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ORGANIZATIONAL PSYCHOLOGY
www.orgpsyjournal.hse.ru
Personality resources and work motivation: A beneficial synergy
Evgeny OSIN Tatiana IVANOVA Ekaterina OREL Elena RASSKAZOVA
National Research University "Higher School of Economics", Moscow, Russia
Abstract. Purpose. The paper aims to show the motivational function of personality resources in the organizational context. Based on the Personality Potential model (Leontiev, 2011) and Self-Determination Theory (SDT), we hypothesized that personality resources facilitate productive motivation and engagement with the work environment, resulting in positive outcomes for the individual, as well as for the organization. We aimed to explore three research questions: 1) whether personality resources positively predict autonomous motivation and negatively predict controlled motivation, 2) whether work motivation mediates the effects of personality resources on well-being outcomes, and 3) whether personality resources and work motivation have synergistic effects on workplace well-being outcomes. Study design. We used data from two samples of employees of a Russian production enterprise using a cross-sectional design (Study 1, N = 4,708) and a longitudinal design with a two-year interval between measurements (Study 2, N = 372). The participants completed measures of personality resources (hardiness, dispositional optimism, generalized self-efficacy, tolerance for ambiguity), work motivation, and well-being outcomes (life satisfaction, job satisfaction, work-life balance, work engagement, organizational commitment). Findings. A single dimension of personality resources emerged as a positive predictor of autonomous motivation and a negative predictor of controlled motivation, both in the cross-sectional and in the longitudinal perspective. The change in well-being outcomes was mainly explained by autonomous motivation at Time 1. Using a moderated mediation model, we found that work motivation partially mediated the effects of personality resources on well-being outcomes and exhibited the theoretically predicted interaction effects on work-life balance, job satisfaction, and organizational commitment. Value of the results. The results are in line with the hypothesis about the motivating function of personality resources.
Keywords: Self-Determination Theory, hardiess, workplace well-being, work engagement, job
The study was supported by the Russian Foundation for Basic Research, project #15-0610933 "Personality, motivational, and organizational resources of psychological well-being in professional activity".
satisfaction.
Address: 20, Myasnitskaya 101000, Moscow, Russia
E-mail: evgeny.n.osin@gmail.com
Introduction
The concept of personality resources
The problem of personality dispositions underlying workplace well-being and performance has been the focus of attention in organizational attention for many decades. The term "resources" usually used to denote such dispositions came into psychology from economics and management theory, but nowadays plays an important role in the field. Modern theories take into account different kinds of resources: internal, external, economical, physical, labour, natural, cognitive, psychological, informational, etc. — virtually anything that can be used by human beings as means to be effective and to maintain life quality (Hobfoll, 1989).
According to resource theories (Hobfoll, 2011; Ivanova, 2013; Leontiev, 2016), resources of different types disposable by individual do not exist separately from one another, but are organized in a system. Resources of different types can be acquired or lost, exchanged or replaced by one another, and, finally, used with various degrees of efficiency. According to D. Leontiev (2016), any object or property is not by itself a resource, but only becomes a resource in the context of a certain goal or activity.
In the present paper, we focus on personality resources. We define personality resources at work as relatively stable personality dispositions that lead to optimal and sustained activity engagement and result in higher productivity and higher workplace well-being in most work situations. Unlike trait theory, which stresses the stable character of the personality core (Emmons, 1999), modern approaches to personal resources view them as relatively stable personality characteristics that evolve over one's lifetime (Ivanova, Leontiev, Osin, Rasskazova, Kosheleva, 2018). This idea is supported by findings of various studies testing interventions aimed to develop personality resources, such as optimism (Seligman, 1998), hardiness (Maddi et al., 1998), psychological capital (Luthans et al., 2006).
D. Leontiev (2014) described four groups of dispositions conducive to optimal and sustained activity engagement, including resources of stability (attitudes and values which provide a sense of support, sustainable self-esteem, and inner grounds for decision making), resources of self-regulation (strategies of dynamic interaction with life circumstances), motivational resources (reflecting an energy supply available to the individual), and, finally, instrumental resources (such as abilities, skills, and competencies relevant for a specific activity). The term "personality resources" is typically only applied to the variables from the first three groups.
The functions of personality resources
A large number of studies focus on the role of personality resources at work showing that these variables are not only correlates, but also causes of well-being. Personality resources moderate the causal relationships between external circumstances and psychological outcomes (Wise, Stake, 2002; Xanthopoulou et al, 2007; Luthans et al., 2008; Mastenbroek et al., 2014). In the organizational context, special attention is paid to the efficacy of individuals at high-level management positions (Kalimo et al., 2002; Kalimo et al., 2003; Xantoupoulou et al., 2007; McDougall, Drummond, 2010), where personality resources were shown to be key predictors of well-being and performance.
Personality resources are positively associated with work engagement (Hakanen et al., 2006; Saks, 2006; Xanthopoulou et al., 2007; Kuhnel et al., 2012; Mandrikova, Gorbunova, 2012), which mediates their associations to workplace well-being. High levels of personality resources enable employees to keep a sustained level work of engagement even under stress and even when the level
of well-being is low (Hobfoll, Shirom, 1993). Personality resources help to cope with stress (Nelson, Simmons, 2003) and emerge as important predictors of successful workplace adaptation (Hobfoll, 1989; Judge, Bono, 2001). Emotional burnout is associated with low levels of personality resources, such as self-esteem, self-efficacy, and optimism regarding the future (Wells, Hobfoll, & Lavin, 1999; Garrosa et al., 2011).
