rewarding, employees perform it with the aim of taking pleasure and satisfaction from it [24].

Despite the importance of proactive personality and flow at work in the positive psychology framework [2], to the best of our knowledge no previous studies have investigated the relationship between these variables. The previous literature concerning personal resources as antecedents of flow at work is quite scarce. As a matter of fact, only optimism [25] and self-efficacy have been identified as predictors of flow at work [26]; proactive personality has not yet been tested as an antecedent, although, in line with the JD-R model scholars [27,28] have suggested that personal initiative, i.e., proactivity, may be a precondition of flow.

For the first time, therefore, we aimed to empirically test whether proactive personality is an antecedent of flow at work. People with high levels of proactivity can be expected to better experience a pleasant state of immersion in their work. Therefore, we propose the following hypothesis:

Hypothesis 1.

Proactive personality is positively related to flow at work.

1.2. Proactive Personality and Job Crafting

High levels of proactive personality may impact autonomy and responsible work behavior, both of which are able to promote employees’ ability to adjust their jobs to their needs and resources. In other words, proactive employees may be able to redesign their work, i.e., using job crafting, defined as modalities that can be changed while always remaining within the boundaries of specific job duties [29]. Job crafting is initiated by workers and constitutes a form of proactive behavior at work [30]. Job crafting refers to behaviors introduced autonomously by the worker and aimed at bringing about a change in the work environment, aligning one’s work with one’s preferences, motivations, and passions [31]. In other words, it allows individuals to shape their identity and their work roles through the personal construction of their way of working and consequently of their work [31]. From the JD-R model perspective [32], job crafting involves such employee changes in order to balance job demands/resources with their abilities. It comprises four dimensions: (1) increasing structural job resources; (2) increasing social job resources; (3) increasing challenging job demands and (4) decreasing hindering job demands. Increasing structural job resources concerns the active opportunity to improve one’s career or job autonomy; increasing social job resources refers to the ability to create a positive support network. Increasing challenging job demands refers to active behavior for goal achievement; finally, decreasing hindering dimensions concerns job demands that get in the way of workers’ personal growth. In line with several previous research studies [4,33], we focused only on the positive and proactive dimensions of job crafting, excluding “decreasing hindering job demands” as this requires more passive adjustments to job situations. In sum, crafting behavior represents a highly promising strategy through which to foster positive behaviors and bring about change.

Hence, job crafting proactively seeks to adjust workers’ working conditions to their needs and capabilities. Proactive employees strive for harmony with their work environment [15,34]. Previous studies have investigated the relationship between proactive personality and job crafting, showing a positive association [35]. Furthermore, studies [4,36] have suggested that having a proactive personality is an important antecedent of job crafting as proactive employees are prone to increase job resources and challenging job demands.

Employees with high proactivity are more involved in their own work and are able to shape their work according to their resources. For this reason, following the JD-R model and previous literature, we hypothesize that:

Hypothesis 2

. Proactive personality is positively related to job crafting.

1.3. Job Crafting and Work Engagement

Prior studies have pointed out that job crafting is strictly related to both job performance and positive states at work, including work engagement [4,32,37].

Work engagement is a multidimensional motivational construct that is characterized by vigor, dedication and absorption [38]. Vigor refers to high levels of energy and mental resilience while working as well as to the willingness to invest effort in one’s work. Dedication is characterized by intense work involvement and comprises feelings of inspiration, pride, enthusiasm, and challenge. Finally, absorption refers to being fully concentrated and happily engrossed in one’s work. Work engagement shows that engaged employees have a sense of energetic and effective connection with their work activities and see themselves as capable of managing the demands of their job [39].

Several studies have shown that an environment with a good organizational climate, i.e., a good balance of job demands and job resources, facilitates work engagement [39]. A previous study investigating managers and executives of a Dutch telecommunications company found that when working in an environment with good work resources, the commitment continued for a period of one year [40]. Increases in work resources (i.e., autonomy, learning opportunities) can be excellent predictors of increases in job resources, such as work engagement, and can bring benefits to the organization, such as reduced employee absenteeism. According to the JD-R model, increasing work resources may lead to improved organizational results such as work engagement and job satisfaction [41,42].

