Social Power May Enhance Workplace Initiative: An Experimental Investigation Among Two Samples

Abstract

Organizational citizenship behavior (OCB) refers to voluntary actions members take to benefit organizational function. However, the benefits of OCB for organizations are sometimes countered by detriments for employees who exhibit them, resulting in threats to organizational members’ psychological wellbeing. The present research examined whether social power—the perceived ability to control allocations and outcomes in a social hierarchy—could increase OCB endorsement while buffering against negative personal costs. Indeed, manipulated social power enhanced OCB endorsement. This effect was mediated by increased positive affect and goal seeking among participants assigned to a high-power condition relative to participants assigned to a low-power condition. Further, participants assigned to a high-power (vs. low-power) condition did not report increased occupational burden despite their greater OCB endorsement. Patterns of results were similar among a sample of community members (N = 149; M_age = 37 years) and a sample of university students (N = 129; M_age = 20 years). Organizations might empower members by employing procedural justice principles that facilitate members’ meaningful contributions to workplace operations.

Keywords

social power organizational citizenship behavior (OCB)initiative affect goal seeking

Organizational citizenship behavior (OCB) refers to non-compensated activities performed by organizational members who act beyond their obligated job responsibilities (Organ, 1997). OCB promotes organizational effectiveness and efficiency, and contributes to a positive workplace culture that can attract and maintain a satisfied workforce (Kataria et al., 2013). However, the benefits of OCB for the organization are sometimes offset by detriments for employees who exhibit them: Employees who consistently take initiative on activities not formally recognized or rewarded by the organization can experience negative affect and become burdened by stress, work-family conflict, and role overload (sometimes referred to as good soldier syndrome; Bolino et al., 2015; Bolino & Turnley, 2005; Deery et al., 2017; Lavy, 2019; Organ, 1988). Organizations have an interest in developing interventions that limit the negative effects of OCB as a means of both promoting organizational effectiveness and employee wellbeing. Social power—that is, the extent to which employees feel that they can influence others and control their own outcomes (Magee & Galinsky, 2008)—might be a suitable target for such interventions. Feelings of social power are positively associated with positive affect (Keltner et al., 2003; Livingston, Cummings, et al., 2024) and goal seeking (Guinote, 2017), each of which might enhance employee initiative and protect against occupational burden. This study examined the effect of social power on OCB endorsement and tested positive affect and goal seeking as explanatory pathways.

Organizational Citizenship Behavior

OCB benefits organizations through at least two pathways: First, OCB can enhance organizational effectiveness by bolstering employee participation in organizational efforts (Kataria et al., 2013; Posdakoff & MacKenzie, 1997). Second, OCB contributes to the social capital among organizational members, facilitating a culture of cooperation and trust (Baker & Dutton, 2007; Coleman, 1988; Williams & Anderson, 1991). These corollaries of OCB can enhance an organization’s productivity and culture.

Organizational Effectiveness

Employees who engage in OCB facilitate a more effective organization (Kataria et al., 2013). Early correlational investigations of this hypothesis suggested that evaluators more frequently observed OCB (e.g., individual initiative-taking, representing the organization in a positive manner) among members of higher-performing versus lower-performing workplace teams (Karambayya, 1990). These findings inspired a deluge of more complex research studies that replicated and extended these effects among employees from diverse industries (for review, Posdakoff et al., 2000). Such studies assessed more objective outcomes such as sales performance (Posdakoff & Mackenzie, 1994), units of product produced (Posdakoff & MacKenzie, 1997), revenue, customer satisfaction, and others (Walz & Niehoff, 2017). A meta-analysis of four such studies indicated that OCB explained 19% of the variance in the quality of organizational performance and 38% of the variance in customer satisfaction and complaints (Posdakoff et al., 2000). These findings, although still the outcome of correlational rather than experimental research designs, suggested that organizations have an interest in encouraging OCB as a means of increasing earnings and establishing a positive public-facing image. More recent studies continue to highlight these patterns (Chun et al., 2011; Jiang et al., 2017; Lavy & Littman-Ovadia, 2017; Yaakobi & Weisberg, 2020). Organizations have a clear interest in promoting OCB to enhance effectiveness.

Social Capital

Employees who engage in OCB further benefit organizations by contributing to the social capital; that is, by promoting cooperative and trusting interpersonal relationships that facilitate communal exchange of knowledge and assistance (Coleman, 1988). Voluntary membership on committees tasked with enhancing job satisfaction, advocacy on behalf of underserved employees, and simple courtesies such as refilling the shared copy machine with paper or exchanging sincere greetings are examples of OCB that strengthen social ties between organizational members (see Ariani, 2012; Baker & Dutton, 2007; Zarea, 2012). Organizations characterized by positive social capital attract talented personnel and stimulate their ingenuity (Kroll & Tantardini, 2019; Leana & Pil, 2006). It is in the financial and reputational interest of organizations to promote OCB among employees.

OCB is not without detriments to employees. Resource drain theory assumes a zero-sum relationship in the allocation of time and cognitive resources (e.g., motivation, positive affect; Edwards & Rothbard, 2000; Morris & Madsen, 2007). The bounded nature of personal resources entails that employees must divert efforts away from one arena (e.g., family time, wellness) if they wish to apply those efforts elsewhere (e.g., toward organizational goals; Deery et al., 2017; Michel et al., 2011). Although organizations benefit from OCB, employees who exceed job expectations without compensation sometimes report occupational burden in the form of elevated job stress, work-family conflict, and role overload (Bolino et al., 2015; Bolino & Turnley, 2005; Deery et al., 2017; Lavy, 2019), consistent with predictions from resource drain theory. Research should identify intervention targets that can enhance cognitive resources (e.g., goal directedness, positive affect) so that employees may allocate optimal resources toward both OCB and personal wellbeing. Such an intervention target could facilitate organizational outcomes, enhance the social capital to attract more talented and satisfied personnel, and prevent exacerbation of occupational burden. The present research tested social power as one such intervention target given its documented cognitive and affective affordances; namely, goal directedness and positive affect.

