Does Corporate Social Responsibility Affect the Timeliness of Audited Financial Information? Evidence from “100 Best Corporate Citizens”

Abstract

Companies are under immense pressure to integrate activities that will improve society and the environment with their business objectives. Such integration is likely to introduce complexity into the firms’ activities and impact the timeliness of the financial statements. Audit report lag is significant to investors as it directly impacts investor decision-making and investment fortunes. This study examines the association between corporate social responsibility (CSR) and audit report lag. We measure CSR activities using a composite variable representing a firm’s inclusion on or exclusion from the annual list of “100 Best Corporate Citizens.” In the robust regression analyses with a sample of 3661 firm-year observations from 2011 to 2016, we found a positive and significant association between CSR activities and audit report lag after controlling for extraneous variables potentially influencing audit report lag. Furthermore, the additional results with the six CSR components in the list confirm our finding that, except for governance, all the other components, such as environment, climate change, human rights, employee relations, and philanthropy, have a positive and significant association with audit report lag. Our findings suggest that CSR activities introduce audit complexities and risks that compel auditors to assess a high risk of material misstatements, translating into more audit effort and longer times to complete audits.

1. Introduction

The importance of corporate social responsibility (hereafter, “CSR”) to the survival of businesses has culminated in an increase in the number of firms now committing enormous resources, and in the quantity of resources committed by these firms to CSR activities. Consumers expect companies to integrate activities that will improve society and the environment with their business objectives (Brînzea et al. 2014). Anecdotal evidence suggests that 90% of Americans are less likely to purchase products from companies that are not socially responsible. Thus, the role of CSR in ensuring the long-term survival of companies cannot be over-emphasized. Additionally, the Organization for Economic Co-operation and Development, the United Nations (UN), and the European Union (EU) have all emphasized the immense importance of CSR activities to organizations (Grimstad et al. 2020). However, CSR activities introduce complexity into the firm’s financial reporting (Hickman et al. 2020) and could delay the release of audited financial statements. Audit report lag is significant to investors as it directly impacts decision-making and investment fortunes (Bartov and Konchitchki 2017). Agency theory suggests that managers could capitalize on the importance of CSR activities and engage in actions that will increase the organization’s risk level (Masulis and Reza 2015).

The motivation of this study is the increased demand for companies to engage in socially and environmentally responsible activities while also increasing the bottom line, although there is a tendency for these activities to introduce complexities into the firm’s financial reporting and extend the completion of the audit. Additionally, many researchers, policymakers, and corporate directors question the impact that CSR activities are having or may have on organizations and their stakeholders.

The literature suggests that there is no consensus on the impact of CSR activities on organizations and their stakeholders. While one school of thought believes that CSR activities are beneficial to organizations and financial information users (Ferrell et al. 2016), others believe that CSR activities may be detrimental to organizations and their stakeholders (Garcia et al. 2020). Prior studies have examined the factors that influence the delay in the release of audited financial statements. Determinants of audit report lag studied by Habib et al. 2019 found that, amongst others, audit report lag is significantly and positively impacted by the complexity of the firm, the firm’s risk exposure, and the internal controls employed by the firm. Habib et al. (2019) noted that audit report lag is inversely related to board independence and firm profitability. Researchers are also divided on the relationship between audit fees and audit report lag (Garcia et al. 2020; Carey et al. 2017). Some researchers contend that the complexity of CSR activities introduces complexities and risks to the firm’s financial reporting and increases the time and effort required by the auditor to complete the audit. The extended time culminates in an increase in the fees charged by the auditor. However, other researchers contend that the audit fees charged do not necessarily imply that audit report lag will be impacted.

Thus, the objective of this study was to examine the impact of CSR on the timeliness of audited financial statements. We contend that if CSR introduces complexity into the firms’ financial reporting and increases the auditors’ risk exposure, then it is likely that auditors will spend more time and effort to mitigate the propensity for material misstatements. Thus, the audit report lag will be extended. Additionally, auditor risk exposure increases in firms with unethical management and could culminate in extended audit report lags as well.

Studies reveal that companies are redirecting their attention to include more social and environmental activities (i.e., green innovation practice and the United Nation’s (UN’s) 2030 sustainable development goals (SDGs)) in their strategic decision-making to, amongst others, satisfy the needs of the investing public, boost their image, and enhance reported financial performance (Ali et al. 2022; Khan et al. 2021a, 2022). For example, Khan et al. (2021a) provide empirical evidence that firms that adopt green product innovation tend to achieve better financial performance such as returns on equity (ROE). Furthermore, in recent years, larger firms are incorporating the UN’s 2030 SDGs in their business models, implying that the firms attempt to utilize them as their strategic mechanism for implementing their CSR initiative (Santos and Bastos 2020). A recent study by Khan et al. (2022) empirically examines the impacts of firms’ implementation of the UN’s 2030 SDGs on their firm’s performance and documents that the environmental (social) SDGs exhibit a positive (negative) relation with firms’ financial performance.

This reaction of firms to CSR activities can be viewed from the perspective of the legitimacy theory within the social and accounting literature. The legitimacy theory suggests that a firm’s quest for survival compels it to make every effort to engage in activities that demonstrate its utmost desire to deal with societal and environmental issues (Olateju et al. 2021). Consistent with the legitimacy theory, firms often discretionarily report their CSR activities utilizing various voluntary or mandatory channels to ensure that the public is aware of their environmental and societal contributions. Indeed, Cong et al. (2020) provided evidence that firms attempt to legitimize their greenhouse gas emissions via climate-related disclosures. KPMG (2020) reports that 80% of the 5200 companies sampled worldwide are now reporting on sustainability1. The same report claims that, in North America, 90% of the companies provide sustainability reports. In addition, the number of firms reporting under the Global Reporting Initiative has skyrocketed. The number of reporting firms increased from 48 in the year 2000 to more than 14,750 in the year 2020 (Global Reporting Initiative 2020).

The News media is now providing extensive support in disseminating CSR activities due to the immense public interest (Lee and Carroll 2011; Huang and Watson 2015). The positive publicity that organizations stand to derive from engaging in CSR activities engenders top management to place significant emphasis on CSR activities. Asongu (2007) contends that CSR activities are investments (not expenses) that have enormous potential benefits to organizations. Considering the quantity of resources that organizations currently employ and the emphasis that organizations now place on CSR activities, it is conceivable that the organizations’ CSR activities may influence their control environment as it relates to management’s philosophy, operating style, and ethical values, to name but a few. The tone at the top concerning CSR activities could have significant ramifications on the organizations’ risk levels, including but not limited to, class action lawsuits against the firms for possible social and environmental infractions.

