Career Calling and Task Performance: The Moderating Role of Job Demand

Abstract

The Work as a Calling Theory (WCT) predicts that career calling fosters job performance. A quantitative summary of previous work supports this prediction and shows that the relation between calling and job performance is moderate in size (ρ = .29, K = 11, N = 2286). Yet, the environmental conditions that modulate this relation are completely unknown. According to an interactionist perspective, we argue that calling may predict performance only when job demand is low. Results of a multisource study on salesmen and managers dyads (N= 965) partially supported this prediction. We observed that highly demanding work environments, characterized by pressure to perform, high workload, and unachievable deadlines, suppress the positive relation between calling and self-reported performance. Job demand directly impairs performance and suppresses the positive effect of career calling. Theoretical and practical implications of these results are discussed.

Keywords

career calling task performance job demand moderation multi-level

In industrialized contemporary societies, working for a promotion or mere compensation is not sufficient: Employees see their job as an opportunity to fulfill an increasingly larger set of social and psychological needs (Casey, 1995), such as building a positive work identity (Miscenko& Day, 2016), deriving a sense of meaning (Rosso et al., 2010), or pursuing a calling (Thompson & Bunderson, 2019). Matching the neoclassical and modern traditions, we conceptualize calling as a way to approach work in which individuals feel a strong passion for their job, which becomes central to their identity, pervasive and worth sacrificing other areas of life, and which transcend their selves and make them feel that they have a purpose in life and that they are useful to the society or the greater good (Dik & Duffy, 2009; Dobrow&Tosti-Kharas, 2011; Vianello et al., 2020). Employees with higher callings derive increased meaningfulness and motivation from their work (Dik et al., 2008; Duffy et al., 2017). Calling has many beneficial outcomes, such as increased well-being (Conway et al., 2015; Dalla Rosa & Vianello, 2020; Goštautaitė et al., 2020), job satisfaction (Duffy et al., 2011), and organizational citizenship behavior (Park et al., 2016).

Calling and Job Performance in the Work as a Calling Theory

The positive relation between calling and performance is predicted by the Work as a Calling Theory (WCT; Duffy et al., 2018), which proposes a complex set of predictors and outcomes of perceiving and living a calling at work. The WCT starts its chain of predictions from perceiving a calling, which is the first step toward experiencing the positive effects of living out a calling at work: job satisfaction and job performance. Once people perceive they have a calling toward a job or a career, the extent to which they will live it out depends on the degree to which they feel fit with their work environment, which in turn increase work meaning and career commitment. According to the WCT, the mediation of person–environment fit in the relation between perceiving a calling and work meaning and career commitment is moderated by the level of motivation that people have toward pursuing their calling (Calling Motivation), the extent to which they change the relational, behavioral, and cognitive engagements involved in one’s work (Job Crafting), and the extent to which they feel supported, assisted, and encouraged by their work environment (Organizational Support). The theory also states that, if people have access to opportunities, the extent to which they feel their work has meaning and feel committed to their career are related to the extent to which they live out their calling at work, in a virtuous cycle in which all states influence one another.

For the purposes of this study, the most salient part of the theory is the relation that calling is expected to have with job performance. The WCT predicts that the extent to which people feel that they are living out their calling at work predicts how they perform in their jobs and how much they will be satisfied by their job. In the WCT, the positive relation between calling and performance is explained by the motivating role of calling: Calling can motivate one’s job-directed actions, and the task itself becomes important for employees to practice their sense of calling (Duffy et al., 2017; Lee et al., 2018; Lobene& Meade, 2013).

The WCT also admits that for some people in some situations calling may be positively related with negative outcomes, such as workaholism, burnout, and exploitation. The relation between calling and possible negative outcomes is predicted to be moderated by both internal and external factors, such as personality and psychological climate at work. The WCT does not predict any moderator of the calling–performance relationship. With the aim of enriching our understanding of the situations in which calling predicts performance, in this paper we investigate whether job demand moderates the relation between calling and performance. Specifically, we will argue that when job demand is high, approaching jobs as a calling will not predict job performance. On the contrary, we expect a positive relation when job demand is low to moderate. Given the focus of this study and the extant literature that supports the relation between perceiving and living a calling (see Duffy et al., 2019), we will not investigate this relation any further. Instead, we will center our study around the extent to which people feel that they are called toward their current job, which include both perceiving and living out a calling at work.

Empirical Evidence Supporting the Relation Between Calling and Performance

The calling-performance relation predicted by the WCT has recently been supported empirically by a few studies. Lee et al. (2018) demonstrated that employees working in service and high-tech industries who perceived a higher calling reported higher task (r = .20) and contextual performance (r = .35). The authors argued that perceiving a calling motivates employees to perform well. A supportive climate was found to moderate the relation between calling and contextual performance, but not the relation with task performance. A relation of r = .24 between calling and performance has been observed by Wu et al. (2019) in a sample of construction project managers. The highest relation between calling and performance can be found in Liu et al. (2019, r = .58). The authors investigated the relation between calling and safety performance in a sample of train drivers and found that it is stronger when perceived organizational support is high. Furthermore, the authors found that the calling-safety performance relation is partially mediated by work engagement. The positive relation between perceived calling and task performance, measured as employees’ recall of their manager’s last rating, has been also observed in teachers (Lobene & Meade, 2013; r = .24): Those who perceive a calling are more dedicated to their work and show superior performance despite the perception of overqualification.