Social Power

Social power refers to the self-perceived ability to influence people and direct resources within a social hierarchy (Magee & Galinsky, 2008). Organizations often make social power salient because some members may exert control over subordinates (e.g., in task assignment or employee evaluation; Livingston, Vik, et al., 2024; Northouse, 2015; Weick & Guinote, 2008). Similarly, negotiations can affect feelings of power when one party perceives a sense of control over mutually valued resources (Magee et al., 2007). Power facilitates creativity (Galinsky et al., 2003), empathetic accuracy (Côté et al., 2011), and trust (Carney et al., 2013), liberating powerful members of organizations to pursue goal-directed behavior while promoting the interests of themselves and others. The prosocial effects of power might benefit organizational climate and protect powerholders against OCB-related burden. Positive affect and goal seeking, each of which is positively associated with power, can help to explain the hypothesized relationship between power and OCB.

Power and Affect

The approach theory of power (Keltner et al., 2003) and situated focus theory (Guinote, 2007) guide hypotheses related to the effect of power on OCB and its associated mechanisms. The approach theory of power predicts that powerful people experience more positive affect compared to their powerless counterparts, a valuable resource that disinhibits productive behavior (Peñalver et al., 2019; Zelenski et al., 2008). Power-induced positive affect can increase risk tolerance (Anderson & Galinsky, 2006), self-expression (Chen et al., 2009), and creativity (Galinsky et al., 2003; Gervais et al., 2012) in pursuit of personal and organizational goals. Indeed, power is associated with enhanced positive affect and reduced negative affect in a variety of domains including perceived health (Livingston, Cummings, et al., 2024), romantic relationships (Langner & Keltner, 2008), and workplace tasks such as negotiations (Anderson & Thompson, 2004) and allocating bonuses to employees (Anderson & Berdahl, 2002). Positive affect motivates the powerful to pursue goals with relatively little fear of failure or concern for possible negative outcomes associated with their behavior (Livingston & Davis, 2020). Power-induced positive affect could explain OCB by disinhibiting active, approach-oriented behavior (Cho & Keltner, 2020). In addition, enhanced positive affective resources resulting from power could protect employees from the occupational burden often associated with OCB.

Power and Goal Seeking

Power additionally activates goal directed thinking and behavior (Guinote, 2017). An extension of approach theory, situated focus theory (Guinote, 2007; Willis & Guinote, 2011) predicts that power systematically motivates people to want more: Because power activates thought and behavior, the theory predicts that the powerful (vs. the powerless) will articulate goals with greater precision and recruit the necessary and more plentiful cognitive resources to succeed in goal attainment (Guinote, 2017, for review). Goal seeking should in turn predict OCB.

Although predictions from situated focus theory are conceptually supported (Guinote, 2017), research is needed to empirically assess the direct relationship between power, goal seeking, and workplace outcomes. A purpose of the current study was to test a measure of goal seeking developed based on theoretical work in the domain of goal pursuit (Gollwitzer, 1996; Heckhausen & Gollwitzer, 1987). This measure allowed for a direct test of hypotheses from situated focus theory related to the effect of power on goal seeking at four stages of goal pursuit; namely, goal identification, planning, persistence, and self-evaluation of progress (Gollwitzer, 1996; Heckhausen & Gollwitzer, 1987). We assessed goal pursuit as a function of power as well as its potential to mediate the effect of power on OCB endorsement.

Study Overview

The theoretical perspectives and prior research findings outlined above informed the present study’s hypotheses. We tested conceptual models linking power to OCB endorsement through positive affect and goal seeking. That is, we expected that OCB endorsement would be significantly greater among participants assigned to a high-power condition versus a low-power condition, and that positive affect and goal seeking could explain this effect. We tested each mediator individually, then simultaneously in a parallel mediation analysis. Separate from the mediation models, we also examined the ancillary hypothesis that there would be direct effects of power to reduce occupational burden operationalized as job stress, work-family conflict, and role overload.

Given that this study tested novel hypotheses regarding a causal relationship between manipulated power and OCB endorsement, we attempted to replicate our findings among two samples—one community sample and one student sample—to examine the robustness of the present effects. Patterns of results were similar across samples. After describing the characteristics of each sample below, we report primarily on findings from the community sample given participants’ higher mean age and greater life experience relative to the student sample. We note observed instances of deviation between the samples.

Method

The study used a two-group (high-power vs. low-power) between-participants experimental design. At the onset of the study, participants received random assignment to a high-power or low-power condition. We expected the power manipulation to affect subsequent responses to quantitative measures relevant to OCB. The study was approved by the institutional review board (IRB) at a university in the southern U.S. under the approval code LIV061622.

Participants

We recruited participants from two samples to test the extent to which the hypothesized effects were reliable and generalizable among community members and university students. A sensitivity analysis performed in G*Power (Faul et al., 2007) for the primary mediation model tested among the community sample (N = 149) demonstrated that Cohen’s f² = .09 was the smallest effect our analysis could reliably detect, assuming a Type I error rate of α = .05 and a desired statistical power to detect an effect (1 – β) of .95. The observed effects on the primary parallel mediation models met this minimum effect size criterion (f²s > .55), suggesting an adequate sample size to reveal reliable effects. We cleaned each dataset by excluding participants who failed an attention check question (n_{community sample} = 3; n_{student sample} = 0) or stated outright that we should not use their data because they did not put their best effort toward completing the study (n_{community sample} = 1; n_{student sample} = 4). These quality checks allowed us to retain approximately 97% of the data from each sample. Below, we report on sample characteristics after data cleaning.