We discuss the relationship between accounting for climate change and audit risk and environment and audit risk together. Ngwakwe (2012) argues that accounting for climate change focuses on greenhouse gas (GHG) footprints, carbon emissions, carbon capture and storage, and appropriations calculations. Similarly, Brown et al. (2009) posit that accounting for climate change comprises a myriad of elements, including climate change performance, environmental audits, and sustainability. All these elements involved in environmental accounting present significant accounting issues. The absence of formal accounting standards results in a lack of trust and uncertainty in climate change accounting (Gulluscio et al. 2020). Milne and Grubnic (2011) found that accounting for GHG and carbon presents immense challenges due to the ambiguity in estimation methods. These challenges inject complexities and risks that translate into high audit risk.

Asare et al. (2002) suggested that organizations with weak governance represent high audit risk and pay high audit fees. The high audit risk and fees translate to extensive audit effort. We interchange corporate charitable contributions with philanthropy in our paper. The literature posits that various factors may influence corporate charitable contributions. The altruistic theory suggests that organizations will make charitable contributions because they truly care about the cause to which they donate (Choi and Wang 2007). The social pressure theory suggests that organizations may also contribute to certain causes because they do not want to deal with the pressure that will be directed their way, as they are perceived as unconcerned about a cause that appears to be dominant in society. Agency theory argues that managers may abuse corporate charitable contributions to enhance their own wealth due to managerial opportunism, potentially increasing the organizations’ risk level and eroding future firm gains (Masulis and Reza 2015). The literature claims that 62% of organizations give charitable contributions to charities associated with their CEOs (Masulis and Reza 2015). The legitimacy theory suggests that organizations will make charitable contributions to compensate for bad news (Ashforth and Gibbs 1990). Thus, it appears that corporate philanthropy is only a means for organizations to satisfy their parochial interests. Therefore, these organizations may be willing to engage in illegal acts that auditors will expend significant energy and time to avoid audit failure. Hence, the auditors assess high audit risk. These arguments are also in line with how organizations approach human rights.

Employee relation is a critical factor that directly impacts the financial performance of organizations. Employees with specialized skills have continued investments in their organizations (Maltby and Wilkinson 1998). Employees are also financially dependent on their organizations. Cavanaugh and Noe (1999) argue that current employment practices are based on personal responsibility for career development, commitment to a particular kind of work rather than a particular employer, and an expectation of job insecurity. These factors place the employees firmly in charge of their professional growth development. Considering that employees now emphasize their work rather than the employer and expect job insecurity, accounting for employee relations could present potential accounting challenges, especially because of turnovers. Such turnovers can potentially increase audit risk since auditors will see a lack of continuity and a longer learning curve for new employees, leading auditors to spend more time auditing the financial statements. Tournament theory also suggests that senior employees (managers) engage in silent tournaments to prove who is more suitable to become the next CEO of the organization (Bryan and Mason 2017). The literature argues that these managers may engage in behaviors that impact the organization’s financial statement. These behaviors may force auditors to assess a high risk of material misstatements and therefore expend more effort and time auditing the organization’s financial statements.

CSR activities may potentially result in legal concerns and environmental liabilities that may translate into accounting and financial reporting complexities for companies (Garcia et al. 2020). Garcia et al. (2020) note that CSR performance injects complexity into audits. Hickman et al. (2020) suggest that CSR activities may influence accounting judgments and decisions, resulting in inaccurate accounting estimates and adjustments such as allowance for bad debts, among others.

The research suggests that organizations’ CSR activities influence auditors’ assessment of the risk levels and the audit fee (Chen et al. 2011; Leventis et al. 2013; Koh and Tong 2013). Hickman et al. (2020) argued a relationship exists between firms’ CSR performance and auditor risk assessment. Given that CSR activities inject complexities into audits, which is likely to impact the auditors’ risk assessment, we conjecture that CSR activities might cause the auditors to assess high audit and business risks.

The high audit and business risks could include both reputational and potential litigation risks. When auditors assess high audit risk, they are inclined to perform extended procedures and expend more effort that can extend the audit completion time.

The empirical question to which this study finds answers is whether CSR activities will culminate in the delay of audited financial statements. This study explores the association between CSR activities and the time an auditor spends completing the audit. Therefore, we investigate the relationship between CSR activities and audit report lag. We contend that if CSR activities inject complexity into the audit, we expect that it will take the auditor longer to complete the audit, making the financial information less timely.

The timeliness of financial information is critical to its relevance. Atiase et al. (1989) argued that financial information loses its relevance when it is delayed. A key determinant of the timeliness of financial information is how long it takes the auditor to complete the audit (Knechel and Sharma 2012). This duration is referred to as the audit report lag. The audit report lag is defined as the time between a firm’s fiscal year-end and the audit report date (Lamptey et al. 2021; Bryan and Mason 2020). We measured CSR activities using a composite binary variable, CSR_100, representing a firm’s inclusion on or exclusion from the annual list of “100 Best Corporate Citizens” issued by 3BL Media. According to 3BL Media, the list is prepared based on the evaluation of six CSR components and one financial component. The six CSR components include environment, climate change, human rights, employee relations, governance, and philanthropy. Considering that the primary evaluation sources used by 3BL Media in generating the CSR_100 firms are those firms’ CSR performance and disclosure, we considered a firm’s inclusion on the list as a consequence of its substantially high level of CSR activities.

To examine the association between CSR activities measured by CSR_100 and audit report lag, we used robust regression analyses and found a strong positive and significant relation between CSR_100 and audit report lag after controlling for other variables affecting audit report lag. Furthermore, we examined whether there is an association between the timeliness of financial information and each of the six components of CSR_100. We found a positive and significant association between audit report lag and the environment, climate change, human rights, employee relations, and philanthropy. However, our result did not show a significant association between audit report lag and governance.

Our study makes a significant contribution to the CSR and audit literature by examining the potential effect of an organization’s proactive CSR activities on their audit risk, business risk, and managerial ethical behavior. Numerous prior studies have explored potential factors that significantly influence business complexity and audit risk, but our study concentrated on an organization‘s CSR activities as a new driver of audit risk. Another important contribution of our study is that our study introduces and seriously discusses a relatively new and adverse feature of an organization’s CSR initiatives and activities. That is, our study revealed that, although CSR activities can ultimately enhance reported performance, unethical behavior of the managers and the complexity introduced by CSR activities can introduce risks with adverse consequences to firms. Stakeholders expect socially responsible firms to exhibit high ethical behavior (Gelb and Strawser 2001; Lee 2017). However, agency theory suggests that managers have the propensity to engage in activities that are inimical to the interest of the stakeholders. Thus, managers could be inclined to engage in CSR activities to mislead stakeholders (Ben-Amar and Belgacem 2018; Jensen 2001).

