Navigating Government Funding During a Pandemic: A Study on Nonprofits’ Receipt of Disaster Relief Funds
-
Xintong Chen
and
Zheng Yang
Abstract
American communities have been the hardest hit by the COVID-19 pandemic. The collaboration between governments and nonprofits is needed to satisfy the needs of the American communities. This article investigates the organizational factors of nonprofits that contribute to the obtainment of government disaster relief funds in the context of the COVID-19 pandemic by surveying nonprofits whose main offices were located in California. The findings show that, in general, having internal professionals in fundraising, and having previous experience in government applications contribute to the successful receipt of government relief funds. Moreover, different factors are associated with the receipt of relief funds from different levels of government. This article offers valuable insights to government and nonprofit funding relations and how their collaboration can enhance community resilience during times of disasters.
1 Introduction
American communities have been the hardest hit by the COVID-19 pandemic. The growing needs of the American communities during COVID-19 cannot be satisfied by the governmental sector alone. The nonprofit sector serves as a significant service provider of the American communities and plays an important role in supplementing the social provision of governments (Lipsky and Smith 1989). Nonprofits are on the front lines of caring for families and individuals who have been affected by the COVID-19 pandemic. In the meantime, they are facing fiscal challenges in maintaining their operations and service provision. Kim and Mason (2020) surveyed more than 600 human service and arts and cultural nonprofits immediately after the COVID-19 outbreak and found that the revenue of most nonprofits was impacted by the pandemic. Maher, Hoang, and Hindery (2020) surveyed the public and nonprofits about their financial status in May 2020 and found that approximately 30 % of the surveyed nonprofits experienced financial difficulties during the COVID-19 pandemic. Government allocations can be especially critical for the survival and success of nonprofits during times of disaster. Obtaining government funds, such as the CARES (Coronavirus Aid, Relief and Economic Security) Act and/or the Federal Emergency Management Agency, can help nonprofits to reduce the fiscal impact of COVID-19 and maintain their financial stability (Maher, Hoang, and Hindery 2020). Thus, it is important to understand the mechanisms of government grants allocation in a disaster context.
Nonprofits that provide goods and services to the public in a redistributive manner receive more government support in the form of contracts and grants of various kinds (Young and Soh 2016). Among these nonprofits, nonprofits with the capacity to invest in administrative infrastructure and meet government service standards have advantages in receiving government funds since government support usually comes with administrative and service quality requirements (Young and Soh 2016). Besides these organizational level factors, Garrow (2011) found that ecological factors such as resource-poor environments also affect government and nonprofit funding relations. The COVID-19 pandemic has posed unprecedented environmental changes for governments and nonprofits. Governments have assumed new expectations, such as leading disaster response, coordinating resources, providing disaster-related services, and stabilizing communities. In the meantime, more nonprofits might seek government assistance in response to the adverse situations, as the majority have been significantly impacted by the pandemic. With these new expectations and an influx of grant applications, governments may adopt different criteria for reviewing applicants in reaction to the crisis situation. For example, since the purpose of the relief funds is to provide relief support, governments may switch their priority to providing funds to sectors that are most severely affected by the pandemic, as opposed to those offering services akin to the governmental functions.
Previous studies have shown that in a non-disaster context, variables such as ecological factors, structural factors, strategic actions, and previous government grant receipts are important predictors for nonprofits’ acquisition of government grant (Garrow 2011; Lu 2015). However, few empirical studies have explored the acquisition of government funds by nonprofits during times of disaster. Moreover, different types of governments (i.e. federal, state, county, city, etc.) may also be associated with different priorities, requirements, and selection criteria. For example, the federal government may prioritize healthcare needs and reopen economics, while local governments often concentrate on the needs of local individuals and communities (Dzigbede, Gehl, and Willoughby 2020). Furthermore, federal funding typically comes with more stringent regulations, reporting requirements, and oversight mechanisms to ensure accountability and compliance with national policies. Regarding the selection process, the federal government may rely more heavily on the merits of application, while the local government might also take into account local influences and the reputation of nonprofits. However, there is a notable gap in existing literature regarding whether different levels of government employ distinct rationales and criteria for selecting grant recipients.
Given the identified research gap, this article explores whether governments use different rationales to allocate relief funds in a disaster context and whether these rationales vary among the different levels of governments. To be more specific, in this study, the types of government funds (i.e. federal, state, county, city, etc.) that nonprofits in California have applied for and obtained since COVID-19 are explored, and the organizational resources and characteristics that explain the obtainment of government funding since COVID-19 are examined. Exploring the mechanisms through which nonprofits secure government funds during times of disaster can shed light on the dynamics of government and nonprofit funding relations in disaster contexts and how their collaboration can enhance community resilience in the face of disasters. Additionally, the findings of this study can significantly contribute to our understanding of which nonprofits are better equipped to maintain fiscal health and bolstering fiscal resiliency during critical times like the COVID-19 pandemic. Furthermore, these findings have the potential to identify best practices and inform policy decisions that support the most vulnerable and crucial sectors of the nonprofit landscape.
In the following, the literature on concepts and topics that are relevant to the receipt of government grants is reviewed and hypotheses based on previous research are developed. Data collection and variable operation are then discussed. Finally, descriptive and regressive findings are reviewed. The conclusion includes a discussion of the findings and their implications for research and practice. In summary, variables that contribute to the receipt of government relief grants were identified, including having previous experience in government grant applications and internal or external professionals employed who specialize in fundraising.
2 Literature Review
2.1 Government Funding
Nonprofits usually obtain their revenues from diverse sources, and government funds are a major source of revenue (Carrol and Stater 2009). Nonprofits have delivered government-funded services on behalf of all levels of government for decades (Gazley 2008; Gronbjerg 1993; Luksetich 2008; Salamon 1987; Smith and Lipsky 1993). Governments have relied more on nonprofits to provide public services since the needs of American communities have grown increasingly diverse and cannot be satisfied by government provision (Weisbrod 1997). Thus, government funding is primarily targeted at programs and services that have widespread public and redistributional benefits. As such, nonprofits that engage in human services and environmental conservation are more likely to receive government support compared to those that focus on expressive activities, such as arts and religion. In contrast to other sources, however, government funds usually come with stringent requirements (Young and Soh 2016). Nonprofits receiving government funds may be required to use governmental funding management systems, as well as report and evaluate their programs in line with government stipulations. This necessitates investment in administrative infrastructure and the recruitment of professionals to comply with these government standards. Additionally, there is also the possibility of signaling that government funding may benefit nonprofits by inducing a “crowd-in” effect (Heutel, 012), potentially attracting further resources or support.
