Framing Effects, Procedural Fairness, and the Nonprofit Managers' Reactions to Job Layoffs in Response to the Economic Shock of the COVID-19 Crisis.

The COVID-19 pandemic has challenged the viability and effectiveness of nonprofit organizations compelling them to make tough choices. Evidence suggests that different wordings or message settings may affect people's decisions when presenting equivalent outcome information with positive or negative framing. Nevertheless, there have been few attempts to assess how procedural fairness and framing effects shape nonprofit managers' reactions to job layoffs due to the COVID-19 pandemic. Using a survey experiment, we explore whether framing effects-by affecting perceived outcome favorability-and procedural fairness interact to influence nonprofit managers' trust and support for their organizations. The findings of this 2 × 2 between-participants experimental design indicated that only when procedural fairness was relatively low did nonprofit managers react more favorably in the positive frame (keep) than in the negative frame (layoff) condition. This study adds to our understanding of how the pandemic impacts nonprofit managers, including their commitment to continue working in the sector, and has practical implications for nonprofit organizations that manage resilience in a crisis. © International Society for Third-Sector Research 2021.

Introduction

The layoffs in United States (hereafter U.S.) nonprofit organizations have been particularly challenging since 2020 due to COVID-19, and nonprofit employees expect more of the same in 2021. For example, between March and May 2020, nonprofit organizations across the U.S. had a total of 1,643,128 job losses, as follows: 14,689 in professional, scientific, and technical services, 323,201 in educational services, 574,530 healthcare, 259,007 social assistance, 205,964 arts, entertainment, and recreation, 218,167 other services (except public administration), and 47,450 in other fields (Salamon & Newhouse, 2020).1 Further, according to a survey conducted by Eagle Hill Consulting (2021), 20% of nonprofit employees said their employers implemented layoffs in 2020, and 49% expect more cuts in 2021. These estimates are worrisome because the COVID-19 pandemic resulted in many nonprofit organizations experiencing greater demand while canceling vital fundraising events due to strong social distancing measures (Courtemanche et al., 2020).

Previous literature on procedural fairness suggests that perceived outcome favorability and procedural fairness interactively influence the managers’ reactions to job layoffs (Colquitt, 2001; Cropanzano, Byrne, Bobocel, & Rupp, 2001; Moorman, 1991).2 There have been some successful attempts to improve the remaining employees’ reactions to job layoffs in the for-profit sector (Brockner, 1992; Brockner et al., 1995),3 but an empirical evaluation of whether this holds in nonprofit organizations is missing. This gap in the literature is problematic given the efforts of nonprofit organizations worldwide to make themselves more resilient in various, often innovative ways to ameliorate the shocks associated with crises such as pandemics. More research is required to develop preventive and coping strategies to enhance nonprofit managers’ reactions to job layoffs in response to the economic shock of the COVID-19 pandemic.

The negative economic aspects of the COVID-19 pandemic affect nonprofit managers’ trust and support for the organization (The NonProfit Times, 2020). When recovery of pandemic-related job losses is slow in the nonprofit sector, it leads to managers’ erosion of trust and support in the organization with ensuing management difficulties. In this regard, prospect theory suggests that managers evaluate decision outcomes differently when presented with matching criteria with either a procedurally fair or unfair framing. Generally, framing effects mean that the presentation method of a decision problem influences how people summarize and ultimately act upon the problem (Chong & Druckman, 2007). Brockner et al. (1995) found that the interaction between decision frame and procedural fairness influences remaining employees’ trust and support for the for-profit organization. In Brockner et al.’s (1995) study, the effect of decision frames (positive or negative) on organizational trust and support in the private sector is statistically significant only when it is procedurally unfair. In other words, employees had less confidence in their organization due to job layoffs, only when the procedure was unfair. Of interest to this study is whether nonprofit managers also suffer from this framing effect. Addressing this problem will give nonprofit managers the insight to adjust their policy and strategies, ensuring that managers receive the support they need and deserve, contributing to a more nuanced understanding of the behavioral aspect of the prospect theory for nonprofit organizations.

This research investigated effective strategies to help the nonprofit workforce cope with the pressures suffered by its members. We conducted experiments to measure the effect of job layoffs on trust and support contingent upon the fairness of decision-making procedures. Building on previous literature in prospect theory, we replicated Brockner et al.’s (1995) study to investigate how to minimize the inevitable side effects of layoffs in U.S. nonprofit organizations during the COVID-19 pandemic.4 Brockner et al.’s (1995) study showed multiple determinants of employees’ reactions to job layoffs: a negatively framed decision should matter to a greater extent in procedural unfairness contexts. Under such conditions, decision frame influences employees’ beliefs about improvements in their career opportunities and should affect their trust and support for the organization. Our conceptual replication examined framing effects on nonprofit managers’ trust and support in an economic downturn battering nonprofit organizations with ensuing layoffs because of the COVID-19 pandemic.