Although many researchers have explored the influence of CSR activities on financial performance, our comprehensive literature review shows a gap in the literature about the impact of complexities introduced by CSR activities on financial reporting and the audit process. Specifically, extant literature does not show empirical evidence to accentuate the association between the composite CSR_100 and the timeliness of financial information. Neither does it provide support for the relationship between CSR activities and audit report lag. Additionally, to the best of our knowledge, we are not aware of any research that examines the relationship between the top 100 best CSR performers and others and audit report lag using either the composite CSR_100 or the components of CSR_100. Therefore, our study fills this gap by providing empirical evidence to support these relationships.

The finding provides important implications for various audiences (i.e., company managers, investors, auditors, and policymakers) in that a company’s proactive CSR activities would accelerate business complexity, which in turn could lead to an increase in audit risk and audit report lag. In particular, our study offers important insights to policymakers that more standardized and consistent reporting and auditing standards concerning CSR activities need to be established and implemented. We note that, while CSR activities have the potential to increase a firm’s return on investment, any delay in the release of the financial statements is likely to have adverse consequences on investor decision-making. We adopted a firm’s inclusion in the “100 Best Corporate Citizens” list as an empirical proxy to represent CSR activities. Our findings should be important to researchers, policymakers, and auditors as they consider the effect of CSR activities on organizations and stakeholders.

The remainder of our study is organized as follows. Section 2 provides the literature review and develops the hypotheses. We discuss our research method in Section 3. We provide the empirical analyses and discussion of our results in Section 4. In Section 5, we draw our conclusions and articulate the implications of the study. Section 6 discusses the limitations of our study and suggestions for future research.

2. Literature Review and Hypothesis Development

CSR activities have the propensity to be either beneficial or inimical to firms and their stakeholders. While Ferrell et al. (2016) found that CSR activities are more likely to culminate in high investor returns in firms with fewer agency problems, Garcia et al. (2020) found that CSR activities may potentially result in legal concerns and environmental liabilities. CSR activities may translate into accounting and financial reporting complexities for companies.

The time it takes the auditor to complete the audit is critical to investors, as any delays could impact their decision-making. Copious studies ascertain the factors that impact the timeliness of financial statements. The literature documents the determinants of audit report lag (Leventis et al. 2005; Abernathy et al. 2017; Habib et al. 2019). Habib et al. (2019) found that audit report lag is significantly and positively related to firm complexity, firm risk, audit fees, and internal control weakness and negatively related to board independence and firm profitability.

Abernathy et al. (2017) found that audit report lag is longer for firms with weaknesses in their internal control, poor financial performance, and high industry risk and shorter for firms with robust corporate governance mechanisms. Sultana et al. (2015) found that audit report lag is shortened when firms have independent audit committee members. Lamptey et al. (2021) found that managerial entrenchment shortens audit report lag. They suggested that entrenched managers are more likely to behave ethically. Leventis et al. (2005) found that the existence of extraordinary items extends the audit report lag. Asante-Appiah (2020) found that while reputational damages arising from environmental and governance practices increase audit report lag, reputational damage arising from social practices does not increase audit report lag as auditors tend to discount the risk.

The literature suggests that researchers are divided on the relationship between audit fees and audit report lag. Whereas researchers like Chan et al. (1993) and Knechel and Payne (2001) found that higher audit fees may lead to longer audit report lag, others including Carcello et al. (1992) and Leventis et al. (2005) documented that audit fees may not lead to longer audit report lag. The proponents of the positive association between audit fees and audit report lag contend that CSR-related activities engender audit complexity that requires the auditor to expend a considerable amount of effort to complete the audit, thereby culminating in high audit fees (Garcia et al. 2020; Koh and Tong 2013; Chen et al. 2016; Carey et al. 2017; Garcia et al. 2020; Saeed et al. 2020). Koh and Tong (2013) attributed the positive association between audit fees and audit report lag to the business risks associated with clients’ engagement in controversial CSR activities. Studies revealed that the auditor’s failure to deal with the risks effectively could expose the auditor to high potential legal liability (Simunic 1980; Scism 1995; Hays 2004; Barbaro 2006; Koh and Tong 2013). The auditor is therefore compelled to expend additional effort to avoid audit failure. Leventis et al. (2005) found that the type of auditor appointed impacts the timeliness of the financial statements.

Studies found a positive relationship between financial statement complexity and audit fees. CSR-related activities engender financial statement complexity, increase the audit effort, and impact the fees charged by the auditors. Hoitash and Hoitash (2018) found a positive association between the complexity of accounting reporting and the propensity for financial statements to be misstated. They argued that financial reporting requires adequate knowledge of the applicable accounting standards to properly disclose the accounting items. Thus, the more complex the reporting requirements of the firm, the greater the chances that the financial statements will be prone to errors and the audit report extensively delayed.

Managers of firms with weak internal controls often engage in opportunistic behaviors, including, but not limited to, manipulating earnings to enhance reported income. Thus, management introduces a colossal risk to auditors and could impact the timely release of financial statements. While Chih et al. (2008) documented that CSR firms are more likely to manipulate earnings. Shleifer (2004) found that firms with good CSR reputations are less likely to manipulate earnings.

Considering that CSR activities increase audit complexity and require the auditor to expend a lot of audit effort to ensure that the financial statements are free from material misstatements, we contend that the auditor will likely increase audit efforts to mitigate the audit risk (Simunic 1980; Koh and Tong 2013). Consequently, we expect a positive association between the composite CSR activities and audit report lag. We state our first hypothesis as follows:

H1. 

Ceteris paribus, there is a positive association between the composite CSR activities and audit report lag.

The legitimacy theory and the political cost theory underscore the investments that organizations make and the benefits that those organizations expect from such investments. Consistent with the legitimacy theory, organizations being aware that society expects them to invest some of their profits in their communities, will spend some of their resources protecting the environment and supporting the communities (Blasio 2007; Cashore et al. 2003), and obtain even greater publicity for their efforts.

The political cost theory, as it relates to CSR, is the deliberate organizational strategy to invest some of their resources in various CSR activities in conjunction with the government to gain the leverage to influence legislation or regulations at some point (Halme 2002; Ruihua and Bansal 2003). Organizations do this to avoid political scrutiny that can hurt their operations.

The legitimacy theory and the political cost theories underscore the behavior of organizations as they include CSR activities in their strategic plans and ensure that investments in such activities are brought to the attention of stakeholders and the public to influence the relationship between the organization and the public. However, investments in these various CSR activities, including those that constitute CSR_100 (environment, climate change, human rights, employee relations, governance, and philanthropy), potentially introduce accounting and legal concerns for the organizations. Even when the organizations properly record these transactions, there may be inherent and control risks that constitute the risk of material misstatement associated with these transactions. Investing in CSR activities with the associated risks injects complexities into the audits. Hay (2013) found a significant positive association between firm complexity and audit fees.

