Organizational citizenship behavior in the military context: Are we missing the mark?

ABSTRACT

Organizational citizenship behavior (OCB), discretionary behavior that promotes organizational effectiveness, is a well-developed construct with great importance to the military. Despite its significance, few studies have examined OCB within the armed services. Those that have tended to use existing OCB scales without additional validation and only minimal adaptation to the military context. This is problematic because of the distinctive features of the American armed services, such as the substantial power leaders possess to compel behavior and the uniqueness of behaviors that create military value. The purpose of this study is to develop and validate five OCBs and a second-order OCB factor that are fully discretionary and produce unique and substantial value for the military. These military OCBs include sacrificing, providing positive word-of-mouth endorsement of the military, voluntary retention in the organization, voluntary participation in activities, and use of services that improve welfare and readiness. Some of these behaviors are so vital that the military could not achieve its mission without them. This study also seeks to understand and assess antecedents of military OCB. Using survey data from several Army populations and a series of validation analyses, the results reveal five military OCB factors, a second-order OCB construct, and four new military OCB antecedents. Opportunities and implications for the use of military OCBs are developed and the limitations of the study are examined.

What is the public significance of this article?—This study developed and validated the first military organizational citizenship behavior (OCB) measure using discretionary behaviors known to create significant value for most U.S. military organizations and addressed concerns that existing OCB measures included compulsory activities and did not target the most valuable behaviors. This study also developed and validated four new military OCB antecedents and identified that being currently deployed to combat, being in the combat arms, and having greater time in service diminishes military OCB.

The role of organizational citizenship behavior in the military

Organizational citizenship behavior (OCB) has been a key element of organizational research for almost a half century. Katz and Kahn identified the importance of discretionary behaviors that contribute to organizational effectiveness in 1978, and Organ later conceptualized these discretionary, non-enforceable behaviors as OCB (Organ, 1988). OCB is generally defined as an individual’s voluntary behavioral contributions to the organization that are beyond their required duties and create a substantial positive impact on organizational effectiveness in aggregate (Organ, 1988, 1990). OCB is particularly important for the armed forces because some of the most valuable military behaviors are discretionary (Gurbuz, 2009). The U.S. military depends on its members to go beyond their assigned tasks and responsibilities to accomplish the most challenging missions and inspire others through positive role-modeling and reinforcing the cultural norms of selfless service and duty. Imagine the difference between a military organization where members make sacrifices and seek to create value and a military unit where members only do what is explicitly required.

The strong relevance of OCB to the military is reflected in the title of Organ’s formative 1988 book, “Organizational Citizenship Behavior: The Good Soldier Syndrome” and Bateman and Organ’s conceptualization of OCB as “good soldier syndrome” that promotes the prosperity and good effectiveness of every organization (Bateman & Organ, 1983). Despite the “good soldier” characterization, OCB and its antecedents have been researched primarily in civilian organizations (Gurbuz, 2009; Jordan et al., 2007). This is unfortunate because military OCB appears to have positive effects on military unit achievement (Gurbuz, 2009). Several research projects have begun to address the dearth of military OCB (Deluga, 1995; Gurbuz, 2009; Jordan et al., 2007; Rose et al., 2017), but this research has largely relied on the constructs and scales developed in civilian organizations and contexts. If military research is to understand the full functioning and nomological network of OCB, it will require a development and validation of OCBs and their antecedents in military contexts.

Therefore, the purpose of this paper is to identify and validate specific OCBs that are 1) truly discretionary (non-enforceable) despite the significant social and structural control that exists in the military and 2) create the most value for military organizations. Additionally, this research seeks to identify and validate additional OCB antecedents that have heightened relevance in the military context. In doing so, this research will enhance our general understanding of the functioning and impact of OCBs in U.S. military organizations.

Issues with traditional organizational citizenship behavior use in the military context

There are a couple reasons why traditional OCBs are insufficient for the military context. First, typical citizenship behaviors in the civilian context may not be fully discretionary in military organizations (Rose et al., 2017). In short, behaviors that are enacted voluntarily in civilian contexts may be compulsory in a military context. Second, the distinctive attributes of military organizations may create a unique set of OCBs based on its needs and missions. Despite the insufficiency of traditional OCBs, these behaviors have some validity and relevancy for the military, but we can do better.

There are currently no studies that have developed and validated OCBs and its antecedents specifically for the military context. Instead, most military OCB studies have used prevailing OCB scales or lightly adapted scales for use with military personnel and organizations (Jordan et al., 2007). For example, Gurbuz (2009) adapted measures from past OCB research (Organ & Konovsky, 1989; Williams & Anderson, 1991) and Deluga (1995) used the 1990 Podsakoff Organizational Citizenship Scale with general statements like “does not take extra breaks” or inserting the word “military” in the item. This could be problematic because behaviors that are discretionary in a civilian context (e.g., not taking extra breaks) may be expected behavior among service members based on military norms and values (e.g., U.S. Army values of duty, loyalty, and selfless service; Rose et al., 2017).

Military organizational citizenship behaviors and antecedents

Military organizational citizenship behaviors

Instead of using the prevailing OCB scales, this research develops military OCB using discretionary military behaviors that are critical to mission success but cannot be compelled by leaders or organizational systems. While many scholars have suggested that OCB is composed of multiple behavioral dimensions (Organ, 1988), a metanalysis by LePine et al. (2002) demonstrated that these dimensions are highly related, not empirically distinguishable, and function as equivalent indicators of OCB. Accordingly, this research approaches OCB as a singular underlying construct.

