Working Hard or Hardly Working? An Examination of Job Preservation Responses to Job Insecurity

Abstract

The question of how job insecurity affects workplace behaviors has been the source of debate in the academic literature as well as in the popular press. The current study leverages and expands ideas from the Conservation of Resources theory about resource investment to examine how and when job insecurity is associated with behaviors indicative of promotive or protective job preservation strategies aimed at social or task targets. We present two studies. The first study takes a longitudinal approach to examine the bidirectional relationships between job insecurity and job performance, counterproductive work behaviors, knowledge hiding, and self-presentation ingratiatory behavior. The second study examines job preservation motivation as a mechanism linking job insecurity to these work behaviors, and it considers specific elements of threats as moderators (i.e., perceived threat controllability, perceived threat proximity). Together these studies suggest that job insecurity is associated with strategic behavior when employees are facing proximal threats to their jobs; however, these efforts are rarely in the best interest of organizations.

Keywords

job insecurity job preservation job performance counterproductive work behavior knowledge hiding self-presentation ingratiatory behavior

Job insecurity (JI) concerns a perceived threat to the continuity of employment as it is currently experienced (Shoss, 2017). The number of people worried about their jobs has risen steadily since the 1970s, especially in the private sector (Hollister, 2011). There are concerns that JI has become a ubiquitous feature of the modern world of work, brought on by trends toward globalization and technological advancement as well as diminished labor power and weakened bonds between employer and employee (Hoffman, Shoss, & Wegman, 2020).

Although research has been fairly consistent in establishing JI as a harmful threat to worker well-being (De Witte, Pienaar, & De Cuyper, 2016), one of the field’s largest unanswered questions concerns how JI affects behavior on the job. Early explorations into JI portrayed employees as agentic actors who endeavor to avoid job loss by “working harder,” striving to “prove one’s indispensability to the organization,” “trying to improve one’s relationship with one’s superior,” or even competing with one’s colleagues (Klandermans, Van Vuuren, & Jacobson, 1991). Indeed, using an experimental manipulation, Probst, Stewart, Gruys, and Tierney (2007) demonstrated that JI led to greater effort and performance (see also Probst, 2002). Job-insecure employees also report efforts to portray themselves as the ideal employee and avoid absence (Hewlin, Kim, & Song, 2016; Miraglia & Johns, 2016). This evidence seems to suggest that JI may motivate employees to take action in an effort to secure their jobs (i.e., the job preservation perspective on JI; Shoss, 2017).

Yet, other studies reveal opposite patterns of results. For example, some report negative or nonsignificant relationships between JI and job performance (e.g., Huang, Niu, Lee, & Ashford, 2012; Selenko, Mäkikangas, & Stride, 2017). Research on the relationships between JI and other behavioral outcomes, such as counterproductive work behavior and impression management, have likewise yielded conflicting results (e.g., Huang, Wellman, Ashford, Lee, & Wang, 2016; Shoss, Brummel, Probst, & Jiang, 2020).

Several challenges contribute to this inconsistency. First, much of the research on JI and workplace behavior is cross-sectional. Therefore, the findings might reflect that one’s behavior is the reason for JI rather than the result of JI. Second, little is known about what types of strategies employees might pursue to try to secure their jobs. Third, the variability of findings may reflect variability in salient threat characteristics that serve to enhance or diminish motivation to enact behaviors to secure one’s job (i.e., job preservation motivation; Shoss, 2017).

The current research aims to address these challenges and, in doing so, provide rich theoretical and empirical insights into job preservation efforts as a potential response to JI. From a theoretical perspective, we leverage and extend ideas from the Conservation of Resources (COR) theory (Hobfoll, Halbesleben, Neveu, & Westman, 2018) about resource investment when facing threat. We build from Hobfoll et al. (2018) and Alicke and Sedikides (2009) to develop a 2 × 2 typology of job preservation behaviors that captures (a) promotive or protective strategies directed toward (b) task elements or social elements of the job. This typology suggests several potential job preservation behaviors, including four that we examine in the current research: job performance, refraining from counterproductive work behaviors, self-presentation ingratiatory behaviors, and evasive knowledge hiding. Together, these behaviors reflect ways that individuals could invest their energy/effort by promoting their value and contributions to the organization or by protecting themselves from inviting additional threats.

From an empirical standpoint, we present two studies. Our first utilizes three-wave longitudinal data to clarify the directionality of the relationships between JI and work behaviors, which is critical for understanding workplace behaviors as a response to JI. This first study sets the foundation for our second study, which develops and tests theory about job preservation. Using lagged, multiwave data, our second study examines (a) job preservation motivation as an explanation for the indirect effects of JI on behavior and (b) perceptions of threat controllability and threat proximity as potential moderators of the JI–job preservation motivation relationship. Together, these studies advance JI research by providing insights regarding (a) the directionality of JI–workplace behavior relationships, (b) the behaviors associated with job preservation motivation, and (c) the conditions under which individuals are more likely to be motivated to enact behaviors aimed at securing their jobs.

COR Theory and Job Preservation Responses to JI

COR theory (Hobfoll, 1989) is concerned with how individuals acquire, manage, and respond to resources, including those tied to conditions (e.g., employment) and energy (e.g., effort). Our study builds on a lesser-investigated element of COR theory, in particular, resource investment as a mechanism to protect against potential resource loss. While COR theory has been largely used in the management literature to study experienced resource loss (e.g., in the cases of workplace stressors or unemployment), our focus is on individual behavior in the face of threat of loss.

Hobfoll et al. (2018: 104) explained that “at its core, COR theory is a motivational theory that explains much of human behavior based on the evolutionary need to acquire and conserve resources for survival, which is central to human behavioral genetics.” COR theory argues that, because resources are crucial for survival, humans are highly sensitive to resource loss. For this reason, the threat of loss is also highly salient. While not all resources are equally important, a large body of literature speaks to employment as a particularly valuable resource (De Witte et al., 2016). Consistent with COR’s emphasis on potential loss that is perceived as a threat to one’s resources, we adopt the affective conceptualization of JI that captures the extent to which an individual is concerned or worried about potential job loss (Jiang & Lavaysse, 2018).

Under mundane circumstances, COR theory suggests that people will focus their efforts on acquiring valued resources. That is, individuals will invest resources (e.g., time, energy) in the hopes of obtaining further resources. A fundamental principle of COR theory (the third principle; Hobfoll et al., 2018) is that resource investment takes on importance in the face of loss or potential loss. Hobfoll et al. (2018: 107) argued that “the motivation to build a resource gain cycle will increase when losses occur and will have higher payoff under high stress conditions.” By extension, we anticipate that resource investment similarly takes on added importance where there is a threat of resource loss. This prediction aligns with COR theory’s second principle: resource investment is crucial for protecting against future resource loss. Hobfoll (1989: 519) suggested that individuals will make every available attempt to pursue a gain strategy in the face of potential loss of important resources, even “strategies that have a high cost and poor chance of success.” These arguments imply that people should be motivated to invest resources to protect against threats to stable employment, referred to as job preservation motivation in the JI literature (Shoss, 2017).

Targets and Strategies for Job Preservation

COR theory provides an important foundation for our research. The idea that individuals invest resources (e.g., time, energy) to counteract threats to resources suggests that JI should be associated with behaviors aimed at reducing threats. However, it is unclear what forms of behavior (i.e., resource investment) job preservation efforts may take. To address this question, we integrate reasoning from Hobfoll et al. (2018) and Alicke and Sedikides (2009) to suggest that potential job preservation strategies can be categorized by a 2 × 2 typology (Table 1) corresponding to direction (task vs. social) and strategy (promotion vs. protection).

Table 1
A Framework of Job Preservation Behaviors

Resource Investment Target

Job Preservation Strategy Task Oriented Social Oriented

Promotive Performance Self-presentation ingratiatory behaviors

Protective Avoiding counterproductive work behavior Evasive knowledge hiding

The first dimension of our typology concerns whether one’s efforts are primarily socially or task oriented. Hobfoll et al. (2018) argued that language and social bonding play an important role in resource investment. With regard to JI, efforts to portray one’s accomplishments and worth to one’s supervisor may therefore serve as a social strategy for reducing threats (Huang, Zhao, Niu, Ashford, & Lee, 2013). At the same time, research utilizing COR theory has pointed to nonsocially (i.e., task) directed resource investment in the workplace (Witt & Carlson, 2006). In this vein, efforts to enhance or maintain performance capture task-directed job preservation strategies (Shoss, 2017).