Kim et al. (2018) analyzed the relation between calling and self-rated performance (Study 1: r = .35; Study 2: r = .11) and manager-rated performance (Study 3: r = .33). In Study 1 (involving a sample of staff members of a Presbyterian megachurch) and in Study 3 (involving teams in companies operating banking, telecommunications, and electricity services), the authors found that work commitment partially mediates the relation between calling and performance and that ideological contract fulfillment moderates the mediation effect. In Study 2, the relation between calling and self-rated performance, assessed 1 month apart, was found to be nonsignificant. Similarly, Park et al. (2019) adopted a temporal separation between variables and included managers’ ratings of performance. They investigated the relation between the calling of newcomers, assessed during the first week of orientation at work, and managers’ evaluation of their employees’ performance, assessed 2 years after organizational entry. The correlation was found to be positive and significant (r = .24). In a hospital setting, Romney (2020; Study 3) showed that the positive relation between employees’ calling and manager’s ratings of their performance (r = .24) was suppressed by the managers’ perception of how effective employees deliver their voices regarding suggestions or comments on how work might be conducted more effectively (constructive voice delivery).

Finally, only one study investigated the relation between calling and productivity. Park et al. (2016) observed a positive but nonsignificant relation between sales performed in 1 year (total commission and policies sold) and perceiving a calling (r = .14), and a positive and significant relation between sales and living out a calling at work (r = .24). The relation between calling and sales was found to be completely mediated by occupational self-efficacy.

Adopting a different point of view, Park et al. (2018) investigated the relation between leader’s calling and employees’ calling among matched pairs of combat flight managers and employees. They observed a positive relation (r = .40) between manager’s calling and manager’s evaluation of employees’ performance.

Overall, the average meta-analytic correlation that has been observed in the literature across 11 studies on calling and performance is ρ = .29, 95% CI [.18, .39], τ = 0.00, I² = 0.00, Q(10) = 7.04, and p = .29. Removing the effect in Park et al. (2018), which measured managers’ calling instead of employees,’ the meta-analytic average correlation between calling and different measures of performance is ρ = .28, 95% CI [.16, .39]. Although heterogeneity is null after accounting for sampling error in the distribution of effect sizes, the number of studies allows investigating the moderating role of the type of performance measure employed. The relation between calling and performance is small-to-moderate (Cohen, 1992; Gignac&Szodorai, 2016) in studies that employed self-reported measures of performance (weighted mean ρ = .21, 95% CI [.14, .28]) and moderate-to-large when supervisor’s ratings of employees’ performance has been employed as an outcome (weighted mean ρ = .38; 95% CI [.22, .51]). This difference suggests either that the managers are influenced in their evaluations by both actual performance and employees’ attitude toward their job, or that employees with a calling underestimate their actual performance. Figure 1 provides the forest plot of all effects included in the meta-analytic estimation.

Figure 1.

Forest Plot of the Meta-Analysis Conducted on 11 Published Studies on the Relation Between Calling and Job Performance.

The Calling-Performance Relation According to an Interactionist Perspective

It has been observed that when the environment constrains options and provides clear signals about what is expected (strong situations; Mischel, 1977), individual factors such as personality and attitudes may lose their predicting power. According to an interactionist perspective, behavior is indeed the product of both internal (personal) and external (situational) factors (Endler& Parker, 1992; Weiss & Adler, 1984). Strong situations are characterized by high demands. Conversely, weak situations do not generate clear expectancies concerning behavior, and “do not offer sufficient incentives for its performance” (Mischel, 1977, p. 347). Weak situations let the individual free to choose their behavior, whereas strong situations impose a limit on the range of actions that the individual can perform. It is therefore likely that individuals who approach their work as a calling would perform better only when demands are low. Although reasonable, this assertion lacks empirical support because no study investigated whether job demand suppresses the positive relation between calling and performance. Furthermore, the different sizes of the effects that have been observed between calling and performance seem to depend on how performance is measured: Managers’ ratings are likely more sensitive to employees’ calling. Hence, in this study we fill a gap of knowledge in the literature by investigating whether job demands moderate the relation between calling and performance, by means of a multisource design in which job performance is measured across three different sources: the individual, the line manager, and archival information on actual productivity.

Multi-source designs have been introduced in publishing practices as a way to mitigate common method bias (Podsakoff et al., 2012), a source of error that is known at least since 60 years ago (Campbell & Fiske, 1959). Common method bias is a distortion in observed relationships across measurements due to shared method variance that is erroneously interpreted as shared trait variance (i.e., the “true” score variance that is shared by the constructs under investigation and that is of theoretical interest). Although it is widely supposed that common method bias invariably inflates observed relations, this is a common misconception (Conway & Lance, 2010). Shared method variance can either inflate or deflate observed relations. The latter bias occurs when measurement methods are negatively related. In both cases, controlling for biases in the estimates is critical because interpreting method variance instead of true variance can erroneously inform theories. Another common misconception is that other-reports are superior to self-reports (Conway and Lance, 2010). Other methods are also subject to method effects, which can be the same or different from those that bias self-reports. For instance, supervisors’ ratings of job performance (r_xx=.52; Salgado et al., 2016) are typically much less reliable than self-report measures. An effective way to gather information on potential biases in the estimates is combining different sources of information within the same study (i.e., multi-source designs), rather than substituting self-reports with other-reports or objective measures of performance.