Behaviors that have proven to be discretionary, valuable to the military, and reflect a broader tendency to enact selfless service include sacrificing for the mission, the unit, or its members; providing positive word-of-mouth to promote the unit/military; voluntary reenlistment and continuation of military service; participation in voluntary activities that benefit the military; and increased consumption of voluntary services that enhance service member warfighting readiness and family wellbeing (Woodruff, 2017). While not exhaustive, several of these discretionary behaviors are so vital that the U.S. military could not achieve its mission without them. Additionally, they reflect the affiliative and promotive quality of OCBs (Organ, 1997) better than ambiguously voluntary behaviors.¹ Selection of these OCBs is discussed in the methods section.

Hypotheses 1 – Sacrificing, positive word-of-mouth, voluntary retention, volunteerism, and use of readiness enhancing services will create a second-order military OCB factor.

Antecedents of organizational citizenship behavior

While this study is centered on the development of military OCBs, it is important to also develop its nomological network to understand and validate the construct. Much of the existing research on OCB antecedents has focused on organizational commitment (Gurbuz, 2009; Organ & Ryan, 1995), job satisfaction (Organ & Konovsky, 1989; Organ & Ryan, 1995), and motives (Gould-Williams et al., 2013; Perry, 2000; Rioux & Penner, 2001). This research develops organizational identification, job satisfaction, and military enlistment and service motives as antecedents of OCB.

Organizational identification

Organizational Identification is a form of social identity and argues that individuals derive their identity principally from the social categories to which they belong (Brewer, 1991; Stets & Burke, 2000), with identified individuals evaluating themselves using the in-group’s characteristics, behaviors, values, and beliefs. Organizational identification also implies a psychological connection and a sense of oneness with the organization, where the individual defines himself/herself in terms of the organization and would feel loss if the connection to the organization was ended or threatened (Stets & Burke, 2000).

Identification is most likely to occur when the individual feels a sense of oneness and connection to the organization (Ahearne et al., 2005; Bergami & Bagozzi, 2000; Van Knippenberg & Sleebos, 2006). The more salient the identity, the more it influences perception and behavior, and the more individuals tend to reinforce their most salient identities by engaging in relationships and behaviors associated with those identities (Oakes, 1987).

Organizational identification has also been shown to be a significant antecedent of OCB, with individuals having higher levels of identification being more likely to demonstrate OCB (Nguyen et al., 2016; Shim & Faerman, 2017). Identification also creates the potential for heightened citizenship behaviors, where individuals enact OCBs despite substantial cost. For example, a highly identified person may enact behaviors that strongly benefit their team even when the team does not provide proportionate benefits to the individual (Ashforth & Mael, 1989).

Several studies have demonstrated that organizational identification influences behaviors that are of importance to the military and could be classified as OCBs, including increased retention, positive WOM/promoting, participation, and helping (Mael & Ashforth, 1992). Similarly, Arnett et al. (2003) showed that organizational identity was related to promoting the organization and O’Reilly and Chatman (1986) found it influenced remaining with the organization (both are aspects of the OCB measure used for this research). Bhattacharya et al. (1995) found that highly identified individuals create substantial value for organizations through their relational behaviors. It seems clear that the U.S. military and organizations with high levels of affiliation can benefit from the development of identified individuals and the resulting increase in its members’ OCB. In general, the more the environment provides the opportunity for affiliation and the more enacting OCB provides the basis for positive self-comparison, the more likely organizational identification should affect OCB.

Hypothesis 2 – Organizational identification will have a positive relationship with military OCB.

Job satisfaction

Job satisfaction refers to an individual’s satisfaction with characteristics of the job such as supervision, working conditions, pay, promotion, and relationships with workers. Other research takes a more general approach, where characteristics are merely components of a general job satisfaction factor (Macdonald & Maclntyre, 1997). Multiple studies have identified a relationship between job satisfaction and OCB (Organ & Konovsky, 1989; Organ & Ryan, 1995). Jordan et al. (2007) found that job satisfaction was the strongest predictor of OCB among U.S. Air Force members. But other research has found that only intrinsic job satisfaction contributed to OCB (Chiu & Chen, 2005; Zeinabadi, 2010), and Geyskens et al. (1999) found that social and economic satisfaction are separate constructs with different relationships across situations. Given that some research has found that intrinsic job satisfaction effected OCB when the general construct did not, combined with the findings of Geyskens et al. (1999), this study separates social job satisfaction and economic job satisfaction constructs. Social job satisfaction is defined as a form of intrinsic job satisfaction where an individual has positive emotions regarding coworkers, supervisors, and other work-related relationships and social working conditions. Given that employees who are generally satisfied with their job are more likely to reciprocate with OCB and other positive behaviors (Zeinabadi, 2010) and the support for intrinsic social job satisfaction having a positive effect on OCB, it is likely that those who are satisfied with their supervisor, coworkers, and other work relationships will be more likely to enact OCB.

Hypothesis 3 – Social job satisfaction will have a positive relationship with military OCB.

