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Organizational citizenship behavior: understanding interaction effects of psychological ownership and agency systems

• Original Paper
• Open access
• Published: 17 December 2022
• Volume 18 , pages 1–27, ( 2024 )

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• Ben Wilhelm 1 ,
• Nastaran Simarasl 2 ,
• Frederik J. Riar 3 &
• Franz W. Kellermanns   ORCID: orcid.org/0000-0002-1441-5026 4  

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Organizational citizenship behavior is a highly sought-after outcome. We integrate insight from the psychological ownership perspective and agency theory to examine how the juxtaposition of informal psychological mechanisms (i.e., ownership feelings toward an organization) and formal and informal governance mechanisms (i.e., employee share ownership, agency monitoring, and peer monitoring) influences employees' organizational citizenship behaviors. Our empirical results show that psychological ownership has a positive effect on organizational citizenship behavior. Contrary to the common belief that informal and formal mechanisms complement each other, we find that the positive influence of psychological ownership on organizational citizenship behavior is more pronounced when employee share ownership and agency monitoring is low compared to high. Implications for theory and future research are discussed.

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1 Introduction

Agency theory suggests that one of the biggest challenges of an organization is to forgo employees’ self-interest and motivate them to act in the best interests of the organization. It specifically assumes that unless individuals have formal ownership, they tend to prioritize their self-interests (Eisenhardt 1989 ; Jensen and Meckling 1976 ). Hence, agency theory predicts that by curbing employees’ self-interested behaviors through governance mechanisms, organizations can better achieve their goals (Aluchna and Kuszewski 2021; McConville et al. 2016 ; Alchian and Demsetz 1972 ). Some predictions of agency theory, however, have been challenged (Bosse and Phillips 2016 ; Madison et al. 2017 ). Proponents of the psychological ownership perspective contradict agency theory by suggesting that ownership feelings in organizations and their consequent positive work behaviors can be induced without formal ownership (Zhang et al. 2021 ; Pierce et al. 2001 ; Van Dyne and Pierce 2004 ; Hernandez 2012 ). Furthermore, despite their enormous implementation costs, governance mechanisms have failed to result in unanimous positive organizational outcomes (Loughry and Tosi 2008 ; Sieger et al. 2013 ; Pierce and Rodgers 2004 ). In addition, the emphasis of governance mechanisms has predominantly focused on curbing employees’ negative behaviors, such that their impact on employees’ positive behaviors has been undermined.

To better understand the impact of agency mechanisms, scholars have called for research integrating agency theory and other perspectives, specifically the psychological ownership theory (Chi and Han 2008 ; Sieger et al. 2013 ). Although these theories focus on similar outcomes (i.e., how to induce employee behaviors aligned with organizational goals), their underlying mechanisms are different. For the most part, agency theory emphasizes a formal (hard) approach centered on organizational interventions that trigger extrinsic motivation (e.g., Bratfisch et al. 2023 ). In contrast, psychological ownership is geared toward an informal (soft) perspective that stimulates employees’ intrinsic motivation to act in the organization’s best interest (e.g., Sieger et al. 2013 ). Instead of being examined in isolation, these theories may be juxtaposed because the soft and hard elements underlying these theories coexist in organizations and impact each other (Pesch et al. 2021 ; Sieger et al. 2013 ; LePine et al. 2002 ; Wagner et al. 2003 ). To address the shortcomings in the literature, we integrate these two theories to examine how psychological ownership influences organizational citizenship behavior and how governance mechanisms, including employee share ownership, agency monitoring, and peer monitoring, bound the relationship between informal psychological ownership and organizational citizenship behavior? To address these research questions, we propose a set of hypotheses and empirically test them with primary survey data from 324 employees in two architectural, engineering, and surveying organizations in the United States.

We make four theoretical contributions: First, by juxtaposing the assumptions of psychological ownership and agency theories regarding human motivation and behaviors in organizations, we show how the coexistence of ownership feelings and governance mechanisms (employee share ownership, etc.) impacts employees’ extra-role behaviors. Although the direct relationship between psychological ownership and organizational citizenship behavior has been studied before (e.g., Zhang et al. 2021 ; O’Driscoll et al. 2006 ; Vandewalle et al. 1995 ), our work goes beyond by advancing the theory about interventions with formal and informal governance mechanisms to induce, maintain, and nurture the relationship between ownership feelings and citizenship behaviors (Aluchna and Kuszewski 2021; Wagner et al. 2003 ; Buchko 1993 ). This further enables us to contribute to the sparse research stream that challenges the prevailing assumptions about the effect of extrinsic motivators on intrinsic ones by showing that not all extrinsic incentives necessarily reduce the positive impact of intrinsic motivators. Instead, attention should be paid to more fine-grained characteristics of extrinsic motivators, such as whether they are implemented through formal or informal organizational procedures. Second, we contribute to agency theory (Eisenhardt 1989 ; Jensen and Meckling 1976 ) by moving beyond past research's common emphasis on how governance mechanisms enhance organizational and financial performance under the assumption of minimizing employees’ negative, calculative, and self-serving behaviors (Bratfisch et al. 2023 ; Flammer et al. 2019 ; Keum 2021 ; Welbourne et al. 1995 ). Rather, in this study, we literally examine how governance mechanisms induce and impact employees' cognitive-affective states and behaviors, not in terms of minimizing negative behaviors (past research common assumption) but instead regarding employees' positive and desirable cognitive-affective states and behavioral outcomes. Furthermore, contrary to past organizational governance research that has mainly relied on archival data (Daily et al. 2003 ), our work relies on primary survey data from two organizations to provide possible answers to why different governance mechanisms may not always bring about the expected outcomes (Basterretxea and Storey 2018 ); hence, increasing the predictive validity of agency theory. Third, we contribute to the literature on employee ownership (e.g., Poutsma et al. 2006 ) by examining its dual facets (psychological and formal) together. This sets our work apart from past studies that investigate the facets of the same concept, employee ownership, exclusively and in isolation from each other as if they do not exist simultaneously in an organization (Buchko 1993 ; O’Boyle et al. 2016 ); hence, our work promises results with higher rigor and validity. Our findings show that formal and psychological ownership coexistence does not create a positive synergistic influence on citizenship behaviors. Fourth, our research contributes to the theory about monitoring as a governance mechanism (e.g., Sieger et al. 2013 ; Wagner et al. 2003 ) by uncovering different types of monitoring, agency (supervisor) monitoring vs. peer monitoring, each having different implications for employees' ownership feelings and extra-role behaviors. In doing so, we have examined the under-studied construct of peer monitoring as an independent governance mechanism, in contrast to past research that had predominantly considered it as the aftermath of employee profit-sharing plans and collaborative outcomes in organizations (Core and Guay 2001 ; Bolduan et al. 2021 ). Our findings suggest that peer monitoring may have other unexplored faces and that it may not necessarily fit in with other governance mechanisms that are predominantly preventive in nature.

2 Theoretical framework

Our theoretical model is summarized in Fig.  1 . As we will outline in more detail below, we will argue that the relationship between psychological ownership and organizational citizenship behavior is moderated by three factors. Specifically, we focus on employee share ownership, agency monitoring, and peer monitoring.

Research model

2.1 Agency theory

Agency theory, a dominant paradigm in management theorizing, has been applied extensively across various research disciplines, such as organizational behavior (e.g., Larkin et al. 2012 ; Buchko 1993 ), strategic management (e.g., Shi et al. 2016 ; Perryman and Combs 2012 ), family business (e.g., Eddleston et al. 2018 ; Madison et al. 2017 ), and entrepreneurship (e.g., Bratfisch et al. 2023 ). It examines the relationship between principals (e.g., owners) and agents (e.g., employees), whereby the principal engages the agent to perform certain services and to make decisions on the principal’s behalf (Jensen and Meckling 1976 ; Davis et al. 1997 ).

According to agency theory, agents are assumed to be self-interested, rational, profit-maximizing individuals whose interests are incongruent with those of principals (Eisenhardt 1989 ; Jensen and Meckling 1976 ). As a result, agents’ actions and decisions may not be consistent with principals’ desires for long-term profit maximization and organizational growth. Agents can hide their (undesirable) intentions from principals due to information asymmetry. Ex-ante this may lead to adverse selection and ex-post to moral hazard (Eisenhardt 1989 ).

To align principals’ and agents’ interests, principals often use corporate governance mechanisms, including incentives (e.g., employee share ownership plans) and monitoring (e.g., formal and informal employee job assessments) (Chrisman et al. 2007 ; Ang et al. 2000 ; Nyberg et al. 2010 ). Research suggests that such mechanisms encourage agents to act and make decisions in line with organizational objectives because, under such circumstances, their interests will correlate with those of principals (Eisenhardt 1989 ; Chrisman et al. 2007 ; Madison et al. 2017 ). However, according to scholars who have challenged this view, formal governance mechanisms may not inherently lead to agents’ behavioral changes (Pierce and Furo 1990 ), especially when these mechanisms intertwine with psychological elements, such as individuals’ ownership feelings toward an organization (Pierce et al. 2001 ).

Prior research suggests that formal mechanisms, in addition to agents’ psychological states, impact their behaviors (Zhang et al. 2021 ; Buchko 1993 ). However, because these concepts have mainly been investigated separately, it remains unclear if they are effective in combination and whether different formal mechanisms positively or negatively change the impact of psychological ownership on employees’ work behaviors (Liu et al. 2019 ). In light of these shortcomings in the prevailing literature, we examine how psychological ownership shapes employees’ organizational citizenship behavior toward their organization and how governance mechanisms prescribed by agency theory—employee share ownership plans, agency monitoring, and peer monitoring—moderate our proposed baseline relationship.

2.2 The influence of psychological ownership on organizational citizenship behavior

Organizational citizenship behavior, defined as “contributions in the workplace that go beyond role requirements and contractually rewarded job achievements” (Organ and Ryan 1995 , p. 775), is a lubricant for “the social machinery of the organization” (Podsakoff et al. 1997 , p. 263). As a highly sought-after outcome, true organizational effectiveness is achieved when employees willingly engage in extra-role behaviors that exceed their formal job descriptions to help the organization achieve its goals in response to various contingencies (Motowidlo and Van Scotter 1994 ). Organizational citizenship behavior is especially relevant here because, as a contextual performance variable, it demonstrates the extent to which organizations can influence employees’ positive behaviors (Organ and Ryan 1995 ).

In line with prior literature (e.g., Van Dyne and Pierce 2004 ; Liu and Wang 2013 ), we expect that there will be a positive relationship between psychological ownership and organizational citizenship behavior. Prior research suggests that ownership feelings induce positive emotions in employees by meeting their need for belonging, which positively impacts their willingness to contribute to the organization beyond their formal roles (Beggan 1992 ). When employees feel that they belong to the organization, they view the organization as an extension of themselves over which they can exert control; that is, the organization becomes part of their self-concept and self-identity (Belk 1988 ). To boost their self-concept, employees who identify with their organization feel more responsible for the organization and its outcomes, which encourages them to engage in proactive extra-role behaviors that will elevate the organization’s well-being (Van Dyne and Pierce 2004 ; Liu and Wang 2013 ; Pierce et al. 2001 ).

Individuals who feel that they own something valuable tend to feel protective and proud of the target of their ownership (Vandewalle et al. 1995 ). Ownership feelings trigger protective behaviors in employees not only to maintain the target of ownership but to enhance its future status. Employees with ownership feelings are more likely to exhibit voluntary extra-role behaviors that will improve important organizational outcomes, even if this requires them to go above and beyond their formal responsibilities (Van Dyne and Pierce 2004 ).

When employees perceive that they can meet their need for belonging and effectance through the organization, they become motivated to give back to the organization voluntarily. Although these volitional actions are not necessarily rewarded through formal organizational processes, employees engage in them because they perceive that the organization is attentive to and considerate of their needs (Dawkins et al. 2017 ).

Taken together, we expect that psychological ownership positively impacts employees’ organizational citizenship behavior through three explanatory mechanisms. First, psychological ownership feelings lead to the satisfaction of the need to belong and the nurturing of self-concept. Second, the satisfaction that employees perceive as a result of meeting their need to belong triggers their reciprocating behaviors to satisfy the organization’s needs and enhance its outcomes. Third, feelings of ownership are associated with strong tendencies and behaviors that will protect the target of ownership from harm and boost its image and performance. Therefore, we hypothesize that:

Hypothesis 1

Employees’ psychological ownership feelings toward their organization are positively related to their organizational citizenship behaviors.

Although the relationship between psychological ownership and organizational citizenship behavior has been examined, the findings have been inconsistent. For instance, in most studies, a positive relationship has been established between the two constructs (e.g., Pierce et al. 2001 ; Van Dyne and Pierce 2004 ), while others have not found a significant relationship (Liu et al. 2012 ; O’Driscoll et al. 2006 ). Hence, it is likely that this relationship depends much on boundary conditions. To provide more clarity, we examine whether the governance mechanisms prescribed by agency theory (employee share ownership, agency monitoring, and peer monitoring) moderate the relationship between psychological ownership and organizational citizenship behavior. We discuss each contingency separately below.

2.3 The moderating effect of employee share ownership

To curb employees’ opportunistic behaviors, organizations implement employee share ownership plans, which give equity (shares) to employees to better motivate them to work toward organizational goals (Jensen and Meckling 1976 ; Poutsma et al. 2006 ). While some have found employee share ownership to have a positive impact on employees’ desirable intentions, behaviors, and, ultimately, performance (Guery 2015 ; Whitfield et al. 2017 ), the results have been inconsistent (Long 1978 ; McCarthy et al. 2010 ), indicating that in addition to formal ownership, the feelings of informal ownership may be at play to impact the desired employee behaviors in organizations. So, what happens when psychological ownership and employee share ownership coexist in an organization?

Past research regarding the coexistence of intrinsic and extrinsic motivators in organizations follows a dualistic logic: According to the proponents of the "diminishing" view, extrinsic motivators diminish the positive impact of intrinsic motivators (Grant 2008 ; Deci 1971 ). They argue that extrinsic motivators are more tangible, conspicuous, and noticeable (Kuvaas et al. 2017 ); hence, in competition with intrinsic motivators, they attract a larger share of employees' limited attention; therefore, intrinsic motivators lose their impact on individuals' perceptions and behaviors at the presence of extrinsic motivators (Lindenberg and Foss 2011 ; Gagné and Deci 2005 ; Sue-Chan and Hempel 2016 ). On the other hand, the advocates of the newly emerged "additive" perspective argue that extrinsic motivators do not always diminish intrinsic motivators but may actually support and amplify the intrinsic motivators' positive impact on desired behaviors (Frey 1997 ; Osterloh and Frey 2000 ). This line of research builds on the assumption that extrinsic motivators hurt the positive impact of intrinsic motivators only when they trigger employees to shift their locus of control from internal to external (Deci 1975 ). Otherwise, employees may perceive extrinsic motivators in ways that strengthen the positive impact of intrinsic motivators with which they overlap; for instance, if they perceive the extrinsic motivator to be associated with a positive public image or desirable social goal (Bruni et al. 2020 ; Frey 1997 ). Therefore, their findings suggest that the diminishing view of extrinsic motivators does not apply to all situations in organizations.

Similarly, it is possible to theoretically identify the tracks of both additive and diminishing effects of governance mechanisms that are predominantly extrinsically motivating on employees' behaviors. Being a shareholder and an employee could enhance employees’ perceptions of their influence and control over the organization and its outcomes, leading them to feel like an owner, hence, strengthening the relationship between their feelings of psychological ownership and organizational citizenship behavior. The motivational power of formal ownership encourages employees to see the organization as part of themselves and perceive their interests intertwined with that of the organization and other shareholders, hence, feeling a higher sense of belonging (Buchko 1993 ; Van Dyne and Pierce 2004 ). In addition, employee share ownership may convey to employees that their contributions to the long-term organization's success are desired, valued, and recognized (Long 1980 ).

On the other hand, employee share ownership may neutralize or diminish the positive outcomes of psychological ownership on organizational citizenship behavior. If employees do not associate employee share ownership with increased influence and control over the organization, they may consider them ineffective and superficial (Freeman et al. 2010 ). Furthermore, employee share ownership may harbor perceptions of unfairness if they are not distributed based on objective performance and merit criteria (Hansmann 1996 ). In addition, when granted to employees with high psychological ownership, employees' formal ownership may become redundant (Kuvaas et al. 2017 ); therefore, diminishing the marginal positive effect of psychological ownership on organizational citizenship behavior because employees high in psychological ownership are already intrinsically motivated to strive for the best possible organizational outcomes (Sieger et al. 2013 ).

In sum, we expect the diminishing effect of employee share ownership to be stronger than its additive effect. We reason that between the two competing influences, the diminishing effect will be more salient to employees because it may bring up a comparison of their performance with peers; hence, it harbors perceptions of unfair distribution criteria and treatment (Bakan et al. 2004 ; Bruni et al. 2020 ; Sengupta et al. 2007 ). Therefore, it is more reasonable to anticipate the employee share ownership plans to weaken the relationship between psychological ownership and organizational citizenship behaviors. Hence, we propose that:

Hypothesis 2

Employee share ownership moderates the relationship between employee psychological ownership and organizational citizenship behavior. The positive influence of psychological ownership on organizational citizenship behavior is stronger when employee share ownership is low compared to high.

2.4 The moderating effect of agency monitoring

Establishing alignment between managers’ and employees’ interests can be achieved through organizational control systems, which seek to coordinate employees’ behaviors and organizational goals through incentives and monitoring (Tosi et al. 1997 ). Agency monitoring consists of supervisors observing employees’ behaviors and outcomes through surveillance, codified policies, and rules to ensure agents’ conformity with organizational goals (Kreutzer et al. 2016 ). According to agency theory, employees tend to shirk their job responsibilities if their behaviors are left unmonitored (Conlon and Parks 1990 ). Therefore, in agency monitoring, a formal control mechanism, managers monitor employee behaviors and outputs relative to a set of agreed-upon policies and procedures that tend to clarify their organizational roles in hopes of reducing employees’ shirking behaviors (Pesch et al. 2021 ; Fong and Tosi 2007 ; Alchian and Demsetz 1972 ).

We expect that the relationship between psychological ownership and organizational citizenship behavior is contingent on the level of agency monitoring. As an extrinsic motivator, agency monitoring is expected to discourage undesirable behaviors, making it more likely for an organization to achieve its goals (Chrisman et al. 2007 ). It may, however, also diminish the intrinsic motivating effect of psychological ownership on citizenship behaviors.

When agency monitoring is enforced, employees perceive their work environment as more structured with higher formalization, routinization, and more centralized decision making (Fredrickson 1986 ; Ohly et al. 2006 ). This leaves less latitude for employees to act on their sense of psychological ownership to exercise discretion in performing their jobs and exert autonomy over the organization through their volitional extra-role behaviors (Maynard et al. 2012 ; Sieger et al. 2013 ; Deci and Ryan 2012 ). Managerial monitoring encourages employees to focus on supervised tasks, usually reflected in employees’ formal job descriptions (Stanton 2000 ). This discourages employees from engaging in organizational citizenship behavior that originates from psychological ownership.

Implementation of agency monitoring infuses distrust in the relationship between employees and managers, likely triggering employee resistance and other negative attitudes toward the organization (Spitzmüller and Stanton 2006 ). These negative emotions (Liao and Chun 2016 ) shatter employees’ feelings of psychological ownership and motivate them to disengage from organizational citizenship behaviors.

Monitoring harms employee psychological well-being, including increased stress, anxiety, anger, and tension (Hartman 1998 ; Holman et al. 2002 ). Employees who are constantly monitored experience an ongoing sense of pressure to act based on managers’ expectations (Zhou 2003 ). This stressful environment encourages conformity (Brown 2000 ) at the cost of discouraging employees from expressing their psychological ownership through citizenship behaviors.

Overall, we expect low perceived control, diminished sense of trust, and psychological pressures that employees feel due to agency monitoring systems sabotaging the positive emotions associated with psychological ownership and the tendency to engage in organizational citizenship behaviors. Thus, we hypothesize that:

Hypothesis 3

Agency monitoring moderates the relationship between employee psychological ownership and organizational citizenship behavior. The positive influence of psychological ownership on organizational citizenship behavior is stronger when agency monitoring is low compared to high.

2.5 The moderating effect of peer monitoring

As an informal control mechanism, peer monitoring aligns the interests of owners and employees through social processes that take place among employees (Glover and Kim 2021 ). Employees positioned at the same organizational level notice and respond to each other’s task performance (Chrisman et al. 2007 ), especially when working on inter-related and collective organizational goals (Welbourne et al. 1995 ). Peer monitoring can extrinsically motivate employees to refrain from opportunistic and shirking behaviors due to the perceived threat of peer sanctions (Li et al. 2017 ; Loughry and Tosi 2008 ; Welbourne et al. 1995 ).

Peer monitoring can trigger cognitive dissonance and frustration in employees with psychological ownership who feel pressured to focus on those tasks noted and monitored by their peers rather than engage in extra-role behaviors that may remain unnoticed or even be sanctioned by peers (De Jong et al. 2014 ). When peer monitoring is in place, employees feel escalated pressure to act according to their peers’ expectations of appropriate behavior (Feldman 1984 ; O’Reilly III and Caldwell 1985; Sewell 1998 ). Like agency monitoring this creates a stress-infused working climate that diminishes psychological ownership and encourages employee conformity with social and group expectations to gain their peers’ social approval (Loughry and Tosi 2008 ; Aubé et al. 2009 ).

Even if we consider the positive connotations of peer monitoring, such as reduced information asymmetry because of enhanced transparency (Palanski et al. 2011 ; Walter et al. 2021 ), the reinforcing impact of peer monitoring on employees with psychological ownership is unnecessary because the intrinsic motivation from psychological ownership already enhances their likelihood of engaging in organizational citizenship behaviors. Although we expect only a marginally positive effect of psychological ownership on organizational citizenship behavior under high peer monitoring, it diminishes relative to the same effect under low peer monitoring; high psychological ownership already encourages high organizational citizenship behavior. We expect that under high peer monitoring, the difference in organizational citizenship behavior of employees with low vs. high psychological ownership becomes insubstantial. At high levels of peer monitoring, the organizational citizenship behavior of employees with low psychological ownership becomes more similar to those with high psychological ownership.

In sum, employees' peer pressure to conform to their work group’s social expectations and norms is likely to discourage them from engaging in extra-role behaviors, especially when group norms do not favor such behaviors. Similarly, employees with high psychological ownership may feel tremendous psychological and emotional strain if peer monitoring emphasizes formal job-related behaviors, undermining the exercise of positive discretionary behaviors that other employees may deem appropriate for organizational well-being. Accordingly, we hypothesize that:

Hypothesis 4

Peer monitoring moderates the relationship between employee psychological ownership and organizational citizenship behavior. The positive influence of psychological ownership on organizational citizenship behavior is stronger when peer monitoring is low compared to high.

3 Research method

3.1 research design and sample.

Our sample includes employees of two organizations in the United States that consented to participate in our study and provided us with access to their employees’ email addresses. Both organizations provide professional engineering, architectural, and surveying services to the U.S. domestic construction industry. One firm is headquartered in Michigan, while the other is in Virginia. Both firms have multiple offices and operate independently of one another. Employees of these organizations were allocated company shares upon reaching one year of service while maintaining full-time employment status. The survey instrument was distributed via email with a link to an online questionnaire. Over four weeks, 2,026 emails (an invitation and three reminders) were sent. Removing the responses with missing data resulted in 324 completed surveys (response rate of 16%, which is slightly higher relative to other survey research on psychological ownership and agency systems, e.g., Sieger et al. 2013 ). Sixty-two percent of respondents were male; the average age was 42.5 years old, and the average tenure was 7.23 years. On average, employees owned 20% of company shares.

3.2 Variables

3.2.1 dependent variable, 3.2.1.1 organizational citizenship behaviour.

We used Lee and Allen’s ( 2002 ) 8-item scale to measure the extent to which respondents exhibited organizational citizenship behaviors toward their organization. Responses were measured using a 7-point Likert-type scale (1 =  strongly disagree to 7 =  strongly agree ). All items of this and the other multi-item constructs are displayed in the Appendix.

3.2.2 Independent variables and moderators

3.2.2.1 psychological ownership.

We used Van Dyne and Pierce’s ( 2004 ) 7-item scale, which is the measure of choice for psychological ownership (Dawkins et al. 2017 ). Responses were measured using a 7-point Likert-type scale (1 =  strongly disagree to 7 =  strongly agree ).

