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Article

The Effect of Management Characteristics on Audit Report Readability

1
Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran
2
Department of Finance, Banking, and Accountancy, The Faculty of Management, Rzeszow University of Technology, 35-959 Rzeszow, Poland
3
Economics and Administrative Sciences, Qeshm Branch, Islamic Azad University, Qeshm 7953163135, Iran
*
Authors to whom correspondence should be addressed.
Economies 2022, 10(1), 12; https://doi.org/10.3390/economies10010012
Submission received: 22 October 2021 / Revised: 19 December 2021 / Accepted: 20 December 2021 / Published: 1 January 2022

Abstract

:
The present study investigates the relationship between management characteristics (managerial entrenchment, CEO narcissism, overconfidence, board effort, real and accrual-based earnings management) and the audit report readability of listed firms. In other words, this paper seeks to answer the question of “whether management characteristics can have a favourable effect on the audit report readability or not.” The multivariate regression model is used for this study. Research hypotheses were also examined using a sample of 1004 observations on the Tehran Stock Exchange during 2012–2018 and by employing multiple regression patterns based on a panel data technique and fixed effects model. The results show a negative and significant relationship between managerial entrenchment and real and accrual-based earnings management and the audit report readability, based on the FOG index, and a positive and significant relationship between management narcissism, CEO overconfidence, and board effort and the audit report readability, based on the FOG index. Moreover, a negative and significant relationship exists between management entrenchment, CEO overconfidence, real and accrual-based earnings management, and audit report readability based on text length and Flesch indices. A positive and significant relationship was evident between CEO narcissism and board effort and audit report readability based on the same indices. Besides, research models were also examined for more confidence using other additional methods, including FE, T + 1, ABB, and GMM, which confirm the study’s preliminary results. Since the present study is the first paper to investigate such a topic in the emergent markets, it provides valuable information about intrinsic and acquisitive characteristics of management for users, analysts, and legal institutions that contribute significantly to financial statement readability.

1. Introduction

Audit report communications’ effectiveness is partly a function of ease of readability and understanding of audit reports. Hence, the audit report is the main factor between auditors and financial statement users. Therefore, for such a relationship to be effective, the auditor’s presented report should be easily understandable for the users and their references to make sound decisions. In other words, financial statement users should be able to read the audit report easily and understand it. To some extent, comprehending a written text is under the influence of the existing degree of difficulty in that text. The previous studies, including Still (1972); Regazzi (1974); and Soper and Dolphin (1964), show that readability contributes to the effectiveness of the relationship between the auditor and financial statement users.
Therefore, the audit report source of the business annual financial reports is essential, since financial statements are provided based on such annual reports. The audit report is an inseparable part of the relationship between financial statement users and business economic information. Readability is a criterion for measuring the existing complication within a text. Within a standard report for business, text narration indicates information disclosure from the managers’ side. The US Securities and Exchange Commission (SEC) acted clearly for the audit firms’ extremely complicated reports. As suggested by the head of the Commission, some direct and transparent measures should be adopted for combating complicated reports. According to SEC, the main reason for presenting and disclosing information from the business firms’ side is to inform the investors and other financial statement users. Therefore, the presented reports should be understandable for the public users, such that, by referring to them, the financial statement users can easily make decisions about their economic plans (SEC 2007). Li (2008) declares that the annual report’s readability has enhanced the performance of business firms. Readability improves auditing; some argue that the type of audit opinion affects investment analysts’ investment decisions (Duréndez Gómez-Guillamón 2003; Zimon and Chlodnicka 2019), loan lending (Duréndez Gómez-Guillamón 2003; Goicoechea et al. 2021) and investors’ decisions (Chen et al. 2020; Kausar and Lennox 2017; Köhler et al. 2020; Ianniello and Galloppo 2015). The audit report readability is important because audit reports are essential to analysts as a signal of financial statements’ reliability (Coram et al. 2011).
Burgstahler and Dichev (1997) state that managers conceal their earnings management and managerial misbehavior, and complicate the financial statements. Although businesses deliver good news about reaching the objectives, they also have some derivers for concealing the tools used to fulfil the objectives. When the reported performance is different from basic principles, the managers are expected to make the annual reports lengthier and use circumlocution to hide their earnings management actions and misbehaviors.
Given the abovesaid facts, the present study assesses the relationship between management characteristics and audit report readability. In addition, this paper investigates whether management entrenchment, CEO narcissism and overconfidence, board effort, and real/accrual-based earnings management can enhance or debilitate the readability and understanding of audit reports. Since no study has been carried out so far on such a topic by considering the economic and political conditions of the emergent countries, including Iran, the obtained results from this paper can provide the scholars and experts with helpful information. Moreover, this paper’s results help develop science and knowledge in this field and fill the existing literature gap to show the relationship between management characteristics on auditors’ report readability. In the following, we discuss the theoretical principles and conducted studies in this field, methodology, data analysis, discussion, and conclusion.