Community Sample

The community sample consisted of 149 research participants recruited via Amazon’s Mechanical Turk (MTurk) in exchange for $0.75. To qualify for the study, participants had to live in the U.S. and have recorded a 98%+ approval rate on 500+ completed human intelligence tasks (HITs). These inclusion criteria helped to protect response quality consistent with scholarship examining best practices for recruitment using MTurk (Paolacci & Chandler, 2014; Paolacci et al., 2010; Peer et al., 2014). Most participants in the community sample were men (n = 94; 63%). The mean age of the sample was 36.62 years (SD = 11.86). The majority of the sample identified as White (n = 116; 78%) followed by Black or African American (n = 7; 5%), Asian (n = 3; 2%), Hispanic or Latino/a (n = 2; 1%), and other racial/ethnic groups or mixed race (n = 21; 14%). Most participants were employed full-time (n = 137; 92%) or part-time (n = 7; 5%). A plurality of participants lived in the Southern U.S. (n = 52; 35%) followed by the Northeast (n = 42; 28%), Midwest (n = 41; 28%), and West (n = 14; 9%).

Student Sample

The student sample consisted of 129 university students who participated in exchange for course credit. To qualify for the study, participants had to be aged 18 years or older and have access to an Internet-connected device. Most participants in the university student sample were women (n = 107; 83%). The mean age of the sample was 19.67 years (SD = 4.10). The majority of the sample identified as White (n = 66; 51%) followed by Hispanic or Latino/a (n = 49; 38%), Black or African American (n = 8; 6%), Asian (n = 4; 3%), and other racial/ethnic groups or mixed race (n = 2; 2%). Most participants were employed part-time (n = 64; 50%) or full-time (n = 7; 5%).

Materials

For both samples, the Qualtrics survey platform randomly assigned participants to a high-power condition (n_community = 78; 52%; n_student = 64; 50%) or low-power condition (n_community = 71; 48%; n_student = 65; 50%). After responding to manipulation check items, participants proceeded to assessments of mediating and dependent variables. Reported measures of reliability and internal consistency from the community sample were replicated among the student sample.

Manipulation of Power

Participants viewed a figure depicting a ladder accompanied by instructions adapted from Goodman and colleagues, 2001; Livingston et al., 2024; Livingston & Burns, 2024; for similar methods that prime power, see Dubois et al., 2010; Galinsky et al., 2015). Participants received instructions to imagine that the ladder depicted how power is distributed in the workplace: People at the top of the ladder have the most power, and people at the bottom have the least. Then, participants received random assignment to a location near the top of the ladder (i.e., high-power condition) or near the bottom of the ladder (i.e., low-power condition). In the high-power condition, participants read that their position in the workplace afforded them “a lot of power” to control, influence, and evaluate others. In the low-power condition, participants read that their position in the workplace afforded them “very little power” to control, influence, and evaluate others. The appropriate figure depicting participants’ assignment to the high- or low-power condition remained visible to participants for the duration of the survey to maintain a consistent effect of the experimental manipulation. See Appendix for an example of the images and instructions.

Participants responded to a manipulation check to assess whether assignment to the high- versus low-power condition affected participants’ feelings of power. The manipulation check measure consisted of four items (i.e., “In my position on the power ladder, I can control/influence/evaluate/am powerful compared to others”; Fischer et al., 2011) each rated on a scale from 1 (not at all) to 7 (completely). The items were internally consistent and thus combined into a composite score assessing feelings of power (α = .94).

Measure of Goal Seeking

We constructed an original measure of goal seeking based on Gollwitzer and colleagues’ four phases of goal pursuit (Gollwitzer, 1996; Heckhausen & Gollwitzer, 1987). The measure consisted of 10 statements rated on a continuous scale from 1 (disagree strongly) to 7 (agree strongly). In the first phase of goal pursuit, the actor identifies preferences and decides which goals are worthy of pursuing. We included three items to measure this phase: “I have a lot of goals,” “I know exactly what I want,” and “I know what to do to achieve my goals.” In the second phase, the actor sets an intention to achieve a specific goal and plans goal-directed behavior. We included three items to measure this phase: “When I want to pursue a goal, I succeed,” “I intend to achieve,” and “I know where to begin achieving my goals.” In the third phase, the actor remains persistent until the goal is achieved. We included two items to measure this phase: “When I want something, I can make it happen” and “I do not stop until I achieve my desired outcome.” In the fourth phase, the actor evaluates their outcomes and sets new goals, if necessary. We included two items to measure this phase: “After I achieve my goal, I set a new one” and “I evaluate my progress to determine how to proceed toward my next goal.”

A Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy indicated that the relationship between the items was adequate for factor analysis (overall measure of sampling adequacy [MSA] = 0.96/1.00; acceptability cut-off ≥ 0.50; Kaiser, 1960, 1974). Factor analysis indicated that the subscales together explained 90% of the variance of the general factor. The factor loadings for each item on the general factor were greater than the 0.70 cut-off for retention (range = 0.75-0.90). High reliability for the full 10-item scale indicated that it was appropriate to combine the items into a composite score measuring goal seeking (α = .97). The measure was highly reliable among the student sample as well (MSA = 0.93; α = .94).

Positive and Negative Affect Schedule (PANAS)

The 20-item Positive and Negative Affect Schedule (PANAS; Watson et al., 1988) instructed participants to report their current affectivity considering their position on the power ladder. The scale consisted of 10 positive affect words (e.g., active, determined, excited) and 10 negative affect words (e.g., afraid, distressed, upset) presented to participants in random order. Participants reported the extent to which they felt this way on a scale from 1 (not at all) to 7 (very much). Both subscales were internally consistent and combined into composite scores measuring positive affect (α = .96) and negative affect (α = .98), respectively. Below, we report primarily on positive affect as it was most pertinent to the present hypotheses.

Individual Initiative

Participants responded to a 15-item measure of individual initiative (Bolino & Turnley, 2005) to assess OCB endorsement. The measure assesses the extent to which organizational members complete activities not required of them, but that can benefit the organization (i.e., organizational citizenship behavior; Organ, 1997). Items measured, for example, how often participants would stay at work after normal business hours, volunteer on special projects in addition to regular job duties, and participate in community activities that benefit the organization. Participants responded to each item on a scale from 1 (never) to 7 (always). The items were internally consistent and thus combined into a composite score assessing individual initiative (α = .97).

