Perception of Internal Controls Helps Explain Whistleblowing

Abstract

The nonprofit sector may suffer financially from inconsistency in regulations and polices surrounding internal control implementation. To address this issue, our study explores how perceived internal control strength differs between nonprofit and for-profit organizations. Furthermore, we examine three components of the Committee of Sponsoring Organization framework to determine which components might significantly influence whistleblowing for nonprofit organizations. As expected, all three components appear to significantly influence whistleblowing for those in for-profit organizations. For those in nonprofit organizations, the perception of control activities and monitoring activities significantly mediates the relationship between organization type and whistleblowing intentions. Finally, the data indicate that the use of an anonymous website for whistleblowing at a nonprofit organization may require added attention and resources if employees at nonprofits are to use this outlet to the same extent as it is used at a for-profit organization.

Keywords

whistleblowing reporting intentions nonprofit organization type internal controls

Introduction

Nonprofits are not immune to fraud, and even those with the best intentions can still become victims. Nonprofit fraud cases that make the news shock the public and bring up questions as to what nonprofits are doing to protect themselves and their donors. Such headlines include “How Red Cross fraud cost Ebola fight efforts $6 million” (Mukherjee, 2017); “Indictment in US$6.7 million IT fraud at charity” (The NonProfit Times, 2019); and “Nonprofit manager charged with embezzling money meant for disabled kids” (Rasmussen, 2019). Because fraud is an issue in nonprofits, the control systems need to be effective not only in reducing fraud intentions but also in increasing whistleblowing intentions. Tips from insiders are one of the most prevalent forms of whistleblowing. Thus, it is important to know to what extent the perception of the organization’s existing internal controls encourages whistleblowing. We investigate this question, focusing on the nonprofit community.

The nonprofit community lacks the regulatory attention for-profits have relating to internal controls. Furthermore, there is a lack of clarity and consistency across nonprofits that choose to implement internal controls. This shortcoming may lead to a perception that nonprofits do not place the same emphasis on internal controls that for-profits do. Little research investigates this perception within nonprofit organizations. One study focuses on for-profits but acknowledges the potential usefulness of documentation and testing for nonprofits (Graham, 2015). Overall, literature is uninformed about how the strength of each perceived internal controls affects whistleblowing, especially in nonprofit organizations.

Recent research has shown that nonprofits experience similar pressures as for-profits to obtain positive audit opinions (Feng, 2014); manage pension assumptions (Vermeer et al., 2014) and taxable income (Omer & Yetman, 2003); and actively manage ratios that may help to attract donors to a nonprofit, because greater efficiency is associated with higher donations (Parsons et al., 2017; Tinkelman, 1999). These financial pressures may increase the pressure for individuals to commit fraud. Yet, where public for-profit organizations are mandated to have internal controls that help counter these incentives, nonprofit organizations lack such mandates. As a result, those in nonprofit organizations may not be influenced by all of the same controls as are those in for-profit organizations.

Literature finds that firms with strong internal controls are less likely to experience fraud. For example, strong internal controls reduce the opportunities to engage in self-interested behavior (Patterson & Smith, 2007). Furthermore, Liu et al. (2015) find that the way in which management frames the purpose of the controls influences fraud intent. When controls are framed as being used for monitoring purposes, fraud intent decreases, whereas when controls are framed as being used for coordinating purposes, fraud intent increases. This framing is consistent with regulatory actions and auditing standards commonly associated with for-profit organizations (e.g., American Institute of Certified Public Accountants [AICPA], 2002; Committee of Sponsoring Organizations [COSO], 1999; Public Company Accounting Oversight Board [PCAOB], 2007a, 2007b, 2010). Up until now, little prior knowledge has existed about how the perception of internal controls affects whistleblowing intentions, particularly in environments where internal controls are not required.

Thus, informed by literature and practice, this study attempts to address part of the gap in knowledge by examining the relationship of internal controls on the path between organization type and whistleblowing intentions. To measure the strength of internal controls, we developed questions based on the COSO framework, focusing on control environment, control activities, and monitoring activities. Each of the three components is examined to identify the effect of organization type on the perception of internal controls. Furthermore, the paths between each internal control component and whistleblowing intentions are tested.

We conduct a survey of 272 individuals who are currently employed full-time in either a nonprofit or for-profit organization. Research suggests the implementation of Section 404 of Sarbanes–Oxley (SOX 404) in public companies led to both stronger internal controls and a decrease in fraud (Patterson & Smith, 2007). Thus, it seems likely that nonprofits with similar internal controls may also benefit similarly. As a result, we believe that perception of internal controls describes the path between organization type and whistleblowing intention. Untabulated results suggest that these findings apply to asset misappropriation in a similar manner to the financial statement fraud results reported in this study.

The data suggest organization type influences the perceived strength of the total internal control framework, as well as each of the components (control environment, control activities, and monitoring activities). In all instances, the perceived strength of the internal control framework and the perceived strength of each of the three components of the framework significantly predict reporting intentions to the whistleblowing hotline. Similarly, perceived internal control strength, control activities, and monitoring activities separately mediate the path between organization type and whistleblowing intention. The data suggest a focus on control and monitoring activities would be beneficial for nonprofits seeking to encourage a culture of whistleblowing. Finally, it is helpful for nonprofits to know that nonprofit employees may not yet be as comfortable reporting through a website as are for-profit employees. With this knowledge, theory is extended, and nonprofit management can take steps to improve internal controls and encourage whistleblowing.