This study selected nonprofit executives as its research subjects for the following three reasons. First, we selected nonprofit executives as respondents because this study is about whether nonprofit managers are susceptible to framing effects. Second, nonprofit executives are in charge of most of the day-to-day management of their organization and are likely to be most familiar with important issues related to the organization, not to mention that they exert substantial influence on key decision-making processes (Ingram, 2019). Lastly, designing transparent decision-making processes and institutionalizing regulations to ensure accountability and responsibility for nonprofit managers’ decisions is challenging in nonprofit management for the post-COVID-19 era (Delronge et al., 2019).

Equivalence Framing and Managerial Assessment of Procedural Fairness

A core insight from prospect theory demonstrates that responses to information depend on whether the information is negatively or positively framed (Tversky & Kahneman, 1981, 1992). The effects are attributed to information frames resulting from a cognitive bias, meaning that individuals do not carefully evaluate the information to which they are exposed. The main takeaway from this research is that framing can influence managers’ decision-making.

Applying prospect theory to the nonprofit sector, we see that the prospects of gains and losses drive the day-to-day decisions made by nonprofit organizations and their managers (Kahneman & Tversky, 1979). Based on prospect theory, framing effects can transform an individual’s point of reference for judging whether perceived information is a benefit or harm to some individual or organization by framing the information in a positive or negative light (Schelling, 1984). That is, if you present probabilistically equivalent information in a positive light, its interpretation will be different than if giving it in a negative light (Kahneman & Tversky, 1979). This notion of equivalency framing has been expanded and adopted in experimental research to examine the behavioral aspect of nonprofit organizations.

The literature on nonprofit organizations includes the effect of framing effects on charitable giving. For example, Chang (2008) argued that when the price of a product is low, the donation amount in absolute U.S. dollars is more effective than in percentage terms. Furthermore, Chang and Lee (2009) indicated that donation advertisements are more effective when sending negative pictures and negative messages. Similarly, Zolner et al. (2010) show that it is effective for nonprofit organizations to frame solicitation as a donation when the amount of the donation is small. In a more recent study, Qu and Daniel (2021) investigated the framing effects of nonprofit organizations’ overhead on donor decisions.

These studies have contributed to our understanding of donors’ behaviors. However, gaps in the previous literature remain regarding the behavior of nonprofit managers when a job layoff is inevitable due to the negative economic prospects of COVID-19. While there is heavy debate on the effects of the COVID-19 pandemic on human resource management in the private sector,5 it remains unclear how COVID-19 affects nonprofit human resource policies. For example, Young et al. (2020), using survey data in San Diego nonprofits in March and April 2020, report that there has been a significant and unprecedented hollowing out of the nonprofit workforce, with 53% reporting staff furloughs, layoffs, reduced work hours, and reduced pay. Similarly, Kim and Mason (2020) found that nonprofits with more financial reserves are less likely to reduce operating hours, lose staff, or experience difficulty acquiring supplies or vendor services in response to the immediate impact of COVID-19 on human services and art nonprofits. However, today a more relevant question is just how procedural (un)fairness moderates the impact of decision frame on nonprofit managers’ trust and support for the organization during the COVID-19 pandemic. Thus, our study builds on the available evidence and extends it to investigate sensemaking of COVID-19’s impact on the sector’s workforce.

Defining Trust

According to Greiling (2007), trust in the nonprofit sector has an internal (organizational) and external (environmental) perspective. However, the internal view—although no less important—has received considerably less attention than the external view. The internal perspective focuses on the dynamics of interpersonal trust within nonprofit organizations and has more recently garnered attention for its impact on overall organizational performance (Greiling, 2007; Knapp et al., 2019).

According to previous literature on trust in the nonprofit sector, trust comprises three major overlapping constructs: fairness, confidence, and risk-taking. Greiling’s (2007) literature assessment notes that confidence and fairness are reliable attributes of trust. Nonprofit managers who consistently experience confidence and fairness within the organization and their relationships with their board of directors are exposed to trust as a measure of reciprocity, a notion grounded in social exchange theory (Knapp et al., 2019). Based on existing studies on trust in the nonprofit sector, the present analyses employ the following six statements measuring trust and support for the organization:

The managers trust local ________ management.