2. Theoretical Issues and Hypothesis Development

The audit report generally has a standard framework, and auditors are obliged to be aligned with that for expressing their opinions. In a paragraph peculiar to opinion principles, the auditor expresses a set of results that contain distortion, limitation, and ambiguity. In this paragraph, the auditor is not limited to a particular framework and voices his opinions relative to his experience and knowledge. Such a paragraph should be understandable for all users, because a good relationship with the audit report users will be established when the report is understandable for the readers. Today, auditing is a well-established career, and all users are fully aware of the effect of decision-making (Endaya and Hanefah 2013; Arena and Azzone 2009). However, it is noteworthy that some factors will lower such effectiveness (Mihret and Yismaw 2007). Auditors should identify such factors and neutralize their influences in their reporting, because users of audit reports have relied on them for any kind of decision. In case of mistakes or dissatisfaction, their professional credentials will be subject to question, and they will lose their position. One factor affecting users’ inappropriate decisions, and even misleading them, is the audit report’s unreadability. Writing audit reports will perplex the reader, for which specialization and knowledge are required, and public users will not benefit from the audit report.
According to Standard 200, auditors’ primary duty is to assess the accuracy of annual reports and give credit to financial statements by voicing their opinions. Hence, the less the financial statement disorders, the higher the quality is expected to be from the audit report. It is worth mentioning that the simpler the language of such reports, the better the users can benefit from them, since several financial statement users may not have the required specialization in this field. Therefore, the report should be readable and straightforward to understand by the users and applicable for their decisions. In this regard, Li (2008) posits that investors less attract firms with less readable annual reports. Tan et al. (2015) show that better readability of financial statements will improve future decisions and investors and users of financial statements. Sultan (2016) studied the relationship between annual reports’ readability and the auditing role. He found that less readable financial statements increase audit costs.
On the other hand, Lo et al. (2017) indicate that those business firms that embark on either real or accrual-based earnings management have had highly complicated and lengthy annual reports in that year. Ajina et al. (2016) also obtained similar findings to Lo et al. (2017). Earnings management is a method that is increasingly used for manipulating financial results. However, a few studies have assessed the effect of that on the readability of the independent auditor’s report. Pentland (1993); Carrington and Catasús (2007) show that earnings management has a negative effect on the working volume of auditors and ease of the auditing process (e.g., risk of non-discovery due to nonrealization of errors and mistakes). According to the conducted studies, including Guénin-Paracini et al. (2014), earnings management, especially real earnings management, causes auditors’ workload. Lobo and Zhou (2001) express that, in firms with readable information, since their disclosure policy and the amount of disclosure are easily tractable by the shareholders, managers are less willing to manipulate the earnings. Ajina et al. (2016) show that earnings management would decline financial statement readability. Cheng et al. (2018) show a positive and significant relationship between real and accrual-based earnings management and financial statement readability. Salehi et al. (2020a) observe a negative and significant relationship between accrual-based earnings management and family and nonfamily firms’ reputation. Seifzadeh et al. (2021) declare a significant relationship between real and accrual-based earnings management and financial statement comparability. Moardi et al. (2019) perceive that opportunistic earnings management is negatively and significantly associated with future cash flows and shows no significant relationship between accrual-based earnings management and future cash flows in the pharmaceutical industry. Such a relationship is negative and influential in the car industry. So, the first and second hypotheses of the study are as follows:
Hypothesis 1 (H1).
There is a significant relationship between real earnings management and audit report readability.
Hypothesis 2 (H2).
There is a significant relationship between accrual-based earnings management and audit report readability.
The relationship between management entrenchment and board effort and audit reports’ readability’.
In recent years, the amount of research carried out was mostly about the readability of financial statements and less attention to audit reports’ readability. In this study, we seek the readability of auditors’ reports and their relationship with management characteristics. On the other hand, according to corporate governance mechanisms, the CEO has always been the first executive power in organizations, and this factor arms him with a considerable influence on the board of directors. Thus, a conflict of interests between managers and shareholders, given managers’ executive power, raises some organizations’ problems. Moreover, the CEO’s dual role causes the managers to dominate the board of directors to the extent possible and control the board’s receivable information. Broadly, compared with their peers, dual managers are more willing to better show the performance of the business firm (Davidson et al. 2005). One of the motivational factors for manipulating accounting earnings to show the performance of an organization better by managers is CEO compensation, because one of the appropriate criteria for allocating the compensation of managers is measuring their performance; furthermore, CEO compensation is positively associated with the size and firm performance, and so CEO duality moderates the positive association between CEO compensation and firm performance. Since there are no good criteria for allocating rewards to managers, managers’ performance evaluation has always been a metric for granting rewards. Hence, accounting figures and information are a kind of available criterion for measuring managers’ rewards, among which accruals are one of the major contributing factors for managers when signing contracts (Kazan 2016). Accruals’ presence provides the opportunity for managers to employ accounting policies to manage the accruals and manipulate the firm’s real financial events to preserve their benefits (Bianchi and Chen 2015). Li and Kuo (2017) show a positive relationship between CEO compensation and earnings management. Besides, managers with financial specialization will carry out better earnings management due to more familiarity with accounting techniques and accounting policies.
Further, Krishnan et al. (2009) posit that managers with financial knowledge are more competent than others in earnings management through accruals and carry out some real activities, including excessive production and the decline of optional costs. In other words, managers with financial experience guide the analysts more frequently, and the earnings management less so. They have a more in-depth understanding of financial information disclosure’s advantages concerning the increased firm value and decreased information asymmetry (Matsunaga and Yeung 2008; You and Zhang 2009).
Managerial entrenchment is a phenomenon that can be either useful or detrimental to the business firm. Such a phenomenon occurs when the manager has a dual role (CEO duality means the manager is both the head or vice president of the board and the CEO of the firm at the same time (Salehi et al. 2018)). The presence of entrenched managers can have favorable influences on the firm in the long run, but such a phenomenon can hurt the Stock Exchange. For example, lowering the dividend can cause the nonsatisfaction of short-term investors, reluctance of such investors, and withdrawal of capital from the Stock Exchange (Salehi et al. 2018; Frankel and Kelly 2019; Wong et al. 2011). Moreover, Zhou (2017) indicates that older managers present more readable reports than newer ones. The tenure of managers is one of the salient features used to calculate managerial entrenchment in this paper. In addition, there is a determining role in the quality of papered financial statements and management characteristics that affect the readability of financial statements (Seifzadeh et al. 2020). Smulders (1973) declares a significantly negative relationship between management entrenchment and the firm’s financial leverage.