The next section of this article consists of literature review and hypothesis development, followed by the “Method” and “Results” sections. We close with the “Discussion” section where we address implications of our findings, limitations, and future research.

Literature Review and Hypotheses

Whistleblowing

Near and Miceli (1985) provided what has become the standard in whistleblowing literature by defining whistleblowing as “the disclosure by organization members (former or current) of illegal, immoral, or illegitimate practices under the control of their employers, to persons or organizations that may be able to affect action.” Near and Miceli (1988) further expanded their definition to include identifying and bringing attention to questionable practices in an attempt to help potential victims and/or benefit the organization if the practices diverged from the organization’s stated values. They later (1996) identified three elements necessary to whistleblowing: (a) someone needs to commit a perceived wrongdoing, (b) another needs to become aware of the perceived wrongdoing and report it, and (c) someone else needs to record the report of wrongdoing (Near & Miceli, 1996).

Lee and Xiao (2018) and Gao and Brink (2017) recently completed a review of the whistleblowing literature, examining what has been studied as determinants of internal and external whistleblowing. Such determinants include characteristics of the whistleblower (personality, affective states, attitudes, moral judgment, demographics, compensation, perceived responsibility, costs and benefits, etc.); report recipient (similar to whistleblower, plus inquiry, retaliation, likeability, etc.); reporting channel (administration, anonymity, monetary incentives, etc.); wrongdoer (power, credibility, likeability, social relationship, etc.); wrongdoing (evidence, legality, dependence on the wrongdoing, severity, etc.); and organization (climate, response, justice, structure, governance, etc.) (Gao & Brink, 2017; Lee & Xiao, 2018).

The 2020 Global Study on Occupational Fraud and Abuse includes information about reported nonprofit fraud. The study notes a median loss for fraud in nonprofits as US$75,000 (which rises to US$250,000 if the fraud is committed by an executive) and an average loss of US$639,000 (Association of Certified Fraud Examiners [ACFE], 2020). In 35% of the cases reported, a lack of internal controls was cited as the primary weakness that contributed to the occurrence of fraud (ACFE, 2020). An investigation by the Washington Post revealed that between 2008 and 2012 more than 1,000 nonprofit organizations indicated on Internal Revenue Service (IRS) Form 990 that the organization had experienced a significant diversion of assets (Stephens & Flaherty, 2013). Many of the losses ranged from US$1 million to well over US$40 million (Stephens & Flaherty, 2013). Archambeault et al. (2015) found that less than 20% of the organizations, which met the criteria for Form 990 diversion of asset disclosure, correctly completed the report requirements. Their findings suggest the number of nonprofits experiencing fraud may be much higher than the statistics indicate. Furthermore, Snyder et al. (2017) indicated that 19% of their nonprofit sample specified an incidence of fraud in the prior year, a number far higher than that typically seen in reports.

Rothschild (2013) discovered that employees of nonprofits generally view their organizations as having much higher moral leadership than employees of other organization types and these nonprofit employees are less likely to whistleblow. Overall, Rothschild (2013) concludes that whistleblowing is much more prevalent among public sector employees than among nonprofit employees. Scheetz, Smalls, Wall, and Wilson (2020) examined organization size and type to find that nonprofit employees are significantly less likely to whistleblow than for-profit employees, especially those nonprofit employees in international organizations where inconsistency in policies (such as whistleblowing or internal control implementation) between regions may be an issue.

The nonprofit literature has, for the last decade or two, tried to bring attention to the lack of internal controls in the nonprofit sector (Archambeault et al., 2015; Gallagher & Radcliffe, 2002; Greenlee et al., 2007). These studies highlight the nonprofit fraud problem and express a belief that internal controls can help curb this problem.

Internal Controls

Although Section 404 of the SOX Act of 2002 applies mostly to public companies, some nonprofit organizations, due to their funding sources,¹ are also required to implement internal controls and undergo audits (U.S. Congress, 2002). In addition, many nonprofits simply choose to adopt best practices from SOX, including internal controls (Iyer & Watkins, 2008). The implementation of SOX reporting requirements on the effectiveness of internal controls provides data on how the implementation of such controls affects fraud occurrences and detection. Nezhina and Brudney (2012) learned that in their sample of nonprofit organizations, half had implemented some components of SOX. Those nonprofits that adopted SOX provisions experienced better internal controls, to which many nonprofits attributed their reduced fraud risk (Nezhina & Brudney, 2012). Patterson and Smith (2007) recorded that following the implementation of SOX 404, the strength of internal controls increased and fraud decreased. Similarly, Donelson et al. (2017) observed a significant association between material internal control weaknesses and financial reporting fraud. Recent research has suggested nonprofits report financial statement error rates that are nearly twice as high as those of similarly sized publicly traded corporations (Burks, 2015) and that SOX may increase reporting quality for nonprofits (Garven et al., 2017). Although nonprofit organizations are not required to adhere to SOX, the data about error rates and ineffective controls are troubling and reaffirm the need for internal controls in all organizations.

Some research suggests that parts of internal controls may be detrimental to the firm (e.g., Christ, 2013; Christ et al., 2008, 2012; Das & Teng, 2001; Falk & Kosfeld, 2006; Hannan et al., 2006; Liu et al., 2015). For example, Christ (2013) contends that employees reduce effort when formal controls are in place, as employees infer the control as a sign of distrust. Christ et al. (2008) also propose that behavioral controls can compromise trust and cooperation. Falk and Kosfeld (2006) suggest most employees exhibit control-adverse behavior, where performance can decrease in reaction to controls. These studies have primarily focused on the impact controls have in a public company environment. Thus, the debate over the impact of required controls (such as in public companies) versus the impact of voluntarily instituted controls (such as in private companies and nonprofits) is both restricted in scope and unresolved.

