strong situation hypothesis

The strong situation hypothesis

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• 1 Queen's University. [email protected]
• PMID: 19144905
• DOI: 10.1177/1088868308329378

A conventional wisdom in personality and social psychology and organizational behavior is that personality matters most in weak situations and least in strong situations. The authors trace the origins of this claim and examine the evidence for the personality-dampening effect of strong situations. The authors identify the gap between claim and evidence and suggest an agenda for future research.

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• Organizational Culture*
• Personality*
• Psychological Theory
• Psychology, Social
• Social Behavior*
• Social Conformity
• Social Control, Formal
• Social Control, Informal

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The Strong Situation Hypothesis

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• Original Paper
• Published: 13 October 2022

Situational Strength as a Lens to Understand the Strain Implications of Extra-Normative Work

• Charles Calderwood   ORCID: orcid.org/0000-0001-6209-6421 1 ,
• Rustin D. Meyer 2 &
• Molly E. Minnen 3  

Journal of Business and Psychology volume  38 ,  pages 637–655 ( 2023 ) Cite this article

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Employees must often perform work outside of the time and/or space requirements that typically define their job role (e.g., working after-hours, teleworking), especially during the COVID-19 pandemic. We introduce the concept of extra-normative work to capture this idea and draw on situational strength theory to test the seemingly paradoxical hypotheses that (1) the effects of extra-normative work are more harmful to employee strain when this work represents a stronger situation (i.e., one that unambiguously prescribes expected behavior), relative to when this work represents a weaker situation (i.e., one that allows for greater personal choice and behavioral latitude), but that (2) this strain is diminished when situational strength is achieved by maximizing the clarity and consistency of extra-normative work, while this strain is enhanced when situational strength is achieved by imposing greater constraints and consequences surrounding extra-normative work. These predictions were supported in an experimental vignette study, a survey focused on after-hours work experiences, and an investigation of telework in response to COVID-19. We discuss the theoretical implications of viewing extra-normative work through the lens of situational strength, while also outlining how our findings inform best practices surrounding how to communicate about and frame extra-normative work to employees.

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While organizational life has long been recognized to be characterized by a variety of behavioral norms and expectations (Cooke & Rousseau, 1988) that influence the perceived scope of the typical job role, less is known about whether and how employees are affected by work that falls outside the norms and expectations of their job. We conceptualize this situation to be representative of a new construct that we refer to as extra-normative work, which reflects work arrangements wherein effort is required in ways, at times, and/or from locations that differ substantially from employees’ typical expectations. We further contend that the strain implications of extra-normative work depend largely on how this work is conveyed and perceived. Specifically, we frame these effects through the lens of situational strength.

Situational strength reflects the idea that human social environments provide information about what behaviors should or should not be enacted. Environments that provide unambiguous information about prescribed behaviors (i.e., strong situations) encourage behavioral compliance, while environments where such information is absent and/or difficult to interpret (i.e., weak situations) leave people to their own devices to determine what to do (Mischel, 1977 ). Situational strength is a multi-faceted construct, encompassing perceptions of (1) consistency (compatibility of cues regarding job-related responsibilities across time and organizational levels), (2) clarity (the availability and understandability of cues regarding job-related responsibilities), (3) consequences (the negative or positive implications of an employee’s decisions or actions), and (4) constraints (the limiting of an employee’s decision making by forces outside of their control) (Meyer et al., 2010 ). Our central contention is that this facet structure of situational strength is particularly critical to understanding the employee strain implications of extra-normative work. In other words, when considering that these arrangements by definition operate outside the boundaries of the typical norms that help to define and shape the scope of the work role, we argue that the situational strength of these extra-normative work arrangements and how that situational strength is achieved are key to the degree to which these arrangements influence employee strain.

We conducted three multi-modal studies (Highhouse, 2009 ) to test whether the situational strength of extra-normative work influences employee strain. We first used experimental vignettes (Study 1) to demonstrate that employees expect to exhibit more behavioral compliance and experience greater strain in stronger extra-normative work situations, compared to weaker extra-normative work situations. We then examined whether the four facets of situational strength have diverging implications for strain criteria in the extra-normative work context of working after-hours (e.g., nights, weekends, holidays; Study 2). Finally, we evaluated whether the situational strength of extra-normative work influences employee strain in workers who have abruptly and unexpectedly transitioned to teleworking in response to COVID-19 (Study 3). The participants in this latter study had rarely teleworked prior to the onset of the COVID-19 pandemic, such that their engagement in this telework was extra-normative relative to the scope of their typical work role. As teleworking was less common prior to the pandemic in comparison to during the pandemic, and when considering that working after-hours was arguably the most common type of extra-normative work prior to the pandemic, Study 2 provides an evidence-based comparison of the extra-normative work of working after-hours to the extra-normative work of teleworking during COVID-19 examined in Study 3.

We aim to make several contributions to the situational strength, work demand perceptions, and occupational health literatures. Conceptually, we synthesize numerous experiences reflecting working outside of the typical job role, such as supplemental work (Venkatesh & Vitalri, 1992 ), after-hours teleworking (Duxbury et al., 1992 ), and unplanned teleworking in response to COVID-19, under the umbrella extra-normative work construct. In terms of theoretical contributions, we advance situational strength as a unifying explanation for employee reactions to different manifestations of extra-normative work. Moreover, we argue that a facet-level perspective can resolve past empirical inconsistencies in documenting the strain implications of situational strength (Meyer et al., 2018 ; Steel et al., 2008 ). Specifically, we argue that clarity and consistency perceptions surrounding extra-normative work co-vary with lower strain and argue that consequence and constraint perceptions surrounding extra-normative work engender greater strain (i.e., anxiety surrounding the work role; perceptions of job stress; emotional exhaustion; McCarthy et al., 2016 ; Motowidlo et al., 1986 ; Wharton, 1993 ). Thus, one of our primary contributions is to test the notion that strain-based reactions are less a function of the extent to which one’s behavior is perceived as being influenced by external considerations and more a function of the extent to which these considerations are perceived by employees as either facilitating (i.e., clarity and consistency) or inhibiting (i.e., constraints and consequences) forces. Our unraveling of these contradictory influences of extra-normative situational strength yields practical implications for how extra-normative work expectations should be communicated to employees.

Positioning the Construct Space of Extra-Normative Work

We position extra-normative work to represent an overarching class of experiences in which employees are called upon to apply effort to work in ways, at times, and/or from locations outside of their expectations surrounding their work role. While potentially related to organizational citizenship behavior (OCB), which reflects discretionary behavior that contributes to organizational functioning despite not being part of the formal organizational reward structure (Organ et al., 2006 ), extra-normative work is broader because it reflects the parameters of how, when, and why work is performed outside of the traditional work role scope, rather than what specific behaviors are enacted. In other words, while OCBs may be part of the criterion space of extra-normative work, extra-normative work reflects the conditions under which work is performed, rather than the occurrence of any specific contextual performance-relevant behavior or set of behaviors.

Furthermore, other work arrangements such as working overtime, telecommuting, and flexplace working (Thompson & Payne, 2015) could reflect extra-normative work, but only if these arrangements fall outside the traditional scope of a given work role. As one example, overtime is unlikely to represent extra-normative work in a work role in which employees frequently and regularly accrue overtime, while it likely does represent extra-normative work if the work role infrequently calls for overtime. In a similar manner, teleworking in response to COVID-19 likely constitutes extra-normative work if the job previously involved little to no teleworking, but is unlikely to constitute extra-normative work if the job previously included regular teleworking. Additionally, engagement in supplemental work (i.e., performing job-related responsibilities at home; Venkatesh and Vitalri, 1992 ) or technology-assisted supplemental work (i.e., using information and communication technologies to complete job tasks at home; Fenner & Renn, 2010 ) could reflect extra-normative work, but only if this work is outside the scope of the typical work role. Accordingly, extra-normative work is primarily defined by whether the work arrangement in question is or is not outside of the traditional work role scope, rather than by any objective characteristics of the work arrangement in question.

Extra-normative work is also distinct from key constructs within the role stressor literature, such as role conflict (i.e., competing demands from two or more work roles) and role ambiguity (i.e., unclear behaviors or expectations that define a work role) (Kahn et al., 1964 ). Regarding the former, role conflict is conceptualized to result from incompatible demands between work roles that are difficult to meet simultaneously (House & Rizzo, 1972 ). In contrast, extra-normative work is not by definition incompatible with meeting the demands of any core work role or multiple work roles, but instead defined by whether the work being done is outside of the typical work role. In terms of the latter, role ambiguity reflects a lack of clarity in the scope and expectations of the work role (Van Sell et al., 1981 ). In contrast, from a theoretical perspective, extra-normative work depends on the existence of at least some minimal definition of the typical work role and corresponding norms that govern the work role. Thus, while high levels of role ambiguity may certainly undermine clarity of what the norms guiding a work role are (Judeh, 2011 ), this role stressor is conceptually distinct from extra-normative work.

In addition, extra-normative work is conceptualized to be distinct from several constructs within the work/non-work boundary management literature (Ashforth et al., 2000 ; Matthews et al., 2010 ). Of particular note, segmentation preferences (i.e., the degree to which employees desire to keep work segmented from home life; Kreiner, 2006 ) and collective work group norms that influence experienced work/non-work segmentation (Yang et al., 2019 ) may both shape perceptions of the typical work role. However, departures from these norms would still constitute extra-normative work. For example, even individuals with strong segmentation preferences working in work groups with strong segmentation norms may have had to abruptly violate these preferences and norms when moving to teleworking in the early days of the COVID-19 pandemic. Thus, this teleworking situation would reflect an extra-normative work arrangement, and would remain so until norms shifted to accommodate enduring changes to work induced by the pandemic and a corresponding adaptation in what reflects normative behavior (Miller & Prentice, 2016 ). Thus, while a variety of individual, interpersonal, and organizational factors may shape the work norms that influence employee behavior, there still can be a variety of extra-normative work arrangements that employees engage in that fall outside the scope of these typical norms. Footnote 1

Theoretical Background

Situational strength theory posits that situations that provide more information about expected behaviors (i.e., stronger situations) yield greater compliance with the prescribed behavior pattern, relative to weaker situations (Meyer et al., 2010 ; Mischel, 1977 ). Applications of this theory to job-related phenomenon have demonstrated that situational strength is comprised of the multiple facets of consistency , clarity , consequences , and constraints , which reflect unique but complementary inputs to the situational strength of work-relevant situations (Meyer et al., 2010 ). These facets of situational strength are theorized to be generalizable across a range of different work-relevant contexts (Meyer et al., 2014 ), which would be expected to include extra-normative work given the broad applicability of situational strength to job-related phenomenon. Crucially, while there have been numerous and varied perspectives that emphasize the nature and structure of situations across a variety of literatures (Johns, 2006 ; Parrigon et al., 2017 ; Rauthmann et al., 2015 ), situational strength is the only perspective that focuses exclusively on the ways in which human behavior is externally influenced by broad situational characteristics. Consequently, we contend that this theory can best account for the range of work arrangements that could represent extra-normative work across different industries, occupations, and employment contexts.