Economic job satisfaction

Economic job satisfaction is happiness or fulfillment with pay and other economic job factors. There is substantial evidence that suggests economic job satisfaction has behavioral consequences. Organ and Konovsky (1989) found that pay satisfaction explained significant OCB variance and seemed to be related to fairness of pay (Moorman, 1991; Organ, 1988). Similarly, pay satisfaction among government workers on a fixed pay scale had positive significant impact on OCB (Farooq et al., 2017).

Hypothesis 4 – Economic satisfaction will have a positive relationship with military OCBs.

Enlistment motives

Enlistment motives reflect the reasons members give for joining the military. Woodruff (2017) found that two intrinsic enlistment motives and two economic motives were most influential in their effect on post-enlistment behaviors. The first intrinsic motive was a patriotic/altruistic service motive focused on serving one’s country and being part of a meaningful mission or team. The second intrinsic enlistment motive was self-enhancement and is related to developing as a person (e.g., improving one’s character or leadership) and reflects a belief that association with the organization will lead to actual or perceived improvement of character, maturity, or values associated with the organization (Woodruff, 2017).

There is ample reason to believe that these intrinsic military enlistment motives will promote OCB. First, Penner et al. (1997) suggested that OCB can be proactive, with people electing to engage in OCB to satisfy one or more motives. Second, motives will generally instill effort and persistence to execute behaviors that are perceived to support the motive. The more the behavior facilitates the motive, the more positively it will be evaluated and the more motivated the person will be to enact the behavior (Brendl & Higgins, 1996). The self-enhancement motive instills persistent effort by the service member to seek and volunteer for challenging new experiences perceived to be developmental. In the military, these experiences typically aligned with the needs of the organization and its mission (Woodruff, 2017). For example, a soldier with a self-enhancement motive related to being a better leader would be more likely to volunteer to lead important tasks and mission or seek out opportunities to exercise increased responsibility.

The patriotic/altruism enlistment motive should instill effort and persistence toward supporting the mission and team, creating a greater likelihood of enacting OCBs. The patriotic/altruistic service motive is also closely related to Rioux and Penner’s organizational concern and prosocial values (Rioux & Penner, 2001). Researchers have found that organizational concern and prosocial values (Rioux & Penner, 2001) and public service motives (Gould-Williams et al., 2013; Kim, 2006; Pandey et al., 2008) are important antecedents of OCB.

Hypotheses 5 and 6 – Self-enhancement and patriotic/altruistic enlistment and service motives will have a positive relationship with military OCB.

Economic enlistment motives are common among military members and reflect economic goals such as having a steady income and access to housing and health care. In the military context, members are paid at a standard rate and receive fixed benefits like on-base housing or a housing allowance and free health care. OCB in the American military do not directly contribute to economic outcomes (e.g., military members do not receive merit-based raises or bonuses). In the U.S. military, increased economic benefits come primarily from relatively fixed-term promotions, particularly in the first four years, and longevity-based pay raises that occur every two years. Individuals who join for economic motives generally find those economic outcomes are achieved by the act of enlistment and continuation in the service Woodruff, 2017). There is some potential economic benefit if individuals enacting OCB are selected for earlier promotion, but the promotion system significantly limits this effect. Looking outside the military, when there is a performance-pay link, members that had lower alignment with the organization’s values avoided engaging in OCB (Deckop et al., 1999). Because of the transactional nature of the economic motive, military members with this motive should be less likely to internalize military values (e.g., selfless service) and will be less likely to enact OCB.

A second economic enlistment motive is the desire to gain future employment after service in the military. The motive includes getting a better civilian job in the future and acquiring training for later employment. These motives are typically fulfilled by attending required military initial-entry and specialty schools and military experiences associated with knowledge and skills valued by the civilian job market. Behaviors associated with these motives tend to be nondiscretionary. Additionally, they tend to predispose the individual to exiting the military to use their acquired knowledge in skill in the civilian job market. While there is some alignment between acquiring job skills and OCBs, these behaviors more often compete with OCBs for the individual’s time and effort (Deckop et al., 1999). For example, imagine a soldier who wants to gain computer skills and exit the military to get a civilian job, that person will be reluctant to voluntarily pull guard shifts or sacrifice a civilian job opportunity to deploy for a humanitarian assistance mission.

OCB does not seem to contribute to the achievement of either economic motive in this context. This is important because behaviors that do not contribute to the motive have been shown to elicit negative evaluation (Shah et al., 2002). In this case, OCBs do not contribute to achieving an individual’s economic motives (pay, benefits, and future employment) and should create a negative evaluation. Additionally, if the member has a transactional economic motive, he or she may have a low relational orientation and avoid OCBs like sacrifice, participation, and providing positive word-of-mouth. Accordingly, I expect economic enlistment motives to have a modest negative association with OCB.

Hypothesis 7 – Extrinsic/economic enlistment and service motives will have a negative relationship with OCB.

Methods

Participants and procedure

The study used three samples from the United States Army: currently serving active duty soldiers, new soldiers in initial entry training, and future soldiers who enlisted and are awaiting their report dates for initial entry training. The primary sample was drawn from roughly 400,000 soldiers currently serving on active duty in the ranks of private to staff sergeant and having between six months and 15 years of service (Department of Defense, Statistical Information Analysis Division, 2011).