Often, the COSO internal controls framework is used as a basis for designing internal controls by those small public or private companies and nonprofit organizations that choose to adopt an internal control focus. The COSO framework established five interrelated components related to these controls: control environment, risk assessment, control activities, information and communication, and monitoring activities (COSO, 2013). This study uses the COSO framework to measure perception of internal controls and focuses on control environment, control activities, and monitoring activities because they are more observable by employees at every level of the organization.

The control environment component of the COSO framework focuses on the entity’s organizational structure, processes, policies, and standards to facilitate a healthy control culture within an organization (COSO, 2013). This component captures a range of elements considered necessary for a strong internal control system. One of the factors considered when assessing the strength of the control environment is whether people throughout the organization both are aware of the importance of risk management and understand the risk profile of the organization. Another factor to consider is whether management and the board of directors set a strong tone at the top. In a poor control environment, retaliatory actions may be tolerated or empowered, thus reducing whistleblowing intent. Donelson et al. (2017) suggest that weaknesses in entity-wide controls are associated with an increased risk of fraud instance and disclosure by the entity. Thus, a strong control environment may reduce fraud instances, but increase the likelihood of whistleblowing.

Control activities help address control environment weaknesses. Control activities refer to the internal control system of the organization, which includes the policies and procedures that define the approval processes, authorization levels, security of assets, and the segregation of duties (Agbejule & Jokipii, 2009; COSO, 2013). COSO (2013) defined control activities as “the actions established through policies and procedures that help ensure that management’s directives to mitigate risks to the achievement of objectives are carried out” (p. 6).

Although control activities define an organization’s internal control system, the monitoring activities component focuses on the observation of these systems and ensuring their effectiveness, such as direct supervision and evaluation (Agbejule & Jokipii, 2009; COSO, 2013). Research has found that weak monitoring of controls results in a pervasive negative impact through an increased reporting of material weaknesses (Klamm & Watson, 2009). In addition, high degrees of monitoring contribute to highly effective internal control systems, which provide reasonable assurance to those charged with governance that financial statements are being reliably prepared (Agbejule & Jokipii, 2009).

Much of literature has found that the control environment, control activities, and monitoring activities help prevent, deter, and detect fraud in public organizations (Dorminey et al., 2012). And yet, there is little direct evidence linking internal controls to higher whistleblowing intentions. Given the lack of literature specifically examining the influence of internal controls on whistleblowing intentions, we believe strength will beget strength. Given the findings of Scheetz et al. (2020) that organization type significantly influences whistleblowing intentions, we expect that the perception of internal controls will help explain the path between organization type and whistleblowing intention. Prior research suggests whistleblowing intention is high in the for-profit community. This higher whistleblowing intention makes sense given the mandatory internal control environment in the public for-profit community. However, because nonprofit organizations choose their control environment, it seems likely this whistleblowing intention may be better explained by the perception of the internal controls. To determine the effect, the responses of those in nonprofit organizations need to be tested. Thus, our hypotheses, formally stated, are as follows:

Hypothesis 1 (H1): The overall perception of the combined internal controls system will mediate the path between organization type and whistleblowing intention.

Hypothesis 2 (H2): Each primary component of an internal control system will mediate the path between organization type and whistleblowing intention.

Although we believe that internal controls will mediate the path between organization type and whistleblowing intention, and expect strong internal controls to increase whistleblowing, we have not yet answered the question of what aspects of internal controls are most useful to nonprofits in this context. A vast review of literature informs us of the tendency of nonprofit organizations to become more business-like (Maier et al., 2016). Furthermore, a compendium of contributions from around the world finds that internal controls are very important but are inconsistently implemented (Anheier & Toepler, 2020). The same book suggests ways firms could adopt policies keeping COSO components in mind. Yet, nonprofits have limited resources and often face immense pressure to employ practices that primarily benefit whichever resources are provided (Verbruggen et al., 2011). Thus, not all COSO components may matter to those in nonprofit organizations. Understanding which components influence whistleblowing intentions in nonprofits, as measured through the lens of each primary component of an internal control system, should help nonprofits design policies, which are more effective in increasing whistleblowing intentions. Thus informed, we ask the question:

Research Question 1 (RQ 1): Which primary components of an internal control system are relevant to nonprofit organizations seeking to encourage whistleblowing?

Method

Design

Due to the lack of literature exploring whistleblowing intentions in nonprofit and for-profit organizations in the same study and, more specifically, how perceived internal controls mediate whistleblowing behavior, we implemented a survey approach to assess judgment and decision-making differences between individuals working in these organization types. We utilized a survey in which (n = 272) full-time workers answer questions about the organization for which they work, their perceptions of internal controls in their workplace, and their likelihood of whistleblowing.

Materials and Procedures

A large survey company contacted the participants who met our desired participation requirements. The survey company emailed individuals directly with the access code to our online survey. Initial screening questions were provided to ensure that participants met our desired employment requirements, which were the following: the individual works for pay 30 or more hours a week for a nonprofit or for-profit and has also been employed by the organization for at least 1 year. Participants who qualified were then allowed to proceed with the remainder of the survey.²

Participants were provided with a brief scenario describing a financial statement fraud that was occurring within their organization. The scenario stated, You discover your supervisor within the organization is falsely manipulating the financials to make the organization look better than it is. This scenario was chosen because it is very broad and could apply to any size or type of organization.³ Participants were then asked to identify the likelihood that they would report the fraud via an anonymous reporting phone hotline. The remainder of the survey consisted of questions to assess the participant’s perception of internal controls in their organization, as well as capture their demographic information.