In a meta-analysis study [43], job crafting was found to describe a set of proactive behaviors through which individuals alter their behaviors and work environments. Hence, it is believed that workers’ level of job crafting may be associated with greater work engagement, which is associated with several positive life outcomes. Many studies have demonstrated that job resources, including job crafting, promote engagement. For example, a longitudinal study showed a positive relationship between job crafting and work engagement [44]. Another study [45] showed that employees who score highly on work engagement actively craft their work both physically (i.e., looking for challenges) and relationally (i.e., looking for resources). In line with previous studies and the JD-R model, we hypothesize that:

Hypothesis 3.

Job crafting is positively related to work engagement.

1.4. Job Crafting and Work Engagement as Mediators between Proactive Personality and Flow at Work

A large body of previous results and meta-analysis [41,46] has clearly ascertained the positive role of engagement in promoting several outcomes, including performance, attitudes (i.e., job satisfaction), and individual well-being (i.e., mental health). Only two recent studies focused on the relationship between work engagement and flow at work. The first study [47] considered three dimensions of work engagement as predictors of flow at work, suggesting that only the dedication dimension had a positive and significant effect. Another study [48] reported a positive effect of flow at work as a mediator in the relationship between the calling of employees, i.e., ability to fulfil one’s core values at work, and work engagement.

The JD-R model may offer a good perspective from which to explain this relationship. In line with previous scholars [4,49], employees with high levels of engagement tend to feel positive emotions at work (for instance, happiness, joy and enthusiasm), subsequently achieving good performance. Furthermore, engaged employees feel fully dedicated and enthusiastic within the organization [38]. Following this perspective, we propose that work engagement leads to experiencing a state of flow at work. Thus, in line with previous studies and the JD-R model, we hypothesize that:

Hypothesis 4

. Work engagement is positively related to flow at work.

Using the JD-R model, a recent meta-analysis [41] identified five types of resources as antecedents of engagement: social resources, job resources, organizational resources, developmental resources, and personal resources. Among personal resources, resilience, self-efficacy, optimism, learning, and proactivity showed significant associations with work engagement. Personal resources can be used to manage job demands in order to improve performance [50,51] and create positive emotions at work. With respect to the performance domain, a previous study [4] showed that proactive personality leads to work engagement via job crafting. However, this model has not yet been tested on positive states such as individual well-being, satisfaction, and flow at work. Therefore, and for the first time, we investigated the effect of proactive personality on flow at work, using job crafting and work engagement as mediators.

Specifically, we expected that proactive people would be more prone to redesign their work through job crafting [4,36]. Consequently, job crafting would tend to improve the level of work engagement, as it drives employees to mobilize the work resources necessary to face job challenges [45]. Finally, engaged employees were expected to be more likely to have a pleasant state of mind when carrying out their work [52,53,54]. In sum, we propose the following hypothesis:

Hypothesis 5.

Proactive personality is indirectly related to flow at work via job crafting and work engagement in a sequential mediation.

2. Materials and Methods

This study is a part of a research project entitled “Promoting flow at work: the positive role of personal resources”, approved by the Ethics Committee of Lumsa University of Rome.

The research protocol consisted of an online questionnaire on Google form. Employees were personally contacted by a researcher according to the proximity, availability, and easy accessibility criteria of snowball convenience sampling. On the first page of the online questionnaire, we inserted an informed consent notice in which we specified that all participation was free and voluntary and that data would be utilized in an aggregated manner.

2.1. Sample

Participants were selected through a non-probabilistic sampling according to the following inclusion criteria: (a) age ≥ 18 years old; and (b) employed in a private, public, or non-profit organization. Therefore, the exclusion criteria were: (a) age < 18 years old; and (b) being self-employed. The sample consisted of 362 Italian employees; 52.5% of participants were female, while 47.5% were male. In terms of age, 15.2% were between 18 and 25 years old, 19.6% between 26 and 35 years old, 13.3% between 36 and 45 years old, 28.7% between 46 and 55 years old, 21.5% between 56 and 65 years old, and 1.7% more than 65 years old. Regarding education, 57.8% had a university degree, 39.2% had a high school diploma, and the remaining 3.0% had only completed compulsory education.

Employees worked in private (55.5%), public (43.4%), or non-profit (1.1%) organizations. In terms of organizational size, 39.3% of respondents worked in small organizations, 13.3% in medium organizations, and 47.5% in large organizations. Furthermore, the average organizational tenure was 14 years (SD = 11.96). Finally, regarding their contract type 80.7% of participants were permanently employed and 19.3% were temporary employees.