However, each component of CSR activities might require varying amounts of firm resources and efforts, leading to different levels of audit complexity. Thus, it is an empirical question of how significantly each component of CSR activities affects audit report lag. To address this question, we test the association between the components of CSR activities and audit report lag.

Furthermore, the composite CSR performance is an aggregate assessment outcome based on the evaluation of all the CSR components. Hence, we cannot guarantee that the firms with overall good CSR reputations necessarily achieve superior performance in each of all the CSR components. Therefore, we hypothesized, in an alternative form, that:

H2. 

Ceteris paribus, there is a positive association between CSR components and audit report lag.

3. Research Design and Methodology

3.1. Data and Sample Description

Our sample comprised 3661 firm-year observations and 776 firms from 2011 to 20162. We believe our sample period could completely avoid all potential effects of the global COVID-19 pandemic on socio-economic circumstances (including auditing practice) during the COVID-19 era. Thus, we expect that our results could be applicable to the upcoming post-COVID-19 periods. We obtained the data for CSR_100 from the annual list of “100 Best Corporate Citizens”, which is available on the website of 3BL Media (https://100best.3blmedia.com/, assessed on 1 January 2022). According to 3BL Media, the top 100 U.S. firms are selected from the 1000 largest publicly traded U.S. firms and included on the list every year, based on the evaluation of CSR performance and disclosure in terms of the six CSR components (environment, climate change, human rights, employee relations, governance, and philanthropy) and the one financial component. The evaluation is conducted with publicly available information on each factor contained in each component. A firm included on the list would garner substantial CSR-related recognition and reputation from the public (Lewis 2018; Lewis and Carlos 2023). Indeed, firms with superior CSR performance have improved their brand image and reputation by proactively engaging in CSR activities (Laksmana and Yang 2009). Because a firm’s inclusion on the list is a reputable achievement and is indicative of its CSR-oriented business strategy, intensive CSR effort, and investment in CSR activities, we considered a firm’s inclusion on the list as an empirical proxy of CSR activities.

We obtained the remaining variables from Wharton Research Data Services (WRDS). We extracted our data for audit opinion, audit fee, SOX404, and material control weaknesses from Audit Analytics and the data on firm fundamentals and segments from Compustat. We obtained the governance data from the Institutional Shareholder Services (ISS) database.

We constructed our sample by obtaining 14,843 firm-year observations from the ISS governance database. We excluded 8908 firm-year observations with missing Compustat data. We excluded 1750 firm-year observations with missing audit fees, nonaudit fees, and audit opinion information. We also excluded 78 firm-year observations and 432 firm-year observations for SOX404 and segment information, respectively. We excluded 14 firm-year observations that have unusually longer audit report lags because of issues related to revenue recognition and legal matters resulting in a sample of 3661 firm-year observations.

Finally, we merge the result with data obtained from the 3BL media giving us our final sample of 3661 firm-year observations. We winsorized our continuous variables at 1% and 99% to minimize the effect of outliers. We report the summary of the sample selection in

Table 1. Sample Construction.

Institutional Shareholder governance data for firms with available data	14,843
Less firms-years with missing Compustat data	8908
Less firm-years with missing audit fee, nonaudit fees, and audit opinion data	1750
Less firm-years with missing SOX404 data	78
Less firm-years with missing Segment data	432
Less firm-years with missing unusually longer ARL	14
Subtotal	3661
Merge with CSR data obtained from the 3BL website	3661
Final Sample	3661

.

3.2. Variables of Interest

Our independent variable of interest is CSR_100, which is a composite dichotomous variable that has the value of one if a firm is included in the “100 Best Corporate Citizens” list for each of our sample years, and a value of zero otherwise. As discussed, we adopted this variable as an empirical proxy of corporate CSR activities to test H1. The “100 Best Corporate Citizens” list also provides the rankings of the firms included in the list in terms of each of the six CSR components, environment, climate change, human rights, employee relations, and philanthropy. To test the H2, we formed the six variables, ENV_100, CLI_CHG_100, HUM_RGT_100, EMP_REL_100, GOVERN_100, and PHILAN_100, representing each of the CSR components considered in the list, respectively. For example, ENV_100 is a dichotomous variable equal to 1 if a firm is included in the “100 Best Corporate Citizens” list and ranked within 100 in the environment component, and 0 otherwise. The other five variables are also defined similarly, as shown in Appendix A.

Following the literature (Lamptey et al. 2021; Bryan and Mason 2020), we adopted as our dependent variable ARLP365 representing audit report lag, which is defined as the number of days between a firm’s fiscal year-end and the audit report date scaled by 365.

3.3. Control Variables

We used the following control variables in our model. The Altman’s ZSCORE (Z_SCORE), TOBINQ (TOBIN_Q), leverage (LEV), return on assets (ROA), auditor type (BIG4), material weakness (MCW), the natural logarithm of nonaudit fee (LNAFEE), the natural logarithm of audit fee (LAFEE), business segments (BUSSEG), whether the firm is involved in litigation (LIT), going concern opinion (GC), firms with December fiscal year-end (DEC), accelerated filer (ACF), large-accelerated filers (LACF), and auditor change (AUDCH). We controled for governance using managerial entrenchment that we proxy by the variable EINDEX. We also controled for managerial behavior using accrual earnings management (EM_ABSDA) developed by Kothari et al. (2005). We included the year (YR) and industry (INDUSTRY) dummy variables in our model to control for the year and industry effect on the audit report lag.

3.4. Multivariate Regression Model

In estimating the association between CSR_100 and audit report lag, we used robust regression to mitigate the effect of potential outliers or influential observations. In an untabulated result, we estimated the model using OLS, and the results are consistent with those obtained using robust regression. We use a modified version of the audit report lag model from Tanyi et al. (2010) to estimate our model for H1 as below.