Levy and Szafarz (2016) show that parallel ownership when new shares are waiting and should be granted to the management is a vital tool for the management entrenchment. Salehi et al. (2018) found a significant relationship between management entrenchment, innovation, and firm reputation. Martins (2019) states a negative and significant relationship between management entrenchment and cash holding. Akbari et al. (2018) perceive a significant relationship between managerial characteristics and tax avoidance. Meo et al. (2017) show that management entrenchment can have some advantages for the business firms and their owners. When there are some motivations for increasing the firm performance, the entrenched managers are less willing to be involved in earnings management activities that endanger shareholders’ interests. Salehi et al. (2020b) indicate no significant relationship between management ability and competition in the product market, which means management ability has no impact on competition in the product market. Salehi and Moghadam (2019) reveal a positive and significant relationship between managerial characteristics, namely management ability, and CEO confidence and firm performance. These two managerial features enhance the performance level of business firms. Surroca et al. (2020) indicate that management entrenchment is not always unwelcome, and social responsibility is not always beneficial. That management entrenchment is entangled with social responsibility, and each of them can, in some specific ways, increase the interests of shareholders and the value of business firms. Lari Dashtbayaz et al. (2020) show that board independence, financial expertise, and audit committee are associated negatively and significantly with relational capital. The relationship between audit committee independence and relational capital is positive and significant. Moreover, their study results show that there is also a positive relationship between board independence and human capital, and the relationship between audit committee size and human capital is significant and negative. Seifzadeh et al. (2021) posit that managerial entrenchment is negatively associated and significantly with financial statement comparability.
Further, the board effort and financial statement comparability are associated positively and significantly. Salehi et al. (2020a) observe that firms’ management entrenchment and financial performance, based on the indices of return on assets and Tobin’s Q, have a positive and significant relationship. Moreover, their results show that there is a positive and significant relationship between management entrenchment and social responsibility, so the third and fourth hypotheses are as follows:
Hypothesis 3 (H3).
There is a significant relationship between board effort and audit report readability.
Hypothesis 4 (H4).
There is a significant relationship between management entrenchment and audit report readability.
The relationship between CEO narcissism and audit report readability.
Today, the management of business firms has a determining role in increasing efficiency and output. The increasing complication of societies has caused efficient managers to be recruited for managing business firms. Most scholars believe that decision-making is among the most critical management cores that influences a firm’s failure or success (Daft 1989). On the other hand, according to psychology, making an appropriate decision from the managers’ side is also influenced by personal characteristics (narcissism and overconfidence) and behaviors. Narcissism and overconfidence are a type of psychological disorder, showing itself with some signs, including self-superiority, ignoring others, excessive reward-seeking, and being at the center of attention (Tamborski et al. 2012). Hence, such people in business firms, in terms of dominating others, annoying people, and making decisions in such units, are based on agitation. So, such firms’ operations and performance face serious interventions, because the managers have the intransitive power to affect the unit’s strategies and general structure. The firm’s performance will be afflicted. The conducted studies (e.g., Conger 2002; Chatterjee and Hambrick 2007; Olsen et al. 2014; Olsen and Stekelberg 2016) show that narcissistic managers utilize the business as a tool for increasing their benefits, so such firms suffer from a weak organization. Hence, some factors, such as risky operations, fraud, earnings management, and rules and regulations infringement, are rampant (Johnson et al. 2013; Amernic and Craig 2010). Since the responsibility for providing financial reports is up to the board and business management is one factor to be considered, in this paper, the effect of narcissistic and overconfident managers, managerial entrenchment, and board efforts on audit report readability is explored, because such managers have personality characteristics, such as selfishness, exploiting others, and seeking dominance (Campbell et al. 2011). Self-superiority is more likely than others to present fraudulent and complicated financial reports. This occurs because such managers gain personal benefits, satisfy the sense of superiority and arrogance, do not mind the presented rules and regulations, manipulate financial reports, make them complicated, and conceal their misbehavior actions to draw the admiration and attention of others (Capalbo et al. 2018). This will decline financial statements’ readability and follow the independent auditor’s report (Bloomfield 2008). Therefore, we can claim that narcissism can contribute to the managers’ judgment about the chance of their success. Extremely narcissistic managers may consider those actions deemed impossible publicly, or with little chance of success, as optimistic and perform such bold efforts to attract others’ attention (Wallace and Baumeister 2002). According to Nietzsche, narcissistic managers are “superior men.” The regular rules cannot be applied. Such a belief can increase the chance of immoral actions, such as earnings management, and justifying them. Zhang and Wiersema (2009), Hasan (2017) show that competent managers publish more readable financial reports. Ajina et al. (2016); Bonsall and Miller (2017); Ertugrul et al. (2017) also note that financial statement readability leads to the decline in debt costs. Ham et al. (2017) also declare that narcissistic managers often have the decision-making process under their dominance and are unwilling to consult with others. Hence, the chance of earnings management is higher in business with narcissistic managers. Ham et al. (2018) show a negative and significant relationship between narcissistic managers and performance in business firms. Church et al. (2019) identify a meaningful relationship between auditors’ narcissism and aggressive reporting. Salehi et al. (2020c) indicate a negative and significant relationship between managers’ overconfidence and conservatism. They conclude that a negative and significant association exists between CEO overconfidence and real earnings management. When overconfident Iranian managers have financial problems, they are not involved in real earnings management. This does not increase the firm value in the long run, but hurts the business units. Seifzadeh et al. (2020) show a positive and significant relationship between managers’ narcissism, overconfidence, and financial statement readability. So, the fifth and sixth hypotheses of the study are as follows:
Hypothesis 5 (H5).
There is a significant relationship between CEO narcissism and audit report readability.
Hypothesis 6 (H6).
There is a significant relationship between managers’ overconfidence and audit report readability.