The managers are proud to tell others that they are a part of ________.

The managers’ co-workers might have been quite mistrustful of top management since the beginning of the layoff.6

Managers treat survivors fairly and consistently concerning HR.

The managers trust management concerning HR decisions.

The managers feel that they can trust the organization to treat them fairly.

The respondents answered on a five-point scale: 1 = Strongly disagree, 2 = Somewhat disagree, 3 = Neither agree nor disagree, 4 = Somewhat agree, and 5 = Strongly agree.

We explored whether U.S. nonprofit leaders are susceptible to framing effects when the decision-making procedures are unfair but less sensitive to framing effects when the process is fair. This potential reduction in bias from equivalence framing may be attributable to their professional experience in the nonprofit sector. For instance, Fuenzalida et al. (2020) found that civil servants are significantly more reflective and less susceptible to framing effects thanks to their professional experience. Further, Olsen (2015) found that citizens are less sensitive to framing effects depending on their current or previous work experience in the public sector. Thus, based on the available evidence, we offer the following hypothesis:

H: The effect of decision frame on nonprofit managers’ trust and support for the organization is stronger in procedural unfairness contexts and weaker in procedural fairness contexts.

We drew upon the arguments of Yin (2003) on the merits of replication as a form of empirical generalization to build external validity across contexts (Piening, 2011; Zhu, 2014). In other words, we can determine the representativeness of the results of a previous study for a different sector by replicating Brockner et al.’s (1995) study with a different population. Replications compare findings across various subject groups to assess their degree of similarity and appropriateness for future research. While for-profit and nonprofit organizations are different in many ways, even down to the core of how and why they conduct business and operations, there are some similarities because they both do monetary transactions. For example, expectancy theory posits that for-profit employees act to maximize expected satisfaction with outcomes (Vroom, 1964). On the other hand, Lanfranchi et al. (2010) found that nonprofit employees had higher intrinsic work motivation than private workers because the nonprofit sector focuses on organizational missions, goals, stakeholders, and employee motivation. We posited that if the results of this study are similar to those of Brockner et al.'s (1995) study, researchers might expect that this study will produce stronger support for its empirical generalization in nonprofit organizations. If not, then this study will offer weaker results.

Methods

2 × 2 Between-Subjects Experimental Design

We employed a 2 (framing effects: keep or layoff) × 2 (procedural fairness: fair or unfair) between-subjects survey experiment to examine the proposed hypothesis (Fig. 1). First, we assigned respondents to one of four treatment groups following four types of hypothetical scenarios: 1) procedural fairness × keep condition, 2) procedural fairness × layoff condition, 3) procedural unfairness × keep condition, and 4) procedural unfairness × layoff condition. Then, respondents answered questions on the managers’ trust and support for the organization. Figure 2 provides an overview of this design.

Fig. 1

A prospect theory framework

Fig. 2

Experimental design

We distributed a survey to learn about the moderating role of procedural fairness on framing effects of nonprofit leaders across the U.S. We received responses from 403 participants between March and May 2020, including organizations based in all 50 states. The participants were nonprofit executives of various National Taxonomy of Exempt Entities (hereafter NTEE) subgroups. The sample consisted of 1,192 stratified random sampled nonprofit organizations from the National Center for Charitable Statistics (2013). Here, strata are made by randomly selecting 10% of the organizations from each defined group. A self-administered survey required obtaining email addresses for the selected 501(c)(3) organizations’ executive directors, which we accomplished by visiting each nonprofit’s webpage. We received Institutional Review Board (IRB) approval for the surveys used in this study, including the participant questionnaire and consent form (IRB ID: STUDY00010762).

Using G* Power software, we determined the sample size based on an a priori power calculation (Faul et al., 2007). We calculated the appropriate sample for finding an effect that is small in size (0.2) at 80% power given α = 0.05. By the end of the data collection, from the 1,018 respondents that had received the survey, 403 nonprofit organizations participated (132 emails bounced back), representing 50 states and an overall response rate of 39.6%.7

The present study sought to replicate the framing effects experiment conducted by Brockner et al. (1995), but with a different context: nonprofit organizations responding to the economic shocks from COVID-19. Thus, we can characterize our study as an empirical generalization rather than a direct or exact replication (Makel et al., 2012; Tsang & Kwan, 1999). The survey instrument consisted of one open-ended and 16 closed-ended questions. The first section included several general questions about the services provided by nonprofit organizations, the second section contained the experimental study, and the final section included sociodemographic questions. We generated the survey items from previous studies (Battaglio & Condrey, 2009; Brockner et al., 1995). At the end of the survey, we asked respondents, “Are there any comments you would like to add? [Optional].” We finalized the questionnaire after pretesting it with several nonprofit leaders. We administered the survey online. We distributed the initial invitation to leaders in March 2020 and sent the first reminder in April 2020. We sent the second reminder in May 2020. As discussed in Dillman et al. (2014), we used multiple modes of contact in the recruitment phase of the survey to obtain high response rates and ensure that respondents prioritized answering the survey carefully. Figure 3 provides a data collection flowchart. The experimental vignette can be found in “Appendix A”.