But despite the promising findings at the level of specific variables, the field still experiences a lack of coherent theory of personality resources (Ivanova, Leontiev, Osin, Rasskazova, Kosheleva, 2018). Different studies use different dependent variables (well-being, motivation, performance) and fail to specify the "object" of personality resources or criteria for selection of candidate variables. This leads to a confusion, as the same variable, such as well-being, can be viewed as a resource and as an outcome variable in different studies (Fredrickson, 2004; Lubomirsky et al., 2005; Lebedeva, 2012). In order to overcome these contradictions, the functions of personality resources need to be specified.
Another issue lacking theoretical clarity is the problem of dynamics of personality resources: are these dispositions supposed to be stable or dynamic? The answer to this question defines whether such variables as emotional states or IQ can be viewed as personality resources. Even though the majority of the resource variables can be developed during the lifetime, they are still treated empirically as stable dispositions. Future theoretical work needs to clarify the conditions when certain types of resources can be considered as "stable" or "malleable."
Despite the systemic character of personality resources (Hobfoll, 2011), researchers keep trying to find the "best" variables in terms of explaining human success in different settings. For instance, optimism and hardiness are often said to be the best predictors of well-being and coping with stress (Leontiev, 2011), but "best" is defined as having the most shared variance with these criteria. However, the causality and even the direction of these associations is rarely demonstrated. On the other hand, there is a tendency to look for a general factor of personality resources, which is reflected in such integral constructs as psychological capital (Luthans, Youssef, Avolio, 2007) or core self-evaluations (Judge, Erez, Bono, 1998; Judge et al., 2002). However, a general factor is hardly a substitute for substantive theory: in our opinion, such data-driven models fail to fill this gap. The shared variance between different constructs may reflect similarities in their respective empirical operationalizations or measurement procedures. We believe that a theory describing the systemic interactions between personality resources is badly needed.
One pathway toward arriving at such a theory was suggested by D. Leontiev (2011), who proposed the concept of the personality potential. He defines the personality potential as an integral systemic characteristic of individual psychological properties which underlies the capability of a personality to act based on stable inner criteria, to maintain one's orientation towards meaning, and to remain effective under pressures and in changing circumstances. Thus, personality potential describes the capacity for effective and flexible self-regulation. Unlike other models, the personality potential model states that psychological properties only become "resources" when they can serve as means for a certain activity. Hence, the specific list of personality resources and the structure of their associations are supposed to differ in different situations.
The personality potential theory (Leontiev, 2011; Ivanova, Leontiev, Osin, Rasskazova, Kosheleva, 2018) suggests that personality resources may be linked to positive outcomes via different pathways. First, they sustain motivation for activity by facilitating engagement and interaction with the environment. Second, they buffer against the detrimental effects of stress and challenges (by reducing the evaluation of stressors, by improving the evaluation of coping resources, increasing the motivation for active coping, providing additional coping resources). Third, they are associated with more effective self-regulation at different stages of activity execution. Finally, certain personality
resources may have specific instrumental functions relevant to specific activities or stages of their implementation.
The present study
In the present study, we aim to test the hypothesis about the motivating function of personality resources in the work context. Existing studies based on Self-Determination Theory (SDT) (Ryan, Deci, 2000), a leading research approach in the field, undertaken in the work context have mainly focused on the positive effects of autonomous and the negative effects of controlled work motivation on organizational outcomes, as well as the effects on job characteristics and management practices on autonomous work motivation (Ryan, Deci, 2017).
Within SDT, autonomous and controlled motivation is typically studied separately from personality dispositions that may be related to the emergence of motivation. One study (Ratelle, Vallerand, Chantal, Provencher, 2004) using a prospective design in a general population sample found that three variables reflecting constructive cognitions or cognitive adaptation (positive self-perceptions, perceptions of control, and dispositional optimism) predict self-determined motivation in a one-year perspective and that motivation mediates the effects of these variables on well-being.
We aim to test a similar hypothesis in the organizational context, bringing together SDT with the personality resource approach to investigate the relationships between personality resources, work motivation, and work well-being outcomes. We present two empirical studies aimed to explore three research questions: 1) Are higher levels of personality resources associated with more productive (more autonomous and less controlled) patterns of work motivation? 2) Does work motivation mediate the effects of personality resources on well-being outcomes? 3) Do personality resources and work motivation exhibit synergistic effects on workplace well-being?
We chose four personality resource variables, which reflect positive beliefs about oneself and the world and are not specific to the work context, dispositional optimism, hardiness, generalized self-efficacy, and tolerance for ambiguity. First, we expected that individuals high in these beliefs would be more likely to engage actively with the work environment and to be more selective in their choice of work situations and environments, resulting in higher levels of autonomous and lower levels of controlled motivation. Second, we expected that work motivation would mediate the positive effects of personality resources on well-being outcomes: this expectation was based on the idea that personality resources only exhibit their positive effects when they are utilized in activity, which is supported by motivation. Finally, we expected that the effects of work motivation on workplace well-being outcomes would be moderated by personality resources: on the one hand, resources may be instrumental in facilitating the pursuit of autonomous goals resulting in higher well-being; on the other hand, they may buffer against the detrimental effects of controlled motivation on well-being by various pathways (e.g., by facilitating the choice of intrinsic goals and satisfaction of basic psychological needs in non-work activities).
Thus, the aim of our studies was to investigate the interplay of personality resources and work motivation in predicting subjective well-being of organization employees. Study 1 used a cross-sectional design in a large sample. Study 2 used a prospective design based on a follow-up survey in the same organization two years later.
Study 1
The aim of Study 1 was to investigate the interactive effects of personality resources and work motivation in a large sample using a cross-sectional design.