3. Research Methodology

The statistical population of this paper includes all listed firms on the Tehran Stock Exchange. The systematic elimination method is used for samplings and, after imposing the following conditions, the statistical sample of the study will be selected with the following conditions:
Firms should be enlisted on the Tehran Stock Exchange until the end of 2011;
The required financial information should be presented completely during the period of the study;
Firms should not be affiliated with investment firms, banks, insurance, and financial intermediaries.
Concerning these limitations at the end of 2018, the final sample was obtained according to Table 1.

3.1. Data Collection and Method

The primary and raw information and data for hypothesis testing were collected using the Tehran Stock Exchange information bank, including Tadbir Pardaz and Rah Avard-e Novin. The published reports of the Tehran Stock Exchange were obtained via direct access (by analyzing the released reports in the Codal Website and manually collected data) to CDs and by referring to rdis.ir website and other necessary resources.

3.1.1. Data Analysis Method

The data analysis method is cross-sectional and year-by-year (panel data). This paper uses the multivariate linear regression model for hypothesis testing. Descriptive and inferential statistical methods are used for analyzing the obtained data. Hence, the frequency distribution table is used for describing data. At the inferential level, the F-Limer, Hausman test, normality test, and multivariate linear regression model are used for hypothesis testing.

3.1.2. Research Model

The following models are used to examine the hypotheses of the study:
Model (1)
FOGit = a0 + a1MEit + a2Over.Conit + a3CEO_NARit + a4REMit + a5AEMit + a6BEFit + a7ageit + a8roait +
a9levit + a10GRWit + a11sizeit + a12IINVit + a13Intangit + a14OWNit + a15segit + a16busyit + a17currentit
+ a18restit + a19lossit + a20mtbit + a21Yearit + a22Industryit + εit
Model (2)
textindexit = a0 + a1MEit + a2Over.Conit + a3CEO_NARit + a4REMit + a5AEMit + a6BEFit + a7ageit +
a8roait + a9levit + a10GRWit + a11sizeit + a12IINVit + a13Intangit + a14OWNit + a15segit + a16busyit +
a17currentit + a18restit + a19lossit + a20mtbit + a21Yearit + a22Industryit + εit
Model (3)
flashindexit = a0 + a1MEit + a2Over.Conit + a3CEO_NARit + a4REMit + a5AEMit + a6BEFit + a7ageit +
a8roait + a9levit + a10GRWit + a11sizeit + a12IINVit + a13Intangit + a14OWNit + a15segit + a16busyit +
a17currentit + a18restit + a19lossit + a20mtbit + a21Yearit + a22Industryit + εit
where:
Dependent variables
Auditor’s report readability is computed using the following three indices:
FOG Index:
FOG: Audit report readability. To calculate the audit report readability, according to the study of (Lawrence 2013) Zhang, You, Lawrence, and Ajina et al., the following index is used, the reliability and validity of which for examining Persian text readability are confirmed by some local scholars. The audit report readability index is FOG (FOGIND), which is a function of two variables of sentence length (based on words) and complicated words (defined in the form of the number of three or multi-syllable words), and is calculated as follows:
FOG index = (average no. of words in each sentence + percentage of complicated words) × 0.4
The process and manner of determination of audit report level of readability in the above index are as follows:
Selecting a 100-word sample from the beginning, a 100-word sample from the middle, and a 100-word sample from the end of the report, randomly;
Counting the number of sentences of each sample;
Determining average sentence length by dividing the number of words into the number of complete sentences of each sample of 100 words;
Counting the number of existing three-syllable and more than three-syllable words (complicated words) in each 100-word text;
Adding the number of complicated words with the average number of words in sentences;
Multiplying the number of complicated words and average words in sentences by the fixed figure of 0.4;
Calculating no. 4, 5, and 6 for two other 100-word samples;
Calculating the average results of all three samples by adding and dividing by number.
The relationship between the FOG index and readability level is as follows: FOG > 18 means the text is not readable and more complicated; 14–18 (hard text), 12–14 (average text), 10–12 (acceptable text), 8–10 (easy text).
Text length index (INDEX):
The second index for financial reporting readability is text length (index), which is calculated as follows:
Text length index = Ln number of text words.
Since higher values of the above indices indicate lower audit report readability, each calculated index is multiplied by −1 to obtain a direct criterion from the audit report readability index.
Flesch Index: The Flesch index determines the degree of difficulty or simplicity of the text based on two linguistic factors of average sentence length and the number of syllables of each sample.
Flesch readability index = average number of words × −1.015 (average words length × 262.835 − 84.6)
The process and manner of placement of financial reporting readability in the above index are as follows:
Calculating average word length: syllables are counted in the text and divided into total numbers of the text;
Word length is multiplied by 84.6;
The obtained figure from the previous step is subtracted from 206.835;
Calculating the number of average words: the number of words of the text is divided into the number of complete sentences;
The average number of words is multiplied by 1.015;
The obtained figure from the previous step is subtracted from the one calculated in the third step to determine the degree of text simplicity.
The relationship between the Flesch index and readability level is as follows: 71 or higher (extremely simple), between 60 and 70 (normal readability), lower than 60 (hard and unreadable).
Independent variables
ME: managerial entrenchment, for the evaluation of which, according to the study of Salehi et al. (2020a), the following six indices will be used:
Managerial ownership: the number of stocks available to the CEO divided by total published stocks of the firm;
CEO tenure: the duration the CEO has been in position consistently until the year under study;
CEO duality: if the CEO is the head or vice president of the board, 1; otherwise, 0;
Board compensation: the amount of compensation assigned to the approved board of Annual Ordinary General Assembly in the year under study;
CEO change: if the CEO has changed during the year, 1; otherwise, 0;
Board independence: unbounded members to total board members.
This paper uses the exploratory factor analysis to calculate the management entrenchment variable. Factor analysis is a multivariate statistical method for classifying and realizing the available structures among research data. This statistical method is usually used for two purposes: first, the exploratory factor analysis enables us to combine a broad spectrum of corporate governance variables to create managerial entrenchment proxy, while, in the previous studies, either a limited set of corporate governance factors were considered as managerial entrenchment or the problem of multilinearity is taken for granted, which can be due to the presence of control and independent corporate governance variables in empirical methods, and, on the other hand, controlling the potential mutual relationship between variables is a significant and hard task. Second, one of the exploratory factor analysis characteristics assigns a weight to each involved variable in managerial entrenchment based on the correlation coefficient matrix’s output. This method contrasts with the previous studies that assume each corporate governance factor’s effect is equal.