3.2.2.2 Employee share ownership

This scale reflects indirect ownership of company shares as part of employment benefits (e.g., Poutsma et al. 2006 ). Employees were asked to specify the approximate value (in dollars) of their shares. To establish normality and to address original values of zero in the variable, the natural log for the variable was taken after 1 was added to the value.

3.2.2.3 Agency monitoring

We used Chrisman and colleagues’ (2007) 5-item scale to examine agency monitoring, which measures the extent to which employees are assessed through monitoring activities, including supervisors’ observation and regular assessment of progress toward short and long-term goals. Responses were measured using a 7-point Likert type scale (1 =  strongly disagree to 7 =  strongly agree ).

3.2.2.4 Peer monitoring

We used Welbourne and colleagues’ (1995) 9-item scale to examine the extent to which employees monitored each other’s behaviors and adhered to organizational expectations. Responses were measured using a 7-point Likert-type scale (1 =  strongly disagree to 7 =  strongly agree ).

3.2.3 Control variables

We controlled for employees’ age (Basterretxea and Storey 2018 ), gender, education (Hallock et al. 2004 ), organizational tenure, and organizational role (Bayo-Moriones and Larraza-Kintana 2009 ). Gender was a dichotomous variable (1 =  male , 0 =  female ). Two variables represented the respondent’s role within the company: (a) executive and (b) non-executive. Education level included five response choices: (a) some high school, (b) high school diploma, (c) some college, (d) college graduate, and (e) graduate school. Last, we controlled for the organization membership because we sampled from two organizations. While both organizations are part of the same industry and provide similar services, we still wanted to eliminate organizational-level effects on our dependent variable.

Table 1 displays the means, standard deviations, and correlations of the study variables. We utilize ordinary least square (OLS) analysis in our study, as it is the preferred tool to test the moderation effect (Aiken and West 1991 ). The variables were entered as a block stepwise in each model, beginning with a control-only model (Model 1). The independent variable, the moderators, and the interaction effects were entered in the subsequent three steps. Below, we elaborate on these four models in detail.

To check for common method bias, we conducted Harman’s single-factor test (Podsakoff et al. 2003 ). Common method bias was not a significant concern because the one-factor model accounted for only 16% of the variance. In confirmatory factor analysis, we allowed the independent, dependent, and moderator variables to load onto one method factor, which showed a very poor fit with χ 2 = 3444.07 (405) and a CFI of 0.498, which supports our conclusion (Podsakoff et al. 2003 ). Furthermore, we need to note that while common method bias may potentially affect mediational models, Evans ( 1985 ) has shown that common method bias cannot affect moderation models, as we propose in our study, which further mitigates this concern.

Table 2 reports the OLS regression results of the hypothesized relationships. We regressed organizational citizenship behavior (the dependent variable) on the control variables (Model 1), which explained 14% of the variance in organizational citizenship behavior. Second, we included psychological ownership to measure our main effect (Model 2), which significantly increased the explained variance in organizational citizenship behavior (Adjusted R 2  = 0.33). Finally, we entered the moderators and the two-way interaction terms (Model 3 and Model 4), with a final adjusted R 2 of 0.40.

As shown in Model 2, we found support for hypothesis 1, given that the main effect of psychological ownership is positive and statistically significant ( β  = 0.47, p  < 0.001). Regarding hypothesis 2, Model 4 demonstrates that employee share ownership moderates the relationship between psychological ownership and organizational citizenship behavior ( β  = −0.09, p  < 0.05). Therefore, our results support hypothesis 2. To interpret this moderating effect, we plotted the interaction relationship. As shown in Fig.  2 , when employee share ownership increases, the relationship between psychological ownership and organizational citizenship behavior becomes weaker.

Moderating effects of employee share ownership on the relationship between psychological ownership and organizational citizenship behavior (H2)

Regarding hypothesis 3, the interaction between psychological ownership and agency monitoring is significant ( β  = −0.11, p  < 0.05). Therefore, we found support for hypothesis 3. As Fig.  3 shows, when agency monitoring increases, the relationship between employee psychological ownership and organizational citizenship behavior becomes weaker. Our results in Table 2 show that peer monitoring does not moderate the relationship between psychological ownership and organizational citizenship behavior ( β  = −0.002, p  = 0.96); hence, we did not find empirical support for hypothesis 4.

Moderating effects of agency monitoring on the relationship between psychological ownership and organizational citizenship behavior (H3)

In further analysis not reported here, we also checked if the moderation was significant for the moderators' low, medium, and high levels (Hayes 2022 ). Furthermore, as reported above, the confidence interval around the B value for both significant moderation hypotheses did not contain zero.

5 Discussion

The focus of this study has been on integrating insights from psychological ownership and agency theory. We drew on empirical survey data to address the following research questions: (1) How does psychological ownership influence organizational citizenship behavior, and (2) how do governance mechanisms, including employee share ownership, agency monitoring, and peer monitoring, serve as boundary conditions? Our results show that psychological ownership positively affects organizational citizenship behavior. Contrary to the common belief that informal and formal mechanisms complement each other, we find that the positive influence of psychological ownership on organizational citizenship behavior is more pronounced when employee share ownership and agency monitoring is low compared to high. Figure  4 portrays the summary of the findings of our research model, which we will discuss in more detail below.

Summary of results

5.1 Theoretical contributions

Our study’s findings contribute to the literature on how organizations can motivate employees to demonstrate positive extra-role behaviors (Dawkins et al. 2017 ). One well-established path to organizational citizenship behavior is through employees' ownership feelings (Zhang et al. 2021 ; O’Driscoll et al. 2006 ; Vandewalle et al. 1995 ). What gives credence to our research is that employee ownership feelings towards an organization do not exist in a vacuum. Instead, it seems that ownership feelings are intertwined with various formal and informal organizational mechanisms that may impact employees' ownership feelings and subsequent behaviors. To add to the complexity, one should also consider that it is challenging for managers to directly gauge and manipulate employees' cognitive-affective states, such as ownership feelings. Instead, managers have more latitude to enforce governance mechanisms that may implicitly but adversely impact employees' ownership feelings. Therefore, an important piece to this puzzle is how governance mechanisms as important organizational interventions boost or undesirably compromise the positive effect of ownership feelings on employees' extra-role behavior. Compared to past research that has studied the impact of the formal and informal mechanisms in separate studies (e.g., Sieger et al. 2013 ; Wagner et al. 2003 ), our research makes an important contribution by examining these mechanisms in the same study. Hence, our work adds to the understanding of governance mechanisms’ impact on employee behaviors. In addition, despite past research positing that these mechanisms impact employee behaviors directly (Hallock et al. 2004 ; Basterretxea and Storey 2018 ), we have shown that it is reasonable to consider them as boundary conditions that change the relationship between employees' cognitive-affective states and organizational citizenship behavior (Johns 2006 ). For instance, our results show that employee share ownership does not have a direct impact on organizational citizenship behavior but an indirect one by influencing the relationship between employees' psychological ownership and organizational citizenship behavior. Hence, our theorizing captures organizational reality more accurately because, in essence, these mechanisms serve as contextual variables that may provide ground for employees' psychological and behavioral manifestations to unfold (Johns 2006 ). In this sense, our study`s findings contribute to the broader literature on workplace conditions in organizations by showing that the general work environment can have important implications for employees’ behaviors. Considering the insights from recent theoretical advancements, such as the sociomaterial perspective (Leonardi 2012 ; Orlikowski 2007 ), our study emphasizes the ability of ownership feelings to influence organizations not only externally (e.g., organizational performance) but also internally. For example, collective psychological ownership feelings among many employees might have the power to transform organizations into a more open and social conversational environment. Such structural conditions, in turn, might enhance identification among employees with the organization and, ultimately, facilitate organizational processes like information flows and behaviors like collaboration (e.g., Aslam et al. 2021 ; Bouncken et al. 2021 ).

Regarding agency theory (Eisenhardt 1989 ; Jensen and Meckling 1976 ): This perspective posits that governance mechanisms such as employee share ownership effectively curb agents’ (employees’) opportunistic and self-interested behaviors in organizations. However, it overemphasizes governance mechanisms’ preventive impact so that it undermines how these mechanisms impact positive employee states and behaviors (Daily et al. 2003 ). Surprisingly, from the three governance mechanisms examined, we found a positive and statistically significant direct effect of agency monitoring and peer monitoring as independent variables on organizational citizenship behavior as the dependent variable. Employee share ownership, in turn, did not exert a direct statistically significant relationship on organizational citizenship behavior. This implies that governance mechanisms may influence employees' positive extra-role behaviors, but they do not exert this effect consistently. We conjure that the relational aspect (i.e., interactive nature, etc.) of agency monitoring and peer monitoring may better encourage employees to strive for extra-role behaviors, compared to governance mechanisms that are more procedural, such as employee share ownership that is consistently applied to employees, usually without regard for merit and performance (Hansmann 1996 ). Our results regarding hypothesis 2 (i.e., employee share ownership plans’ negative moderation effect) indicate that employees' perceptions of employee share ownership plans and its fair distribution may impact how employees' ownership feelings translate into extra-role behaviors. Indeed, per the Employee Retirement Income Security Act in the U.S., organizations cannot treat their employees differently in share distribution if an employee share ownership plan is used. In this sense, employees who meet the employee ownership qualifications join a class of shareholders whereby the method to determine their pro-rata share distribution is equal to all the other participants (in proportion to their salary, tenure, etc.) irrespective of their merit and individual performance (Kim and Ouimet 2014 ; Beatty 1995 ). The unfair perceptions that employees may associate with such treatments are likely to weaken identification processes with the organization, which would typically translate their ownership feelings into extra-role behaviors. The perceived unfairness may also diminish employees' sense of belonging, dwindling their willingness to give back to their organization through organizational citizenship behaviors. In addition, employees in share ownership plans are accustomed to being communicated with as an owner, yet they often have no actual managerial responsibilities or decision-making authority resulting from their share ownership; this likely has negative implications for identification processes of employees with the organization, and, as a result, cultural skepticism and distrust among employees might emerge. Our results regarding hypothesis 3 (i.e., the negative moderation effect of agency monitoring) suggest that agency monitoring may undermine ownership feelings' impact on organizational citizenship behavior because it projects hierarchy and separation between employees and ownership; hence, infusing a lack of internal locus of control (Kuvaas et al. 2017 ; Gagné and Deci 2005 ; Pierce et al. 2001 ). It may also trigger employees to question their genuity because ownership usually implies that the owners act in the best interests of the organization, hence, negating a need to be monitored (Sieger et al. 2013 ; Wagner et al. 2003 ).

Lastly, we contribute to agency theory by tapping more profoundly into "monitoring" as a governance mechanism by examining agency (supervisor) monitoring (Chrisman et al. 2007 ) and peer monitoring (Welbourne et al. 1995 ) as independent constructs. According to our results, peer monitoring does not moderate the relationship between psychological ownership and employee organizational citizenship behavior. We can explain this finding from a few perspectives. Comparing the findings of hypotheses 2 and 3 with hypothesis 4, we suggest that governance mechanisms moderate the relationship between psychological ownership and citizenship behaviors only when these extrinsic motivators are formally implemented in the organization through policies, guidelines, and organization procedures. It is possible that because peer monitoring mostly occurs through informal mechanisms (informal observation, employees’ word of mouth, etc.), it does not possess sufficient power to change the relationship between psychological ownership and organizational citizenship behavior compared to other governance mechanisms that are usually implemented through formal mechanisms. Even though peer monitoring has been anecdotally proposed as a governance mechanism to stall self-serving behaviors due to fears induced by peers' sanctions (Li et al. 2017 ; Loughry and Tosi 2008 ; Welbourne et al. 1995 ), it has another aspect that the other two mechanisms lack: It is self-initiated with fewer explicit and extrinsic triggers such as the direct impact on employees' incomes or threat of direct punishment by supervisors; therefore, it better lends itself to employee's interpretations and is more malleable regarding the functions that it serves. For instance, it can become a source of self-assessment and self-regulation (relative to peers). It can also boost the sense of morale among peers because of feedback loops and increased transparency (Mani and Mishra 2020 ). Therefore, when considered as a governance mechanism tool, peer monitoring should be analyzed with deeper scrutiny as its preventive capacity may be impacted by various roles that it plays in an organization. In addition, the non-significant moderation could result from the nature of the employees' tasks and their level of interdependence in our sample organizations. In other words, it is likely that only in organizations with high employee task interdependence does the moderating effect of peer monitoring become statistically significant (Bolduan et al. 2021 ). Finally, it is possible to attribute this non-significant relationship to the measurement of the peer monitoring construct in this study. For instance, respondents may not feel sufficient normative pressures at the departmental level, where we measured peer monitoring; hence, peer monitoring may not change the relationship between employees' ownership feeling and their citizenship behaviors.

By and large, one theoretical dilemma that we have tried to resolve comprises the circumstances under which governance mechanisms become less effective in the presence of employees' ownership feelings (Pierce and Furo 1990 ). One interesting (post-hoc) finding of our research is that at all levels of the two moderators (low, medium, and high), employee share ownership and agency monitoring, the relationship between psychological ownership and organizational citizenship behavior becomes weaker. Therefore, our findings regarding the weakening effect of employee share ownership and agency monitoring contribute to and add credence to the ongoing debate (Kuvaas et al. 2017 ) about the diminishing impact of extrinsic motivators on intrinsic ones (Gagné and Deci 2005 ; Calder and Staw 1975 ; Porter and Lawler 1968 ; Stajkovic and Luthans 2003 ). Beyond that, we have contributed to the theory by showing that the nature of the governance mechanism, formal vs. informal, may impact the relationship between psychological ownership and organizational citizenship behavior. According to our findings, the informal mechanisms underlying peer monitoring did not change the main relationship between psychological ownership and organizational citizenship behavior.

Furthermore, theoretically and empirically, our knowledge about the coexistence of (informal) ownership feelings and formal ownership in organizations is underdeveloped (Pierce et al. 1991 ; Chi and Han 2008 ). Contrary to the common assumptions about the construct of ownership, the logic of “the more, the better” does not apply here. Rather, it is possible that the ownership quality and substance matter more than its quantity. It is also possible that to serve effectively, employees should genuinely perceive themselves as owners because of share ownership plans to feel motivated to go above and beyond their assigned tasks (McConville et al. 2016 ).

5.2 Practical contributions

Organizations can use our findings to promote organizational citizenship behavior among their employees. We show that the one-size-fits-all approach to governance mechanisms is not effective. When designing the organizational architecture to encourage pro-organizational behaviors, managers should consider the combining effect of employees’ psychological ownership and different governance mechanisms. For instance, implementing employee share ownership or agency monitoring for employees with high psychological ownership can be ineffective. Furthermore, to mitigate the diminishing effect of governance mechanisms on employees' positive psychological attributes and extra-role behaviors, organizations may be able to frame such mechanisms in ways that align with employees' sense of belonging, self-identification with, and control over the organization.

5.3 Limitations and future research

Because the survey was conducted in the commercial engineering and construction industries in the United States, the generalization of our findings to other industries and cultural contexts should be made with caution. We encourage future researchers to examine our theoretical model across industries and employees of different cultural backgrounds. The cross-sectional design of this study represents another limitation. Our results suggest that our research model’s variables are related. However, albeit the order of our variables was guided by theory, we cannot make causal inferences from our data. Future research can explore these relationships in a longitudinal design (Spector 2019 ), for example, how participants’ organizational citizenship behavior changes with subsequent years of growth in employee share ownership. In addition, to further explore our non-significant moderation effect, examining this relationship on a narrower referent group (e.g., direct peer or workgroup) may be more desirable. Last but not least, the nature of our data may expose our findings to single-source bias. Other researchers can examine this relationship by collecting data not only from the employees but also from their peers and supervisors (Avolio et al. 1991 ) or by using qualitative methods, such as case studies to gain knowledge about the social contexts that underlie human decisions and behaviors (e.g., Riar et al. 2022 ).

There are ample opportunities to examine the role of individual characteristics (e.g., gender, skillsets, etc.) in the relationship between different ownership modes, governance, and organizational citizenship behavior. Although organizational citizenship behavior is a well-established indicator of extra-role behaviors, alternative measures, such as stewardship (Davis et al. 1997 ), servant leadership (e.g., Greenleaf 1977 ), and organizational commitment (e.g., Allen and Meyer 1990 ), may be applied to examine whether they will yield different results. Similarly, it is crucial to better understand the negative consequences of psychological ownership (e.g., escalation of commitment, etc.) on employees' positive behaviors (e.g., Pierce et al. 2009 ) and how perceived ownership feelings are interpreted by external stakeholders when they notice them, for which a signaling theory might be useful perspective (Spence 1973 ; Tao-Schuchardt et al. 2023 ).

Last, although some basic ideas of workplace research indirectly resonate in our study (as we consider governance systems that shape employees’ work environment and ultimately their behavior), we encourage researchers to expand on our theoretical arguments based on more recent workplace-focused theories, such as the previously mentioned sociomaterial lens (e.g., Orlikowski 2007 ). For example, it would be interesting to analyze in more detail how the sociomateriality of the interior architecture could change old agency relationships in organizations and how shifting sociomaterial assemblages entailed in contemporary organizations influence employees feeling, attitudes, and behaviors as well as organizational processes (e.g., Bouncken and Aslam 2021 ). Very little is known about how the workplace design as well as the technology structure employed in the organizations can facilitate both pro-organizational behavior (as in the focus of our study) or more general team or organizational performance. Particularly when focusing on employee-owned companies, such design choices may have different consequences than for non-employee-owned firms. Accordingly, we encourage more research in this area.

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Wilhelm, B., Simarasl, N., Riar, F.J. et al. Organizational citizenship behavior: understanding interaction effects of psychological ownership and agency systems. Rev Manag Sci 18 , 1–27 (2024). https://doi.org/10.1007/s11846-022-00610-z

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Annual Review of Organizational Psychology and Organizational Behavior

Volume 5, 2018, review article, organizational citizenship behavior: recent trends and developments.

• Dennis W. Organ 1
• View Affiliations Hide Affiliations Affiliations: Professor Emeritus, Kelley School of Business, Indiana University, Bloomington, Indiana 47405, USA; email: [email protected]
• Vol. 5:295-306 (Volume publication date January 2018) https://doi.org/10.1146/annurev-orgpsych-032117-104536
• First published as a Review in Advance on November 13, 2017
• © Annual Reviews

For decades, the accepted view in organizational psychology was that job satisfaction and job performance were unrelated. However, recent years have found increasing evidence that satisfaction, while not strongly related to task productivity by individuals, is more closely related to a different kind of contribution, which is referred to as organizational citizenship behavior (OCB). Furthermore, research in the past two decades has enriched the theoretical and empirical knowledge base of OCB, examining its relationship to culture, attitudes, personality, mood state, stress, and organizational performance.

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Does It Matter Where You’re Helpful? Organizational Citizenship Behavior from Work and Home

Rachel williamson smith.

Louisiana State University

Young-Jae Kim

University of Georgia

Nathan T. Carter

Associated data.

Organizational citizenship behaviors (OCBs) are commonly studied in the organizational and occupational health literature, yet, current OCB measures inherently assume individuals are performing these behaviors while physically at work. However, recent technological advances have afforded employees greater flexibility to engage in work-related behaviors at home, begging the question of whether OCBs are also being performed from home and their distinction from traditional OCBs. We provide evidence that OCBs performed while physically at work (OCB-W; i.e., traditional OCBs) are conceptually and empirically distinct from OCBs performed while physically at home (OCB-H). In Study 1 ( N = 292), we examine construct validity evidence for OCB-H with regard to its distinction from OCB-W and its unique nomological network. In Study 2, we further examine the distinction between OCB-H and OCB-W at the between- and within-person level using an experience sampling approach in a sample of 162 workers. Utilizing results from multilevel confirmatory factor analysis, we show that between-person variance in OCB-H is considerably higher than for OCB-W, and that although OCB-H and OCBW-H are strongly correlated at the between-person level, they are independent of one another within-person. We also examine these two forms of OCB as parallel mediators of the relation between work engagement-work interfering with family (WIF). Results suggest OCB-H and OCB-W are indeed distinct in the strength of their relationships to work engagement and WIF between- and within-persons.

Introduction

Organizational citizenship behaviors (OCBs) are actions that are generally prosocial in nature ( Organ, 1997 ), such as helping a supervisor without being asked, helping a co-worker with a heavy workload, or taking time to listen to a co-worker’s (personal or work) problem. OCBs have been a major focus in the organizational literature for decades, stemming from the notion that organizations depend on their employees to exhibit characteristics including helpfulness, general goodwill, altruism, and suggestions for improvement ( Katz, 1964 ; Smith, Organ, & Near, 1983 ). Since its inception, the OCB literature has largely focused on the target of the behavior ( Williams & Anderson, 1991 ), motives for OCBs ( Kim, Van Dyne, Kamdar, & Johnson, 2013 ; Lin, Savani, & Ilies, 2019 ), and its construct space ( Hoffman, Blair, Meriac, & Woehr, 2007 ; Organ, 1997 ). All the while, research on OCBs has assumed these behaviors are performed while physically at work. Yet, the growing literature on communication technology in relation to work have afforded employees much greater flexibility to perform work-related behavior while at home ( Boswell & Olson-Buchanan, 2007 ; Dettmers, Vahle-Hinz, Bamberg, Friedrich, & Keller, 2016 ), highlighting the need for research to examine differences related to where work-related behaviors, such as OCBs, are performed.

In the present paper, we extend the conceptualization of OCBs by exploring the notion that these behaviors can be performed either while physically at work or while physically at home, and that this distinction makes a critical difference in the construct space of OCBs regarding its correlates, predictors, outcomes, and the degree of variability at both the between- and within-person level. Specifically, we distinguish between OCBs that are performed while employees are physically at work (OCB from work, or OCB-W; the traditional conceptualization of OCB, such as helping a co-worker while physically at work) versus OCBs that are performed while the employee is physically at home (OCB from home, or OCB-H, such as helping a co-worker while physically at home). In Study 1, we provide evidence of construct validity for OCB-H and its distinction from OCB-W, as well as its distinction from related constructs such as work-family conflict and workaholism. In Study 2, we examine between- and within-person differences of OCB-H and OCB-W. Using experience sampling methodology, we test the utility of daily OCB-W compared with daily OCB-H as mediators in the relationship between daily work engagement and daily work-family conflict, two constructs that likely relate to both OCB-H and OCB-W and may highlight one of the many relationships in which the distinction between these two forms of OCB is critical.

The present research makes at least three major contributions to the literature. First, we clarify the construct space of OCB regarding where these work-related behaviors are performed. Given that OCBs have been linked with performance evaluation decisions ( Whiting, Podsakoff, & Pierce, 2008 ) and are often perceived by employees to be a part of their job description ( Turnipseed & Wilson, 2009 ), the potential finding of OCB-H as a distinct construct has important organizational implications. Second, we provide evidence of validity for a measure of OCB-H across two studies, including both a general measure and a day-level measure. Finally, in Study 2 we utilize experience sampling methodology to demonstrate the nuances of OCB-H and OCB-W at both the between- and within-person level in the context of variables that should relate to both forms of OCB but in unique, meaningful ways. We selected the work engagement-OCB-WIF relationship given that all three constructs have shown substantial between- and within-person variability, that this relationship has been observed in at least three separate samples ( Halbesleben, Harvey, & Bolino, 2009 ), and in particular, that the construct of WIF reflects conflict between the work and nonwork domains, which may be especially useful for capturing differences between OCB-W and OCB-H. As past research suggests that OCBs have substantial within-person fluctuation (e.g., Dalal, Lam, Weiss, Welch, & Hulin, 2009 ; Koopman, Lanaj, & Scott, 2016 ; Spence, Brown, Keeping, & Lian, 2014 ), we extend this research by examining whether the same is true of OCB-H.

The goal of Study 1 was to follow best practices for establishing evidence of construct validity for our OCB-H measure regarding its distinction from OCB-W as well as other related constructs. We provide initial evidence of construct validity for a previously developed measure of OCB (the OCB Checklist; Fox, Spector, Goh, Bruursema, & Kessler, 2012 ) adapted to capture that the behavior was performed at home (OCB-H). Given that the original measure was developed to capture OCB-W, the focus of our research is on establishing evidence of validity for our OCB-H measure, including evaluating the partial correlation of OCB-H with each hypothesized construct while controlling for OCB-W.