Participants

We believe that practical experience best uncovers underlying differences in organization types and, therefore, sought a wide range of participants with experience working in nonprofit and for-profit organizations. We asked participants to answer questions about internal control strength in their organizations based on their experiences at their organizations. It was imperative that the participants be currently employed by a nonprofit or for-profit so that we could tease out how perceptions of control strength differed by organization type and ultimately affect whistleblowing. Two hundred seventy-two of the participants selected by the survey company fully completed the survey.

One hundred fifty-three participants were from for-profit organizations, while 119 were from nonprofit organizations. Although the gender of participants is relatively evenly split in the for-profit sample, gender is skewed female (82%) in the nonprofit sample. This imbalance reflects the gender imbalance seen in practice (Lennon et al., 2013). The mean age, full-time work experience, and years at current employer of both samples are relatively similar. However, the nonprofit sample has a higher average level of education: 18% of for-profit employees have a master’s degree and 8% have a PhD, compared with 27% and 10% of nonprofit employees. Participants come from a wide range of occupations such as clerk, pastor, health care executive, case manager, legal assistant, marketing specialist, receptionist, and director of communications. Demographic information can be found in Table 1.

Table 1.

Demographic Statistics (N = 272).

Demographic Categories	Total^a	For-profit	Nonprofit
Gender
Male	35.5%	49.7%	16.8%
Female^b	64.5%	50.3%	82.4%
Age
Mean	42.35	41.22	43.80
SD	13.93	13.64	14.78
Education
High school diploma	14.7%	19.6%	8.4%
Associate degree	13.2%	13.7%	12.6%
Bachelor’s degree	41.2%	40.5%	42.0%
Master’s degree	22.1%	18.3%	26.9%
Doctoral or terminal degree	8.8%	7.8%	10.1%
Years of full-time work experience
M	18.18	18.46	17.81
SD	10.30	10.37	10.23
Years at current employer
M	9.28	9.11	9.49
SD	7.37	7.02	7.82
Overall internal controls perception
M	5.32	5.49	5.11
SD	1.21	1.12	1.29
Organization type
For-profit public	27.9%	—	—
For-profit private	28.3%	—	—
Nonprofit	43.8%	—	—
Location^c
Northeast (New England and Mid-Atlantic)	22.06%	15.69%	30.25%
Midwest (East and West North Central)	27.21%	24.84%	30.25%
South (South Atlantic, East, and West South Central)	30.88%	36.60%	23.53%
West (Mountain and Pacific)	19.85%	22.87%	15.97%

All participants are paid employees working at least 30 hr per week for a for-profit or nonprofit organization. ^bNonprofit organizations have a large imbalance of females compared with males. Research notes the percentage of females to be about 75 (Lennon et al., 2013). ^cForty-five states and the District of Columbia are represented.

Variables

Measured variable: Organization type

Organization type is a measured variable with two levels: nonprofit and for-profit. Participants were initially contacted by the survey company based on their reported employment and were further measured within the survey by their responses regarding the type of organization (nonprofit versus for-profit) they are currently employed by in a full-time capacity.

Measured variable: Internal controls

Because actual internal controls cannot be measured in a survey we chose to focus on the individuals’ perceptions of internal controls in their current organization. To measure these perceptions, we use the COSO framework, which has been accepted by regulators and used by public companies for several decades and thus provides a sound basis for questions. We adopted the questions for this study directly from the principles laid out in the updated COSO framework (COSO, 2013). We are focusing on three of the five core COSO components: control environment, control activities, and monitoring activities. Pilot testing indicated that the components of risk assessment and communication were performed at a level of the organization beyond that of our participants. As a result, pilot participants indicated they could not knowledgeably answer questions related to these components. Thus, we chose to exclude these two components from the final study.

Participants were given a scale with questions to assess each of the three components: control environment, control activities, and monitoring activities. Each of the variables in the scale, shown in Online Appendix A, is measured on a 7-point Likert-type scale, with 1 being “strongly disagree” and 7 being “strongly agree.” The variables for the three components are created by averaging the Likert-type scale responses for that component (four for control environment, three for control activities, and three for monitoring activities). The internal control systems variable is created by averaging the Likert-type scale responses to all 10 questions (encompassing all three components).

Dependent variable: Whistleblowing intention

Employee tips are the most common fraud detection method in a nonprofit (40%) (ACFE, 2020). Overall (for all organization types), this number increases to 49% for companies that provide hotlines for whistleblowers (ACFE, 2020). Greenlee et al. (2007) reported that in their sample of 58 nonprofit frauds, 43% were detected through tips, but internal controls (14%) also was a significant contributor. Formal tip reports were made most often through a whistleblowing telephone hotline, email, or web-based/online form (all used about 30% of the time) (ACFE, 2020).

As a result of the above, the primary dependent variable for the main analyses is intention to report via phone to a whistleblowing hotline. Participants were asked to respond on a 7-point Likert-type scale, with 1 being labeled “extremely unlikely” and 7 being labeled “extremely likely.” The question posed to the participants was, “How likely are you to report the discovery to the whistleblowing hotline by phone?” Participant responses to this question were used to capture our dependent variable of interest.