As for the calculation of the variable of managerial entrenchment, initially, the information related to six corporate governance factors that affect the motivation and management competency is collected for each year–company. The linear correlation coefficient matrix of the above six variables is extracted, divided by year, and, finally, exploratory factor analysis is carried out. The weight of each sixfold variable is obtained. The factor’s total weight coefficient achieves the variable of managerial entrenchment by a numerical value of the related factor.
Over.CON: managers’ overconfidence. In this paper, the index of surplus investment in properties is used to measure managers’ overconfidence as follows:
Following Schrand and Zechman (2012) study, this index indicates the amount of surplus investment in properties achieved from the residual of total asset growth regression in sales growth, estimated separately for each industry year. If the regression residual is larger than 0, this index equals 1; otherwise, 0 will be assigned. This index’s basis is that managers invest more infirm than their peers in firms whose assets go up at a higher rate than sales.
Assets.Grit = a0 + a1sales.Grit + εit
CEO-NAR: CEO narcissism
There are three criteria for measuring managerial narcissism:
Cash compensation index: narcissistic executive managers usually ask for higher cash compensations and stabilize their organizations. The cash compensation index of managers is achieved by dividing the approved cash compensation in the general assembly session into the firm’s total payroll for the fiscal year.
CEO signature: it seems that those firms managed by CEOs with big signatures (a psychological index for narcissism) are less efficient than CEOs with small signatures. Recently, a research program focusing on leaders’ signature size effort to judge a narcissistic leader’s impacts on his organization (Campbell et al. 2011) measured 605 CEOs’ signatures with 10 years of working experience from 400 firms (affiliated with 500 premium stocks in the New York market). All signatures were placed at the bottom of the annual financial reports. It is specified that bigger signatures, which indicate narcissistic personal characteristics, dominance on others, and self-confidence, are associated positively with the managers’ mis-spend and lower return of the property. Compared with other active members in that industry, such managers are contradictorily more inclined to pay an increase.
It is worth mentioning that two cash compensation and signature criteria are used in this paper to measure narcissism, since the first index is not available due to the nondisclosure of managers’ pictures by firms.
REM: real earnings management. Abnormal cash flow (EM_CFO), abnormal cost (EM_PROD), and abnormal discretionary costs (EM_DISX) are used for measuring firm sales control, production control, and discretionary cost control. Formula (2) is used for estimating abnormal cash flow of the firm (EM_CFO), Formula (3) for estimating abnormal production cost of the firm (EM_PROD), and Formula (4) for estimating the abnormal discretionary cost of the firm (EM_DISX). In this paper, Formula (4) is employed for estimating real earnings management.
CFOi,t Ai,t-1 = β11 Ai,t-1 + β2si,t Ai,t-1 + β3∆si,t Ai,t-1 + δi,t
PRODi,t Ai,t-1 = β11 Ai,t-1 + β2si,t Ai,t-1 + β3∆si,t Ai,t-1 + β4∆si,t-1 Ai,t-1 + δi,t
DISXi,t Ai,t-1 = β11 Ai,t-1 + β2si,t-1 Ai,t-1 + δi,t
Si,t in Formula (2) is the sales income of the firm i in the year t. Prodi,t in Formula (3) is the total cost of the firm i of product in the year t, which equals the total product cost and inventory change.
DISX,t in Formula (4) is the total office costs and sales costs of the firm i in the year t. For a similar industry and year, given the Formulas (2)–(4), EM_COF (abnormal cash flow of the firm), EM_PROD (abnormal production cost), and EM_DISX (abnormal discretionary costs) are assigned to the regression residuals. Since the firm may select a combination of these three methods, we used Cohen and Zarowin (2010) and Zang (2012) to create a total index of real earnings management:
EM PROXY = EM PROD − EM CFO − EM DISX
AEM: accrual-based earnings management, the calculation of which uses the adjusted Jone’s model. The coefficients are estimated through Equation (2):
TAi,t Assetsi,t-1 = α11 Assetsi,t-1 + α2∆Salesi,t Assetsi,t-1 + α3PPEi,t Assetsi,t-1 + εi,t
After estimating the coefficients, nondiscretionary accruals are calculated after coefficient estimation:
NDAi,t Assetsi,t-1 = α11 Assetsi,t-1 + α2∆Salesi,t-∆ARi,t Assetsi,t-1 + α3PPEi,t Assetsi,t-1
Finally, for the calculation of the discretionary accruals, we have:
DAi,t Assets,t-1 = Tai,t Assets,t-1 − NDAi,t Assets,t-1
In the above equation, TA is accruals, Assets is total assets, Sales is income, AR is accounts receivable, PPE is gross properties, machinery, and instrument, and NDA is nondiscretionary accruals.
In this paper, the following formula is used for calculating accruals, which is referred to as profit and loss:
Accruals = Operational cash flow − profit before unpredicted items
Most previous studies have used discretionary accruals (DA) to measure earnings and audit quality. This paper uses DA as a proxy for audit quality because it presents a degree of negotiations related to audit setting decisions. Abnormal accruals of performance setting estimate the size of DA.
BEF: board effort equal to the number of sessions held by the board during the year.
Control variables
LEV: financial leverage, which is equal to total debts divided by total assets;
Age: firm age, which is equal to the time interval between firm establishment date until the year under study;
Size: firm size, the natural logarithm of firm assets;
ROA: return on assets, which is equal to net profit divided by total assets;
GRW: sales growth that is equal to the sales of this year minus that of the previous year divided by sales of the previous year;
OWN: major shareholder, a shareholder with more than 5% ownership, 1; otherwise, 0;
linve: institutional shareholder, the number of stocks available to investors, public institutions, banks, insurance, and state-owned institutions;
Intang: intangible assets to total assets of the firm;
Seg: the number of commercial sections of the firm in the year under study;
Current: a current ratio that is equal to total current assets divided by current debts;
Rest: financial restatement, if the firm has restated the financial statements of the current year, 1; otherwise, 0;
Loss: firm loss, should the firm be losing in the year under study, 1; otherwise, 0;
Busy: if the end of the fiscal year is set on January 20, one will be assigned; otherwise, 0;
Mtb: market value to book value of equity;
Year: dummy variable for the year.
Industry: dummy variable for industry.