2.2 Government Funding in Disasters
In the disaster context, the service needs of impacted communities have grown extremely fast, and government provision alone is far less than sufficient. This means the government has to rely more on nonprofits to deliver disaster relief and recovery services. One important strategy for governments to encourage nonprofits to provide disaster relief services is through relief grants. Lein et al. (2006) found that limited resources and expertise can be better utilized in disaster contexts through coordination between government and nonprofits. Therefore, it is interesting to explore how such funding relationships are formed.
Government funds are very helpful for organizational relief and recovery after nonprofits are affected by external shocks, such as natural disasters and economic recessions. Wicker, Filo, and Cuskelly (2013) surveyed sports clubs in Queensland, Australia, regarding their organizational resiliency after natural disasters (flooding, cyclone) and found that the use of government grants had a significant positive effect on organizational recovery. Joseph (2011) found that nonprofits that relied on government grants are more resilient compared to those who rely on private contributions by studying nonprofit financial health following the Great Recession. Park and Mosley (2017) found that human service nonprofits can successfully increase their revenue during the Great Recession by increasing their dependency on government funds.
During the COVID-19 pandemic, particularly, governments play an important role in stabilizing American society and the national economy through integrating nonprofit and private sector efforts and providing assistance to individuals, families, and the private sector (Dzigbede, Gehl, and Willoughby 2020). For example, the Coronavirus Aid, Relief, and Economic Security (CARES) Act provided crucial support to nonprofit organizations in various ways. One of the primary benefits was the creation of the Paycheck Protection Program (PPP) loans, offering eligible nonprofits with 500 or fewer employees’ access to emergency loans of up to $10 million to cover payroll, operational costs, and debt service (National Council of Nonprofits 2023). Additionally, the act included Economic Injury Disaster Loans (EIDL) and emergency grants for nonprofits, providing immediate financial assistance. Furthermore, the CARES Act introduced tax incentives for charitable giving, allowing deductions for donations and raising caps for both individuals and corporations. Nonprofits also benefited from the Employee Retention Payroll Tax Credit, delayed payment of payroll taxes, and potential access to the Economic Stabilization Fund (National Council of Nonprofits 2023). These provisions aimed to stabilize nonprofits, ensuring their continued operations during the pandemic and offering essential financial assistance to facilitate their mission-driven endeavors.
Although government grants are very helpful, not all nonprofit applicants can receive these grants after disasters. Smith (2012) interviewed nonprofit executives after Hurricane Katrina and found that federal funding for nonprofits was very limited and that only a few nonprofits obtained assistance. Chen (2022a) interviewed nonprofits that were impacted by Hurricane Florence and found that federal grants, especially long-term relief grants, are very competitive and not available to all nonprofits. Thus, understanding the mechanisms of obtaining government funds is extremely helpful for the resiliency of nonprofits in the face of external shocks.
2.3 Factors That Influence the Receipt of Government Funding
Previous studies have shown that diverse factors are associated with whether nonprofits are successful at obtaining grants. Ashley and Faulk (2010) examined whether nonprofit financial health and financial efficiency ratios have an impact on the grant amount using the Georgia grants marketplace as a case study, and they found that nonprofits with higher debt and fundraising ratios are negatively associated with the grant amount. For government grants specifically, Ashley and Van Slyke (2012) used state-level grant data from the state of Georgia to explore the relationship between administrative cost ratios and state government grant allocation among nonprofits and found that the significant impact of administrative cost ratios on government grant allocations was not consistent. Garrow (2010) explored the factors influencing the receipt of government grant allocation by surveying human services nonprofits in Los Angeles County in 2002 and found that both ecological factors and strategic actions contribute to the receipt of government funding. Lu (2015) surveyed nearly 100 human service nonprofits in Maryland to explore organizational factors that are associated with the obtainment of government funding and found that bureaucratic orientation, domain consensus with government, and previous government grant receipts positively contribute to it. However, the mechanisms of obtaining government funds have only been studied in a normal context, which does not differentiate government disaster relief grants and other types of government grants. The mechanisms of obtaining government relief funds might be different from other types of government funds because government may receive a larger number of grant applications and use different review criteria during the times of disasters. Therefore, this study explores the characteristics of nonprofits obtain government relief grants during the COVID-19 pandemic. In the following section, variables that may influence the receipt of government relief grants are discussed.
2.4 Factors That Influence the Receipt of COVID-19 Government Relief Funds
Institution theory argues that organizational structure is one of the important factors that influence organizations’ relationship with their external environments (DiMaggio and Powell 1983). Organizations are more likely to collaborate if they have similar structures since it is easier for two similarly structured organizations to communicate and build trust in each other (Child, Faulkner, and Tallman 2005). Such a concept can be extended to the dynamics between government and nonprofit organizations. The American governmental structure is typically characterized by bureaucratic norms and values (Schneider 1992), potentially influencing its interactions with nonprofit entities. Additionally, government funds are usually tied to public policies and required to adopt state-level accounting and reporting procedures (Anheier, Toepler, and Wojciech Sokolowski 1997).
Nonprofit organizations, known for their diverse organizational structures (Schneider 1992), have recently trended towards increased professionalization. This shift is marked by a growing presence of managerial staff, such as accountants and human service specialists, outside of direct service provision. This evolution may lead to functional differentiation and a more complex organizational structure (Toepler 2010). In other words, the organizational structure of nonprofit organizations tends to evolve towards a more bureaucratic model. Such bureaucratic structures are perceived as indicative of a greater ability to meet government requirements, leading governments to allocate funds to nonprofits exhibiting these characteristics. For example, Shaw (2003) found that structure compatibility affects governments and nonprofits in establishing their relationship. In terms of the funding relationship between governments and nonprofits, based on a survey of human service nonprofits in Maryland, Lu (2015) found that nonprofits with a similar bureaucratic structure as governments are more likely to be the recipient of governmental grants. As the bureaucratic structure is also predominant in the governmental disaster response system (Schneider 1992), they may prefer to provide grant support to nonprofits with similar bureaucratic structures. However, in terms of COVID-19 relief funds, governments use different criteria to select recipients, including the needs of the organization or community compared to other grants. Therefore, it is interesting to explore whether nonprofits with a similar bureaucratic structure as governments are at an advantage in obtaining government grants during disasters. Thus, this research adds to the literature by testing whether nonprofits that have a structure similar to that of governments are more likely to obtain government relief grants in the context of COVID-19.
Hypothesis 1.
Nonprofits with a higher degree of bureaucratic orientation are more likely to obtain government grants related to COVID-19 relief.