Current soldier data was collected by sampling operational organizations using a method similar to stratified cluster sampling and simple random sampling from across the Army. The use of multiple sources helps limit issues from single source, self-reported data (Podsakoff & Organ, 1986). Three Army units were selected, one deployed to combat, one unit just returned from deployment, and one unit that spent the previous year at its home station. The organizations included combat and non-combat subordinate units and soldiers. Response rates exceeded 50% and generated 481 usable surveys. Simple random sampling was used to send web-based survey links to soldiers using the Army’s e-mail system, resulting in 702 responses and a response rate that was at least 25%.

The new and future soldier samples were used to test the robustness of the findings from the current soldier sample and assess the validity of the Military OCB measures, antecedents, and their relationship across multiple lifecycle cohorts. The sample size for future soldiers was 781 with a response rate of 42% from a web-based survey. A total of 646 new soldiers completed hardcopy surveys with a 90% response rate. Table 1 includes the descriptive statistics for all three samples. Three smaller samples were used to pilot test the survey and are discussed in the scale and item development section of the paper. All institutional review board protocols were followed, and the subjects’ confidentiality was maintained at all times.

Table 1.

Cohort descriptive statistics.

	Future Soldiers	New Soldiers	Current Soldiers
Age	22 years	22 years	28 years
Average Affiliation	2 months	5 months	5.7 yrs of active duty
% Unmarried	84%	77%	62%
Race	Caucasian 69% African Amer. 10% Hispanic 13% Other 8%	Caucasian 59% African Amer. 19% Hispanic 14% Other 9%	Caucasian 62% African Amer. 15.5% Hispanic 12% Other 10.5%
% Male	82%	100% male basic training	86.5%
Education	High School 96.7% Some College 50%	High School 96.7% Some College 45%	High School 93.5% Some College 65.7%
Rank	NA	Four most junior ranks	Six most junior ranks
% Combat Specialty	50%	22%	43.5%
Combat Deployments	None	None	2 on average

Measures

Control variables

Time in service, age, education, rank, race, gender, marital status, number of children, and combat/non-combat job type, current combat deployment, and number of combat deployment variables were included as control variables. Acknowledging the current practice of limiting control variables (Becker, 2005), there is reasonable argument for the inclusion if these specific variables. The positive effect of relationships has been shown to plateau over time (Palmatier, 2008), and it is reasonable to expect that greater time in an organization may diminish the energy or desire to enact OCB. A study of OCB among corrections officers found that age and education level had a significant positive correlation with OCB (Lambert et al., 2008), while studies of OCB among educators found that seniority and tenure, which are analogous to rank in a military context, increased OCB (Chen & Chiu, 2009). Gender and race in the U.S. military are particularly salient within the military context. Less than a decade ago women were prohibited by law from serving in direct combat position or front-line combat organizations (Woodruff & Kelty, 2017) and African Americans are underrepresented in combat branches. Both of these have resulted in their underrepresentation in positions of leadership and central functions within the military, creating potential perception of inequity and injustice. This is important because there is evidence that perceptions of fairness, equity, and justice affect OCB (Fassina et al., 2008). Finally, the military and family are considered greedy institutions, with both making significant demands on its members’ time (Woodruff & Kelty, 2017). As such, it is possible that being married and having children could compete for the time and energy available to the individual to enact OCB. There is also a significant positive correlation with job type and OCB. Lambert et al. found that being a corrections officers (versus staff) in a corrections facility was associated with lower OCB (Lambert et al., 2008), which is somewhat analogous to combat and non-combat positions in the military. Current and cumulative deployment into harm’s way create significant stress for some military members, which is important because research has shown a relationship between increased stress and decreased OCB (Lambert et al. (2008); Bragger et al. (2005).

To control for the effects of combat deployment experience, both the current deployed status (deployed, not deployed) and the total number of combat deployments were also included as control variables. Time in service was measured as the number of years and months of service. Age was reported in years. Rank was measure using the soldiers’ pay grade (E1-E6). Respondents selected race from Asian/Pacific Islander, Black/African-American, Hispanic, Native American, White /Caucasian, and Other Race options. Educational level responses included non-high school graduate, high-school graduate, some college, four-year degree, some graduate school, and completed graduate school. Marital status was reported as married, single, divorced, and widowed/separated/other. Children were measured 0 – more than 6. Job type options were limited to combat arms and non-combat arms/support.

Military organizational citizenship behaviors

Based on a review of the extant OCB literature and analysis of the military context, the author, and a panel of experts identified OCBs that create substantial value for the military. In the next step, the panel removed behaviors that were not discretionary for soldiers, meaning the behaviors could be compulsory in a military context. The panel included a military sociologist with knowledge of the population and classical test theory, organizational behavior PhD students with education in research methodology and psychometrics, and several military officers having experience with the population and research methodology. Five OCBs were identified that create substantial value for the military and are discretionary for soldiers: sacrificing, positive word-of-mouth, retention, volunteerism, and use of readiness and welfare enhancing services.

Sacrificing measured the soldier’s willingness to take hazardous, disliked, or hardship inducing actions for the benefit of the organization or mission and used a new four-item scale (later reduced to three items). Positive word-of-mouth measures soldiers “talking up” the organization and providing positive information to other about the military in social environments, which is critical for attracting new talent to military and used items adapted from the Arnett et al. scale (Arnett et al., 2003). Retention measures the intention to reenlist and continue in the service beyond their current requirement and was measured using a highly reliable scale used by the Army to assess retention likelihood among soldiers. Volunteerism was measured using a five-item scale (later reduced to three items) to measure the soldier’s willingness to attend discretionary events that benefit the Army or their unit. Use of services was measured using a seven-item scale (later reduced to four items) designed to measure the use of Army provided services intended to increase soldier and family welfare and enhance deployment readiness.