Methods Sample
The sample was comprised by 4,708 employees of a large energy generating enterprise with 20 local branches in six regions of Central and North-West Russia. The demographic composition of the sample is presented in Table 1. The average experience of work in the same company was 13.32 years (SD = 10.21), the average experience of work in the same position was 9.88 years (SD = 9.30).
Table 1. Demographic composition of Study 1 (N = 4708) and Study 2 (N = 372) samples
Demographic Value Study 1 N (%) Study 2, N (%)
Gender Male 3,106 (65.97%) 223 (59.95%)
Female 1,602 (34.03%) 149 (40.05%)
Age 18-29 732 (15.55%) 87 (23.29%)
30-39 1,146 (24.34%) 117 (31.45%)
40-49 1,344 (28.55%) 104 (27.96%)
50-59 1,220 (25.91%) 61 (16.40%)
60-75 259 (5.50%) 3 (0.81%)
Education Secondary, 9- or 11-years 741 (15.74%) 22 (5.91%)
Professional school 1,806 (38.36%) 103 (27.69%)
Degree / some university 1,983 (42.12%) 218 (58.60%)
Second degree / PhD 177 (3.76%) 29 (7.80%)
Position in company Blue-collar workers 2,570 (54.59%) 132 (35.48%)
White-collar specialists 1,236 (26.25%) 134 (36.02%)
Mid-level managers 612 (13.00%) 73 (19.62%)
High-level managers 290 (6.16%) 33 (8.87%)
Procedure
Data were collected using an anonymous computerized survey. HR managers of each division approached employees, asking them to participate in an anonymous research survey of psychological climate in the organization conducted by an independent research team. The survey was carried out on dedicated computerized workplaces, in isolated rooms. In order to control for position effects, the questionnaires were presented in random order to each participant. The response rate was more than 80% of permanent staff.
Instruments
We used four measures of personality resources:
Brief Hardiness Test (Osin, Rasskazova, 2013), based on PVS-III (Maddi, Khoshaba, 2001), a 24-item measure with a four-point response scale, comprised by items tapping into three constructive beliefs, commitment (a preference for active participation in the whatever is going on), control (a belief that one is able to influence the outcome of events), and challenge (a tendency to view problems and adversity as learning opportunities rather than as threats to be avoided at all costs) (a = .91).
Dispositional Optimism Test (Gordeeva, Osin, Sychev, 2010) based on Life Orientations Test (Scheier, Carver, 1985) with eight items reflecting generalized positive expectations about the future and life in general. We used five-point response scale for this study (a = .86).
Brief Ambiguity Tolerance Scale, based on MSTAT-I (McLain, 1993; Lukovitskaya, 1998; Osin, 2010), which measures acceptance of and attraction to ambiguous (new, unpredictable or complex) stimuli. Nine items (8, 10, 12, 14, 16, 17, 18, 19, 22) with high factor loadings reflecting different facets of the construct were chosen from the Russian version of MSTAT-I and administered with a five-point response scale. In the present sample, one item (16) failed to show a significant factor loading and was removed. After adding an error covariance for two reverse-scored items, a single-
factor model fit the data well (MLM: /(19) = 244.72, p < .001, CFI = .963, RMSEA = .050 [.045-.056], SRMR = .026) (a = .77).
Generalized Self-Efficacy Scale (Schwarzer, Jerusalem, 1995; Schwarzer, Jerusalem, Romek, 1996), a 10-item instrument with a four-point response scale measuring perceived belief in one's ability to achieve one's goals and cope with difficulties (a = .91).
To measure work motivation, we used the Professional Motivation Questionnaire (Osin, Ivanova, Gordeeva, 2013) based on Self-Determination Theory (SDT) with a five-point response scale and indices of intrinsic motivation (a = .93), identified extrinsic motivation (a = .86), external extrinsic motivation (a = .82), and amotivation (a = .64). According to SDT, intrinsic and identified extrinsic motivation are autonomous forms of motivation, whereas external extrinsic motivation is a controlled one. Amotivation can also be considered as a controlled form of motivation in situations when the activity is already being carried out by the subject without his/her conscious engagement.
Because of their simplex structure, questionnaires based on the SDT model permit three types of scoring (Sheldon et al., 2017; Osin et al., 2017): using the scales independently, calculating the general indices of autonomous and controlled motivation, or calculating the Relative Autonomy Index (RAI), which reflects the overall quality of motivation (a relative dominance of autonomous motivation over controlled motivation) and is complemented by the mean score across the scales, which may be interpreted as motivation strength or acquiescence. The latter two scoring models are mathematically equivalent in terms of the variance they capture.
To calculate the RAI, we first mean-centered the scores on the motivation scale based on individual mean and inverted the controlled motivation items; the resulting index was reliable (a = .91). The indices of autonomous motivation (a = .90) and controlled motivation (a = .81) were calculated as averages across autonomous and non-inverted controlled motivation items.
To measure workplace well-being, we used several measures:
Satisfaction with Life Scale (SWLS: Diener, Emmons, Larsen, Griffin, 1985; Russian version by D. Leontiev: see Osin, Leontiev, 2008). Includes five items reflecting a positive cognitive evaluation of one's life as a whole, rated on a five-point scale (a = .83).
Utrecht Work Engagement Scale (UWES: Schaufeli, Bakker, 2003; Lovakov, Agadullina, Schaufeli, 2017). The short version of the scale includes nine items rated on a seven-point scale and tapping into three dimensions of work engagement, vigor, dedication, and absorption. In the present study, we excluded one item ("I get carried away when I'm working") at the request of HR specialists, because the Russian formulation was perceived literally by employees with low levels of education. We only used the general index of work engagement (a = .94).