While we theorize that OCB-H and OCB-W are distinct constructs, we expect the two will be strongly related, given that they involve the same behaviors that only differ in terms of where the behaviors are physically performed. To establish additional evidence of construct validity, we will examine the relationship between our OCB-H measure and an OCB-W measure (the OCB-Checklist adapted to specify the behaviors were performed at work; Fox et al., 2012 ), which are identical with the exception of the item stem depicting where the behavior was performed. To provide additional evidence of construct validity, we examine the relationship between our OCB-H measure with another commonly used OCB-W measure developed by Lee and Allen (2002 ; referred to as OCB-LA).

• Hypothesis 1: OCB-H will be positively correlated with OCB-W

We also sought to demonstrate initial evidence of the nomological network of OCB-H. Regarding personality, meta-analytic evidence suggests OCB is related to conscientiousness (ρ = .18), agreeableness (ρ = .14), and neuroticism (ρ = .12) ( Chiaburu, Oh, Berry, Li, & Gardner 2011 ). Past research has argued that these traits are related to citizenship given the associations between conscientiousness and responsible behavior, agreeableness and interpersonal sensitivity, and the absence of neuroticism with positive emotions ( Chiaburu et al., 2011 ). Given the prosocial nature of OCBs, regardless of where they are performed, we anticipate these findings will extend to OCB-H and will remain related when controlling for OCB-W given the relative stability of personality traits.

• Hypothesis 2: OCB-H will be positively related to (2A) conscientiousness, (2B) agreeableness, and negatively related to (2C) neuroticism, and will remain significant after controlling for OCB-W

Another construct that is related to OCB is work engagement, a positive and fulfilling work-related state consisting of three components: vigor (high energy and mental resilience when working), dedication (a sense of pride, enthusiasm and significance to work), and absorption (happily engrossed in one’s work) ( Schaufeli, Salanova, Gonzalez-Roma, & Bakker, 2002 ). While these two constructs are related, they are distinct in that work engagement involves a motivational component, whereas OCB reflects the observed behaviors ( Simbula & Guglielmi, 2013 ). Generally, work engagement is positively related to OCB-W ( Halbesleben et al., 2009 ; Matta, Scott, Koopman, & Conlon, 2015 ; Simbula & Guglielmi, 2013 ), which we expect to extend to OCB-H. Additionally, meta-analytic evidence suggests that work engagement predicts contextual performance (a broader conceptualization of extrarole performance that includes OCBs) beyond job satisfaction, job involvement, and organizational commitment (Δ R 2 = .16) ( Christian, Garza, & Slaughter, 2011 ). Thus, we hypothesize that OCB-H will be positively related to work engagement, and will remain significantly related when controlling for OCB-W.

• Hypothesis 3: OCB-H will be positively related to work engagement and will remain significant after controlling for OCB-W

Given that OCB-H involves conducting work-related behaviors in the non-work domain, we anticipate OCB-H will relate to work-family conflict (WFC). WFC refers to interrole conflict in that the work and family domains elicit pressure on each other ( Carlson, Kacmar, & Williams, 2000 ; Greenhaus & Beutell, 1985 ), and can exist in two different directions, work interfering with family (WIF), and family interfering with work (FIW). Theory suggests three types of work-family conflict that are pertinent to both WIF and FIW: a) time-based conflict, b) strain-based conflict, and c) behavior-based conflict. Time-based work-family conflict occurs when something work-related requires time that interferes with time spent participating in the family domain. Strain-based work-family conflict occurs when stress in one domain interferes with the other domain (e.g., carrying over stress from work to home). Finally, behavior-based work-family conflict occurs when specific behaviors required in one role are not compatible with the behavior required in another role in the other. While these distinctions are important in many contexts, in the current study we focus on the general underlying variable of WIF as a composite of two of these types (time and strain). Although one of the seminal articles ( Greenhaus & Beutell, 1985 ) on work-family conflict theorized three forms of both WIF and FIW, the majority of the literature has focused on time- and strain-based WFC. Furthermore, we chose to include only time- and strain-based WIF as we have taken a conservation of resources lens and are hypothesizing specific relationships based on a shortage of resources, which corresponds with time-and strain-based WIF. As behavior-based WIF reflects a different type of conflict – that of behavioral expectations, we chose to exclude this aspect of WIF as it is not reflective of a resource-lens perspective. Furthermore, this rationale and practice is common in work-family research (e.g., Cho & Allen, 2012 ; Keeney, Boyd, Sinha, Westring, & Ryan, 2013 ; Rotondo, Carlson, & Kincaid, 2002).

As OCB-H involves taking time away from the nonwork domain to perform work-related behaviors, we anticipate that OCB-H will be especially important for predicting WIF. Although OCBs are beneficial for organizations and their members, recent studies suggest performing such behaviors at work consumes employees’ resources and energy, leading to lower emotional support for their family and spouse ( Lin, Ilies, Pluut, & Pan, 2017 ), and past research has found support for a positive relationship between OCB-W and WIF ( Halbesleben et al., 2009 ). We expect this finding to extend to OCB-H, given that the use of communication technology for work-related purposes after work hours is associated with increased WIF ( Diaz, Chiaburu, Zimmerman, & Boswell, 2012 ; Butts, Becker, & Boswell, 2015 ). Thus, we hypothesize that OCB-H will be positively related to WIF. Given the work-nonwork aspect of WIF, we expect this relationship will remain significant after controlling for OCB-W.

• Hypothesis 4: OCB-H will be positively related to work interfering with family and will remain significant after controlling for OCB-W

As OCB-H involves the work domain spilling over into the nonwork domain, we anticipate OCB-H will be particularly important for constructs involving the permeability of work and nonwork. As organizational expectations of after hours work predict increased after hours work ( Fenner & Renn, 2010 ), we anticipate a negative relationship between segmentation supplies (the extent to which an employer allows employees to segment work and nonwork) and OCB-H. Additionally, an employee’s own preferences for work and nonwork segmentation will likely influence the degree to which they perform OCB-H. Indeed, use of technology at home for work-related purposes is negatively associated with segmentation preferences ( Park, Fritz, & Jex, 2011 ). Given the work-nonwork aspect of these constructs, we hypothesize that OCB-H will be negatively related with segmentation preferences and segmentation supplies, and that both relationships will remain significant after controlling for OCB-W.

• Hypothesis 5: OCB-H will be negatively related to (5A) segmentation preferences and (5B) segmentation supplies, and will remain significant after controlling for OCB-W

Counterproductive work behavior (CWB; discretionary behavior that is harmful to an organization) is one of the most commonly studied constructs in relation to OCB. OCB and CWB used to be considered opposite poles, as theoretical and empirical work established a negative relationship between these constructs ( Dalal, 2005 ). However, more recent research has uncovered that the negative relationship between these two constructs may be due to measurement artifacts. In particular, measures of OCB which include antithetical items (e.g., reverse-coded CWB items) may unintentionally overlap OCB and CWB content, when in fact OCB is not the opposite of CWB ( Fox et al., 2012 ). Furthermore, measures which utilize agreement scales may introduce acquiescence, reflecting one’s general impression of their behavior rather than the actual frequency. Theoretically, scholars have noted that behavior is complex, and negative work experiences may in fact result in both OCB and CWB. A number of reasons have been proposed regarding a potentially positive relationship between OCB and CWB, including injustice and anger, moral licensing, resource depletion, and impression management ( Bolino & Klotz, 2015 ). Thus, studies utilizing the OCB-Checklist (which utilizes a frequency response scale and lacks antithetical items) and CWB measures relying on a frequency response scale have observed a positive relationship between OCB and CWB ( Bauer, Wright, Askew, & Spector, 2018 ; Fox et al., 2012 ; Spector & Che, 2014 ). Given that our OCB-H measure is derived from the OCB-Checklist, and that we utilize a CWB measure with a frequency response scale, we hypothesize that OCB-H will be positively related to CWB. Furthermore, given that individuals performing OCB-H may experience some degree of frustration or dissatisfaction with having to perform work-related behaviors during nonwork time, we expect this relationship will remain significant after controlling for OCB-W.

• Hypothesis 6: OCB-H will be positively related to CWB, and will remain significantly related after controlling for OCB-W.

Due to the nature of OCB-H involving the performance of work tasks outside of standard working hours, we theorize that these behaviors are likely related to workaholism, a relatively stable strait that reflects the compulsion to work beyond what is reasonably expected. Employees high in workaholism are more likely to perform work-related tasks from home ( van Wijhe, Peeters, Schaufeli, & Ouweneel, 2013 ) and prefer working over engaging in a leisure activity during non-work time ( Snir & Zohar, 2008 ). Yet, while research has consistently shown that workaholics continue to perform work-related activities during leisure time, there is a lack of research uncovering the specific behaviors workaholics are performing during leisure time. Thus, we propose that they will likely find any possible task to continue working while at home to satisfy their compulsions, which may take the form of OCBs. In other words, engaging in OCB-H may be one way for a workaholic to continue their work even after they have physically left the workplace, by performing behaviors such as finishing additional work, continuing to work from home through meals, or finishing some work- related assignment for a co-worker. Therefore, we hypothesize that OCB-H will be positively related to workaholism, and will remain significantly related after controlling for OCB-W.

• Hypothesis 7: OCB-H will be positively related to workaholism and will remain significant after controlling for OCB-W

Regarding discriminant validity, we expect that OCB-H will be statistically distinct from task performance. Whereas past research suggests that OCB and task performance are related yet distinct constructs ( Hoffman et al., 2007 ; Kamdar & Van Dyne, 2007 ), we anticipate this extends only to OCB-W, given that both OCB-W and task performance are conducted while physically at work. As OCB-H reflects an individual going above and beyond during nonwork time, we expect that OCB-H will be unrelated to task performance. This is in line with recent research suggesting that OCBs may have diminishing returns on task performance, particularly when they require a large amount of personal resources ( Ellington, Dierdorff, & Rubin, 2014 ), as is the case with OCB-H. Taken together, we do not expect OCB-H and task performance to be related.

Additionally, past meta-analytic research suggests that the personality traits of extraversion and openness are more relevant for change-oriented citizenship than general OCBs ( Chiaburu et al., 2011 ), which reflects proactive behaviors rather than prosocial behaviors. The authors suggested this was likely due to the association of these traits with a need for growth and agency ( Digman, 1997 ), which is more consistent with change-oriented citizenship. Given that personality traits are relatively stable individual differences, we anticipate these findings will extend to OCB-H. Thus, we do not expect OCB-H to be related to extraversion or openness.

Participants and procedures.

Participants were recruited through Prolific Academic ( https://prolific.ac/ ), an online platform connecting researchers and participants. Participants were eligible to sign up for the study if they lived in the United States and were employed full-time. 301 participants completed the study and were paid $2.00 each. Of the 301 participants that completed the survey, three participants were removed for incorrectly responding to an attention check (e.g., “please select strongly agree”), and six were removed for reporting they worked fewer than 30 hours per week, bringing our final sample to 292 participants. Participants were 35.56 years old on average ( SD = 9.64), worked an average of 41.82 hours per week ( SD = 5.18), and had an average job tenure of 4.59 years ( SD = 5.21). 50.7% of the sample were male (47.9% female, 1.4% non-binary), and the majority were Caucasian (83.6%), followed by Asian/Pacific Islander (6.8%), African American (5.8%), Hispanic/Latino (5.8%), and Native American or American Indian (1.0%) 1 . The majority of participants held at least a 4-year college degree (70.6%). A little over half (57.5%) of participants reported living with their spouse/partner, 34.2% reported living with children, and 11.6% reported living with one or both parents.

OCB-H and OCB-W.

To capture OCB-W and OCB-H, we utilized OCB items from a commonly used scale: the OCB checklist ( Fox et al., 2012 ). All items were measured on a 5-point scale (1 = never, 5 = everyday). The OCB-W measure included all 20 items from the OCB checklist, and participants were instructed to indicate how often then engaged in each behavior while physically at work. An example item is “I volunteered for extra work assignments.” The OCB-W measure presented acceptable evidence of reliability (α = 90). The OCB-H items were identical to the OCB-W items, except that the instructions requested participants indicate how often they engaged in each behavior while physically at home. Four items could not be adapted for performing from home (e.g., “I picked up a meal for others at work.”) and thus were not included in our data collection. 2 The OCB-H measure presented acceptable evidence of reliability (α = 95). We also included an additional measure of OCB-W (OCB-LA), a 16-item measure developed by Lee and Allen (2002) . Example items include “attend functions that are not required but that help the organizational image” and “give up time to help others who have work or nonwork problems.” Items were measured on a 5-point scale (1 = never, 5 = everyday). The measure demonstrated adequate reliability (α = .91).

Personality traits.

The five personality traits were measured using the mini-IPIP ( Donnellan, Oswald, Baird, & Lucas, 2006 ; Goldberg, 1999 ), which consists of four items per personality trait. Items were measured on a 5-point scale (1 = strongly disagree, 5 = strongly agree). All personality traits demonstrated adequate reliability: neuroticism (α = .76); agreeableness (α = .81); conscientiousness (α = .78); extraversion (α = .89); openness (α = .79).

Work engagement.

Work engagement was measured using the 9-item version of the Utrecht Work Engagement Scale (UWES-9; Schaufeli, Bakker, & Salanova, 2006 ). The UWES-9 consists of three facets (vigor, dedication, and absorption) comprised of three items each. An example item is “at my work, I feel bursting with energy” (vigor). Items were measured on a 7-point scale (1 = never, 7 = always). The measure demonstrated adequate reliability (α = .93).

WIF was measured using the eight-item negative work-home interface (WHI) subscale of the SWING (Survey Work-Home Interaction NijmeGen; Geurts et al., 2005 ) on a 7-point scale (1 = never, 7 = always). Items are framed in the context of how often they are experienced, such as “You are irritable at home because your work is demanding.” The WIF measure presented acceptable evidence of reliability (α range = .93).

Segmentation preferences.

Segmentation preferences were measured with the 4-item scale by Kreiner (2006) , with higher scores indicating a stronger preference for segmentation. An example item is “I like to be able to leave work behind when I go home). Items were measured on a 7-point scale 1 = strongly disagree, 7 = strongly agree). The scale demonstrated adequate reliability (α = .93).

Segmentation supplies.

Segmentation supplies were measured with the 4-item scale by Kreiner (2006) , with higher scores indicating greater segmentation supplies. An example item is “at my workplace, people are able to prevent work issues from creeping into their home life.” Items were measured on a 7-point scale 1 = strongly disagree, 7 = strongly agree) and demonstrated adequate reliability (α = .96).

CWB was measured using the 10-item version of the CWB-Checklist (CWB-C; Spector, Bauer, & Fox, 2010 ). Example items include “ignored someone at work” and “stayed home from sick and said you were sick when you weren’t.” Items were measured on a 5-point scale (1 = never, 5 = every day). The scale demonstrated adequate reliability (α = .83).

Workaholism.

Workaholism was measured using the 9-item compulsive tendencies subscale of the Work Addiction Risk Test (WART; Robinson, 1999 ). Example items include “I feel guilty when I am not working on something” and “I overly commit myself by biting off more than I can chew.” Items were measured on a 4-point scale (1 = strongly disagree, 4 = strongly agree) and demonstrated adequate reliability (α = .81).

Task performance.

Task performance was measured via self-report with three items developed by Griffin and colleagues (2007) . An example item is “I carry out the core parts of my job well.” Items were measured on a 6-point scale (1 = strongly disagree, 6 = strongly agree). The scaled demonstrated adequate reliability (α = .90).

All correlations were conducted in SPSS v. 25. Mean scores were created for all measures. Descriptive statistics and bivariate correlations between study variables can be found in Table 1 . To provide additional evidence of construct validity, we compared bivariate correlations as well as partial correlations of OCB-H with all variables controlling for OCB-W (see Table 2 ). Additionally, we utilized the mirt ( Chalmers, 2012 ), lavaan ( Rosseel, 2012 ), and semPlot ( Epskamp, 2015 ) packages in R to provide evidence of internal structural validity.

Correlations between Study 1 variables

Note. N = 292. OCB-W = Organizational Citizenship Behaviors at Work; OCB-H = Organizational Citizenship Behaviors at Home;

WIF = Work interfering with Family; CWB = Counterproductive Workplace Behaviors

All correlations in bold indicate the value is statistically significant at p < .05.

Bivariate and partial correlations of OCB-H in study 1

Note. N = 292. OCB-H controlling for OCB-W reflect partial correlations. OCB-W = Organizational Citizenship Behaviors at Work; OCB-H = Organizational Citizenship Behaviors at Home; WIF = Work interfering with Family; CWB = Counterproductive Workplace Behaviors.

Internal structural validity.

To further examine the psychometric properties of our 16 OCB-H items, we first estimated the unidimensional item response theory (IRT) graded response model (GRM; Samejima, 1968 ). This IRT model proposes that item options are necessarily ordered, but that the space between options can vary, just as we would suspect this measure would function. Indeed, the model showed good global fit to the data, M 2 (56) = 115.76, CFI = .98, TLI = .97, RMSEA = .061 (90% CI: .045; .076), SRMSR = .060, with IRT-based marginal reliability of .89. Item fit statistics (i.e., S – c2; Orlando & Thissen, 2000 ), showed no p -values below the Bonferonni corrected value of .002 (see Table 3 ), suggesting all items behaved as expected. Figure 1 shows the test characteristic and item information curves. These curves suggest that those higher in OCB-Hs are most reliably measured by this scale, but suggest reliability is sufficient for those at least 1 SD below the mean of the underlying variable.

Test Characteristic (right) and Test Information Curves (left) for the OCB-H Measure in Study 1.

Note . T(θ) indicates the total score give θ, whereas I(θ)

Item response theory parameters and item-level fit statistics for the OCB-H Measure in Study 1

Table 3 shows the IRT item parameters. The item discrimination parameter, a , is conceptually similar to a factor loading, in that larger numbers indicate a stronger relation to the underlying variable. Discrimination parameters fell between 1.05 and 3.74, a reasonable range for this parameter, given recommendations that low discrimination parameters suggest poor items ( Zickar, 1998 ), and that larger item discriminations are often observed in conceptually narrow constructs ( Reise & Waller, 2009 ), such as OCB-H. The b parameters are “location” parameters that index the level of the underlying variable at which one response option becomes more attractive than the previous option. For example, for Item OCBH_1, b 1 = 0.18, indicating that those 0.18 SD above the mean level of OCB-H have a 50% chance of choosing response option 2 over response option 1; similarly, b 2 = 2.92, indicating that those 2.92 SD above the mean level of OCB-H have a 50% chance of choosing response option 3 over response option 2, and so on. Items with higher average thresholds ( b ^ ) are “extreme” items, in that one must be very high in the underlying variable to fully endorse such items, whereas it is “easy” to endorse less extreme items. It is not surprising that the majority of b 3 and b 4 parameters are 3 or larger (indicating 3 SD above the mean) as each scale point reflected the frequency each behavior was performed per day. Our data suggest that it is far more common for employees to perform OCBs once or twice a day, if it all, with very few performing OCBs three or more times a day. The mapping of item content onto these values seems sensible, in that the most extreme items involved picking up food, and taking phone calls/messages for a co-worker at home, whereas less extreme items involved lending a compassionate ear or giving encouragement to a coworker.

To determine whether OCB-H is indeed distinct from OCB-W, we conducted confirmatory factor analyses (CFAs) using diagonally weighted least squares estimation. First, we estimated a three-factor model in which our OCB-H measure reflected one factor and two popular measures of OCB-W reflected their own factors. This model showed good fit to the data, χ 2 (1,271) = 2240.06, p < .001, CFI = .97, TLI = .97, RMSEA = .051 (90% CI: .048; .055), SRMSR = .081, AIC = 37471, BIC = 37864. The OCB-H factor correlated similarly with the two OCB-W factors at .50 with the Spector and Fox measure and .54 with the Lee and Allen measure; the two OCB-W factors correlated .84. Next, we simplified this model such that both OCB-W measures loaded onto the same factor. This model showed equivalently good fit to the data compared to the three-factor, χ 2 (1,273) = 2,380.16, p < .001, CFI = .96, TLI = .96, RMSEA = .055 (90% CI: .051, .058), SRMSR = .083, AIC = 37675, BIC = 38060, suggesting the OCB-W measures reflected the same underlying factor; the OCB-H factor correlated .54 with the OCB-W factor. The three-factor model fit the data significantly better than the two-factor model per the chi-square difference test (Δχ 2 (2, N = 292) = 207.81, p < .001), suggesting the three-factor model fit slightly better than the two-factor model. Finally, we tested a single-factor model, which showed considerably poorer fit compared to the two-factor model, χ 2 (1,274) = 3,824.75, p < .001, CFI = .91, TLI = .91, RMSEA = .083 (90% CI: .080, .086), SRMSR = .128, AIC = 39531, BIC = 39912. The two-factor model fit the data significantly better than the one-factor model per the chi-square difference test (Δχ 2 (1, N = 292) = 1857.60, p < .001), suggesting the two-factor model fit better than the one-factor model. When comparing models, we took a collective approach, considering the chi-square difference test and goodness-of-fit indices based on past recommendations (Jöreskog & Sörbom, 1996). Our results concluded that the two-factor model fit the data better than the one-factor model, suggesting that OCB-H is distinct from OCB-W. While the three-factor model fit the data slightly better than the two-factor model, the difference in fit indices were minimal, suggesting it was appropriate to collapse the two OCB-W constructs together to form a composite OCB-W variable. Thus, all analyses in Study 1 include a combined OCB-W construct comprised of the two OCB-W measures.

Construct validity.

Our OCB-H measure was significantly correlated with OCB-W ( r = .51, p < .001) suggesting a strong correlation, yet not to a level that would suggest OCB-W and OCB-H are overlapping constructs. Together, this provides evidence of construct validity for our OCB-H measure, supporting Hypothesis 1.

OCB-H was unrelated to conscientiousness ( r = −.02, p = .791), positively related to agreeableness ( r = .18, p < .01), and unrelated to neuroticism ( r = .08, p = .161). However, OCB-H was unrelated to all three of these traits when controlling for OCB-W (conscientiousness: r = −.07, p = 236; agreeableness: r = .05, p = .354; neuroticism: r = .10, p = .091), providing partial support for Hypothesis 2. OCB-H was positively related to work engagement ( r = .27, p < .001), but was unrelated when controlling for OCB-W ( r = .06, p = .279), providing partial support for Hypothesis 3. OCB-H was positively related to WIF ( r = .24, p < .001), and remained significantly associated when controlling for OCB-W ( r = .13, p < .05), supporting Hypothesis 4 3 . OCB-H was negatively related to both segmentation preferences ( r = −.19, p < .01) and segmentation supplies ( r = −.19, p < .01), and OCB-H remained significantly correlated with both segmentation preferences ( r = −.20, p < .01) and segmentation supplies ( r = −.16, p < .01) when controlling for OCB-W, supporting Hypothesis 5. OCB-H was positively related to CWB ( r = .29, p < .001), and remained positively related when controlling for OCB-W ( r = .24, p < .001), supporting Hypothesis 6. Finally, OCB-H was positively related to workaholism ( r = .18, p < .01), but was unrelated after controlling for OCB-W ( r = .03, p = .673), partially supporting Hypothesis 7.

Regarding discriminant validity, OCB-H was unrelated to task performance ( r = .06, p = .300), and remained unrelated when controlling for OCB-W ( r = −.06, p = .321), in line with our expectations. OCB-H was positively related to extraversion ( r = .17, p < .01), but was not related to openness ( r = .08, p = .179). OCB-H was no longer significantly related to extraversion when controlling for OCB-W ( r = .09, p = .113), and remained unrelated to openness when controlling for OCB-W ( r = .02, p = .713).

Study 1 Discussion

Study 1 provided initial evidence of construct validity for OCB-H. Through multiple analytic approaches including correlations, CFA, and IRT, we provided evidence that OCB-H was significantly associated with, yet distinct from, OCB-W. While our hypotheses regarding OCB-H and the personality traits of openness and agreeableness were supported, the relationships between OCB-H and extraversion, conscientiousness, and neuroticism were not. Furthermore, all personality traits were unrelated to OCB-H after controlling for OCB-W. One explanation for this may be the measure we selected, which is a short version of each personality trait. Given that each of the broad personality traits are comprised of lower-order aspects and facets ( Judge et al., 2013 ), it could be the case that our measures did not adequately capture the full trait, explaining the unexpected relationships. Additionally, it could be that personality traits simply have a stronger relationship with OCB-W than OCB-H. More research is needed to uncover the nature of these relationships.