All OCB and OCB antecedent scales, except word-of-mouth, asked the respondent to rate their level of agreement or disagreement with a statement on a seven-point Likert scale with values ranging from 1 (strongly disagree) to 7 (strongly agree). The word-of-mouth (WOM) scale used a balanced seven-point scale ranging from −3 to 3, with negative and positive statements anchoring the ends. See Appendix 1 for measurement scales and items.

All measures, except service-use and word-of-mouth promoting, assessed behavioral intentions. This decision was made in consultation with the military and research methods experts from the panel and two additional researchers with specialized expertise in psychometric measures. Asking the members “I would” instead of “ I do” was assessed as preferable because the behaviors can be infrequent (e.g., retention decisions/behavior) or context specific (e.g., sacrificing behaviors). In the case of retention, military members can only elect to remain or leave service at the end of each enlistment contract, yet the behavior could not be more important because the U.S. military cannot bring in mid-level or senior talent through lateral entry. Every leader or expert must be developed from the lowest level. Sacrificing behaviors are equally important, with the U.S military’s highest award (the Medal of Honor) recognizing sacrificing behavior, yet the behaviors are more frequently observed during combat or humanitarian deployments and other times of hardship. So, for example, a military member who is in his/her initial enlistment period or has not yet deployed to combat may be forced to “disagree” with the statement “I do” when in fact they strongly intend to do so given the opportunity. While necessary, this decision is not without drawbacks, and behavioral intentions do not always result in the actual behavior.

As a robustness test of the connection between intention and behavior, findings from the primary sample of current soldier were compared to new soldiers, who have just joined the military. Current soldiers were asked to agree-disagree with the statement “I use services … ” and new soldiers ask to agree-disagree with the statement “I will use services … .” The two sampled populations were compared using multigroup CFA, and both the service-use measurement model and the structural model (the relationship between the service-use construct and the antecedents) were invariant.

OCB antecedent variables

Soldiers’ identification with the Army (the focal organization) was measured using Mael and Ashforth’s (1992) six-item scale (reduced to four), which has demonstrated reliabilities ranging from .83 to .90 and has been successfully adapted for use with the U.S. Army.

Social job satisfaction was adapted from the Geyskens and Steenkamp (2000) scale and is the member’s evaluation the work relationships and personal contacts and interactions within or enabled by organizational membership. Economic job satisfaction scales for pay and future employment were also adapted from the Geyskens and Steenkamp (2000) scale and are defined as the member’s satisfaction with pay and future employment opportunities that result from their membership with the organization.

Enlistment motives were adapted from the Army’s enlistment motives (Baker, 1990). Reliabilities for these constructs have historically exceeded .80. Patriotic service/altruism is a common enlistment and service motive that reflects a desire to serve the organization (the Army) or its cause and contribute as a member of a team with a higher purpose. The self-enhancement enlistment and service motive reflect desire to develop as a person (e.g., improvement of character, maturity, and values) through association with the Army. It does not include acquiring new skills or training. Economic benefits enlistment/service motives reflect a desire for economic independence and a steady income. The future employment enlistment motive reflects a desire to acquire skills and experiences that will make the individual more marketable for employment outside the Army.

Scale and instrument development

Scale and item development process

Scale development used steps suggested by Netemeyer et al. (2003) and included defining the construct and its content domain, generating and judging measurement items, and studies to develop, refine, and finalize the scales. Construct definitions are consistent with previous studies and well grounded in theory, with all items adapted for the sampled population from existing scales demonstrating good psychometric properties. Additional items were generated to tap the full content domain and crafted to avoid the issues of universal endorsement, double barreled wording, and wording redundancy, which can inflate scale reliability. Initial scales included negatively worded items to limit response bias from acquiescence or yea-saying.

Items were assessed for content and face validity by a panel of expert judges consistent with recommendations by Netemeyer et al. (2003). The same expert panel discussed in the OCB selection process later completed a Q-sort to assess items for clarity and wording issues and were provided with the list of constructs and definitions and all proposed items. The panel then sorted the items by construct. Q-sort responses demonstrated very strong consistency, with over 90% agreement. The few problematic items were easily identified and removed or rewritten. Overall, the results of the Q-sort and expert feedback indicate strong content and face validity. A population panel of 30 soldiers (current, new, and future soldiers) also identified items that were ambiguous or confusing and were subsequently revised.

Survey instrument pretesting and factor analysis

The initial survey instrument was pilot tested, and the data split to conduct initial EFA and CFA analysis. The split samples included 124 current soldiers, 65 new soldiers, and 65 future soldiers. This is separate from the data discussed earlier in the Participants and Procedure section and later used in analysis of the measurement model and hypothesis testing. The first sample was analyzed using exploratory factor analysis (EFA) with both common factor and principal components analysis (PCA). EFA/PCA was used to assess the dimensionality of the scales and reduce the number of items without losing information. PCA, which maximizes variances in the items, was used for item reduction. Common factor analysis, which maximizes shared variance, was used for assessing dimensionality (Netemeyer et al., 2003). Both analyses provided largely consistent results. Oblique (PROMAX) rotation was used in all solutions.