Professionalization can provide nonprofits with legitimation and rationalization (Hwang and Powell 2009). Professionals are those who receive formal education and training in an occupation and hold specialized expertise in a particular field (DiMaggio and Powell 1983). Nonprofits with professionals are more likely to meet government requirements and develop contracts with them (Frumkin and Andre-Clark 2000). Professionals in fundraising are those who develop occupational knowledge of fundraising through formal education provided by universities and professional training institutions. These professionals are more likely to be familiar with government grant application norms and standards and thus can write grants that meet government requirements. Thus, nonprofits employing fundraising professionals may have advantages when applying for government relief grants. There are two different ways for nonprofits to work with professionals in fundraising. Some nonprofits choose to hire professionals in fundraising as their internal staff. In contrast, some nonprofits may not have budgets large enough to employ specialized staff and rather choose to collaborate with external professionals in fundraising. Therefore, it is interesting to test whether having a professional fundraiser makes a difference in obtaining COVID-19 relief grants, and if hiring professionals in fundraising as internal staff or external consultants have different influences on the receipt of government relief grants. Therefore, in terms of professionalization in fundraising, the following two hypotheses were developed.
Hypothesis 2.
Nonprofits with internal fundraising professionals are more likely to obtain government grants related to COVID-19 relief.
Hypothesis 3.
Nonprofits with external fundraising professionals are more likely to obtain government grants related to COVID-19 relief.
Path dependence is a concept stating that historical events and decisions can have a lasting impact on current and future outcomes, with current organizational performance highly depending on past performance. Besides, the successful obtainment of government funds in the past can serve as a signal of an organization’s trustworthiness, thereby enhancing its prospects for future funding success (Heutel 2012). Using forty-seven service departments in the Welsh local government, Andrews et al. (2009) found that past performance positively contributes to organizational service provision performance. Walker et al. (2010) found that the past performance of public organizations is positively associated with their service performance using a sample of English local governments. Similarly, previous experiences and successes in governmental grant applications may also serve as indicators of a nonprofit’s future performance in grant acquisition. These organizations’ familiarity with governmental grant application processes, nuanced understanding of government requirements, and forged relationships with funding agencies may significantly influence their grant-obtaining proficiency. Consequently, prior experience is often invaluable for nonprofit organizations in successfully securing government relief grants. Therefore, the following hypothesis was developed.
Hypothesis 4.
Nonprofits with previous receipt of government grants are more likely to obtain government relief grants after disasters.
3 Methods
3.1 Data and Sample
The study focuses on nonprofit organizations in California, a state characterized by a high density of such entities. This density not only facilitates the construction of a substantial sample for research purposes but also introduces a competitive dynamic for relief funds, adding an intriguing aspect to the investigation. Moreover, California is the most populous state in the U.S. with a diverse range of nonprofits operating across various sectors. Its scale and diversity provide a broad sample of organizations to study, allowing for a more comprehensive analysis. The data for this study were collected from an online survey of 501(c)3 charitable nonprofits located in California and the National Center for Charitable Statistics (NCCS) 2019 Core Files. The NCCS 2017 Core Files (the latest available at the time of study) was used to identify nonprofits in the sample frame. The email addresses of nonprofits in the list were obtained from their website through data mining techniques based on the publicly available dataset. A total of 9524 nonprofits email addresses were identified. The survey was administered using the Qualtrics Platform in November 2021. We pretested out survey questions by sending out a pilot survey to 500 randomly selected nonprofits in the sample frame. After that, invitations were sent out to the rest of the nonprofits in the sample frame and two rounds of follow-up reminders were sent out within a month. The survey data consist of responses from 496 public charities, predominantly answered by executive directors or individuals in an equivalent position. Detailed below are the sampling selection and data. cleaning process. First, 236 nonprofits were dropped from the analysis because they omitted to answer the questions pertaining to government grant receipts, as participants were allowed the discretion to skip any question in the survey. Next, an additional 35 nonprofits were excluded during the data integration phase, as their Employer Identification Numbers (EINs) did not correspond with those in the NCCS Core PC files. To further refine our dataset, 7 outliers, defined as observations deviating beyond the 3-sigma range of the sample distribution, were eliminated based on the surplus variable. Furthermore, 102 nonprofits were excluded from the final regression analysis due to missing values in our dataset. As a result, the regression results are based on a final dataset consisting of 116 nonprofits. The survey included thirteen questions, and for this study, eight of them were used, which have been explained in the variable section.
3.2 Variables
Receipt of government grants is the key interest of this study and is measured by the following survey questions: (1) “Has your organization applied for any type of government grant related to COVID-19 relief?” Five choices were offered for this question – “federal grants”, “state grants”, “county grants”, “city grants” and “other grants”. (2) “For each of the following types of government grants related to COVID-19 relief, how many of such grant applications have been approved by government agencies?” Based on these two survey questions, four dependent variables were constructed– federal level funds, state level funds, county level funds, and city level funds and each of them measured the number of funds received by a nonprofit at a particular level of government. The total number of government funds of all types were summed, and a new dependent variable is created, named total government grants.
As summarized in the literature review, a range of variables may help explain the COVID-19 relief funds provided by governments. Bureaucratic orientation is measured by an index that combines three indicators following Lu (2015), who constructed the index based on the most obvious characteristics of Weber’s bureaucracy model. To be more specific, bureaucratic orientation is measured by the following three survey items: (1) A superior in my organization could expect subordinates to carry out his or her orders without question or deviation; (2) formal relationships between staff, based on job rank or position, are maintained by members of your organization; and (3) there is a complete set of rules, regulations, and standard operating procedures for staff to follow. Nonprofit respondents were asked to indicate their agreement with these survey items by a seven-choice Likert scale from strongly disagree to strongly agree. Their answers were coded as 1 = “strongly disagree,” 2 = “disagree,” 3= “somewhat disagree,” 4 = “neither agree nor disagree,” 5 = “somewhat agree,” 6 = “agree,” and 7 = “strongly agree.” The index of bureaucratic orientation is calculated as the average score of these three indicators. The Cronbach’s alpha for bureaucratic orientation stands at 0.69, which suggests that the three survey items related to bureaucratic orientation demonstrate a moderate level of internal consistency and generally exhibit a coherent variation.
Another important group of independent variables measures nonprofit professionalization on fundraising, which is indicated by internal fundraising professionals and external fundraising consultants. To measure internal fundraising professionals, we asked respondents, “Does your organization have fundraising professionals (internal staff)?” Their answers were coded as 1 for “Yes” and 0 for “No”. To measure external fundraising consultants, respondents were asked, “Does your organization have fundraising consultants (external consultants)?” The answers were coded as 1 for “Yes” and 0 for “No”.