The positive relationship between OCB-H with both work engagement and WIF provides additional evidence of construct validity and is in line with past research ( Halbesleben et al., 2009 ), although, the relationship became non-significant after controlling for OCB-W, counter to expectations. The negative relationships between OCB-H and both segmentation preferences and segmentation supplies provide additional insight into the nomological network of OCB-H. The fact that OCB-H remains significantly correlated with both segmentation preferences and segmentation supplies after controlling for OCB-W suggests that individuals who perform OCBs from home are likely those who prefer to integrate work and nonwork, but that organizational pressure may also be at play. The positive relationship between OCB-H and CWB is in line with past research ( Bauer et al., 2018 ; Fox et al., 2012 ; Spector & Che, 2014 ). Additionally, the positive relationship between OCB-H and workaholism provides initial insight into potential work-related behaviors workaholics may perform during non-work time. As expected, OCB-H was not related to task performance, whereas OCB-W was positively related to task performance. This serves as evidence of both discriminant validity for OCB-H from task performance, as well as an example of different nomological networks for OCB-H and OCB-W. It should be noted that we used a self-report measure of task performance which warrants the need for future research to confirm our findings with other-reports of performance. In sum, while some questions remain regarding the relationships between OCB-H and personality traits, the majority of our hypotheses were supported, together providing evidence of construct validity.

In Study 2, we extend our findings concerning OCB-H and OCB-W through an experience sampling approach, in line with the growing body of research in occupational health psychology utilizing daily diary studies to examine within-person experiences ( Allen & Martin, 2017 ). Thus, the current research has important implications for the field of occupational health and particularly the influence of occupational stress on both the work and family domains. Although Study 1 served to provide evidence of validity and the nomological network of OCB-H, we were unable to examine differences regarding between- and within-person fluctuations of OCB-H and OCB-W due to the cross-sectional design of our study. We view this as an important next step, given that OCB-W has significant variability both between- and within-individuals ( Koopman et al., 2016 ; Spence, Ferris, Brown, & Heller, 2011 ; Spence et al., 2014 ). OCB-H may exhibit similar levels of variability, or, OCB-H may better reflect a between-person difference, in that employees either regularly perform these work-related behaviors at home or not at all. In Study 2, our primary goal was to compare the between- and within-person differences across OCB-W and OCB-H. We selected the work engagement-OCB-WIF relationship given that this relationship has been confirmed in at least three distinct samples ( Halbesleben et al., 2009 ), and given that a substantial amount of research has provided evidence of day-level fluctuation of these constructs. Finally, given the work-domain nature of work engagement and the home-domain nature of WIF, we anticipated the work engagement-OCB-WIF relationship may highlight one of the many ways OCB-W and OCB-H differ. Next, we discuss these hypothesized relationships in further detail.

The Work Engagement-WIF relationship

Given that the focus of Study 2 is on the mediating effects of OCB-H and OCB-W on the relationship between work engagement and WIF, we begin by discussing the direct relationship between work engagement and WIF. The construct of work engagement reflects a positive state operationalized by vigor, dedication, and absorption in the conduct of work-related behavior ( Demerouti, Bakker, De Jonge, Janssen, & Schaufeli, 2001 ; Schaufeli et al., 2002 ). Generally, work engagement is associated with positive outcomes, including well-being ( Shimazu, Schaufeli, Kamiyama, & Kawakami, 2015 ), job performance ( Bakker & Bal, 2010 ), and work-family facilitation ( Bakker, Shimazu, Demerouti, Shimada, & Kawakami, 2014 ). However, a new vein of research has posited there may be a downside to work engagement, as highly engaged employees may expend too much of their time and energy on work as opposed to their familial roles, leading to work-family interference ( Halbesleben et al., 2009 ).

Drawing on conservation of resources theory ( Hobfoll, 1989 ), Halbesleben and colleagues (2009) theorized that although engaged employees may complete more tasks during the workday ( Salanova, Agut, & Peiro, 2005 ), the completion of these tasks requires effort, time, and psychological investment. This view has been supported empirically at the within-person level: on days when employees expend resources to help their organization, they have fewer resources to expend at home, taking the form of less spousal support ( Lin et al., 2017 ). To date, theoretical justification for a positive association between work engagement and WIF has been addressed with only a handful of empirical evidence, which notably has primarily been observed at the between-person level. Using a between-person approach, Halbesleben and colleagues (2009) found that across three samples, work engagement was associated with increased WIF. Furthermore, a meta-analysis conducted by Halbesleben (2010) found a positive relationship between work engagement and WIF (ρ = .42).

However, the relationship between work engagement and WIF may differ at the within-person level. For instance, Derks and colleagues (2015) theorized that daily work engagement should be associated with decreased WIF due to engaged workers’ ability to disconnect from work during nonwork time ( Bakker, 2014 ; Kuhnel, Sonnentag, & Westman, 2009 ). To date, a handful of studies have examined daily work engagement and work-family outcomes. Derks and colleagues observed a negative correlation ( r = −.31, p < .01) between daily work engagement and daily WIF (2015). Simbula and colleagues (2010) observed a non-significant relationship between daily work engagement and daily WFC ( r = .01). Sanz-Vergel and colleagues (2010) examined day-level WIF and daily vigor (one facet of work engagement) and found the two were negatively correlated ( r = −.22, p < .01). In a separate study, Sanz-Vergel and colleagues (2011) found no relationship between morning vigor and evening WIF ( r = .07). Given the mix of findings at the daily level, we do not hypothesize a specific direction regarding the relationship of daily work engagement measured during the workday on daily WIF measured during the evening. Next, we expand upon past research on the mediating influence of OCB-W and OCB-H in this relationship.

Organizational Citizenship as an Explanatory Mechanism

The nature of employee work engagement has theoretical overlap with OCB; work engagement is associated with positive emotion ( Bindl & Parker, 2010 ), thus employees in a state of work engagement may be more adaptive and helpful in the workplace ( Eldor & Harpaz, 2016 ). Indeed, Eldor and Harpaz (2016) theorized and found support for work engagement leading to increased extra-role behaviors, as engaged employees were more likely to take initiative, desired sharing knowledge with coworkers, and were more open to change. Additionally, recent empirical work suggests that work engagement can lead to OCB and explains incremental variance beyond more commonly-studied job attitudes, including organizational commitment and job satisfaction ( Christian et al., 2011 ). In sum, these findings are in line with theory suggesting that to the extent individuals invest more of themselves into work via work engagement, the more willing they should be to engage in behaviors outside of their formal boundaries, including OCB ( Rich, LePine, & Crawford, 2010 ).

While work engagement may be beneficial for organizations and their members due to its association with prosocial work behaviors such as OCB, the enactment of OCBs may come at a cost for the individual ( Bolino & Grant, 2016 ; Deery, Rayton, Walsh, & Kinnie, 2016 ) and thus their families ( Lin et al., 2017 ). Generally, researchers have drawn on conservation of resources theory ( Hobfoll, 1989 ) to suggest that OCBs limit the resources (i.e., time, energy) available for other activities. Several studies have found that the performance of OCBs is associated with higher levels of emotional exhaustion ( Koopman et al., 2016 ), WFC ( Deery et al., 2016 ), and less support provided to one’s spouse ( Lin et al., 2017 ).

To date, one paper has examined the potential mediating mechanism of OCB for explaining work engagement leading to increased WIF. Halbesleben and colleagues (2009) examined this relationship in three separate studies, even separating out the forms of WIF (time-, strain-, and behavior-based). While the authors found support for their proposed relationship across all three studies and forms of WIF, the present study aims to expand upon the findings of Halbesleben and colleague’s research in a number of ways. First, Halbesleben and colleagues utilized a between-person approach, whereas the present study is examining the proposed relationships from both a between- and within-person perspective. Whereas cross-sectional studies only allow for comparisons between participants, experience sampling studies afford the ability to disentangle both between- and within-person differences. In fact, work engagement ( Breevart & Bakker, 2017 ), OCB ( Koopman et al., 2016 ), and WIF ( Butts et al., 2015 ) have all been examined separately using experience sampling methodology, as these constructs are thought to fluctuate both between- and within- individuals. Thus, the present study seeks to examine the dynamic relationship between these constructs at the daily level. Additionally, although research by Halbesleben and colleagues (2009) suggests OCB acts as an explanatory mechanism for the positive relationship between work engagement and WIF, we propose that this link can be better understood by differentiating between OCBs that are conducted in the workplace versus those an employee performs at home. As noted above, conservation of resources theory would suggest OCBs limit time and energy for activities both inside and outside the workplace. Thus, although OCB-W may drain resources and lead to WIF, we propose that it is also important to consider OCB-H, which are likely to drive more strain-, and time-based conflict between work and family roles.

From the perspective of conservation of resources theory, theoretical and empirical work suggests OCBs represent a mediating mechanism for the positive association between work engagement and WIF ( Halbesleben et al., 2009 ). Specifically, engaged employees expend high levels of their personal resources by performing higher-than-average OCBs, leading ultimately to the depletion of resources and thus WIF. In other words, while work engagement itself reflects a high level of involvement and investment in work, the link between work engagement and WIF may be explained by the associated behaviors (i.e., OCB) of engaged employees which deplete resources that would otherwise be available for the family domain. Thus, resources devoted to the work domain through OCB-W and OCB-H ultimately impact the available resources for the home domain, resulting in increased WIF through the process of resource drain ( Edwards & Rothbard, 2000 ). We propose that in the context of WIF, it will be particularly important to account for where an employee is when they are carrying out OCBs. We believe this distinction is particularly timely as recent advances in communication technology (e.g., e-mail, cell phones, pagers, wearable technology) have afforded employees much greater flexibility to engage in work-related behavior at home ( Boswell & Olson-Buchanan, 2007 ; Dettmers et al., 2016 ), as many jobs now present the possibility for employees to work at any time from any location. This is especially relevant in the context of WIF, as the extent to which employees perform work-related tasks after working hours (often using communication technologies) has been linked to increased WIF ( Butts et al., 2015 ; Fenner & Renn, 2010 ). However, there is limited research on the specific behaviors performed by employees after work hours. Given that OCBs are discretionary, yet often perceived by employees as part of their job description ( Turnipseed & Wilson, 2009 ), we theorize that OCBs performed at home may be one conceptualization of the type of conduct alluded to in communication technology-WIF research.

A common example of an OCB is lending a compassionate ear when someone has a work problem. If this behavior is performed at work, it requires the employee to expend resources that could not have been expended in the family domain in real time, reflecting the process known as resource drain ( Edwards & Rothbard, 2000 ). Specifically, a negative relationship is theorized between work and family resources, as those resources drained for the purpose of one domain (i.e., work) are therefore unavailable for the other domain (i.e., family). We propose that OCB-W would lead to WIF, but perhaps exhibits a weaker relationship (than OCB-H), as these behaviors are more distal to the home environment. On the other hand, an OCB such as lending a compassionate ear when someone has a work problem can also be performed after leaving the workplace. While this OCB can be performed at work, a colleague that wants to vent about a work problem may prefer to talk about it away from work, such as over the phone once both individuals are away from the work environment and other coworkers. If an employee is engaging in the behavior within high proximity to the familial environment, as opposed to spending their resources (e.g., time, energy) on their family, the employee should experience significantly more WIF. From a conservation of resources theory lens ( Hobfoll, 1989 ), we theorize that OCB-W and OCB-H will consume energies resources, such as time and strain, leading to increased WIF. Notably, energies resources are defined as volatile resources, such that they are fleeting and thus irreplaceable ( ten Brummelhuis & Bakker, 2012 ). For instance, the time devoted to performing OCB-H on any given day inherently means that this time is taken away from nonwork-time in the home domain.

• Hypothesis 8A: Daily OCB-W will mediate the relationship between daily work engagement and daily WIF.
• Hypothesis 8B: Daily OCB-H will mediate the relationship between daily work engagement and daily WIF.

Between- and Within-Person Fluctuations of OCB-W and OCB-H

While between- and within-person fluctuations of OCB-W have been observed in past research ( Dalal et al., 2009 ; Koopman et al., 2016 ; Spence et al., 2014 ), given that this the first examination of day-level OCB-H, we seek to examine the degree of fluctuation in OCB-H at the between- compared with the within-person level, and ultimately compare our hypotheses across levels. Thus, we examine the following research question in conjunction with our hypotheses:

• Research Question 1: Do findings differ at the between- and within-person level of analysis?

Subjects were recruited through social media efforts (e.g., Facebook, LinkedIn, Reddit). To be eligible, participants had to be working full-time in an organization with only one job, living in the United States, able to read English, be 18 years of age or older, work only one job that (a) requires them to physically leave their home for at least 6 hours a day on workdays, and (b) requires they work at least five days a week. As the focus of Study 2 includes WIF as our dependent variable, we screened participants to ensure they were currently living with a family member, as an individual who lives alone may not experience WIF. Upon completion, participants received a check for $20. Participants with perfect compliance received a $10 bonus, resulting in $30 total.

We utilized experience sampling methodology. During the initial screener we measured four control variables – age, gender, marital status, and children living at home, and additional demographic items that did not relate to eligibility. During this survey we also captured a number of variables from Study 1 to replicate our findings: personality, segmentation preference, and workaholism. Eligible participants were then contacted with details about when to expect the daily surveys (twice a day for five working days; once at the end of the workday and once before bed). Daily surveys were sent at specific times based on participants work schedule for the given week. Afternoon surveys were sent an hour before the end of each participant’s workday. Participants were instructed to complete afternoon surveys before they left work for the day, so as to ensure the behavior was performed while physically at work. Evening surveys were sent around 9:00 PM; participants were instructed to complete evening surveys before they went to bed. The end of workday surveys included measures of state work engagement and OCB-W. The surveys taken before bed included measures of OCB-H and WIF. Upon finishing their final survey, participants were sent a check for $20.00 (or $30.00 for perfect compliance).

Out of 322 participants that took the initial screener, 201 were eligible, of which 163 responded and completed the daily surveys (81.1% response rate). The average number of daily surveys completed was 7.79 (out of 10). The final number of surveys completed was 1,261. Participants held a range of occupations (e.g., Professor, Vet Tech, Physical Therapist, Finance Manager, Attorney, Chef, etc.). The average age of participants was 31.34 years ( SD = 7.86). Participants had an average tenure of 4.17 years ( SD = 3.43) and worked 45.09 hours on average each week ( SD = 6.80). 38.3% of participants held a supervisory role. 79% of the participants were female, and 90% identified as Caucasian. 79.6% were married and/or living with their partner. 30.2% of the sample reported living with one or more of their children, and 1.2% reported that one or both of their parents lived with them.

Study measures: Initial survey.

Personality..

The five personality traits were measured using the same scales as Study 1, with the exception that we expanded our conscientiousness measure from a 4-item measure to a 10-item measure. Items were measured on a 4-point scale (1 = strongly disagree; 4 = strongly agree). All five personality traits displayed adequate reliability (extraversion α = .86; neuroticism α = .73; conscientiousness α = .81; agreeableness α = .82; openness α = .80).

Segmentation preferences was measured with the same 4-item scale as Study 1 by Kriener (2006), with higher scores indicating a stronger preference for segmentation. Items were measured on a 4-point scale 1 = strongly disagree, 4 = strongly agree) and demonstrated adequate reliability (α = .90).

As with Study 1, workaholism was measured using the 9-item compulsive tendencies subscale of the Work Addiction Risk Test (WART; Robinson, 1999 ). Items were measured on a 1–5 Likert scale (1 = strongly disagree, 5 = strongly agree). The workaholism measure presented acceptable evidence of reliability (α = .78).

Day-level measures.

Organizational citizenship behaviors..

To measure OCBs, we utilized the same measure from Study 1, adapted to day level measurement. Our daily OCB-W measure included all 20 items from the OCB checklist. An example item is “Today at work, I volunteered for extra work assignments.” The OCB-W measure presented acceptable evidence of reliability at all time points (α range = .84 to .89). An example OCB-H item is “while at home, I volunteered for extra work assignments.” Four items could not be adapted for performing from home (e.g., “Today, I picked up a meal for others at work.”). 4 The OCB-H measure presented acceptable evidence of reliability at all time points (α range = .73 to .95).

Work engagement was measured with the same scale as Study 1, the Utrecht Work Engagement Scale (UWES-9; Schaufeli et al., 2006 ), adapted to day-level measurement. As is common with the UWES, we scored this measure using a mean-score based on all 9 items. Items were measured on a 0–6 frequency scale (0 = never; 1 = almost never; 2 = rarely; 3 = sometimes; 4 = often; 5 = very often; 6 = always) and presented acceptable evidence of reliability at all time points (α range = .91 to .94).

Day-level WIF was measured using the same eight-item negative work-home interface (WHI) subscale of the SWING (Survey Work-Home Interaction NijmeGen; Geurts et al., 2005 ) as in Study 1, but adapted to day-level measurement ( Derks & Bakker, 2014 ). The items were measured on a 1–5 Likert scale (1 = strongly disagree, 5 = strongly agree). The WIF measure presented acceptable evidence of reliability at all time points (α range = .84 to .93).

Control variables.

Based on the nature of our outcome variable, we controlled for relevant demographic variables that may systematically impact our results: gender, age, living with a spouse/partner and living with children. Gender was coded as “0” for male and “1” for female and age was measured in years. Living with a spouse/partner (0 = not living with a spouse/partner, 1 = living with a spouse/partner) and living with children (0 = not living with children, 1 = living with children) were both measured dichotomously.

Preliminary analyses.

Before testing our hypotheses, we screened the data for outliers. We utilized the non-compliant responding techniques described by Christensen and colleagues (2003) for experience sampling data by screening for random responding by correlating two items that should be related if a person is responding honestly for each participant (e.g., two items from the same subscale of state work engagement should be highly correlated) (Christensen, Barrett, Bliss-Moreau, Lebo, & Kaschub). We then examined any responses suggesting potential inconsistency in depth. We checked for any set responses (e.g., selecting the same option for all items). If found, we then removed the set of responses prior to data analyses, in line with practices recommended by Christensen and colleagues (2003) . In total, only one participant was removed, resulting in a final sample size of 162 participants. After cleaning our dataset, we ran descriptive analyses. Table 4 displays descriptive statistics and correlations between all study variables. For each scale, we calculated the mean score of all items.

Correlations between study variables and variance composition of Study 2 variables

Note. N at level 1 = 534–664; N at level 2 = 148–162. Variables 1–4 are within-person variables; variables 5–15 are between-person variables. Correlations above the diagonal represent within-individual correlations. Correlations below the diagonal represent between-individual correlations. OCB-W = Organizational Citizenship Behaviors at Work; OCB-H = Organizational Citizenship Behaviors at Home; WIF = Work interfering with Family; Seg. Pref. = Segmentation Preferences. ICC = Intraclass Correlation. Values in bold indicate the value is statistically significant at p < .05.

As our study utilizes experience sampling methodology, we incorporated best practices for analyzing this type of data. Experience sampling methodology typically involves one of three approaches: interval-contingent, signal-contingent, and event-contingent ( Bolger, Davis, & Rafaeli, 2003 ). This study utilizes interval-contingent experience sampling methodology, as participants responded to daily surveys at prescribed times (once about an hour before they left work, and once at approximately 9:00 pm). First, we conducted a multilevel CFA using robust Huber-White standard errors and the Yuan-Bentler scaling correction to the test statistic using the lavaan ( Rosseel, 2012 ) in R. This technique was utilized to test the proposed two-factor structure, examine the variability and covariance of OCB-H and OCB-W, and to examine the reliability of the measure at the between- and within-person levels. Next, using Mplus 8 ( Muthén & Muthén, 1998–2017 ), we estimated a model with no predictors for each level 1 variable, which determines how much variance in each model can be attributed to within individuals or between individuals, and allows the calculation of the intraclass correlation coefficient (ICC) ( Fisher & To, 2012 ) (see Table 4 ). All predictors were entered at level 1, which includes work engagement, OCB-W, OCB-H, and WIF. Consistent with past experience sampling research, all variables were group-mean centered. All analyses utilized multilevel modeling, in that days were nested within individuals. Maximum likelihood estimation was used for all analyses.

Hypothesis testing.

First, we tested a subset of hypotheses from Study 1 with our second dataset by examining correlations. Regarding our hypotheses relating to Study 2, all hypotheses were tested with a single model using the MLMED macro ( Hayes & Rockwood, in press ). Initially, we included four demographic control variables in our model: gender, age, living with a spouse/partner and living with children. These demographic variables were chosen as controls as they may impact relationship between the work and family domain (e.g., having children living at home may result in less time available for performing OCB-H), and were included as Level 2 covariates. Ultimately, our final models did not include any controls, because the addition of each control variable suggested that our results would not change. As Research Question 1 involved examining between- and within-person differences of our hypotheses, we report the findings of each hypothesis at both levels.

A multilevel CFA hypothesizing two factors both between- and within-persons was estimated; two items from the OCB-H scale 5 were removed due to low loadings. After removal of these items, the model generally showed good fit as indicated by RMSEA of .041 (90% CI: .039; .043). The SRMSR indicated good fit for the Level 1 model at .071, but less satisfactory fit for the between-subjects portion of the model (.15). The CFI was .793 and the TLI was .784. At first glance, this would indicate poor fit, however, our null model suggests that the CFI and TLI are not informative. The RMSEA of the null model was .097. When the null model’s RMSEA is less than .158, the CFI, TLI, and other relative fit indices may not be very informative ( Kenny, Kaniskan, & McCoach, 2015 ). Interfactor correlations suggested the correlation between OCB-H and OCB-W was high at the between-persons level, φ Between = .78, z = 2.54, p = .011, but very low at the within-person level, φ Within = .11, z = 1.18, p = .238. Examination of the factor variances suggested 84.2% of the variance in OCB-W and 62.1% of the variance in OCB-H was between-subjects. The between-person correlation between OCB-W and OCB-H was .78, whereas their within-person correlation was .11. Thus, as expected, although persons who typically engage in OCB-W are highly likely to engage in OCB-H, a person who engages in OCB-W on a given day is not more or less likely to engage in OCB-H on the same day. The multilevel CFA-based composite reliability of this measure was good both at the within- (OCB-H: ω = .76; OCB-H: ω = .83) and between- (OCB-H: ω = .98; OCB-H: ω = .92) person levels.

Next, we examined the correlations hypothesized from Study 1 that were available in Study 2 (see Table 4 ). Consistent with Hypothesis 1, the findings of Study 1, and the multilevel CFA, OCB-H was significantly correlated with OCB-W at the between-person level ( r = .59, p < .001). However, the two constructs were uncorrelated at the within-person level ( r = −.01, p = 903). At the between-person level, OCB-H was unrelated to all five personality traits, providing support for our discriminant validity predictions (extraversion and openness) but contrary to the predictions of Hypothesis 2A-2C (conscientiousness, agreeableness, and neuroticism, respectively). OCB-H was significantly correlated with work engagement at the between-level ( r = .24, p < .01), but was unrelated at the within-person level ( r = −.03, p = .607), providing partial support for Hypothesis 3. Similarly, OCB-H was significantly correlated with WIF at the between-level ( r = .30, p < .001), but was unrelated at the within-person level ( r = .08, p = .080), providing partial support for Hypothesis 4. At the between-person level, OCB-H was not significantly related to segmentation preferences ( r = −.07, p = .402), thus Hypothesis 5A was not supported. OCB-H was significantly related to workaholism at the between-person level ( r = .18, p < .05), supporting Hypothesis 7. Notably, the correlations of variables measured at the daily level (work engagement, OCB-H, OCB-W, and WIF) were almost identical at both the between- and within-person level for all constructs except correlations involving OCB-H, suggesting substantial differences at the within- compared with the between-person level, which we discuss further in relation to Research Question 1.

Next, we examined the relationship between work engagement in the afternoon predicting WIF measured in the evening after controlling for OCB-W and OCB-H. The direct effect was not significant when controlling for OCB-H at the within-person level ( b = .02, p = .70, 95% CI = [−.08, .12], see Figure 2 ). The relationship was significant at the between-person level ( b = −.24, p <.01, 95% CI = −.39, −.09]), which is consistent with past research. Hypothesis 8 proposed that daily OCB-W (Hypothesis 8A) and daily OCB-H (Hypothesis 8B) would mediate the relationship between daily work engagement and daily WIF. Hypothesis 8A was fully supported, as OCB-W significantly mediated the relationship between work engagement and WIF at both the within-person level ( indirect effect = .06, 95% CI = [.03, .10] and between-person level ( indirect effect = .09, 95% CI = [.02, .17]). Hypothesis 8B was partially supported, as OCB-H did not significantly mediate the relationship between work engagement and WIF at the within-person level ( indirect effect = .00, 95% CI = [−.02, .02], but did significantly mediate the relationship at the between-person level ( indirect effect = .05, 95% CI = [.01, .11]) 6 .