The dependent variables for the post hoc analysis are reporting intentions through other channels. Participants were additionally asked to respond on a 7-point Likert-type scale, with 1 being labeled “extremely unlikely” and 7 being labeled “extremely likely” to the following questions. “How likely are you to report the discovery to the supervisor’s manager?” and “How likely are you to report the discovery to the whistleblowing hotline by website?” Participant responses to these individual questions were used to capture our post hoc dependent variables.

Results

Test of Covariates

We tested our demographic variables of gender, age, education, work experience, and years at current employer as potential covariates and found none to be significant. Given the large bias toward females in our nonprofit sample, we also conducted further testing around gender. Whistleblowing does not significantly differ by gender in for-profits (t = 0.760, p = .449) or nonprofits (t = 0.417, p = .677). Furthermore, perception of internal controls does not differ by gender in for-profits (t = 0.986, p = .326) or nonprofits (t = 0.474, p = .636).

Descriptive Statistics

Prior to running the below mediation analyses, we examined the means of each control component by organization type. As seen in Panel A of Tables 2 through 5, for-profit employees perceive the overall internal control system (for-profit mean of 5.49, SD = 1.12; nonprofit M = 5.11, SD = 1.29), control environment (for-profit mean of 5.68, SD = 1.15; nonprofit M = 5.51, SD = 1.30), control activities (for-profit mean of 5.51, SD = 1.19; nonprofit M = 5.03, SD = 1.42), and monitoring activities (for-profit M = 5.21, SD = 1.34; nonprofit M = 4.66, SD = 1.49) to be higher than nonprofit employees. Given that these controls are mandated in public for-profits and not in nonprofits, this is not surprising, but the differences in the means do provide an indication of which components may act as mediators.

Tests of Hypotheses

To test our hypotheses, we used mediation analyses. There is a growing set of literature which disputes the logic of the Baron–Kenny procedure first laid out in Baron and Kenny’s (1986) “Moderator-Mediator Variables Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations.” Hayes (2009) states that a significant total effect (X must affect Y) is not required to test indirect effects (M): “a failure to test for indirect effects in the absence of a total effect can lead you to miss some potentially interesting, important, or useful mechanisms by which X exerts some kind of effect on Y” (Hayes, 2009, p. 415). Zhao et al. (2010) agree and state that a “zero-order effect of X on Y is in fact mathematically equivalent to the “total effect” of X on Y . . . that is, it exactly equals the sum of the “indirect path” (path a x path b, usually hypothesized) and the “direct path” (path c, usually not hypothesized)” (Zhao et al., 2010, p. 199). In alignment with this logic, we do not test or show results for the direct effect of X (organization type) on Y (whistleblowing intention). To test mediation, the Hayes Process macro was used (PROCESS Procedure for SPSS Version 3.5) (Hayes, 2018). Based on the guidance provided by Preacher and Hayes (2008), a bootstrapping iteration of 5,000 was used in the mediation analysis.

Tables 2 –5 display the results for the hypotheses. Table 6 displays the results for the research question and Table 7 displays the results for the post hoc analysis. Figure 1 depicts the mean values for control environment, control activities, and monitoring activities for the various organization type conditions.

Figure 1.

Mean values of perceived strength of internal control components by organization type.

We first examine the effects of the perception of the internal controls system as a whole (the average of the three components together). The results are located in Panel B of Table 2. Results indicate that organization type significantly predicts the perception of the overall internal control system (B = −0.381, SE = 0.147, p < .01), where perception of internal controls is lower among nonprofit employees, and that perception of the overall system positively and significantly predicts whistleblowing intention (B = 0.255, SE = 0.098, p < .01), where higher perceived controls increase whistleblowing. These results support mediation. Organization type is not a significant predictor of whistleblowing after controlling for the mediator, perception of the overall internal control system (B = −0.105, SE = 0.239, ns), consistent with mediation. The results indicate that the indirect coefficient (the effect of organization type on whistleblowing through perception of the control system) is significant (B = −0.097, SE = 0.060, 95% confidence interval [CI] = −0.238, −0.008), further supporting mediation. Nonprofit organizations were associated with intentions to whistleblow, which were 0.097 points lower as mediated by perception of the overall internal control system.

Table 2.

Overall Internal Control System Results.

Panel A: Descriptive Statistics of Perceived Overall Internal Controls by Organization Type
Type of organization	M	SD	N
For-profit	5.49	1.12	153
Nonprofit	5.11	1.29	119
Total	5.32	1.21	272

Panel B: Perceived Overall Internal Control Mediation Analysis.

Path A—Organization type predicts perception of overall internal control system
	Coefficient (unstandardized B)	SE	t	p-value
	−0.381	0.147	−2.603	.005
Path B—Perception of overall internal control system predicts whistleblowing
	Coefficient (unstandardized B)	SE	t	p-value
	0.255	0.098	2.600	.005
Path C′—Mediated path—Organization type predicts whistleblowing through perception of IC
	Coefficient (unstandardized B)	SE	t	p-value
	−0.105	0.239	−0.438	.331
Total direct effects
	Coefficient (unstandardized B)	SE	t	p-value
IC system	−0.105	0.239	−0.438	.331
Total indirect effects
	Effect	Boot SE	Boot LLCI	Boot ULCI
IC system	−0.097	0.060	−0.238	−0.008

Note. SE = standard error; IC = internal controls; LLCI = lower level of confidence interval; ULCI = upper level of confidence interval.