Whereas the social-versus-task dimension captures an important distinction in the target of job preservation behaviors, it is also worth differentiating the strategy underlying individuals’ job preservation attempts (the second dimension in our typology). Alicke and Sedikides (2009: 6) describe self-enhancement and self-protection as two core motivational strategies related to how individuals protect themselves against threat; specifically, “self-enhancement entails instrumental action designed to promote oneself and one’s prospects, whereas successful self-protective measures obviate falling below one’s standards.” Although the authors primarily focused on the consequences of these strategies for the self-concept, we suggest that the basic idea of promotive-versus-protective strategies is a useful one to examine how individuals approach the task of job preservation. Promotive approaches reflect attempts to actively demonstrate one’s worth to the organization. In contrast, protective approaches involve trying to refrain from behaviors that might invite threat.

Although several behaviors could fall in each category, we focus on four candidate workplace behaviors in the current research. We conceptualize directing effort toward job performance, defined as behaviors directly relevant to the organization’s goals (Campbell, McCloy, Oppler, & Sager, 1993), as a promotive job preservation strategy aimed at task-oriented resource investment. We view refraining from organizational counterproductive work behavior, defined as intentional misbehavior at work that has the potential to harm the organization (Bennett & Robinson, 2000), as a protective task-oriented resource investment strategy. Our rationale is that job-insecure individuals will want to refrain from engaging in behaviors that may invite additional threats, such as leaving early or stealing.

We examine self-presentation ingratiatory behaviors, defined as “a set of assertive tactics that are used by organizational members to gain the approbation of superiors” (Kumar & Beyerlein, 1991: 619), as a socially oriented promotive job preservation strategy. Ingratiation has been found to assist in gaining social capital and the favor of supervisors (Sibunruang, Garcia, & Tolentino, 2016). We focus on self-presentation ingratiation tactics because they emphasize the individual’s accomplishments and skills and thus may be used by job-insecure individuals to make a case that they are valuable to the organization and should be retained.

Finally, we examine evasive knowledge hiding, defined as providing colleagues with “incorrect information or a misleading promise of a complete answer in the future,” as a socially oriented protective job preservation strategy (Connelly, Zweig, Webster, & Trougakos, 2012: 76). Although viewed as desirable from the organization’s point of view, knowledge sharing could be seen as inviting threats from competitors in the workplace and threatening one’s role as an expert (Serenko & Bontis, 2016). We focus on evasive knowledge hiding because we view it as the dimension of knowledge hiding that best captures a socially oriented protective job preservation strategy. When engaging in evasive knowledge hiding, employees simultaneously protect themselves against threats due to loss of unique knowledge and try to avoid diminishing social bonds that they might need in the future.

As noted, research has yielded inconsistent findings about JI’s relationship with these outcomes, underscoring the need for research to better establish directionality as a necessary first step for understanding potential job preservation responses to JI. For example, in experimental work, Probst et al. (2007) found that JI positively affected productivity. However, other studies, including those with lagged or longitudinal designs, have reported negative (e.g., Probst, Gailey, Jiang, & Bohle, 2017) or nonsignificant (e.g., Selenko et al., 2017) relationships between JI and performance. A recent meta-analysis found a significant negative correlation in cross-sectional but not longitudinal research designs (Sverke, Låstad, Hellgren, Richter, & Näswall, 2019).

Likewise, research on the relationship between JI and counterproductive work behavior has revealed discrepant findings, with lagged studies reporting positive or nonsignificant relationships between JI and counterproductive work behavior (Huang et al., 2016; Shoss et al., 2020) and with cross-sectional studies reporting negative, positive, or nonsignificant relationships (Piccoli, De Witte, & Reisel, 2017; Probst et al., 2007; Reisel, Probst, Chia, Maloles, & König, 2010). Sverke and colleagues’ (2019) meta-analysis found significant positive associations across cross-sectional and longitudinal research designs; however, the small number of longitudinal studies limits this result.

Although JI research has not examined self-presentation ingratiatory behavior, some studies have focused on impression management behavior more generally. In cross-sectional research, the link between JI and impression management has been reported as both significantly positive (De Cuyper, Schreurs, Vander Elst, Baillien, & De Witte, 2014) and significantly negative (Kang, Gold, & Kim, 2012). Acknowledging contention in the literature and competing theoretical models, Probst, Lixin, and Bohle (2020) found support for a reverse causation model in which supervisor-focused impression management negatively predicted JI 1 month later.

Other researchers have anticipated a link between workplace knowledge behaviors and JI. One cross-sectional study suggested that JI promoted knowledge hiding (Serenko & Bontis, 2016) while another suggested that JI was associated with greater knowledge sharing (McKnight, Phillips, & Hardgrave, 2009). Another study found no significant association between JI and knowledge-sharing behaviors (Bartol, Liu, Zeng, & Wu, 2009). All in all, research into these relationships has been limited and equivocal.

Study 1

Given the inconsistency in the literature regarding the nature of relationships between JI and work behaviors, Study 1 utilizes a cross-lagged panel design with three waves of data collection to shed light on the directional relationship between JI and workplace behavior. Cross-lagged panel designs are advantageous because they model causal and reversed causal associations as well as autoregressive effects in a set of variables over time, thus allowing for insight into potential subsequent effects of each variable. This design is critical for overcoming methodological challenges in the JI literature (e.g., the predominance of cross-sectional designs) and provides an important foundation for understanding whether job preservation is a useful perspective through which to understand responses to JI. Based on theory articulated earlier suggesting that people should be motivated to invest resources (e.g., time, effort) to mitigate threats to their jobs, a job preservation perspective on JI would predict relationships between JI and subsequent workplace behaviors:
Hypotheses 1a-1d: JI is (a) positively associated with performance, (b) negatively associated with counterproductive work behaviors, (c) positively associated with self-presentation ingratiatory behaviors, and (d) positively associated with knowledge hiding.

In addition to being a useful methodological technique for understanding directionality, a cross-lagged approach provides insights into whether these behaviors truly serve a job preservation function in that they reduce subsequent JI. From a COR theory perspective, investment of time and energy resources should beget status resources such as stable employment (Spurk, Hirschi, & Dries, 2018). Although little research has examined workplace behavior as an antecedent to JI, poor performance and acts of counterproductive work behavior have been linked to involuntary turnover (Stumpf & Dawley, 1981). In fact, poor performance is inherent in definitions of involuntary turnover: “a termination reflects a bad hiring decision that must be corrected” (Shaw, Delery, Jenkins, & Gupta, 1998: 513). Other factors—such as relationships with superiors, accumulation of expert power, and a person’s experience and qualifications—may similarly relate to the likelihood of being fired, retained, or even promoted (Serenko & Bontis, 2016; Wayne, Liden, Kraimer, & Graf, 1999). Although subjective, employees’ perceptions of JI have been found to be partly reflective of their objective standings (De Cuyper & De Witte, 2007). Thus, we anticipated reversed directional effects:
Hypotheses 2a-2d: (a) Job performance, (b) self-presentation ingratiatory behavior, and (c) knowledge hiding are negatively associated with subsequent JI, whereas (d) counterproductive work behavior is positively associated with subsequent JI.

Study 1: Method

Participants and Procedure

We recruited 415 working adults in the United States from a variety of occupations and industries in spring 2018 through social media and newspaper ads. Participants were asked to complete three electronic surveys, distributed via email, each 3 months apart. Participants were compensated with gift cards of escalating amounts upon completion of each survey. After removal of participants who changed jobs in the Time 2 and/or Time 3 survey and those who completed surveys in <5 minutes,¹ 369 participants remained for the analyses. The 369 participants had an overall response rate of 96.5%, with 1,068 returned surveys out of 1,107 potential observations (369 participants × 3 waves). A logistic regression model revealed that none of the studied variables or demographic variables (gender, race, income, age) predicted attrition.

Participants had an average age of 32.57 years (SD = 5.42; range, 22-64) and came from 48 states across America. The sample was 67.21% male, 77.24% White, 9.21% Hispanic, and 8.94% African American. Participants were primarily well educated, with 75.61% earning a college degree or higher. Participants reported an average of 39.25 hours worked per week (SD = 5.10) and an average job tenure of 5.77 years (SD = 2.82). About half (50.14%) of participants reported a personal annual income <$60,000; 35.77% reported an income of $60,000 to $89,999; 11.38% reported an annual income >$89,999. As indicated by participant-provided ONET codes, management (16%), engineering (18%), sales (8%), and office and administrative support (8%) were the most common occupations. As compared with the U.S. workforce, our sample had comparable job tenure, hours worked per week, and minority ethnicity participants (Bureau of Labor Statistics, 2019). However, our participants were younger on average, and our sample had more males.