Fig. 3

Data collection flowchart

We used stratified random sampling to select the leaders of nonprofit organizations in various NTEE subgroups. Strata ensure an even distribution of leaders from different types of nonprofit organizations, and the random assignment prevents selection bias of participants on treatments (Angrist & Pischke, 2008). Concerning organizational missions, respondents differed in percentages (see Table 1). In this study’s sample, educational institutions and related activities (18.15%), human services (12.22%), arts, culture, and humanities (9.26%), general and rehabilitative health (5.93%), and housing (5.93%) ranked high. Although this ranking is similar to the National Center for Charitable Statistics (2013), the samples used for our analysis are not a perfect representation of the entire nonprofit sector in the United States. In this sense, our study intends not to generalize our findings to the population at large but rather to provide empirical insights into theorized processes to link procedural fairness to nonprofit managers’ trust and support for their organizations.8

Table 1

A comparison between population and this study’s sample (N = 403)

Organizational Missions	National Center for Charitable Statistics (2013)	National Survey of Nonprofit Leaders
A: Arts, Culture, and Humanities	9.23%	9.26%
B: Educational Institutions and Related Activities	15.74%	18.15%
C: Environmental Quality, Protection, and Beautification	2.26%	2.96%
D: Animal Related	2.00%	2.59%
E: Health—General and Rehabilitative	8.77%	5.93%
F: Mental Health, Crisis Intervention	2.85%	3.70%
G: Disease, Disorders, Medical Disciplines	2.44%	2.22%
H: Medical Research	0.69%	4.73%
I: Crime, Legal Related	1.74%	2.22%
J: Employment, Job Related	1.48%	2.96%
K: Food, Agriculture, and Nutrition	1.15%	2.22%
L: Housing, Shelter	7.01%	5.93%
M: Public Safety, Disaster Preparedness, and Relief	1.98%	1.11%
N: Recreation, Sports, Leisure, Athletics	5.91%	4.07%
O: Youth Development	2.44%	4.81%
P: Human Services—Multipurpose and Other	14.30%	12.22%
Q: International, Foreign Affairs, and National Security	2.17%	0.07%
R: Civil Rights, Social Action, Advocacy	0.66%	2.96%
S: Community Improvement, Capacity Building	4.30%	2.96%
T: Philanthropy, Voluntarism, and Grantmaking Foundations	4.47%	3.33%
U: Science and Technology Research Institutes, Services	0.59%	1.11%
V: Social Service Research Institutes, Services	0.28%	0.04%
W: Public. Society Benefit: Multipurpose and Other	1.09%	4.07%
X: Religion Related, Spiritual Development	6.08%	0.11%
Y: Mutual/Membership Benefit Organizations, Other	0.27%	0.27%
Z: Unknown	0.08%	0.00%
Number of Observations	216,924	403

Using the randomizer function embedded in Qualtrics, an online survey software, we randomly assigned participants to one of the four treatment groups. Table 2 shows the sample’s demographic characteristics. An analysis of differences between the treatment groups showed that groups were balanced at the outset: none of the differences across the groups concerning the basic organizational characteristics was statistically significant at the 0.01 level (see Table 2).