The third independent variable is previous experience with government grant applications. The survey asked, “Had your organization received any type of grants by this level of government agencies prior to COVID-19? a. Federal Grants b. State Grants c. County Grants d. City Grants.” If nonprofit respondents chose any one type of government grants, this variable would be coded as 1; otherwise, as 0.
The organizational characteristics of nonprofits were used as control variables in this study. Organizational age, size of staff and assets, surplus, mission area, and subsector were used to indicate organizational characteristics. According to the “liability of newness”, younger nonprofits have a higher chance of failing than older nonprofits because they may lack support and experience and be viewed as less legitime compared to established nonprofits (Stinchcombe 2000). Thus, younger nonprofits are more likely to fail when applying for COVID-19 relief grants and it is expected that organizational age is positively associated with “receipts of government grants”. To measure organizational age, it was asked “In which year did your organization achieve nonprofit (501(c)3) status?” Organizational age was obtained using 2021 subtracted by their founding year.
Governments are more likely to provide grants to large nonprofits, on the one hand, since they may have a higher capacity to provide services to the community in need (Rosenthal 1996). On the other hand, governments may view larger nonprofits as more legitimate because size is positively associated with previous success (Baum 1996). Therefore, it was expected that organizational size is positively associated with “receipts of government grants”. Organizational size was measured by two indicators: staff size and asset size. To measure the variable staff size, we asked in our survey, “Approximately how many paid staff does your organization currently have (including both part-time and full-time employees)?” The variable asset size was obtained from the Core File and calculated as a logarithmic form of total assets due to its right-skewed distribution.
Nonprofit mission areas also affect funding. In a disaster context, having mission and offering services related to disaster response indicates a nonprofit with expertise and experience in disaster relief and response. Therefore, providing funding to nonprofits may be considered more legitimate by governments. Thus, it is assumed that nonprofits with missions related to disaster response are more likely to obtain government grants. To measure “mission area”, it was asked “Was disaster response (or emergency response, crisis response) part of your organization’s mission before COVID-19?”
Nonprofit subsectors may also be considered by governments in grant distribution, as the importance of government funding varies by subsector. For example, while government funding is an often a major contributor to human service nonprofits, its impact is markedly less in arts and health care nonprofits (Young and Soh 2016). The data for subsector were obtained from the NCCS Core file, which categorize them into five groups: art and humanity, education, human services, health, and others.
Surplus refers to the total operating margin, which is calculated as the difference between total revenue and total expense to total revenue (Tuckman and Chang 1991). Surplus is predicted to have a positive relationship with nonprofit resilience in a disaster context (Chen 2021a; Lin and Wang 2016). Therefore, nonprofits with more surplus are likely to have advantages in government grant applications. Table 1 summarizes the definitions and operation for all variables used in this study.
Variable description.
| Variable | Description (survey questions) | Operation/calculation |
|---|---|---|
| DV1: Total government fund | # of federal grants + # of state grants+ # of county level grants+ # of city level grants | |
| DV2: Federal level | How many of such grant applications have been approved by government agencies? – a. Federal Grants - # of grants | |
| DV3: State level | How many of such grant applications have been approved by government agencies? – b. State Grants - # of grants | |
| DV4: County level | How many of such grant applications have been approved by government agencies? – c. County Grants – # of grants | |
| DV5: City level | How many of such grant applications have been approved by government agencies? – e. City Grants - # of grants | |
| IV1: Bureaucratic orientation | (1) A superior in my organization could expect subordinates to carry out his or her orders without question or deviation (2) Formal relationships between staff, based on job rank or position, is maintained by members of your organization (3) There is a complete set of rules, regulations, and standard operating procedures for staffs to follow |
Total score of the three questions Each of the three questions 1–7 from strongly disagree to strongly disagree |
| IV2: Internal staff | Does your organization have fundraising professionals (internal staff)? | Dummy variable |
| IV3: External consultant | Does your organization have fundraising consultants (external consultants)? | Dummy variable |
| IV4: Previous experience | Support from any previous will be considered as yes Had your organization received any type of grants by this level of government agencies prior to COVID-19? a. Federal Grants b. State Grants c. County Grants d. City Grants |
Dummy variable |
| IV5: Age | In which year did your organization achieve nonprofit (501(c)3) status? | 2021- the year |
| IV6: Mission area | Was disaster response (or emergency response, crisis response) part of your organization’s mission before COVID-19? | Dummy variable |
| IV7: Staff size | Approximately how many paid staff does your organization currently have (including both part-time and full-time employees)? | |
| IV8: Assets size | 2019 core pc file | Ln (ass_boy) |
| IV9: Surplus | 2019 core pc file | (Totrev-exps)/totrev |
| IV10: Subsector | 2019 core pc file | Ntmaj5 |
4 Results
The descriptive results of variables and regression results are based on 116 nonprofits without missing values of variables. Figure 1 shows the distribution of dependent variables. Nearly 60 % of nonprofits in the sample obtained at least one COVID-19 relief grant from the governments. Nine nonprofits (8 %) obtained more than five government grants. A total of 45 % of nonprofits in the sample obtained federal COVID-19 relief grants. Compared to federal grants, fewer nonprofits in the sample obtained local grants. A total of 40 %, 24 %, and 14 % of nonprofits in the sample obtained state, county and city COVID-19 relief grants, respectively. Table 2 shows descriptive results of all variables. The nonprofit respondents used in the regression analysis have the following characteristics. The average age of nonprofit organizations was 26 and ranges from 4 to 69. The smallest nonprofit does not have any paid staff and is 100 % run by volunteers, and the largest nonprofit in the sample has 160 paid employees. Approximately 24 % of nonprofits had a disaster response as part of their organizations’ mission before the COVID-19 pandemic. In terms of professionalization in fundraising, 32 % of nonprofits in the sample have internal professionals who work on fundraising, and 22 % of them have external consultants in fundraising. A total of 30 % of nonprofits in the sample have previous experience in government grant application.
Grant type distributions.