The between- and within-person level effects for OCB-W and OCB-H mediating the work engagement-WIF relationship

* p < .05, ** p < .01, *** p < .001

Regarding our Research Question, it is clear from a comparison of our results across Study 1 and Study 2 that OCB-W exhibits similar effects at both the between- and within-person level, yet OCB-H has distinct differences. This was further confirmed with our hypothesized mediation (Hypothesis 8) through evidence of a significant contextual effect for OCB-H ( b = .05, 95% CI = [.01, .11]), whereas the contextual effect for OCB-W was not significant ( b = .02, 95% CI = [−.04, .11]). Contextual effects are a way to statistically test for differences regarding the within-group effect and between-group effect, thus a significant contextual effect means the relationship is significantly different at the between- compared with the within-person level (e.g., for OCB-H). Additionally, we examined indirect effect contrasts, which if significant, would suggest the indirect effect of our two mediators (OCB-W and OCB-H) are significantly different at the respective level. Results suggested that the within-indirect effect contrasts were significant (difference = −.06, 95% CI = [−.10, −.03]), whereas the between-indirect effect contrasts were not significantly different (difference = −.04, 95% CI = [−.14, .06]) 7 .

Study 2 Discussion

In Study 2, we sought to examine the work engagement-OCB-WIF relationship by disentangling the hypothesized relationships (1) by OCB-W compared with OCB-H, and (2) by comparing the relationships at the between- and within-person level. The goal of this study was to highlight potential differences between the aforementioned forms of OCB and uncover whether OCB-H exhibits the same degree of variability at both levels. Notably, OCB-H exhibited much greater variability at the between-person level, suggesting employees either generally perform these behaviors or generally refrain from these behaviors, whereas OCB-W exhibited significant variability at both levels. Additionally, OCB-H was a significant predictor of WIF, but appears to emerge as a direct effect at the within-person level, whereas it serves as an indirect effect of the work engagement-WIF relationship at the between-person level.

We confirmed past research on the work engagement-OCB-W-WIF relationship and extended these findings to confirm they exist both between individuals as well as within individuals. Finally, we highlighted that the relationship between work engagement and WIF differs at the between- and within-person level, such that the constructs appear to be unrelated at the daily level but are negatively related between-individuals. Furthermore, the nature of this relationship appears to be influenced by the degree to which OCBs are performed, as evidenced by the significant indirect effects.

General Discussion

The aim of the present research was to establish initial evidence of validity for the construct of OCB-H and begin to explore the degree of variability at the between-and within-person level of this construct. In Study 1, we presented evidence of construct validity, highlighting that OCB-H is similar to, yet distinct from, OCB-W, and thus exhibits a different nomological network, particularly in the context of constructs with overlap in the home domain. In Study 2, we extended our findings to examine the degree of fluctuation at the within- and between-person levels of OCB-H. Specifically, we focused on the nature of OCB-H and OCB-W as mediators of the work engagement-WIF relationship, given past evidence of this relationship ( Halbesleben et al., 2009 ), and that work engagement reflects the work domain whereas WIF captures the influence of work on the home domain. The overarching findings of Study 2 are that while OCB-W differs both within- and between- individuals, OCB-H displays much more between-person variability than within-person variability. In other words, employees either generally perform OCB-H to some degree or do not perform these behaviors from home at all. Furthermore, OCB-H does appear to predict WIF, however, it takes the shape of a direct effect at the within-person level, whereas it emerged as a mediator of the work engagement-WIF relationship at the between-person level.

The daily fluctuation of OCB-W also accounted for the positive relationship between work engagement and WIF, in that state work engagement during the day led to the performance of OCB-W, in turn resulting in greater levels of WIF in the evening. In other words, OCB-W helped to explain both between- and within-person variance in the work engagement-WIF relationship, whereas OCB-H only explained between-person variance. This suggests that both OCB-W and OCB-H offer unique explanatory power behind why work engagement is associated with greater WIF. Below, we discuss the theoretical and practical implications of this study, limitations, and directions for future research.

Theoretical Implications

The present research offers a number of theoretical implications. First, the findings of both studies suggest that OCB-W and OCB-H are distinct constructs, underscoring the importance of considering the context of work behaviors. Although OCBs by definition are discretionary, aspects of OCBs have been linked with performance evaluation decisions ( Whiting et al., 2008 ), and are often perceived by employees to be a part of their job description ( Turnipseed & Wilson, 2009 ). The present study extends the implications of OCBs into the field of occupational health psychology by expanding the OCB content domain, offering a caveat to this well-studied construct – where the behavior was performed – which has important implications for stress outcomes, such as conflict between work and nonwork. Furthermore, OCB-H and OCB-W appear to have distinct nomological networks. Additionally, these constructs are distinct in that we observed both between- and within-person fluctuation in OCB-W (i.e., individuals differ in their general performance of OCB-W, and individuals who perform OCB-W also exhibit daily fluctuation of these behaviors), whereas we only observed between-person fluctuation in OCB-H (i.e., individuals tend to either regularly perform OCB-H or regularly refrain from OCB-H). Organizations may not be aware that employees are performing OCBs not only during their paid work hours but also at home during non-work hours. Our differentiation of OCB-W and OCB-H serves as a novel contribution to the OCB literature in that to our knowledge, this is the first body of research to examine if there is a need to distinguish where OCBs are performed, which has previously been assumed to have been performed while physically at work. This differentiation is timely, as communication technology advances have afforded more opportunities for work behaviors outside of work, which has been previously linked with WIF ( Butts et al., 2015 ; Fenner & Renn, 2010 ). OCBs may be beneficial for organizations initially; the current study suggests that the performance of both OCB-W and OCB-H are associated with greater WIF and would likely result in the depletion of other resources. This is in line with past research suggesting that OCBs are associated with lower job satisfaction ( Munyon, Hochwarter, Perrewé, & Ferris, 2010 ) and burnout ( Vigoda-Gadot, 2007 ). Additionally, the performance of OCB is associated with citizenship fatigue, which consequently leads to fewer OCBs performed in the future ( Bolino, Hsiung, Harvey, & LePine, 2015 ).

Practical Implications

The current research also has several practical implications. First, the findings of both studies highlight the growing body of literature suggesting that employees are performing work-related behaviors even after work has ended, which past research has largely attributed to technological advances, such as e-mail and mobile devices ( Boswell & Olson-Buchanan, 2007 ; Dettmers et al., 2016 ). The findings of Study 1 highlight the influence of individual’s preferences for integration or segmentation on performing such behaviors, as well as the degree to which they are able to segment work and home depending on organizational expectations (i.e., segmentation supplies). Organizations should be aware of the effect of segmentation/integration congruence, such that the degree of congruence between segmentation preferences and supplies are associated with decreased WIF ( Chen, Powell, & Greenhaus, 2009 ). Thus, OCB-H may not be inherently associated with negative outcomes, so long as the individual performing these behaviors is doing so out of their own volition rather than organizational pressure.

Regarding the findings of Study 2, although work engagement can lead to increased WIF (depending on the behaviors engaged employees perform), organizations and society as a whole can help reduce the behaviors that may lead to increased WIF and other potential negative consequences that result from the high level of resources associated with work engagement. At a societal level, countries could employ formal laws limiting employers’ right to expect work after-hours. For example, France recently implemented a law banning work-related emails after 6:00 pm ( Morris, 2017 ). A policy such as this would reduce the likelihood of OCB-H, leading to lower levels of WIF, and potentially helping to retain the good parts of work engagement, while limiting its detriments. Finally, organizations may want to encourage supervisors to restrict their own OCB-H, in turn setting an example to employees that continuing to work “off the clock” is not necessary or expected, as social norms regarding technology use after working hours are associated with increased WIF ( Derks et al., 2015 ).

Finally, organizations should be cognizant that OCBs can be associated with higher levels of WIF, depending on the resulting behaviors performed and associated resources that may be depleted. A past meta-analysis found that WIF was related to negative outcomes for employees (e.g., increased psychological strain, higher levels of depression, stress, and anxiety), their families (e.g., higher family-related stress, lower family-related performance), and for organizations (e.g., higher rates of absenteeism, lower work-related performance) ( Amstad, Meier, Fasel, Elfering, & Semmer, 2011 ). Thus, although organizations often strive to encourage OCBs ( Skarlicki & Latham, 1997 ), these behaviors can have detrimental impacts on the employee, their family, and the organization.

Limitations and Future Directions

Despite the strengths of the current study, there are notable limitations. Study 1 was conducted using Prolific, an online panel system. However, we are optimistic our results would extend to conventional field samples, given recent findings that online panel data and conventional field samples typically converge ( Walter, Siebert, Goering, & O’Boyle, 2019 ). Furthermore, additional research is warranted regarding the constructs examined in Study 1 that were not the focus of Study 2 (e.g., personality, task performance, etc.). The main limitation of Study 2 is the homogeneity of the sample, in that the sample was almost entirely Caucasian (90%) and female (79%). This limits the generalizability of the current findings in that generalizations are mostly limited to Caucasian females. However, recent studies, and especially experience sampling studies, have had similar sampling problems (i.e., Clark, Robertson, & Carter, in press ; Koopman et al., 2016 ; Sianoja, Syrek, de Bloom, Korpela, & Kinnunen, in press ). Additionally, the homogeneity of the sample limited the ability to test for race and gender differences, which may show different causal mechanisms for the work engagement-WIF link. For instance, drawing on gender role theory, certain OCBs are more theoretically associated with the behaviors of women (e.g., altruism, courtesy), while other OCBs are more theoretically associated with the behaviors of men (e.g., sportsmanship, civic virtue) ( Kidder, 2002 ). Furthermore, work-related helping behaviors are often assumed to be less optional for women and more rewarded for men ( Heilman & Chen, 2005 ). Indeed, gender has exhibited both main effects and moderating effects on OCB ( Allen & Jang, 2018 ). In sum, the relation between gender and OCB is complex, and adding the additional layer of where these behaviors are physically formed via OCB-H introduces new dynamics which warrant future research.

Another area of research that may be fruitful relating to OCB-H and OCB-W is the motives behind these behaviors, given that they influence performance evaluations ( Whiting, et al., 2008 ). For instance, impression management and prosocial motives are associated with supervisor ratings of citizenship, meaning that some employees are “good actors” while others are “good soldiers” ( Grant & Mayer, 2009 ). Future research should examine the motives behind those who typically perform OCB-W compared with those who typically perform OCB-H, perhaps using latent class analysis. Furthermore, different motives may be at play for OCB-H, as feelings of job insecurity are associated with an increased willingness to allow work to spill over into nonwork time ( Boswell, Olson-Buchanan, & Harris, 2014 ), and work pressure appears to attenuate the relationship between work-nonwork integration preference and actual integration behavior ( Capitano & Greenhaus, 2018 ). However, questions remain regarding these past findings in terms of whether the performance of work behaviors at home are attributable to work obligations (e.g., being on-call) or extra-role citizenship behaviors such as OCB-H.

Finally, future research is needed to examine the construct clarity between OCB-H and behavior-based WIF. While OCB-H and WIF were significantly correlated in both Study 1 ( r = .24) and Study 2 (between-person r = .30; within-person r = .22), it is important to note that our measure of WIF did not include a behavior-based dimension. However, we anticipate a similar correlation between behavior-based WIF and OCB-H. Theoretically, behavior-based WIF conceptualizes conflict experienced when behaviors required in one role are incompatible with behaviors in another role (e.g., “the problem-solving behaviors I use in my job are not effective in resolving problems at home”) ( Carlson et al., 2000 ), whereas OCB-H reflects extra-role behaviors going above and beyond typical task performance via one’s own volition (e.g., I volunteered for extra work assignments”). Thus, we believe these two constructs are theoretically distinct, in that one may experience behavior-based WIF but refrain from engaging in OCB-H, or vice versa. Future research is needed to clarify the distinction between these two constructs.

The current study aimed to introduce a physical aspect to the content domain of OCBs – whether they were performed while physically at work or physical at home. In Study 1, we provided evidence of validity for a measure of OCB-H. Specifically, we provided initial evidence of construct validity, ultimately confirming that OCB-H is related yet distinct from OCB-W, and establishing initial evidence of the nomological network of OCB-H. In Study 2, we expanded the measurement of OCB-H to the day-level by examining the mediating influence of both OCB-W and OCB-H on the relationship between work engagement and WIF. Our findings suggest that while OCB-W exemplifies significant between- and within-person variation and significantly mediates the work engagement-WIF relationship at both levels, the vast majority of OCB-H variability is at the between-person level, and the mediating effect of OCB-H was only observed at the between-person level. Overall, our research suggests that OCB-W and OCB-H are distinct constructs regarding both their construct space and degree of variability. Ultimately, the present research suggests organizations should be aware that many employees may continue to perform work-related behaviors in the nonwork domain, and clarify expectations relating to availability after scheduled work hours.

Supplementary Material

Supplemental material, acknowledgments.

This research is based on the first author’s doctoral dissertation conducted at the University of Georgia. We thank Malissa Clark and Kristen Shockley for their valuable suggestions as members of the first author’s dissertation committee. An earlier version of this work was presented at the 2019 Society for Industrial and Organizational Psychology Conference in Chicago, IL. This research was supported in part by a grant from the Sunshine Education and Research Center at the University of South Florida, which is supported by Grant No. T42-OH008438 from the Centers for Disease Control and Prevention/National Institute for Occupational Safety and Health (NIOSH).

1 Sum is larger than 100% as participants were instructed to select all that apply

2 In hindsight, this item may have been adapted to OCB-H, for instance, framing the item as buying or preparing food for work colleagues during off-work hours. We thank a reviewer for highlighting this and encourage future research to further develop and refine OCB-H measures.

3 We further examined this hypothesis at the dimension level of WIF. OCB-H had the same strength of relationship with both WIF-Time ( r = .23, p < .001) and WIF-Strain ( r = .23, p < .001).

4 In hindsight, this item may have been adapted to OCB-H, for instance, framing the item as buying or preparing food for work colleagues during off-work hours. We thank a reviewer for highlighting this and encourage future research to further develop and refine OCB-H measures.

5 The two items were: “While I was at home, I helped a co-worker learn new skills or shared job knowledge” and “While I was at home, I finished something for a co-worker who had to leave early.”

6 We also tested our multiple mediator model predicting both WIF-Time and WIF-Strain (see Figures 1 and 2 in the Supplemental Materials , respectively). There were notable differences: OCB-H at the between-person level was more strongly related to WIF-Strain ( b = .70, p < .001) than WIF-Time ( b = .53, p < .01). Additionally, at the within-person level, OCB-H significantly predicted WIF-Strain ( b = .33, p < .05) but not WIF-Time ( b = .22, p = .15). The indirect effect of OCB-H at the between person level was significant for WIF-Strain but not WIF-Time. Finally, the indirect contextual effect of OCB-H was significant for WIF-Strain but not WIF-Time. Taken together, while Study 1 suggests OCB-H is similarly related to both WIF-Strain and WIF-Time, these supplemental analyses in Study 2 suggests OCB-H may be much more strongly related to WIF-Strain than WIF-Time.

7 In the spirit of transparency, our original manuscript included workaholism as a first stage moderator of the work engagement-OCB-H relationship and work engagement-OCB-W relationship. Through the revision process we ultimately moved this to supplemental material , as the moderation was not significant. Please see the supplemental material ( Figures 3 and 4 ) for the complete results.

Contributor Information

Rachel Williamson Smith, Louisiana State University.

Young-Jae Kim, University of Georgia.

Nathan T. Carter, University of Georgia.

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• Research Article
• Published: 20 August 2011

Research on the organizational citizenship behavior continuum and its consequences

• Yongjun Zhang 1 ,
• Jianqiao Liao 1 &
• Jun Zhao 1  

Frontiers of Business Research in China volume  5 ,  pages 364–379 ( 2011 ) Cite this article

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Through literature review and induction from management practices, this paper firstly identifies four subtypes of organizational citizenship behavior (OCB), namely altruistic OCB based on personality, responsible OCB based on reciprocity, instrumental OCB based on self-interest, and compulsory OCB based on stress. The four OCB subtypes constitute an OCB continuum in the order of an individual’s degree of voluntariness. Both the positive and negative impacts of the four OCB subtypes on organizations and individuals are analyzed. Conclusions, limitations and future research directions are presented.

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Zhang, Y., Liao, J. & Zhao, J. Research on the organizational citizenship behavior continuum and its consequences. Front. Bus. Res. China 5 , 364–379 (2011). https://doi.org/10.1007/s11782-011-0135-2

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Organizational Citizenship Behavior: Benefits and 3 Best Practices

What is organizational citizenship behavior?

Types of organizational citizenship behavior

• Altruism – Altruism in the workplace occurs when an employee helps or assists another employee without expecting anything in return. A simple example of altruistic behavior at work is when someone offers their assistance to a co-worker who is swamped by taking over (part of) their tasks or volunteering to help clean up the canteen after an internal company event. Altruism in the workplace can boost employee morale, productivity, and effectiveness.
• Courtesy – Courtesy is polite and considerate behavior towards other people, in this case, other employees. Examples of courtesy at work include saying good morning (!), asking a co-worker how their holiday was, how their kids are doing, how a project they’re currently working on is going; basically any question related to a (personal) subject someone has previously spoken about that shows people you’ve listened to what they were saying.
• Sportsmanship – Put simply, sportsmanship is about an employee’s ability to be a good loser. It’s about being able to deal with situations that don’t go as planned – or negative surprises – and to not demonstrate negative behavior when that happens. An example of good sportsmanship in the workplace is an employee who is temporarily taking over the tasks of a team member who broke his leg and will be on sick leave for a few weeks. While this considerably increases this employee’s workload, she isn’t complaining about it to her colleagues because she knows it’s a temporary situation and that she’s taking one for the team (to stick with the sports jargon).
• Conscientiousness – Conscientiousness is defined as behavior that involves a certain level of self-control and discipline and that goes beyond the minimum requirements. In a work setting, this means that employees don’t just show up on time and stick to deadlines, but that they, for instance, also plan ahead before they go on holiday so that their colleagues won’t be drowning in a big workload. An example that’s related to a remote work set-up is having enough self-discipline to get up in the morning and get the work done, even when there is no manager around to give you a nudge. Conscientiousness also means knowing that sometimes the job simply needs to get done, despite the fact that it’s after hours.
• Civic virtue – Civic virtue is about how well someone represents the organization they work for. It’s about how an employee supports their company when they’re not in an official capacity. How do they talk about the organization to their friends and family for instance? Civic virtue can also be demonstrated by employees signing up for business events such as fundraisers, or running a (semi) marathon for a charity with a team of co-workers. Civic virtue is a type of organizational citizenship behavior that creates a sense of community and camaraderie within the organization. This, in turn, leads to higher job satisfaction and better job performance.

Benefits of OCB

• OCB can boost employee morale
• It increases people’s levels of work meaningfulness
• It is good for employee performance and productivity; in fact, research shows that OCB positively predicts performance
• It creates better social interactions between employees
• It reduces stress
• It creates a sense of community among employees
• It is good for your Employer Brand

Organizational citizenship behavior – 3 Best Practices

1. hire right.

• Job description – Your job description can (should) reflect company values so candidates can decide whether or not those values are in line with their own. If your values resonate with them, they’ll be more likely to show, for instance, acts of civic virtue than when they don’t.
• Realistic job preview – Using a realistic job preview enables you to show candidates an actual ‘day in the life of’. This means you can show applicants how people treat each other in the company (courtesy), how people work (conscientiousness), and collaborate (altruism), etc. In other words, a realistic job preview is a great opportunity to demonstrate candidates the kind of organizational citizenship behavior you would like to see in your organization. Here too, they can then decide for themselves if working for your company suits them or not.
• Pre-selection – Organizations that recruit high volumes of people often use a pre-employment assessment tool . These tools can include a wide range of different assessments like cognitive testing, job sample tests, a personality test – to measure people’s conscientiousness for instance! – but also questions that determine whether or not there is a culture fit between the candidate and the company culture.
• Interview – During the interview phase, the hiring manager or anyone else who interviews the candidates can highlight some examples of organizational citizenship behavior when they talk about the company or the team. When they ask candidates questions, for instance using the STAR method (STAR stands for Situation, Task, Action, Result), they’ll be able to gauge whether or not someone is likely to engage in OCB.

2. Involve management

3. rethink performance management.

• Goals and objectives – as well as evaluation and rewards – are set in a way that encourages workers to look out for the team
• Someone’s altruism or other types of organizational citizenship behavior can result in a performance rating of more than 100%
• Criteria like ‘how people collaborate with other teams in the organization’ are part of the evaluation

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ORIGINAL RESEARCH article

Organizational citizenship behavior predicts quality, creativity, and efficiency performance: the roles of occupational and collective efficacies.

• 1 Business Administration, Ono Academic College, Kiryat Ono, Israel
• 2 Business Administration, Bar-Ilan University, Ramat Gan, Israel

Although numerous studies have shown that prosocial behavior impacts performance within organizations, the mechanisms that encourage or discourage these effects have rarely been explored. Two studies were conducted to shed light on the role of psychological beliefs on prosocial dynamics in predicting organizational performance. In Study 1, employees’ beliefs in their inner job-related resources (Occupational Efficacy – OE) were examined as a predictor of OCB. It was posited that OE, which is an inner resource, should positively predict OCB. Study 2 examined whether Collective Efficacy (CE), which is an external resource over which employees have less control, would moderate the OCB-performance prediction. Overall, performance and three core dimensions of performance (quality, creativity and efficiency) were assessed to better capture the specific influence of OCB effects on performance. In Study 1, employees completed inventories measuring their OE, OCB and performance. In Study 2, employees completed inventories measuring their CE and OCB. In addition, their managers completed inventories measuring the CE of their employees’ teams and their employees’ performance. The results of Study 1 revealed that OE emerged as an antecedent of OCB in predicting performance. In Study 2, OCB positively predicted employee performance above and beyond and the effects of their managers’ tenure in position, and CEs. In addition, both employees’ and managers’ CEs moderated the effects of OCB on performance: the performance effects of OCB increased as employees’ and managers’ CE increased, and specifically performance efficiency and performance creativity. These findings contribute to a better theoretical and practical understanding of the core factors that affect the organizational dynamics of prosocial behaviors that can lead to higher performance, and the ways in which OCB positively predicts performance in organizational settings.

Introduction

Giving and receiving help constitute an integral part of organizational life ( Lee et al., 2019 ). Research on the implications of prosocial behavior in organizations dates back to the 1980s, and has identified three main facets of prosocial behavior: prosocial motives (the willingness to benefit or make an effort for others), prosocial behaviors (gestures that contribute to the welfare of individuals, groups, or organizations), and prosocial impact (attempts to positively influence the lives of others as a result of one’s work).

Although prosocial motives have been discussed in the literature ( Bolino and Grant, 2016 ), few if any empirical studies have explored the role of employees’ beliefs in their inner job-related resources as an antecedent of prosocial behavior. In addition, to the best of our knowledge, no study has examined the moderating effects of employees’ and managers’ beliefs in their work teams on OCB effects on performance.

Motowidlo et al. (1997) argued that knowledge and contextual skills are predictors of OCB. Individuals with high self-efficacy make greater use of adaptive behavioral strategies ( Maddux and Lewis, 1995 ; Raghuram et al., 2003 ). They are likely to know which citizenship behaviors are appropriate in a workplace situation and how to plan for and deploy these behaviors effectively ( Beauregard, 2012 ). Thus, employees who have high beliefs in their inner resources (i.e., high occupational efficacy-OE) should be more likely to attend voluntary meetings or volunteer to help co-workers with work-related problems because they are better able to proactively plan for these activities and organize their workday to accommodate them. Beauregard (2012) showed that general self-efficacy predicted greater participation in citizenship behaviors in men. Speier and Frese (1997) . Morrison and Phelps (1999) found that generalized self-efficacy predicted personal initiative and “taking charge” behavior.