We obtained self-ratings for several deliberate purposes tied to the study’s aims. Employees are in the best position to report on their work effort, knowledge hiding, self-presentation ingratiatory behaviors, and counterproductive work behavior, as they are the ones enacting these behaviors. We were also concerned that job-insecure employees would feel uncomfortable asking supervisors or others to report on their work behavior and that others’ ratings would blur the different behaviors examined in our research (Choi, Miao, Oh, Berry, & Kim, 2019). Our use of self-ratings was buttressed by previous research demonstrating that self-ratings may have correlations closer to true score correlations (Conway & Lance, 2010).

Measures

Full-scale items are available in Appendix A in the online supplement.

JI.* We used Hellgren, Sverke, and Isaksson’s (1999) three-item quantitative JI scale. Items were rated from 1 (strongly disagree) to 5 (strongly agree; α = .88 T1, .84 T2, .84 T3).

Job performance. Self-rated job performance was measured by a five-item scale from Pearce and Porter (1986) and used by Ashford and Black (1996). The instructions asked participants to estimate how they rate relative to their coworkers on a 9-point Likert scale from 1 (10th percentile) to 9 (90th percentile). Pearce and Porter found that this measure correlated highly with supervisors’ ratings of performance, and Ashford and Black argued that the item wording and response scale are ideal for studies that include participants from multiple organizations (α = .87 T1, .82 T2, .77 T3).

Counterproductive work behavior. Organization-directed counterproductive work behavior was measured via a 12-item checklist from Bennett and Robinson (2000). Participants were asked to rate the extent to which they engaged in each behavior in the last 3 months on a 5-point Likert scale from 1 (never) to 5 (very often; α = .96 T1, .95 T2, .95 T3).

Self-presentation ingratiatory behavior. To measure self-presentation ingratiatory behavior, we used the four-item scale from Kumar and Beyerlein (1991). The scale asked participants to rate how frequently they interact with their supervisor in ways such as “Try to make sure he/she is aware of your successes.” We dropped the third item from this scale because it was associated with reduced reliability. Items were rated on a 5-point Likert-type scale from 1 (never do it) to 5 (almost always do it; α = .73 T1, .61 T2, .60 T3).

Knowledge hiding. We used Connelly and colleagues’ (2012) four-item evasive knowledge hiding scale. Items were rated on a 7-point Likert type scale from 1 (not at all) to 7 (to an extremely large extent; α = .89 T1, .87 T2, .90 T3).

Analytical Approach

Confirmatory factor analyses (CFAs) and latent cross-lagged panel models were conducted via Mplus Version 8 (Muthén & Muthén, 1998-2017). To account for missing data, we used full information maximum likelihood estimation, which has been shown to provide unbiased parameter estimates for longitudinal studies with missing time points (e.g., Enders & Bandalos, 2001). We used the following fit statistics as criteria: information criteria such as the Bayesian information criterion (BIC), chi-square difference tests, and model fit indices including the comparative fit index (CFI), the root mean square error of approximation (RMSEA), and the standardized root mean squared residual (SRMR). A satisfactory fit was indicated by relatively lower BIC and conventional cutoffs such as 0.90 for CFI, 0.06 for RMSEA, and 0.08 for SRMR (Bentler, 1990). CFA was used to establish the validity and temporal invariance for the measurement model. Using a full longitudinal panel design, the latent cross-lagged model with paths for causal and reversed effects was conducted to test bidirectional relationships between JI and workplace behaviors.

Study 1: Results

Table 2 displays the means, standard deviations, Cronbach’s alphas, and bivariate correlations.

Table 2
Means (SD) and Correlations Among Study 1 Variables

M (SD) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

1. Job insecurity 1 2.77 (1.21) (.88)

2. Job insecurity 2 2.47 (1.10) .63 (.84)

3. Job insecurity 3 2.76 (1.12) .54 .43 (.84)

4. Counterproductive work behavior 1 2.83 (1.08) .68 .60 .45 (.96)

5. Counterproductive work behavior 2 2.67 (1.00) .70 .62 .41 .80 (.95)

6. Counterproductive work behavior 3 2.50 (1.01) .78 .71 .57 .76 .83 (.95)

7. Knowledge hiding 1 4.42 (1.44) .43 .31 .36 .64 .54 .46 (.89)

8. Knowledge hiding 2 3.83 (1.4) .50 .45 .20 .66 .76 .57 .61 (.87)

9. Knowledge hiding 3 3.55 (1.51) .57 .56 .29 .70 .83 .74 .53 .84 (.90)

10. Self-presentation 1 3.54 (0.79) .38 .31 .39 .45 .35 .32 .55 .24 .22 (.73)

11. Self-presentation 2 3.37 (0.72) .24 .22 .35 .22 .22 .24 .32 .18** .12* .50 (.61)

12. Self-presentation 3 3.20 (0.69) .32 .19 .40 .14** .13* .33 .17 −.01 .09 .40 .36 (.60)

13. Performance 1 6.76 (1.15) −.43 −.28 −.37 −.43 −.45 −.54 −.37 −.31 −.40 −.19 −.14** −.14* (.87)

14. Performance 2 6.61 (1.12) −.40 −.21 −.26 −.44 −.49 −.47 −.39 −.41 −.46 −.16 −.20 −.10 .71 (.82)

15. Performance 3 6.76 (0.91) −.32 −.24 −.43 −.42 −.40 −.38 −.51 −.36 −.38 −.20 −.17 −.08 .66 .65** (.77)

Note: Diagonal values are Cronbach’s alphas.

*p < .05.

**p < .01.

CFA

CFA models with varying numbers of factors were used to examine the discriminant validity of our measures. Consistent with Meier and Spector (2013), who used the same organizational counterproductive work behavior scale (Bennett & Robinson, 2000) in cross-lagged panel models, we created four 3-item parcels as indicators for the construct of organizational counterproductive work behavior using the item-to-construct balance approach (Little, Cunningham, Shahar, & Widaman, 2002). Factors of all three times were correlated, and residuals of indicators for the same construct were correlated over time (Meier & Spector, 2013). Consistent with previous research (e.g., Meier & Spector, 2013), the residual covariances were retained in the subsequent analyses. Factor loadings were freely estimated. This model—a 15-factor model with JI, performance, counterproductive work behavior, evasive knowledge hiding, and self-presentation ingratiatory behavior at three times—was tested against three alternative models. As seen in Table 3, only the 15-factor model evidenced a satisfactory fit (CFI = .92, RMSEA = .051, SRMR = .055) and the lowest BIC among the three models. The 15-factor model fit statistically better than the three alternative models (p < .01).

Table 3
Fits of CFA Models With Different Numbers of Factors: Study 1

BIC χ² df CFI RMSEA SRMR

3-factor model 57,119.73 6,593.20 1,479 0.69 0.097 0.116

6-factor model 56,284.88 5,687.51 1,467 0.74 0.089 0.114

12-factor model 54,833.00 3,934.60 1,416 0.85 0.070 0.072

15-factor model

Free factor loadings 53,834.52 2,705.91 1,377 0.92 0.051 0.055

Longitudinal constraints on loadings 53,744.14 2,780.81 1,405 0.92 0.052 0.061

Note: The 15-factor model (job insecurity, performance, counterproductive work behavior, evasive knowledge hiding, and self-presentation ingratiatory behavior at three times) was tested against three alternative models. The first alternative model (three-factor model) placed all the indicators of each time into one factor, which ended up with three correlated factors (one for each time). The second alternative model (six-factor model) placed all the job insecurity indicators into one factor and all the performance-related outcome indicators into another factor, which ended up with six correlated factors (two for each time). The third alternative model (12-factor model) placed indicators of counterproductive work behavior and knowledge hiding into one factor, which ended up with 12 correlated factors (four for each time). BIC = Bayesian information criterion; CFA = confirmatory factor analysis; CFI = comparative fit index; RMSEA = root mean square error of approximation; SRMR = standardized root mean squared residual.