Measures of Work-Family Conflict, Job Stress, and Role Overload

Items from prior research assessed job stress, work-family conflict, and role overload, each measured on a scale from 1 (disagree strongly) to 7 (agree strongly). The measure of work-family conflict (Bolino & Turnley, 2005) consisted of 18 items and demonstrated high internal consistency (α = .96). Using item analysis, we reduced the measures of job stress (Motowidlo et al., 1986; α = .68) and role overload (Beehr et al., 1976; α = .82) by two items each to achieve adequate internal consistency for assessing each construct.

Procedure

Participants enrolled in research described as “a study assessing attitudes toward workplace behaviors.” After reading the informed consent document and agreeing to proceed, participants received random assignment to one of two experimental conditions, responded to the dependent variables in the order described above, and provided their demographic information. Participants read a debriefing statement and received compensation at the end of the survey.

Results

Data are available via the Open Science Framework (OSF; https://osf.io/jdy9x/?view_only=8db19db6c5df4f0fb6b698ba1ccb7fd9). Results reported below were observed among the community sample. Effects replicated among the student sample unless otherwise noted. All continuous variable distributions were normal with skewness and kurtosis within the range of ±2 requiring no transformation (George & Mallery, 2010). Analyses to test hypotheses included t-test, regression, and mediation (JASP Team, 2024). We report the results of Welch’s (1947) t-test to account for heterogenous variances where appropriate (Delacre et al., 2017). See Table 1 for means and standard deviations of each construct separated by sample, experimental condition, and participant gender.

Table 1.

Means and Standard Deviations of Each Construct Separated by sample, Experimental Condition (High-Power vs. Low-Power), and Participant Gender.

Measure	Community sample							Student sample
	Overall M (SD)	High-power	Low-power	p	Men	Women	p	Overall M (SD)	High-power	Low-power	p	Men	Women	p
	Overall M (SD)	M (SD)	M (SD)	p	M (SD)	M (SD)	p	Overall M (SD)	M (SD)	M (SD)	p	M (SD)	M (SD)	p
Feelings of power	5.02 (1.78)	5.73 (1.21)	4.24 (1.98)	<.001	5.18 (1.72)	4.82 (1.81)	ns	3.90 (1.95)	5.59 (0.93)	2.24 (1.05)	<.001	3.64 (1.97)	3.97 (1.95)	ns
Goal seeking	5.56 (1.29)	5.85 (0.99)	5.23 (1.51)	.004	5.67 (1.15)	5.46 (1.39)	ns	5.10 (1.31)	5.68 (0.86)	4.53 (1.42)	<.001	5.01 (1.23)	5.12 (1.33)	ns
Positive affect	5.50 (1.40)	5.86 (1.08)	5.09 (1.60)	<.001	5.54 (1.34)	5.50 (1.40)	ns	4.85 (1.65)	6.04 (0.79)	3.67 (1.41)	<.001	4.51 (1.47)	4.92 (1.69)	ns
Negative affect	3.82 (2.08)	3.65 (2.15)	4.00 (2.01)	ns	4.25 (2.11)	3.07 (1.85)	<.001	3.15 (1.31)	2.93 (1.06)	3.36 (1.50)	ns	2.91 (1.24)	3.21 (1.32)	ns
Individual initiative	5.27 (1.37)	5.49 (1.19)	5.04 (1.52)	.04	5.32 (1.43)	5.17 (1.28)	ns	4.19 (1.58)	4.87 (1.26)	3.53 (1.60)	<.001	3.67 (1.67)	4.29 (1.56)	ns
Job stress	5.35 (1.26)	5.51 (1.21)	5.16 (1.30)	ns	5.39 (1.28)	5.23 (1.22)	ns	4.97 (1.61)	5.79 (1.01)	4.17 (1.69)	<.001	4.55 (1.56)	5.07 (1.61)	ns
Work-family conflict	5.11 (1.26)	5.22 (1.31)	5.00 (1.21)	ns	5.26 (1.26)	4.86 (1.25)	ns	4.03 (0.94)	3.97 (0.86)	4.09 (1.02)	ns	3.89 (1.14)	4.06 (0.91)	ns
Role overload	5.34 (1.23)	5.37 (1.33)	5.32 (1.11)	ns	5.43 (1.23)	5.17 (1.21)	ns	4.20 (1.32)	4.17 (1.15)	4.22 (1.47)	ns	3.79 (1.03)	4.29 (1.36)	ns

Note. — All items measured on a 7-point scale. All measures were normally distributed with skewness within the range of ±2 and kurtosis within the range of ±7 requiring no transformation (Byrne, 2010; Hair et al., 2010). Reported p-values represent results of t-tests comparing means between high-power versus low-power conditions and women versus men, respectively. ns indicates p > .05.

Manipulation Check

An independent samples t-test examined whether the experimental manipulation affected participants’ feelings of power (Welch’s t(113.43) = 5.50, p < .001, d = 0.91). As expected, participants assigned to the high-power condition reported greater feelings of power (M = 5.73, SD = 1.21) compared to participants assigned to the low-power condition (M = 4.24, SD = 1.98). The experimental manipulation was effective.

Mediation Analyses

Mediation analysis performed using Lavaan (Rosseel, 2012) tested the hypotheses that power would increase individual initiative (a measure of OCB endorsement), and that positive affect and goal seeking could explain this effect. We report the results of mediation analyses in steps. First, we report the total effect of power on individual initiative (c). Second, we report the effect of power on individual initiative through positive affect (a₁b₁). Third, we report the effect of power on individual initiative through goal seeking (a₂b₂). Fourth, we report the results of a parallel mediation model that examined both mediators simultaneously (total indirect effect). Variance inflation factors (VIF) among the mediators were less than 10 and tolerances were greater than 0.10 (Marquardt, 1970; O’Brien, 2007), suggesting that the models were properly specified (see also Marcoulides & Raykov, 2019). Tables 2 and 3 display the results of each step among the community sample and the student sample, respectively.

Table 2.

Results of Mediation Models Testing the Effects of Power on Individual Initiative Among a Community sample.