Hypotheses

Career calling and performance. In the previous paragraphs, we proposed a theoretical framework on the calling–performance relation and quantitively reviewed a summary of empirical evidence supporting this relation. We expect to replicate previous results suggesting that career calling is positively related to all measures of performance adopted in this study: self-reported, manager-reported, and productivity.

Hypothesis 1: There is a positive relation between calling and self-reported task performance (H1a), manager’s rating of task performance (H1b), and productivity (H1c).

Job demand and performance. Job demands are stressors that can be of physical, psychological, social, or organizational nature and they are associated with physical or psychological costs (Bakker & Demerouti, 2007), generally leading to decreased job performance (Bakker et al., 2008; Gilboa et al., 2008). According to the literature, we expect to observe a negative relation between job demand and task performance. Higher demands make the employee focus on the gap between their performance and the expectations of the organization. As a consequence of focusing on expectations, they concentrate on coping with role stressors instead of committing to performing their tasks (Gilboa et al., 2008). Following this reasoning, we expect that performance will be lower when job demand is high.

Hypothesis 2: There is a negative relation between demand and self-reported task performance (H2a), manager’s rating of task performance (H2b), and productivity (H2c).

The moderation role of job demand. As predicted by the Person x Situation interactionist perspective (Cooper &Withey, 2009; Mischel, 1977), we expect that higher calling will relate to higher performance only when job demand is low, that is, when the situation is weak. The lack of strong pressure to perform offers individuals the opportunity to behave according to their calling, which is already known to lead to effective work behaviors that ultimately result in increased performance. Conversely, when job demands are high, that is, when the situation is strong, employees will be less free to choose which behavior to perform, thus calling will not drive their behavior. In addition, job demand is expected to decrease job performance because employees will be more focused on complying to organizational expectations, rather than pursuing their sense of calling and performing their tasks. Therefore, the following hypotheses were developed.

Hypothesis 3: Demand moderates the relation between calling and self-reported task performance (H3a), manager’s rating of task performance (H3b), and productivity (H3c) such that the relation between calling and task performance is larger when demand is low.

Differential effects. We expect that the presence of common method variance (Podsakoff et al., 2012) will inflate the observed relation between calling and self-reported task performance, which will turn out to be stronger than the relation between calling and other task performance measures. Even in the absence of common method bias, higher correlations between calling and self-reported performance may be due to individuals with high calling perceiving their ability to be higher than others, an effect that has been observed by Dobrow and Heller (2015). This may lead to an altered perception of their results and inflated self-reported performance measures.

Hypothesis 4: The relation between calling and self-reported task performance is stronger than the relation between calling and other task performance measures (rated by the manager and productivity).

Within the same reasoning, we expect that the relations between job demand and self-reported task performance will be stronger than the relation between job demand and managers’ reported task performance due to common-method bias (Podsakoff et al., 2012). Furthermore, demand affects performance, but perceptions of performance can also inform employees’ perception of demand. When employees perceive that they are unable to meet assigned standards of performance, they might develop a sense of being overloaded by environmental demands, which would lead them to perceive (and report) an increased level of demand. A stronger relation between demand and self-reported performance has also been observed in Gilboa et al. (2008).

Hypothesis 5: The relation between demand and self-reported task performance is stronger than the relation between demand and other task performance measures (rated by the manager and productivity).

All hypothesized relations are summarized in Figure 2.

Figure 2.

Moderation of Job Demand Between Calling and Measures of Performance: Self-rated (panel a), Manager-rated (panel b), and Productivity (panel c). Direction of Relations and Hypotheses are Reported. H = Hypothesis.

Method

Sample and Procedure

The data were collected online in 51 branches of a frozen food delivery company in Italy that serves clients all over the national territory. Italy is an industrialized society and the third-largest economy in the euro zone. Its economy is dominated by private companies and driven in large part by the manufacture of high-quality consumer goods, many of which are family-owned. Italy’s culture is individualist and avoids uncertainty (Hofstede, 2021), which means that Italians value individual’s (vs. group’s) ideas and goals and that bureaucracy and detailed planning are generally favored over a flexible planning process. Although the company in which data were collected is multinational with a headquarter in Germany, the organizational culture in which our participants live their workday mostly reflect the Italian culture. Each branch is led by one Italian manager, who coordinates from 14 to 46 salesmen. The data were collected within a larger project aimed at assessing work-related stress risks, a yearly process that is enforced by the Italian law. The CEO invited employees to take part to the study by email. Two sets of online surveys were administered: one for subordinates and another one for their line managers. All participants were provided with measures of Career Calling, Job Demand, and Task Performance. The survey also included measures of Organizational Citizenship Behaviors (OCB: altruism, courtesy, and compliance), Job Control, Social Support, Job Satisfaction, and turnover intentions. Scores at these scales are not used in the present study. The complete list of questions is provided here: https://osf.io/6nkue/. Managers were also asked to rate their employees’ task performance. The company delivered 1.530 questionnaires to the employees (51 managers and 1479 subordinates) and we collected 965 responses (46 managers and 919 subordinates), yielding a response rate of 63%. In this sample, 783 participants were male, 16 were female, and 24 preferred not to answer. The average age of the subordinates was 40.31 years (SD = 9.1) and 43.25 years for managers (SD = 7.8). Most subordinates have a high school degree (64.6%), 27.1% completed a middle school, 3.5% got a Bachelor’s degree, 1.5% completed a Master’s degree, 0.1% finished a post-graduate study, and 3.2% did not report a specific education level. Most managers have a high school degree (65.9%), 29.5% stopped their education at the middle school, 2.3% completed a Master’s degree, and 2.3% finished a post-graduate study. On average, subordinates worked for 9 years (SD = 9.0) in their profession and for 8 years (SD = 8.8) in their current organization. The average working time is 47.44 hours per week. Managers worked on average for 13 years (SD = 9.5) in their profession and for 12 years (SD = 9.2) in their current organization. The average working time for managers is 51.13 hours per week.