To examine the effect of common method variance, we conducted the common method factor technique (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). In particular, we added the common method factor to the 15-factor CFA model. All items were allowed to load onto an unmeasured common method factor; the path coefficients of the common method factor were constrained to be equal; and the variance of the common method factor was fixed at 1. The model with the common method factor had a larger chi-square and BIC, an equivalent CFI, and a larger RMSEA and SRMR (common method factor model: χ² [1,376] = 2,719.49, BIC = 53,854.00, CFI = .92, RMSEA = .052, SRMR = .063), and the factor loadings of items between the model with and without the common method factor did not change.²

Temporal Measurement Invariance

Based on the CFA results, measurement invariance of the 15-factor model over time was then examined by comparing the model with free loadings against the model with loadings of each indicator constrained to equality over time. If the constrained model does not fit worse than the unconstrained model, then metric invariance is empirically justified and indicates that the latent constructs maintain the same meanings across time (Schmitt & Kuljanin, 2008). Fit indices of the 15-factor model with longitudinal constraints on factor loadings across all three times are shown in Table 3 and were compared with those of the unconstrained model with free loadings. The chi-square difference test was significant between the unconstrained model and the model in which loadings were constrained to equality across all three times (Δχ² [28] = 74.90, p < .01). Previous research has argued against the heavy reliance on the significance of chi-square tests when comparing different models (Schmitt & Kuljanin, 2008); instead, CFI has been suggested as the best index for change in model fit and that a difference in CFI ≤.01 was considered the criterion to indicate invariance (Cheung & Rensvold, 2002). Chen (2007) suggested pairing the criterion of a .01 difference in CFI with differences in RMSEA of .015 and SRMR of .03 such that the null hypothesis of invariance would be rejected when differences in fit exceeded these criteria. As shown in Table 3, the parsimonious constrained model did not fit worse than the unconstrained model. Thus, metric invariance was suggested for the 15-factor model. Given this, we chose to move forward with the more parsimonious constrained model.

Structural Models and Tests of the Hypotheses

Latent cross-lagged panel models were then built to test for longitudinal bidirectional relationships between JI and work behaviors. Autoregressive paths were included to control for baseline levels for each factor. Since reversed causality should be considered within full longitudinal panel designs (Zapf, Dormann, & Frese, 1996), causal effects and potential reversed effects were tested simultaneously in the bidirectional model. In line with previous research (e.g., Meier & Spector, 2013), to test a more parsimonious and conservative model, we constrained the path coefficients (autoregressive and cross-lagged coefficients) to be equal across all time points. Synchronous correlations were specified between constructs measured at the same time point. This latent cross-lagged panel model had a reasonable fit (χ² [1,439] = 3,148.15, BIC = 53,910.79, CFI = .90, RMSEA = .057, SRMR = .072). Estimates of path coefficients are presented in Figure 1.

Figure 1
Unstandardized Path Coefficients of the Latent Cross-Lagged Panel Model of Study 1

Most of the cross-lagged paths of causal effects and reversed effects were significant, except for the bidirectional relationships between job performance and JI. The lagged relationships between JI and subsequent self-presentation ingratiatory behavior (b = 0.09, SE = 0.03, p < .01) and knowledge hiding (b = 0.40, SE = 0.05, p < .01) were significant, supporting Hypotheses 1c and 1d. JI was positively associated with subsequent counterproductive work behavior (b = 0.39, SE = 0.03, p < .01), counter to our prediction in Hypothesis 1b. Regarding the reversed effects described in Hypothesis 2, knowledge-hiding behavior was negatively related to subsequent JI (b = −0.19, SE = 0.04, p < .01), while counterproductive work behavior was positively related to subsequent JI (b = 0.47, SE = 0.07, p < .01). This supports Hypotheses 2c and 2d. Although self-presentation ingratiatory behavior also predicted subsequent JI, this relationship was positive (b = 0.36, SE = 0.09, p < .01), counter to Hypothesis 2b.

Study 1: Discussion

Our findings suggest that JI is positively associated with subsequent organization-directed counterproductive work behaviors, evasive knowledge hiding, and self-presentation ingratiatory behaviors but no change in job performance. Examining these findings in conjunction with our 2 × 2 typology of job preservation behaviors suggests that JI may lead individuals to focus on more socially oriented resource investment strategies as indicated by self-presentation ingratiatory behavior and evasive knowledge hiding. In turn, evasive knowledge hiding serves as a successful strategy to reduce subsequent JI. This echoes one knowledge worker’s comments in a popular press report: “One of the most valuable things I learned was to give the appearance of being courteous while withholding just enough information from colleagues to ensure they didn’t get ahead of me” (Maier, 2016, para. 4). The findings of a nonsignificant relationship between JI and subsequent performance and a positive relationship between JI and organizational counterproductive work behaviors, however, raise questions about whether employees, on average, tend to put forth effort for job performance and refrain from counterproductive work behavior as potential job preservation strategies.

Study 2

In our second study, we seek to clarify these findings by examining (a) the indirect effect of JI on work behaviors through job preservation motivation, as well as (b) the potential moderating factors tied to the perceived nature of the JI threat. As noted, COR theory’s ideas about resource investment suggest that feeling that one’s job is in jeopardy motivates individuals to try to avoid loss by enacting specific behavioral strategies. Although this may be implied by patterns of relationships, such as the positive directional relationship between JI and subsequent self-presentation ingratiatory behavior found earlier, examining the indirect effects of job preservation motivation provides a more direct test of this idea.

Additionally, there may be reason to anticipate that perceptions of threat characteristics may influence the JI–job preservation motivation relationship, thereby shaping the indirect effects of JI on work behaviors. Building on the ideas that energy and effort can be depleted over time, Hagger (2015) recently drew from models of self-regulation (e.g., Muraven, Shmueli, & Burkley, 2006) to offer a useful expansion of COR theory that addresses when individuals would be motivated to invest effort and energy to counteract threats. Hagger suggested that individuals’ investment of time and energy will be shaped by (a) the extent to which they believe that investment can be useful, as well as (b) the time frame by which they anticipate needing to mobilize and expend resources. Thus, Hagger conceptualized individuals’ investment of resources as a strategic decision made with respect to the specific situation at hand.

Perceived threat controllability, reflecting “individuals’ appraisals regarding the degree to which a given threat can be counteracted—in other words, whether there are ways to keep the threat of loss from translating into actual loss” (Shoss, 2017: 1937), aligns with Hagger’s (2015: 91) idea that people will be more motivated to invest resources when they view this investment as potentially worthwhile. Hagger argued that “individuals are less likely to part more with their ‘limited’ or ‘precious’ resources when there is little justification to do so and may, therefore, opt to conserve them thereby leading to reduced capacity.” Thus, to the extent to which employees believe that threats can be counteracted by their own behavior, they should have greater motivation for investing their time and energy into potential job preservation efforts (Ouwehand, de Ridder, & Bensing, 2008).

Threat proximity captures employees’ anticipation of when threats might come to fruition. Some threats to job security may reflect acute threats that will occur imminently (e.g., impending organizational restructuring, warnings from one’s supervisor) and would be anticipated to motivate a more immediate response (Fried et al., 2003). Other threats, such as concern about eventual job loss due to automation, may occur more distally. Immediate threats garner more attention and more immediate motivation to resolve (Hagger, 2015).

Past research found indirect evidence in support of these ideas (see Shoss, 2017), although the studies did not necessarily allow for disentangling the impact of perceived controllability and proximity. For instance, Probst and colleagues’ (2007; Probst, 2002) laboratory research found that performance increased among those in the layoff threat experimental condition who were told that “layoffs will be determined based on your overall work in the next work period.” The threats in these experiments can be viewed as controllable and imminent. Similar findings have been reported in studies of professional athletes and CEOs, who perform better by some metrics during the last year of their contracts (Liu & Xuan, 2020; White & Sheldon, 2014). Outside of the JI literature, research on goal threat has found that perceptions of threat controllability and proximity are associated with greater motivation to reduce the threat (Ouwehand et al., 2008). Thus, we hypothesized the following:
Hypotheses 3a-3d: The indirect effects of JI on (a) performance, (b) refraining from counterproductive work behavior, (c) self-presentation ingratiatory behaviors, and (d) knowledge hiding through job preservation motivation are stronger under conditions of higher perceived threat controllability.

Hypotheses 4a-4d: The indirect effects of JI on (a) performance, (b) refraining from counterproductive work behavior, (c) self-presentation ingratiatory behaviors, and (d) knowledge hiding through job preservation motivation are stronger under conditions of higher perceived threat proximity.