Job Satisfaction Scale (JSS: Ivanova, Rasskazova, Osin, 2013). Comprised of 19 items rated on a five-point scale, this instrument measures satisfaction with salary (a = .86), work conditions and organization (a = .74), management (a = .66), colleagues (a = .76), and job process and content (a = .83). An overall index of job satisfaction can also be calculated (a = .88).
Organization Commitment Questionnaire (OCQ: Porter, Smith, 1970; Russian version by Dominyak, 2006). The measure contains 15 items rated on a seven-point scale (a = .85).
Brief Work-Life Balance Scale (BWLBS: Mospan, 2014; based on Hayman, 2005). This brief instrument includes seven items rated on a five-point response scale comprising two dimensions measuring perceived lack of work-life balance: work interferes with life, or work/life imbalance (a = .90) and life interferes with work, or life/work imbalance (a = .83).
Results
During the preliminary data quality checks we excluded the responses of individuals who gave the same answer to all the items of the Professional Motivation Scale (N = 73) or two or more measures of personality resources (N = 371), resulting in N = 4298. Next, we investigated the associations of personality resources with work motivation indices. The resulting correlations are shown in Table 2.
Table 2. Pearson correlations of personality resources and work motivation scales (N = 4,298)
Variables 123456789 10
1. Optimism 2. Self-Efficacy 3. Tolerance for Ambiguity 4. Hardiness .45 .31 .59 .42 .52 .35
5. Intrinsic motivation .27 .22 .16 .39
6. Identified regulation .32 .23 .21 .38 .65
7. External regulation - .37 - .21 - .23 - .46 - .38 - .36
8. Amotivation - .32 - .15 - .12 - .43 - .43 - .38 .56
9. Autonomous motivation .32 .25 .21 .42 .85 .95 - .40 - .44
10. Controlled motivation - .39 - .21 - .21 - .50 - .45 - .41 .92 .83 - .47
11. RAI .42 .27 .25 .54 .77 .80 - .76 - .73 .87
Note: all the coefficients are significant at p < .001.
All the four measures of personality resources showed positive and significant intercorrelations. To test whether these four scales could be treated as indicators of a single factor, we tested a simple single-factor CFA model (Mplus 7.4, MLM estimator), which showed acceptable fit (x2(2) = 118.23, CFI = .970, RMSEA = .115, SRMR = .030). Hardiness exhibited the strongest loading on the common factor (R2 = .63, A = .80), followed by optimism (R2 = .51, A = .71), self-efficacy (R2 = .44, A = .67), and tolerance for ambiguity (R2 = .23, A = .48). We used regression-based factor score estimates in subsequent analyses where we treated personality resources as a single dimension.
To confirm the validity of the Relative Autonomy Index (RAI), we tested a measurement model (model 1) with four first-order factors corresponding to different motivation types, an alternative model with a single second-order factor (model 2), and two bifactor models (Howard et al., 2016) with four uncorrelated specific factors corresponding to different motivation types and either a single global factor (RAI, model 3) or two correlated global factors (autonomous and controlled motivation, model 4).
The fit indices for all the models tested are shown in Table 3. Both bifactor models fit the data well with better practical fit indices than those shown by the measurement model and the alternative model. The parameters of the two resulting bifactor models are presented on Figure 1. The loadings of variables on the two global factors were statistically significant in both models, supporting the validity of the RAI and of autonomous and controlled motivation indices.
Table 3. Structural models for the 16-item Professional Motivation Questionnaire
Model X2(df), p CFI RMSEA (90% CI) SRMR
1. Four first-order factors 1305.91 (96), p < .001 .962 .052 (.050-.055) .044
2. Single second-order factor 1886.88 (98), p < .001 .943 .063 (.060-.065) .064
3. Bifactor model (4 + 1 factors) 1245.38 (86), p < .001 .963 .054 (.051-.057) .055
4. Bifactor model (4 + 2 factors) 751.92 (85), p < .001 .979 .041 (.038-.044) .036
Personality resources showed weak to moderate positive associations with autonomous motivation, as well as the RAI, and negative associations of similar magnitude with controlled motivation (see Table 2). To investigate whether these effects of personality resources were due to their shared variance or peculiar to certain resources, we performed a series of multiple regression analyses comparing the variance explained by the general factor of personality resources and the four individual scales comprising it (the tolerance values were above .56 for all variables, suggesting acceptable amount of multicollinearity).
Note. IM - intrinsic motivation, IDM - identified regulation, EM - external regulation, AM - amotivation, AUT - autonomous motivation,
CON - controlled motivation, RAI - Relative Autonomy Index.
Figure 1. Standardized parameters of the bifactor models three (left) and four (right)
The results of these analyses are provided in Table 4. The amount of variance of autonomous motivation explained by the individual personality resources was comparable to that explained by the general factor. However, in the case of controlled motivation and the RAI individual personality captured a larger amount of variance, compared to the general factor. For these criteria we found a paradoxical effect of self-efficacy (discussed below). Consistent with its highest loading on the common factor, hardiness emerged as the strongest predictor of work motivation variables, but the contributions of the other three resource variables were also significant.
Table 4. Personality resources as predictors of work motivation
Autonomous motivation Controlled motivation RAI
Model 1, R2 .19*** .28*** .31***
fi, Optimism 11*** _ 17*** .16***
fi, Self-Efficacy .00 .12*** - .07***
fi, Tolerance for Ambiguity .06*** - .05** .06***
fi, Hardiness .34*** - .45*** .46***
Model 2, R2 .18*** .23*** .27***
fi, PR Factor .42*** - .47*** .52***
Note: *** p < .001, **p < .01.