Measures

The questionnaire was administered in Italian. All scales were developed or validated in Italian except for Task Performance, which has been translated and back-translated following Brislin (1970).

Career Calling

Calling was measured through an improved version of the UMCS (Vianello et al., 2018). The UMCS measures the extent to which individuals perceive a calling for their current job by means of seven factors: passion, pervasiveness, purpose, prosocial orientation, transcendent summons, sacrifice, and identity. The UMCS was validated in a sample of Italian college students and adult workers and demonstrated good internal and external validity (Vianello et al., 2018). Scores on the calling scale showed good internal consistency (α = 0.93) and measurement invariance across time and study domains. The UMCS showed convergent validity with both the CVQ-presence scale (Dik et al., 2008) that measures perceiving a calling (r=.72, Dalla Rosa et al., 2019b), a single-item measure of living a calling (r=.58, Vianello et al., 2020), and the living a calling scale by Duffy et al. (2012; r₍₃₄₈₎=.78, Dalla Rosa & Vianello, 2021; r₍₁₅₂₎=.73, Vianello & Dalla Rosa, 2020). Example items are “I am passionate about my work,”“I believe that I have been called to pursue my current line of work,” and “My work helps me live out my life’s purpose.” The original scale is composed of 22 items, in this study we used a longer version of the UMCS composed of 28 items. To test whether the UMCS-28 is an improved version of the original 22-item scale, we compared nested second-order confirmatory factor analysis models. The analysis showed slightly better fit indexes for the 28-item version and overall higher loadings on the items: UMCS-28: χ²(343) = 1021.084, CFI = .952, RMSEA = .049, 95% CI [.045–.052], SRMR = .039; UMCS-22: χ²(202) = 730.501, CFI = .947, RMSEA = .056, 95% CI [.052–.060], SRMR = .044; Δχ²(141) = 290.58, p< .001, ΔCFI =−.01; ΔRMSEA = .01; ΔSRMR = .01. The best fitting model (UMCS-28) showed a good fit to the data according to the most stringent criteria reported in Marsh et al. (2004). In the current study, answers were given on a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) and Cronbach’s α was .96. Supplemental information and detailed results supporting the use of the 28-item scale are reported at the following link: https://osf.io/7ftx6/.

Job Demand

Demand was measured with eight items taken from the Italian version of the Health and Safety Executive Indicator Tool (HSE-IT; INAIL, 2017). The HSE-IT is used as a first step in risk assessment for work-related stress. The demand scale is a subscale of the HSE-IT that assesses potential sources of stress in the workplace, such as issues regarding workload, work patterns, and the work environment. The scale was validated in a sample of 6,378 Italian workers and 30,903 employees in the UK, the internal reliability of the demand scale scores was .75 and .87, respectively (Edwards et al., 2008; Rondinone et al., 2012). To account for construct validity, we conducted a confirmatory factor analysis (CFA). The results showed that a one-factor model had a good fit to the data: χ²(19) = 87.301, CFI = .958, RMSEA = .063, 95% CI [.050, .077], SRMR = .033, and is in line with previous literature (Edwards et al., 2008). Example items are: “I have unrealistic time pressures” and “I have unachievable deadlines.” Answers were given on a Likert scale ranging from 1 (never) to 5 (always). In the current study, Cronbach’s α was .79.

Task Performance

Task Performance was measured with the 7-item In-Role Behavior scale by Williams and Anderson (1991). Example items are: “adequately completes assigned duties” or “meets formal performance requirements of the job.” Items were adjusted for use with employees or managers (e.g., “I fulfill all the requirements of the job”; “This employee fulfills all the requirements of the job”). The scale was validated in a sample of 127 employees (α = .91, Williams & Anderson, 1991). Answers were given on a Likert scale from 1 (strongly disagree) to 5 (strongly agree). In the current study, Cronbach’s α was .77 for self-reported task performance. The results showed that a one-factor model for self-reported task performance had a good fit to the data, χ²(13) = 62.542, CFI = .977, RMSEA = .066, 95% CI [.050, .083], SRMR = .024.

The reliability of managers’ rating of employee’s task performance was estimated using a three-level model (scores are nested within employees, employees are nested within managers). The multilevel model was estimated using formula 8 in Jeon et al. (2009). The reliability of the manager-level scores was estimated as the proportion of between-managers variance (σ² = .10) on the total variance (variance of employees within managers, σ² = .27; variance of scores among employees, σ² = .34), corrected for the average number of employees for managers (n = 29) and the number of items (seven items for each employee; formula 9 in Jeon et al., 2009). Considering an average of 29 employees for each manager and seven scores for each employee, the reliability of manager-rated performance scores was .88.