2.2. Measures

Proactive personality was assessed using the Italian version [55] of the Proactive Personality Scale (PPS) [56]. This unidimensional scale measures personal initiative to take action toward an aim. It is composed of ten items on a scale ranging from 1 (absolutely false) to 7 (absolutely true). In the present study, Cronbach’s alpha reached 0.87.

Job crafting was evaluated using the Italian version [57] of the Job Crafting Scale (JCS) [4]. The Italian version measures three positive factors: increasing structural job resources, increasing social job resources, and challenging job demands. Furthermore, it is able to provide a total score for job crafting. The Italian version of the measure is composed of thirteen items on a frequency scale ranging from 1 (never) to 7 (always). In the present study, Cronbach’s alpha reached 0.89.

Work engagement was measured using the Italian validation [58] of the short version of the Utrecht Work Engagement Scale (UWES-9) [59], which is composed of nine items with a frequency scale ranging from 0 (never) to 6 (always). In the present study, Cronbach’s alpha reached 0.94.

Flow at work was assessed using the Italian version [60] of the WOrk-reLated Flow inventory (WOLF) [39]. Respondents were asked to answer thirteen items about their work experience during the last two weeks on a frequency scale ranging from 1 (never) to 7 (always). In the present study, Cronbach’s alpha reached 0.93.

2.3. Statistical Analyses

First, we assessed the confirmatory factor analysis (CFA) of our hypothesized four-factor model (M1) by comparing it to all alternative measurement models. Each model was evaluated by the following fit indices: root mean square error of approximation (RMSEA), standardized root mean squared residual (SRMR), comparative fit index (CFI), and Tucker Lewis Index (TLI). RMSEA and SRMR declare that a good fit is approximately equal to or lower than 0.08, while CFI and TLI suggest an acceptable fit model of equal to or greater than 0.90. Each alternative model was compared to M1 via the significance of the χ² difference (Δχ²) with respect to the degrees of freedom difference (Δdf).

Second, we tested our sequential mediation model via structural equation modeling (SEM) using a partial disaggregation model [61]. This technique suggests using two or more indicators for each latent variable rather than for all items in order to reduce the number of iterations needed to reach an identified model (Little et al., 2002). Therefore, we created two parcels, i.e., item aggregations, to measure proactive personality, while the other three latent variables were measured by their own dimensions. Specifically, job crafting was measured by increasing structural and social job resources along with challenging job demands. Work engagement was measured by vigor, dedication, and absorption. Flow at work was measured by absorption, enjoyment, and intrinsic motivation.

We tested the significance of the total, direct, and indirect effects of proactive personality on flow at work via bootstrap method [62] with 5000 resampling and corrected 95% confidence intervals (CI).

3. Results

Table 1. Descriptive statistics and correlations. ** p < 0.01. Cronbach’s alpha for both total score and dimensions are reported diagonally.

	Mean	SD	1	2	3	4	5	6	7	8	9	10	11	12	13
1. PPS	3.71	0.66	0.87	0.53 **	0.24 **	0.50 **	0.49 **	0.44 **	0.46 **	0.49 **	0.50 **	0.24 **	0.32 **	0.27 **	0.32 **
2. JCS	4.73	1.10		0.89	0.83 **	0.78 **	0.91 **	0.49 **	0.51 **	0.50 **	0.54 **	0.38 **	0.47 **	0.37 **	0.46 **
3. Structural resources	5.40	1.18			0.85	0.39 **	0.75 **	0.52 **	0.50 **	0.51 **	0.55 **	0.38 **	0.50 **	0.33 **	0.46 **
4. Social resources	3.77	1.50				0.79	0.53 **	0.29 **	0.31 **	0.30 **	0.33 **	0.19 **	0.25 **	0.18 **	0.23 **
5. Challenging demands	4.96	1.27					0.83	0.45 **	0.48 **	0.46 **	0.50 **	0.38 **	0.44 **	0.42 **	0.48 **
6. UWES-9	3.70	0.89						0.94	0.92 **	0.94 **	0.93 **	0.54 **	0.76 **	0.61 **	0.73 **
7. Vigor	3.88	0.94							0.82	0.82 **	0.76 **	0.49 **	0.72 **	0.54 **	0.66 **
8. Dedication	3.72	0.91								0.76	0.82 **	0.53 **	0.67 **	0.59 **	0.68 **
9. Absorption (UWES)	3.49	1.03									0.90	0.50 **	0.72 **	0.58 **	0.69 **
10. WOLF	4.57	1.30										0.93	0.81 **	0.90 **	0.90 **
11. Absorption (WOLF)	4.77	1.36											0.86	0.64 **	0.56 **
12. Enjoyment	4.92	1.56												0.96	0.73 **
13. Intrinsic motivation	4.12	1.53													0.86

Notes. PPS = Proactive Personality Scale; JCS = Job Crafting Scale; UWES = Utrecht Work Engagement Scale; WOLF = WOrk-reLated Flow inventory. ** p < 0.01.

shows the means, standard deviations (SD), and correlations for the dimensions (in lowercase) and the scales’ total score (in uppercase).