4. Results

This paper uses three models to assess the relationship between management characteristics (real/accrual-based earnings management, management entrenchment, managers’ overconfidence, managers’ narcissism, and board effort) and the audit report readability. The present study (Table 2) has inserted the panel data method in its database, including 150 Iranian firms from 2012 to 2018. The variables of real/accrual-based earnings management, management entrenchment, managers’ overconfidence, managers’ narcissism, board effort, auditor’s readability report, and a series of control variables have been used for estimating the models.

4.1. Linearity Test

According to Table 3 and Table 4, by analyzing the linearity of variables, no linearity is evident among variables, and they are independent of each other.
As shown in the table, since the obtained VIF statistic for all variables is less than 10, there is no linearity among model variables.

4.2. Sensitivity Analysis

Table 4 shows the results of sensitivity analysis model.
Table 4. Sensitivity analysis model.
Table 4. Sensitivity analysis model.
FogTextindexFlashindexMeOverconCeonarRemAemBefAgeRoaLevGrwSizeOwnIinvIntangSegBusyCurrentRestLossMtb
Fog1.000
Textindex0.0221.000
Flashindex−0.0510.0671.000
me−0.0320.0600.0491.000
Overcon0.036−0.054−0.083−0.0091.000
Ceonar−0.0030.0170.017−0.0650.0861.000
Rem0.0260.003−0.004−0.038−0.070−0.0541.000
Aem0.0680.0010.0120.051−0.054−0.009−0.0061.000
Bef−0.0050.090−0.0140.099−0.011−0.032−0.013−0.0261.000
Age−0.0600.004−0.027−0.0740.034−0.0900.0070.056−0.0131.000
Roa−0.010−0.073−0.0320.0500.0030.089−0.0230.0540.049−0.1031.000
Lev0.0650.085−0.070−0.0200.065−0.0560.062−0.031−0.0460.048−0.6201.000
Grw0.0210.0170.038−0.045−0.0240.0030.0000.0190.0190.0110.208−0.0921.000
Size−0.0070.189−0.0130.026−0.0790.0650.014−0.0890.3710.0350.0380.0710.0031.000
Own0.089−0.087−0.004−0.0410.0840.030−0.006−0.068−0.107−0.1380.0160.089−0.034−0.0801.000
Iinv−0.007−0.015−0.0480.0510.0250.122−0.024−0.1050.077−0.1950.0370.148−0.0110.1890.4551.000
Intang−0.0000.005−0.0490.004−0.064−0.018−0.022−0.097−0.054−0.1260.000−0.029−0.007−0.0560.1240.1161.000
Seg−0.0050.2820.0060.055−0.032−0.0410.0130.0820.1490.068−0.2660.246−0.0730.247−0.190−0.076−0.1271.000
Busy−0.1200.0160.0900.009−0.053−0.017−0.0150.075−0.0650.035−0.000−0.0290.020−0.0350.1420.2330.031−0.0671.000
Current−0.069−0.0420.1020.051−0.0440.009−0.0090.158−0.0320.0840.492−0.5940.104−0.132−0.121−0.215−0.051−0.1280.0161.000
Rest0.0070.0350.0440.036−0.0440.046−0.0020.0430.0650.036−0.0900.058−0.0430.001−0.0860.025−0.0630.1780.013−0.0551.000
Loss0.0210.0560.012−0.0610.010−0.042−0.0510.0510.0220.078−0.5590.463−0.1460.001−0.0330.0170.0090.309−0.023−0.2620.0871000
Mtb0.0430.001−0.0370.0070.013−0.035−0.0080.024−0.0320.0210.068−0.0670.1010.097-0.015−0.0200.0680.0040.0370.019−0.107−0.0551.000