The number of factors was assessed based on theory and a combination of Horn’s parallel analysis and scree test results. PCA results identify items that either failed to load to a factor at .500 or higher, cross-loaded above .300, or had difference between the primary and secondary loadings of less than .300. These were candidates for elimination. EFA analysis was conducted in three stages. First, items intended for a single construct were run to confirm that parallel and scree analysis suggest only one factor and ensure the items load at .500 or higher. In the second stage, items from the two most theoretically related constructs were analyzed together to ensure that parallel and scree analysis suggest two factors and identify items that fail to load as expected at .500 or higher or cross-loaded to the other factor above .300. Finally, all constructs were grouped together (OCBs, satisfactions, motives, and identification) to assess their dimensionality and identify poorly performing items.

Using a second sample from the same pilot study, items having acceptable performance during EFA/PCA were further evaluated with confirmatory factor analysis (CFA), which allows specifying items to load to specific constructs and assesses individual items, item loading (significance of parameters), standardized residuals, modification indices (which indicate cross-loading items or correlated error), and measurement model fit. Items were retained if they loaded significantly to the intended factor and did not have cross-loading modification indices larger than 3.84. CFA was completed on the related groups of constructs and their intended items (e.g., OCBs, satisfactions, identification, and motives). CFA confirmed the factor structure suggested by theory and EFA/PCA results, and convergence was never an issue and no offending estimates were observed. As is often the case, reverse coded items did not load as strongly as the positively worded items and only the best loading negatively worded items were retained for the final survey.

The survey data and respondent comments were reviewed for any remaining issues. The overall process enabled the number of items to be trimmed and resulted in 13 unidimensional factors with 3 to 5 items and reliabilities between .822 and .940. These included five OCBs, organizational identification, social job satisfaction, two economic job satisfaction factors, and four enlistment motive factors. Pretesting, combined with the performance of the subsequent measurement and structural models using the full sample, provided evidence for content, face, convergent, discriminant, nomological, and predictive validity. Items, scales, and reliabilities are reported in Appendix 1.

Measurement model and hypotheses testing

Analysis of the data was completed using structural equation modeling (AMOS 17.0) and the entire sample of current soldiers. Assessment of the individual factors and the overall measurement model was completed in three steps. First, factors were analyzed using CFA of a first-order factor model. Second, the model was adjusted to include three second-order factors and again tested using CFA. Third, multigroup CFA, using the three subpopulations (current, new, and future soldiers), tested for metric invariance in the first- and second-order measurement models. A similar approach was used with the structural equation model (SEM) used to assess antecedent hypotheses and better understand the effects of various factors on the first- and second-order OCBs.

Results

CFA of the first-order measurement model produced adequate fit indices, with a comparative fit index (CFI) of .937 and a root mean square error of approximation (RMSEA) of .049 (χ2 = 4093.051, df =1146). These fit indices meet the prevailing recommendations for RMSEA of .06 or less and are close to the CFI recommendation of .95 or greater (Hu & Bentler, 1999). All item loadings were significant with Z-scores varying from 62.6 to 23.1 and demonstrated convergence for all factors. Modification indices were small and indicated acceptable discriminant validity of the measures. Standardized residual covariances are also acceptable, with the largest standardized residual being 3.04 and only 13 residuals exceeding ± 1.96, indicating internally and externally consistent item-to-factor assignment (see Table 2).

Table 2.

Measurement model properties.

Construct -Indicators	Estimate	S.E.	Reliability	Construct -Indicators	Estimate	S.E.	Reliability
Patrt/Altru Motive Altru_1 Altru_2 Altru_3 Altru_4	1.00 1.178 1.203 1.204	.031 .033 .028	.937	Social Job Satisf. SatSoc1 SatSoc2 SatSoc3 SatSoc4 SatSoc5	1.00 .936 1.054 .862 .927	.034 .034 .031 .032	.858
Self-Enhanc Motiv Slf_Imp1 Slf_Imp2 Slf_Imp3 Slf_Imp4	1.00 1.125 1.058 1.002	.029 .028 .029	.933	Pay Job Satisf. SatEcn1 SatEcn2 SatEcn3	1.00 .853 .982	.030 .029	.851
Pay Motive Pay_1 Pay_2 Pay_3	1.00 .953 1.049	.026 .023	.919	Future Job Sat. SatEmp1 SatEmp2 SatEmp3 SatEmp4	1.00 1.049 1.081 1.075	.030 .032 .032	.885
Future Job Motive Job_1 Job_2 Job_3 Job_4	1.00 .855 .969 .918	.026 .023 .023	.940	Identification ID1 ID2 ID3 ID4	1.00 1.232 1.275 1.217	.047 .050 .053	.901
Retention Retent1 Retent2 Retent3	1.00 .890 1.007	.020 .015	.913
WOM WOM1 WOM2 WOM3 WOM4	1.00 .782 1.005 .826	.024 .027 .026	.912	Second-Order Factors
Service Use Serve1 Serve2 Serve3 Serve4	1.00 1.042 .812 .948	.028 .028 .033	.852	Military OCB Sacrifice Retention WOM Service Use Volunteering	1.120 1.395 1.148 .912 1.301	.046 .052 .047 .039 .044
Volunteering Part1 Part2 Part3	1.00 .927 1.096	.033 .028	.822	Economic Motv. Pay Motv. Futr. Job Mot.	.888 1.326	.037 .039
Sacrifice Sacrif1 Sacrif2 Sacrif3	1.00 .852 1.029	.030 .037	.862	Economic Sat. Pay Satisf. Futr. Job Sat.	.803 1.187	.054 .044