We proceeded by investigating the associations of personality resources and work motivation with dependent variables. Because the effects of the two autonomous and of the two controlled motivation types were substantially similar, for brevity we only used summary indices of autonomous and controlled motivation. The resulting correlations are presented in Table 5.
Table 5. Zero-order correlations of personality resources and work motivation with outcome variables
PR Optimism Self-efficacy Toler. for ambig. Hardiness AM CM RAI
SWLS: Life Satisfaction .41 .36 .22 .13 .42 .41 - .28 .40
BWLBS: Work/life - .25 - .19 - .12 .02x - .32 - .24 .26 - .29
BWLBS: Life/work - .31 - .25 - .15 - .04x - .36 - .17 .33 - .29
OCQ: Commitment .41 .35 .23 .15 .41 .68 - .42 .64
UWES: Engagement .42 .33 .28 .21 .41 .56 - .37 .55
JSS: Salary .21 .18 .05 .07 .24 .45 - .22 .40
JSS: Work conditions .37 .33 .17 .13 .39 .54 - .34 .52
JSS: Management .40 .31 .20 .12 .45 .43 - .35 .46
JSS: Colleagues .41 .31 .31 .14 .40 .33 - .26 .35
JSS: Work process .49 .36 .33 .28 .46 .70 - .43 .67
JSS: Total .50 .41 .28 .21 .52 .71 - .45 .68
Note: all the associations, except for those marked x, are significant at p < .001. PR = personality resources factor, AM = autonomous motivation, CM = controlled motivation, RAI = Relative Autonomy Index.
The associations of various personality resources with the outcome variables were all in the same direction, consistent with the theoretical expectations (except for the two non-significant associations of tolerance for ambiguity with work-life balance). The effects for hardiness were generally the strongest and comparable in magnitude to the effects exhibited by the general factor of personality resources. Autonomous motivation and the RAI were consistently associated with well-being, whereas controlled motivation was consistently associated with ill-being. Predictably, the associations of work motivation with domain-specific well-being measures (organizational commitment, work engagement, job satisfaction) were stronger than the corresponding effects of personality resources.
Finally, to test the interactive effects of personality resources and work motivation we tested a series of moderated mediation models (Preacher, Rucker, Hayes, 2007) in Mplus. In these models (see Figure 2), the effect of personality resources on the outcome variable was mediated by autonomous and controlled motivation and two corresponding interaction terms between personality resources and motivation were entered (Preacher et al., Model 1). Predictors were centered prior to analysis and the error terms of autonomous and controlled motivation were allowed to covary with each other and with their respective interaction terms, resulting in saturated models.
Figure 2. The prototypical moderated mediation model
The same prototypical model was tested for each dependent variable in turn. The standardized estimates of the effects or personality resources on autonomous and controlled motivation, PA and PC, were .42 and — .47, respectively, in all models. The standardized estimates of the five effects of predictors on each dependent variable are shown in Table 6. To test the significance of the interaction effects we used Wald test comparing the saturated model with a more restrictive one, where both regression coefficients of the interaction terms were constrained to zero.
To evaluate the proportion of personality resource variance mediated by work motivation for each dependent variable, we calculated PM (see Preacher & Kelley, 2011), the ratio of the total indirect effect of personality resources on the DV ([A * [AM + [C * [CM) to the total effect (sum of the direct and all the indirect effects). The significance of the total indirect effect is given in the PM column.
Table 6. Parameter estimates of the moderated mediation models
Dependent Predictor, ß R2 PM Wald test, x2(2)
variable PR AM CM PR x AM PR x CM
SWLS .28*** .29*** - .01 .02 .02 .24*** .31*** 2.28
BWLBS: Work - .14*** - .13*** .13*** .06** - .06** .10*** .46*** 11.76**
BWLBS: Life -.20*** .03 .25*** .08*** - .09*** .15*** .34*** 27.65***
OCQ .13*** .59*** - .07*** .08*** .03 .49*** .68*** 26.45***
UWES .20*** .48*** - .07*** .02 .04* .37*** .52*** 16.12***
JSS: Salary .02 .45*** - .01 .08*** .03 .21*** .90*** 21.65***
JSS: Condit. 17*** .46*** - .05** .05** - .01 .33*** .56*** 14.38***
JSS: Manag. .24*** .28*** - 11*** .07*** .03* .26*** .41*** 17.24***
JSS: Colleagues .33*** .19*** - .02 .03 - .01 .20*** .21*** 5.13
JSS: Process .21*** .58*** - .06*** .02 .00 .54*** .56*** 1.91
JSS: Total .23*** .59*** - .06*** .06*** .01 .56*** .54*** 16.99***
Note: *** p < .001, ** p < .01, * p < .05. PR - Personality resources factor, AM - autonomous motivation, CM - controlled motivation. AR2 -difference in variance explained by the models with and without the two interaction terms.
Personality resources and work motivation characteristics emerged as significant independent predictors of all outcome variables, except for life/work imbalance and satisfaction with salary. Predictably, the effects of work motivation were generally stronger for domain-specific dependent
variables (organizational commitment, work engagement, job satisfaction). The direction of main effects of personality resources and work motivation was consistent with the expectations (positive effects for personality resources and autonomous motivation and negative effects of controlled motivation on well-being variables, and vice versa for the only two ill-being variables, namely, BWLBS subscales).