Table 2

Respondents’ characteristics and organizational context across groups

Category	Subgroup	Procedural fairness × keep condition (%) (n = 101)	Procedural fairness × layoff condition (n = 101)	Procedural unfairness × keep condition (n = 101)	Procedural unfairness × layoff condition(n = 100)	χ2	df	p value
Current	Executive Director	85.71	57.23	59.38	48.28	11.883	6	0.688
Position	Chief Executive Director	0.00	14.29	15.63	22.41
	Deputy Director	0.00	0.00	9.00	1.72
	Program Coordinator	0.00	14.29	6.25	1.72
	Manager	0.00	0.00	6.25	10.34
	Publicist/Marketing	0.00	0.00	0.00	0.00
	Other	14.29	14.29	12.49	15.53
Race	Black/African American	0.00	33.33	6.25	0.00	17.933	5	0.118
	White	85.71	66.67	68.75	87.72
	Asian/Pacific Islander	14.29	0.00	12.50	3.51
	Native American	0.00	0.00	0.00	0.00
	Other	0.00	0.00	6.25	5.26
	Prefer not to answer	0.00	0.00	6.25	3.51
Gender	Female	57.14	66.67	65.63	59.65	0.437	1	0.933
	Male	42.86	33.33	34.37	40.35
Population	10,000 to 24,999	14.29	0.00	9.38	0.00	20.175	7	0.510
	25,000 to 49,999	14.29	0.00	3.13	5.36
	50,000 to 99,999	0.00	0.00	6.25	14.29
	100,000 to 249,999	14.29	16.66	21.82	16.07
	250,000 to 499,999	14.29	0.00	15.63	8.93
	500,000 or more	42.84	66.68	40.66	46.43
	Not sure	0.00	16.66	3.13	7.14
	Refuse	0.00	0.00	0.00	1.78
Region	Northeast	16.66	16.66	37.50	23.21	7.027	3	0.634
	Midwest	16.66	0.00	3.13	12.50
	South	16.66	33.32	28.13	30.36
	West	50.02	50.02	31.24	33.93

Measures

Dependent Variable

To measure the managers’ trust and support for the organization, we used an index comprising the six items in Table 3. For the index design, we referred to the previous literature by Brockner et al. (1995) and Battaglio and Condrey (2009). The following text preceded the six items: “Please refer to a hypothetical scenario in which you are one of the managers at a nationwide 501(c)(3) organization called Alliance. To what extent, if at all, do you agree with the following statements as they relate to the managers’ trust and support for the organization? (Select one answer in each row)” We randomized the item order. Respondents answered on a five-point scale: 1 = Strongly disagree, 2 = Somewhat disagree, 3 = Neither agree nor disagree, 4 = Somewhat agree, and 5 = Strongly agree. We generated the index as a simple additive measure (Cronbach’s α = 0.88).

Table 3

Survey questions regarding the managers’ trust in and support for the organization

		Mean	Standard deviation	Range
The managers' trust in and support for the organization (index):		2.26	0.99	1–5
	"The managers trust local _______ management"	3.20	1.32	1–5
	"The managers are proud to tell others that they are a part of _______"	3.14	1.22	1–5
	"The managers’ co-workers might have been quite mistrustful of top management since the beginning of the layoff"*	2.16	1.07	1–5
	"Managers treat survivors fairly and consistently with respect to HR"	2.82	1.20	1–5
	"The managers trust management with respect to HR decisions"	3.27	1.33	1–5
	"The managers feel that they can trust the organization to treat them fairly"	3.29	1.32	1–5

Note * Item was reverse coded to create the managers’ trust in and support for the organization index

Independent Variable

Procedural Fairness

We manipulated procedural fairness along dimensions of inclusiveness or respectfulness (Tyler, 1997, 2006a, 2006b). In manipulating inclusiveness, our treatments explained whether the rank-and-file employees had opportunities to express their viewpoints to management before the layoff announcement and whether those laid off had opportunities to appeal their layoff. In manipulating respectfulness, our treatment explained whether local management clarified the layoff reasons to the laid-off employees and whether local management expressed regret about the layoffs (see “Appendix A”).

Framing Effects

One section of the survey asked participants a series of questions about the organization’s criteria for identifying employees to be laid off. The following text preceded the six items: “Management could have used the following factors to decide which employees would keep their jobs/be laid off and which employees would not during the layoffs. To what extent do you believe that each of the following factors actually would have been used to decide which employees would keep their jobs/be laid off?” As with previous items, we randomized the item order, and the respondents answered on a five-point scale:1 = Not at all, 2 = A little, 3 = A moderate amount, 4 = A lot, and 5 = A great deal.

We bolstered the framing effects manipulation with the definition accompanying each of the six criteria rated by participants. For example, in the keep condition, information about “job function” included that “those who kept their jobs during the job layoffs might have been in jobs identified as essential.” In the layoff condition, contrarily, we pointed out that “the laid-off during the job layoffs might have been in jobs identified as no longer essential.” In the survey, the framing effects manipulation preceded most procedural fairness items and all dependent variables.

Findings

We discuss the descriptive results before moving on to the experimental findings in response to hypothetical job layoffs. Table 4 contains some descriptive statistics for the 403 U.S. nonprofit organizations under examination.9 The sample comprises young and old organizations, with an age range from 4.55 to 143 years. As the data demonstrate, there is high variability in some variables—particularly for donations, fundraising, program expenses, size, and revenue. In addition, the variable of size has four organizations with negative values for their assets.