Study 2: Method

In fall 2020, we recruited participants using the Prolific Academic platform. Recruitment criteria were that participants had to be 18 years of age, currently reside in the United States, have a minimum approval rate of 94% on Prolific, have a supervisor at work, interact regularly with coworkers, and currently work full-time. Participants were asked to complete three online surveys, spaced 1 month apart, such that Time 3 occurred 2 months after Time 1. An overall 398 participants were invited. Participants were paid at the Prolific rate recommendation of $9.64 per hour. After invalid responses were dropped (mostly blank surveys, failing multiple attention checks), 319 individuals were recruited for the three-wave study, and response rates for the subsequent two waves were 81% and 87.5%, respectively. Those who reported that they had significant job changes (became unemployed, switched employers, etc.) during the study were removed (n = 17), as were those who completed surveys in <5 minutes (n = 6). This resulted in a final sample size of 296. A logistic regression model revealed that none of the focal variables or demographic variables (gender, race, income, age) predicted attrition.

Participants averaged 33.0 years of age (SD = 8.3; range, 18-60). They worked in a variety of industries, including professional/scientific/technical services (18.24%), education (14.53%), and health care or social assistance (12.50%). The majority identified as White (71.62%); 44.59% were female. Participants worked an average of 41.91 hours per week (SD = 8.94), and the average job tenure was 10.07 years (SD = 5.20). Roughly half (48.31%) reported a personal annual income <$60,000. When compared with the U.S. workforce, our sample had comparable hours worked, women, and minority ethnicity participants (Bureau of Labor Statistics, 2019). However, our sample was younger on average and had longer job tenure.

Measures

Similar to Study 1, participants completed self-report measures related to their current employment situations and feelings of JI. We measured JI and the moderators at Time 1, job preservation motivation at Time 2, and workplace behaviors at Time 3. The same scales used in Study 1 were used to measure counterproductive work behavior (α = .83), self-presentation ingratiatory behavior (all four items were included, α = .87), and knowledge hiding (α = .92). All scale items are in Appendix A, and additional validation for the job preservation motivation and threat proximity scales is in Appendix B, available in the online supplement.

JI. We adapted Hellgren and colleagues’ (1999) scale to reduce potential overlap between JI and threat proximity by removing temporal indicators from two items (e.g., “I feel uneasy about losing my job”; α = .87).

Job performance. We used the three-item individual task proficiency measure from Griffin et al. (2007). Items were rated on a scale from 1 (very little) to 5 (a great deal) (α = .91).

Threat controllability. We utilized a three-item scale adapted from Peacock and Wong (1990); a sample item reads “The future of your job security is under your control.” Items were rated on a scale from 1 (strongly disagree) to 5 (strongly agree) (α = .94).

Threat proximity. We developed four items to capture participants’ perceptions regarding the proximity of threats to their employment. The prompt reads “I see threats to my job as happening . . . ,” and participants responded using a 1-5 scale with the ends labeled “in the distant future . . . in the near future,” “far away . . . soon,” “a long way off . . . any day now,” and “in the long term . . . in the short term” (α = .96).

Job preservation motivation. We utilized Barrick, Stewart, and Piotrowski’s (2002) measure of intensity and persistence work motivation as a foundation for creating our job preservation motivation scale. As the outcomes of JI in our model are behavioral (e.g., performance) rather than cognitive or emotional, we deemed the intensity and persistence items most relevant as opposed to attention or arousal. We created five items that adapt Barrick and colleagues’ items with a focus on motivation to avoid job loss. A sample item is “I put a lot of effort into keeping my job.” Responses were provided on a scale from 1 (strongly disagree) to 5 (strongly agree) (α = .90).

Open-ended question. The Time 3 survey included an open-ended question about individuals’ strategies for job preservation. We randomized two item wordings to be sure that the wording would not bias toward promotive or protective strategies: “We are curious about how people respond when they are worried about losing their jobs (being able to keep their jobs). If you’ve been in this situation, please describe the things you’ve done to try to avoid losing your job (keep your job).”

Analytical Approach

To test Hypotheses 3 and 4, we modeled the focal variables as latent variables in a mediation model and included perceived threat controllability and threat proximity as the first-stage latent moderators. Because there might be other mechanisms linking JI to our outcomes (e.g., stress, social exchange; Staufenbiel & König, 2010), we model an indirect effect through job preservation motivation and a direct link from JI to our outcomes. To test the moderation effects, we used the XWITH command in Mplus to create latent interaction terms. Because case-based bootstrapping is unavailable in Mplus for models with latent interactions, Monte Carlo bootstrapped confidence intervals with 10,000 repetitions were used to assess the conditional indirect effects and + 1/−1 standard deviation of the moderator (Preacher & Selig, 2012).

Study 2: Results

Table 4 displays the means, standard deviations, Cronbach’s alphas, and bivariate correlations.

Table 4
Means (SD) and Correlations Among Study 2 Variables

M (SD) 1 2 3 4 5 6 7 8

1. Job insecurity 2.42 (1.18) (.87)

2. Job preservation motivation 4.05 (0.83) .09 (.90)

3. Counterproductive work behavior 1.47 (0.42) .12 −.37 (.83)

4. Knowledge hiding 1.56 (1.04) .12 −.05 .29 (.92)

5. Self-presentation 2.42 (0.88) .01 .13* .11 .29** (.87)

6. Performance 4.37 (0.75) −.14* .32 −.35 −.33 −.01 (.91)

7. Threat controllability 3.34 (1.23) −.28 .08 −.05 .00 .10 .06 (.94)

8. Threat proximity 1.91 (1.04) .64** −.03 .15* .21 .04 −.22 −.38** (.96)

Note: Diagonal values are Cronbach’s alphas.

*p < .05.

**p < .01.

CFA

CFA models were used to confirm construct distinctiveness. As in Study 1, items were used as indicators for all corresponding constructs except for counterproductive work behavior, which used four 3-item parcels as indicators. The anticipated eight-factor model—JI, job preservation motivation, counterproductive work behavior, self-presentation ingratiatory behavior, knowledge hiding, job performance, perceived threat controllability, and threat proximity—was tested against four alternative models. As seen in Table 5, only the eight-factor model showed a satisfactory fit (χ² [377] = 706.17, CFI = .95, RMSEA = .054, SRMR = .048) and the lowest BIC. The eight-factor model fit better than the four alternative models (p < .01).

Table 5
Fits of CFA Models With Different Numbers of Factors: Study 2

BIC χ² df CFI RMSEA SRMR

5-factor model 18,586.13 2,117.39 395 0.73 0.121 0.128

6-factor model 18,185.23 1,688.04 390 0.80 0.106 0.083

7-factor model I 17,966.25 1,434.92 384 0.84 0.096 0.077

7-factor model II 17,678.10 1,146.77 384 0.88 0.082 0.092

8-factor model 17,277.34 706.17 377 0.95 0.054 0.048

Note: The eight-factor model (job insecurity, job preservation motivation, counterproductive work behavior, self-presentation ingratiatory behavior, knowledge hiding, job performance, perceived threat controllability, and threat proximity) was tested against four alternative models. The first alternative model (five-factor model) combined the four outcomes into one factor. The second alternative model (six-factor model) combined threat controllability, threat proximity, and job insecurity indicators into one factor. The third alternative model (seven-factor model I) combined threat controllability and threat proximity into one factor. The fourth alternative model (seven-factor model II) combined counterproductive work behavior and knowledge hiding into one factor. BIC = Bayesian information criterion; CFA = confirmatory factor analysis; CFI = comparative fit index; RMSEA = root mean square error of approximation; SRMR = standardized root mean squared residual.

To examine the common method variance, similar to Study 1, we added the common method factor to the eight-factor CFA model and evaluated the change in model fit. The model with the common method factor had a larger BIC and equivalent CFI, RMSEA, and SRMR (χ² [376] = 705.94, BIC = 17,282.80, CFI = .95, RMSEA = .054, SRMR = .048). The factor loadings of items between the models with and without the common method factor did not change.³

Tests of the Hypotheses

The results of the latent moderated mediation model are shown in Table 6. Threat proximity was a significant moderator (interaction = 0.25, SE = 0.08, p < .01) on the relationship between JI and subsequent job preservation motivation, whereas perceived threat controllability was not a significant moderator (interaction = 0.03, SE = 0.07). Simple slopes analyses (Figure 2) showed that JI was more positively associated with job preservation motivation under conditions of high threat proximity (b = 0.42, SE = 0.14, p < .01) as compared with low threat proximity (b = −0.08, SE = 0.13; Figure 2).