A multi-level confirmatory factor analysis (MCFA; Dyer et al., 2005) was performed for task performance evaluations provided by managers. Running a single-level CFA on managers’ ratings would have introduced two potential sources of biases in the estimates. A CFA conducted on the variance–covariance matrix estimated on the entire dataset would have ignored the dependency that exists among ratings provided by the same manager. A CFA conducted on the sample between-group variance–covariance matrix would have underestimated the fit of the group level factor structure. None of them would have informed us on whether the factor structure holds both in the within- and between-group variance–covariance matrix. Hence, we estimated a two-level CFA, which specifies two different factor structures for the within- and between-group levels. The within-group level parallels a traditional CFA on disaggregated data with seven observed indicators, seven random errors, and one latent factor. The between-manager structure specifies seven latent indicators estimated from group means of all observed indicators, seven random errors, and one latent factor. The two structures are linked by regressing group means on the observed indicators. The results of the MCFA suggests that the same factor structure holds at both the organizational and individual levels: χ²₍₂₆₎ = 73.014, CFI = .982, RMSEA = .038, SRMR within = .019, and SRMR between = .0311.

Productivity

The productivity levels of employees were provided by the company using a 5-level discrete measure. Employees were ranked from 1 (lowest productivity) to 5 (highest productivity) according to their yearly amount of sales. Salesmen in rank 1 are those who realized the lowest amount of sales (less than € 200.000,00 in a year) and salesmen in rank 5 are those who realized the highest amount of sales (more than € 288.500,00). The intervals determining the levels of performance (from 1 to 5) were set by the organization based on their historical record of sales. Further information on this measure is protected by industrial secrecy.

Preliminary Analysis

Preliminary analyses were performed to test for assumptions behind multilevel linear models. The skewness and kurtosis of the calling, demand, self-reported task performance, manager’s ratings of employees’ performance and productivity distributions were all within plus or minus one, indicating univariate normality. To test whether calling and job demand are linearly related to self-reported task performance, managers’ rating of task performance and productivity, plots of OLS estimates and raw residuals against each predictor were examined. Results support linearity of relations among the dependent and independent variables considered in this study.

Missing values for variables ranged between 0% (productivity and managers’ rating of task performance) and 13% (calling). Little’s MCAR test including calling, job demand, and self-reported task performance suggests that data are missing completely at random: χ²(3) = 2.720, p = .437. Missing data were handled with the maximum likelihood (ML) estimation procedure available in IBM SPSS 27.

Results

Correlations among the study variables are reported in Table 1. Calling was positively correlated with self-reported task performance and task performance rated by the manager. Demand was negatively correlated with self-reported task performance and task performance rated by the manager. Neither demand nor calling were significantly correlated with productivity.

Table 1.

Descriptive Statistics, Cronbach’s Alphas, and Correlations for All Study Variables.

Variables	n	M	SD	1	2	3	4	5
1. Demand	900	2.66	.61	.79	837	869	723	549
2. Calling	837	3.54	.64	−.30**	.96	837	669	502
3. Self-reported task performance	869	4.29	.48	−.23**	.23**	.77	697	527
4. Managers’ratings of task performance	1220	3.99	.69	−.13**	.12**	.18**	.88 ^a	806
5. Productivity	954	4.44	1.19	−.02	.05	.08	.43**	—

Note. Numbers above the main diagonal report sample size of Pearson’s zero-order correlations, which are provided below the main diagonal that reports scale scores’ reliabilities (Cronbach’s alpha unless otherwise noted).

^aManager-level reliability was estimated using formula 9 in Jeon et al. (2009).

**p< .01, two-tailed.

In this dataset, employees are nested within branches. It is reasonable that employees within the same branch are more similar in work-related attitudes and behaviors compared to employees working in different branches, as a result of selection practices and subcultures within the organization. Hence, we accounted for possible clusters in the dataset, decomposing variance within branches from variance across branches. Failure to do so may provide biased estimates of model parameters and their standard errors. We estimated for each hypothesis a series of nested generalized linear multilevel models (West et al., 2007). As a baseline model (M0), we estimated a null model with no predictors and a random intercept to partition the variance of the dependent variable into between- and within-branches variation. Then, we added fixed effects of demand and calling (M1) and kept them in subsequent models even if they were non-significant. In model 2 (M2), we added the random effects of demand and calling, and removed them from subsequent models if the variances of the slopes were non-significant to avoid estimation problems. Model 3 tested the fixed interaction effect by adding the product term between demand and calling. The last model (M4) tests the variance across branches of the interaction slope, which was removed if non-significant. The Intraclass Correlation Coefficient (ICC) was used as an indicator of the proportion of between-branch variance on the total variance and can be interpreted as the degree of group heterogeneity for a measure (Hox, 2002). To correctly interpret interaction effects, measures of performance were standardized; calling, demand and the interaction term were grand-mean centered in all models. The codes for reproducing all analysis presented in this article are available here: https://osf.io/aqpjr/.

Self-Reported Task Performance

The null model (M0) showed that the between-branches variance of self-reported task performance is non-significant (μ_between = .02, p = .19, μ_within = .98, p< .001). The proportion of between-branches variance is tiny (ICC = .02). The fixed effects of calling (H1a, β = .25, p< .001) and demand (H2a, β =−.28, p< .001) as level 1 predictors of self-reported task performance are significant (M1). M2 tested the between-branches variance of slopes, which is small and non-significant (μ_demand= .06, p =.17; μ_calling = .01, p =.81), hence random slopes were dropped from subsequent models testing fixed (M3; H3a, β =−.28, p< .001) and random interaction effects (M4; μ= .01, p = .72). Table 2 provides parameter estimates and Figure 3 shows the moderation effect of demand on the relation between calling and self-reported task performance. To illustrate further the shape of the interaction, we estimated the effects at different levels of the moderator (Aiken et al., 1991). When job demand is low (1 SD below the mean), the calling–performance relation is β = .57, 95% CI [.31, .78]. When job demand is high (1 SD above the mean), the calling–performance relationship is β = .003, 95% CI [−.21, .21].