Applying Situational Strength Theory to Extra-Normative Work

The central prediction of situational strength theory is that strong situations lead employees to perform the behaviors dictated by the situation (Meyer et al., 2010 , 2014 ; Mischel, 1977 ). Consistent with this view, higher levels of each of the four facets of situational strength are argued to increase prescribed job-related behavior patterns, a prediction supported by meta-analytic (Bowling et al., 2015 ; Meyer et al., 2009 ) and primary study research (Meyer et al., 2014 ). Specifically, this research generally demonstrates that the criterion-oriented validity of relevant individual differences is attenuated in stronger work environments, thereby suggesting that the behavioral influence of strong situations is overriding employees’ default tendencies. Unfortunately, however, existing meta-analytic research only examines two theorized facets of situational strength and primary studies (which test all four facets) tend to largely focus on performance-relevant criteria. Thus, the effects of the four facets on strain-based outcomes are unknown.

Although it may be tempting to conclude that extra-normative work is, by definition, less likely to occur in strong situations where norms, expectations, and contingencies are relatively more established, it is important to point out that both situational strength and extra-normative work are generally enacted in a top-down fashion (i.e., from supervisors – Alaybek et al., 2017 ), so the same forces that set the terms and conditions of situational strength (e.g., supervisors who set schedules and reward structures) also have the power to change those arrangements (e.g., through requests for extra-normative work). Accordingly, it does not necessarily follow that extra-normative work is precluded or even less likely in jobs and work environments characterized by higher levels of situational strength.

This theorizing and empirical evidence from the situational strength literature forms the basis for two inter-connected predictions. First, just as employees can perceive the situational strength of their job at a more general level (Meyer et al., 2014 ), they can distinguish between weaker and stronger extra-normative work situations. Second, applying the core proposition that stronger situations yield prescribed behaviors to the extra-normative work context, it follows that employees who perceive extra-normative work to represent a stronger situation would be more likely to exhibit extra-normative work demand compliance (i.e., perform the behaviors necessary to meet extra-normative work demands). We note that, given that all four facets of situational strength are expected to increase prescribed behavior patterns, we do not expect diverging implications of different facets of situational strength for extra-normative work demand compliance. Thus, we expect that:

Hypothesis 1: Employees can distinguish between weak and strong extra-normative work situations.

Hypothesis 2: Aggregate extra-normative situational strength is positively associated with extra-normative work demand compliance.

However, while all four facets of situational strength (clarity, consistency, constraints, and consequences) are expected to influence extra-normative work demand compliance in the same direction (i.e., increasing it), the theoretical picture becomes substantially murkier when considering strain criteria. At the broadest level, situational strength has been suggested to engender strain because it encourages people to engage in behaviors that they otherwise might not (Meyer et al., 2010 , 2018 ; Shoda et al., 1994 ). However, the few empirical investigations that are directly relevant to this prediction have yielded inconsistent results (see Steel et al., 2008 , for a review). We contend that these inconsistent results can be resolved by considering the potentially diverging implications of different facets of extra-normative work situational strength for strain. More specifically, we argue below that it should be expected that consistency and clarity facets of extra-normative work situational strength will associate with lower strain, while consequences and constraint facets will co-vary with the higher strain predicted by broader situational strength theorizing.

Regarding consistency and clarity, both of these facets provide employees with a more accurate view of what behaviors are expected of them, which should clarify the work role and reduce ambiguity surrounding extra-normative work. Greater clarity surrounding the work role is widely recognized to have a salutary influence on strain criteria (Bliese & Castro, 2000 ; Lang et al., 2007 ), while conversely ambiguity surrounding the work role is one of the most widely supported contributors to higher levels of employee strain (Schmidt et al., 2014 ). These associations have typically been explained through the lens of role theory (Kahn et al., 1964 ), which posits that when a set of expectations relevant to the job (i.e., a role) is ambiguously defined, this ambiguity yields downstream strain reactions that undermine health, well-being, and performance (Beehr, 1976 ; Tubre & Collins, 2000 ; Van Sell et al., 1981 ). Therefore, while driving greater situational strength of extra-normative work, it is plausible that both consistency and clarity reduce, rather than increase, resultant strain because they present understandable and available cues that allow employees to better know the scope and expectations of this extra-normative work. Synthesizing these lines of theoretical and empirical evidence, we would thus expect that consistency (i.e., compatibility of available cues) and clarity (i.e., availability and understandability of these cues) of extra-normative work will co-vary with lower levels of employee strain.

In contrast, we anticipate that consequences and constraints underlying extra-normative work will engender the theorized elevation of strain posited within broader situational strength theory (Meyer et al., 2010 ; Shoda et al., 1994 ). Work-related consequences are thought to be a major influence on anxiety surrounding the work role, which empirical evidence suggests is directly relevant to employee strain criteria (Calderwood et al., 2018 ; McCarthy et al., 2016 ). Constraints, by definition, undermine autonomy and the ability to make decisions about how extra-normative work should be carried out, both of which are seen as crucial to strain mitigation and well-being promotion in numerous frameworks, such as the Job Demands – Control Model (Karasek, 1979 ) and Self-Determination Theory (Ryan & Deci, 2017 ). This view aligns with past arguments built on situational strength theory, in which the undermining of perceived autonomy and the freedom to have greater agency over one’s own behavior is argued to be strain-inducing (Meyer et al., 2010 , 2018 ; Shoda et al., 1994 ). Thus, to summarize our expectations surrounding how different facets of situational strength surrounding extra-normative work will relate to strain criteria, we predict that:

Hypothesis 3: Aggregate extra-normative situational strength is positively associated with employee strain.

Hypothesis 4: Extra-normative (a) consistency and (b) clarity are negatively associated with employee strain.

Hypothesis 5: Extra-normative (a) consequences and (b) constraints are positively associated with employee strain.

Selection of Strain Criteria

To provide an initial demonstration that situational strength surrounding extra-normative work is relevant to strain criteria, we examined several different strain criteria across the three studies reported subsequently. In Study 1 (an experimental vignette study), we elected to evaluate how extra-normative work situations varying in situational strength would influence emotional exhaustion and anxiety. We selected these strain criteria because they are viewed as widespread in organizations, have consistently been established as contributors to employee health, wellness, and performance (Bakker & Demerouti, 2017 ; McCarthy et al., 2016 ), and could be adapted to a vignette context (i.e., predicted emotional exhaustion and anxiety when facing a given situation). In Studies 2 and 3 (survey-based studies focused on the extra-normative work contexts of working after-hours and abruptly teleworking in response to COVID-19, respectively), we again evaluated emotional exhaustion, but also investigated work anxiety (nervousness and apprehension surrounding the completion of job tasks; McCarthy et al., 2016 ) to provide a closer conceptualization of our anxiety indicator with the employment context, relative to our approach in Study 1. We also added a measure of perceived job stress in Studies 2 and 3, as this more global perception of the stressfulness of one’s job has long been recognized to be relevant to a wide range of strain criteria in occupational contexts (e.g., Blau, 1981; Eden, 1990; Motowidlo et al., 1986 ).

Participants working at least 32 h per week were recruited via Prolific Academic for a within-subjects experimental vignette study. Prolific Academic ( https://www.prolific.co/ ) is a research-oriented crowdsourcing platform that allows researchers to target study advertisements to interested participants that meet inclusion criteria. Prolific demonstrates distinct advantages over other crowdsourcing platforms in terms of participant management, data quality, and multi-wave study capabilities (Palan & Schitter, 2020). A total of 311 participants provided informed consent, viewed a series of three vignettes, and completed an online survey to gauge their anticipated behaviors and reactions in response to these vignettes. Participants were screened out for (1) failing an attention check item (e.g., “Please select ‘Moderately Agree’ for this item”; n  = 25), (2) suspicions of careless responding (i.e., survey response times equal to less than one second per item; Huang et al., 2012 ; n  = 29), or (3) not reporting at least a high English language proficiency ( n  = 14). The final sample consisted of 243 participants ( N  = 243). The sample was fairly evenly split between males (50.2%) and females (48.6%). The majority of participants were White (87.7%), while the remainder of the sample were largely Asian (5.3%), Hispanic/Latinx (4.1%), or Black/African American (2.5%). Participants were roughly 36 years old ( M  = 36.26, SD  = 9.76), had worked in their current job for 4.55 years ( SD  = 3.89), and worked 41.38 h per week ( SD  = 5.25) on average.

After reading a study description and providing informed consent, participants were presented with a randomized series of three work situations and asked to describe how they would behave and feel in each situation (see Table 1 ). Vignettes were written to reflect extra-normative work and were experimentally manipulated to be weaker or stronger by altering contextual information pertaining to the four facets of situational strength. Participants were randomly assigned to see a Weak or Strong manipulation for each vignette and the order that the vignettes were presented to participants was randomized. The stem of the extra-normative work situation was identical across these two conditions for each vignette, and only the four pieces of presented contextual information underneath the stem were altered to manipulate situational strength. Participants rated the perceived situational strength of the described situation, their predicted behavior compliance, their predicted emotional exhaustion , and their predicted anxiety after reading each vignette Footnote 2 . Participants were compensated $2.25 US for participating in this study, which took approximately 20 min to complete.

Descriptive statistics, correlations, and internal consistency estimates for all Study 1 variables are in Table 2 . Unless otherwise noted, participants responded on a 6-point Likert-type scale (1 =  strongly disagree ; 6 =  strongly agree ).

Perceived Situational Strength

Participants used a 7-point sliding scale to rate the perceived situational strength of each situation, which ranged from − 3 ( feel free to behave in whatever way I wanted ) to + 3 ( feel pressured to behave in a certain way ).

Behavioral Compliance

Four customized response options for each vignette were created that were continuously ordered to range from a complete absence of behavioral compliance (a score of 1) to complete behavioral compliance (a score of 4).

Predicted Emotional Exhaustion

Predicted emotional exhaustion was rated using six items adapted from Wharton ( 1993 ). Sample item: “If I experienced this situation, I believe I would feel emotionally drained at work” ( ω  = 0.93–0.96 across responses to the three vignettes). Footnote 3

Predicted Anxiety

Predicted anxiety was evaluated with nine items adapted from the tension/anxiety subscale of the Profile of Mood States (McNair et al., 1971 ). Sample item: “If I experienced this situation, I believe I would feel tense” ( ω  = 0.90–0.92).