4.3. Research Models Estimation

Based on the FOG index (Table 5).
We should first analyze whether the data are pooled or panel, using the F test to estimate the model. This test’s null hypothesis expresses that data are pooled, and hypothesis 1 declares that data are panel. After performing the F test, H0 is rejected. The question is based on which models of fixed effects or random effects that the model is analyzable, which is determined by the Hausman test. Regarding the pooled test results reported in Table 6, the null hypothesis concerning the pooled data is rejected for the first models at 99%. Hence, a model with panel data should be used to estimate the model’s coefficients.
Moreover, according to Table 6, the Hausman test statistic based on the first model’s estimation equals 33.54. The probability level of 0.0294 is smaller than the table, so the null hypothesis is rejected. Hence, a model with a fixed effect is more appropriate for the research model.
Table 6 shows a negative and significant relationship between managerial entrenchment and real/accrual-based earnings management and auditor’s report readability based on the FOG index. Their p-values are 0.000, 0.000, and 0.048 lower than the 0.05 significance level. Their coefficients are 0.016, 0.096, and 0.217, showing a negative relationship between these variables and the auditor’s report readability. Moreover, according to the hypotheses’ results, there is a positive and significant relationship between managers’ overconfidence, managers’ narcissism, and board effort and auditor’s report readability based on the FOG index. Because their p-values are 0.042, 0.000, and 0.043 lower than the 0.05 significance level, their coefficients are 0.114, 0.042, and 0.003, there is a positive and significant relationship between these variables and audit report readability based on the FOG index. Since the p-value of the model is 0.0082, the model enjoys sufficient significance.
Based on a text index.
We should first analyze whether the data are pooled or panel using the F test to estimate the model. This test’s null hypothesis expresses that data are pooled, and hypothesis 1 declares that data are panel. After performing the F test, H0 is rejected. The question is based on which models of fixed effects or random effects that the model is analyzable, which is determined by the Hausman test. Regarding the pooled test results reported in Table 6, the null hypothesis concerning the pooled data is ejected for the first models at 99%. Hence, a model with panel data should be used to estimate the model’s coefficients. Moreover, according to Table 6, the Hausman test statistic based on the first model’s estimation equals 21.76, larger than in the table, so the null hypothesis is not rejected. Hence, a model with a random effect is more appropriate for the research model.
Table 6 shows a negative and significant relationship between managerial entrenchment, managers’ overconfidence, real/accrual-based earnings management, and auditor’s report readability based on the text length index, because their p-values are 0.007, 0.024, 0.049, and 0.001 lower than the 0.05 significance level. Their coefficients are 0.019, 0.046, 0.086, and 0.042, showing a negative relationship between these variables and the auditor’s report readability. Moreover, according to the hypotheses’ results, there is a positive and significant relationship between managers’ overconfidence, board effort, and auditor’s report readability based on the text length index. Their p-values are 0.000 and 0.006 lower than the 0.05 significance level. Their coefficients are 0.106 and 0.023, showing a positive and significant relationship between these variables and audit report readability based on the text length index. Since the p-value of the model is 0.0014, the model enjoys sufficient significance based on the Flesch index
We should first analyze whether the data are pooled or panel using the F test to estimate the model. This test’s null hypothesis expresses that data are pooled, and hypothesis 1 declares that data are panel. After performing the F test, H0 is rejected. The question is based on which models of fixed effects or random effects that the model is analyzable, which is determined by the Hausman test. Regarding the pooled test results reported in Table 7, the null hypothesis concerning the pooled data is rejected for the first models at 99%. Hence, a model with panel data should be used to estimate the model’s coefficients. Moreover, the Hausman test statistic based on the first model’s estimation equals 21.76, which is larger than the table, so the null hypothesis is not rejected. Hence, a model with a random effect is more appropriate for the research model.
Table 7 shows a negative and significant relationship between managerial entrenchment, managers’ overconfidence, real/accrual-based earnings management, and auditor’s report readability based on the Flesch index p-values, which are 0.000, 0.016, 0.030, and 0.000 lower than the 0.05 significance level. Their coefficients are 0.028, 0.019, 0.074, and 0.028, showing a negative relationship between these variables and the auditor’s report readability. Moreover, according to the hypotheses’ results, there is a positive and significant relationship between board efforts and auditor’s report readability based on the Flesch index, because its p-value is 0.004 lower than the 0.05 significance level. Its coefficient is 0.024, showing a positive and significant relationship between these variables and audit report readability based on the Flesch index. Since the p-value of the relationship between managers’ narcissism and auditor’s report readability, based on the Flesch index, is 0.051, there is no significant relationship between these two variables at a 95% confidence level. Still, there is a positive and significant relationship at a 90% level, because the coefficient of that is 0.094, showing that, if managers’ narcissism goes up, the readability of the audit report increases. Since the p-value of the model is 0.000, the model enjoys sufficient significance.
Robustness testing.
The FOG index.
In this paper, to obtain better results and confirm them, research hypotheses were also tested by using other additional methods, the results of which are as follows:
To confirm model (1), the relationship between management characteristics and auditor’s report readability is examined based on the FOG index using the FE, GMM, and t + 1 methods. According to the results in Table 8 and based on the FOG index, there is a negative and significant relationship between management entrenchment and real/accrual-based earnings management and audit report readability, and the relationship between managers’ overconfidence, managers’ narcissism, and board effort and auditor’s report readability is positive and significant. The findings follow the results of the primary method and confirm that. Since the results of the additional methods are in total conformity with the study’s main method, we can confidently claim that a significant relationship between management characteristics and auditor’s report readability is examined based on the FOG index. It is worth mentioning that the relationship between board effort and managers’ narcissism and auditor’s report readability based on the FOG index is confirmed via fixed effects and t + 1 methods at a 90% level.
Based on a text index.
To confirm model (2), the relationship between management characteristics and auditor’s report readability is examined based on the text index using the ABB, FE, and t + 1 methods. According to the results in Table 9 and based on the text index, there is a negative and significant relationship between management entrenchment, managers’ overconfidence, and real earnings management and auditor’s report readability, and the relationship between managers’ narcissism and auditor’s report readability is positive and significant. The relationship between accrual-based earnings management and auditor’s report readability was negative and significant based on the same index. Simultaneously, the board effort has a positive and significant relationship with the so-called variable at a 90% level. All these relations were not evident at the 95% level. Since the random effects method results conform with the study’s main method, we can confidently claim that a significant relationship between management characteristics and independent auditor’s report readability is examined based on the text index.
Based on the Flesch index.
To confirm model (1), the relationship between management characteristics and audit reports’ readability is examined using the t + 1 method. According to the results in Table 10 and based on the Flesch index, there is a negative and significant relationship between management entrenchment, managers’ overconfidence, and real/accrual-based earnings management and auditor’s report readability, and the relationship between managers’ narcissism and board effort and auditor’s report readability is positive and significant. Since the results of the additional methods are in total conformity with the study’s main method, we can confidently claim that a significant relationship between management characteristics and auditor’s report readability is examined based on the Flesch index (Table 11).