Path	Positive affect (M1)						Goal seeking (M2)						Parallel mediation (M1 & M2)
Path	Effect	95% CI LL	95% CI UL	SE	z	p	Effect	95% CI LL	95% CI UL	SE	z	p	Effect	95% CI LL	95% CI UL	SE	z	p
Total effect (c)	0.45	0.02	0.89	0.22	2.05	.04	0.45	0.02	0.89	0.22	2.05	.04	0.45	0.02	0.89	.02	2.05	.04
Direct effect (c’)	−0.03	−0.38	0.33	0.18	−0.15	.88	0.06	−0.29	0.42	0.18	0.35	.73	−0.01	−0.37	0.34	0.18	−0.08	.94
IV-M1 (a₁)	0.77	0.34	1.20	0.22	3.50	<.001							0.77	0.34	1.20	0.22	3.50	<.001
IV-M2 (a₂)							0.60	0.20	1.00	0.21	2.91	.004	0.60	0.20	1.00	0.21	2.91	.004
M1-DV (b₁)	0.62	0.50	0.75	0.07	9.65	<.001							0.40	0.12	0.69	0.15	2.76	.006
M2-DV (b₂)							0.65	0.51	0.79	0.07	9.26	<.001	0.26	−0.04	0.57	0.16	1.70	.09
IV-M1-DV (a₁b₁)	0.48	0.19	0.77	0.15	3.29	.001							0.31	0.03	0.59	0.14	2.17	.03
IV-M2-DV (a₂b₂)							0.39	0.11	0.66	0.14	2.77	.006	0.16	−0.05	0.37	0.11	1.47	.14
Total indirect effect													0.47	0.18	0.76	0.15	3.16	.002

Note. — N = 149. All models include power (low vs. high) as the independent variable (IV) and individual initiative as the dependent variable (DV).

Table 3.

Results of Mediation Models Testing the Effects of Power on Individual Initiative Among a Student sample.

Path	Positive affect (M1)						Goal seeking (M2)						Parallel mediation (M1 & M2)
Path	Effect	95% CI LL	95% CI UL	SE	z	p	Effect	95% CI LL	95% CI UL	SE	z	p	Effect	95% CI LL	95% CI UL	SE	z	p
Total effect (c)	1.34	0.85	1.84	0.25	5.34	<.001	1.34	0.85	1.84	0.25	5.34	<.001	1.34	0.85	1.84	0.25	5.34	<.001
Direct effect (c’)	0.08	−0.57	0.72	0.33	0.24	0.81	0.74	0.24	1.23	0.25	2.91	.004	0.27	−0.39	0.92	0.33	0.81	.42
IV-M1 (a₁)	2.38	1.99	2.77	0.20	11.87	<.001							2.38	1.99	2.77	0.20	11.87	<.001
IV-M2 (a₂)							1.15	0.75	1.56	0.21	5.61	<.001	1.15	0.75	1.56	0.21	5.61	<.001
M1-DV (b₁)	0.53	0.34	0.73	0.10	5.32	<.001							0.30	0.02	0.58	0.14	2.12	.03
M2-DV (b₂)							0.53	0.34	0.72	0.10	5.40	<.001	0.32	0.04	0.59	0.14	2.28	.02
IV-M1-DV (a₁b₁)	1.27	0.76	1.78	0.26	4.86	<.001							0.71	0.04	1.38	0.34	2.08	.04
IV-M2-DV (a₂b₂)							0.61	0.30	0.91	0.16	3.89	<.001	0.36	0.03	0.70	0.17	2.11	.04
Total indirect effect													1.08	0.54	1.61	0.27	3.93	<.001

Note. — N = 129. All models include power (low vs. high) as the independent variable (IV) and individual initiative as the dependent variable (DV).

Step 1: Total Effect of Power on Individual Initiative

A simple linear regression model examined the relationship between power condition and individual initiative among the community sample (c-path; b = 0.45, t(147) = 2.03, p = .04). Going from the low-power condition to the high-power condition was associated with a 0.45-unit increase in individual initiative. Power explained 16.5% of the variance in individual initiative. This effect replicated among the student sample.

Step 2: Indirect Effect through Positive Affect

We modeled positive affect as a mediating variable to test the hypothesis that positive affect would offer an explanation for the effect of power on individual initiative among the community sample (see Figure 1). The indirect effect of power on individual initiative through positive affect was significant (a₁b₁-path; b = 0.48, SE = 0.15, z = 3.29, p = .001, 95% CI [0.19, 0.77]). Controlling for positive affect rendered the direct effect of power on individual initiative nonsignificantly different from zero (c’-path; 95% CI [-0.38, 0.33]), indicating that positive affect explained the relationship between power and individual initiative. Path analysis revealed that going from the low-power condition to the high-power condition was associated with a 0.77-unit increase in positive affect (a₁-path; b = 0.77, SE = 0.22, z = 3.50, p < .001, 95% CI [0.34, 1.20]). In turn, a one-unit increase in positive affect was associated with a 0.62-unit increase in individual initiative (b₁-path; b = 0.62, SE = 0.07, z = 9.65, p < .001, 95% CI [0.50, 0.75]). The significant indirect effect replicated among the student sample. Findings supported the hypothesis that positive affect would offer an explanation for the relationship between power and individual initiative.

Figure 1.

Model testing positive affect as a mediator of the relationship between power condition and individual initiative among the community sample. —Note. *** = p < .001, ** = p < .01, * = p < .05, † = p < .10, ns = p ≥ .10.

Step 3: Indirect Effect through Goal Seeking

We modeled goal seeking as a mediating variable to test the hypothesis that goal seeking would offer an explanation for the effect of power on individual initiative among the community sample (see Figure 2). The indirect effect of power on individual initiative through goal seeking was significant (a₂b₂-path; b = 0.39, SE = 0.14, z = 2.77, p = .006, 95% CI [0.11, 0.66]). Controlling for goal seeking rendered the direct effect of power on individual initiative nonsignificantly different from zero (c’-path; 95% CI [-0.29, 0.42]), indicating that goal seeking explained the relationship between power and individual initiative¹. Path analysis revealed that going from the low-power condition to the high-power condition was associated with a 0.60-unit increase in goal seeking (a₂-path; b = 0.60, SE = 0.21, z = 2.91, p = .004, 95% CI [0.20, 1.00]). In turn, a one-unit increase in goal seeking was associated with a 0.65-unit increase in individual initiative (b₂-path; b = 0.65, SE = 0.07, z = 9.26, p < .001, 95% CI [0.51, 0.79]). The significant indirect effect replicated among the student sample. Findings supported the hypothesis that goal seeking would offer an explanation for the relationship between power and individual initiative.