Study 1 Results

We computed a random coefficients regression, with repeated measurements across vignettes nested within individuals ( n  = 729 Level 1 observations), to test Hypotheses 1–3 in this initial evaluation of the effects of aggregate situational strength surrounding extra-normative work. Condition ( Strong , Weak ) was entered as a predictor of perceived situational strength, anticipated behavioral compliance, predicted emotional exhaustion, and predicted anxiety in this model. We statistically controlled for vignette exposure when conducting these analyses by entering two dummy coded variables that combined to represent the three experimental vignettes. In support of Hypothesis 1, participants perceived the situational strength of extra-normative work to be higher in the Strong condition than in the Weak condition ( γ  = 1.27, SE  = 0.13, z  = 9.86, p  < 0.01). In support of Hypotheses 2 and 3, exposure to the Strong condition caused increases in predicted behavioral compliance ( γ  = 1.00, SE  = 0.06, z  = 16.04, p  < 0.01), emotional exhaustion ( γ  = 0.33, SE  = 0.08, z  = 4.05, p  < 0.01), and anxiety ( γ  = 0.15, SE  = 0.06, z  = 2.68, p  < 0.05), relative to the Weak condition. These findings provide an initial proof-of-concept supporting extra-normative situational strength as a contributor to employees’ intended behavioral compliance and strain expectations.

Examination of the intra-class correlations (ICC (1)  = 0.19–0.49) within this random coefficients regression model suggested that between 51–81% of the criterion variance was within-person across the different measured criteria (i.e., 1–ICC (1) ). Therefore, we conducted an exploratory comparison to evaluate if some extra-normative work vignettes may have engendered greater perceptions of situational strength than others (see Fig.  1 ). The Strong condition of all three vignettes seemed effective in engendering a moderate-to-large effect size increase in perceived situational strength, relative to the Weak condition ( d  = 0.59–0.89). However, we did observe the meeting spillover vignette, which focused on having to continue to work outside of regularly scheduled work hours, to yield greater perceptions of situational strength than the office party ( t (242)  = 2.85, p  < 0.01, d  = 0.18) and the post-work e-mail ( t (242)  = 2.75, p  < 0.01, d  = 0.18) vignettes, which bolstered our decision to focus on after-hours work as an extra-normative work arrangement in Study 2. Footnote 4

Mean values of perceived situational strength for participants randomly assigned to view weak or strong contextual information across three different extra-normative work situations. Note. Error bars represent standard errors. ** p  < .01

Procedure and Sample

Amazon MTurkers completed an approximately 30-min online survey housed on Qualtrics. Participants were required to (1) work in a non-executive, full-time job with expectations to work within standard business hours, (2) work in a job in which they at least occasionally work outside of these regularly scheduled hours (to ensure some extra-normative work among participants); (3) live with a significant other and at least one dependent minor, Footnote 5 (4) have a past work approval rating of 95% or higher on MTurk (see Hauser & Schwarz, 2016 ), and (5) report strong English language skills. The first and second parameters were set particularly with the intent of examining extra-normative work (i.e., expectations are to work within standard business hours but some work outside of these hours occurs), with the second criteria also being necessary to ensure the presence of at least some extra-normative work that participants could provide ratings about. Participants received $2 in compensation for completing the online survey.

In total, 777 participants met all of these inclusion criteria. Participants were screened out for (1) providing a job title likely to violate the inclusion criteria (e.g., “MTurk worker”; n  = 9), (2) suspicions of careless responding ( n  = 66), or (3) excessive missing data across multiple composite scales ( n  = 12). Finally, we excluded 254 ( n  = 254) participants who reported working overnight shifts, as we felt it unlikely that they technically met the inclusion criteria of working within standard business hours.

The final sample consisted of 436 participants ( N  = 436). A majority of participants were female (58.0%). The majority of participants were White (83.3%), with the remainder of the sample comprised largely of participants who were Black/African American (6.9%) or Asian (5.7%). Approximately 10 percent of participants (10.6%) reported that they were Hispanic/Latinx. Participants were 34.78 years old ( SD  = 7.77), had worked in their current job for 5.57 years ( SD  = 4.61), and worked 41.11 h per week ( SD  = 4.41) on average. A wide variety of occupations were represented in the sample, with the largest percentages of participants working in business management and administration (17.2%), marketing (12.4%), and information technology (11.7%).

Descriptive statistics, correlations, and internal consistency estimates for all Study 2 variables are in Table 3 . All items were answered on a 6-point Likert-type scale ranging from 1 ( strongly disagree ) to 6 ( strongly agree ).

Extra-Normative Situational Strength

Situational strength was measured using an adaptation of the Situational Strength at Work scale (SSW; Meyer et al., 2014 ) to an extra-normative, after-hours work context. The full adapted scale is presented in the Appendix, with the original scale items presented for comparative purposes. Basic psychometric information for the adapted scale is presented in Table 4 . All facet-level subscales exhibited acceptable internal consistency ( ω  = 0.81–0.88).

Emotional Exhaustion

Emotional exhaustion was assessed with six items from Wharton ( 1993 ). Sample item: “I feel emotionally drained from my work” ( ω  = 0.91).

Work Anxiety

Work anxiety was measured with eight items from McCarthy et al. ( 2016 ). Sample item: “I am overwhelmed by thoughts of doing poorly at work” ( ω  = 0.95).

Job Stress Perceptions

Job stress perceptions were evaluated with four items from Motowidlo et al. ( 1986 ). Sample item: “I feel a great deal of stress because of my job” ( ω  = 0.84).

Study 2 Results

We first evaluated a seven-factor measurement model in MPlus Version 8.4 (Muthén & Muthén, 1998 –2017), comprising the four situational strength facets and the three hypothesized strain correlates ( emotional exhaustion , work anxiety , perceived job stress ), which yielded a good fit to the data ( CFI  = 0.94, RMSEA  = 0.05, SRMR  = 0.05). We then computed a structural model in which the four facets of situational strength simultaneously predicted emotional exhaustion, work anxiety, and job stress perceptions (see Table 5 for parameter estimates), which also yielded a good fit to the data ( CFI  = 0.94, RMSEA  = 0.05, SRMR  = 0.05). Footnote 6 In support of Hypothesis 4a, consistency was associated with lower emotional exhaustion ( B  =  − 0.37, p  < 0.01), work anxiety ( B  =  − 0.38, p  < 0.01), and perceived job stress ( B  =  − 0.34, p  < 0.01). However, Hypothesis 4b was unsupported, as we had no evidence to link clarity to strain criteria ( B  =  − 0.05–0.10, all ns ). Hypothesis 5a was supported, with consequences found to co-vary with higher emotional exhaustion ( B  = 0.33, p  < 0.01), work anxiety ( B  = 0.22, p  < 0.01), and perceived job stress ( B  = 0.46, p  < 0.01). In contrast, Hypothesis 5b was only partially supported, with constraints positively related to emotional exhaustion ( B  = 0.19, p  < 0.05), but no evidence to link constraints to work anxiety ( B  = 0.10, ns ) or perceived job stress ( B  =  − 0.03, ns ). Using Cohen’s (1988) effect size guidelines, the contributions of the set of extra-normative work situational strength facets to perceived job stress ( R 2  = 0.16), work anxiety ( R 2  = 0.13), and emotional exhaustion ( R 2  = 0.19) corresponded to between medium and large effect sizes.

Full-time employees were recruited via Prolific Academic to complete an approximately 30-min online survey hosted on Qualtrics. All participants were required to (1) be currently working from home every day, (2) have rarely (i.e., less than one day per week) worked from home before the COVID-19 pandemic, and (3) be fluent English speakers. Consistent with our approach in Study 2, the first and second criteria combined to focus on employees engaged in extra-normative work, as these employees were now engaged in a work arrangement (i.e., working from home every day) that was not within the scope of the traditional work role (i.e., rarely working from home prior to the pandemic). Consistent with this view, participants reported that they had typically spent 7.80% of their working time working from home prior to COVID-19 on average ( SD  = 10.17), bolstering the conclusion that this work arrangement represented extra-normative work for these participants. We also note that Study 3 data were collected in June 2020, which was within the first few months of many organizations moving to teleworking in response to COVID-19 (International Labour Organization, 2020), such that longer-term pandemic-induced changes in how the traditional scope of many of these work roles were perceived likely had yet to stabilize. Participants were compensated $3.50 for their participation.

In total, 367 participants provided informed consent and indicated that they met the inclusion criteria. Participants were screened out for (1) failing an attention check item (e.g., “Please select ‘Moderately Agree’ for this item”; n  = 31), (2) suspicions of careless responding ( n  = 7), (3) providing a job title suggesting that they did not meet the inclusion criteria (e.g., “student”; n  = 18), or (4) reporting teleworking for more than 50% of their work time prior to the COVID-19 pandemic ( n  = 21). The final sample consisted of 290 participants ( N  = 290). The sample was fairly evenly split between males (54.8%) and females (45.2%). Most participants were White (82.1%), while the remainder of the sample were largely Asian (9.0%) or Black/African American (4.5%). Approximately 7.6% of the sample were Hispanic/Latinx. Participants were roughly 31.99 years old ( SD  = 7.87) and had worked in their current job for 4.80 years ( SD  = 4.92) on average. Most participants worked either 31–40 (63.4%) or 41–50 (32.4%) hours per week. A wide variety of occupations were represented in the sample, with the largest percentages of participants working in business management and administration (29.3%), information technology (16.2%), and education and training (11.0%).

Descriptive statistics, correlations, and internal consistency estimates for all Study 3 variables are presented in Table 6 . Unless otherwise noted, all items were answered on a 6-point Likert-type scale ranging from 1 ( strongly disagree ) to 6 ( strongly agree ).

To evaluate extra-normative situational strength while teleworking during the COVID-19 pandemic, participants were presented with the original version of the SSW (Meyer et al., 2014 ). However, to draw attention to the extra-normative work implications of teleworking in response to COVID-19, the instructions and rating approach for this scale were modified (see the example screenshot presented in the Appendix). More specifically, participants were instructed to first provide ratings of each situational strength facet when reflecting about their job before teleworking in response to COVID-19 (left-hand side of screenshot) and then to provide ratings when reflecting on their job while teleworking in response to COVID-19 (right-hand side of screenshot). The latter ratings (i.e., while teleworking in response to COVID-19) were used in all subsequent analyses to represent situational strength surrounding this extra-normative work context. Footnote 7 Participants responded to all items on a 7-point Likert-type scale (1 =  Strongly disagree ; 7 =  Strongly agree ). Estimates of internal consistency were acceptable for all facets ( ω  = 0.86–0.93).

Employee Strain

Emotional exhaustion, work anxiety, and job stress perceptions were measured using the same approach as in Study 2 ( ω  = 0.92, 0.94, and 0.88, respectively), with the exception that participants were asked to reflect on their experiences since teleworking in response to COVID-19 (rather than their experiences at a more general level).

Study 3 Results

We first computed a seven-factor measurement model in which the items corresponding to the four facets of situational strength ( clarity , consistency , constraints , consequences ) and the three strain criteria ( emotional exhaustion , work anxiety , job stress ) loaded on their intended factors, which yielded a reasonable fit to the data ( CFI  = 0.90, RMSEA  = 0.06, SRMR  = 0.06). We then computed a structural model in which each facet of situational strength was modeled as a predictor of each strain criteria (see Table 7 for obtained parameter estimates), which also yielded a reasonable fit to the data ( CFI  = 0.90, RMSEA  = 0.06, SRMR  = 0.06).