The two studies presented here were designed to explore the role of psychological beliefs on OCBs in predicting organizational performance. Specifically we examined whether OE, which is related to a person’s occupation, would predict employee OCBs better than the general self-efficacy because it is more closely related to the working context and is likely to better capture the psychological beliefs linked to the organizational setting. Study 1 was thus designed to test the hypothesis that OE would predict OCBs. Since the work team acts as one of the main, and frequently the sole, sources of support and assistance to employees in organizations, we posited that the positive effects of prosocial behaviors on performance would be moderated by employees’ and managers’ collective efficacy (CE), a recent extension of Bandura (1997) well-established Efficacy Theory. CE is defined as an “individual’s belief in the capacity of her or his team, department, division, or other relevant organizational unit to execute the courses of action required for performing its mission effectively” ( Eden, 2001 , p. 79–80). Here we posited that low CE would undermine the performance effects of prosocial behavior, in that work teams whose team members and superiors have low beliefs in their efficacy may become frustrated and thus benefit less from prosocial resources. Study 2 examined how employees’ and managers’ beliefs in their external human resources (CE) moderate the OCB prediction of performance. We conjectured that the influence of OCB on performance would be more closely related to external resources because performance (at least in organizational settings) is becoming increasingly more dependent on group work, synergy and collaboration. Specifically, we hypothesized that higher employee and manager CE would lead to the greater impact of OCB on performance and vice-versa.

Theoretical Background and Hypothesis Development

Performance.

Companies are cognizant of the financial benefits and competitive edge associated with enhanced employee performance. This involves the ongoing development of high quality innovative goods and services that are delivered on schedule and undercut the competition in terms of price ( Miron et al., 2004 ). When employees’ abilities are aligned with the resources they need to fulfill their goals, performance is enhanced and contributes to firm performance, as do training and motivational perks. Quality, innovation, and efficiency are considered to be the main components of performance in organizations ( Miron et al., 2004 ). Employees are asked to be innovative, while guaranteeing quality output by adhering to company regulations, and working efficiently to meet the constraints imposed by brief delays and tight budgets.

Work also comprises a significant interpersonal component ( Blustein, 2004 ). One of the factors that should lead to better performance within organizations is related to employees’ ability to interact constructively with others, and specifically, their ability to extend and accept assistance in problem solving. An important subset of interactions among employees that can be expected to be related to employee performance is prosocial behavior.

Prosocial Behavior (OCB)

Resource control theory states that pro-sociality as well as anti-sociality are basic patterns of resource control in human psychological and social functioning ( Hawley, 1999 ). For example, employees need various types of resources (e.g., informational, material, and social) to carry out their tasks in an organization. Interpersonal relations are a source of access to important resources including goal support, know-how and know-who ( Ciarrochi et al., 2019 ). In this sense, friendships on the job should be seen as a resource that individuals strive to develop and maintain ( Ciarrochi et al., 2019 ). It has been argued that good cooperators work better and last longer on the job than poor cooperators ( Wilson et al., 2014 ). Recently, Ciarrochi et al. (2019) suggested that being prosocial is perhaps the best path to success.

One of the core behaviors associated with prosocial behaviors within organizations is Organizational Citizenship Behavior (OCB). OCB is defined as actions that support the social and psychological environment where task performance unfolds ( Bolino and Grant, 2016 ). Lee and Allen (2002) noted that these behaviors represent employees’ voluntary actions such as helping coworkers and attending non-obligatory events which facilitate organizational flow although they are not essential components of the task at hand. OCB across individuals leads to better organizational performance ( Choi, 2009 ). OCB constitutes actions that are taken with no expectation for recognition or compensation ( Koslowsky and Pindek, 2011 ). OCB has been conceptualized as a two-dimensional construct ( Williams and Anderson, 1991 ) made up of OCBO, which comprises behaviors targeting the organization as a whole, and OCBI, which defines behaviors directed toward coworkers.

A significant part of the variance in production and performance quality, quality, efficiency and effectiveness can be explained by interpersonal helping, and specifically OCB (e.g., Organ, 1988 ; Organ et al., 2006 ; Podsakoff et al., 2009 ). OCBs provide social facilitation and reduce social friction by enabling group members to focus on their task more than on interpersonal relationships ( Organ, 1988 ) or conflicts. OCBs potentially increase individual performance efficiencies (e.g., Smith et al., 1983 ; Borman and Motowidlo, 1997 ). OCBs can also enhance individuals’ performance by building coordination skills (e.g., Smith et al., 1983 ). Podsakoff et al. (2000) suggested that OCB can contribute to organizational performance by enhancing coworkers’ and managers’ productivity by facilitating collaboration between work groups and enabling the organization to adapt to environmental changes. Lam et al. (2016) found that engaging in OCB behaviors enhances employees’ vitality, which contributes to the enhancement of employees’ resources leading to better well-being. Based on the above we hypothesized the following:

H1: Employees’ Organizational Citizenship Behavior will positively predict their performance, when measured as: (a) overall performance, (b) performance quality, (c) performance creativity and (d) performance efficiency.

Employees’ beliefs as to the extent of their control over their work setting can mitigate the negative impact of work demands and have a positive impact on engagement and job performance ( Bakker and Demeoruti, 2017 ; Molero et al., 2018 ). Employees’ beliefs may also be a useful factor for understanding people’s ability to accept help from others. Self-efficacy, or one’s belief in one’s capacity to execute behaviors required for specific performance using one’s inner resources and the resources in the environment, has been widely studied in Organizational Psychology ( Ventura et al., 2015 ; Barbaranelli et al., 2018 ). Self-efficacy influences how people behave and how one thinks and feels about the future ( Bandura, 1977 , 1997 ). Hence, employees’ self-efficacy beliefs are key to the ways in which they perceive their work context, especially when they face demanding and potentially stressful job demands ( Ventura et al., 2015 ; Molero et al., 2018 ). Jaeckel et al. (2012) distinguished between two forms of self-efficacy. Generalized self-efficacy is defined as the individual’s belief that s/he can deal effectively with a wide spectrum of everyday problems, a measurable trait that can predict behavior across domains ( Chen et al., 2001 ; Scholz et al., 2002 ). Task-specific self-efficacy only applies to specific tasks or situations. OE (occupational efficacy) is a specific type of task self-efficacy that characterizes individuals’ confidence in their ability to carry out their duties with success (e.g., Rigotti et al., 2008 ). OE thus intersects with features of job satisfaction and affective commitment ( Schyns and von Collani, 2002 ). OE is a robust predictor of job performance ( Stajkovic and Luthans, 1998 ; Rigotti et al., 2008 ).

Employees’ generalized self-efficacy was reported to exhibit a positive association with OCB ( Jawahar et al., 2008 ). OE is likely to be associated with OCB since it is part of the self-regulation designed to control one’s own behavior and expend more effort ( Bandura, 1977 ). OCBs are strengthened by impression management, where people try to present a good image of themselves to others, and prosocial motives ( Grant and Mayer, 2009 ) that require self-regulatory efforts ( Vohs et al., 2005 ). OE also enhances personal initiative, an important facet of OCB ( Speier and Frese, 1997 ), such that workers with high initiative contribute to their organization’s aims and long-term goals by engaging in more proactive actions ( Frese et al., 1997 ). Hence, we expected that OE, a type of self-efficacy belief that is strongly related to the work context, would be a core antecedent and predictor of OCBs. This hypothesis was tested in Study 1.

H2: Employees’ Occupational Efficacy will positively predict their Organizational Citizenship Behaviors.

In today’s highly interdependent work arena, employees’ behaviors are affected by other team members. We thus hypothesized that OCB effects on employees’ performance would be moderated by employees’ and their managers’ beliefs regarding the work team to which the employees belong; namely, their collective efficacy.

Forms of Collective Efficacy

Eden argued that “self-efficacy is only half of the efficacy story” ( Eden et al., 2010 , p. 688). Self-efficacy beliefs are complemented by external efficacy, which is a person’s beliefs about available human or inanimate resources that help or undermine performance ( Stirin et al., 2012 ). These range from equipment, tools, effective guidance and support to good working conditions, a superior starting point, and other facilitators ( Eden, 2001 ). External efficacy covers the capacities of one’s group, the availability of means, and the circumstances at hand. The belief that external sources will provide assistance that results in better performance depends to a large extent on one’s belief in the abilities of others from whom such assistance and support are received. Because OCB is a social phenomenon, collective efficacy should moderate OCB effects on performance.

CE is a specific type of external efficacy and was first defined as “the shared perception of a group of its efficacy to perform a behavior and to organize and execute the actions required to reach certain levels of achievement” ( Bandura, 1997 , p. 447; Martínez et al., 2011 ). Eden (2001) defined CE as an “individual’s belief in the capacity of her or his team, department, division, or other relevant organizational unit to execute the courses of action required for performing its mission effectively.” A meta-analysis reported a strong positive association between CE and group performance ( Stajkovic et al., 2009 ). Team efficacy mediated the association between the ability-enhancing practices of one’s team and team creativity ( Ma et al., 2017 ).

CE is considered a key predictor of performance in a variety of collective settings, including work teams ( Salanova et al., 2014 ). CE significantly predicted less error variance in nursing tasks ( Lee and Ko, 2010 ). Studies have also shown that CE is positively associated with self-reported innovations ( Salanova et al., 2012 ) as well as people’s actual innovativeness ( Choi and Chang, 2009 ) and decision-making quality ( Lam and Schaubroeck, 2011 ).

The antecedents of CE may be a function of enactive mastery, where confidence accumulates gradually as teams get feedback on their specific job performance, as well as through vicarious experience and verbal persuasion ( Gist and Mitchell, 1992 ; Tasa et al., 2007 ). Gist and Mitchell (1992) suggested that there is a recursive relationship between past performance and CE since positive feedback on challenging tasks can result in stronger efficacy beliefs, which then can promote greater success. Tasa et al. (2007) reasoned that CE develops in part via exchanges of information and observed behaviors within a team, and that CE is affected by the total amount of teamwork behaviors in a team. Other findings suggest that a team manager may also affect CE beliefs. Goncalo et al. (2010) showed that when there is high group confidence in the initial phase of a group experience, there is less likelihood of process conflict, which nevertheless can be advantageous in the first phases of a project. The group manager becomes a key resource for feedback and evaluations of the group which impacts their CE as well. Recently, Pak and Kim (2018) emphasized the importance of team managers’ role in facilitating performance. They further pointed to the team manager as a primary interpretive filter who enables team members to identify differences in high performance work system intensity, which in turn affects team performance. Therefore, we suggest the following hypotheses:

H3: Employees’ CE will positively predict their (a) overall performance, (b) performance quality, (c) performance creativity, and (d) performance efficiency.

H4: Managers’ CE will positively predict employees’ (a) overall performance, (b) performance quality, (c) performance creativity, and (d) performance efficiency.

Scholars have provided some possible reasons for the positive associations between employee OCBs and performance evaluations. Studies have shown that employees’ OCBs are interpreted by managers as behavioral manifestations of loyalty and/or loyalty commitment ( Allen and Rush, 1998 ), although managers may tend to simply like these individuals more ( Lefkowitz, 2000 ). Employees who exhibit OCBs may receive higher evaluations by managers as a form of reciprocity ( Podsakoff et al., 1993 ). It has also been argued that OCBs are positively related to other individuals such as through reward allocations and to the unit-level such as the quality and quantity of product outcomes and profitability, and can explain a significant fraction of the variance in job performance ratings compared to employees’ task performance ratings ( Podsakoff et al., 2009 ). Therefore, we suggest the following hypotheses:

H5: Employees’ Organizational Citizenship Behavior will only positively predict their overall performance, performance quality, performance creativity, and performance efficiency when they have high collective efficacy but not when they have low collective efficacy.

H6: Employees’ Organizational Citizenship Behavior will only positively predict their overall performance, performance quality, performance creativity, and performance efficiency when their manager’s collective efficacy is high but not when their manager’s collective efficacy is low.

H7: Employees’ Organizational Citizenship Behavior will predict performance more strongly when both employees’ and managers’ collective efficacy beliefs are high than when employees’ collective efficacy beliefs are high and managers’ collective efficacy beliefs are low or vice versa. Employees’ Organizational Citizenship Behavior will not predict performance when both managers’ and employees’ CE are low.

The Current Studies

Study 1 examined whether employees’ OCB would predict overall performance, performance quality, performance creativity, and performance efficiency. In this study, we also examined the antecedents of OCB in terms of OE. We focused on intra-individual processes by hypothesizing that OE, which relates to an internal quality, would best predict OCBs. Figure 1 presents the research model for Study 1.

Figure 1. Mediation effect of OCB on the association between occupational efficacy and performance (Study 1).

Study 2 consisted of an empirical examination of the factors that strengthen or inhibit the effects of OCB on the four performance measures above. Specifically, we examined whether employees’ and managers’ CE would moderate the OCB effects on the four performance measures. In addition, to control for common method bias, in Study 2 we collected data from employees and their managers, where managers evaluated their employees’ performance. We hypothesized that OCB, which is a social phenomenon, would predict performance moderated by more social external processes, and specifically the CE of employees and managers. Dyads of managers-employees were also considered in conceptualizing how CE impacts performance. Figure 2 presents the research model for Study 2.

Figure 2. Moderating effect of employees’ and managers’ collective efficacy on the association between employees’ OCB and facets of performance (Study 2).

All participants were salaried employees who volunteered to take part in this study. All worked full time and were enrolled in a weekend M.B.A. program at one of two leading academic institutions in Israel.

Study 1 examined stage one of the model. In this study we examined whether OCB would predict all three dimensions of employee performance (quality, creativity, efficiency) above and beyond demographic effects, and explored one of the core antecedents of prosocial behaviors in predicting performance. Specifically, we examined whether OE serves as an antecedent to prosocial behavior (OCB) using a mediation model of OCB on OE effects on performance. These were hypothesized since previous findings have revealed that OCB positively predicts performance (e.g., Lam et al., 2016 ; Park, 2018 ; Germeys et al., 2019 ). Moreover, job self-efficacy was found to serve as a core antecedent of OCB in customer service employees ( Reizer and Hetsroni, 2015 ). Here we combined these two findings and examined both concurrently and in terms of the three core performance facets rather than only one general measure.

Sampling and Subjects

One hundred twenty two employees agreed to participate. All worked full time. Of the employees, 44% were men, with ages ranging from 22 to 62 (mean age = 37.59). Experience in their profession ranged from 1 to 26 years (mean = 6.19), tenure in their position ranged from 1 to 38 years (mean = 11.3) and tenure in their current organization ranged from 1 to 47 years (mean = 12.89). Most of the participants worked in high-tech industries as engineers. All participants signed an informed consent form before filling in the questionnaires and were instructed that they could withdraw at any time without penalty. No one did so.

Most of the employees were tenured, had enough experience in the labor market, and represented a diverse range of professions. All participants completed questionnaires during class at a major Israeli academic institution in 2018–2019 for a response rate of 100%.

Materials and Procedure

Performance was assessed on the well-established Miron et al. (2004) Inventory, which comprises 14 items tapping employee quality, creativity and efficiency on a 7-point Likert-type scale ranging from 1 ( strongly disagree ) to 7 ( strongly agree ). The questionnaire consists of three subscales assessing quality [e.g., Thorough in work, Adheres to rules, Does not cut corners (α = 0.83)], creativity [e.g., Finds unusual solutions, Implements new ideas (α = 0.89)] and efficiency [e.g., Attends to matters of efficiency and saving, Keeps to planned schedule (α = 0.82)]. The measure of performance was found to be valid ( Miron et al., 2004 ; Yaakobi and Weisberg, 2018 ).

Organizational citizenship behavior

OCB was defined here in terms of the target or beneficiary of citizenship behavior. The Smith et al. (1983) altruism and compliance subscales have been used elsewhere to assess OCBI and OCBO (I = directed toward other individuals in the workplace; O = directed toward the organization; Farh et al. (1990) , and Williams and Anderson (1991) also differentiated between OCBI and OCBO. Since we focused on individual CE beliefs, we only administered the OCBI measure. Eight items reflecting OCBI were used (see Appendix ). Employees indicated how frequently they engaged in these behaviors on a 7-point scale ranging from 1 ( never ) to 7 ( always ). Confirmatory factor analysis clearly showed that the OCBI-factor model was a one-factor model, which thus lends weight to a single OCBI measure (α = 0.83).

Occupational efficacy

The OE questionnaire ( Horovitz, 2012 ) was used to measure employees’ OE (job-specific efficacy at the individual level). Employees evaluated their efficacy at work. Participants ranked OE on a 5-point Likert-type scale that ranged from 1 ( strongly disagree ) to 5 ( strongly agree ). Sample items were “I can persuade any employer to hire me”; “I can learn new demands at work quickly” (α = 0.76).

Control variable

Employees with longer job tenure have more work experience and may perform better. The same logic may apply to tenure in the organization and tenure in the profession. In addition, employees’ gender and age were examined in the analyses to capture the main demographic variables. The study was approved by the institutional review board.

A correlational analysis revealed that employees’ organizational citizenship behaviors were positively associated with their performance (see Table 1 ).

Table 1. Means, standard deviations, and inter-correlations between variables (Study 1).

When examining the three performance dimensions, the correlational analyses revealed that OCB was positively associated with both performance creativity and efficiency but not with performance quality. Regarding demographics, only tenure in the organization and gender were positively correlated to performance, but only to specific dimensions ( Table 1 ).

A regression analysis was performed to better capture the predictive power of OCB on performance dimensions above and beyond employees’ demographic effects. In the first step of the regression analysis, employees’ tenure in their organization, tenure in their profession, and gender were entered simultaneously into the equation. The decision to enter these demographics was based on the results of the correlational analyses. Kidder (2002) also found that women engage in more OCBI than men.

In step two, employees’ OCB was entered into the equation (see Table 2 ).

Table 2. Hierarchical regression analysis predicting performance by OCB (Study 1).

As can be seen in Table 2 , none of the demographic variables were associated with employees’ overall performance. However, OCB was strongly associated with employees’ overall performance, above and beyond demographic effects, thus supporting H1. With respect to the three dimensions of performance, OCB positively predicted performance creativity and performance efficiency above and beyond demographic effects, but in line with the results of the correlational analysis, OCB did not predict performance quality.

To examine whether OE was a prerequisite for OCB concurrently with the prediction of OCB on performance we used the PROCESS macro ( Hayes, 2013 ) to calculate two sets of regressions 1 . The first set tested for an association between occupational efficacy and OCB. The second set examined the relationship of OCB and performance. To test the significance of the indirect effects of OE on performance via OCB, the bootstrapping approach was used. The 95% CI for the indirect effects was calculated on 5,000 resamples ( Hayes, 2013 ). We conducted 4 sets of analyses, one for the overall performance measures, and three for the three performance dimensions (quality, creativity and efficiency).

Table 3 presents the results. With respect to the overall performance measure, OE was positively associated with OCB, as indicated by the significant unstandardized regression coefficient. Supporting our hypotheses, there was a positive association between OCB and performance, when controlling for the OE effects. OE had an indirect effect on performance. The two-tailed significance test (assuming a normal distribution) indicated that there was an indirect effect of OE on performance. The bootstrapped 95% CI around the indirect effect did not include zero.

Table 3. Regression result for simple mediation (Study 1).

With respect to the performance quality measure, OE was positively associated with OCB, as indicated by the significant unstandardized regression coefficient. However, in contrast to our hypothesis on performance quality, no significant positive association was found between OCB and performance when controlling for the OE effects. The indirect effect of OE on performance failed to reach significance. The two-tailed significance test (assuming a normal distribution) indicated that there was no indirect effect of OE on performance. The bootstrapped 95% CI around the indirect effect included zero.

With respect to the performance creativity measure, OE was positively associated with OCB, as indicated by the significant unstandardized regression coefficient. Consistent with our hypothesis, there was a positive association between OCB and performance when controlling for the OE effects. OE had an indirect effect on performance. The two-tailed significance test (assuming a normal distribution) indicated that the indirect effect was significant. The bootstrapped 95% CI around the indirect effect did not include zero.

With respect to the performance efficiency measure, OE was positively associated with OCB, as shown by the significant unstandardized regression coefficient. In support of our hypothesis, there was a positive association between OCB and performance when controlling for OE effects. OE had an indirect effect on performance. The two-tailed significance test (assuming a normal distribution) indicated that the indirect effect was significant. Bootstrap results showed that the bootstrapped 95% CI around the indirect effect did not include zero.

Study 1 suggested that OCB predicted the general performance measure and specifically creativity and efficiency performances above and beyond demographic effects but not the quality performance measure. This findings leads to a more accurate and in-depth understanding of the specific effects of OCB on specific performance facets than has been reported in the literature for general performance ( Choi, 2009 ; Lam et al., 2016 ; Park, 2018 ; Germeys et al., 2019 ). In addition, OE appeared to be a core antecedent of prosocial behaviors in predicting performance for the general performance measure and specifically creativity and efficiency performance, but not the quality performance measure. The findings that OE serves as a core antecedent of OCB is consistent with previous findings on job self-efficacy and OCB in customer service employees ( Reizer and Hetsroni, 2015 ).

Study 2 was conducted to examine the next step in the model and specifically, the moderating roles of CE as assessed separately for managers and employees in OCB effects on performance. Our main hypothesis was that the OCB prediction on the three performance facets would be stronger when employees’ and managers’ score high on CE. These hypotheses were based on previous findings that pointed to the important role of beliefs in team efficacy (CE) on performance ( Myers et al., 2004 ; Salanova et al., 2014 ) coupled with the finding that team managers play a prime role in facilitating performance ( Pak and Kim, 2018 ). Moreover, to control for possible common method bias, in Study 2 employees’ performance was evaluated by their managers.

Participants

Ninety managers and their employees (a total of 180 participants) agreed to participate. All worked full time. Of the managers, 62% percent were men, with ages ranging from 23 to 72 (mean age = 37.62), their tenure in their profession ranged from 0.5 to 30 years (mean = 5.27), their tenure in their position ranged from 0.5 to 25 years (mean = 2.09), and their tenure in the current organization ranged from 0.5 to 22 years (mean = 4.21).

Fifty-two percent of the employees were men, with ages ranging from 19 to 57 (mean = 36.69), their tenure in their profession ranged from 0.5 to 20 years (mean = 4.42), their tenure in their position ranged from 0.5 to 15 years (mean = 2.29), and their tenure in the current organization ranged from 0.5 to 18 years (mean = 2.85). Thus, most of the managers and employees were tenured and had sufficient experience in the labor market. They represented a variety of professions, and most were working in high-tech industries as engineers. All participants completed the surveys in class at a major Israeli academic institution in 2018–2019 (100% response rate).

To avoid possible self-report-biases, the managers were asked to evaluate their employees’ performance on the same well-established measure developed by Miron et al. (2004) used in Study 1. The reliability of the performance measures assessed by managers was α = 0.89 for overall performance, α = 0.84 for performance quality, α = 0.93 for performance creativity, and α = 0.82 for performance efficiency.

Study 2 used the same measure as in Study 1 (α = 0.92).

Collective efficacy

The CE scale ( Guzzo et al., 1993 ) was used by managers and employees to assess CE. This questionnaire is composed of 15 items assessing various beliefs regarding team or group performance. These items are scored on a 5-point Likert-type scale ranging from 1 ( strongly disagree ) to 5 ( strongly agree ). In the original measure, participants assess themselves. In the current study, employees evaluated the efficacy of their respective work teams, and managers evaluated the efficacy of a target employee’s work team. Sample items included “I believe that the employees in my/my employee’s team will have high productivity if they work hard” and “I believe that the employees in my/my employee’s team can solve any problem they face” (α = 0.93).

Based on studies that found that managers’ tenure potentially affects their employees’ performance ( Drazin and Rao, 1999 ; Goldsmith, 2013 ; Chen et al., 2017 ), this study used managers’ tenure in their profession as a control variable. Managers with longer tenure in their profession have more work experience that may have an effect on their employees’ performance.

We first conducted a correlational analysis between performance, employees’ CE, managers’ evaluations of CE, and managers’ tenure in their profession 2 . Table 4 presents the means, standard deviations, and correlations.

Table 4. Means, standard deviations, and inter-correlations between variables (Study 2).