Figure 2
Moderating Effect of Perceived Threat Proximity on the Relationship Between JI and Subsequent Job Preservation Motivation: Study 2

Table 6
Unstandardized Path Coefficients (SE) of the Latent Moderated Mediation Model of Study 2

Job Preservation Motivation Job Performance CWB Self-Presentation Knowledge Hiding

Job preservation motivation 0.41 (0.08) −0.49 (0.08) 0.16 (0.07)* −0.10 (0.07)

JI 0.17 (0.10) −0.22 (0.08) 0.22 (0.08) −0.01 (0.07) 0.15 (0.07)*

Threat proximity −0.29 (0.12)*

JI × Proximity 0.25 (0.08)**

Control 0.01 (0.07)

JI × Control 0.03 (0.07)

Indirect effect at low proximity −0.03 [−0.14, 0.08] 0.04 [−0.08, 0.17] −0.01 [−0.07, 0.03] 0.01 [−0.02, 0.05]

Indirect effect at high proximity 0.18* [0.06, 0.31] −0.21* [−0.37, −0.07] 0.07* [0.01, 0.15] −0.04 [−0.12, 0.02]

Note: The 95% Monte Carlo bootstrapped confidence intervals for conditional indirect effects are in square brackets. CWB = counterproductive work behavior; JI = job insecurity. Significant indirect effect based on 95% CIs excluding zero is marked with an asterisk.

*p < .05.

**p < .01.

For the conditional indirect effects, supporting Hypothesis 4a, the indirect effect of JI on job performance through job preservation motivation was significant and positive at high threat proximity (ab = 0.18, 95% CI [0.06, 0.31]); this indirect effect was nonsignificant at low threat proximity (ab = −0.03, 95% CI [−0.14, 0.08]). The indirect effect of JI on counterproductive work behavior through job preservation motivation was significant and negative at high threat proximity (ab = −0.21, 95% CI [−0.37, −0.07]) and nonsignificant at low threat proximity (ab = 0.04, 95% CI [−0.08, 0.17]), supporting Hypothesis 4b. The indirect effect of JI on self-presentation ingratiatory behaviors through job preservation motivation was significant and positive at high threat proximity (ab = 0.07, 95% CI [0.01, 0.15]) and nonsignificant at low threat proximity (ab = −0.01, 95% CI [−0.07, 0.03]), supporting Hypothesis 4c. Additionally, we found a negative direct effect from JI to performance (b = −0.22, SE = 0.08, p < .01) and positive direct effects from JI to knowledge hiding (b = 0.15, SE = 0.07, p < .05) and counterproductive work behavior (b = 0.22, SE = 0.08, p < .01).

Open-Ended Responses

We examined our open-ended responses to provide greater insight into workers’ job preservation strategies. A total of 233 participants provided a response to the item. Responses were coded with the themes of preservation strategy type (protective, promotive) and resource investment target (task oriented, social oriented) from our 2 × 2 typology in Table 1. Each response was first independently rated by the third and fourth authors. Raters were permitted to select multiple codes per response. Initial interrater agreement was 95%. Disagreements were discussed and consensus was met on all responses. We found that all four of our quadrants were reflected in participants’ answers (see Table 7). Approximately 84% of all substantive responses referenced at least one of the four categories. There was no discernable pattern in codes or content between the phrasings of the question.

Table 7
Sample Open-Response Descriptions of Job Preservation Behaviors as Matched to the Framework of Job Preservation Strategies and Targets

Job Preservation Strategy Resource Investment Target

Task Oriented Social Oriented

Promotive “I started working extra hard to prove my job was important to keep. I worked overtime and at nights to show that I was hardworking and dedicated.”“I have taken on new tasks to help management and the front desk, so I am trying to . . . increase my worth.”“Make an extra effort so that [my] work product is as good as possible, with no errors. Accept extra work if asked.” “Lately, I've been communicating weekly with my boss to keep him informed on what I've been accomplishing and make sure he knows about all the areas where I'm contributing.”“I just try to make sure that my manager likes me and go above and beyond to try to show my worth.”“Promoting oneself modestly is a key part of protecting my job.”

Protective “I focus on the things that I can control, like showing up to work on time. Getting my work done. Not creating drama in the workplace. etc.”“Always ensuring I was on time, never took long lunches and tried my best to clock out on time to avoid overtime if possible.”“I’ve tried to put my head down and work. I tried to become a ghost and just not draw attention to myself.” “There are definitely some processes that only I know how to do. . . . If I were to leave these processes would not get done.”“They would have trouble replacing me in the short term because not many others have learned how to perform my role yet.”“I have made sure I have a set of skills that is hard to replace at my work. I am one of the few that knows all our systems. I learned early on pay and job security is not based on how hard your [sic] work but on how hard it is to replace you.”

Study 2: Discussion

As anticipated, JI was associated with job preservation motivation under the condition of more proximal threats; in turn, job preservation motivation positively predicted performance and self-presentation ingratiatory behavior and negatively predicted counterproductive work behavior. These findings are in line with our hypotheses that job-insecure employees, under certain conditions, would be motivated to act in a manner to try to preserve their jobs and that this motivation would be associated with promotive and protective social- and task-oriented behaviors. This idea is bolstered by qualitative responses that illustrate these strategies and demonstrate job preservation as a useful way to understand how people respond to feelings of JI. However, opposing direct effects for performance and counterproductive work behavior suggest that these particular strategies may be difficult to enact at higher levels of JI, helping to explain the overall pattern of relationships found in Study 1 as well as inconsistencies in the literature.

General Discussion

The question of whether JI motivates employees to try to secure their jobs has perplexed researchers for decades. Our research addresses (a) the directionality of JI–workplace behavior relationships, (b) the specific strategies that employees may pursue, (c) the conditions under which JI is associated with job preservation motivation, and (d) how these efforts feedback to shape JI.

Contributions to Research and Theory

Our findings are generally in line with the idea that individuals are motivated to direct energy and effort toward trying to counteract threats to their jobs, particularly when faced with proximal threats. Study 1 establishes a link between JI and socially oriented resource investment strategies as indicated by self-presentation ingratiatory behavior and evasive knowledge hiding. Study 2’s findings suggest that people may use social- and task-oriented strategies when facing highly proximal threats. However, the findings of a negative direct effect of JI on job performance and a positive direct effect of JI on counterproductive work behavior may help explain why Study 1 found a null overall relationship between JI and subsequent performance and a positive relationship between JI and subsequent counterproductive work behavior. Although individuals may be motivated to perform well and refrain from counterproductive work behavior, doing so appears to be difficult under higher JI. These results provide interesting insights into JI as a threat of future loss: individuals are motivated to counteract this threat and mobilize effort and energy to do so, but at the same time, the experience of JI makes certain expenditures potentially more difficult—specifically, the task-oriented strategies of performance and refraining from misbehavior.

In doing so, these findings advance and clarify JI research. Our longitudinal findings are consistent with past findings of null relationships between JI and performance (e.g., Selenko et al., 2017), but they suggest that such findings do not mean that job performance is not a relevant outcome of JI. Rather, the relationship is nuanced, reflecting both threat conditions that may encourage job preservation motivation and, at the same time, potential countervailing effects. In this sense, our Study 2 finding of a positive indirect effect of JI on performance under conditions of higher threat proximity echoes Probst and colleagues’ (2007) experimental findings: under more proximal threat conditions, JI is associated with motivation to preserve one’s job, which in turn is positively associated with performance and negatively associated with counterproductive work behavior. This pattern of findings is consistent with other research as well; for instance, research finds that pregnant women worried about job threat (a proximal threat) try to exceed performance expectations (Gatrell, 2011). Surprisingly, Study 1 did not reveal the anticipated reversed relationship between performance and JI, which we thought would help explain the negative relationship found in many cross-sectional studies (Sverke et al., 2019). Perhaps one’s past performance does little to assuage concerns about potential job loss. Alternatively, the negative direct effect of JI on performance that we observed in Study 2 and/or any negative reversed effects that exist may be stronger in the more immediate time frames captured by cross-sectional research. Future research is needed to examine this further.

Regarding counterproductive work behaviors, Study 1’s results indicate a negative spiral wherein people respond to JI with counterproductive work behavior that in turn makes them more worried about their jobs. These findings help explain recent meta-analytic findings by Sverke et al. (2019) of a positive JI–counterproductive work behavior relationship. The reversed relationship is also consistent with the turnover literature’s finding that misbehavior can put employees’ jobs at risk (e.g., Spurk et al., 2018). That said, as Study 2 showed, this relationship is muted when people perceive more proximal threats, suggesting that at least some effort might be made to refrain from these behaviors depending on the circumstance.