Hypothesis 4a was not supported, as we had no evidence to suggest that consistency negatively co-varied with any strain criteria ( B  =  − 0.12–0.21, all ns ). Hypothesis 4b was fully supported, as clarity was associated with lower perceived job stress ( B  =  − 0.24, p  < 0.05), work anxiety ( B  =  − 0.55, p  < 0.01), and emotional exhaustion ( B  =  − 0.39, p  < 0.01). In support of Hypothesis 5a, consequences were related to higher perceived job stress ( B  = 0.35, p  < 0.01), work anxiety ( B  = 0.29, p  < 0.01), and emotional exhaustion ( B  = 0.16, p  < 0.05). Finally, and replicating findings from Study 2, Hypothesis 5b was partially supported, with constraints linked to higher emotional exhaustion ( B  = 0.32, p  < 0.01), but not perceived job stress ( B  = 0.04, ns ) or work anxiety ( B  = 0.05, ns ). Drawing on Cohen’s (1988) recommendations for effect size interpretation, the contributions of the set of situational strength facets to perceived job stress ( R 2  = 0.16) and work anxiety ( R 2  = 0.14) approximated a medium-sized effect, while the contributions of these facets to emotional exhaustion ( R 2  = 0.30) reflected a large effect size.

Work demands have long been recognized to push beyond the normative boundaries and expectations of the job (e.g., Meissner, 1971 ), but common perceptual filters underpinning extra-normative work have yet to be considered. Our findings suggest that situational strength is a useful theoretical lens to understand how extra-normative work influences employee strain. More specifically, we showed that (a) perceptions of extra-normative situational strength co-vary with expectations to comply with extra-normative work demands and employee strain, (b) enhancing extra-normative work through some avenues (e.g., consistency, clarity) could help employees to cope with this increasingly ubiquitous phenomenon, but that (c) enhancing extra-normative work by emphasizing or increasing consequences may be counterproductive due to harmful implications for employee strain.

Most notably, our results demonstrate that extra-normative work requests which are perceived to be consequential (e.g., “Make sure to attend this virtual meeting or your boss will be angry”) yield enhanced strain. In contrast, consistency and clarity perceptions co-varied with lower strain in the extra-normative work contexts of after-hours work and teleworking in response to COVID-19, respectively. These findings support our assertion that there are unique insights to be gained from adopting a faceted approach to extra-normative work situational strength when predicting employee strain. Finally, our replication of the relevance of constraints to emotional exhaustion specifically (but not other strain criteria) across multiple extra-normative work contexts suggests that certain facets of situational strength may be differentially relevant to specific manifestations of strain, which may further explain inconsistencies in detecting relationships between situational strength and strain in past research.

Theoretical Implications

At the broadest level, our findings suggest that situational strength may be a common perceptual factor that underlies how employees react to extra-normative work. By its very nature, this work extends employees beyond the typical boundaries of what is expected in their job, which has the potential to lead to ambiguity that causes strain (Beehr, 1976 ). Although the rise and expansion of knowledge work has pushed employees towards working in a more flexible and agile fashion for years (Fenner & Renn, 2010 ), the COVID-19 pandemic has introduced substantial uncertainty into how work will be structured, scheduled, and carried out in the future (Kniffin et al., 2020 ). Perhaps the starkest indicator of this difference in the present study pertains to the differential support for Hypotheses 4a and 4b in Studies 2 and 3, respectively. Namely, in Study 2 (which occurred prior to the pandemic), the influence of increased situational strength on reduced strain was carried primarily through consistency (as opposed to clarity), but in Study 3 (which occurred during the pandemic), the impact of increased situational strength on reduced strain was carried primarily through clarity (as opposed to consistency). Although speculative, one potential explanation of this diverging pattern of associations is that in the more stable/predictable pre-COVID world, knowing when, how, and why extra-normative work was likely to be required in a more consistent fashion helped employees cope with the effects of extra-normative work (e.g., by planning and coordinating accordingly), but in the more unstable/unpredictable world of the COVID-19 pandemic, consistency-based situational strength surrounding extra-normative work was no longer feasible, so employees began to take solace in any extra-normative work messaging that seemed to be logical, transparent, and easy to understand (i.e., entailed greater clarity).

As this example illustrates, the situational strength-based approach advanced here is both strongly theoretically grounded in extant perspectives to work situations (Meyer et al., 2010 ; Mischel, 1977 ), but also adaptable to new extra-normative work arrangements that may arise in the post-pandemic world and beyond. For example, as restrictions are lifted and the world of work begins to establish a new normal (whatever that might look like), perhaps the effects of consistent extra-normative work will return to being the dominant reducer of strain, but if or when the next major disruption hits that alters ways of working, clarity will again become paramount. Thus, our central theoretical contributions have been to demonstrate the broad applicability of situational strength theorizing to work arrangements that involve departures from when, how, and where work is typically done and to show the importance of conveying novel behavioral expectations in a way that is clear and/or consistent, as opposed to focusing on behavioral restrictions and placing contingencies on employees’ actions.

Our application of a multi-faceted view of extra-normative situational strength also helps to explain why the theorized detrimental influence of situational strength on strain has been inconsistently observed in empirical research (Steel et al., 2008 ). While we did observe extra-normative situational strength in the aggregate to co-vary with higher anticipated strain in Study 1, moving to a facet-level perspective in Studies 2 and 3 yielded a more nuanced pattern of results. Specifically, although consequence perceptions were harmful to strain across all criteria observed in all measured extra-normative work contexts, consistency was associated with lower strain in an after-hours work context, whereas clarity was related to lower strain in the context of teleworking in response to COVID-19. It is thus possible that variability in situational strength–strain relationships across different past studies may extend from the extent to which participants in these samples perceived different facets of situational strength, which is likely to be influenced not just by the nature of their jobs (Meyer et al., 2009 ) and proximal sources of information (Alaybek et al., 2017 ), but also by their personality and key demographic considerations (e.g., generational cohort, gender) (Meyer et al., 2014 ). We thus contend that a facet-oriented approach is necessary to understand the strain implications of situational strength because it permits a fine-grained assessment into the specific ways in which individuals respond to strength as communicated in various ways from various sources.

Theorists have typically positioned situational strength as a boundary condition for work-relevant relationships, such as the influence of personality (Meyer et al., 2009 ) or job satisfaction (Bowling et al., 2015 ) on job performance. In contrast, little consideration has been given to the direct prediction of employee outcomes from situational strength. Moreover, organizational research on situational strength has typically focused on perceptions of the job in general (Meyer et al., 2010 ), rather than more discrete aspects of context (Johns, 2006 ). By examining situational strength surrounding extra-normative work and expanding the nomological network of this strength to encompass the direct prediction of strain criteria, we push the boundaries of theorizing surrounding job-related situational strength and provide a roadmap for future applications of this construct. One particularly interesting application for future research that would capitalize on the interactionist tendencies of past situational strength work would be to longitudinally explore whether the occurrence of extra-normative work interacts with situational strength in predicting strain criteria over time. For example, it would be plausible that potential strain-inducing aspects of extra-normative work may have a more pronounced impact on strain criteria in strong jobs wherein extra-normative work represents a more profound deviation from typical expectations and a less impactful effect on strain criteria in weak jobs that might be characterized by a more “expect the unexpected” type mentality. Longitudinal research of this nature would be a natural extension of the foundation for applications on the extra-normative work construct that we have developed here.

When considering constraint perceptions specifically, only emotional exhaustion was supported as a correlate of this facet, a finding replicated across the after-hours work and teleworking in response to COVID-19 extra-normative work contexts. This finding suggests that some facets of situational strength may be selectively related to certain indicators of employee strain. Emotional exhaustion is a symptom of the chronic strain condition of burnout (Maslach et al., 2001 ), the development of which has been argued to be accelerated by organizationally imposed constraints (Leiter, 1991 ). In particular, constraints have long been recognized to be a major driver of employee frustration (O’Connor et al., 1982), which is a precursor to the development of burnout (Lewandowski, 2003 ). Future research directly targeted at understanding if and why extra-normative constraints are particularly relevant to emotional exhaustion, relative to other strain criteria, may benefit from considering the process and timescale by which reactions to extra-normative situational strength unfold.

Practical Implications

Our approach illustrates a strategy for reducing employee strain in situations that push employees to work beyond the boundaries of their typical work role. Providing consistency in policies, communications, and actions surrounding the need for extra-normative work may be an effective way to encourage meeting atypical work demands without sacrificing employee well-being. Furthermore, providing clear and easily understandable communications surrounding extra-normative work expectations appears key to mitigating strain within the specific extra-normative work context of teleworking in response to COVID-19. In contrast, constraint-based strategies to framing extra-normative work seem to engender emotional exhaustion and consequence-based strategies may be more generally counterproductive as they are likely to drive multiple aspects of employee strain that can influence health and performance (Bakker & Demerouti, 2017 ; Calderwood et al., 2018 ; Igic et al., 2017 ). We encourage organizations to be more cognizant of how extra-normative work demands and requests are framed in the service of diminishing employee strain, which is crucial to maintaining organizational effectiveness over time (Beehr & Newman, 1978 ).

Limitations

Our findings are contextualized by several limitations common to all three studies. First, all variables were measured via self-reports, which are subject to biases and distortions that may inflate measurement error (Donaldson & Grant-Vallone, 2002 ). We encourage future research to evaluate whether the strain implications of subjective perceptions of extra-normative situational strength may differ from more objective features of the work environment that impact situational strength. Utilizing objective sources of data that could be coded for factors relevant to situational strength, such as full-text e-mails (Butts et al., 2015 ), may also allow for direct comparisons of objective and perceptual factors relevant to extra-normative situational strength and its relationships with criteria.

In addition, data in all three studies were collected at a single point in time, which left us unable to establish how stable extra-normative situational strength is over time. Future research may benefit from efforts to understand how within-person variability in extra-normative situational strength may impact shorter-term strain criteria (e.g., insufficient daily recovery from work-related effort expenditure; Sonnentag, 2001 ). Investigations of this nature may add additional nuance to how extra-normative situational strength influences strain over time, as it is conceivable that some facets of situational strength (such as consequences connected to the completion or lack of completion of daily extra-normative work tasks) may show greater intra-individual variability than other facets of situational strength (such as the consistency with which extra-normative work expectations are communicated) over time.

Across three empirical studies, we demonstrated that situational strength is a useful framework to understand extra-normative work arrangements, in which employees work outside the boundaries of their typical work role. Results demonstrated that extra-normative situational strength predicts strain criteria, with diverging positive and negative implications of this situational strength depending on the specific facets considered. As such, situational strength provides an adaptable perspective to understand how changes in the nature, timing, and location of work may influence employee strain, while also providing practitioners with guidance in how best to communicate extra-normative work expectations to employees.