Descriptive results.
| Count | Mean | S.D. | Min | Max | |
|---|---|---|---|---|---|
| Total | 116 | 1.862069 | 2.084713 | 0 | 9 |
| Federal funds | 116 | 0.7931034 | 0.9914174 | 0 | 3 |
| State funds | 116 | 0 0.4913793 | 0.6915099 | 0 | 3 |
| County funds | 116 | 0.3793103 | 0.8408606 | 0 | 5 |
| City funds | 116 | 0.1982759 | 0.1982759 | 0 | 3 |
| Bureaucratic | 116 | 4.390805 | 0.5311158 | 1 | 7 |
| Internal professionals | 116 | 0.3275862 | 1.371396 | 0 | 1 |
| External consultant | 116 | 0.2241379 | 0 0.4713692 | 0 | 1 |
| Previous experience | 116 | 0.3017241 | 0.4188225 | 0 | 1 |
| Age | 116 | 25.88793 | 0.4609975 | 4 | 69 |
| Mission area | 116 | 0.2413793 | 14.99204 | 0 | 1 |
| Staff size | 116 | 13.65948 | 0.4297763 | 0 | 160 |
| Assets size | 116 | 12.5418 | 22.47855 | 0 | 18.37055 |
| Surplus | 116 | 0.0759034 | 2.579568 | −0.4037587 | 0.7243758 |
| Subsector | Frequency | Percent | Cumulated percent |
|---|---|---|---|
| Art and humanity | 30 | 25.86 | 25.86 |
| Education | 18 | 15.52 | 41.38 |
| Health | 10 | 8.62 | 50.00 |
| Human services | 32 | 27.59 | 77.59 |
| Others | 26 | 22.41 | 100 |
| Total | 116 | 100.00 |
A Poisson regression model was utilized to explore how bureaucratic orientation, professionalization level on fundraising, previous experience in fundraising, and organizational characteristics affected the obtainment of government relief grants by nonprofits during the COVID-19 pandemic. Given that the dependent variable in this study is a count measure, a Poisson regression model was deemed the most appropriate for analysis. A series of diagnostic tests was used to ensure that the regression was unbiased and that the models were correctly specified. Table 3 shows the correlation between the variables and indicates no multicollinearity issues between variables. The Poisson regression models were run with different dependent variables five times. Table 4 presents the results from Poisson regression models. All hypotheses are mixed supported by the Poisson regression models.
Correlation table.
| Total funds | Fed. funds | State funds | Count funds | City funds | Bureau. | Inter. pro. | Exp. pro. | Pre. Exp. | Age | Mission | Staff size | Assets | Surplus | Sub sector | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Total funds | 1 | ||||||||||||||
| Federal funds | 0.6887 | 1 | |||||||||||||
| State funds | 0.7592 | 0.3525 | 1 | ||||||||||||
| County funds | 0.6651 | 0.1575 | 0.3347 | 1 | |||||||||||
| City funds | 0.5982 | 0.1281 | 0.4901 | 0.2974 | 1 | ||||||||||
| Bureaucratic | −0.0763 | −0.0956 | −0.1431 | 0.0362 | 0.0081 | 1 | |||||||||
| Internal professional | 0.2676 | 0.2207 | 0.1688 | 0.1664 | 0.1551 | 0.132 | 1 | ||||||||
| External consultant | 0.1353 | 0.1127 | 0.2469 | −0.0954 | 0.1503 | 0.0127 | 0.1534 | 1 | |||||||
| Previous experience | 0.4237 | 0.0997 | 0.4038 | 0.3303 | 0.4283 | −0.0139 | 0.0614 | 0.0971 | 1 | ||||||
| Age | 0.0908 | 0.092 | −0.0257 | 0.111 | 0.0421 | −0.0572 | −0.0169 | 0.1024 | 0.0716 | 1 | |||||
| Mission area | 0.0084 | −0.1063 | 0.0071 | 0.1054 | 0.0552 | 0.232 | 0.1214 | −0.0133 | 0.112 | 0.0285 | 1 | ||||
| Size | 0.0532 | −0.0323 | 0.1048 | −0.0663 | 0.2373 | 0.0749 | 0.2503 | 0.1772 | 0.1015 | 0.1667 | 0.0437 | 1 | |||
| Assets size | 0.1043 | 0.1981 | 0.0202 | −0.0177 | 0.0415 | 0.0959 | 0.3437 | 0.1201 | 0.0377 | 0.2283 | 0.0741 | 0.3741 | 1 | ||
| Surplus | −0.0749 | −0.1419 | −0.0436 | −0.009 | 0.042 | 0.0438 | −0.1554 | 0.1254 | −0.0985 | −0.2026 | −0.119 | −0.0408 | −0.1762 | 1 | |
| Sub sector | −0.1384 | −0.0953 | −0.1463 | −0.0354 | −0.1188 | −0.0055 | 0.108 | 0.0223 | −0.071 | −0.0061 | 0.0597 | 0.0655 | 0.2628 | 0.0335 | 1 |
Regression results.
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | |
|---|---|---|---|---|---|
| Total funds | Federal funds | State funds | County funds | City funds | |
| Bureaucratic | −0.0720 | −0.0809 | −0.148 | 0.0237 | −0.0529 |
| (0.0503) | (0.0775) | (0.0983) | (0.114) | (0.160) | |
| Internal professionals | 0.579*** | 0.473* | 0.440 | 1.064** | 0.942 |
| (0.154) | (0.237) | (0.303) | (0.351) | (0.530) | |
| External consultants | 0.0902 | 0.141 | 0.522 | −0.984* | 0.0118 |
| (0.163) | (0.253) | (0.305) | (0.462) | (0.534) | |
| Previous experience | 0.856*** | 0.272 | 0.982*** | 1.475*** | 2.459*** |
| (0.144) | (0.233) | (0.278) | (0.340) | (0.624) | |
| Age | 0.00232 | 0.00222 | −0.0106 | 0.0225* | 0.000762 |
| (0.00517) | (0.00783) | (0.0110) | (0.0113) | (0.0192) | |
| Mission area | −0.0457 | −0.492 | 0.0651 | 0.511 | 0.894 |
| (0.175) | (0.292) | (0.349) | (0.353) | (0.592) | |
| Staff size | −0.00274 | −0.0103 | 0.00287 | −0.0128 | 0.0109 |
| (0.00326) | (0.00648) | (0.00588) | (0.0114) | (0.00769) | |
| Assets size | 0.0496 | 0.142* | 0.0104 | −0.0597 | 0.0494 |
| (0.0384) | (0.0601) | (0.0700) | (0.0817) | (0.145) | |
| Surplus | 0.236 | −0.510 | −0.290 | 1.916* | 2.775 |
| (0.440) | (0.651) | (0.901) | (0.975) | (1.602) | |
| Education | −0.0537 | 0.0674 | −0.0998 | −0.135 | −0.610 |
| (0.248) | (0.359) | (0.467) | (0.671) | (0.941) | |
| Health | −0.478 | −0.509 | −0.887 | 0.289 | −1.342 |
| (0.300) | (0.463) | (0.633) | (0.640) | (1.083) | |
| Human services | −0.621** | −0.550 | −0.867 | −0.00720 | −1.830 |
| (0.218) | (0.329) | (0.456) | (0.451) | (0.955) | |
| Others | −0.266 | −0.265 | −0.308 | 0.186 | −0.457 |
| (0.201) | (0.301) | (0.382) | (0.485) | (0.698) | |
| _cons | −0.0771 | −1.596* | −0.393 | −2.104 | −3.995* |
| (0.493) | (0.766) | (0.894) | (1.103) | (1.960) | |
| Log likelihood | −204.95598 | −130.76405 | −90.268954 | −81.620111 | −44.913082 |
| Wald chi-square | 75.61*** | 26.25** | 31.33** | 40.91*** | 40.31*** |
| df | 13 | 13 | 13 | 13 | 13 |
| Pseudo R 2 | 0.1557 | 0.0912 | 0.1479 | 0.2004 | 0.3098 |
| N | 116 | 116 | 116 | 116 | 116 |
-
Standard errors in parentheses; art and humanities nonprofits is the reference group. * p < 0.05, ** p < 0.01, *** p < 0.001.