Table 2.

Parameter Estimates for Fixed Main and Interaction Effects on Self-reported Task Performance, Manager’s Ratings of Task Performance and Productivity (M3).

Variable	Estimate	SE	95% CI		t	p
			LL	UL
Self-reported task performance
Intercept	−.02	.04	−.09	.05	−.59	.59
Demand	−.28	.06	−.40	−.17	−.4.94	<.01
Calling	.29	.06	.18	.40	5.17	<.01
Demand*Calling	−.28	.08	−.43	−.13	−3.60	<.01
Manager’s rating of task performance
Intercept	.13	.08	−.03	.28	1.66	.10
Demand	−.14	.06	−.26	−.03	−2.47	<.05
Calling	.12	.06	.004	.23	2.04	<.05
Demand*Calling	.004	.08	−.15	.16	.05	.96
Productivity
Intercept	.06	.08	−.09	.21	.78	.44
Demand	.07	.07	−.08	.21	.91	.36
Calling	.19	.07	.05	.32	2.68	<.01
Demand*Calling	−.04	.09	−.22	.15	−.38	.71

Note. CI = confidence interval; LL = lower limit; UL = upper limit.

Figure 3.

Job Demand Suppresses the Relation Between Calling and Self-Reported Task Performance. Note: “Low” categories represent participants who are −1 SD below the sample mean. “High” categories represent participants who are +1 SD above the sample mean (Aiken et al., 1991).

Consistently with our predictions, we observed that calling is positively related to self-reported task performance (H1a), that job demand is negatively related to self-reported task performance (H2a), and that job demand suppresses the positive effects of calling on performance (H3a).

Managers’ Ratings of Task Performance

M0 partitioned the variance of manager’s ratings of task performance into between- (μ = .21, p< .001) and within-subjects variance (μ = .78, p < .001), indicating that 21% of the overall variation in managers-rated performance lies between managers or branches (ICC=.21). M1 tested the fixed effects of calling (H1b, β = .12, p =.04) and demand (H2b, β =−.14, p = .01), which turned out to be significant predictors of managers’ rating of employee’s task performance. M2 allowed to observe that these effects do not vary across branches (μ_demand = .01, p =.72; μ_calling = .002, p = .96). The fixed interaction effect between calling and demand was not significant (M3; H3b, β = .004, p = .96) and did not vary across branches (M4; μ = .06, p = .23).

Consistently with our predictions, we observed that calling is positively related to managers’ ratings of task performance (H1b), and demand is negatively related to managers’ ratings of task performance (H2b). Contrary to our expectation (H3b), job demand does not moderate the effects of calling on managers’ ratings of task performance. When job demand is low (1 SD below the mean), the calling–performance relationship is β = .12, 95% CI [−.10, .37]. When job demand is high (1 SD above the mean), the calling-performance relationship is very similar, β = .15, 95% CI [−.07, .42].

Productivity

Hypotheses regarding productivity were tested in the third set of nested models. We observed that the between-branches variance is μ = .16 (p< .001), whereas the within-subjects variance in productivity is μ = .82 (p< .001, ICC = .16), indicating that 16% of the variance in productivity occurs between branches. According to the same strategy adopted for previous dependent variables, M1 specified the random intercepts, and added the fixed effects of calling (H1c, β = .18, p = .001) and demand (H2c, β = .07, p = .36). Only calling turned out to predict productivity. M2 showed that between-branches variance of the main effects of demand and calling are null (μ_demand = .003, p =.92; μ_calling = .002, p = .97). The fixed interaction effect is nonsignificant (M3; H3c, β =-.04, p = .71), and does not vary across branches (M4; μ = .004, p = .94).

Consistently with our prediction, we observed that calling positively relates to productivity (H1c) and, contrary to our expectations, job demand does not affect productivity and does not moderate the effect of calling on productivity (H3c). When job demand is 1 SD below the mean, the calling–performance relationship is β = .04, 95% CI [−.23, .30]. When job demand is high (1 SD above the mean), the calling-performance relationship is β = .08, 95% CI [−.14, .31].

Differential Effects of Calling and Demand on Measures of Performance

Hypotheses 4 and 5 state that the effects of calling and demand on self-reported task performance will be stronger than the effects on other task performance measures (rated by the manager and productivity). To examine these hypotheses, two multivariate multilevel models (one for calling and one for demand) were estimated and post analysis contrasts were computed to compare the fixed effects across measures of performance (Baldwin et al., 2014). Self-reported task performance, manager’s ratings of task performance, and productivity were allowed to correlate. Measures of task performance, calling, and demand were standardized to interpret the differences between fixed effects.

The fixed effect of calling on self-reported task performance (β = .21, p< .001), manager’s rating of task performance (β = .09, p = .001), and productivity (β = .11, p = .001) were all statistically significant. The effect of calling on self-reported task performance was stronger than the effect of calling on manager’s ratings of task performance (Δβ = .13, SE = .002, p = .002) and stronger than the effect of calling on productivity (Δβ = .11, SE = .05, p = .03).