The interaction effects of personality resources and work motivation emerged as significant for most variables, except for satisfaction with life, colleagues, and work process. The effects of the interaction term of personality resources and autonomous motivation were positive for the well-being variables and negative for ill-being variables, suggesting that employees with high levels of personality resources and high levels of autonomous work motivation in combination are more likely to be committed to the organization, satisfied with their salary, management, as well as work conditions, and tend to experience lower levels of conflict between the demands of their job and personal life. The effects of the interaction term of personality resources and controlled motivation were weaker and in the same direction (opposite to that of the main effects of controlled motivation), indicating that in employees with high levels of personality resources the negative main effects of controlled motivation on work engagement, satisfaction with management, and work-life balance are less pronounced.
Discussion
The findings of correlational analyses and confirmatory factor analyses indicate that personality resources are positively interrelated, with hardiness showing the strongest contribution to the common factor and tolerance for ambiguity being the most distinct from the other three variables. This finding is in line with the hypothesis about the systemic organization of personality resources proposed by the personality potential theory. Indeed, the very fact that different constructive beliefs tend to come together is not new and hardly surprising. However, it suggests that existing integral conceptions of personality resources (such as psychological capital or core self-evaluations) based on this empirical fact should only be seen as first steps towards more comprehensive theoretical models that would explain the similarities and the differences between various resource variables and their respective effects on well-being and performance in various contexts.
We found that personality resources are positively associated with autonomous work motivation, suggesting that employees with higher levels of hardiness, optimism, tolerance for ambiguity, and self-efficacy may find it easier to discover something of interest in their work process or to find a personal meaning of their work (i.e., integrate their work motivation). Another potential cause of these associations could be a selection effect: employees with higher levels of personality resources might be more likely to get promoted to higher positions based on their performance and might be more active in abandoning controlled and dissatisfying job settings to engage in more autonomously motivated and personally satisfying jobs. In contrast, individuals with lower levels of personality resources may be more likely to get stuck in jobs that they do not enjoy but lack the courage or motivation to change. Personality resources were positively associated with hierarchical position in company (r = .16, p < .001) and inversely associated with the number of years spent working in the same position (r = - .15, p < .001); these associations remained significant after controlling for employee age (r = .16 and r = - .08, respectively, p < .001), suggesting that both effects may take place. Longitudinal studies are needed to disentangle them reliably. We interpret these findings as evidence of the motivational function of personality resources.
Because we used existing measures of personality resources modelled as observed variables, differences in measurement reliability and in response bias, such as acquiescence, may have
contributed to the picture. Thus, we believe that the paradoxical effect of self-efficacy on motivation may be explained by response bias. The other three scales include a sizeable proportion of reverse-scored items (70.1%, 50%, and 25% for the hardiness, optimism, and tolerance for ambiguity measures, respectively), whereas the self-efficacy scale is the only one to be comprised entirely by non-reverse-scored items; hence, its unique variance (non-shared with the other three personality resources) may also include the effects of response bias. Because controlled motivation items are, essentially, reverse-scored, it is not surprising that only the unique (acquiescence) variance of self-efficacy shows a positive association here. Future studies could develop dedicated balanced measures of personality resources and of dependent variables in order to reliably separate the specific variance of different personality resources from item direction effects. Rigorous approach to data screening and measures to control for social desirability could further refine the findings.
The interaction effects of personality resources and work motivation suggest that variables from these two groups may have synergistic effects on workplace well-being outcomes. As a tentative causal interpretation, we believe that personality resources may be utilized more actively by autonomously motivated individuals, leading to more satisfying outcomes. In turn, personality resources may buffer against the detrimental effects of controlled motivation on well-being outcomes by enabling individuals to cope better even with work that is rather boring or meaningless. The effect sizes for these moderation effects were not strong: Cohen's f2 ranged from .003 to .010 for significant effects (median f = .005). However these effect sizes even exceed those typically found in applied psychology studies (Aguinis, Beaty, Boik, Pierce, 2005) and suggest that large samples are needed to detect them with sufficient statistical power.
Study 2
Study 2 aimed to extend the findings of Study 1 by using a prospective design. We intended to explore two research questions: 1) Do personality resources predict sustained autonomous motivation? 2) Do personality resources and work motivation exhibit interactive effects in predicting well-being in the long term?
Methods
Sample and procedure
The sample was comprised by respondents who participated in a follow-up study two years later, following a change of company CEO and the management team. The second study had the same aims and procedure. Because the survey was anonymous, no identifiers were provided by the respondents and we matched individual scores across two occasions based on a combination of demographic characteristics. Only the data of respondents who could be matched unambiguously (N= 372) were retained for longitudinal analyses. Based on the same screening procedure as in Study 1, data of 27 respondents were excluded, resulting in the remaining sample size of N = 345.
Instruments
The Time 1 (T1) instruments measuring personality resources are described in Study 1 above. Below we describe the scales used at Time 2 (T2). As the longitudinal design was not envisioned initially, some versions of the instruments differed at T1 and T2 and we only used subsets of items with exactly the same formulations at both measurement occasions. The reliabilities of all the resulting measures at both occasions are given in Table 7.
Satisfaction with Life Scale (SWLS: Diener et al., 1985; Russian version: Osin, Leontiev, 2008) and Utrecht Work Engagement Scale (UWES: Schaufeli; Russian version: Kutuzova) were the same as in Study 1.
Professional Motivation Questionnaire. The revised version (Osin et al., 2017) of the measure contained only 3 intrinsic motivation (IM) items ("...because I like my work", "...because I find the process of my work interesting", ".because I enjoy working here") and 2 external regulation (EM) items (".because I have no choice but to work here", ".because I am afraid I won't find another job") from the old version used at T1.
Organizational Commitment Questionnaire. Items 2, 5, 6, and 8 from the Organizational Commitment Questionnaire (Mowday, Steers, Porter, 1979) were chosen for the follow-up study based on their factor loadings and substantive content.