H2 predicts that control environment will mediate the relation between organization type and whistleblowing intention. Results are displayed in Panel B of Table 3. Results indicate that organization type does not significantly predict the perception of the internal control environment (B = −0.175, SE = 0.149, ns) but that control environment does significantly predict whistleblowing intention (B = 0.181, SE = 0.097, p < .05). However, these results do not support mediation, and thus mediation analysis is discontinued.

Table 3.

Internal Control Environment Results.

Panel A: Descriptive Statistics of Perceived Control Environment by Organization Type.

Type of organization	M	SD	N
For-profit	5.68	1.15	153
Nonprofit	5.51	1.30	119
Total	5.60	1.22	272

Panel B: Control Environment Mediation Analysis⁴.

Path A—Organization type predicts perception of control environment
	Coefficient (unstandardized B)	SE	t	p-value
	−0.175	0.149	−1.175	.120
Path B—Perception of control environment predicts whistleblowing
	Coefficient (unstandardized B)	SE	t	p-value
	0.181	0.097	1.868	.031

H2 also predicts that control activities will mediate the path between organization type and whistleblowing intention. Results are displayed in Panel B of Table 4. Results indicate that organization type significantly predicts the perception of internal controls activities (B = −0.485, SE = 0.159, p < .01), where perception of internal control activities is lower among nonprofit employees, and that perception of control activities positively and significantly predicts whistleblowing (B = 0.280, SE = 0.090, p < .01), where higher perceived control activities increase whistleblowing intention. These results support mediation. Organization type is not a significant predictor of whistleblowing after controlling for the mediator, perception of control activities (B = −0.066, SE = 0.239, ns), consistent with mediation. The results indicate that the indirect coefficient (the effect of organization type on whistleblowing through perception of control activities) is significant (B = −0.136, SE = 0.065, 95% CI = −0.280, −0.027), further supporting mediation. Nonprofit organizations were associated with intentions to whistleblow, which were 0.136 points lower as mediated by perception of control activities.

Table 4.

Internal Control Activities Results.

Panel A: Control Activities Cell Means and Standard Deviations.

Type of organization	M	SD	N
For-profit	5.51	1.19	153
Nonprofit	5.03	1.42	119
Total	5.30	1.32	272

Panel B: Control Activities Mediation Analysis.

Path A—Organization type predicts perception of control activities
	Coefficient (unstandardized B)	SE	t	p-value
	−0.485	0.159	−3.058	.001
Path B—Perception of control activities predicts whistleblowing
	Coefficient (unstandardized B)	SE	t	p-value
	0.280	0.090	3.103	.001
Path C′—Mediated path—Organization type predicts whistleblowing through perception of CA
	Coefficient (unstandardized B)	SE	t	p-value
	−0.066	0.239	−0.277	.391
Total direct effects
	Coefficient (unstandardized B)	SE	t	p-value
CA	−0.066	0.239	−0.277	.391
Total indirect effects
	Effect	Boot SE	Boot LLCI	Boot ULCI
CA	−0.136	0.065	−0.280	−0.027

Note. SE = standard error; CA = control activities; LLCI = lower level of confidence interval; ULCI = upper level of confidence interval.

Finally, H2 predicts monitoring activities will mediate the path between organization type and whistleblowing intention. Results are displayed in Panel B of Table 5. Results indicate that organization type significantly predicts the perception of internal control monitoring activities (B = −0.553, SE = 0.172, p < .01), where the perception of monitoring activities is lower among nonprofit employees, and that perception of monitoring activities predicts whistleblowing intention (B = 0.197, SE = 0.084, p < .01), where higher perceived monitoring activities increase whistleblowing. These results support mediation. Organization type is not a significant predictor of whistleblowing after controlling for the mediator, perception of monitoring activities (B = −0.093, SE = 0.241, ns), consistent with mediation. The results indicate that the indirect coefficient (the effect of organization type on whistleblowing through perception of monitoring activities) was significant (B = −0.109, SE = 0.064, 95% CI = −0.258, −0.006), further supporting mediation. Nonprofit organizations were associated with intentions to whistleblow, which were 0.109 points lower as mediated by perception of monitoring activities.

Table 5.

Internal Control Monitoring Activities Results.

Panel A: Monitoring Activities Cell Means and Standard Deviations.

Type of organization	M	SD	N
For-profit	5.21	1.34	153
Nonprofit	4.66	1.49	119
Total	4.97	1.43	272

Panel B: Monitoring Activities Mediation Analysis.

Path A—Organization type predicts perception of monitoring activities
	Coefficient (unstandardized B)	SE	t	p-value
	−0.553	0.172	−3.213	.008
Path B—Perception of monitoring activities predicts whistleblowing
	Coefficient (unstandardized B)	SE	t	p-value
	0.197	0.084	2.357	.010
Path C′—Mediated path—Organization type predicts whistleblowing through perception of MA
	Coefficient (unstandardized B)	SE	t	p-value
	−0.093	0.241	−0.385	.350
Total direct effects
	Coefficient (unstandardized B)	SE	t	p-value
MA	−0.093	0.241	−0.385	.350
Total indirect effects
	Effect	Boot SE	Boot LLCI	Boot ULCI
MA	−0.109	0.064	−0.258	−0.006

Note. SE = standard error; MA = monitoring activities; LLCI = lower level of confidence interval; ULCI = upper level of confidence interval.