Figure 2.

Model testing goal seeking as a mediator of the relationship between power condition and individual initiative among the community sample. —Note. *** = p < .001, ** = p < .01, * = p < .05, † = p < .10, ns = p ≥ .10.

Step 4: Total Indirect Effect of Parallel Mediators

We modeled both positive affect and goal seeking as parallel mediators to examine the unique contributions of each mediator controlling for the other (see Figure 3). Controlling for the indirect effect through goal seeking, the indirect effect through positive affect was significant (a₁b₁-path; b = 0.31, SE = 0.14, z = 2.17, p = .03, 95% CI [0.03, 0.59]). Power increased positive affect (a₁-path; p < .001]), which was associated with greater individual initiative (b₁-path; p = .006). Controlling for the indirect effect through positive affect, the indirect effect through goal seeking was not significantly different from zero (a₂b₂-path; b = 0.16, SE = 0.11, z = 1.47, p = .14, 95% CI [-0.05, 0.37]). Power increased goal seeking (a₂-path; p = .004), which was marginally associated with greater individual initiative (b₂-path; p = .09)². Thus, positive affect offered additional explanation for the effect of power on individual initiative beyond that of goal seeking. The total indirect effect through both mediators was significant (b = 0.47; SE = 0.15, z = 3.16, p = .002, 95% CI [0.18, 0.76]), with these variables accounting for 41.3% of the variance in individual initiative. Controlling for both mediators rendered the direct effect nonsignificantly different from zero (c’-path; 95% CI [-0.37, 0.34]). The significant total indirect effect replicated among the student sample. Findings suggested that the effect of power on individual initiative operated through positive affect and goal seeking.

Figure 3.

Model testing positive affect and goal seeking as parallel mediators of the relationship between power condition and individual initiative among the community sample. —Note. *** = p < .001, ** = p < .01, * = p < .05, † = p < .10, ns = p ≥ .10.

Effects of Power on Occupational Burden

Although the manipulation of power increased individual initiative, t-tests examining the effect of power condition on occupational burden variables revealed that power did not exacerbate ratings of job stress, work-family conflict, nor role overload among the community sample (ts(147) < 1.71, ps > .09, ds < 0.28). Among the student sample only, participants assigned to the high-power condition reported greater job stress (M = 5.79, SD = 1.01) compared to participants assigned to the low-power condition (M = 4.17, SD = 1.69; Welch’s t(104.86) = 6.64, p < .001, d = 1.17). Replicating results from the community sample, power did not increase ratings of work-family conflict nor role overload among the student sample (ts(127) > −0.71, ps > .48, ds > −0.12). Although this pattern of results failed to support the hypothesis that social power would reduce occupational burden, it demonstrated that social power might enhance individual initiative without exacerbating burden. Similarly, there was no significant difference in negative affect between the high-power versus low-power experimental conditions (community sample: t(147) = −1.06, p > .05, d = −0.17; student sample: Welch’s t(115.64) = −1.90, p > .05, d = −0.33).

Discussion

The current study tested social power as an intervention target for increasing OCB endorsement without exacerbating burden. Consistent with our hypotheses, manipulated power enhanced self-reported individual initiative in the workplace. These findings provided support for a causal effect of power on individual initiative. These effects were mediated by positive affect and goal seeking such that powerful (vs. powerless) participants expressed greater positive affect and goal seeking, each of which in turn positively predicted OCB endorsement. Patterns of findings were mostly consistent among separate samples of community members and university students. Moreover, random assignment to a location near the top (vs. the bottom) of a power hierarchy enhanced OCB endorsement without exacerbating ratings of work-family conflict and role overload. Present findings indicated that enhancing employees’ perceived social power may be an appropriate intervention target for organizations seeking to increase OCB without burdening their employees. The effects of power to enhance goal seeking and positive affect might buffer against occupational burden often associated with OCB. Organizations should increase employees’ feelings of power by offering opportunities to lead in task groups, express their perspectives to supervisors, and contribute meaningfully to organizational function.

Effects of Power on OCB Endorsement

Social power might enhance the bounds on limited motivational and affective resources (Guinote, 2010, 2017; Keltner et al., 2003). Resource drain theory assumes that efforts directed toward a given task (e.g., OCB) cannot be equally invested in competing pursuits (e.g., time with family, personal hobbies; Edwards & Rothbard, 2000; Morris & Madsen, 2007). Social power does not fundamentally alter the zero-sum nature of resource allocation: Instead, it facilitates greater recruitment of finite resources to aid powerholders in accomplishing personal and organizational goals. The present manipulation of social power increased positive affect and goal seeking among powerholders relative to the powerless, and these motivational and affective resources in turn enhanced OCB endorsement.

Social power in an organizational hierarchy enhanced OCB endorsement without exacerbating occupational burden often associated with OCB, sometimes referred as good soldier syndrome (Bolino et al., 2015; Bolino & Turnley, 2005; Deery et al., 2017; Organ, 1988). Participants in our community sample did not report increased job stress, work-family conflict, nor role overload as a consequence of enhanced social power. Participants in our student sample reported increased job stress as a consequence of power, but not increased work-family conflict nor role overload. Although participants in our student sample recognized that greater power in the workplace might entail a more stressful occupation, they did not believe this stress would translate to negative outcomes such as work-family conflict and role overload. Power increased positive affect without influencing negative affect. This finding comports with prior research demonstrating that the experience of power is more closely linked to positive emotional states compared to negative ones (Berdahl & Martorana, 2006; Cho & Keltner, 2020; Guinote, 2017; Livingston, Cummings, et al., 2024; Van Kleef & Lange, 2020; but see Livingston, Vik, et al., 2024). Power might be a feasible and effective intervention target to enhance OCB without inflicting a personal cost on employees.