From the total scores of the scales, Table 1 illustrates positive and significant correlations among proactive personality, job crafting, work engagement, and flow at work. For the dimensions, Table 1 shows that each dimension was mostly correlated with its own scale. As a matter of fact, increasing structural and social job resources and challenging job demands was mostly correlated with job crafting. In the same way, vigor, dedication, and absorption (UWES) were mostly correlated to work engagement. Finally, the three dimensions of WOLF (absorption, enjoyment, and intrinsic motivation) were mostly correlated with flow at work.

Second, we compared a four-factor hypothesized CFA model (M1) with each latent variable measured by its own items to all possible alternative models. Specifically, we created alternative models (from three-factor models to a one-factor model) combining items of different latent variables. The comparison via Δχ² indicated that all alternative models showed a fit significantly worse than M1 (

Table 2. Comparison between M1 and alternative CFA models.

Model	χ2	df	M…-M1	CFI	NNFI	RMSEA	SRMR
M1	2813.52	939	-	0.869	0.856	0.082	0.071
M2	3145.42	942	331.90 **	0.728	0.714	0.100	0.081
M3	3355.43	942	541.91 **	0.702	0.687	0.104	0.098
M4	3502.63	942	689.11 **	0.684	0.668	0.108	0.117
M5	3560.82	942	747.30 **	0.677	0.660	0.109	0.094
M6	3796.93	942	983.41 **	0.648	0.630	0.114	0.119
M7	3243.59	942	430.07 **	0.716	0.702	0.102	0.080
M8	3976.15	944	1162.63 **	0.626	0.608	0.117	0.106
M9	4387.86	944	1574.34 **	0.575	0.554	0.125	0.130
M10	3878.22	944	1064.70 **	0.638	0.620	0.115	0.113
M11	4158.20	944	1344.68 **	0.603	0.584	0.120	0.116
M12	4700.17	945	1886.65 **	0.537	0.515	0.130	0.127

Notes. M1: Hypothesized four-factor model; M2: three-factor model (F1: personal proactivity + job crafting; F2: work engagement; F3: flow at work); M3: three-factor model (F1: personal proactivity + work engagement; F2: job crafting; F3: flow at work); M4: three-factor model (F1: personal proactivity + flow at work; F2: job crafting; F3: work engagement); M5: three-factor model (F1: job crafting + work engagement; F2: personal proactivity; F3: flow at work); M6: three-factor model (F1: job crafting + flow at work; F2: personal proactivity; F3: work engagement); M7: three-factor model (F1: work engagement + flow at work; F2: personal proactivity; F3: job crafting); M8: two-factor model (F1: personal proactivity + job crafting + work engagement; F2: flow at work); M9: two-factor model (F1: personal proactivity + job crafting + flow at work; F2: work engagement); M10: two-factor model (F1: personal proactivity + work engagement + flow at work; F2: job crafting); M11: two-factor model (F1: job crafting + work engagement + flow at work; F2: personal proactivity); M12—one-factor model (all items loaded on F1). ** p < 0.01.

). Fit indices of M1 were acceptable (RMSEA and SRMR) or very close (CFI and TLI) to cut-off criteria; therefore, the model may be considered globally adequate. Although latent variables shared certain conceptual matters (for example, proactive personality and job crafting share several features including personal initiative and active behaviors, while work engagement and flow at work share features such as positive emotions and work absorption), they were well distinguished empirically. In other words, the CFA results did not show issues regarding items overlapping.