Job Satisfaction Scale. The revised version of the measure (Ivanova, Osin, Rasskazova, in preparation) contained 17 out of 19 items administered at T1. Two items were dropped from the subscale measuring satisfaction with job conditions.
Results
The scale reliabilities and differences between the scores at two measurement occasions are summarized in Table 7. The data reflected a decrease in intrinsic motivation, satisfaction with salary, management, and work process, combined with an increase in extrinsic motivation (attributed to background effects). The sizes of these effects, however, are small (d < .30).
Table 7. Reliabilities and descriptive statistics across two measurement occasions (N=372)
Scale No. items a 2011 M (SD) a 2013 M (SD) Student t Cohen's d
SWLS 5 .83 3.90 (1.03) .87 3.94 (1.11) .74 .04
UWES 8 .95 4.25 (1.60) .94 4.15 (1.51) 1.17 - .06
IM 3 .94 3.90 (0.96) .91 3.75 (1.01) 2.75** - .15
EM 2 .78 2.10 (1.09) .68 2.31 (1.04) 3.69*** .20
JSS: Salary 4 .88 2.90 (0.96) .92 2.77 (1.05) 2.75** - .14
JSS: Conditions 2 .67 3.28 (0.97) .74 3.28 (1.02) .11 .01
JSS: Management 3 .64 3.59 (0.84) .65 3.43 (0.87) 3.81*** - .20
JSS: Colleagues 3 .81 4.27 (0.54) .76 4.24 (0.56) .99 - .05
JSS: Work Process 5 .84 3.96 (0.69) .85 3.74 (0.73) 5.65*** - .30
Org. Commitment 4 .81 4.25 (1.12) .90 4.17 (1.30) 1.38 - .07
Note: *** p < .001, ** p < .01.
We proceeded by testing a series of multiple regression models. First, we tested the models where personality resources at T1 predicted change in motivation scores from T1 to T2. To do this, we entered the scores on dependent variable at T1 as a predictor at the first step, followed by the T1 latent score estimate for the personality resources factor at the second step, in order to see if it would capture additional variance.
The results are summarized in Table 8. Higher level of personality resources at T1 predicted an increase in intrinsic motivation and a decrease in external regulation at T2, as well as increase in work engagement, satisfaction with colleagues, and satisfaction with work process. Additional analyses revealed that these effects of personality resources on work motivation were mostly associated with hardiness.
At the next step we investigated whether personality resources and work motivation characteristics at T1 would exhibit interactive effects in predicting the same set of dependent variables at T2. We entered the T1 score on the dependent variable at step 1, followed by T1 personality resources and work motivation variables at Step 2, and two interaction terms between
personality resources and work motivation at Step 3. To avoid multicollinearity, the predictors were centered prior to calculation of the interaction terms.
Table 8. Personality resources at T1 predicting change in dependent variables
Dependent variable (T2) AR2 T1 DV, ß AR2 T1 DV, ß T1 PR, ß
Satisfaction with Life .244*** .49*** .003 .46*** .06
Intrinsic motivation .246*** .50*** .020** .44*** .15**
External regulation .244*** .49*** .020** .42*** - .16**
UWES Work Engagement .244*** .49*** .010* .45*** .11*
Organizational Commitment .318*** .56*** .003 .54*** .06
JSS: Salary .273*** .52*** .000 .53*** - .01
JSS: Work Conditions .323*** .57*** .000 .57*** .01
JSS: Management .268*** .52*** .001 .51*** .04
JSS: Colleagues .150*** .39*** .036*** .30*** .21***
JSS: Work Process .249*** .50*** .010* .44*** .12*
JSS: Total .353 .59*** .000 .59*** .01
Note: *** p < .001, ** p < .01, * p < .05. DV Dependent variable, PR = personality resources factor.
The results are presented in Table 9. In line with the previous analysis, personality resources predicted an increase in satisfaction with colleagues. Controlling for the differences in personality resources, autonomous motivation predicted increased work engagement, satisfaction with the process of work, and satisfaction with work conditions two years later. Because we failed to find any significant effects for the interaction terms, the results of Step 3 are not shown.
Table 9. Personality resources and work motivation at T1 predicting change in dependent variables
Dependent variable
Step 1
Step 2
T2 AR2 T1 DV, ß AR2 T1 DV, ß T1 PR, ß T1 AUT, ß T1 CON, ß
Satisfaction with Life .244*** .49*** .006 .44*** .06 .06 .02
Work Engagement .244*** .49*** .064*** .31*** .05 .28*** - .02
Org.Commitment .318*** .56*** .008 .49*** .03 .09 - .02
JSS: Salary .273*** .52*** .007 .49*** - .05 .09 - .02
JSS: Work Conditions .323*** .57*** .019* .51*** - .06 .14* - .05
JSS: Management .268*** .52*** .011 .47*** - .02 .04 - .11
JSS: Colleagues .150*** .39*** .044*** .28*** .16** .06 - .07
JSS: Work Process .249*** .50*** .043*** .27*** .07 .23** - .07
JSS: Total .353*** .59*** .007 .52*** - .02 .08 .06
Note: *** p < .001, ** p < .01, * p < .05.
Discussion
The findings of the longitudinal study corroborate the Study 1 results showing the motivational function of personality resources. We found that individuals with higher levels of personality resources at the outset were more likely to maintain their intrinsic work motivation in the long term and less likely to develop external regulation two years later. These individuals were also more likely to remain engaged into their work process and satisfied with it, enjoying their relationships with colleagues. These effects of personality resources were particularly evident against the general backdrop of decreasing workplace well-being due to organizational change and other potential background effects. These findings are reminiscent of the results obtained by S. Maddi in the Illinois
Bell study (Maddi, 2002) and suggest that interventions aimed at the development of personality resources (in particular, hardiness) may indeed make employees more resilient in stressful settings.