As a consequence of increased positive affect, social power might lead employees to perceive OCB as voluntary acts of altruism that enhance their cognitive resources rather than drain them. In prior work, altruistic behaviors in the workplace were conspicuously exempt from exacerbating emotional exhaustion or work-family conflict (Deery et al., 2017). These prior findings comport with the present results and fit within a larger theoretical framework supporting the association between good feelings and helpful behavior (Carlson et al., 1988). The “feel good, do good” hypothesis suggests that positive affective states motivate altruistic behavior by making cooperative goals salient (Holloway et al., 1977). Indeed, OCB such as supporting colleagues with heavy workloads entails cooperation likely to follow from positive affective states (Deery et al., 2017; Organ, 1988). Moreover, people experiencing positive affect are inclined to engage in helping behavior to maintain their pleasant affective states (Isen et al., 1978). Thus, positive affect resulting from power might generate a feedback loop whereby powerholders engage in OCB to maintain positive affect, which in turn promotes continued OCB (Wang et al., 2021). If power fundamentally alters employees’ construal of OCB as voluntary helping behavior that energize positive affect, powerholders may engage in OCB to enhance their own enjoyment of daily tasks and simultaneously buffer against occupational burden.

Power also facilitated goal seeking, providing a second mechanism by which power may enhance OCB. Situated focus theory predicts that powerholders are particularly goal-oriented relative to the powerless; active in search of opportunities to achieve desired outcomes (Guinote, 2017; Guinote & Chen, 2018). Powerholders might engage in OCB not only to maintain positive affect but also to facilitate advancement in an organizational hierarchy. Although OCB is not formally rewarded within the organizational incentive structure, those employees who engage in OCB may make a compelling case for promotions or increased compensation over time. OCB, especially civic virtue (i.e., acting to strengthen organizational welfare), was associated with promotion and salary increases among a sample of bank employees (Alkahtani, 2015). Moreover, when performing employee evaluations, supervisors tend to recognize those who engage in OCB (MacKenzie et al., 1993). If power motivates action in pursuit of productive goals as posited by situated focus theory, OCB may be an additional avenue by which powerholders believe they can earn recognition. Powerholders may additionally seek organizational advancement to facilitate greater autonomy in the workplace, as power may be associated with fewer constraints (Overbeck et al., 2006) and greater agency (Locke & Heller, 2017).

Positive affect and goal seeking individually offered significant explanatory pathways for the effect of power on individual initiative. Entered into a parallel mediation model that examined the effects simultaneously controlling for one another, the pathway through positive affect remained significant whereas the pathway through goal seeking was rendered nonsigificantly different from zero (among the community sample only). This effect through the goal seeking mediation pathway occurred due to a marginal association between goal seeking and individual initiative (see Figure 3, b₂-path). This finding suggests that although goal seeking remains relevant to understanding OCB, its contribution might be less pronounced compared to positive affect in the context of power. The effect of power on OCB might be driven primarily by positive affective states rather than by goal pursuit. Given that the pathway through goal seeking remained significant among the student sample, and that the b₂-path trended toward significance among the community sample, it may be prudent to continue to examine relationships between these variables before dismissing goal seeking as a potential explanation of the association between power and OCB.

Present findings suggest that power can facilitate citizenship behavior such as participation in organizational efforts (Kataria et al., 2013) and cooperation between employees (Baker & Dutton, 2007). An alternative view of power inspired by earlier research investigating this construct might emphasize power’s potential to enhance selfishness (Rucker et al., 2011) and devalue subordinates (e.g., Georgesen & Harris, 2006; Kipnis, 1972; Kipnis et al., 1976). Power can indeed motivate self-serving tendencies via a more agentic, rather than communal, orientation (Rucker et al., 2012). However, the effects of power on social thinking and behavior are complex, as the pursuit of self-interest sometimes confers benefits on other people. For example, a manager may perform thorough and fair performance evaluations of subordinates to demonstrate effectiveness in his or her role as manager (i.e., self-interest), yet a thorough and fair evaluation process might also contribute positively to employee morale (i.e., benefit to others). Power may also facilitate prosocial outcomes (Côté et al., 2011; Schmid Mast et al., 2009), especially among persons who tend toward a communal orientation as a matter of temperament (Chen et al., 2001; Galinsky et al., 2015). Although power in the workplace may disinhibit selfishness, positive affect and goal seeking associated with power might facilitate OCB that confers benefits on others including organizational effectiveness (Chun et al., 2011; Jiang et al., 2017; Lavy & Littman-Ovadia, 2017) and strengthened social capital (Ariani, 2012; Baker & Dutton, 2007; Zarea, 2012). Responsibly activated and deployed, feelings of power among employees might benefit organizational function and individual wellbeing.

Increasing Power among Organization Members

Organizations should implement strategies to increase feelings of social power that may benefit individuals and the organization at large. The present effects of power to enhance OCB endorsement via positive affect and goal seeking were the result of a brief, unobtrusive manipulation by which participants imagined that they were positioned near the top or bottom of an organizational hierarchy. Given that the mere thought of holding power facilitated endorsements of beneficial personal and organizational outcomes, empowering organizational members may produce considerable effects in the field. Organizations can empower members by delegating real control over valued resources (e.g., evaluations, promotions, monetary awards, work schedules) or by facilitating members’ perceptions that their concerns and suggestions make an impact on the organization (Magdaleno et al., 2023). Organizations that promote procedural justice—that is, the perception among members that their inputs are considered in pursuit of fair decision-making processes and outcomes (Greenberg & Tyler, 1987)—can enhance members’ perceptions of influence over operations that affect the individual and the organization (Thibaut & Walker, 1978; Tyler, 1989). Autonomy in task groups, open-door policies among organizational members including supervisors, and opportunities for members to advance their perspectives on consequential decisions may increase feelings of power and thus disinhibit positive affect, goal seeking, and OCB (Magdaleno et al., 2023). Such workplaces may also enhance the broader social capital to attract talented personnel and stimulate their ingenuity (Kroll & Tantardini, 2019; Leana & Pil, 2006).