In order to test sequential mediation hypotheses, we performed a model via SEM in which proactive personality was indirectly related to flow at work via job crafting and flow at work. The sequential mediation model, reported in Figure 2, reached good fit indices: χ² (df = 38) = 104.53, p < 0.001, CFI = 0.964, NNFI = 0.948, RMSEA = 0.086, SRMR = 0.029. First, the results showed that proactive personality had a positive and significant total effect on flow at work (β = 0.37 with 95% CI between 0.26 and 0.49, supporting H1). Second, the effects of proactive personality on job crafting, β = 0.68 with 95% CI between 0.56 and 0.78, as well as the effect of job crafting on engagement, β = 0.47 with 95% CI between 0.27 and 0.63, were significant and positive. These results support H2 and H3, respectively.

Furthermore, the total effect of proactive personality on work engagement was positive and significant (β = 0.52 with 95% CI between 0.40 and 0.63) as were its direct (β = 0.20 with 95% CI between 0.04 and 0.39) and indirect (β = 0.32 with 95% CI between 0.19 and 0.44) effects via job crafting. Thus, job crafting partially mediated the relationship between proactive personality and work engagement. Moreover, the total effect of job crafting on flow at work was positive and significant at β = 0.53 with 95% CI between 0.35 and 0.70, as was its indirect effect (β = 0.40 with 95% CI between 0.23 and 0.56) via job crafting. However, the direct effect of job crafting on flow at work was not significant (β = 0.12 with 95% CI between -0.04 and 0.31), suggesting a total mediation by work engagement.

Finally, the sequential mediation model suggested that the indirect effect of proactive personality on flow at work via job crafting and work engagement was positive and significant, with β = 0.27 and 95% CI between 0.16 and 0.38, while the direct effect, β = −0.16 with 95% CI between −0.37 and 0.09, was not significant, suggesting a total mediation. Therefore, job crafting and work engagement fully and sequentially mediated the relationship between proactive personality and flow at work, supporting H4.

4. Discussion

Over the last several decades, organizations have become increasingly interested in employees’ well-being, as this can bring benefits to the organization [2]. This study investigated the relationship between proactive personality and flow at work through job crafting and work engagement using JD-R as a model. The results supported our hypotheses: proactive personality was indirectly related to flow at work via job crafting and work engagement via sequential mediation. Employees with a proactive personality were more likely to create their own work, such that they engage and feel as though they are flourishing. These results contribute to previous studies while filling gaps in the literature concerning flow at work overall. Indeed, we consider flow at work to be an important outcome in the workplace, one which may be derived by positive organizational as well as individual dynamics. From an individual point of view, our results suggest that proactive personality does not directly influence a state of well-being, as flow at work does; rather, its positive effect is passed along through other resources. In line with the JD-R model, personal resources, i.e., proactive personality, contributes to increased job resources, i.e., job crafting and engagement, in order to manage organizational demands [4]. Indeed, only through job crafting and subsequently through work engagement is there an increase in flow at work.

Furthermore, our results suggest practical implications in order to promote flow at work through personal and job resources.

4.1. Theoretical Implications

Our results may shed light on previous studies and the wider literature in several ways.

First, few previous studies have investigated the predictive role of personal resources, i.e., autonomy and internal locus of control and optimism, on flow at work [8,42]. Furthermore, no studies have yet investigated the association between proactive personality and flow at work. Therefore, a first contribution is to fill this literature gap. In line with the JD-R model, we identified that proactive personality was significantly and positively related to flow at work. In other words, personal resources related to taking initiative, including proactive behaviors, may be considered as a precursor of flow at work [27]. These results are consistent with previous studies pointing out that proactivity is an excellent predictor of positive working attitudes [14].

Second, our results support the importance of resources, including proactive personality, job crafting and work engagement, in predicting flow at work. A meta-analysis [63] highlighted that job crafting is consistently and positively related to proactive personality and behavior. Furthermore, previous studies have shown that job crafting positively predicts work engagement [12,36]. These results are consistent with a study which has already investigated the sequential relationship between proactive personality, job crafting and work engagement, finding positive associations [32]. In line with the JD-R model, we found that employees who manage to optimize work demands using work resources are able to flourish. Therefore, the present study may provide new insights about the JD-R model that may be used to explain well-being and positive states at work.

Third, the present paper extends previous studies in order to explain the psychological mechanisms by which proactive personality is able to activate a positive mental state at work. Proactive personality can act as a stimulus for job crafting, which in turn can play a motivating role in feeling more engaged in one’s own work [4,37,64] with a consequent increasing of flow at work. In line with a previous study [32], our sequential mediation model suggested that the dynamic process from proactivity to outcomes is not directly due to the personality itself, but rather to its ability to influence employees’ behaviors. Indeed, our results showed an indirect effect of proactive personality on flow at work via, sequentially, job crafting and work engagement.