Hypothesis 1 proposes that nonprofits with higher degrees of bureaucratic orientation are more likely to obtain government relief grants during the COVID-19 pandemic. This result is not supported by the OLS regression models. Bureaucratic orientation is not statistically significantly associated with receipts of government grants in general, federal grants, county grants and city grants. The finding suggests that bureaucratic orientation is not associated with the recipients of state relief grants during the COVID-19 pandemic.
Hypothesis 2A proposes that nonprofits with internal fundraising professionals are more likely to obtain government relief grants during the COVID-19 pandemic. The hypothesis is partially supported by the results of the regression models. For receipts of government relief grants in general, the coefficient for internal fundraising professionals is positive, and the variable is significant at the 0.01 level. To be more specific, the analysis estimates that nonprofits with internal fundraising employees have an expected count of receiving government funds that is 1.785 times (exp (0.579)) higher than nonprofits without internal fundraising employees. The finding indicates that nonprofits with professional staff who work on fund raising generally have advantages in obtaining government grants. Similar to the general trend observed in the acquisition of government relief grants, the presence of internal fundraising professionals is positively associated with receipt of both federal and county relief grants. The effect sizes for these associations are 0.473 and 1.064, achieving statistical significance at the 0.05 and 0.01 levels, respectively. In contrast to receipt of government relief grants in general, federal and county relief grants, internal fundraising professionals are not statistically significantly associated with receipt of state or city relief grants. The findings suggest that nonprofits with internal fundraising professionals is beneficial for securing government grants at the federal and county levels. Hypothesis 2B proposes that nonprofits with external consultants on fundraising are more likely to obtain government relief grants during the COVID-19 pandemic. The hypothesis is not supported by the regression models. Specifically, a negative association is observed between external fundraising consultant and the receipts of county grants, with an effect size of −0.984 (p < 0.05), which is contrary to our initial expectations. Unlike receipts of state relief grants, having external consultants in fundraising is not statistically significantly associated with the receipt of relief grants in general or from other levels of government. The findings suggest that the engagement of external fundraising consultants may not be advantageous for nonprofits in their efforts to secure relief grants.
The analysis provides partial support for Hypothesis 3, which proposes that nonprofits with previous experience in government grant applications are more likely to obtain government relief grants during the COVID-19 pandemic. The hypothesis does not achieve statistical significance only using federal grants as the dependent variable. For the receipt of relief grants in general, the coefficient is positive and is significant at the 0.001 level, which suggests that nonprofits with previous experience in government grant application are more likely to obtain government relief grants during the COVID-19 pandemic in general. Similarly, having previous experience in government grant application is positively associated with receipts of relief grants at the local level, including at the state, county and city level. The findings indicate that previous experience in government grant applications helps in the obtainment of relief grants at all levels, except for the federal level.
The results of the six control variables are also reported in Table 4. Organizational age achieves statistical significance at the 0.05 level in the model explaining county funds as the dependent variable. It suggests that older nonprofits are more likely to achieve government funding at the county level. Contrary to what we expected, organizational staff size and mission area are not significantly associated with the receipts of relief grants from governments. The findings suggest that nonprofits appear to have equal opportunities to obtain government relief grants, regardless of their staff size and whether their mission was focused on disaster response before the COVID-19 pandemic. The size of assets achieves statistical significance at the 0.05 level in the model explaining the receipt of federal funds. It suggests that nonprofits with larger financial size have a higher likelihood of receiving federal-level government financing. Similar to organizational age, surplus is observed to be positively associated with the receipts of relief funds from county governments, at the significance level of 0.05. This suggests a favorable relationship for nonprofits with higher surpluses in terms of accessing relief funds. Subsector achieves statistical significance at the 0.01 level in explaining the total number of government funds as the dependent variable. To be more specific, the analysis estimates that human services nonprofits are expected to receive government funds at a rate that is approximately 53.6 % (exp (−0.621)) of the rate for arts and humanities nonprofits. The finding indicates that human services nonprofits are less likely to receive government funds compared to arts and humanities nonprofits.
5 Discussion
The receipt of government funds during disasters have not been explored adequately by previous studies. This article investigated how organizational characteristics and strategies are associated with the receipt of government relief funds (Table 5). The findings reveal that several factors, including the presence of internal fundraising professionals, prior grant application experience, organizational age, asset size, surplus, and subsector, contribute to the receipt of some type of government relief fund by nonprofit organizations. The study improves our understanding of the government and nonprofit funding relationship in the disaster context. The findings of this article are discussed in detail below.
Summary of results.
| Factors evaluated | Hypothesized direction | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 |
|---|---|---|---|---|---|---|
| Total funds | Federal funds | State funds | County funds | City funds | ||
| Bureaucratic | + | |||||
| Internal professionals | + | More likely | More likely | More likely | ||
| External consultants | + | Less likely | ||||
| Previous experience | + | More likely | More likely | More likely | More likely | |
| Age | + | More likely | ||||
| Mission area | + | |||||
| Staff size | + | |||||
| Assets size | + | More likely | ||||
| Surplus | + | More likely | ||||
| Education | + | |||||
| Health | + | |||||
| Human services | + | Less likely | ||||
| Others | NA |
-
All results noted are statistically significant.