ARLP365_i,t = β₀ + β₁CSR_100_i,t+ β₂SIZE_i,t + β₃Z_SCORE_i,t + β₄TOBIN_Q_i,t + β₅LEV_i,t + β₆ROA_i,t + β₇BIG4_i,t + β₈MCW_i,t + β₉LNAFEE_i,t + β₁₀LAFEE_i,t + β₁₁BUSSEG_i,t + β₁₂LIT_i,t + β₁₃GC_i,t + β₁₄DEC_i,t + β₁₅ACF_i,t + β₁₆LACF_i,t + β₁₇AUDCH_i,t + β₁₈EINDEX_i,t + β₁₉EM_ABSDA_i,t + INDUSTRY + YR + ε

(1)

where:

ARLP365_i,t is the audit report lag which we operationalize as the number of days between the firm i ’s fiscal year-end and the audit report date scaled by 365;

CSR_100_i,t is our variable of interest which is a composite binary variable equal to one when firm i is listed in the “100 Best Corporate Citizens” issued by 3BL Media in year t and zero otherwise;

SIZE_i,t is the size of the firm i in year t. measured by that natural logarithm of total assets;

Z_SCORE_i,t is the altman’s Zscore

TOBIN_Q_i,t is a measure of firm i’ s performance in year t;

LEV_i,t is the leverage of the firm i in year t measured by total liabilities divided by total assets;

ROA_i,t is the return on assets of firm i in year t measured as earnings before interest and taxes scaled by the total assets;

BIG4_i,t is a binary variable equal to one when firm i is audited by a BIG4 audit firm in year t, and zero otherwise;

MCW_i,t is a binary variable that is equal to one when firm i has material control weaknesses in year t, and zero otherwise;

LNAFEE_i,t is the natural logarithm of the fees paid by the firm i in year t for nonaudit services;

LAFEE_i,t is the natural logarithm of fees paid by the firm i in year t for audit services;

BUSSEG_i,t is a binary variable equal to 1 if the firm i has more than one segment in year t, 0 otherwise;

LIT_i,t is a binary variable equal to one when firm i is engaged in a highly litigious industry in year t, and zero otherwise (2-digit SIC codes 28, 35, 36, 38, and 73);

GC_i,t is a binary variable equal to one when firm i receive a going concern opinion in year t, and zero otherwise;

DEC_i,t is a binary variable equal to one when firm i has a fiscal year-end of December in year t, and zero otherwise;

ACF_i,t is a binary variable equal to one when firm i is an accelerated filer in year t, and zero otherwise;

LACF_i,t is a binary variable equal to one when firm i is a large-accelerated filer in year t, and zero otherwise;

AUDCH_i,t is a binary variable that takes the value of 1 if a firm i changes auditors during the year t, 0 otherwise;

EINDEX_i,t is a categorical variable that takes values from zero to six such that zero indicates that firm i did not adopt any of the six entrenchment provisions in year t used by Bebchuk et al. (2009) to create the index, whereas six indicates that firm i adopted all six entrenchment provisions in year t used in the EINDEX;

EM_ABSDA_i,t is the earnings management variable operationalized by the absolute value of discretionary accruals using the Kothari et al. (2005) model.

To test H2, we replaced the independent variable, CSR_100, with each of the following CSR component variables, ENV_100, CLI_CHG_100, HUM_RGT_100, EMP_REL_100, GOVERN_100, and PHILAN_100.

We tested for multicollinearity using the variance inflation factor (VIF) and reported that the highest VIF is 4.5 for LAFEE. This VIF is lower than the critical value of 10 suggested in the literature. Thus, our model is not influenced by multicollinearity concerns. We depict the results of our multicollinearity test in

Table A2. Heteroscedasticity Test.

	Chi-Sq Value	p-Value
Model 1—Without SIZE Variable	284.72	<0.0001 ***
Model 2—Without Audit Fee Variables	314.11	<0.0001 ***
Model 3—Full Model	383.22	<0.0001 ***

*** indicates significance at less than 1%.

of Appendix A.

Next, we tested for homoscedasticity assumption, that is, whether our dependent variable has equal variability across the independent variables. Violations of the homoscedasticity assumption led to heteroscedasticity. We show the result of this test in

Table A3. VIF (Variance Inflation Factor).

Variables	VIF	1/VIF
CSR_100	1.328	0.753
SIZE	4.064	0.246
Z_SCORE	2.330	0.429
TOBIN_Q	2.104	0.475
LEV	1.743	0.574
ROA	1.322	0.756
BIG4	1.161	0.861
MCW	1.036	0.965
LNAFEE	1.864	0.537
LAFEE	4.515	0.222
BUSSEG	1.073	0.932
LIT	1.167	0.857
GC	1.011	0.989
DEC	1.088	0.919
ACF	1.081	0.925
LACF	1.292	0.774
AUDCH	1.075	0.931
EINDEX	1.096	0.912
EM_ABSDA	1.026	0.975
Mean	1.651	0.739

of Appendix A. Using the White test (Halbert White 1980) we show that our models portray heteroscedasticity. Therefore, we rejected the null hypotheses in all three models. Hence, we used robust regression with fixed effects for our analyses to minimize the impact of the unequal variances in the residual.

4. Empirical Results

4.1. Descriptive Statistics and Univariate Analysis Results

Table 2. Descriptive Statistics.

Variable	N	Mean	SD	Min.	Q1	Median	Q3	Max.
AUD_REP_LAG	3661	54.48	8.51	21.00	50.00	56.00	59.00	91.00
ARLP365	3661	0.15	0.02	0.06	0.14	0.15	0.16	0.25
CSR_100	3661	0.10	0.30	0.00	0.00	0.00	0.00	1.00
SIZE	3661	3.53	0.68	1.77	3.04	3.47	3.97	5.61
Z_SCORE	3661	4.70	5.04	−55.65	2.43	3.74	5.38	98.14
TOBIN_Q	3661	2.13	1.29	0.57	1.37	1.77	2.45	14.67
LEV	3661	0.53	0.23	0.03	0.39	0.53	0.65	3.63
ROA	3661	0.06	0.09	−2.28	0.03	0.06	0.09	0.46
BIG4	3661	0.94	0.24	0.00	1.00	1.00	1.00	1.00
MCW	3661	0.03	0.17	0.00	0.00	0.00	0.00	1.00
LNAFEE	3661	5.59	0.77	3.00	5.16	5.64	6.11	7.83
LAFEE	3661	6.44	0.43	4.85	6.13	6.41	6.72	7.82
BUSSEG	3661	0.20	0.40	0.00	0.00	0.00	0.00	1.00
LIT	3661	0.30	0.46	0.00	0.00	0.00	1.00	1.00
GC	3661	0.00	0.02	0.00	0.00	0.00	0.00	1.00
DEC	3661	0.62	0.49	0.00	0.00	1.00	1.00	1.00
ACF	3661	1.00	0.07	0.00	1.00	1.00	1.00	1.00
LACF	3661	0.90	0.30	0.00	1.00	1.00	1.00	1.00
AUDCH	3661	0.11	0.32	0.00	0.00	0.00	0.00	1.00
EINDEX	3661	1.77	1.30	0.00	1.00	1.00	2.00	6.00
EM_ABSDA	3661	0.08	0.12	0.00	0.02	0.05	0.10	1.73

This Table provides the descriptive statistics for the variables in our model. See Appendix A for variable definitions.

presents the descriptive statistics for our sample. Consistent with the audit report lag research, our study shows a mean (median) audit report lag of 54 (56) days. The descriptive statistics do not suggest extreme values in our sample. About 99.5% of our observations are accelerated filers, whereas only about 3% report material control weaknesses. Thirty percent of the observations operate in litigious industries, whereas 94% are audited by BIG4 auditors. Sixty-two percent have December 31 fiscal year-end.