4.2. Practical Implications

The practical implications of our results may concern both the organization itself and employees, with the aim of adequately managing the relationship between job demands and resources.

First, our results suggest that proactive employees are able to model demands and work resources and feel more involved by obtaining higher scores on the flow at work. However, having a proactive personality is a rather stable trait, and there are not many practical implications for how to improve it even though it is desirable to stimulate employees to create their own working methods. A first suggestion concerns the opportunity to assess proactive personality in recruitment, as it is positively related to job satisfaction and career success [65,66]. Furthermore, regular organizational surveys asking employees how they handle job requests and what resources they put in place might help them and promote personal activation.

Other interventions may be addressed to the promotion of job crafting and work engagement, which lead to employees feeling that they are flourishing.

For job crafting, HR managers can provide specific interventions. In line with the JD-R theory, results for job crafting interventions showed the possibility of stimulating employees’ behavior related to adapting their job demands and resources [67]. Job crafting interventions could be preceded by training aimed to increase employees’ awareness of the possibility of their influencing, i.e., crafting, their job characteristics. Practically speaking, to foster job crafting, a possible strategy regards organizational communication at different levels [68].

First, interventions at one level should be made involving senior management using a structural conversation on job crafting with employees to include it as a daily routine. This strategy could involve the facilitation of direct communication between employees and managers about the kinds of work activities involved. For example, HRMs may request that employees optimize their resources and challenges at work through customized reports. Furthermore, organizations can use surveys to find out whether employees experience sufficient opportunities to craft their work activities [31].

Second, interventions at another level should be implemented through senior management giving more feedback at work, aiming to stimulate employees to increase their job resources as a way of empowering the job crafting practice [68]. This kind of feedback intervention has the purpose of pushing employees to think about when, where, and how to craft their work environment.

From a work engagement point of view, direct communication may indirectly promote employees’ positive, fulfilling, and affective–motivational state of work-related well-being. Indeed, improving both internal and external communication may promote a good organizational climate, which can influence work engagement [69,70], well-being, and positive states (i.e., flourishing).

In addition, HRM practices can be critical in improving job crafting and work engagement. For example, organizations may stimulate team-building activities in order to promote team knowledge sharing, which is positively related to both job crafting and work engagement [71].

As the results reveal that work engagement can have a positive relationship with flourishing, the mobilization of this resource should be a significant component of individual interventions for employees. From this perspective, work engagement could be enhanced to provide more job resources such as autonomy, social support and feedback [70] through training programs and coaching tailored to workers’ individual needs [72]. Generally speaking, interventions aimed at increasing resources such as job crafting could help employees to become more engaged, in accordance with the JD-R model, and to flourish in their work environment.

4.3. Limitations and Future Research

There are some limitations worthy of being discussed and with respect to which we provide potential suggestions for future studies.

First, the use of cross-sectional data does not allow us to fully support the causality between proactivity, job crafting, work engagement, and flow at work. However, we believe that the predominant direction of influence among the variables considered follows the direction proposed by previous studies based on the JD-R model [4].

Second, the use of a self-report questionnaire may include a potential single-method bias. Indeed, to decrease the bias due to social desirability, we requested that participants complete an online questionnaire, ensuring anonymity. However, future studies will be able to resume the same study with a different method of measurement, such as, for example, a longitudinal study or daily diary study of what employees do during their working day.

A third limit concerns the sample as well as non-random (snowball convenience) sampling. There are more employees who work in private rather than public organizations; however, the sample showed good homogeneity between females and males, as well as with regard to age and education. Although our sample size was not very large, several authors [73,74,75,76] consider 150 respondents a reasonable sample size of for testing hypotheses via SEM.

Furthermore, the generalization of the results may not be applicable in other countries because the questionnaires were collected only from Italian employees. Hence, future studies could individually focus on different sectors while expanding the research to other countries.

Finally, future research in large samples might test the generalizability of these results in representative samples, or include other measures of personality and try to expand the knowledge of their effects on promoting flow at work.

5. Conclusions

There is a growing focus on employee well-being and what organizations can do to improve flow at work. Based on the JD-R model, the present paper emphasized the importance of proactive personality in helping employees to effectively respond to job requests using job crafting and work engagement in order to feel the enjoyment inherent in their activity.