First, the degree of bureaucratic orientation is generally not statistically significantly associated with the receipt of government relief funds. This is not consistent with previous research findings that bureaucratic orientation is a positive predictor in terms of receiving government funds. The finding suggests that governments may not take bureaucratic orientation as a consideration when allocating their disaster relief grants, as when they allocated other types of grants or contracted it out. One possible reason is that having a similar organizational structure helps government and nonprofits develop long-term collaboration. Most relief funds are just one-time funds, and governments do not develop long-term collaboration with nonprofits by providing this type of fund. Thus, bureaucratic orientation is not evaluated by governments. In sum, the relationship between bureaucratic orientation and the receipt of government grants is not as clearly related as in previous literature, and this relationship needs further research. Second, having internal fundraising professionals is a strong predictor of the receipt of government relief grants in general, whereas the use of external fundraising consultants does not show to significantly relate to receiving government grants in most cases (the exception being in securing county funds). The trend is particularly evident when nonprofits apply for grants at the federal and county levels but not at the state and city levels. The rationale for this difference is unclear and needs further research. In contrast, having external fundraising consultants appears to offer limited advantage in securing government relief grant. Therefore, organizations seeking to secure government relief grants should consider giving priority to investing in their internal grant professionals over external grant consultants. Third, previous experience in the receipt of government grants is a strong predictor of the receipt of government relief grants. The finding suggests that nonprofits benefit from their previous successful experience in grant applications at all levels except for federal level grant. This might be because federal funds are typically the most formal and competitive, with stringent requirements, while local grants might be more informal and flexible. Nonprofits with experience may have established relationships with grantors and a deep understanding of the local grant context, which gives them an advantage in receiving local funds. Thus, nonprofits may consider taking advantage of pre-disaster experience to develop strategies to cope with external disasters. This article also confirms “path dependence” in government grant application and indicates that previous performance in funding application influences current performance.
Among the variables of organizational characteristics, organizational age is found to positively relate to the receipt of county-level government relief funds, which is consistent with the liability of newness theory and the findings of previous studies on government and nonprofit funding relationships. The finding may indicate that organizational age of nonprofits is considered an important factor when county governments allocate COVID-19 relief funds. Compared to federal and state funds, local funds – city and county – embrace a more intimate approach, valuing local community integration and impact. Older nonprofits are often deeply embedded within their communities. This local presence and the trust they have built over time resonate well with county officials who prioritize community-based impacts. Though with a community focus, California cities compared to counties have broad powers of self-government (California State Association of Counties 2024) and more like to target on addressing urban-specific challenges efficiently and newer and more agile nonprofits that are perceived as more innovative or capable of addressing these types of challenges.
Moreover, the financial robustness of a nonprofit, indicated by its asset size and surplus, plays a crucial role in securing funds from different levels of government. Nonprofits with significant assets are more likely to obtain federal funds, which are typically larger and more competitive than state, county, and city level funds. Federal funding bodies prioritize projects that promise measurable impacts on a broader scale, naturally favoring well-endowed nonprofits that can extend their reach effectively. In contrast, local governments, including counties and cities, often operate with tighter budgets. They may perceive nonprofits with surplus funds as financially stable and sustainable, and thus capable of fulfilling funding requirements with lower risk. This perspective can influence county officials to trust these nonprofits with funds critical for continuing essential community services. Cities, on the other hand, may allocate their more modest budgets towards specific issues such as homelessness, urban blight, or public health crises. In such cases, the availability of a nonprofit’s surplus funds might be less of a deciding factor compared to the nonprofit’s ability to deliver innovative solutions or target projects with substantial impact. Therefore, nonprofits boasting larger assets and reserves are in a favorable position when competing for federal and county relief funds, as their financial capacity is often associated with lower risk and greater potential for widespread impact. Conversely, factors like previous provision of disaster-related services or the staff size do now show significant relationship with the receipt of government funds, indicating that these aspects may not be primary considerations in governments fund allocation decisions.
Subsector is significantly associated with the receipt of relief funds in general. Notably, the finding suggests that human services nonprofits receive fewer governmental relief funds in general compared to arts and humanities nonprofits, a finding that diverges from previous literature. This discrepancy might stem from the disproportionate impact of COVID-19 on the arts sector, as suggested by Kim and Mason (2020), leading governments to allocate relief funds based on the severity of impact rather than subsector classification. Therefore, human services nonprofits should be aware of their disadvantages in securing government relief funds during disaster or crisis scenarios. They may find it beneficial to strategically leverage this knowledge to attract more private grants and donations. Additionally, government agencies may need to ensure that human services organizations are allocated a fair share of funding, especially considering their essential role in serving minority and vulnerable populations.
In comparing various models, this article finds that distinct factors are associated with the receipt of relief funds from federal, state, and local governments. Federal-level relief funds are more likely to be allocated to nonprofits that have internal professionals and large total assets. In contrast, the receipt of state-level relief funds is only found to relate to organizations’ previous experience in receiving grant application. For county level relief funds, a combination of factors, including professional and previous experience, organizational age, and surplus, play a role. Meanwhile, city-level relief funds appear to only be associated with previous experience in receiving grant applications.
6 Limitations
This article is not without limitations. Some limitations are related to data collection. First, the NCCS 2017 Core File was used to identify nonprofits in the sampling frame. This sampling frame has sampling bias toward larger nonprofits whose revenue is larger than $50,000 and nonprofits founded before 2017. Therefore, generalizing the findings of the research to smaller and younger nonprofits is not possible. Second, accurately identifying the exact sources of government finances presents a challenge, particularly when funds traverse multiple levels of government, including federal, state, and local. In some cases, respondents to our survey might not have had complete insight into the precise origins of specific funds. This limitation potentially affects the validity of our dependent variable, as it is based on self-reported data regarding the types of government funds nonprofits receive. Third, our survey faced a low response rate. We initially reached out to 9524 nonprofits but ultimately analyzed data from only 116. A major factor contributing to this steep decline is likely survey fatigue among respondents during COVID-19. It is likely that nonprofit leaders were feeling overwhelmed or exhausted by the volume of surveys they were being asked to complete regarding COVID-19. Moreover, the data mining techniques used to collect the contact information of nonprofits in this study may have introduced a selection bias, as some email contacts listed on organizations’ websites might be outdated or incorrect.