Our research sheds light on socially oriented job preservation strategies, which have been the focus of less JI research. We found positive relationships between JI and self-presentation ingratiatory behavior in Studies 1 and 2, echoing findings from Huang et al. (2013). These findings provide strong support for socially oriented promotive strategies as a behavioral response to JI. Surprisingly, self-presentation ingratiatory behavior was positively associated with subsequent JI. It may be that higher self-presentation behaviors ingratiatory inadvertently make individuals feel that there is a spotlight on their performance. The resulting pressure to maintain their advertised achievements and skills may then increase JI. Although this finding runs counter to Probst and colleagues’ (2020) conclusions, their measure of impression management could be viewed as being more akin to supervisor-directed citizenship than self-presentation.

Study 1 found that JI was positively associated with subsequent evasive knowledge hiding. In turn, knowledge hiding was negatively associated with subsequent JI, suggesting that this strategy is successful at reducing JI. This pattern of longitudinal relationships (positive directional, negative reversed) helps to explain equivocal findings in cross-sectional research, which capture directed and reversed relationships simultaneously (e.g., Bartol et al., 2009; Serenko & Bontis, 2016). That said, we did not find the expected indirect effects in Study 2. The reason may be that Study 2 took place during the COVID-19 crisis where decisions about how organizations handle nearly every aspect of their business (e.g., operations, marketing, safety) were rapidly changing and many workers had transitioned to remote work, where there was less opportunity to interact with others. This may have limited opportunities for knowledge hiding or, in some cases, made it such that hiding knowledge could actually threaten one’s job by making one look incompetent or unhelpful in an organizational crisis situation. Indeed, the mean for knowledge hiding was much lower in Study 2 than in Study 1. However, the open-ended findings in Table 7 echo the idea that people view having unique knowledge as a valuable strategy for attaining job security. We encourage research to explore context-driven changes in the job preservation strategies that individuals attempt.

The notion of job preservation is often dismissed because it could be taken to imply that JI is beneficial for organizations. However, our findings do not suggest an overall benefit for organizations from JI. Although job preservation motivation may be indirectly positively associated with job performance under perceptions of more proximal threats, there is a negative countervailing effect, suggesting that individuals may be working harder simply to maintain performance. Moreover, JI is linked with greater social job preservation behaviors (knowledge hiding, self-presentation ingratiatory behavior), neither of which can be considered beneficial for the organization. However, the general pattern of results observed in the research, especially the indirect effects through job preservation motivation under conditions of higher threat proximity observed in Study 2, points to strategic resource investment as a valuable lens through which to understand reactions to JI. Our 2 × 2 typology suggests that people may pursue different strategies for job preservation, thereby providing a way for the field to organize and investigate potential job preservation responses.

In addition to advancing the JI literature, these findings help clarify COR theory (Hobfoll, 1989), which provides limited explanation of (a) the resource investment strategies that people pursue and (b) the conditions under which people pursue resource investment to counteract threats versus when they choose to conserve energy and effort. Counter to Hagger’s (2015) ideas about justification for resource investment, we did not find significant moderating effects of perceived threat controllability. This finding is in line with Hobfoll’s (1989) contention that people will make every effort to counteract threats, even efforts that are unlikely to be successful. Perhaps the importance of the job is enough justification for resource investment, regardless of perceptions of controllability. That said, it is also possible that these results might be due to the relatively broad measure of controllability. Perhaps another measure would have yielded different results—for example, future research might ask about the extent to which individuals anticipate that they can secure their jobs through engaging in specific forms of behavior (e.g., higher job performance).

Practical Implications

Contrary to popularly held beliefs that JI may motivate employees to achieve maximum performance (Dizik, 2017), our findings suggest that JI may do little to enhance organizational outcomes. Even worse, it may encourage workplace dysfunction marked by ingratiatory behavior and evasive knowledge hiding. Some managers may utilize threats of employment-related punishment to motivate performance or deter undesirable work behaviors. However, concerns about job loss do not appear to make workers stellar employees or performers. Our findings suggest that leaders may benefit from abandoning the stick of job loss as a strategy to motivate performance. In this regard, managers may benefit from rethinking some common managerial concepts, such as the 20-70-10 rule and the “up or out” mentality. The comparative nature of such practices might serve to heighten socially oriented job preservation strategies, as employees may feel the need to stand apart from others to keep their jobs.

Additionally, not only should organizational leaders avoid intentionally increasing JI, but managers should actively work to alleviate insecurity and its effects. Rather than trying to scare employees into high performance, leaders could look to strategies that increase security and engagement (e.g., Lesener, Gusy, Jochmann, & Wolter, 2020). Leadership may also seek to reduce proximal threats, such as those posed by management issues or “lean and mean” organizational strategies (Carusone & Shoss, 2018).

Nonetheless, there may be times when JI is unavoidable. For example, in times of threat to the jobs of the entire organization (e.g., COVID-19 pandemic), job preservation motivation may be useful for promoting some beneficial organizational outcomes to the extent to which counterpressures may be identified and managed. Addressing JI in such circumstances where the threat is imminent will likely yield the most successful results, as our findings suggested that proximal threats were more strongly associated with job preservation motivation. It may be beneficial to communicate the situation to employees while clearly explaining desired behaviors that will help secure their jobs and discouraging undesired behaviors, such as knowledge hiding.

On a related note, our findings of a positive relationship between JI and self-presentation ingratiatory behaviors are in line with popular career advice encouraging workers to continually sell their accomplishments to their boss (e.g., Klaus, 2003). These findings should lead managers to question whether any perceived performance gains due to JI are real or simply self-presentation.⁴ Overall, our results suggest that organizational leaders should carefully consider the impact of failing to address, or attempting to induce, JI among their employees. While JI may be associated with employees’ expenditures of effort in an attempt to preserve their jobs, the associated behaviors are likely to run counter to the ultimate goals of the organization.

Limitations and Future Research Directions

Although our studies have several strengths, they are not without limitations. Both studies involve self-report data. Although we found little evidence for common method bias, one may wonder about the impact of social desirability on our findings. Unfortunately, scales attempting to measure social desirability are more likely to measure elements of personality (e.g., agreeableness; Ones, Viswesvaran, & Reiss, 1996). Therefore, we sought to minimize social desirability through study design, including surveying people outside the workplace.

We also acknowledge differing opinions on the utility of self-reported job performance. Studies have found significant correlations between self-report and supervisor-report measures of job performance (Williams & Levy, 1992), and self- and supervisor-report measures may introduce bias in different ways. Because we anticipated that employees were in the best position to differentiate their actual performance from self-presentation (Huang et al., 2013) and we were concerned that JI would create a reluctance to ask for supervisor reports, we elected to use self-reports. Future research could explore other data sources.

Unfortunately, there is little guidance in the literature regarding appropriate time lags. The 3-month time lag between waves in Study 1 was chosen to align with other longitudinal studies of JI and to minimize attrition between waves (e.g., Huang et al., 2012; Probst & Brubaker, 2001). We compressed the time frame during the COVID-19 crisis (i.e., Study 2) because JI was such a salient societal stressor and we thought that job preservation may play out over a shorter period. More research is needed to examine the temporal dynamics of these effects.

As noted previously, the failure to find an effect for knowledge hiding in Study 2 as compared with Study 1 may have been a function of the COVID-19 pandemic and the “crisis mode” that many businesses were in during the time. It would be beneficial for future research to examine how job preservation efforts are shaped by crises. Study 1’s findings may also reflect the representation of knowledge workers in our sample. While this may speak to the growing sector of the economy categorized by knowledge professions, research might explore potential job preservation strategies in stratified samples designed to assess the role of industry. Future research should also examine performance as a form of job preservation. Although we focused on increases in performance as an indicator of a promotive job preservation strategy, it is plausible that people pursue maintaining a given level of performance as a protective strategy. It may also be that efforts to take on more work (Table 7) can help explain why it is difficult to enhance one’s performance in light of JI.

Future research might examine how income (i.e., job dependence) plays a role in responses to JI. On one hand, individuals with lower incomes may feel more dependent on their job, which would lead to a greater motivation to try to hold on to that job. Shoss (2017) described this as economic vulnerability. On the other, those with higher incomes may worry about potential standard-of-living decreases and identity impacts of job loss and thus be especially motivated to address JI (Lam, Fan, & Moen, 2014).