The fixed effect of demand on self-reported task performance (β =−.24, p< .001) and on manager’s rating of task performance (β =−.12, p< .001) were statistically significant. The effect of demand on productivity (β < .001, p = .996) was not statistically significant. The effect of demand on self-reported task performance was stronger than the effect on managers’ ratings of task performance (Δβ =−.12, SE = .04, p = .021) and stronger than the effect of demand on productivity (Δβ =−.24, SE = .06, p< .001). As predicted in hypotheses 4 and 5, the relation between calling, demand, and self-reported task performance was stronger than the relation between calling, demand, and managers’ ratings of task performance and productivity.

Discussion

In this study, we investigated the role of job demand as a moderator of the relation between calling and three measures of task performance: self-rated, manager-rated, and productivity. We observed a positive relation between calling and all measures of task performance. The size of the relation between calling and self-rated task performance is within the confidence interval around the meta-analytic estimate of the correlation observed in the literature. Hence, our results add consistency to this estimate. Interestingly, we observed that the relation between calling and performance is higher when performance is self-reported by the employee compared to when it is measured using managers’ ratings or productivity. This result could be due to method variance that both calling and self-rated performance have in common, but it could also be explained by an altered perception of ability that has previously been observed to accompany high levels of calling (Dobrow & Heller, 2015). Called employees might prioritize their own perceptions over objective external information about their performance. Importantly, the results of this study show that common method variance or employees’ overestimation of their performance do not account for all the variance shared by calling and performance, which is smaller for managers’ ratings of performance and productivity but not null. In this regard, our results are inconsistent with the literature. The meta-analytic average effect of studies that adopted managers’ ratings of employees’ performance is higher than those that employed a self-report by employees. Yet, this is the first study that employs both measures. It may be that previously published studies that measured performance using managers’ ratings were run on a sample in which the relations between calling and self-reported performance were even higher. More research is needed that directly compares self-reports versus managers’ rating of performance to understand how calling predicts performance in more detail.

Importantly, in this study we observed that when employees perceive high demands from the environment, the impact of calling on performance is null. In 2009, Cooper and Withey lamented that the Person x Situation hypothesis lacks empirical evidence. This study partially fills this gap, providing empirical evidence that the perception of a strong situation, such as a high level of demand, suppresses the positive effect of an individual characteristic such as calling on job performance. Strong situations limit individuals’ behavior, forcing employees to focus on organizational expectations rather than let them free to perform their tasks in line with their sense of calling. Interestingly, we also observed that demand has a negative, rather than positive, effect on performance, in line with previous meta-analyses (e.g., Gilboa et al., 2008). The higher the environmental pressure to work hard, the smaller the employees’ performance. This result could apparently be interpreted as if low performance leads to higher pressure, but we observed no relation between demand and actual productivity. Demands only affect subjective measures of performance (self-reports and managers’ ratings). Hence, it seems more likely that the extent to which employees feel pressured to perform impacts their behavior. In summary, we observed that a demanding work environment harms performance and totally suppresses the positive effect that callings have when demand is low.

Theoretically, our results both support and extend the theory on career calling in clarifying the characteristics of the work environment that can either foster or inhibit the positive effect of calling on work performance. Specifically, these results support and extend the WCT (Duffy et al., 2018), adding to the literature substantive evidence that calling is related to work performance across multiple independent measures. This result is not surprising if we consider that people approaching work as a calling feel passion for their job and derive from it a stronger identity and a purpose in life. Most importantly, this study extends the WCT clarifying that self-reported performance is higher in people with higher levels of calling if and only if job demand is low. Generalizing the concept of demand to situations within an interactionist perspective, it seems reasonable to state that calling matters most in weak situations and least in strong situations. In strong situations, interindividual variation in behavior is reduced, because strong environmental cues for appropriate behavior are provided: People are not free to behave according to their calling. In weak situations, greater discretion and fewer cues regarding appropriate behaviors are provided. As such, performance can be determined by individual differences in calling. Previous evidence supporting an interactionist perspective of the effect of calling on behavior comes from Chang et al. (2020): The authors observed that calling significantly contributes to employees’ crafting behaviors through career commitment, but only when job autonomy is high. Higher autonomy is a defining feature of weak situations: When job autonomy is high, individuals feel free to actively shape and redefine job tasks and settings to reflect their calling and the subjective meaning and purpose they attach to work. On the contrary, the constraints of strong situations make it less likely for individuals to incorporate and emphasize aspects of their calling at work, because adaptive moves represent a deviant behavior that may be difficult or impossible to undertake.

Understanding that calling may impact behavior only in weak situations is crucial for the development of the field. Thompson and Bunderson (2019) were concerned that the existing literature suffered from a lack of evidence regarding the relation between calling and behavior. Our study highlights the need to analyze this relation across different levels of situational strength, and suggest integrating situational strength as a moderator of the calling–performance relation in the WCT.

An interactionist perspective also helps to consider that individuals can alter social situations according to their personal characteristics, and tend to choose settings that are congruent with their traits (Stewart & Barrick, 2004). This is relevant for people working in teams, where the behavior of one individual can alter the situation for others, ultimately impacting their colleagues’ behavior. Empirical evidence that calling can alter a situation and guide people’s preference for a setting has already been found in the literature. For instance, there is evidence that leaders’ calling impact employees’ behavior and performance (Park et al., 2018). In addition, career calling was found to impact career choices (Dobrow & Tosti-Kharas, 2011; Duffy & Sedlacek, 2010) and job search behaviors (Dalla Rosa et al., 2020). Future studies are recommended to consider that, according to the Person x Situation approach, the strength of a situation can impact the likelihood of expressing a calling and that approaching work as a calling can alter relations and the social context.