In order to assess the sample representativeness, we compared the subsector and total asset distributions between all CA nonprofits that are included in the 2019 NCCS core file and the nonprofits in our sample. The comparative results are demonstrated in Tables 6 and 7. Our analysis indicates adequate representation across different subsectors in our sample. In terms of assets size, both the sample and the entire CA nonprofits from the 2019 core files show similar means and ranges. It is noted, though, the maximum value of organization size in the sample is smaller than that of the broader group, suggesting that the results from this study may not apply to extremely large nonprofits. Despite these limitations, this study is among the first to investigate how nonprofits’ receipt of government COVID-19 relief grants is explained by organizational and institutional factors. We believe the findings speak to how collaborative governance can be better leveraged for societies to effectively respond to disasters through understanding the needs and challenges of nonprofits with different profiles during disaster times, which may deviate from what are observed under non-disaster contexts.
Sample and population comparison among subsectors.
| Subsector | Frequency | Frequency | Percent | Percent |
|---|---|---|---|---|
| All CA nonprofits | Sample nonprofits | All CA nonprofits | Sample nonprofits | |
| Art and humanity | 6005 | 30 | 11.54 | 25.86 |
| Education | 9964 | 18 | 19.15 | 15.52 |
| Health | 4852 | 10 | 9.32 | 8.62 |
| Human services | 16,377 | 32 | 31.47 | 27.59 |
| Others | 14,840 | 26 | 28.52 | 22.41 |
|
|
||||
| Total | 53,038 | 116 | 100.00 | 100.00 |
Sample and population comparison for assets size.
| Count | Mean | S.D. | Min | Max | |
|---|---|---|---|---|---|
| Assets size in sample | 116 | 12.5418 | 22.47855 | 0 | 18.37055 |
| Assets size for CA nonprofits | 42,861 | 11.70416 | 3.101758 | 0 | 24.66899 |
In terms of the analysis, it is noted that certain potentially relevant variables were not included or focused on in this study, such as the fundraising expense (Ashley and Faulk 2010; Ashley and Van Slyke 2012) and ecological factors (Garrow 2011). Financial indicators were omitted since a low response rate was obtained to financial-related questions, and ecological factors were omitted since the survey was at the organizational level. Therefore, we are unclear about the impact of fundraising expense and ecological factors on the receipts of government relief grants based on this study.
7 Future Direction
Government funding is one of the most essential revenue sources of nonprofits. During the time of disasters, government funding can be especially critical for the survival and success of nonprofits. This article explores the receipt of government COVID-19 relief funds from a nonprofit perspective. It is also interesting to explore government and nonprofit funding relationships in a disaster context from a government perspective. Therefore, one possible future direction is to study the allocation of disaster relief funds from a government perspective. Second, this article only includes relatively large and established nonprofits. However, smaller and younger nonprofits might be more vulnerable after impacts of disasters like pandemics (Chen 2022b; Joseph 2011; Lin and Wang 2016) and in need of government support due to the liability of smallness and newness (Stinchcombe 2000). Thus, future studies could focus on smaller and younger nonprofits and their funding relationship with governments. Third, previous studies show that nonprofits’ financial health and the external environments in which they are embedded may also influence their obtainment of government funds (Ashley and Faulk 2010; Ashley and Van Slyke 2012; Garrow 2011). Although these variables are not the focus of this article, it is interesting to explore whether these variables are associated with the obtainment of governmental relief funds in disaster settings. Further, this article identifies distinct factors associated with the receipt of funds from federal, state, and local governments, but the underlying reasons for these differences remain unclear. Thus, future studies should aim to decipher the distinctions among the different types of government funds and how these differences may affect their respective selection criteria and processes. Finally, linking the receipt of government relief funds to nonprofit performance in a disaster context is an interesting research direction. For example, does the receipt of government relief funds help nonprofits sustain and grow during disasters? Does the receipt of government relief funds contribute to nonprofit performance in service provision?
8 Conclusions
This article explores organizational factors of nonprofits that contribute to the obtainment of government disaster relief funds in the context of the COVID-19 pandemic by surveying nonprofits whose main offices were located in California. The findings show that, in general, having internal professionals in fundraising, and having previous experience in receiving government funds, significantly contribute to the successful receipt of government relief funds during COVID-19. Different levels of government may value different types of nonprofits and are likely to use different requirements and criteria to assess nonprofits. In other words, different nonprofit managerial strategies and organizational characteristics are associated with the obtainment of disaster relief grants from different levels of government. More specifically, nonprofits with internal professionals in fundraising and large total assets are more likely to successfully secure federal-level government relief grants. A history of government funding is helpful for nonprofits to obtain state-level government relief grants. Receiving county-level relief funds is explained by a variety of elements, including professional and prior expertise, organizational age, and surplus. Having previous experiences in government grant applications contributes to the receipt of city-level government relief grants. Finally, the article confirmed that different organizational factors are associated with the receipt of government relief funds when compared with other types of funds.
This article contributes to research in several ways. First, this research adds to the discussion of government and nonprofit funding relations by exploring factors that affect this relationship in a disaster setting. It confirmed that different factors contribute to the receipt of government relief funds compared to other types of funds. Besides, it contributes to the public management literature by deepening our understanding of nonprofit management in a disaster context. In addition, this study also holds implications for practitioners. First, governments can better support nonprofits following disasters by strategically allocating grants and resources to nonprofits based on this information. Moreover, being able to understand which types of nonprofits gain government funds during the COVID-19 pandemics helps in the decision-making of nonprofits in future disasters. Nonprofit managers can gain insights useful for developing strategies and navigating resources to cope with disasters. Private donors can also use this information to strategically donate to nonprofits in a disaster context.
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This work is licensed under the Creative Commons Attribution 4.0 International License.
Articles in the same Issue
- Frontmatter
- Research Articles
- Navigating Government Funding During a Pandemic: A Study on Nonprofits’ Receipt of Disaster Relief Funds
- Giving Voice: Examining the Tactical Repertoires of Nonprofit Advocacy for Disadvantaged Populations
- The Social Enterprise Craze: CSO Financial Sustainability in Ghana
- Policy Actors’ Struggle for Attention: The Role of Peer Networks in the Migration Discourse on Twitter (X)
- Framing of Civil Society Organizations’ Communication on Facebook: Examining the Impact on Audience Engagement in Norway
Articles in the same Issue
- Frontmatter
- Research Articles
- Navigating Government Funding During a Pandemic: A Study on Nonprofits’ Receipt of Disaster Relief Funds
- Giving Voice: Examining the Tactical Repertoires of Nonprofit Advocacy for Disadvantaged Populations
- The Social Enterprise Craze: CSO Financial Sustainability in Ghana
- Policy Actors’ Struggle for Attention: The Role of Peer Networks in the Migration Discourse on Twitter (X)
- Framing of Civil Society Organizations’ Communication on Facebook: Examining the Impact on Audience Engagement in Norway