The research question explores which internal control components are relevant for nonprofits wanting to encourage whistleblowing. Table 6 suggests the overall internal control strength influences whistleblowing for those in nonprofits (p < .05). Furthermore, control activities (p < .05) and monitoring activities (p < .05) influence whistleblowing decisions for those in nonprofits, while control environment does not influence such whistleblowing decisions (p > .10). Combining these earlier results with the findings from Table 6 discussed above suggests that nonprofits should first focus resources on stressing the importance of and implementing control activities and monitoring activities.

Table 6.

Research Question Analysis.

Panel A: Perceived Internal Control Components (Individually) Predicting Whistleblowing Intention Split by Organization Type.

	Independent variable	Unstandardized B	SE	Standardized B	t	p*
For-profit	Internal controls	0.272	0.137	0.160	1.988	.024
	Control environment	0.210	0.134	0.127	1.571	.059
	Control activities	0.317	0.128	0.197	2.468	.007
	Monitoring activities	0.179	0.115	0.126	1.554	.061
Nonprofit	Internal controls	0.238	0.142	0.154	1.680	.048
	Control environment	0.151	0.141	0.098	1.070	.143
	Control activities	0.246	0.128	0.176	1.928	.028
	Monitoring activities	0.216	0.123	0.161	1.764	.040

Note. Regressions were run individually.

The p-values are one-tailed.

Post Hoc Analysis

We gathered responses for several different whistleblowing channels in our survey. Our results are robust to reporting channel outlet choice. Nevertheless, extending our research question, we examined which outlet choices, if any, difference between those in for-profit and nonprofit organizations. The results are displayed in Table 7 (with two-tailed p-values). The dependent variables included in this analysis are intention to report to the whistleblowing hotline using a website and intention to report through the supervisor’s manager or executive manager. The dependent variable in the primary results is the intention to report to the whistleblowing hotline by phone, so the hotline analysis is not repeated here. Our data suggest that while for-profit employees are significantly likely (p < .05) to report in all but one situation (control environment with reporting using the website), those in nonprofit organizations are not significantly likely (p > .10) to report through any internal pathway using a website. Given recent findings (ACFE, 2020) suggesting that website reporting is becoming the most prevalent option, the information from our study may be useful to management within nonprofit organizations as they analyze the reporting outlets they offer.

Table 7.

Post Hoc Analysis: DV by Internal Controls Component and Organization Type.

Panel A: Nonprofit.

Dependent variable	Independent variable	Unstandardized B	SE	Standardized B	t	p
Website	Internal controls	0.118	0.144	0.076	0.821	.413
Website	Control environment	0.078	0.144	0.050	0.547	.586
Website	Control activities	0.111	0.131	0.078	0.848	.398
Website	Monitoring activities	0.115	0.125	0.085	0.923	.358
Supervisor	Internal controls	0.318	0.119	0.239	2.668	.009
Supervisor	Control environment	0.294	0.119	0.223	2.469	.015
Supervisor	Control activities	0.269	0.108	0.223	2.476	.015
Supervisor	Monitoring activities	0.253	0.104	0.219	2.431	.017
Executive manager	Internal controls	0.264	0.125	0.192	2.119	.036
Executive manager	Control environment	0.255	0.124	0.187	2.055	.042
Executive manager	Control activities	0.200	0.114	0.161	1.760	.081
Executive manager	Monitoring activities	0.220	0.108	0.184	2.030	.045

Panel B: For-Profit.

Dependent variable	Independent variable	Unstandardized B	SE	Standardized B	t	p*
Website	Internal controls	0.657	0.112	0.430	5.850	.000
Website	Control environment	0.199	0.139	0.116	1.432	.154
Website	Control activities	0.401	0.132	0.240	3.038	.003
Website	Monitoring activities	0.251	0.118	0.170	2.120	.036
Supervisor	Internal controls	0.657	0.112	0.430	5.850	.000
Supervisor	Control environment	0.650	0.109	0.437	5.966	.000
Supervisor	Control activities	0.492	0.111	0.341	4.450	.000
Supervisor	Monitoring activities	0.506	0.095	0.396	5.304	.000
Executive manager	Internal controls	0.546	0.131	0.321	4.159	.000
Executive manager	Control environment	0.500	0.129	0.302	3.890	.000
Executive manager	Control activities	0.419	0.126	0.260	3.314	.001
Executive manager	Monitoring activities	0.452	0.110	0.317	4.112	.000

Note. Regressions were run individually.

The p-values are two-tailed.

Discussion and Conclusion

Overall, the data suggest four key takeaways from this analysis. First, the overall perception of internal controls differs between nonproft and for-profit organizations. Second, each primary component of an internal controls system helps explain whistleblowing intentions. Third, nonprofit organizations should consider prioritizing the development of control activities and monitoring activities. Finally, nonprofit management may need to spend additional resources in stressing the independence and efficacy of website reporting options for whistleblowing.

First, the findings suggest that the overall perception of internal controls systems matters to whistleblowing to a different degree for those in for-profit organizations and those in nonprofit organizations. For example, future research focused on the prominence of internal controls–related topics in the workplace or on the effects of proposed changes in the internal controls language targeting nonprofits might be useful in helping to connect literature and practice. In turn, meaningful changes could then bridge the gap between nonprofit and for-profit organizations. Furthermore, the results of this study suggest that COSO may want to consider focusing its efforts on nonprofits in the next edition of the Fraud Risk Management Guide.