Table 3. Pearson’s Correlation Coefficient Matrix.

Variable	ARLP365	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)	(16)	(17)	(18)
CSR_100 (1)	−0.13
SIZE (2)	−0.42	0.44
Z_SCORE (3)	0.00	−0.06	−0.27
TOBIN_Q (4)	−0.14	0.03	−0.15	0.57
LEV (5)	−0.13	0.13	0.34	−0.47	0.03
ROA (6)	−0.13	0.08	0.01	0.38	0.40	−0.12
BIG4 (7)	−0.18	0.08	0.27	−0.13	−0.05	0.16	0.02
MCW (8)	0.19	−0.05	−0.09	−0.02	−0.02	−0.01	−0.06	−0.03
LNAFEE (9)	−0.23	0.33	0.61	−0.17	−0.04	0.27	0.04	0.23	−0.03
LAFEE (10)	−0.34	0.43	0.85	−0.30	−0.16	0.37	−0.04	0.28	−0.03	0.67
BUSSEG (11)	0.05	−0.08	−0.08	0.02	0.01	0.02	0.01	−0.03	0.00	−0.09	−0.18
LIT (12)	−0.01	0.04	−0.05	0.17	0.26	−0.11	0.10	−0.06	0.02	−0.02	−0.1	0.00
GC (13)	0.03	−0.01	−0.01	−0.03	−0.02	0.03	−0.06	−0.04	0.00	0.00	−0.03	−0.01	−0.02
DEC (14)	0.06	−0.03	0.07	−0.08	−0.03	0.08	−0.12	−0.03	0.00	0.03	0.09	0.02	−0.21	0.02
ACF (15)	−0.13	0.02	0.10	0.01	0.06	0.05	0.13	0.16	−0.01	0.08	0.10	−0.03	−0.02	0.00	−0.04
LACF (16)	−0.29	0.11	0.37	−0.03	0.10	0.14	0.12	0.25	−0.11	0.26	0.33	−0.08	−0.05	−0.03	0.02	0.21
AUDCH (17)	0.12	−0.05	−0.20	0.02	−0.02	−0.07	−0.07	−0.09	0.11	−0.14	−0.17	0.04	−0.01	−0.01	−0.01	−0.04	−0.14
EINDEX (18)	0.07	−0.18	−0.22	0.00	−0.05	−0.08	−0.02	0.03	−0.01	−0.11	−0.18	−0.04	−0.04	0.00	0.00	0.01	−0.06	0.12
EM_ABSDA	0.03	−0.02	−0.08	0.10	0.13	−0.05	0.06	−0.03	0.01	−0.04	−0.06	−0.01	0.05	0.00	−0.02	−0.01	−0.03	0.03	−0.02

This Table reports the Pearson correlations of the variables for the full sample. See Appendix A for variable definitions. Correlation coefficients marked in bold are statistically significant at the 5% or lower level.

presents Pearson’s correlation-coefficients matrix. We show a negative and significant correlation between audit report lag and CSR_100 at a 1% level of significance. We report four pairs of variables with correlations greater than 0.50 that are significant. They are LNAFEE and SIZE, LAFEE and SIZE, TOBINQ and Z_SCORE, and LAFEE and LNAFEE.

4.2. Multivariate Analyses Results and Discussions

Table 4. Robust Regression Results with the Composite Variable of CSR_100.

Dependent Variable: ARLP365
Model Specifications
	(1) Without SIZE		(2) Without Audit Fee Variables		(3) Full Model
	Coefficients	Chi-Sq Values	Coefficients	Chi-Sq Values	Coefficients	Chi-Sq Values
Intercept	0.2472 ***	157.14	3.6831 ***	38781.3	0.1920 ***	91.42
CSR_100	0.0010	0.68	0.0043 ***	13.54	0.0037 ***	9.73
SIZE			−0.0137 ***	454.05	−0.0165 ***	241.63
Z_SCORE	0.0002 *	3.78	0.0001	0.98	0.0001	0.82
TOBIN_Q	−0.0028 ***	63.11	−0.0033 ***	88.30	−0.0033 ***	85.84
LEV	−0.0011	0.34	0.0013	0.51	0.0000	0.00
ROA	−0.0127 ***	11.34	−0.0058	2.39	−0.0056	2.16
BIG4	−0.0054 ***	14.82	−0.0046 ***	10.65	−0.0053 ***	14.4
MCW	0.0193 ***	110.48	0.0178 ***	94.11	0.0173 ***	88.65
LNAFEE	0.0010 *	3.67			0.0020 ***	13.82
LAFEE	−0.0145 ***	159.91			0.0029 *	2.96
BUSSEG	0.0005	0.34	0.0013	2.57	0.0015 *	3.65
LIT	−0.0003	0.08	0.0021 *	3.52	0.0024 **	4.37
GC	0.011	0.72	0.0137	1.13	0.0134	1.08
DEC	0.0042 ***	34.79	0.0044 ***	38.22	0.0042 ***	36.27
ACF	−0.0157 ***	11.86	−0.0180 ***	15.59	−0.0183 ***	16.27
LACF	−0.0098 ***	72.13	−0.0065 ***	31.48	−0.0067 ***	33.48
AUDCH	0.0004	0.19	−0.0008	0.58	−0.0007	0.51
EINDEX	−0.0005 *	3.59	−0.0008 ***	9.77	−0.0008 ***	10.37
EM_ABSDA	0.0053 **	4.08	0.0044 *	2.76	0.0042	2.58
Industry Fixed Effects	Yes		Yes		Yes
Year Fixed Effects	Yes		Yes		Yes
No. of observations	3661		3661		3661
R-Square	0.1915		0.2272		0.2314
AIC	4234.15		3941.00		3901.89

This Table presents the robust regression results with the primary independent variable of interest, CSR_100, with the three model specifications, the model without SIZE variable, the model without the two audit fee variables, LNAFEE and LAFEE, and the model with all the variables. In this Table, we include all parameter estimates of all variables. See Appendix A for variable definitions. ***, **, and * indicate significance at less than 1%, 5%, and 10%, respectively, based on chi-square values using a two-tailed test.

presents the results of our multivariate analyses. We investigate the relation between CSR_100 and ARLP365 while we control for a set of variables used in the audit report lag literature discussed in the control variables section. These control variables influence the relationship between CSR_100 and ARLP365 by changing the direction of the correlation in the univariate analysis. We defined those control variables in the methodology section of our paper. We specify three models to test H1. In the first model, we excluded the SIZE variable and found no association between CSR_100 and ARLP365. In the second model, we excluded the LAFEE and LNAFEE variables, and we found a significantly positive association between CSR_100 and ARLP365 at the 1% level of significance. Our full model includes the LAFEE, LNAFEE, and SIZE variables omitted from our first two tests. We found a significantly positive association between CSR_100 and ARLP365 at a 1% level of significance. This result is consistent with the literature, which suggests that, for organizations with strong CSR activities, these activities introduce accounting and auditing complexities that require the auditor to spend more effort and time to complete the audit, thereby translating into longer audit report lag (Garcia et al. 2020; Hoitash and Hoitash 2018; Koh and Tong 2013; Hay 2013).