Table 4

Descriptive statistics

Variable	Mean (SD)	Min	Max
Donations	1,853,722(32,914,313)	0	8,550,169,316
Fundraising	20,718(226,200)	0	41,092,401
Program Expenses	7,607,045(166,154,527)	0	62,244,776,774
Age	34.49(97.98)	4.99	143
Size	21,520,490(391,035,676)	-3,165,084	90,501,091,616
Revenue	10,153,694(179,460,831)	111	62,519,341,516

Note Values are expressed in US dollars

This study asked nonprofit executive directors about their prospects for job layoffs in the U.S. nonprofit sector over the next five years. For job layoff expectations, we measured the level of layoffs on a three-point scale, where 1 indicates no job layoffs, 2 is modest job layoffs, and 3 is substantial job layoffs. When asked, “How would you expect the job layoffs in the U.S. nonprofit sector’s response to the economic shock of COVID-19 over the next five years,” 33 respondents (18.33%) expected “substantial job layoffs,” while 66 respondents (36.67%) expected “modest job layoffs.” These results show that the respondent group virtually expected job layoffs to continue five years after the study. Figure 4 shows respondents’ expectations of job layoffs in the next five years.10

Fig. 4

Respondents’ expectations of job layoffs in the next five years

Then, this study explains the experimental findings on the framing effects on the managers’ trust and support for the organization, contingent upon procedural fairness. Table 5 presents the result of OLS regression on the moderating role of procedural fairness on the framing effects on managers’ reactions to job layoffs. For Table 5, the statistically significant regression coefficient of the interaction between procedural unfairness and layoff/keep conditions means that procedural unfairness has a moderating effect. On the other hand, the regression coefficient of the interaction between procedural fairness and layoff/keep conditions is statistically insignificant, indicating that procedural fairness has no moderating effect. Specifically, managers perceived the layoff condition as negative and the keep condition as positive only when procedurally unfair. For procedural fairness, however, we observed no difference in the managers’ response to the layoff and keep conditions for procedural fairness. This result means that framing effects on the managers’ trust and support for the organization vary depending on whether the procedure is fair or unfair.

Table 5

OLS regression results on the moderating role of procedural fairness on the managers’ reactions to job layoffs in response to the economic shock of COVID-19

DV = Managers' Trust and	Support for the organization
	Model 1		Model 2
Procedural Fairness	0.844	***	0.408	**
(Fair = 1)	(0.189)		(0.098)
Procedural Fairness × Keep Condition			0.556
			(0.311)
Keep Condition	0.101	***	0.306	**
(Keep = 1)	(0.283)		(0.409)
Procedural Fairness × Layoff Condition			-0.233
			(0.423)
Procedural Unfairness	-0.500	***	-0.395	**
(Unfair = 1)	(0.531)		(0.569)
Procedural Unfairness × Keep Condition			0.267	**
			(0.423)
Layoff Condition	-0.408	***	-0.339	***
(Layoff = 1)	(0.569)		(0.292)
Procedural Unfairness × Layoff Condition			-0.895	***
			(0.203)
Constant	2.700	***	2.028	***
	(0.281)		(0.376)
N	403		403
Adjusted R2	0.152		0.147

Note Standard errors in parentheses; DV, dependent variable. * p < 0.10; ** p < 0.05; ** p < 0.01 (two-tailed tests)

Figure 5 illustrates the magnitude of these procedural fairness effects by plotting marginal framing effects on the managers’ reactions to job layoffs, contingent upon procedural fairness. The proper test for our hypothesis is to examine whether the differences between procedural fairness × keep and procedural fairness × layoff, and between procedural unfairness × keep and procedural unfairness × layoff, are statistically significant. In Fig. 5, when the decision-making procedure was unfair, the difference between the keep and layoff conditions is statistically significant because 95% confidence intervals of those conditions did not overlap at procedural unfairness. However, when the decision-making procedure was fair, the difference between the keep and layoff conditions was not statistically significant because 95% confidence intervals overlapped at procedural fairness. When the procedurally fair and unfair conditions are combined, the difference between the keep and the layoff conditions is statistically significant. This outcome suggests that procedural unfairness significantly impacts the managers’ trust and support for the organizations compared to procedural fairness. In other words, when we combined procedurally fair and unfair cases, there was also a difference in the managers' responses. At the same time, there was a difference in managers' reactions to the layoff and keep conditions only when the decision-making procedure was procedurally unfair and not in the case of procedural fairness.