Three second-order factors (military OCB, economic motives, and economic job satisfaction) were created to enable better structural modeling and less conceptual complexity. The five OCBs are believed to reflect a more general behavioral orientation to enact Military OCBs. The creation of this factor also acknowledges that although each of these OCBs are distinct and demonstrate adequate convergent and discriminant validity, they are highly correlated and share common variance. A second-order economic motive factor was created using the first-order pay and future employment motive factors and a second-order economic job satisfaction factor was created using the pay and future employment satisfaction factors.

The second-order measurement model, which includes all first-order factors, produced adequate fit indices (CFI = .937, RMSEA = .049, χ2 = 3974.421, df = 1097) and all loadings were significant, with Z-scores for first-order loadings ranging from 67.6 to 23.0 and 33.7 to 14.9 for the second-order loadings. Few standardized residuals and their covariances exceeded ±1.96 and 4.0, respectively. Overall, the second-order measurement model provided acceptable fit and enabled the use of a more theoretically meaningful and comprehensible model. The model also confirms Hypothesis 1 that sacrificing, WOM, retention, volunteering, and service use create a second-order military OCB factor.²

The structural equation model used to assess antecedents of military OCB used a second-order military OCB factor (dependent variable), two second-order and four first-order antecedent factors, and control variables. The model produced good fit (CFI = .960, RMSEA = .059, χ2 = 550.834, df = 114) and confirms Hypotheses 2–5 and 7. The model supports the hypotheses that organizational identification, social and economic job satisfaction, and patriotic service/altruism motives have positive effects on military OCBs. Hypothesis 7 that economic enlistment/service motives have negative effects on military OCB was also confirmed. Hypothesis 6 that self-enhancement motives would have a positive effect on military OCB was unsupported. Standardized effects indicate that organizational identification (.388) and social job satisfaction (.342) have the largest positive effects on military OCB. Economic job satisfaction (.294) and patriotic/altruistic enlistment and service motives (.112) also have significant positive effects. Having an economic enlistment and service motive had a significant negative effect on military OCB (−.173) (See Table 3).

Table 3.

Estimates for military OCB antecedent model (SEM).

Model Fit: RMSEA .059, CFI .960	Estimate	S.E.	Significance P Value	Hypotheses Confirmed
Organizational Identification→ Military OCB	.357	.032	.001	Yes
Social Job Satisfaction → Military OCB	.392	.066	.001	Yes
Economic Job Satisfaction Motive→ Military OCB	.310	.092	.001	Yes
Patriotic/Altruism Motive→ Military OCB	.124	.036	.001	Yes
Self-Enhancement Motive→ Military OCB	−.037	.046	NS	No
Economic Motive→ Military OCB	−.185	.068	.01	Yes
Control Variables
Deployed→ Military OCB	−.151	.058	.009
Number of Deployments→ Military OCB	.015	.022	NS
Time in Service→ Military OCB	−.035	.010	.001
Combat Arms→ Military OCB	−.124	.062	.023
Age→ Military OCB	.021	.007	.002
Gender (being female)→ Military OCB	−.086	.082	NS
Marriage→ Military OCB	.063	.060	NS
Number Children→ Military OCB	.058	.026	.023
African American→ Military OCB	−.119	.078	NS
Other Race→ Military OCB	−.077	.088	NS

Deployment and demographic control variables also influenced military OCB. The most substantial (and negative) influence came from a soldier’s time in service, with more time in service reducing military OCB. Being currently deployed and having a combat arms specialty also reduced military OCB, while being older and having children increased military OCB. Other demographics, such as race, gender, or marital status did not influence military OCB.

The two additional samples were used to check for the robustness of the findings from the current soldier sample and confirmed that the measurement model and antecedent structural model functioned well with other lifecycle populations. Multigroup CFA and multigroup structural equation analysis was conducted using current, new, and future soldier samples. The measurement model demonstrated metric invariance across groups and the structural equation model/antecedent model had configural invariance and the hypotheses results were unchanged between groups. Both multigroup models (CFA and SEM) demonstrated adequate fit. This suggests that the construct measures, the structure of the antecedent model, and the estimates of the relationships are relatively robust across lifecycle samples within the Army/U.S. military context.

Discussion

While the study of OCB is well developed, the understanding and application of OCB in the military context has been limited. Those studies that examined OCB in the military context used prevailing measures of OCB and its antecedents (Gurbuz, 2009; Jordan et al., 2007) with minimal adaptation. These studies were essential to establishing the value of OCB in a military context and the importance of job satisfaction and organizational commitment as antecedents of OCB, but none developed OCB measures and OCB antecedents specific to the military context. This study extends the work by Gurbuz (2009) and Jordan et al. (2007) in several important ways. Foremost, it developed and validated the first military OCB measure using discretionary behaviors that have been shown to create significant value to most U.S. military organizations and addressed concerns that existing measures of OCB included compulsory behaviors and did not target the most valuable behaviors. A rigorous approach to developing and testing first- and second-order military OCB factors validated these measures across three U.S. Army populations. Additionally, the validated first-order OCB behaviors may be beneficial to other military studies. For example, the sacrificing or retention scales may be used in a variety of military studies.