The association between SIZE and ARLP365 is negatively significant at 1%. This relation is important, especially because SIZE, the firm’s size, is a major determinant of the association between CSR_100 and ARLP365. The negative relationship between SIZE and ARLP365 indicates that auditors spend a shorter time and less effort to complete the audit for bigger firms. This can be explained by the fact that big organizations usually have the resources to ensure the effective operations of controls, adapt to any environmental changes (Lamptey and Singh 2018), and hire BIG 4 auditors to perform their annual audits. The results also suggest that LNAFEE and LAFEE do not influence the association between CSR_100 and ARLP365. Consistent with Lamptey et al. (2021), we found a significantly negative association between managerial entrenchment proxied by EINDEX and ARLP365, which suggests that, for organizations with entrenched managers and strong CSR activities, auditors spend a shorter time to complete the audits.

As commented in the recent study by Oh and Jeon (2022), the regression model with the CSR variable as an independent variable might suffer from an endogeneity issue that the measure of corporate CSR performance would not be exogenous, and there might exist potential omitted variables that would influence both the CSR measure and audit report lag. We ran a two-stage least squares (2SLS) regression analysis to mitigate this potential endogeneity concern in the regression model. In the first-stage regression analysis with the dependent variable, CSR__100, we adopted as an instrumental variable, Lag_CSR_100, the lagged variable of CSR_100. Also, in the model, we included the five firm financial characteristics variables as control variables potentially affecting CSR_100. In the second-stage regression analysis, the predicted value of CSR_100 in the first-stage regression was used as our primary test variable.

Table 5. Two-Stage Least Square (2SLS) Regression Results.

	Dependent Variable
	Model 1: CSR_100		Model 2: ARL365
	Coefficient	t-Values	Coefficient	t-Values
Intercept	−0.1755 ***	−7.87	0.1943 ***	8.66
LAG_CSR_100	0.7587 ***	62.79
CSR_100			0.0061 ***	3.54
SIZE	0.0553 ***	9.40	−0.0190 ***	−14.59
Z_SCORE	−0.0006	−0.49	0	0.19
TOBIN_Q	0.0074 **	2.08	−0.0034 ***	−7.93
LEV	−0.0204	−1.08	0.0007	0.30
ROA	0.0305	0.77	−0.0081 *	−1.75
BIG4			−0.0053 ***	−3.00
MCW			0.0182 ***	8.38
LNAFEE			0.0025 ***	3.70
LAFEE			0.0036 *	1.80
BUSSEG			0.0006	0.58
LIT			0.0032 **	2.30
GC			0.0116	0.83
DEC			0.0050 ***	5.88
ACF			−0.0189 ***	−2.89
LACF			−0.0058 ***	−3.97
AUDCH			0.0004	0.28
EINDEX			−0.0005 *	−1.69
EM_ABSDA			0.003	0.92
Industry Fixed Effects	Yes		Yes
Year fixed effects	Yes		Yes
No. of observations	2885		2885
Adj. R-Square	0.6672		0.314

This Table presents the two-stage least squares (2SLS) regression results. See Appendix A for variable definitions. In this Table, we include all parameter estimates of all variables. ***, **, and * indicate significance at less than 1%, 5%, and 10%, respectively, based on t-values using a two-tailed test.

presents the results of our 2SLS regression analysis. The result in the second-stage regression with the dependent variable, ARLP365, reveals that the estimated coefficient of CSR_100 is positive and statistically significant at 1%, even after controlling for endogeneity and a set of variables used in the audit report lag literature. This finding is qualitatively consistent with the result in Table 4, supporting the positive relationship between CSR_100 and ARLP365.

Next, we examined the association between the components of the composite variable, CSR_100, and audit report lag. We included all the control variables in estimating six models for each of the six components of CSR_100, replacing our independent variable with each component in the model. We specified these models in testing H2 and report our results in

Table 6. Robust Regression Results with Each Component of CSR_100.

Dependent Variable: ARLP365
Model Specifications
	Coefficients	Chi-Sq Values	Coefficients	Chi-Sq Values	Coefficients	Chi-Sq Values	Coefficients	Chi-Sq Values	Coefficients	Chi-Sq Values	Coefficients	Chi-Sq Values
Intercept	0.1888 ***	88.60	0.1964 ***	96.16	0.1925 ***	92.06	0.1897 ***	89.74	0.1860 ***	86.39	0.1897 ***	89.73
ENV_100	0.0027 **	4.09
CLI_CHG_100			0.0070 ***	26.31
HUM_RGT_100					0.0048 ***	13.56
EMP_REL_100							0.0038 ***	8.07
GOVERN_100									0.0014	0.77
PHILAN_100											0.0040 ***	8.06
CONTROLS	Yes		Yes		Yes		Yes		Yes		Yes
Industry Fixed Effects	Yes		Yes		Yes		Yes		Yes		Yes
Year Fixed Effects	Yes		Yes		Yes		Yes		Yes		Yes
No. of observations	3661		3661		3661		3661		3661		3661
R-Square	0.2300		0.2344		0.2318		0.2305		0.2278		0.2305
AIC	3920.47		3880.10		3906.72		3923.19		3976.64		3921.77

This Table presents the robust regression results with each of the six CSR components in CSR_100. In this Table, we include the parameter estimates of only the main test variables. We exclude the parameter estimates for the control variables to conserve space. The parameter estimates of the control variables are quantitatively similar to those in Table 4 and Table 5. See Appendix A for variable definitions. *** and ** indicate significance at less than 1% and 5%, respectively, based on chi-square values using a two-tailed test.

. We found a significantly positive association between ENV_100 and ARLP365 at a 5% level of significance. We also found a positive and significant association between CLI_CHG_100 and ARLP365, HUM_RGT_100 and ARLP365, EMP_REL_100 and ARLP365, and PHILAN_100 and ARLP365 at a 1% level of significance. The significant and positive association between each of the five components of CSR_100 and audit report lag indicates that auditors of organizations that make significant investments in the environment, climate change, human rights, employee relations, and philanthropic activities spend more time completing their audits because of the significant accounting complexities introduced by those activities that translate into more effort and time. Again, consistent with the literature, which suggests that CSR-related activities introduce complexities to the financial statements, thus requiring additional time to ensure that the financial statements are not materially misstated.