Fig. 5

Marginal effects of decision frame on the managers’ trust in and support for the organization, contingent upon procedural fairness (95% confidence intervals)

Regarding the size of the effects, the marginal effect of the decision frame on trust and support for the organization is 2.83 for the positive frame (keep) and 1.94 for the negative frame (layoff) condition when the decision-making procedure was procedurally unfair. When it is procedurally fair, the marginal effect of the decision frame on trust and support for the organization is 2.53 for the positive frame (keep) and 2.03 for the negative frame (layoff) condition. Finally, when combining procedural fairness and unfairness, the marginal effect of the decision frame on trust and support for the organization is 2.8 for the positive frame (keep) and 1.95 for the negative frame (layoff) condition. These values correspond to increases by 0.89 when procedurally unfair, 0.5 when procedurally fair, and 0.85 in combined procedural fairness and unfairness. The p values are statistically significant only in the procedurally unfair and combined (procedural fairness + unfairness) conditions with the magnitude of the effect appearing large.

Discussion and Conclusion

This replication study complements previous research by examining the effects of decision frames on managers’ reactions to job layoffs in the context of nonprofit organizations anticipating layoffs during the COVID-19 pandemic. The results align with the initial findings of Brockner et al. (1995) in that procedural fairness plays a vital role in nonprofit organizations: managers who perceive mistreatment of laid-off workers during extreme events will be less motivated to perform jobs well. Moreover, framing effects play a complementary role: framing influences individuals’ perceptions of outcome favorability. In other words, we find that nonprofit managers are prone to be influenced by superficial changes in the valence of discharge information when asked to read and interpret said information. More precisely, results from our experiment confirm equivalence framing effects on managers’ trust and support for their organizations.

Our findings suggest that positively framing the discharge information convinced those who worked under procedurally unfair conditions. Interestingly, a similar pattern is not present for the relationship when it is procedurally fair. In other words, when it is procedurally fair, there is no difference in respondents' reactions to the keep and layoff conditions. This result suggests an asymmetric effect of framing on the managers’ reactions to job layoffs.

Compared with May 2020, when the data for this study was collected, some employers may be more reluctant to lay off staff at this moment due to the American Rescue Plan Act. Most nonprofit managers are having to adjust because in most cases their staffs are underpaid via grant funding. Even if they were at work, they would not earn as much as they could through Economic Impact Payments (EIPs) and unemployment benefits.11 This is because nonprofit employers can only offer low salaries because they have insufficient funding due to reductions in grant funding.

If the nonprofit organizations experienced a decline in trust from their staff since May 2020, when we completed our data collection, until now, the decreased confidence might reflect management’s response to protecting the organization. Management acts to sustain the organization when faced with reduced funding. In other words, the managers would feel that the top management will not consider their needs first. It is doubtful that the managers would feel otherwise. During funding reductions, managers’ trust in their superiors would wane because upper management must consider the overall operation and not just one particular program. This action is despite that each program is equally vital to serving the public. During such times as the coronavirus pandemic, upper management finds a way to plan for serving the public with reduced funding, even if it means providing services to fewer people. For instance, if an organization receives a five percent cut in nonprofit grants from a foundation, corporation, or government agency, it can still serve the same clients but with five percent fewer services.

We found that only when job layoffs were procedurally unfair did managers have less trust in their organization due to job layoffs in response to COVID-19. For example, this would be true if upper management reduced staff for unwarranted reasons such as political affiliation. However, upper management typically reviews its staffing situation and makes recommendations about staffing or programming reductions based upon many years of experience.

Before discussing the study’s implications, we review the limitations that pave the way for future research. First, nonprofit executives are the subjects of this study. Future studies can further deal with the effects of job layoffs by selecting nonprofit workers at more diverse levels. Notwithstanding these limitations, our research findings support our moderation model. For example, if the board of directors laid off its street-level employees, it may negatively influence the managers’ trust and support for the organization. In other words, we expect no significant difference if respondents are leaders or frontline workers. Instead, since nonprofit leaders have experienced job layoffs during past economic crises such as the financial crises between June 2007 and December 2009, we expect the respondents to provide an expert opinion when encountering similar situations due to COVID-19. However, in addition to nonprofit leaders’ perceptions, future research needs to study how street-level employees perceive job layoffs to determine the robustness of these findings.