Second, this study validated several OCB antecedents that have not been used in previous military OCB research. Specifically, it developed organizational identification, social and economic job satisfaction, and enlistment motives as antecedents of OCB, with the economic enlistment motive significantly inhibiting military OCB. These antecedent factors and their relationship with military OCB were validated across all three U.S. Army lifecycle samples.

Third, this study identified several influential control variables that have significant effects on military OCB. While military OCB does not seem to vary by gender, race, or marital status, being currently deployed to combat, being in the combat arms, and being in the Army for longer periods of time diminishes military OCB. One explanation for the negative effects of time in service is that relational growth models (e.g., growth in trust, commitment, gratitude) seem to plateau and then diminish overtime (Palmatier, 2008). Therefore, it would not be surprising to find that OCB also diminishes over time. Additionally, soldiers that are deployed or serving in combat arms specialties experience long periods in harsh conditions, long hours, and family separation and may feel stressed and believe they are already sacrificing, making them less inclined to enact military OCB.

While it is likely these factors will generalize to U.S. and western all-volunteer militaries, given their relevant similarities, its application to non-western militaries, particularly conscripted militaries, is an open empirical question. Future research should use these OCB measures and antecedents in other military organizations and contexts to establish their boundary conditions and generalizability. Future research should also assess if actual reenlistment or other retention behaviors and sacrificing behaviors have the same effect as behavioral expectations. This will likely require a study of soldiers with more time in service and more time deployed. Future qualitative research should seek to identify why deployed, combat arms, and longer serving soldiers are less willing to enact military OCB.

Appendix 1. Items, Scales, and Reliabilities

I will reenlist for another term in the Army I see myself remaining in the Army beyond this enlistment I plan to leave the Army after this enlistment -reverse coded										Retention Intention Reliability =  .913
I will attend optional events that support the Army or my unit I would like more opportunities to be involved in Army activities I would participate in voluntary events and activities that support my unit or the Army.										Volunteer Intention Reliability = .822
I would volunteer for a hazardous mission if it were essential to my unit or the Army I would willingly endure physical hardship if it were important to the Army or my unit. I would deploy to combat with my unit if given the option to remain back at my home duty station.										Sacrifice Intention Reliability = .862
The paired statements in each item represent the −3 and +3 points on this scale. Please select the point on the scales that best represents your actual behavior.										Word-of-Mouth Reliability = .912
−3	−2	−1		0		+1		+2			+3
I discourage my friends and relatives from joining the Army I will go out of my way to tell people about my criticisms of the Army When people ask my opinion, I tell them to not join the Army I speak poorly about the Army in social situations outside the organization							I encourage my friends and relatives to join the Army I will go out of my way to promote the Army to others I recommend the Army to those people who seek my advice I speak favorably about the Army in social situations outside the organization
The Army and Department of Defense (DoD) provides numerous services to its members. Examples include medical care, financial opportunities and assistance, recreational activities and equipment, fitness facilities and equipment, housing, educational assistance, childcare, youth programs, shopping, religious services, schools for children, and many forms of counseling (debt, marriage, substance abuse, depression, etc.). Please consider the services that fit your circumstance (to include services not listed) and answer the following questions using the 7-point agree-disagree scale used shown above. I use services provided by the Army even when civilian alternatives are available I check the availability of Army services before looking outside the community I take time to become familiar with the services offered by the Army If they are comparable in quality, I would prefer to use Army provided services									Service-Use Reliability = .852
When someone criticizes the Army, it feels like a personal insult Org. Identification
Being a Soldier is central to the person I amReliability =.901
I would feel a sense of loss if I were no longer a part of the Army
When someone praises the Army, it feels like a personal compliment
I am satisfied with the level of pay I receive As a member of the Army, I rarely worry about having enough money for myself or family The salary I receive from the Army is satisfactory					Economic Satisfaction: Pay Reliability =.851
I’m satisfied the Army is enhancing my future employability It’s comforting to know the Army is improving my civilian job prospects The Army is providing me with skills needed for a civilian job I’m pleased with the Army’s role in enabling me to earn greater income after the service					Economic Satisfaction: Future Employment Reliability =.885
The level of camaraderie with other soldiers is gratifying I like the people I meet through membership in the Army The Army enables me to associate with people I like to be around My relationships with other soldiers are satisfying The Army enables me to develop valuable relationships					Social Satisfaction Reliability =.858
I joined the Army because it enables me to … ” substituting the endings included below and using this 7-point scale.
Serve my country Defend our way of life Fulfill my patriotic duty Do my part to serve the nation					Patriotic/Altruism Motive Reliability =.937
Develop personal responsibility Build strong values Strengthen my character Become self-reliant					Self-Enhancement Motive Reliability =.933
Earn an income Provide financially for my myself or family Establish financial security					Pay Motive Reliability =.919
Get a better job in the future Acquire training for later employment Be more marketable after getting out Improve my subsequent employment opportunities					Future Employment Motive Reliability =.940

Funding Statement

The author received no financial support for the research, authorship, or publication of this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request: www.westpoint.edu/behavioral-sciences-and-leadership/profile/todd_woodruff

Disclosure statement

No potential conflict of interest was reported by the author(s).