While we did not include an exhaustive set of measures of all constructs discussed in this section in the data collections which are subsequently reported, we did include measures of OCBs directed towards individuals and organizations (Williams & Anderson, 1991 ) and boundary-spanning work demands (which are likely at least partially relevant to engagement in technology-assisted supplemental work; Voydanoff, 2005 ) in Studies 2 and 3, and also included a measure of segmentation preferences (Kreiner, 2006 ) in Study 3. These indicators were at most modestly correlated with facets reflecting extra-normative situational strength across both studies ( r  =  − .35 to .31), which bolsters the contention that extra-normative work can be distinguished from several of these existing constructs in the literature.

Vignettes have been used to manipulate situational strength perceptions in past studies (Meyer et al., 2014 ). Further, predicted behavior, exhaustion, and affect have been evaluated as a function of exposure to vignettes in past research (e.g., Breen & Kashdan, 2011 ; Cameron et al., 2015 ; Chen et al., 2016 ).

The range of reliability estimates reflects internal consistency estimates across the three different vignettes.

We computed two additional robustness checks to bolster confidence in the findings obtained in the main model results. First, we recomputed a supplemental model in which we allowed slopes indexing relationships of condition ( Strong , Weak ) to each criterion variable to vary randomly across individuals. Our results were fully robust in this alternative model, and we also did not observe evidence to suggest the presence of random slope variability indexing these relationships across any measured criterion variable ( γ  = .01–.29, all ns ). Second, we recomputed the original model with an additional statistical control included reflecting the pattern of condition assignment across the three vignettes. More specifically, we entered a block of dummy coded variables to represent the eight possible combinations of ways in which participants could be randomly assigned to the Weak or Strong condition across the three vignettes as a predictor of each criterion variable. All model results were also fully robust when statistically controlling for the pattern of condition assignment across the three vignettes.

The latter inclusion criteria were present because this study is part of a larger project that incorporates how employees perceive their domestic and childcare demands.

While our hypotheses specifically focused on the bivariate relationships of each situational strength facet with strain criteria, because past scale validation work suggests that situational strength facets are positively correlated (Meyer et al., 2014 ), we elected to enter situational strength facets simultaneously when predicting strain criteria to allow us to understand the unique influence of each facet on each criterion when partialling out the influence of the other three facets.

While longitudinal change processes surrounding a transition to extra-normative work are not our core focus in this initial effort to conceptually develop and evaluate the extra-normative work construct, we did evaluate for exploratory purposes whether ratings of the facets of situational strength changed when moving from the normative work context of one’s regular work situation to the extra-normative work context of abruptly teleworking in response to COVID-19. Comparing participant ratings from before to while teleworking in response to COVID-19, we found that perceptions of clarity ( t (289)  =  − 7.21, p  < .01, d  = .42), consistency ( t (289)  =  − 5.00, p  < .01, d  = .29), constraints ( t (289)  =  − 2.16, p  < .05, d  = .13), and consequences ( t (289)  =  − 2.20, p  < .01, d  = .13) all decreased when moving to the extra-normative work context of abruptly teleworking in response to COVID-19.

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Adaptation of Situational Strength at Work Scale to After-Hours Work Context

Instructions. The following statements assess your beliefs about your “ after-hours work ” – that is, work performed for your job that you complete outside of your regular work hours (e.g., conference calls during evenings after work, weekend travel for work, checking e-mails during vacations and holidays) . Using the scale below, please rate the extent of your agreement with each statement as it pertains to your after-hours work (Table 8 ).

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Calderwood, C., Meyer, R.D. & Minnen, M.E. Situational Strength as a Lens to Understand the Strain Implications of Extra-Normative Work. J Bus Psychol 38 , 637–655 (2023). https://doi.org/10.1007/s10869-022-09846-8

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Original research article, situational strength cues from social sources at work: relative importance and mediated effects.

• 1 Department of Psychology, George Mason University, Fairfax, VA, United States
• 2 C 2 Technologies, Inc., Vienna, VA, United States
• 3 DCI Consulting Group, Inc., Washington, DC, United States

Situational strength is considered one of the most important situational forces at work because it can attenuate the personality–performance relationship. Although organizational scholars have studied the consequences of situational strength, they have paid little attention to its antecedents. To address this gap, the current study focused on situational strength cues from different social sources as antecedents of overall situational strength at work. Specifically, we examined how employees combine situational strength cues emanating from three social sources (i.e., coworkers, the immediate supervisor, and top management). Based on field theory, we hypothesized that the effect of situational strength from coworkers and immediate supervisors (i.e., proximal sources of situational strength) on employees' perceptions of overall situational strength on the job would be greater than the effect of situational strength from the top management (i.e., the distal source of situational strength). We also hypothesized that the effect of situational strength from the distal source would be mediated by the effects of situational strength from the proximal sources. Data from 363 full-time employees were collected at two time points with a cross-lagged panel design. The former hypothesis was supported for one of the two situational strength facets studied. The latter hypothesis was fully supported.

Introduction

“To explain social behavior it is necessary to represent the structure of the total situation and the distribution of the forces in it.”

—Kurt Lewin (1939; p. 868).

As Lewin (1939) stated, a central predictor of human behavior is the situation within which the behavior is enacted. An important characteristic of the situation is its “strength.” Situational strength is defined as “implicit or explicit cues provided by external entities regarding the desirability of potential behaviors” ( Meyer et al., 2010 ). Strong situations can pressure individuals to act in similar ways by providing very clear indicators as to what behavior is most appropriate ( Mischel, 1968 ; Meyer et al., 2010 ). For example, a red traffic light represents a strong situation in which the appropriate behavior is to stop one's vehicle; in contrast, a yellow traffic light is a weak situation in which some drivers may stop whereas others may attempt to speed through the intersection before the light turns red ( Mischel, 1977 ; Cooper and Withey, 2009 ). Examples of strong situations in organizational settings might include a formal dress code, an organizational motto such as “The Customer is King/Queen,” and very specific instructions from a supervisor regarding how to perform a task.

Because of its potential to influence (i.e., inhibit or produce) behavioral variation, social scientists have referred to situational strength as “the most important situational moderating variable” ( Snyder and Ickes, 1985 ; p. 904). Within the context of the workplace, situational strength has been conceptualized as a multifaceted construct that includes the clarity of the situational cues from the environment, the consistency of the different situational strength cues, the constraints on the employee's freedom of decision and action, and the consequences of workplace decisions and actions ( Meyer et al., 2010 , 2014 ). Meyer et al. (2014) found weak-to-moderate relationships ( r = −0.22 to 0.49) between the facets and several job characteristics, including feedback (i.e., information from external sources regarding one's performance; Kluger and DeNisi, 1996 ), role conflict (i.e., the incompatibility or incongruence of different job requirements; Rizzo et al., 1970 ), autonomy (i.e., “the degree to which the job provides substantial freedom, independence, and discretion to the individual in scheduling the work and determining the procedures to carry it out”; Hackman and Oldham, 1974 ; p. 258), and production responsibility (i.e., “the cost of errors in terms of both lost output and damage to expensive equipment”; Jackson et al., 1993 ; p. 754).

These at-best moderate empirical relationships can be explained by the fact that situational strength differs from the other situational constructs in terms of breadth. For example, notwithstanding the similarity in nomenclature, the situational strength facet of constraints is more general than older conceptualizations of constraints (cf. Peters and O'Connor, 1980 ): although both conceptualizations pertain to a reduction in the number of options available to the employee (due to restrictions imposed by, for example, the supervisor), the older conceptualization further assumes that only good options are abridged whereas the situational strength conceptualization is concerned with the extent to which options of all kinds are abridged ( Meyer et al., 2010 ). As another example, the situational strength facet of clarity encompasses role clarity (i.e., information that defines the boundaries of the employee's work roles), work behavior prescribed by organizational and societal culture ( Gelfand et al., 2006 ), instructions from the supervisor regarding how to perform tasks properly, and coworker-generated norms regarding backing-up behavior ( Meyer et al., 2010 , 2014 ). As these examples suggest, situational strength represents a broad, psychologically-based conceptualization of situational forces applicable across a variety of situational units (e.g., jobs/occupations, roles, tasks, events; Dalal et al., 2014 ).

Many organizational scientists have highlighted situational strength as an important psychological construct in the workplace because of its outcomes ( Johns, 2006 ; Meyer et al., 2010 ): most notably, the fact that it weakens the extent to which employee behavior can be predicted via employee personality ( Murphy, 2005 ; Meyer et al., 2014 ). In particular, several studies have examined situational strength vis-à-vis the validity of the Big Five personality traits (i.e., agreeableness, conscientiousness, extraversion, neuroticism, and openness to experience; McCrae and Costa, 1985 ; Costa and McCrae, 1992 1 ) in the prediction of job performance. For example, a meta-analysis found that the relationship between the personality trait of conscientiousness and job performance was weaker in occupations characterized by strong situations (e.g., “nuclear equipment operation technicians”; Meyer et al., 2009 ; p. 1,088) than in occupations characterized by weak situations (e.g., “poets, lyricists, and creative writers”; Meyer et al., 2009 ; p. 1,088). A more recent meta-analysis found that all the Big Five personality traits were less predictive of job performance in occupations where work processes involved strong situations (e.g., structured work, decision-making constraints) than in occupations where work processes involved weak situations (e.g., unstructured work, decision-making autonomy; Judge and Zapata, 2015 ). As another example, a recent large-sample study of 17 manufacturing organizations found that the relationship between conscientiousness and employee safety-related behavior was weaker in organizations characterized by strong safety climates (i.e., strong safety-related situations) than in occupations characterized by weak safety climates (i.e., weak safety-related situations; Lee and Dalal, 2016 ). As for employees' perceptions of overall situational strength on their jobs, a recent field study found that the effects of two personality traits (conscientiousness and agreeableness) on organizational citizenship behavior (i.e., a dimension of job performance defined as voluntary behavior that improves the functioning of the organization and benefits its members; Dalal, 2005 ) were weaker for employees who perceived the situational strength associated with their job to be high than for those who perceived it to be low ( Meyer et al., 2014 ). Several additional examples exist in the organizational literature (e.g., Barrick and Mount, 1993 ; Bowling et al., 2015 ).

Although organizational scientists have acknowledged the importance of the outcomes of situational strength on the job (as indicated by the examples in the previous paragraph), little attention has thus far been paid to the antecedents of situational strength. To date, three conceptual papers have discussed the potential antecedents of situational strength at work. The first conceptual paper proposed that the strength of societal culture (i.e., the degree to which deviance from norms is tolerated in societies characterized by different cultures) would exert cross-level effects on the strength of organizational cultures ( Gelfand et al., 2006 ). The second conceptual paper proposed that situational strength on the job would be created by (among others) various interpersonal sources in the organization, and would be communicated through channels such as formal policies and procedures and informal norms ( Meyer et al., 2010 ). The third conceptual paper proposed that an individual's perceptions of situational strength cues would be influenced by the strength of the individual's personality (indicated by the consistency of personality-relevant behavior across situations; Dalal et al., 2015 ). The mechanisms proposed in these conceptual papers have not yet been empirically studied in relation to employees' perceptions of situational strength at work. This is unfortunate because prediction, explanation, and control—the goals of science—require research on antecedents of the construct. Thus, the current study focuses on where (within an organization) the situational strength cues emanate (i.e., sources of situational strength) and how employees combine the situational strength cues emanating from different sources.