Practical implications of the results of this study call managers that want to foster performance to constantly monitor workloads and plan their employees’ activities according to their perception of demand, especially for individuals who feel called to their job. While planning their employees’ activities, managers should take into consideration individual factors that favor or impair performance. There is extant empirical evidence suggesting that employees’ calling is one of those factors. At this point, it would be worth wondering whether calling should be taken into account not only during performance management activities, but also in selection practices. The literature on personnel selection clearly suggests that General Mental Ability (GMA) is the best predictor of performance (Schmidt & Hunter, 1998), and that only a few selection tools contribute to predict performance beyond GMA: structured interviews, moral integrity, conscientiousness, emotional intelligence and goal orientations (O'Boyle et al., 2011; Payne et al., 2007; Van Iddekinge et al., 2012). We suggest future research to study whether applicants’ calling for the job predicts performance above GMA and other common selection tools, that is, whether calling has incremental predictive validity. Should this be the case, measures of career calling could be successfully employed to select individuals for a job.

Limitations and Future Directions

The results of the current study need to be considered in light of some limitations. Longitudinal precedence between calling, performance, and demand cannot be established due to the cross-sectional nature of these data. In this study, we assumed calling and demand to be antecedents of performance. However, the opposite might also be true: self- and other-evaluations of individual’s performance might influence how employees perceive their calling and their job’s demands. For instance, perceiving high levels of performance might increase the sense of being called to the job and might favor the employees to downsize the demands of their job. The idea of calling as an antecedent of performance is in line with the WCT (Duffy et al., 2018), although empirical evidence suggests that positive experiences such as engagement and a clear professional identity actually promote the development of a calling rather than being a consequence of discerning a calling (Dalla Rosa et al., 2019a). A positive feedback from a manager regarding performance can be seen as a positive experience that promotes the development of a sense of calling for that job. In addition, low levels of performance, both perceived and manager-rated, can be justified by an unbalance between demand and resources, which might increase the perception of being overloaded. Future studies should adopt experimental or longitudinal study designs to test whether calling precedes or follows performance over time and whether performance and the experience of perceiving a calling influence the perception of job demand.

Differently from previous studies, calling was found to have a stronger effect on self-rated performance rather than on other measures of performance. This difference might be accounted for by measurement artifacts such as different reliabilities of measures across studies, which are known to set the upper limit of correlations. Yet, it is possible that the stronger calling/performance relation that we observed using self-reports (vs. managers’ ratings or an objective measure of productivity) may be due to the specific sample involved in this study. Specifically, the employees involved in this research are required to spend the majority of their working time outside of the organization. This limits their interaction with the managers, leading to less information that managers can use to rate their employees. In the absence of information regarding employee’s behavior outside of the organization, managers might have been influenced by productivity in rating employees’ task performance. Indeed, we observed a moderate-to-large positive correlation between managers’ ratings of performance and productivity. Hence, the results of this study may be generalizable to salesmen, but it seems premature to generalize them to very different jobs. To gain a more complete understanding of the relation between calling and managers’ rating of performance across different jobs, future research investigating the role of the relation between managers and employees on the effect of calling on performance needs to be conducted on different samples.

Finally, a limitation of our study is that we conceptualized calling towards one’s own current job, without separately measuring the extent to which one perceives a calling and lives it out. Our conceptualization includes both perceiving and living a calling. It is possible that explicitly measuring the extent to which people are living out their calling would have led us to observe higher relations between calling and performance across sources and measures.

Conclusion

This study suggests that career calling is positively related to self-rated performance, managers-rated performance, and productivity, and that job demand suppresses the positive relation between calling and self-reported performance. According to the Person x Situation interaction hypothesis, individuals who approach their work as a calling perform better only when the working conditions allow them to behave according to their inner states and traits, that is, when job demand is low and the situation is weak (Mischel, 1977). Conversely, when job demand is high and the strong situation limits the effect of individual differences on behavior, calling does not lead to increased performance. Future research is needed to identify the situational boundaries of the positive effect of calling on performance.

Identifying the settings in which calling is relevant in work organizations has important theoretical and practical implications. Progress will be made as situational boundaries and theoretical explanations for the relation between calling and performance are developed. As differences in the effect of calling across settings are observed, a clearer understanding of the proper use of calling in selection and human resource management practices may be developed.

Endnotes

1For multilevel CFA models, the covariance matrices for the within-group model and the between-group model are computed separately; therefore, the SRMR is computed separately for each level.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work has been supported by a PhD fellowship funded by the CARIPARO foundation and awarded to the last author. The funding source was not involved in study design, in the collection, analysis, and interpretation of the data, in the writing of the report, or in the decision to submit the article for publication.

Data Availability Statement

The full data set used in this study is available at , doi: 10.17605/OSF.IO/AQPJR. Please contact the corresponding author (michelangelo.vianello@unipd.it) with questions regarding the survey or data.

Open Practices

All study materials, data, and analysis scripts are publicly available on the Open Science Framework:

ORCID iDs

Michelangelo Vianello

Anna Dalla Rosa

Sophie Gerdel

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