Second, the results suggest that each primary component of an internal controls system is relevant to whistleblowing. The data also appear to indicate those in nonprofit organizations report a lower perceived strength of each internal control component measured when compared with those in for-profit organizations. Future research exploring mediation pathways examining nuances in the design of a particular internal control component and how it might need to differentiate between those in nonprofit and for-profit organizations would enhance knowledge regarding controls design and theory. Those who design policies may consider designing education systems for nonprofit organizations that would teach employees the importance and function of these systems within their own organizations. Commitment has been found in recent research to increase prosocial behavior (Shang et al., 2019). Educating employees as to why internal controls are important to the overall organization may increase commitment to implement and comply with internal controls.

Third, the data suggest an increased focus on control activities and monitoring activities may pay dividends for nonprofits. Those designing nonprofit controls may be helped by educating employees as to the purpose and importance of such controls. Even more, these designers are charged with an underlying tenant of all nonprofits, ethical responsibility, when reflecting on promoting whistleblowing. Future research looking at personal ethics, service motivation, and scope of the organization would be useful to expand knowledge and aid those in policy design. Furthermore, this study finds that the indirect effect of organization type on reporting intentions through control activities and monitoring activities represents mediation. Future research testing this finding with geographic and/or sub-types would be useful to verify the generalizability of these results. We limited this study to for-profit and nonprofit organizations, but this research could also be beneficial for governmental organizations. Future research should explore the effect of perception of internal controls on the employees of municipalities, as this area is ripe with fraud and our results may not be generalizable to the government sector.

Finally, while websites are becoming more prevalent as outlets for whistleblowing, data from our participants suggests those in nonprofits may not be quite as accepting of this outlet as their for-profit peers. As a result, managers of nonprofit organizations seeking to maximize the effectiveness of a website reporting outlet should stress the ease, independence, and usefulness of the website outlet option. Without such attention, nonprofit employees may be reluctant to use this form of reporting. Future research should continue to inform the nonprofit community of changes relating to the perception of the nonprofit whistleblowing website option. In addition, research has shown that prosocial behavior is reduced for those with lower recognition need (Dennis et al., 2020). Given the whistleblower protection laws focus on for-profit public companies, future regulation to protect nonprofit whistleblowers may increase such behavior.

This study is subject to limitations. Nonprofit organizations vary greatly in terms of scale, scope, size, and mission. There may be large differences in how those at a nonprofit hospital, religious organization, or international humanitarian aid group make decisions due to applicable laws, geolocation tendencies, stakeholder composition, and business types. Furthermore, this study captures data at a high level (nonprofit versus for-profit), but future research is needed to see if differences in behavior exist between nonprofit and for-profit organizations, as well as to see whether nuanced differences exist within nonprofits that might change these results meaningfully. Our data suggest much of the variance in whistleblowing lies outside our area of study. Although this is somewhat expected due to the lack of consensus regarding proper internal control design, we believe future researchers will see the effect of internal controls on whistleblowing will increase over time, especially in nonprofits. At the present, however, our data suggest internal controls are only one small piece of the puzzle and many other factors contribute to whistleblowing. Furthermore, this study captures data at a specific point in time. However, longitudinal data are lacking in literature. Thus, while this study helps start an important discussion regarding nonprofit and for-profit whistleblowing differences, continual study is required to establish the longevity of these findings as well as to note any changes.

Supplemental Material

sj-pdf-1-nvs-10.1177_08997640211017665 – Supplemental material for Perception of Internal Controls Helps Explain Whistleblowing

Supplemental material, sj-pdf-1-nvs-10.1177_08997640211017665 for Perception of Internal Controls Helps Explain Whistleblowing by Andrea M. Scheetz, Tonya D. W. Smalls, Joseph Wall and Aaron B. Wilson in Nonprofit and Voluntary Sector Quarterly

Footnotes

Acknowledgements

The authors wish to thank all the respondents who participated in the research. We are also deeply thankful for feedback from participants at the 2018 AAA Forensic Accounting Research Conference, the 2018 AAA Ohio Region Conference, and the 2017 Spring Institute for Fraud Prevention meeting, especially from Dr. Charles Bailey. We are additionally thankful for the individual feedback received from Dr. Melissa Carlisle and Dr. Dana Hermanson as well as the reviewers and editor who provided insightful guidance.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Joseph Wall

Aaron B. Wilson

Supplemental Material

Supplemental material for this article is available online.

Notes

Author Biographies

Andrea M. Scheetz is an assistant professor of Accounting at Georgia Southern University. Andrea’s primary area of research is whistleblowing. Andrea came from practice with experience in auditing (Deloitte), project accounting (Forest City Enterprises), and corporate accounting (OM Group).

Tonya D. W. Smalls has more than 25 years of professional accounting/finance experience, which includes approximately 6 years in the audit/assurance practice at PwC and approximately 11 years as an accounting/finance executive at the Global Headquarters of the American Cancer Society, Inc. Dr. Smalls serves as an assistant professor of Accounting at Clark Atlanta University and teaches Principles of Accounting I and II, Intermediate Accounting I and II, and a graduate-level Seminar in Nonprofit Accounting course.

Joseph Wall is an assistant professor of Accounting at Marquette University. He conducts behavioral financial research involving fraud, governance, sustainable systems, whistleblowing, and the unintended consequences of control designs.

Aaron Wilson is an assistant professor of Accounting at Ohio University. He conducts behavioral audit research involving whistleblowing incentives and behavior, auditor fraud inquiry, auditor litigation, the impact of changes in regulation, and nonprofit governance.

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