Knowledge of the sources of situational strength would provide us with a better psychological understanding of how people experience the situational forces acting on them. This understanding, in turn, would advance situational strength theory. It would also facilitate the more applied goal of shaping situational strength to achieve desired effects. Consider an organization that wishes to create strong situations encouraging the enactment of conscientious behavior even by employees who score low on dispositional (i.e., trait) conscientiousness ( Meyer et al., 2009 ). For instance, to increase situational strength in terms of social inclusion of individuals with disabilities, it would be beneficial for top management to identify and train allies who can demonstrate inclusive behavior, reemphasize organizational policies, and confront social exclusion at different units in the organization ( Sabat et al., 2014 ). To accomplish this objective successfully, top management would need to understand the situational strength implications of the various human resources practices at different organizational units ( Dalal and Meyer, 2012 ), which is possible by understanding how employees combine the situational strength emanating from different sources.

Sources of Situational Strength at Work

A number of important sources can influence an employee's perceptions of overall situational strength on the job. Drawing from the literature on reference group and role theories ( Gouldner, 1957 , 1958 ; Blau and Scott, 1962 ; Adams, 1976 ; Aldrich and Herker, 1977 ; Salancik and Pfeffer, 1978 ; Reichers, 1985 ; Becker, 1992 , 2009 ; Becker and Billings, 1993 ; Judge and Locke, 1993 ; Becker et al., 1996 ), sources of situational strength could be categorized into two broad categories: Internal sources (i.e., sources that are inside the organization, such as coworkers) and external sources (i.e., sources that are outside the organization, such as customers).

The current paper examines the situational strength emanating from three internal sources—namely, coworkers, the immediate supervisor, and top management. These are the three social situational sources that have been most studied by organizational researchers interested in examining employee reactions (e.g., job satisfaction) to various aspects of the work situation ( Dalal et al., 2011 ). The reason extant research on job satisfaction considers these three sources to be particularly worthy of research focus—and the reason we do as well—is that only certain types of employees deal with customers, vendors, or other external social sources, whereas virtually all employees deal with top management, the immediate supervisor, and coworkers ( Smith et al., 1969 ; Dalal et al., 2011 ). Therefore, research on the three social sources of situational strength should be applicable to virtually all employees in virtually all organizations.

We use field theory ( Lewin, 1939 , 1943 , 1951 ) to examine how employees make sense of the behavioral cues emanating concurrently from these three social sources to form a unified perception of situational strength on the job. Field theory posits that the environment surrounding an individual can be conceived of as a field or system of forces, and that the behavior of an individual in a specific situation is a function of the individual's personality and various situational forces ( Lewin, 1939 , 1943 ). Situations may emerge as barriers and opportunities to express behavior ( Lewin, 1951 ); these represent strong and weak situations, respectively ( Mischel, 1968 ). Here, we elaborate on how situational strength from different sources might emerge in an organizational setting.

Organizational research has long established that organizations are social systems ( Katz and Kahn, 1978 ) consisting of interrelated entities such as employees, clients, and managers ( Blau and Scott, 1962 ; Salancik and Pfeffer, 1978 ). Organizational entities (also called “role senders”) seek to motivate employees to behave in certain ways to achieve work-related goals ( Reichers, 1985 ). As such, organizational entities compose various sources of situational strength, varying in their nature and in the level of abstraction of informational cues guiding employee behavior.

The three social sources, which are the focus of the current study, can be distinguished on the basis of theories of organizational structure (e.g., Stratified Systems Theory; Jaques, 1976 ). These theories posit that organizations can be viewed as having five hierarchical levels: Front-line employees, first-line supervisors, middle managers, directors, and top management (or “C-suite” executives such as the Chief Executive Officer and the Chief Financial Officer). The focal employees in the current paper are employees who fall within any of the first three hierarchical levels. Moreover, based on previous research showing that employees do not make fine-grained distinctions between specific levels of management higher than their immediate supervisor ( Herzberg et al., 1957 ; Dalal et al., 2011 ), the current paper distinguishes only between the immediate supervisor and top management.

Coworkers act as the employee's social and task partners ( Chiaburu and Harrison, 2008 ). Immediate supervisors allocate tasks, provide performance feedback, and communicate the organizational goals set by top management ( Jacobs and McGee, 2001 ; Zaccaro and Klimoski, 2001 ). Top management creates and communicates strategic vision throughout the organization ( Jacobs and McGee, 2001 ; Zaccaro and Klimoski, 2001 ) and influences the behavior of employees through interventions geared toward formal reward systems, technological factors (e.g., work flow process), physical settings (e.g., architectural design), and social factors (e.g., interactive processes at the individual, group, and intergroup levels; Cardy and Selvarajan, 2001 ). As a result of these differences in the functions and communications of the sources of situational strength, each source should provide a part of the whole amount of situational strength exerted on an employee ( Locke, 1976 ; Judge and Locke, 1993 ).

Indirect evidence for this notion comes from two meta-analyses. The first meta-analysis demonstrated that contextual variables from various sources (e.g., the leader, task properties) typically exhibit incremental validity over each other vis-à-vis criteria such as job attitudes and performance ( Podsakoff et al., 1996 ). The second meta-analysis demonstrated that social influences from coworkers provide incremental validity beyond social influences from leaders vis-à-vis criteria such as job involvement and withdrawal ( Chiaburu and Harrison, 2008 ). As such, we predict that all three sources of situational strength contribute uniquely to employee perceptions of overall situational strength:

Hypothesis 1: Perceptions of situational strength from coworkers, the immediate supervisor, and top management explain unique variance in perceptions of overall situational strength on the job .

Moreover, according to field theory, the psychological distances of environmental factors from the employee predict their level of impact on the employee's behavior ( Lewin, 1943 ). Specifically, psychologically proximal factors tend to exert stronger effects than psychologically distal factors. In organizations, psychological distance has been conceptualized as the frequency of meaningful interaction: the greater the frequency of meaningful interactions an employee has with a source, the more proximal the source should become to the employee ( Becker, 2009 ). Employees likely work in closer physical proximity to and have more frequent interactions with coworkers and immediate supervisors than with top management ( Allen, 1977 ; Sias and Cahill, 1998 ). As a result of close proximity and shared goals, employees develop close friendships with their coworkers ( Sias and Cahill, 1998 ), and they report stronger feelings of attachment and identification with both coworkers and immediate supervisors than with top management ( Becker, 1992 ). Moreover, top management can be distanced from the employees in terms of hierarchical rank or social status, suggesting that employees have a lower sense of attachment and identification with top management ( Bloom, 1999 ; Halevy et al., 2011 , 2012 ).

These findings suggest that employees have more frequent meaningful interactions with their coworkers and immediate supervisors than with their top management. In sum, coworkers and the immediate supervisor are considered to be more proximal sources of situational strength and top management is considered to be a more distal source of situational strength. We therefore suggest that psychologically proximal sources of situational strength have stronger effects than psychologically distal sources on employees' perceptions of overall situational strength on the job:

Hypothesis 2: Psychological proximity positively predicts perceptions of overall situational strength on the job, such that the effect of more proximal sources (i.e., situational strength attributable to coworkers and the immediate supervisor) on overall situational strength is stronger than the effect of the more distal source (i.e., situational strength attributable to top management) .

Another characteristic of the work situation in general, and therefore situational strength in particular, is that the situation at one level of analysis can influence the situation at another level, and that this multilevel influence can manifest in a top-down manner ( Johns, 2006 ). Along these lines, the distal-proximal framework of motivational theories posits that the influence of distal motivational predictors is transmitted through proximal motivational predictors ( Kanfer, 1991 ). Extant applications of this approach relevant to the current study are found in organizational leadership research. For example, Osborn et al. (2002) postulated that the stronger a top leader's connections with his or her subordinate managers, the more likely he or she would be to influence the work environment of those at the bottom of the organizational hierarchy. Berson and Avolio (2004) showed that information regarding strategic organizational goals (which are set by CEOs) was disseminated to department managers through vice presidents and division managers. Similarly, Mayer et al. (2009) showed that the ethical leadership behavior of supervisors mediates the relationships between the ethical leadership behavior of top management and outcomes (i.e., organizational citizenship behavior and counterproductive work behavior) at lower levels of the organizational hierarchy. As such, we hypothesize the following:

Hypothesis 3: The relationship between perceptions of situational strength (SS) from the distal source (i.e., top management) and perceptions of overall situational strength is mediated by perceptions of situational strength from proximal sources (i.e., coworkers and immediate supervisor) .

The overall conceptual model is displayed in Figure 1 .

Figure 1 . Conceptual model. CW, Coworkers; IS, The immediate supervisor; TM, Top management.

Participants and Procedure

We recruited respondents through Amazon.com's Mechanical Turk (MTurk), an online labor market where requesters (e.g., researchers) recruit workers (e.g., respondents) for the completion of human intelligence tasks (e.g., surveys) in exchange for compensation. Research has shown that MTurk participants provide data at least as reliable as data obtained through traditional research methods ( Buhrmester et al., 2011 ; Holden et al., 2013 ). In recent years, MTurk has become an increasingly popular recruitment tool among social scientists ( Amir et al., 2012 ; Fast et al., 2012 ; Crump et al., 2013 ; Giacopelli et al., 2013 ) because it provides instant access to a respondent pool with wide demographic diversity ( Ipeirotis, 2010 ; Casler et al., 2013 ).

We used a cross-lagged panel design ( Farrell, 1994 ; Kline, 2011 ) to collect survey data on the focal variables at two time points, separated by 2 weeks 2 . In accordance with this design, the focal variables (i.e., overall situational strength and situational strength from the three sources) were measured at both time points (see Table 1 for details), and all the other variables (i.e., demographics, frequency of interaction with the sources, and identification with the sources) were measured at Time 1 only. Sample sizes for Time 1 and Time 2 were 451 and 372, respectively (82% retention rate across time points). Nine cases were excluded because they showed one or more abnormal response patterns ( Johnson, 2005 ; Huang et al., 2012 ) associated with insufficient effort responding: namely, had more than 50% missing data, included the same response to all situational strength items, and/or had survey completion times greater than two standard deviations from the mean ( McGrath et al., 2010 ). Elimination of these 9 cases led to an effective sample size of 363, which included four cases with less than 50% missing data. Individual analyses were conducted with complete cases (using listwise deletion of missing data). The sample sizes for individual analyses after listwise deletion varied between 359 and 363 3 .

Table 1 . Situational strength measure modified from Meyer et al. (2014) .