A second limitation is the abstract nature of our experiment. A personal stake in the job layoff decision likely matters, but the survey does not directly relate to the respondents’ interests because they answered based on a hypothetical scenario. Despite this valid criticism, it is important to think creatively about what will happen in the post-pandemic era because it is unclear when the pandemic will end. Particularly in the case of unexpected public health crises such as COVID-19, it is vital to conduct an experimental design to account for a fourth wave or similar economic effects driven by the Delta variant. As such, experiments can provide a window into the impact of procedural fairness on trust that might otherwise be impossible to obtain using alternative research designs.

Lastly, the study offers a snapshot of a single period in time, namely March through May 2020—the early stage of the COVID-19 pandemic in the U.S. Therefore, unlike a longitudinal study, it may not provide specific information about changes over time. Moreover, at the time of this writing, the path of the post-COVID pandemic and its economic consequences remain uncertain. One key source of the uncertainty stems from the intermittent containment remaining in force for longer than expected. For example, the vaccination effort progresses slowly in some advanced economies, and new outbreaks occur, such as the Delta variant in developing economies (Cave, 2021). Nevertheless, we need to understand how the unprecedented crisis of the COVID-19 pandemic impacts nonprofit managers and their commitment to working in the sector. This is because nonprofit organizations face increased demands for services alongside decreased revenues and must make tough decisions to weather these fiscal storms.

Notwithstanding these limitations, our findings offer several vital contributions. First, and perhaps most importantly, procedural fairness, more than the outcome favorability itself, appears to form the basis for nonprofit managers’ trust and support for their organizations. As demonstrated, when procedural fairness is low, nonprofit managers respond very favorably to keep conditions and very negatively to layoff conditions. Their responses are perhaps because nonprofit workers are the lifeblood enabling nonprofit organizations to deliver services that ultimately generate shareholder benefits. For instance, Knapp et al. (2019) argued that nonprofit managers should receive training to apply organizational policies consistently and equitably. In addition, the organization should clearly explain the underlying rationale behind its decisions (i.e., layoffs). It is also crucial that nonprofit managers receive training on treating employees with respect and politeness when resorting to layoffs. For all nonprofit organizations, planning thoughtful workforce change amidst embedded layoffs in nonprofit organizations as a short-term solution for lowering costs can be a better way to address the vicissitudes of the transition in the economic landscape due to the adverse economic prospects of COVID-19.

The study’s second contribution is a practical implication for nonprofit organizations facing layoffs due to the economic shocks of COVID-19. Whenever nonprofit organizations have a layoff situation, this creates fear in managers. All managers want security in their employment. When organizations initiate a layoff action, the more information they can provide their managers about any layoff action, the better. The managers want to know why, who is affected, and whether the layoff is temporary or permanent. They also want to know the process of choosing which positions to include in the layoffs and if they have any rights to voluntarily move to lower-level positions instead of being included in the layoff action. Answering these questions goes a long way in relieving tensions between the board and managers. Managers have a challenging time fighting a layoff action for “reason of economy,” meaning that, for instance, there is insufficient funding for all proposed positions. While the layoff action is the most reasonable conclusion by top management, hurt feelings are inevitable because the managers’ livelihoods are at stake. Being forthright about the organizations’ situation and its intent to maintain as many managers as possible will help maintain organizational trust and support.

Lastly, nonprofits in the post-COVID-19 environment require nonprofit managers to ensure decision-making accuracy, consistency, and comprehensiveness. In addition, designing transparent decision-making processes and institutionalizing regulations to ensure accountability and responsibility for their decisions is challenging in nonprofit management (Delronge et al., 2019). Accordingly, the transition to this ever-changing environment and stakeholder needs demands a leadership commitment to creating a culture of trust based on all internal and external collaborators’ commitments to integrity and transparency. A commitment to integrity would positively affect the social capital dimension of employee and institutional trust among all the collaborators. And the level of trust could be one of the most important driving factors for the speedy development of organizational routines of nonprofit organizations’ ability to thrive in the current environment and future through effective information-sharing, inclusive feedback, and co-creation of values.

This article provides early evidence that the implications of procedural fairness—mainly framing effects—are not as straightforward as is often assumed. Instead, the relationship between framing effects and trust is asymmetric: framing effects matter only in a procedurally unfair condition, but framing effects do not matter when the decision-making procedure is fair. We wrote this article when the U.S. daily infection rates were still high. Thus, we need further analysis to assess the negative impacts of COVID-19 on the nonprofit sector as a whole. Nevertheless, the potential for using prospect theory in developing nonprofit organizations’ resilience strategies to lessen the shocks associated with such crises is a good start.