Controlling for personality resources, we also found that employees who were autonomously motivated at Time 1 were more likely to remain engaged into their work and satisfied with it two years later. These findings were limited by the modest measurement reliability of our reduced measures (particularly, some subscales of the Job Satisfaction Scale and external regulation scale based on overlapping items chosen from two different versions of the Professional Motivation Questionnaire). The fact that we failed to find any significant interaction effects of personality resources with work motivation is hardly suprising, given the relatively small sizes of these effects in combination with the modest Study 2 sample size. Unfortunately, these limitations were hardly avoidable, given that a longitudinal design was not envisioned at the outset.
Future studies could overcome these limitations by planning for longitudinal comparisons and utilizing more rigorous procedures to ensure respondent identification (while preserving anonymity). In order to test for the mediation of the effects of personality resources by work motivation, a longitudinal design with three measurements, albeit at shorter temporal intervals, would be preferable.
General discussion
The findings of the two studies described above indicate that personality resources may facilitate sustained and productive work motivation even under stressful settings associated with an overall decline of well-being. The measures of personality resources that we used are general, rather than domain-specific, like psychological capital. In Study 1 we found that hardiness, optimism, and generalized self-efficacy share 44 to 63% of their individual variance, with tolerance for ambiguity being more distinct.
The effects of these variables were typically similar and we focused on the general effects of personality resources by treating them as a single latent dimension. The differences in the effects of these variables that we discovered in multiple regression analyses can be explained either by differences in the constructs or measurement procedures. In order to reliably separate the common variance of personality resources from their specific variance, new, more refined measures are needed, to control for unequal reliability and response bias.
The specific mechanisms of these effects of personality resources on work motivation need to be clarified in future theoretical and empirical work. Does autonomous work motivation emerge as a result of more active interaction with the work environment facilitated by personality resources, enabling individuals to find more interest in their jobs and to satisfy their basic psychological needs? Can personality resources facilitate cognitive integration of work motivation, leading to a more positive functioning even under controlling settings? Do personality resources protect individuals from the harmful effects of need-thwarting factors by means of active coping or cognitive restructuring? These questions call for future research, placing the effects and variables described within Self-Determination Theory into a larger nomological network of personality resource variables.
The limitations of the studies include the use of self-report measures and, in case of Study 2, modest sample size, resulting in low power to discover the interaction effects found in Study 1. However, we believe that the two studies presented constitute a sound preliminary evidence in favour of the positive effects of the combination of personality resources and work motivation and call for more investigation using various organizational settings, measures, and more rigorous research designs.
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ОРГАНИЗАЦИОННАЯ ПСИХОЛОГИЯ
Личностные ресурсы и профессиональная мотивация: Позитивное взаимодействие
ОСИН Евгений Николаевич ИВАНОВА Татьяна Юрьевна ОРЁЛ Екатерина Алексеевна РАССКАЗОВА Елена Игоревна
Национальный исследовательский университет ««Высшая школа экономики», Москва, Россия
Аннотация. Цель. Исследование посвящено изучению мотивационной функции личностных ресурсов в организационном контексте. Опираясь на модель личностного потенциала (Леонтьев, 2011) и теорию самодетерминации, мы предположили, что личностные ресурсы способствуют поддержанию продуктивного характера мотивации и взаимодействию с рабочей средой, приводя к позитивным последствиям для индивидов и организаций. Мы проверяли три предположения: 1) о позитивном вкладе личностных ресурсов в автономную мотивацию и негативном вкладе в контролируемую мотивацию, 2) о том, что трудовая мотивация выступает медиатором влияния личностных ресурсов на благополучие на рабочем месте, 3) о том, что комбинация личностных ресурсов и профессиональной мотивации связана с позитивными последствиями для благополучия на рабочем месте. Дизайн. Мы использовали данные двух выборок сотрудников российского производственного предприятия со срезовым дизайном (Ы = 4708) и лонгитюдным дизайном (Ы = 372) с двухлетним интервалом между замерами. Респонденты заполняли опросники личностных ресурсов (жизнестойкость, диспозициональный оптимизм, общая самоэффективность, толерантность к неопределённости), трудовой мотивации и благополучия на рабочем месте (удовлетворённость жизнью и работой, баланс работы и личной жизни, увлечённость работой, приверженность организации). Результаты. Единый фактор личностных ресурсов оказался позитивным предиктором автономной и негативным предиктором контролируемой мотивации как в срезовой, так и в лонгитюдной перспективе. Динамика благополучия на протяжении двух лет была связана с уровнем автономной мотивации на первом замере. Трудовая мотивация выступила частичным медиатором эффектов личностных ресурсов на показатели благополучия и продемонстрировала ряд ожидаемых эффектов взаимодействия в предсказании показателей баланса работы и жизни, удовлетворённости трудом и приверженности организации. Ценность результатов. Результаты свидетельствуют о мотивационной функции личностных ресурсов.
Ключевые слова: теория самодетерминации; жизнестойкость; благополучие сотрудников; увлечённость работой; удовлетворённость трудом.
Статья подготовлена при поддержке РФФИ, проект № 15-06-10933 «Личностные, мотивационные и организационные ресурсы психологического благополучия в профессиональной деятельности».
Адрес: 100101, Москва, ул. Мясницкая, 20 E-mail: evgeny.n.osin@gmail.com