The final sample consisted of 55% U.S. and 45% Indian employees, was 29% female, and had a mean age of 33 years (SD = 9.30 years). As per the requirements for participation in the study, all respondents were fluent in English, worked at least 30 h per week in an organization with at least 50 employees (i.e., had a sufficient number of coworkers), and had at least two levels of management above them (i.e., had separate immediate supervisor and top management personnel).

The survey was administered using Qualtrics ( http://www.qualtrics.com ), an online platform for researchers to develop and administer survey questionnaires through the Internet. For reasons discussed subsequently, two facets of situational strength were assessed: clarity and constraints ( Meyer et al., 2010 ). For each facet of situational strength, we measured perceived situational strength emanating from three sources (coworkers, the immediate supervisor, and top management) as well as overall situational strength. Situational strength items for each facet-source combination were presented on a separate page of the survey. The order of the pages, and of the items within a page, was randomized so as to prevent order effects.

We measured perceived situational strength using an adapted version of Meyer et al.'s Situational Strength at Work (SSW) scale ( Meyer et al., 2014 ). The original scale included four facets of situational strength (i.e., clarity, constraints, consistency, and consequences). However, in the current study, due to the need to measure multiple sources of situational strength associated with each facet of situational strength, survey length constraints precluded the possibility of assessing all four facets of situational strength.

We therefore included measures of one “positive” and one “negative” facet of situational strength (see José et al., 2011 ). A positive facet of situational strength is one that is related positively to job attitudes (e.g., job satisfaction and organizational commitment) and one for which an inadequate supply of situational strength (i.e., preferred levels < actual levels) leads to worse job attitudes than an excess supply (i.e., actual levels > preferred levels). A negative facet, in contrast, is one that is related negatively to job attitudes and one for which an excess supply of situational strength leads to worse job attitudes than an inadequate supply. The situational strength facet of consequences (i.e., the extent to which workplace decisions and/or actions have important implications; Meyer et al., 2010 ) can involve both positive and negative consequences to the employee; hence, we did not include it.

We also did not include the facet of consistency. This facet (a positive situational strength facet) is typically defined as the congruency across various sources of situational strength ( Meyer et al., 2010 ). As a result, this facet is incompatible with the current paper's purpose of “unpacking” the various sources of situational strength.

We therefore focused on the remaining two facets of situational strength: clarity (i.e., “the extent to which cues regarding work-related responsibilities or requirements are available and easy to understand”, Meyer et al., 2010 ; p. 125) and constraints (i.e., “the extent to which an individual's freedom of decision and action is limited by forces outside his or her control”, Meyer et al., 2010 ; p. 126). See Table 1 for items, instructions, and response options.

Psychological distance from the sources of situational strength was assessed via frequency of interaction and identification with sources of situational strength. See Table 2 for items and response options. See Table 3 for descriptive statistics, scale reliabilities, and inter-correlations for all measures.

Table 2 . Measures of frequency of interaction and identification with sources of situational strength.

Table 3 . Descriptive statistics, scale reliabilities, and inter-correlations.

We additionally assessed longitudinal measurement invariance (in Mplus 7) for the situational strength measures so as to ensure that respondents interpreted these measures in a conceptually similar manner at both time points. According to the approach recommended by Vandenberg and Lance (2000) , we tested for longitudinal measurement invariance with a confirmatory factor analysis (CFA) approach. First, to establish a baseline fit (also referred to as configural invariance), we conducted a multi-sample analysis with the same factor structure within each group but no invariance restriction on loadings. Next, to evaluate whether the participants attributed the same meanings to the latent constructs across time points (also referred to as metric invariance), we re-estimated the measurement model with an equality constraint placed upon factor loadings across two time points. To evaluate whether the meanings and the mean levels of the latent constructs remained the same across time points, we tested the scalar invariance by setting factor loadings as well as intercepts to be equal across time points 4 . As can be seen in Table 4 , metric invariance was demonstrated for both clarity and constraints (with scalar invariance furthermore being demonstrated for constraints), indicating that the latent constructs of situational strength (i.e., clarity and constraints) were equally well represented across both time points by the measure used in the study.

Table 4 . Longitudinal measurement invariance results.

Hypothesis 1 stated that perceptions of situational strength from each source would explain unique variance in perceptions of overall situational strength on the job. Hypothesis 2 built on this by stating that the effects of proximal sources of overall situational strength on the job would be stronger than those of the distal source. The assumption underlying Hypothesis 1 was that employees would distinguish among situational strength cues emanating from different sources. We began by testing this assumption with CFA. The results (see Table 5 ) showed that, for both clarity and constraints at both time points, a 4-factor model with situational strength from coworkers, situational strength from the immediate supervisor, situational strength from top management, and overall situational strength as distinct factors fit the data well and significantly better than not only a 1-factor model (whereby all situational strength items of a facet at a given time load on a single construct) but also all possible 3-factor models (all chi-squared difference tests yielded p < 0.01). The assumption that employees would distinguish among situational strength from different sources was therefore supported.

Table 5 . Confirmatory Factor Analysis (CFA) results for Hypothesis 1.

The assumption underlying Hypothesis 2 was that coworkers and the immediate supervisor were more proximal sources of situational strength and that top management was a more distal source of situational strength. Mean levels of frequency of interaction and identification with the sources of situational strength (see Table 3 ) and comparisons of the means for proximal vs. distal sources (see Table 6 ), which showed significant differences ( p < 0.01), revealed support for this assumption.

Table 6 . Frequency of interaction and identification: comparison of proximal vs. distal sources.

Moreover, as can be seen in Table 3 , situational strength scores from the three sources (i.e., the predictors in this study) were significantly ( p < 0.05) and positively inter-correlated. When using multiple, meaningfully correlated predictors, both bivariate correlations and regression coefficients from the full model (containing all predictors) can provide misleading conclusions regarding the relative importance of predictors—and therefore a technique such as relative weight analysis is preferred ( LeBreton et al., 2007 ). Relative weight analysis reveals the unique contribution of each predictor variable to the overall model R 2 considering the existence of other predictors ( LeBreton et al., 2007 ). We used Tonidandel and LeBreton (2015) RWA-WEB tool to obtain the relative weight of proximal vs. distal sources of situational strength—and thereby to test Hypotheses 1 and 2.

Analyses were performed separately for the clarity and the constraints facets of situational strength. In all analyses, the criterion (i.e., overall clarity or overall constraints) measured at Time 2 was regressed on the predictors (i.e., clarity or constraints from the sources) measured at Time 1, with overall situational strength measured at Time 1 used as a statistical control, as recommended for evaluating causal relationships in two-wave longitudinal studies ( Cole and Maxwell, 2003 ).

Table 7 summarizes the relative weight analysis results. For comparison purposes, standardized regression weights (β) are also reported. The lower bound of the 95% confidence interval for the relative weights excluded zero for every source of the clarity and constraints facets of situational strength—thereby supporting Hypothesis 1. In contrast, support for Hypothesis 2 depended on the facet of situational strength under consideration. For clarity, the rescaled relative weights for coworkers and the immediate supervisor were actually lower than the rescaled relative weight for top management—thereby falsifying Hypothesis 2. For constraints, however, the rescaled relative weights for coworkers and the immediate supervisor were higher than the rescaled relative weight for top management—thereby supporting Hypothesis 2.

Table 7 . Summary of relative weight analyses for the effect of situational strength from sources on overall situational strength.

Hypothesis 3 , which stated that the relationship between perceptions of situational strength from the distal source and perceptions of overall situational strength would be mediated by the perceptions of situational strength from proximal sources, was tested separately for clarity and constraints via mediation analyses in SPSS using Hayes's PROCESS macro with 1,000 bootstrap samples ( Hayes, 2013 ). Following recommendations for longitudinal mediation ( Cole and Maxwell, 2003 ; MacKinnon et al., 2007 ), we tested two mediation models (summarized in Figures 2 , 3 and Tables 8 , 9 ). Figure 2 and Table 8 show that the effect of perceptions of clarity from top management on perceptions of overall clarity is partially mediated by perceptions of clarity from coworkers and the immediate supervisor. Figure 3 and Table 9 show that the effect of perceptions of constraints from top management on perceptions of overall constraints is fully mediated by perceptions of constraints from coworkers and the immediate supervisor. In sum, Hypothesis 3 is supported 5 .

Figure 2 . PROCESS results for clarity facet of situational strength. N = 363; * p < 0.05, ** p < 0.01; CW, Coworkers; IS, The immediate supervisor; TM, Top management; T1, Time 1; T2, Time 2; Overall Clarity, Perceptions of overall clarity on the job.

Figure 3 . PROCESS results for constraints facet of situational strength. N = 362; * p < 0.05, ** p < 0.01; CW, Coworkers; IS, The immediate supervisor; TM, Top management; T1, Time 1; T2, Time 2; Overall Constraints, Perceptions of overall constraints on the job.

Table 8 . Mediation of the effect of clarity from top management on overall clarity through clarity from the immediate supervisor and from coworkers.

Table 9 . Mediation of the effect of constraints from top management on overall constraints through constraints from the immediate supervisor and from coworkers.

Given the importance of situational strength in predicting employees' behavior and the assumption that situational strength can be exerted on employees by multiple sources simultaneously, it is important to assess how employees develop perceptions of overall situational strength on the job. The current paper sought to answer this question with a focus on situational strength from both distal (i.e., top management) and proximal (i.e., coworkers and the immediate supervisor) sources. We moreover examined the impact of these three sources with regard to two facets of situational strength: clarity and constraints. Confirmatory factor analyses showed that employees distinguished between the various sources of situational strength. Relative importance analyses showed that, as hypothesized, perceptions of both clarity and constraints from each of the three sources explained unique variance in the perceptions of overall situational strength.

With regard to the relative importance of situational strength from the sources, as hypothesized, employees attached more importance to constraints from proximal sources compared to constraints from the distal source. Contrary to expectations, however, employees attached more importance to clarity from the distal sources compared to clarity from proximal sources. Finally, as expected, proximal sources mediated the effect of the distal source on overall situational strength for both clarity and constraints.

How might the unsupportive relative importance results in the case of clarity be explained? In other words, why does clarity from the distal source have a greater impact than clarity from the proximal sources on overall clarity? A way to approach this question is to build on our previous discussions on the nature of situational strength emanating from the sources.

The impact of top management on the employee may operate through multiple channels. For example, as alluded to previously, top management may shape organizational arrangements such as formal reward systems, technological factors such as work flow processes, and even physical settings such as architectural design ( Cardy and Selvarajan, 2001 )—all of which influence employee behavior. Moreover, top management, charged with the strategic planning for the entire organization, creates a vision and establishes broad, long-term goals ( Jacobs and McGee, 2001 ; Zaccaro and Klimoski, 2001 ). Top management's messages reflecting the organization's values and long-term objectives—perhaps communicated to every employee through periodic organization-wide emails—could help the employee see the “big picture” and put the employee's job tasks into context. In other words, whereas communications from the immediate supervisor may help the employee understand what to do, communications from top management may help the employee understand the overarching rationale for what he or she is doing. Consequently, the perceived clarity of informational cues emanating from top management may be more influential than the perceived clarity of informational cues from proximal sources in forming the employee's perceptions of overall clarity on the job.