As shown in Table 4 , tenure was unexpectedly found to be negatively associated with OCB. One possible explanation is that the tenure of the older participants led them to engage in less OCB due to burnout or fatigue, although not empirically controlled for here. With respect to the main hypotheses, employees’ CE was significantly and positively associated with employees’ overall performance and performance efficiency. Managers’ evaluations of CE were positively associated with employees’ overall performance, performance efficiency, and performance creativity. In line with Study 1, the findings of Study 2 supported H1 with respect to the overall performance measure. It also enabled a better, more in-depth understanding of the specific performance dimensions related to OCB. The analyses also supported H3 and H4 regarding the impact of CE on performance for the general performance measure and specifically for the efficiency performance measure and for managers’ CE on the creativity performance measure 3 .

To examine the integrated model, which included the moderating roles of both employees’ CE and their managers’ evaluation of CE in employees’ OCB effects on performance, we used the PROCESS macro ( Hayes, 2013 ) Model 3. We conducted four analyses: one for the overall performance measure and three additional analyses for the three performance dimensions. To test the significance of the effects, and calculate the 95% CI for the indirect effects, bootstrapping with 5,000 resamples ( Hayes, 2013 ) was used (see Table 5 ).

Table 5. β, SE, t, p, and 95% confidence interval values for the analysis of overall performance as a function of OCB on ± 1 SD of managers’ and employees’ collective efficacies (Study 2).

The findings of Study 2 and the correlational analysis showed that employees’ OCB was positively associated with their performance efficiency, above and beyond the effects of managers’ tenure in their position and employees’ and managers’ CE. Moreover, the significant interaction effects suggested that the association between OCBs and performance was dependent on CE beliefs. Specifically, a significant two-way interaction was found between employees’ OCB and their CE beliefs in predicting overall performance, and a significant three-way interaction was found between employees’ OCB, their CE beliefs, and their managers’ CE beliefs in predicting overall performance. Three significant two-way interactions between employees’ OCB and their CE beliefs were found to predict the three performance dimensions (quality, creativity, and efficiency). Thus, the OCB association to performance emerged as dependent on employees’ beliefs in the capabilities of their team to perform its tasks. Furthermore, a significant three-way interaction between employees’ OCB, employees’ CE and managerial CE emerged for the efficiency performance measure.

To probe the essence of these interactions, simple slope analyses ( Aiken and West, 1991 ) were used for each interaction. In each analysis, the moderator was analyzed at plus/minus one SD from the mean as shown in Table 6 .

Table 6. β, SE, t, p, and 95% confidence interval values for the analysis of performance as a function of OCB on ± 1 SD of managers’ and employees’ collective efficacies (Study 2).

Probing the interactions for the overall performance measure

The employees’ OCB x CE interaction analysis to predict their overall performance indicated that OCB was positively associated with employee performance only when their CE was high (+1 SD ), β = 0.83, p < 0.001 [0.50, 1.17] or moderate ( SD ), β = 0.26, p = 0.023 [0.04, 0.47] but not when their CE was low (−1 SD ), β = −0.32, p = 0.129 [−0.74, 0.09] ( Figure 3 ), thus supporting H5. These findings thus suggest that OCB only positively predicts performance when employees have a moderate or strong belief in their team’s capacity to perform its tasks, but not when they have low beliefs in their team’s abilities. When employees do not believe that their team has high abilities, OCB did not have a significant effect on performance.

Figure 3. Impact of OCB on overall performance as a function of employees’ collective efficacy.

The results of a three-way interaction probe that separately analyzed the effects of OCB on overall performance for the different CE values (±1 SD of each CE measure) appear in Table 5 . Figure 4 provides a graphic representation of the results of the three-way interaction.

Figure 4. Impact of OCB on overall performance as a function of employees’ collective efficacy (CE).

As can be seen in Table 6 and Figure 4 , OCB positively predicted performance for (a) high employee CE values, regardless of their managers’ CE or (b) moderate employee CE values when their managers’ CE was high or moderate. This was not the case when managers’ CE was low. Moreover, when both employees and managers had low CEs, OBC was associated with negative effects on performance, possibly due to frustration.

Probing the interactions for dimensions of performance

With respect to performance quality, the analysis revealed that employees who were high on OCB and on CE performed significantly better than participants who were low on OCB, β = 0.75, p < 0.001 [0.42, 1.15]. In contrast, employees who were low on CE performed more poorly than when they were high on OCB, β = −0.74, p = 0.002 [−1.21, −0.27] than when low on OCB. The results for the moderate level of employees’ CE were not significant, β = 0.12, p = 0.966 [−0.24, 0.25] ( Figure 5 ).

Figure 5. Impact of OCB on performance quality as a function of employees’ collective efficacy.

Thus, in line with findings for the overall performance measure, high employee CE is important for leveraging OCB to improve performance. Even more dramatically, when employees do not believe in their team’s abilities, OCB leads to lower performance quality.

With respect to performance creativity, the analysis revealed that employees high on both OCB and CE performed significantly better than employees who were low on CE, β = 0.62, p = 0.001 [0.26, 0.97]. Unlike the results for performance quality, among employees with low or moderate CE, the effects of OCB on performance creativity were not significant, β = −0.26, p = 0.244 [−0.70, 0.18] and β = 0.18, p = 0.131 [−0.05, 0.41], respectively ( Figure 6 ).

Figure 6. Impact of OCB on performance creativity as a function of employees’ collective efficacy.

Thus, with respect to overall performance and performance quality, employees’ positive beliefs in their team are necessary to enable OCB to predict performance. In contrast to performance quality, low CE does not lead to the opposite results of OCB on performance, but rather to non-significant effects.

With respect to performance efficiency, the analysis revealed that employees who were high on OCB and on CE performed significantly better than employees who were low on OCB, β = 0.70, p = 0.001 [0.31, 1.09]. Even for moderate levels of CE, OCB significantly and positively predicted performance efficiency, β = 0.29, p = 0.029 [0.03, 0.53]. For employees who were low on CE, OCB had non-significant effects on creative performance, β = −0.13, p = 0.585 [−0.62, 0.35] ( Figure 7 ).

Figure 7. Impact of OCB on performance efficiency as a function of employees’ collective efficacy.

With respect to performance efficiency, employees’ positive or moderate beliefs in their team are needed to enable OCB to predict performance. However, unlike the performance quality facet, low CE did not lead to the opposite results of OCB on performance, but rather to non-significant effects.

Finally, the results for the three-way interaction were probed by separately analyzing the effects of OCB on the efficiency performance measure for different CE values (± 1 SD of each CE measure). The findings appear in Table 6 .

Figure 8 provides a graphic representation of the results of the three-way interaction.

Figure 8. Impact of OCB on performance efficiency as a function of employees’ collective efficacy.

As shown in Table 6 and Figure 8 , the performance efficiency findings were similar to those reported for overall performance. OCB predicted performance for high values of employees’ CE, regardless of their managers’ CE and for moderate employees’ CE when their managers’ CE was either high or moderate, but not when their managers’ CE was low. Moreover, when both employees and managers had low CE, OBC had negative effects on performance, possibly due to frustration 4 .

Structural equation modeling (SEM) was used for a comprehensive examination of the model. As recommended, a measurement model was examined. It was made up of 6 constructs: OCB, CE (evaluated by managers and employees) and three performance dimensions (quantity, creativity, efficiency). A confirmatory factor analysis (CFA) was used. The ACFA model exhibited good fit with the data [χ 2 = 2.33 (DF = 2); p = 0.312; RMSEA = 0.042; CFI = 0.996; NFI = 0.978], supporting the main hypotheses predicting performance dimensions ( Figure 9 ).

Figure 9. SEM of OCB as a predictor of three performance facets moderated by employees’ and managers’ collective efficacy.

As can be seen in Figure 9 , the results of the SEM revealed that managers’ CE was the most important determinant of all the criteria of job performance. Thus, the role of managers’ beliefs in team resources appears to have significant and specific importance, leading to better performance.

The results of Study 2 supported the hypotheses that managers’ and employees’ CE would moderate the OCB-performance associations. This findings is consistent with the literature that has emphasized the important role of team efficacy on performance ( Myers et al., 2004 ; Salanova et al., 2014 ). The findings revealed that managers’ CE had the greatest influence on employees’ performance. This finding is consistent with the literature that has underscored team managers’ prime role in facilitating performance ( Pak and Kim, 2018 ).

General Discussion

These two studies provide empirical evidence that supports a more accurate and comprehensive picture of the ways prosocial behaviors (OCB) facilitate or inhibit performance. Study 1 supported the first hypothesis that OE, which is related to employees’ beliefs in their internal resources, is a core antecedent of OCB. Study 2 supported the second hypothesis that the CE of both managers and employees, which represents employees’ beliefs in human external resources, moderates the OCB-performance associations. Using SEM, managers’ CE was shown to have the greatest influence on employees’ performance. By using a manager-employee dyadic model, the findings of a positive association between OCB and performance contributed to controlling for potential common method bias. The empirical support for the hypothesis regarding the moderating role of CE of both employees and managers sheds light on the ways in which employees’ OCB affects performance, and identifies the possible relative importance of employees’ and managers’ beliefs. The results also point to the conditions that are the most conducive to positive associations between prosocial behavior and performance, and the conditions that can lead to a negative association between OCB and performance (i.e., low CE among employees for qualitative performance). Finally, in addition to an examination of performance as a single construct, as has generally been the case in the vast majority of publications on this topic, we also examined the three dimensions of performance (quality, creativity and efficiency) that have been found to be crucial for achieving the best overall performance in today’s competitive markets ( Miron et al., 2004 ). This separate analysis for each dimension leads to a better grasp of the specific effects of both employees’ and managers’ CE as moderators of OCB effects on performance.

Specifically, employees’ OCB positively predicted performance even after controlling for demographics. These findings are in line with previous works on the positive effects of OCB on performance ( Choi, 2009 ; Lam et al., 2016 ; Park, 2018 ; Germeys et al., 2019 ). In addition, this positive association was only found when employees strongly believed in the ability of their work team (high employee CE) or when their managers strongly believed in their employees’ team abilities (high manager CE) but disappeared when employees, managers or both had weak beliefs in their teams (low CE). Under these conditions of low CE on the part of both employees and managers, OCB became an obstacle to achieving better performance quality. This effect may have been driven by frustration that can emerge when helping behaviors are met by low beliefs of employees and managers in their team’s abilities. Further empirical work should thus be conducted on this topic.

These results are also consistent with the important role of beliefs in team efficacy (CE) on performance as found in the literature ( Myers et al., 2004 ; Salanova et al., 2014 ). The findings that managers’ CE had the most influence on employees’ performance is consistent with the literature that stresses team managers’ prime role in facilitating performance ( Pak and Kim, 2018 ). In addition, when both employees’ and managers’ CE were high, OCB had the strongest positive effect on performance. Moreover, whereas performance was significantly higher for high OCB employees with high CE than for high OCB employees with low CE, the opposite was found when OCB was low. For low OCB employees, high CE led to lower performance, possibly due to frustration experienced when no assistance was provided by team members believed to have high abilities. Finally, whereas high OCB employees’ performance was significantly higher when managers had high CE than when managers had low CE, the opposite was found for low OCB employees. For low OCB employees, high managers’ CE did not lead to better employee performance than managers’ low CE.

The findings that OE serves as a core antecedent of OCB is consistent with previous findings on job self-efficacy and OCB in customer service employees ( Reizer and Hetsroni, 2015 ) and extends these findings to employees’ overall performance and three performance dimensions. Thus, inducing employees to believe more fully in their inner job-related resources may facilitate their OCB. This might be examined by providing positive verbal feedback to employees on their successful performance at work.

The specific examination of the three performance dimensions revealed that the model was fully supported for performance efficiency and creativity, but less strongly for performance quality. Thus, prosocial behavior in organizations appears to have the greatest impact on performance efficacy and creativity. This finding supports our initial expectation that performance efficiency and performance creativity are more dependent on interactions with other employees whereas performance quality is more dependent on employees’ human capital and less dependent on interactions with other employees. The findings supported the main predictions and are consistent with studies that have examined CE from the employee point of view ( Myers et al., 2004 ; Walumbwa et al., 2008 ; Lee and Ko, 2010 ; Salanova et al., 2014 ).

Overall, these data contribute to a better understanding of the mechanisms that facilitate the effects of prosocial behaviors on employees’ performance. In general, the stronger the beliefs in the abilities of employees’ teams team (high CE), the stronger the association between OCB and higher performance. The more strongly employees believe in their inner job-related resources, the more prosocial behavior they report.

Research Implications

These studies make five theoretical contributions. They provide new insights into the power of OCB to predict performance using a manager-employee dyad when controlling for managers’ tenure in their position. Research findings, based mainly on employees’ self-reports, have shown that OCB has a predictive effect on performance (e.g., Choi, 2009 ), and that CE is predictor of performance as well ( Myers et al., 2004 ; Salanova et al., 2014 ).

However, we found that although OCB has a predictive effect on performance, this effect disappears when the CE beliefs of both employees and their managers are low. Although many studies have examined OCB’s ability to predict performance, the literature review indicated that no study has tested the moderating effects of these associations. Here we used a relational perspective that captures the essence of these associations using the well-established CE concept.

Second, the studies here explored the role of OCB in performance from a relational perspective, which enriches current research frameworks. They examined prosocial behavior effects in work contexts more comprehensively by analyzing a broader spectrum of efficacy beliefs, which included the individual level (occupational-efficacy) and the group level of analysis (CE), which we believe is more relevant to the organizational context.

These studies extend the concept of CE to prosocial behaviors in the organization context. Although previous studies have found associations between group efficacy and collective action ( Besta et al., 2017 ) and between CE and undergraduate students’ performance in teams ( Brown, 2003 ), as far as we know, no study has explored or found associations between CE and prosocial behaviors in organizational contexts.

Fourth, using the well-established efficacy theory, OE was found to be an antecedent to OCB, thus providing a much more comprehensive theoretical grasp of the dynamics of psychological factors that contribute to better performance.

Finally, by not only examining one performance measure, but rather the core dimensions of performance, we were able to better pinpoint the specific areas of performance related to prosocial behavior. Using a dyad manager-employee model, we controlled for potential common method bias, since in Study 2, employees’ performance was evaluated by their managers rather than self-reported.

Practical Implications

These data have implications for managers and organizations interested in achieving better performance. Improving CE beliefs is one way to do so. Tasa et al. (2007) noted that CE emerges in part through continual exchanges of information and observed behaviors within a team, and that CE is influenced by teamwork behaviors as a sum total. Brown (2003) found that verbal self-guidance training led to better CE and performance among undergraduate students. Thus, training both managers and employees in the use of verbal communication that reinforces their CE beliefs and strengthens employees’ beliefs in their inner job-related resources may enhance the associations between OCB and performance relations as well as between OE and OCB. In addition, developing teamwork and improving harmony in work teams may increase the likelihood that helping behaviors in the team will contribute to performance. Moreover, managerial feedback and evaluations conveyed to the team may affect their CE. Therefore, managerial training programs should place greater emphasis on the importance of feedback not only to individuals but also to teams as a whole. In addition, identifying managers’ CE, employees’ CE, and employees’ beliefs in their own job-related resources should improve placement planning that generates a stronger association between employees’ prosocial behavior and performance.

Moreover, if employees’ CE is low, encouraging OCB behaviors in this team may not lead to better performance. In these instances, the first step would be to facilitate employees’ beliefs in their team, which should strengthen the association between prosocial behavior in the team and its performance. This should also be empirically examined in future research using an experimental design. Finally, as prosocial behaviors, and both team-level and individual-level efficacy were found to be related to performance, additional steps should be taken to emphasize the organizational level, specifically by embedding and assimilating processes in the organizational culture that encourage helping behaviors and collective actions.

Limitations and Suggestions for Future Research

Future research should be conducted using an experimental design to examine whether interventions to augment both CE and helping behaviors, as suggested here, also facilitate performance. In addition, helping behaviors in themselves, may increase the CE of team members. Thus, additional research should be conducted to explore the ways in which CE acts a mediator between prosocial behavior and performance. Moreover, although a well-established validated performance measure was used in both studies, and potential common method bias was controlled for, future research should use measures of actual rather than reported organizational performance as well.

These two studies provide empirical support for a more comprehensive model that can better predict and understand the dynamics of prosocial behaviors within organizations and their effects on performance. Specifically, we found that to achieve the best performance from OCB, high CE on the part of both employees and managers are both crucial. In addition, OE emerged as one of the core antecedents of prosocial behaviors within organizations. These findings thus pave the way for theoretical and practical avenues of research that should be examined in future studies.

Data Availability Statement

The datasets generated for this study are available on request to the corresponding author.

Ethics Statement

Ethical approval for this research was obtained from the institutions where the study was conducted. Filling in the questionnaires was indicative of informed consent.

Author Contributions

EY and JW made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

• ^ It could be argued that OE moderates the OCB prediction of performance. Although not hypothesized, we empirically examined this possibility using the PROCESS macro ( Hayes, 2013 ) model 1. Supporting our model (see Figure 1 ) no significant interaction was found between OCB X employees’ OE [ F general performance (3, 111) = −1.83, p = 0.069; F quality(3, 111) = −1.68, p = 0.096; F creative(3, 111) = −1.67, p = 0.099]; F efficiency(3, 111) = 0.11, p = 0.914), This strengthens our model where OE serves as an antecedent to OCB and not as a moderator on the OCB prediction of performance.
• ^ Initially we also included gender in the analyses as an additional control variable when examining H3 and H4. Since similar results were found after controlling for gender, we present the analyses when controlling for managers’ tenure in the position alone.
• ^ It could be argued that OE, which was found in Study 1 to predict OCB, could also serve as a moderator for the effects of OCB on performance. Although not hypothesized, we empirically examined this possibility using the PROCESS macro ( Hayes, 2013 ) model 3. Supporting our model (see Figure 2 ) no significant interaction was found between OCB X employees’ OE [ F general performance(7, 79) = −0.53, p = 0.598; F quality(7, 79) = −0.09, p = 0.926; F creative (7, 79) = −1.33, p = 0.187]; F efficiency(7, 79) = 1.26, p = 0.212), OCB X managers’ OE [ F general performance(7, 79) = 0.02, p = 0.983; F quality(7, 79) = 0.27, p = 0.786; F creative(7, 79) = 0.58, p = 0.561]; F efficiency(7, 79) = −1.57, p = 0.120), employees’ OE X managers’ OE [ F general performance(7, 79) = −0.05, p = 0.960; F quality(7, 79) = −0.50, p = 0.616; F creative(7, 79) = 0.06, p = 0.954); F efficiency(7, 79) = −0.18, p = 0.855],or OCB X employees’ OE X managers’ OE [ F general performance(7, 79) = −0.27, p = 0.788; F quality(7, 79) = −0.11, p = 0.916; F creative(7, 79) = −1.05, p = 0.300]; F efficiency(7, 79) = 1.37, p = 0.174) in predicting the general performance measure or the specific performance facets (quality, creativity, efficiency). This strengthens our claim that OE serves as an antecedent to OCB and not as a moderator on the OCB prediction of performance.
• ^ To examine whether similar results would be found after controlling for the effects of employees’ self-efficacy, we conducted all analyses as presented when also controlling for the employees’ self-efficacy measure. All results were similar to those reported, indicating that the moderation effects of collective efficacy were significant over and beyond the effects of employees’ beliefs in their personal general resources to achieve success.

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OCB Items used in the two studies [from Williams and Anderson (1991) ]

1. Assists others who have been away from the office or on leave.

2. Expresses willingness to take time to help others who have work-related problems.

3. Adjusts schedule to enable other employees to take time off.

4. Goes the extra mile to help newer employees feel welcome on the job.

5. Manifests real concern and courtesy to all, even under difficult business or personal situations.

6. Gives personal time to help others who have work or non-work issues.

7. Helps others do their work.

8. Lends own property to others to ease their workload.

Keywords : performance, organizational citizenship behavior, prosocial behavior, collective efficacy, occupational efficacy

Citation: Yaakobi E and Weisberg J (2020) Organizational Citizenship Behavior Predicts Quality, Creativity, and Efficiency Performance: The Roles of Occupational and Collective Efficacies. Front. Psychol. 11:758. doi: 10.3389/fpsyg.2020.00758

Received: 06 September 2019; Accepted: 27 March 2020; Published: 24 April 2020.

Reviewed by:

Copyright © 2020 Yaakobi and Weisberg. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Erez Yaakobi, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Organizational justice and organizational citizenship behavior: exploring the mediating role of psychological well-being at work

Rajagiri Management Journal

ISSN : 0972-9968

Article publication date: 29 April 2024

Issue publication date: 20 June 2024

The present research paper aims to examine the inter-relationship between organizational justice (Henceforth termed as OJ), psychological well-being at work (henceforth termed as PWBW) and organizational citizenship behavior (henceforth termed as OCB). More specifically, this paper attempts to critically analyze the mediating role of PWBW in the relationship between OJ and OCB. The study solely focuses on nurses working at private hospitals in Kerala, who are the largest group of healthcare personnel.

Design/methodology/approach

Data collected from 308 nursing employees were analyzed by using statistical package for the social sciences (SPSS) software.

The outcomes of the analysis demonstrate that significant correlations exist between all the three key variables and their dimensions. Moreover, it has been found that the relationship between OJ and OCB is partially mediated by PWBW.

Research limitations/implications

In the present healthcare scenario, just after the Covid-19 pandemic, there is a paramount need for the well-being of healthcare staff in order to improve the functioning of the healthcare system.

Originality/value

The study enabled us to develop and provide an explanation as to how social exchange relationship works between OJ and OCB.

Organizational justice

• Fairness perceptions
• Psychological well-being

Organizational citizenship behavior

• Healthcare worker

Changaranchola, M.N. and Samantara, R. (2024), "Organizational justice and organizational citizenship behavior: exploring the mediating role of psychological well-being at work", Rajagiri Management Journal , Vol. 18 No. 3, pp. 233-250. https://doi.org/10.1108/RAMJ-07-2023-0199

Emerald Publishing Limited

Copyright © 2024, Mohamed Nisfar Changaranchola and Rabinarayan Samantara

Published in Rajagiri Management Journal . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

In a fast-moving world where uncertainties are certain, there is absolutely no confusion regarding the fact that health is the most valuable treasure a person can hold. As it is observed, healthcare workers are the real and unsung heroes of the world. In any healthcare setting, nurses are the largest segment of staff who perform a crucial and significant role in providing medical care for patients. Nurses have to focus not only on the patient’s needs but also on all other communities such as the patient’s bystanders, doctors, paramedical staff and hospital management. This may often create an unfortunate burden on nurses irrespective of how difficult their work towards patient care is. At present, the nursing profession has been more challenging due to many reasons such as the emergence of new communicable diseases, advancement in medical technologies, change in demographics, profit motive of hospitals etc. A major portion of the nursing population works in the private sector. It is often noticed that nurses are protesting on various grounds, especially against their unfair treatment in the hands of the management. Fairness perception may have an impact on various organizationally relevant outcomes.

Since 2009, nurses in India have been organizing strikes and protests against long standing grievances relating to poor working conditions, low payment of salary and the mistreatment of nurses at the hands of the hospital managements ( Nair, 2010 ). As George Jacob has rightly reported, the nurses are the only professional group who are badly remunerated, exploited and being abused at the workplace ( Jacob, 2017 ). Kerala is a state known for its significant concentration of registered nurses. The unfair consideration in the hands of hospital management towards nurses has been very much evident during the last decade. In 2009, nurses from private hospitals, who were traditionally refrained from any sort of political activities, outburst out of self-concealed as an outcome of ever-increasing exploitation ( Biju, 2013 ). In 2012, nurses demanded a considerable work environment, better salary, and reasonable duty time and there were few of the requisites put forward by nurses working in the private hospitals ( Koshy, 2012 ). Nevertheless, protection against sexual harassment remains a major concern for this female dominated profession. With the meager amount of salary that is not even subscribed by the government, they were not able to pay loan repayment installments where most of the nurses belonged to economically weaker sections and had taken bank loans to pursue their studies ( Nair, 2010 ). The employees were compelled to work for ten-hours a day and 14-h night shifts and there were instances where employees were made to work for about 20 h when the hospitals were short staffed. Similarly, the hospital management was reluctant to pay the minimum wages that were revised in 2013. Moreover, the hospitals were deploying ‘trainees’ even after several years of work and Employees’ State Insurance (ESI) and Employee Provident Fund (EPF) were also denied ( Barria, 2018 ). The minimum wages that are ensured by the highest court of the land, time bound, unbiased and meaningful appraisal, increment and bonuses, kind behavior from the side of management and doctors, basic facilities like changing rooms, resting rooms, etc. accommodation within the hospital premises or close proximity, and safety of nurses’ young children, are few of the concerns of nurses working in private hospitals ( Jacob, 2017 ). The unjust conditions and the subsequent protests were recurring and still continuing in various parts of the country.