It is conceivable that these organizations may engage in those activities because of their parochial interest and may not report some of the financial resources they have put into them (Hemingway and Maclagan 2004). Auditors may spend a significant amount of time discovering such unreported expenses, which can heighten their skepticism, inject complexity into the audit, and compel them to expend more effort to avoid audit failure (Filzen and Peterson 2015). The additional work may extend the time the auditor takes to complete the audit.

It is important to report that we did not find a significant association between GOVERN_100 and ARLP365. The reason is that, unlike the other five components of CSR, governance is an activity within the organization. The influence of governance as a component of CSR may be challenging to quantify because it has no direct impact on what society sees as investments in social and environmental issues, although governance of the organization may be the driving force on the resources that an organization spends on the other CSR_100 components.

4.3. Robustness Checks

Given that the list of “100 Best Corporate Citizens” is released to the public in the middle of the year, the annual evaluation period for CSR performance and disclosure might not be consistent with a firm’s fiscal year period. To adequately address this concern, we performed the regression analyses lagging the CSR_100 variable by a year and looking ahead by a year. The untabulated regression results with these different definitions of CSR_100 were qualitatively similar to our original analyses. Furthermore, we conduct another robustness test with the variable CSR_50, representing the top 50 ranked firms in the list. The results from the regression analyses with CSR_50 confirm our original finding with CSR_100 that there is a significantly positive association between CSR activities and audit report lag.

5. Conclusions and Implication of the Study

5.1. Conclusion

Companies are pressured to engage in socially responsible activities to continue as a going concern. CSR activities introduce complexity into the firm’s financial reporting and increase audit risk. To mitigate the propensity for the financial statements to be misstated, auditors are compelled to expend additional time and effort conducting the audit. We investigate whether there is an association between CSR_100 and audit report lag. We found a significant and positive association between CSR_100 and audit report lag. We also found a significant and positive association between the environment, climate change, human rights, employee relations, and philanthropy variables and the audit report lag. Overall, our results support the assertion that CSR activities introduce complexities into the audit process, forcing auditors to expend more effort and time to complete their audits. Thus, the association between audit report lag and the CSR_100 as a composite variable and audit report lag and the components of the CSR_100 is influenced by the complexity of the audit, the auditors’ risk assessment, and the audit effort.

Generally, organizations that spend more resources on CSR activities are considered good corporate citizens and enjoy good reputations. However, consistent with our findings, this spending and reputation come with major accounting and auditing complexities that are not apparent to the public. Since auditors will spend more effort and time to audit such organizations, we can expect a higher audit quality and higher-quality financial reports consistent with Cao et al. (2012).

Our findings offer significant insight into how spending on CSR activities influences auditors’ risk assessment and the audit report lag. Additionally, because existing auditing standards do not provide specific guidance on how risks associated with CSR activities may influence the risk of material misstatements (Sharma et al. 2018), auditors have had to spend more time to assess those risks and plan audit procedures that will ensure that those risks do not translate into material misstatements that will potentially lead to audit failure. We also contribute to the discussion on the determinants and incentives of audit report lag. For instance, while Oh and Jeon (2022) articulate the incentives associated with audit report lag, we documented how the complexity of CSR activities impacts audit report lag.

5.2. Implications of Our Study

We outlined the practical implications and the implications of our study to policymakers. We documented how our findings could be of importance to researchers.

5.2.1. Practical Implications

Our study contributes to the literature on the effect of an organization’s CSR activities on audit risk, business risk, and managerial ethical behavior. Our findings suggest that, although CSR activities can enhance reported performance, CSR activities introduce complexity into a firm’s financial reporting and extends the audit report lag. The complexity of the audit requires that auditors assess their capability to effectively audit such firms to avoid facing serious legal liabilities. The risks faced by the auditor are exacerbated by the propensity of unethical managers to take advantage of the attraction of CSR activities to engage in opportunistic behaviors (Ben-Amar and Belgacem 2018; Jensen 2001).

The extension of the audit report lag could have adverse ramifications on the ability of shareholders to make prudent and timely decisions. Bartov and Konchitchki (2017) examined the market consequences of the late filings of quarterly and annual financial statements. They found that stock prices significantly declined the moment companies submit the non-timely (Form NT) form to the Securities and Exchange Commission, notwithstanding the firm’s commitment to meet the extended deadline. This suggests that a 1-day audit report lag is a significant event to investors as it directly impacts decision-making and investment fortunes. It might be important for shareholders to consider appointing to the board people with CSR experience to strengthen managerial oversight.

5.2.2. Policy Making Implications

Our study shows that CSR activities create complexities that influence the timeliness of audited financial statements. The longer audit report lag for superior CSR performers suggests that firms need to provide more standardized and reliable CSR information to the public and for auditing purposes. This will ensure transparency of CSR activities and an efficient CSR auditing process. Therefore, current or future regulations on CSR disclosure need to be thoroughly reviewed and sufficiently improved to provide clear and more enforceable guides.

The complexity introduced by CSR activities and the propensity for unethical managers to take advantage of the attractiveness of CSR activities to engage in acts that are inimical to shareholders makes it imperative that measures be devised to protect investor interest via effective governance mechanisms. The Public Company Accounting Oversight Board (PCAOB) might need to take actions that deter auditors without the needed CSR expertise from auditing firms with a heavy focus on CSR activities. The United States Securities and Exchange Commission might need to consider issuing guidelines encouraging public firms to include people with CSR expertise oversight on the board of directors to strengthen managerial oversight.

5.2.3. Academic Implications

Our finding contributes to the literature by providing empirical evidence that CSR activities increase the complexity of firms’ financial reporting and, consequently, audit report lag. Our study also adds to the discourse on the factors and incentives that influence audit report lag. Consistent with Khan et al. (2021b), our study emphasizes the importance of voluntary disclosures regarding CSR activities.

6. Limitations and Future Research

There is presently no legislation relating to involuntary disclosure. Therefore, organizations may greenwash their way into the top “100 Best Companies.” Greenwashing may be achieved at the CSR activity level. Our study does not explicitly consider greenwashing in the design of our model. This is a limitation of our study. Another limitation of our study is that our data range from 2011 to 2016 to reduce the impact of COVID-19 on our study. Future research may examine the idiosyncratic influence of the only CSR reporting level, including firms’ greenwashing tendency, on overall or CSR-specific audit quality and reporting lag. Subsequent research needs to examine the composition of the board of directors to ascertain the ability of the board to effectively oversee the activities of management in firms engaged in CSR activities. Researchers might also need to conduct research to ascertain the effectiveness of the PCAOB in curbing audit failures related to CSR activities. Researchers might need to examine the relationship between the number of board members with CSR experience and audit report lag.