These arguments are consistent with findings from job satisfaction research, which indicate that top management sometimes exerts an effect on the employee that is stronger than the effects of more proximal sources such as the immediate supervisor and coworkers ( Dalal et al., 2011 ). The arguments are also consistent with findings from organizational communication studies that have examined the relative importance of employees' perceived communication relationships with and quality of information from coworkers, supervisors, and top management ( Putti et al., 1990 ; Allen, 1992 ). These studies found that communication and information from top management had the greatest impact on employees' levels of organizational commitment (because of their impact on employees' sense of organizational membership and their perceptions of organizational climate).

Future research could therefore use qualitative content and discourse analysis techniques (e.g., Atay et al., 2015 ) to examine the themes that emerge from situational strength-related written and verbal messages received by employees from various organizational sources. Future research could also assess perceptions of situational strength from additional sources (e.g., non-social sources such as the nature of the work itself, Meyer et al., 2009 ; external social sources such as clients/customers, Oliver et al., 2016 ) as well as perceptions relevant to additional facets of situational strength not included in the current study (e.g., consistency and consequences, Meyer et al., 2014 ). Of course survey length constraints preclude the simultaneous examination of large numbers of sources of situational strength crossed with large numbers of facets of situational strength within any single study. Nonetheless, several avenues exist for future research. For instance, for a given facet of situational strength (e.g., clarity), future research could examine the relative importance of the multiple channels through which top management may attempt to influence employees' behavior (e.g., immediate supervisors vs. organizational pay/benefits systems vs. organizational promotion systems; Dalal et al., 2011 ).

Another avenue for future research is the role of individual differences on employees' perceptions of situational strength. In this regard, it is important to note that a person's perceptions of the strength of a situation are not solely a reflection of the objective characteristics of the situation associated with situational strength. Instead, perceptions of situational strength also reflect the characteristics of the perceiver. Specifically, objective characteristics of the situation are “filtered through [a person's] expectations, experiences, motives, and dispositions” ( Meyer et al., 2014 ; p. 1,023). One aspect of employees' dispositions that may be of particular relevance here is personality strength, an individual difference construct to which we alluded in the Introduction, and which previous researchers have described as “the other side of the strong vs. weak situation coin” ( Locke and Latham, 2004 ; p. 395). Based on this perspective, personality strength, indicated by an individual's tendency to behave in uniform ways across situations (no matter what the situation requires), would reduce the level of perceived situational strength in a given situation ( Dalal et al., 2015 ). Other individual differences could influence employees' perceived psychological distance between themselves and the various sources of situational strength, and, in turn, could determine how employees combine situational strength emanating from these sources. For example, employees' levels of social dominance orientation (i.e., the tendency to endorse intergroup hierarchies; Pratto et al., 1994 ) could impact their perceptions of social distance between different hierarchical levels in the organization. Future research could therefore draw from the personality and social psychology literatures to examine the role of individual differences as antecedents of perceptions of situational strength.

Limitations and Conclusion

A putative limitation of this study is that the data were collected via self-report measures. However, same-source bias was ameliorated by collecting data at two time points ( Podsakoff et al., 2003 ). Moreover, unlike some self-report data, situational strength data are unlikely to be influenced appreciably by socially desirable responding. Perhaps more importantly, the choice of self-report data was driven by the study's focus on nuanced employee perceptions: specifically, perceptions of situational strength emanating from multiple sources. For perceptual data such as these, self-reports are “not only justifiable but probably necessary” due to the limited insight that observers have into people's perceptions ( Chan, 2009 ; p. 326). In particular, the validity of other-reports of perceptions rests on three dubious assumptions: (a) the focal person's perceptions translate well into observable behavior, (b) other people regularly have the opportunity to observe this perception-relevant behavior, and (c) observers are accurately able to back-translate a specific behavior into a specific valence relevant to a specific perception ( Chan, 2009 ). Because none of these assumptions is likely to hold true, other-reports of people's perceptions cannot substitute for self-reports. It would, however, be interesting to examine the extent of (dis)agreement between self- and other-reports of situational strength from a source (e.g., immediate supervisor) as a variable of interest in and of itself. This, in turn, would lead to an emphasis on the factors that influence (dis)agreement. For instance, we suspect that the clarity of supervisor-to-subordinate communication is adjudged to be higher by the supervisor than by the subordinate. Moreover, we suspect that this disagreement is likely to be lower when both supervisor and subordinate score high rather than low on interpersonal skills such as perspective-taking, and when the supervisor and subordinate have had considerable experience working together. Future research should address questions such as these.

From a practical standpoint, the current research provides insight into the optimal location for situational-strength-related interventions. For instance, Human Resource Management interventions to decrease perceived constraints, and therefore increase the extent of dispositional discretion, would be more fruitfully targeted at proximal sources such as the immediate supervisor than at distal sources such as top management. In contrast, top management can have an outsized impact on employees' perceptions through the situational strength facet of clarity because communication about the organization's strategic plan and resultant policies may spur greater perceived clarity than the immediate supervisor's attempts to turn top management's policies into quotidian procedures to be followed by the employee. In a related vein, while organizations communicate the strategic plan and resultant policies through top management, they should also be mindful of the needs of key frontline employees (e.g., allies that we alluded to in the Introduction section) and immediate supervisors, who will be transmitting the effect of situational strength from top management. When necessary, these individuals should be trained on communicating new procedures and policies.

Finally, each social source of situational strength should consider the situational strength implications of its actions. For instance, several aspects of the organization's human resources management system (e.g., the electronic performance monitoring system, the telework policy) are likely to have large effects in terms of situational strength ( Dalal and Meyer, 2012 ). Accordingly, top management should consider whether each new policy is aligned with the level of situational strength top management wishes organizational employees to experience.

Ethics Statement

We obtained human subjects approval from George Mason University's Institutional Review Board.

Author Contributions

RD developed the broad rationale for the paper and some of the research questions. BA, RD, AT, and SH fleshed out the theoretical foundation, improved, and added to the research questions, designed the study, and selected the instruments. All authors contributed to data collection. BA, ZS, AM, and SH contributed to data analysis. All authors contributed to the interpretation of the results. BA, RD, and ZS contributed to manuscript writing. AM, AT, and SH provided critical reviews for, and helped with the editing of, the manuscript prior to submission. BA, RD, ZS, AM, and SH contributed to manuscript revisions subsequent to reviewer feedback.

This paper was funded by Contract # W5J9CQ-12-C-0036 to RD (Principal Investigator) from the U.S. Army Research Institute for the Behavioral and Social Sciences (URL: https://sslweb.hqda.pentagon.mil/ari/ ). The content of and conclusions from this paper, however, are solely the work of the authors and should not be attributed to the sponsor.

Conflict of Interest Statement

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

The reviewer AP and handling Editor declared their shared affiliation.

Acknowledgments

The authors would like to thank Tiffani R. Chen and Ronald P. Vega, who played a role in the design of the study.

1. ^ Agreeableness is characterized by trust, straightforwardness, altruism, compliance, modesty, and tender-mindedness; conscientiousness is characterized by competence, order, dutifulness, achievement striving, self-discipline, and deliberation; extraversion is characterized by warmth, gregariousness, assertiveness, activity, excitement-seeking, and positive emotions; neuroticism is characterized by anxiety, angry hostility, depression, self-consciousness, impulsiveness, and vulnerability; and openness to experience is characterized by fantasy, appreciation of aesthetics, receptiveness to inner feelings, willingness to try different activities and consider new ideas, and readiness to reflect on values ( Costa and McCrae, 1992 ; see also Judge et al., 2013 ).

2. ^ A very short time interval is more likely to suffer from carryover effects, whereas a very long interval increases the chance that a change in status could occur; a 2-week interval is believed to be a good balance between the two ( Marx et al., 2003 ). A 2-week interval is also commonly chosen in psychological survey designs involving two waves of data (e.g., Hideg and Ferris, 2017 ).

3. ^ Main analyses were also conducted on a data set that excluded the four cases with less than 50% missing data ( N = 359). The substantive conclusions did not change when we restricted the analyses to only the subset of respondents with complete data. Accordingly, we report the results obtained from analyses with listwise deletion of missing data.

4. ^ Vandenberg and Lance (2000) note that a factor variance/covariance invariance test could be used to accompany the test of configural variance or metric invariance. Vandenberg and Lance (2000) also note, however, that support for an overall variance/covariance invariance test indicates that tests for specific aspects of measurement equivalence are neither needed nor warranted; moreover, the rejection of the variance/covariance invariance hypothesis is uninformative of the particular source of measurement inequivalence. Accordingly, to evaluate measurement equivalence of the focal variables we tested a series of increasingly restrictive hypotheses.

5. ^ As alluded to in the Participants and Procedure section, in the Time 1 survey, we included questions assessing: (1) age, (2) number of years worked with the current immediate supervisor, (3) number of years worked with the current top management, (4) number of years completed in the current organization, (5) number of years completed in the current job, (6) gender (male; female; other), (7) whether the respondent considers himself or herself to be a part of the organization's top management (yes; no), and (8) whether the respondent considers his or her immediate supervisor to be a part of the organization's top management (yes; no). After controlling for the continuous variables (i.e., variables 1–5), in addition to the original control variable of overall situational strength at Time 1, substantive conclusions from the RWA and mediation analyses were identical to those reported in the Results section. For the non-continuous variables (i.e., variables 6-8), we conducted the RWA and the mediation analyses separately for each group (using only male vs. female in the case of gender): If results did not vary across groups, then we can conclude that the control variables had no influence on the focal analyses. Results did not vary across the two groups of variables 6–8 for all but one analysis. The one exception is that the mediating effect of constraints from coworkers on the relationship between constraints from top management and overall constraints was stronger for the respondents who considered their immediate supervisors to be top management. This is in line with our overall findings (and field theory; Lewin, 1939 , 1943 , 1951 ): The influence from top management should be stronger if top management includes one's immediate supervisor. Besides, the mediating effect was established regardless of whether an employee considered his or her immediate supervisor to be top management. Readers who are interested in the version of the focal analyses that include the control variables can contact the first author.

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Keywords: situational strength, clarity, constraints, coworkers, the immediate supervisor, top management, psychological distance, field theory

Citation: Alaybek B, Dalal RS, Sheng Z, Morris AG, Tomassetti AJ and Holland SJ (2017) Situational Strength Cues from Social Sources at Work: Relative Importance and Mediated Effects. Front. Psychol . 8:1512. doi: 10.3389/fpsyg.2017.01512

Received: 08 June 2017; Accepted: 21 August 2017; Published: 05 September 2017.

Reviewed by:

Copyright © 2017 Alaybek, Dalal, Sheng, Morris, Tomassetti and Holland. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Balca Alaybek, [email protected]

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• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on August 15, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

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Step 1. Ask a question

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

5. Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in  if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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