Against the background of these observations, we were interested to know how this perception of justice would impact employees’ performance, specifically nurses’ performance in this case. Over time, researchers in the field of organizational studies have investigated various approaches to attaining organizational success through improving employee performance. In this context, citizenship behavior has got much attention as it is not only predicts efficiency performance but also enhances many other organizational outcomes such as quality outcome, creativity etc. ( Yaakobi and Weisberg, 2020 ). Organizational citizenship behavior (OCB) pertains to voluntary and discretionary actions that employees undertake to contribute to their organization's welfare, extending beyond their formal job duties ( Organ, 1988 ). When it comes to the healthcare industry, where the number of skilled employees is limited and especially the patient care that is largely based on manpower or human capital, it requires an exhibition of citizenship behavior for the well-being of the patients ( Basu et al. , 2017 ).

Often the aforementioned injustice leads nurses to commit suicide ( Kerala: Nurses booked for suicide attempt, 2012 ). Working under extreme pressure even in the unfavorable conditions must be creating great psychological impact among these front-line workers. Furthermore, a low perception of justice by employees could potentially create a detrimental impact on how they effectively and efficiently fulfill their job responsibilities and tasks. Even though there are enormous studies on the connection between organizational justice (OJ) and OCB, the present study explains how such a relationship channels. Against the background of these observations, we propose a model in which OJ leads to psychological well-being (PWB) of employees and PWB, in turn, results in citizenship behavior of nurses working at private hospitals in Kerala.

Theoretical background

OJ has been widely used in the organizational context as an explanatory variable to predict many organizationally relevant outcomes. OJ is concerned with how employees judge the behavior of the organization towards them in terms of rewards and outcomes. It also includes the behavior of the organization in other aspects of the work, such as ethicality, recognition, personal development, security etc. According to Elovainio et al. (2005) , OJ is defined as the perception of workers on the grounds of being treated justly and truthfully by the organization or its management. Even though there are arguments regarding dimensionality of OJ, the most acknowledged and widely used dimensions are distributive, procedural and interactional justice. Individuals assess the fairness of their supervisors or organization through these dimensions ( Caleo, 2016 ). Distributive justice pertains to employees’ perception of an organization’s resource allocation. In other words, it is the judgment of people on what they receive ( Saks, 2006 ). Procedural justice is concerned with the equity and fairness of the processes employed in making decisions related to the allocation of organizational resources and benefits ( Thibaut and Walker, 1975 ). On the basis of this dimension, the procedure should be accurate, consistent and unbiased. Interactional justice refers to the status of inter-relations among individuals within the organization ( Folger and Cropanzano, 1998 ). Moreover, this aspect of OJ necessitates that management upholds politeness, nobility, sincerity and consideration throughout the decision-making process. Likewise, taking into account the perspectives of workers in the decision-making process and ensuring effective communication with them can be categorized as interactional justice ( Niehoff and Moorman, 1993 ).

Psychological well-being at work

There has been a plethora of studies in the area of PWB during the last three decades. Similarly, the conceptualization of PWB has been subjected to extensive research ( Dagenais-Desmarais and Savoie, 2012 ; Ryff, 2014 ). Several well-being measures have been developed by economists, psychologists, etc. Over time so as to guide many government and nongovernment organizations in the policy-making process. Human well-being can be defined as an observational assessment of a person’s daily living conditions based on his ability and potential to live a good life in a particular society ( Dasgupta, 1995 ). Ed Diener, a trailblazer in well-being research, regarded well-being as encompassing various aspects like greater positive affect, absence of negative affect, life satisfaction, etc. that involve the evaluation of one's life and emotional experiences ( Diener et al. , 1999 ).

Researchers have been using both context-specific and context-free measures of PWB while measuring organizational correlates. In fact, work is a life domain that can be distinguished from other life domains such as family, leisure, etc. A significant majority of individuals dedicate more than half of their waking hours to work. This sphere of the life has its own special characteristics that contribute to distinctive experiences apart from all other life domains. Context-free measures appear to be ill-suited for the organizational context, as they may not adequately capture the complexities and realities of the workplace ( Dagenais-Desmarais and Savoie, 2012 ). Besides, Warr (1990) has suggested the need to study both context-free and context-specific measures at the workplace. Moreover, researches have demonstrated the enhanced predictive ability of context-specific measures compared to context-free measures in the organizational setting ( English, 2001 ). Psychological well-being at work (PWBW) refers to an individual's subjective experience of positive emotions and overall positive state while on the job ( Dagenais-Desmarais and Savoie, 2012 ).

There has been an abundance of research on the concept of OCB and the related constructs such as pro-social behavior, organizational spontaneity, extra-role performance, etc. since the inception of the phrase OCB by Organ and his colleagues ( Smith et al. , 1983 ) during the early eighties. Dennis Organ, considered as the father of the concept of OCB, defined this concept as something that is not specified by the organization and does not lead to formal reward system straightaway but ultimately leads to overall efficiency of the firm ( Organ, 1988 ). Therefore, OCB can be interpreted as consisting of behaviors that fall beyond job specifications or contractual obligations and promote organizational performance or effectiveness. Different OCB frameworks describe OCB topology in several ways. One of the most accepted approaches distinguishes citizenship behaviors by their targeted beneficiary, i.e. towards organization, known as OCBO and towards individuals, known as OCBI ( Williams and Anderson, 1991 ). OCBI, or OCB towards Individuals, can be defined as voluntary behaviors that benefit individuals within the organization. It encompasses acts of altruism and courtesy. On the other hand, OCBO or OCB towards the organization, is aimed at benefiting the organization as a whole. It includes behaviors such as civic virtue, conscientiousness and sportsmanship ( Organ, 1997 ).

Review of literature and hypotheses formulation

Oj-ocb relationship.

OJ has a positive effect on OCB.

OJ-PWBW relationship

OJ has a positive effect on PWBW.

PWBW-OCB relationship

Research studies have suggested that employees who experience happiness are more likely to demonstrate altruism, empathy, and respect towards others. Additionally, they tend to feel more empowered and promote work engagement ( Tesi et al. , 2019 ). Positive emotions have the ability to foster social connections and create an environment conducive to building and sustaining relationships. Research has shown that employees in good mood tend to produce more of output while unpleasantness creates a negative impact on productivity ( Oswald et al. , 2015 ). In addition, it has been noted that positive feelings of workers reduce absenteeism and promote self-sufficiency, resiliency and optimism at the work situation. Similarly, happy employees have been found to be high in supervisor-rated performance ( Peterson et al. , 2011 ). It has also been noticed that happy individuals are more energetic, cooperative and collaborative ( Carnevale, 2008 ). Similarly, Mousa et al. (2020) found that happy employees are the greatest in keeping long term quality relationships and are more likely to engage in citizenship behavior. As observed by Byrne et al. (2003) , employees who perceive their organization as socially responsible in providing a fair work environment are more inclined to involve themselves in extra-role activities, moving beyond their formal job responsibilities. Moreover, they were more likely to experience a sense of well-being and exhibit a higher likelihood of remaining in the same organization.

PWBW has a positive effect on OCB.

PWBW mediates the positive association of OJ and OCB.

Research method

Research sample and procedures.

The present research aims to draw conclusive findings and provides a detailed description of the phenomenon under investigation using data collected at a single point in time. The study population consisted of all nurses employed in private hospitals within the State of Kerala. Primary data were collected from nurses working in different allopathic hospitals. Convenience sampling was employed after the population was stratified into distinct geographic regions: south, center, and north ( Krishnan et al ., 2016 ). This zoning approach helps in organizing the data collection process and ensuring comprehensive coverage of the State's private hospital nurses. The decision to utilize convenience sampling within the delineated strata stems from the practical challenges associated with achieving a more systematic or random selection of participants. One district was selected from each zone based on the criterion of having the largest number of allopathic hospitals in the private sector. This selection approach ensures representation from areas with a high concentration of private hospitals in each zone. Again, four allopathic hospitals were randomly chosen from each district so as to obtain the desired sample size of respondent-nurses. Finally, the research survey was conducted through the distribution of Google forms among the nurses employed in those healthcare facilities ( Table 1 ). The sample size required for the present study was determined through the performance of Power Analysis. In fact, separate Power Analyses were conducted for each test (i.e. correlation, regression and mediation), and the largest sample size obtained was selected as the basis of recruitment. To determine the appropriate sample size for the study, Monte Carlo Power Analysis and Version 3.1 of G power software were utilized ( Faul et al. , 2009 ; Schoemann et al. , 2017 ). The sample size of the research study was 308. Microsoft Excel was utilized to transform raw data retrieved from Google Forms into a format conducive to subsequent analysis. The encoded data were subsequently imported to the statistical package for the social sciences (SPSS) software for further comprehensive analysis. In assessing the reliability of the questionnaire, Cronbach’s alpha was computed using SPSS. Finally, mediation analysis was conducted utilizing the SPSS PROCESS macro, as presented by Preacher and Hayes (2008) .

The researchers have taken all possible measures to reduce response bias. Employing measures such as ensuring response anonymity or making confidentiality commitments can be considered as a successful approach to control social desirability bias ( Larson, 2019 ). At the outset of the questionnaire, researchers explicitly stated that the identities of the respondents would be treated as confidential. In a written statement, the researchers explicitly stated that the data collected from nurses would be utilized solely for research purposes. This ensures that the information provided by the participants will be used exclusively for the intended research study and will not be disclosed or utilized for any other purposes. In addition, Harman's single-factor score technique was utilized to test for common method bias (CMB) as suggested by Podsakoff et al. (2003) . It examines whether the unrotated factor solution of exploratory factor analysis accounts for variance in the variables. If a significant degree of CMB exists in the data set, it is expected that either a single factor will emerge or one general factor will account for the majority of the covariance among the measures. This indicates that the shared method variance influences the responses, potentially biasing the results. In the current study, it was concluded that CMB was not present, as the single factor identified accounted for only 26% of the variance in the measures, confirming that no single factor explained the majority of the variance.

The OJ Scale, as utilized in the present study, was initially developed by Moorman (1991) , and then modified by Niehoff and Moorman (1993) . Distributive justice, procedural justice and interactional justice dimensions constitute OJ scale. Respondents indicated their responses on a seven-point Likert scale, where one represented “strongly disagree” and seven represented “strongly agree.”

Nurses’ level of OCB was measured using two-dimensional scale, each consisting of eight items, developed by Lee and Allen (2002) . The two dimensions reflect OCB towards individual (OCBI) and OCB towards organization (OCBO). The respondents provided their responses to these 16 items on a seven-point Scale (1 = never, 7 = always). Thus, the respondent-nurses were requested to indicate the extent to which the OCB ratings obtained through self-report measures described their actual citizenship behavior in the organizational setting.

Index of PWBW

PWBW was measured with the help of the PWBW Index (25 items) developed by Dagenais-Desmarais and Savoie (2012) . Different items of PWBW were measured using a scale where one represented disagree and six represented completely agree. Employees' feelings about the work situation were captured by using the scale that contains a range of statements. Respondents were asked to indicate the extent to which they agreed with each statement on the basis of their job experiences over the past four weeks. The PWBW Scale comprises of five components such as interpersonal fit at work (IFW), thriving at work (TW), feeling of competency at work (FCW), personal recognition at work (PRW) and desire for involvement at work (DIW), comprising of five statements each.

Results of analysis

The results of the study included scale reliabilities, correlation co-efficients and mediation output. The results presented in Table 2 show that all the latent variables are reliable as the measure of internal consistency is within the threshold-that is above 0.7, as suggested by Shevlin et al. (2000) . In this context, it would be worthwhile to mention that mean values calculated for different dimensions of both OJ and OCB were relatively higher than mean values calculated for the specific aspects as well as the composite measure of PWB at work. However, the standard deviations calculated for facets of the studied variable were at a moderate level and fell within the range of 0.83 and 1.42. These lower values of standard deviations provide some indication about consistency in the nurses’ responses to various scale items relating to the studied variables. The results as given in Table 2 show the correlations existing between the stated variables, i.e., between OJ and OCB, OJ and PWBW, and PWBW and OCB with significant values of 0.60, 0.65 and 0.75, respectively, thereby supporting H1 , H2 and H3 . Similarly, all the dimensions of OJ, PWBW and OCB correlated with one another with a significance level of five percent. Upon a meticulous examination of the inter-correlation matrix, it becomes apparent that Interactional justice is highly correlated with PWB at work and OCBO. OJ and its dimensions had higher correlations with OCBO as compared to the correlations that existed between OJ and its dimensions with OCBI. Moreover, as compared to OCBI, OCBO has the higher correlations with PWB at work and its dimensions.

The total effect of OJ on OCB is shown in Figure 1 . Such total effect refers to the effect of OJ (predictor) on OCB when the mediating role of PWB is not present in the given model. When PWB at work is not present in the model, OJ happens to significantly predict OCB (i.e. b = 0.640, p is less than 0.05).

It may be noted that mediation analysis was conducted with OJ as an independent variable, OCB as a dependent variable, and PWBW as a mediating variable with 5000 bootstrapping samples at five percent significance level. The results of mediation analysis have been visually demonstrated in Figure 2 and also presented in Table 3 and Table 4 . In fact, the effects of (1) OJ on PWBW (Path a), (2) PWBW on OCB (Path b), (3) indirect effect of OJ and OCB (Path c′) and (4) the total effect of OJ on OCB (Path c) were found to be significant as demonstrated in Table 3 . The fact that the relationship between OJ and OCB gets significantly reduced when the PWBW enters, confirms the role of mediation ( Baron and Kenny, 1986 ). As can be seen from Table 4 , the Beta value for the indirect effect falls between 0.340 and 0.534. As the bias modified and enhanced bootstrapping confidence intervals at 95% level of significance of the indirect effect (OJ-PWBW-OCB) do not contain zero, it is statistically confirmed that the relationship between the constructs of OJ and OCB is mediated by PWBW. Thus, Hypothesis 4 relating to the role of mediation has been supported. The results of mediation analysis indicate that a partial mediation does exist as path c′ is significantly different from zero.

Nurses constitute the backbone of the healthcare sector and are regarded as the custodians of human life. As highlighted in the introduction, a pervasive issue in the healthcare industry in Kerala, and beyond, pertains to the unfair treatment of nurses in private hospitals. In the present study, attempts have been made to critically examine the direct and indirect effects of OJ on OCB with special reference to nurses employed in private hospitals in the State of Kerala. The seamless functioning of hospitals often necessitates discretionary activities from healthcare workers, contributing to the provision of quality healthcare and impacting the physical and mental recovery of patients, ultimately benefiting the hospital. The findings of the study broadly indicate that OJ or fairness perception of nurses has a notable impact on their engagement in citizenship behavior directly as well as indirectly through PWBW. This implies that nurses who perceive more of justice within an organization were more likely to perform OCBs than nurses who perceive a lower level of fairness. In addition, it was observed that the path of OJ through PWB at the workplace accounted for more of variance in OCB than the path of OJ alone. This indicates that employees primarily participate in extra-role behavior due to their inner feelings; therefore, their loyalty and dedication towards the organization would become more enduring and deep-rooted when these are caused by their inner psychological strengths. However, if they engage themselves in OCB only because of their perceptions of organizational support, it is likely to be relatively short-lived in nature ( Seena, 2018 ). This finding aligns with previous research studies on citizenship behavior; for instance, Moliner et al. (2008) observed that PWBW, contingent on burnout and engagement, acts as a mediating variable between OJ and citizenship behavior directed towards customers.

The findings of the study have provided empirical evidence in regard to the conceptualization of OJ and OCB as a social exchange process. Social exchange theory assumes that people are rational-beings who assess the potential outcomes of their actions, considering the benefits and drawbacks ( Blau, 1964 ). In the organizational context, employees perceive OJ as an implicit agreement between them and the organization: fair treatment fosters a sense of reciprocity. This, in turn, influences OCB, wherein employees engage in discretionary, positive and extra-role activities that contribute to the overall functioning and well-being of the organization. When employees feel that they are treated justly, they are more likely to reciprocate with enhanced OCB, viewing their extra efforts as a form of social exchange to maintain the perceived fairness within the organizational context. Thus, the relationship between OJ and OCB exemplifies a social exchange dynamic, where fairness acts as a catalyst for employees to contribute beyond their formal role requirements, ultimately benefiting the organizational social fabric. This major research finding has been in keeping with the findings of many other research studies and further strengthens the predominant role of individual relationships over any material aspect of life ( Organ, 1990 ; Moorman, 1991 ; Jehanzeb and Mohanty, 2019 ). As found earlier by Lee and Allen (2002) , the outcomes of the current study also disclose that OJ is more closely associated with OCBO as compared to OCBI. Therefore, within the scope of the present study, it can be asserted that nurses do not manifest an intention to regulate their citizenship behavior towards individuals based on their perceptions of fairness. Indeed, it is noteworthy that in reality, the impacts of fairness perceptions are more prominently associated with OCB directed towards the organization rather than OCB directed towards individuals. This implies that a decrease in perceptions of justice is likely to result in diminished loyalty and commitment to the hospital, underscoring the principle of reciprocity, “you get what you give”. The findings of the present study indicate that the perception of distributive justice exerts a more pronounced influence on the citizenship behavior of employees. Additionally, it was observed that procedural justice, pertaining to the process through which allocations are made, also has a discernible impact on OCB.

Besides, the research study indicated a significant relationship between OJ and PWBW. Previous research has convincingly demonstrated that when employees are treated fairly by their management or supervisors, it results in heightened PWB of workers. Employees develop more positive attitudes and exhibit acceptable behaviors on the basis of their positive perceptions about their workplace at the workplace ( Colquitt et al. , 2005 ). Here, interactional justice, or the manner in which nurses are treated by their supervisors or managers, showed high correlation with their PWB. The research results clearly revealed the prominent role of procedural justice in influencing PWBW. Consistent with the findings of Rani et al. (2012) , who suggested that equal freedom and opportunity to perform one's own duties and equal reward allocation minimize psychological distress, promote trust and ensure the retention of the employees for a longer period with greater job satisfaction. The findings allied to OJ and PWBW suggest the importance of fair pay, work and responsibility as well as the need for unbiased decision making and the need for nurses being heard by the management. Similarly, consideration from the side of hospital management such as treatment with kindness, respect and dignity is making impact on PWB of nurses. Elements such as dealing with nurses in a truthful manner, knowing their personal needs, discussing the implications, providing adequate justification, etc. have paramount importance while taking decisions as these are directly related with nurses’ PWBW.

The research results obtained point to a positive relationship existing in the middle of PWB of nurses and their citizenship behavior. Nurses rated as having more of PWB were more likely to engage themselves in citizenship behavior. In addition, it has been previously confirmed that employees who are in a good mental state produce better results than employees with a negative mental state and tend to achieve lower work productivity ( Oswald et al. , 2015 ). By transforming the hospitals into healthy workplaces by recruiting and retaining an adequate number of nurses, career satisfaction and job well-being can contribute to the organizational success with better patient care ( Nayeri et al. , 2005 ). The fact that employees in good PWB condition display more of citizenship behavior can be attributed towards their prolonged or sustained good feelings. This may also be because employees with good feelings tend to see things positively with the result that organizational situations and co-workers are perceived as deserving more of discretionary assistance ( Isen et al. , 1978 ). Considering nurses in hospitals, there is a perception that their additional efforts or services are highly valued by patients. As compared to the relationship between PWBW and OCBI, it was found that PWBW and OCBO had a higher correlation. Thus, PWB does not seem to be much affected by OCBI. The nurses’ sense of accomplishment and fulfillment often makes them engage in both individual and organization-oriented citizenship behaviors. All these findings provide evidence for the basic proposition that happy employees tend to exhibit more of citizenship behavior.

In times of healthcare workforce shortages or medical emergencies such as pandemics, the adoption of citizenship behavior emerges as a crucial strategy for hospital management. This study affirms the significance of justice perceptions among nurses in private hospitals, asserting that these perceptions not only contribute to citizenship behavior but also impact the PWB of nurses. The findings underscore that a mere increase in nurses' salaries within private hospitals does not represent the optimal practice for enhancing PWB and citizenship behavior. Instead, a comprehensive approach is warranted, considering factors beyond monetary considerations, notably the manner in which hospital management and fellow employees interact with nurses. Factors such as resource allocation processes, decision-making protocols and interpersonal treatment are deemed crucial, with employees subjectively evaluating the fairness or unfairness of these activities.

Implications for managers and policy makers

Healthcare workers are the vital resources of any country or region. In the present healthcare scenario, healthcare organizations have a great need for efficient healthcare professionals who need to pay complete attention to the patients so as to attain the vision of health policy-makers. The major implication of the present research is that managers or supervisors can very well influence the employees’ well-being at work and their engagement in OCB. The managers can attempt to increase the employees’ PWB through the fairness of their attitudes and behaviors towards employees. Fair procedures followed to achieve the outcomes, fair distribution of rewards, procedures and interpersonal treatment positively contribute to the intellectual prosperity of nurses. In fact, a strong relationship is found to exist between interactional justice and PWB of nurses. Therefore, to promote PWB among employees, there is an absolute need to treat employees with respect, sympathy and dignity, understand their personal needs and aspirations, and uphold their rights as a healthcare professional. Fair distribution of work and resources, transparency in procedures, open disclosure, effective and supportive interpersonal treatment, etc. will do the job for better PWB and citizenship behavior. Training programs may be organized by hospitals for managers and supervisors, especially on the concept and utility of sound human relations in a work situation. Research evidence has shown that a workforce with better PWB is an asset for any organization. Organizations should adopt a humane and rational approach towards their employees as it affects both their work productivity and well-being. Therefore, the hospital administration and policy makers must try to recognize and realize the importance of PWB of healthcare professionals, which is a paramount need of the present-day times. The healthcare system should be driven by the needs of patients and healthcare workers rather than the profit motive needs of the management.

The present study holds paramount significance, particularly in the aftermath of the recent global pandemic, COVID-19. This crisis underscored the remarkable courage exhibited by the healthcare workforce under challenging circumstances to ensure medical care for the afflicted. The world found itself unprepared for such a pandemic, revealing vulnerabilities in hospitals and nursing preparedness. This pandemic serves as a catalyst for instigating systematic preparations to address future events of a similar nature. Hospital management needs to address crucial components such as proper access to insurance, training and psychological rehabilitation in light of the lessons learned from the COVID-19 pandemic.

Additionally, attention must be directed towards maintaining adequate staffing levels and implementing systematic shifts, recognizing that the healthcare profession demands round-the-clock commitment. It is imperative to alleviate the burden on healthcare professionals, thereby promoting their long-term well-being and health. This, in turn, enhances their resilience and capacity to deliver optimal healthcare outcomes.

Limitations and directions for further research

The present research has certain limitations that should be acknowledged and interpreted in the light of scope for further research in the field. First, the research study was conducted among nurses employed in private healthcare settings only. Therefore, further research studies should test a similar model in other organizational settings such as medical institutions (except private hospitals) and also across geographical regions as this injustice situation is prevalent in many states in India. Second, since the research design followed for the current research is cross-sectional, longitudinal studies may provide more useful research results. It should be noted that the present research was carried out during the outburst of Covid-19 pandemic. Therefore, future studies can be conducted to examine whether the findings of the present research have been affected by the pandemic situation or not. Third, the current study was conducted with a sample size of 308 nurses and, thus, further segregation of these sample respondents on the basis of their demographic profile or characteristics has resulted in a minimum number of respondents in certain categories. Therefore, future research can be carried out with more representative samples from each category of nurses.

This study elucidates the dynamics of social exchange relationships between OJ and OCB. It establishes that the PWB of nurses serves as a mediating factor in the connection between their perceptions of justice and their engagement in citizenship behavior. Within the contemporary healthcare landscape, characterized by complex challenges and heightened demand for quality patient care, healthcare workers emerge as indispensable assets for any nation. The present study underscores the critical importance of cultivating a work environment that not only promotes OJ but also recognizes the pivotal role played by the PWB of nurses. This holistic perspective emphasizes the symbiotic relationship between OJ, PWB, and the manifestation of citizenship behavior, offering valuable insights for the strategic management of human resources within healthcare organizations.

Total effect without mediation

Indirect effect with mediation

Demographic profile of respondents