Research may seek to investigate how national culture shapes individuals’ responses to JI. The current studies took place in the United States, which is marked by high cultural value on independence, low union protection, and low dismissal protection (Sverke et al., 2019). In this context, perhaps it is unsurprising that employees seek to preserve their jobs by making themselves look better. Future research should examine these effects in other contexts.

In this vein, future research might examine whether there are individual, situational, organizational, or cultural differences in individuals’ choices to use different job preservation strategies. The typology developed here can be used to identify and organize additional potential job preservation responses. For example, some of the qualitative responses from Study 2 indicate work intensification as a task-oriented promotion strategy. In light of the reversed effects found in Study 1, it would be interesting to examine whether some job preservation behaviors are done to preempt JI rather than respond to it.

Conclusions

Our research suggests that employees attempt to act strategically in the face of higher levels of JI, especially in the case of proximal threats. Such strategies involve promotive and protective efforts directed at task and social targets. However, despite strategic resource investment associated with JI, JI hardly appears beneficial for organizations.

Supplemental Material

sj-docx-1-jom-10.1177_01492063221107877 - Supplemental material for Working Hard or Hardly Working? An Examination of Job Preservation Responses to Job Insecurity

Supplemental material, sj-docx-1-jom-10.1177_01492063221107877 for Working Hard or Hardly Working? An Examination of Job Preservation Responses to Job Insecurity by Mindy K. Shoss, Shiyang Su, Ann E. Schlotzhauer and Nicole Carusone in Journal of Management

	Resource Investment Target
Promotive	Performance	Self-presentation ingratiatory behaviors
Protective	Avoiding counterproductive work behavior	Evasive knowledge hiding

	M (SD)	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15
1. Job insecurity 1	2.77 (1.21)	(.88)
2. Job insecurity 2	2.47 (1.10)	.63**	(.84)
3. Job insecurity 3	2.76 (1.12)	.54**	.43**	(.84)
4. Counterproductive work behavior 1	2.83 (1.08)	.68**	.60**	.45**	(.96)
5. Counterproductive work behavior 2	2.67 (1.00)	.70**	.62**	.41**	.80**	(.95)
6. Counterproductive work behavior 3	2.50 (1.01)	.78**	.71**	.57**	.76**	.83**	(.95)
7. Knowledge hiding 1	4.42 (1.44)	.43**	.31**	.36**	.64**	.54**	.46**	(.89)
8. Knowledge hiding 2	3.83 (1.4)	.50**	.45**	.20**	.66**	.76**	.57**	.61**	(.87)
9. Knowledge hiding 3	3.55 (1.51)	.57**	.56**	.29**	.70**	.83**	.74**	.53**	.84**	(.90)
10. Self-presentation 1	3.54 (0.79)	.38**	.31**	.39**	.45**	.35**	.32**	.55**	.24**	.22**	(.73)
11. Self-presentation 2	3.37 (0.72)	.24**	.22**	.35**	.22**	.22**	.24**	.32**	.18**	.12*	.50**	(.61)
12. Self-presentation 3	3.20 (0.69)	.32**	.19**	.40**	.14**	.13*	.33**	.17**	−.01	.09	.40**	.36**	(.60)
13. Performance 1	6.76 (1.15)	−.43**	−.28**	−.37**	−.43**	−.45**	−.54**	−.37**	−.31**	−.40**	−.19**	−.14**	−.14*	(.87)
14. Performance 2	6.61 (1.12)	−.40**	−.21**	−.26**	−.44**	−.49**	−.47**	−.39**	−.41**	−.46**	−.16**	−.20**	−.10	.71**	(.82)
15. Performance 3	6.76 (0.91)	−.32**	−.24**	−.43**	−.42**	−.40**	−.38**	−.51**	−.36**	−.38**	−.20**	−.17**	−.08	.66**	.65**	(.77)

	BIC	χ²	df	CFI	RMSEA	SRMR
3-factor model	57,119.73	6,593.20	1,479	0.69	0.097	0.116
6-factor model	56,284.88	5,687.51	1,467	0.74	0.089	0.114
12-factor model	54,833.00	3,934.60	1,416	0.85	0.070	0.072
15-factor model
Free factor loadings	53,834.52	2,705.91	1,377	0.92	0.051	0.055
Longitudinal constraints on loadings	53,744.14	2,780.81	1,405	0.92	0.052	0.061

	M (SD)	1	2	3	4	5	6	7	8
1. Job insecurity	2.42 (1.18)	(.87)
2. Job preservation motivation	4.05 (0.83)	.09	(.90)
3. Counterproductive work behavior	1.47 (0.42)	.12	−.37**	(.83)
4. Knowledge hiding	1.56 (1.04)	.12	−.05	.29**	(.92)
5. Self-presentation	2.42 (0.88)	.01	.13*	.11	.29**	(.87)
6. Performance	4.37 (0.75)	−.14*	.32**	−.35**	−.33**	−.01	(.91)
7. Threat controllability	3.34 (1.23)	−.28**	.08	−.05	.00	.10	.06	(.94)
8. Threat proximity	1.91 (1.04)	.64**	−.03	.15*	.21**	.04	−.22**	−.38**	(.96)

	BIC	χ²	df	CFI	RMSEA	SRMR
5-factor model	18,586.13	2,117.39	395	0.73	0.121	0.128
6-factor model	18,185.23	1,688.04	390	0.80	0.106	0.083
7-factor model I	17,966.25	1,434.92	384	0.84	0.096	0.077
7-factor model II	17,678.10	1,146.77	384	0.88	0.082	0.092
8-factor model	17,277.34	706.17	377	0.95	0.054	0.048

	Job Preservation Motivation	Job Performance	CWB	Self-Presentation	Knowledge Hiding
Job preservation motivation		0.41 (0.08)**	−0.49 (0.08)**	0.16 (0.07)*	−0.10 (0.07)
JI	0.17 (0.10)	−0.22 (0.08)**	0.22 (0.08)**	−0.01 (0.07)	0.15 (0.07)*
Threat proximity	−0.29 (0.12)*
JI × Proximity	0.25 (0.08)**
Control	0.01 (0.07)
JI × Control	0.03 (0.07)
Indirect effect at low proximity		−0.03 [−0.14, 0.08]	0.04 [−0.08, 0.17]	−0.01 [−0.07, 0.03]	0.01 [−0.02, 0.05]
Indirect effect at high proximity		0.18* [0.06, 0.31]	−0.21* [−0.37, −0.07]	0.07* [0.01, 0.15]	−0.04 [−0.12, 0.02]

Job Preservation Strategy	Resource Investment Target
Promotive	“I started working extra hard to prove my job was important to keep. I worked overtime and at nights to show that I was hardworking and dedicated.”“I have taken on new tasks to help management and the front desk, so I am trying to . . . increase my worth.”“Make an extra effort so that [my] work product is as good as possible, with no errors. Accept extra work if asked.”	“Lately, I've been communicating weekly with my boss to keep him informed on what I've been accomplishing and make sure he knows about all the areas where I'm contributing.”“I just try to make sure that my manager likes me and go above and beyond to try to show my worth.”“Promoting oneself modestly is a key part of protecting my job.”
Protective	“I focus on the things that I can control, like showing up to work on time. Getting my work done. Not creating drama in the workplace. etc.”“Always ensuring I was on time, never took long lunches and tried my best to clock out on time to avoid overtime if possible.”“I’ve tried to put my head down and work. I tried to become a ghost and just not draw attention to myself.”	“There are definitely some processes that only I know how to do. . . . If I were to leave these processes would not get done.”“They would have trouble replacing me in the short term because not many others have learned how to perform my role yet.”“I have made sure I have a set of skills that is hard to replace at my work. I am one of the few that knows all our systems. I learned early on pay and job security is not based on how hard your [sic] work but on how hard it is to replace you.”

Footnotes

Acknowledgments

We acknowledge Dr. Christopher Rosen and the anonymous reviewers for their helpful feedback throughout the review process. We also thank Dr. Dustin Jundt for his comments on an earlier version of the paper. This research was supported by an internal grant from the University of Central Florida’s Office of Faculty Excellence awarded to Dr. Mindy Shoss.

ORCID iDs

Mindy K. Shoss

Ann E. Schlotzhauer

Notes

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	Resource Investment Target
Job Preservation Strategy	Task Oriented	Social Oriented
Promotive	Performance	Self-presentation ingratiatory behaviors
Protective	Avoiding counterproductive work behavior	Evasive knowledge hiding