Limitations and Future Directions

The current study is not without limitations that future research may address. First, the manipulation of social power was brief and limited in scope. Participants viewed an image of a ladder representing how power is distributed in the workplace (adapted from Goodman et al., 2001; see also Livingston & Burns, 2024; Livingston, Cummings, et al., 2024) and received random assignment to imagine that they were situated near the top or bottom of the power distribution. Although such imagined hierarchical role manipulations are common in the research literature on social power due to their time and resource efficiency for both participants and researchers (Dubois et al., 2010; Galinsky et al., 2015), they may not thoroughly immerse participants in the experience of controlling, influencing, and evaluating others. Future research should consider involving participants in behavioral manipulations of power that allow participants to allocate actual resources in a group setting (e.g., Galinsky et al., 2003) or to evaluate team members in a workgroup (Anderson & Berdahl, 2002). Such immersive behavioral manipulations may provide a closer analogue to real-world organizational power hierarchies. Experimental manipulations are effective to the extent that they activate the underlying psychological processes present in real-world situations (i.e., experimental realism; Aronson & Carlsmith, 1968). The imagined hierarchical role manipulation used in the current study reliably increased participants’ feelings of control, influence, and evaluative efficacy, demonstrated by a successful manipulation check measure. Although behavioral manipulations of power may enhance the mundane realism of the laboratory task (i.e., the extent to which the task resembles the real-world; Aronson & Carlsmith, 1968), the present manipulation achieved experimental realism by activating the relevant psychological processes in an efficient design that did not exacerbate survey fatigue.

Second, participants in the current study self-reported their endorsement of goal seeking and OCB. Self-report measures can provide reliable behavioral prediction (Kraus, 1995), enabling researchers to identify factors that may influence behavior in organizations and beyond (Ajzen, 1991). Future research should test the extent to which power-induced OCB endorsement predicts engagement in goal seeking and initiative taking to establish a relationship between the present psychological constructs and meaningful behaviors in which organizations and their members may engage (see Baumeister et al., 2007). Research examining the association between self-reports and behaviors indicates that variables such as question wording (Schwarz, 1999) and sample characteristics (Kraus, 1995) can moderate the effect; thus, the present research incorporated recommended practices to measure attitudes specific to the behaviors of interest (e.g., goal seeking, initiative taking; Ajzen, 1991; Kraus, 1995) and to utilize a non-student sample. Samples of community members tend to provide self-reports that more strongly correlate with behaviors compared to their student counterparts (Kraus, 1995), perhaps due to greater life experience and self-knowledge. Future research should employ behavioral measures of these outcome variables to advance research examining OCB as a function of social power. Behavioral measures may consist of time spent volunteering after a power manipulation, the number of tasks completed without compensation, or interpersonal behaviors among research participants that enhance the social capital (Ariani, 2012; Batson et al., 1988; Twenge et al., 2007).

Third, self-reports of positive affect, goal seeking, and individual initiative could be influenced by normative responding; that is, a tendency toward responses that participants deemed appropriate within the context of social power. Participants might believe that high-power people ought to have positive feelings, pursue goals, and take uncompensated initiative in the workplace, and that low-power people are characterized by the opposite. In turn, these beliefs might have informed responses. However, if normative responding were responsible for the present results, one might hypothesize opposite findings to those obtained: Stereotypes abound that the powerful are angry (Van Kleef et al., 2011) and contemptuous (Tobore, 2023; i.e., negative affect), that they occupy the highest rungs of social life and therefore have nothing more to achieve (i.e., low goal seeking propensity; Bell, 2020; Pew Research Center, 2020Pew Reseach Center, 2020), and that they act only for personal gain (i.e., low OCB; for review, DeCelles et al., 2012; Kipnis, 1972). Thus, we are inclined to believe that our experimental manipulation produced the present effects beyond normative responding. Future research should examine whether and how perceived social norms can affect responses to imagined hierarchical role manipulations of power (Dubois et al., 2010; Galinsky et al., 2015). Such examinations of perceived social norms might inform comprehensive understandings of power, as the direction of normative responding can reveal cultural values (Fisher & Katz, 2000). Behavioral research designs that provide high-power versus low-power research participants an opportunity to opt into OCB can attempt to replicate and extend the present findings. Given that theory-driven hypotheses received empirical support among two samples in the present research, we expect these effects to replicate across diverse methodological approaches.

Conclusion

Organizational citizenship behaviors, commonly referred to as “going above and beyond” one’s responsibilities in the workplace, benefit the organization but often entail personal costs to individuals. The present findings indicated that a brief and unobtrusive manipulation of social power could enhance OCB endorsement by increasing organizational members’ positive affect and goal-oriented cognition. Further, although powerholders reported increased OCB endorsement relative to the powerless, they tended not to report an exacerbation of negative effects to their personal wellbeing. Organizations should empower members as a means of both enhancing OCB and leveraging the protective effects of power on psychological wellbeing in the workplace.

Supplemental Material

Supplemental Material - Social Power May Enhance Workplace Initiative: An Experimental Investigation Among Two Samples

Supplemental Material for Social Power May Enhance Workplace Initiative: An Experimental Investigation Among Two Samples by Tyler N. Livingston, Carter R. Adams, and Connor MacKinnon in Psychological Reports

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) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Tyler N. Livingston

Data Availability Statement

Data are available via the Open Science Framework (OSF) at

Supplemental Material

Supplemental material for this article is available online.

Notes

Author Biography

Tyler N. Livingston is a social psychologist who studies power and decision-making.

Carter R. Adams is an industrial/organizational psychologist who studies imposter syndrome among STEM employees.

Connor MacKinnon is an industrial/organizational psychologist who studies the effects of leadership on team performance.

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