5. Conclusions

The study results show a negative and significant relationship between management entrenchment, real/accrual-based earnings management, and audit report readability based on the FOG index. There is a positive and significant relationship between management narcissism, managers’ overconfidence, board effort, and audit report readability. Moreover, the Flesch index shows a negative and significant relationship between management entrenchment, managers’ overconfidence, real/accrual-based earnings management, and audit report readability. Further, there is a positive and significant relationship between management narcissism, board effort, and audit report readability. However, various studies conducted on the relationship between management characteristics and financial statement readability are used in this paper for comparison, because the audit report readability is, to a great extent, associated with the readability of financial statements. Hence, should financial statements enjoy good readability. The audit report will be more readable.
The primary findings demonstrate that entrenched managers are more likely to provide less readability of audit reports. Moreover, it can be reasoned that entrenched managers may cover their opportunistic behavior, such as earning managers under the unclear financial notes; the negative and significant relationship between real/accrual-based earnings management and audit report readability leads to such a conclusion. In contrast, the obtained results show a positive and significant relationship between CEO narcissism and board effort and overconfidence and audit report readability, which means that higher CEO narcissism and overconfidence, and board effort, lead to higher audit report readability. Thus, the present study results align with (Lo et al. 2017), Ajina et al. (2016), Bloomfield (2008). They declare that firms with accrual-based earnings management propose more complicated and lengthier reports. The results also contrast with that of Cheng et al. (2018). They posit that accrual-based earnings management is associated positively and significantly with financial statement readability. Since these units make the annual report more complicated and conceal their illegal actions, including earnings management and annual reports, unreadability is the best method for fulfilling such purposes. The more unreadable the financial statements and the quality of financial reporting, the more influence the auditor presented. To increase their social position, auditors make an effort to present reports with an appropriate level of readability to enable the users to understand and better decide on their economic affairs. So, we recommend future studies to assess the effect of audit quality and its components, including financial independence and auditor’s industry specialization, on audit report readability. The present study’s findings show, first, the evidence relative to the advantages that audit report readability has for analysts, investors, and creditors. Second, it shows how managers’ psychological features affect the audit report readability. The ability to foresee the effect of such attributes on firm statements is of great importance for audit report users who make their most important economic decisions based on such comparisons. Then, these findings can lead to the development of theoretical principles of the previous studies concerning audit reporting linguistics in emerging markets in Iran and developing countries. Furthermore, results show to what extent do the psychological features and to what extent does the management competency in real and accrual-based earnings management contribute to audit report readability of business firms, and this issue, as a scientific achievement, can provide useful information for investors, capital market legislation, accounting standard compilers, and other users of accounting information. Finally, the results of this study presented new ideas for conducting new studies in the field of personal characteristics of managers and audit report styles of business firms.

Author Contributions

Conceptualization, M.S. (Mahdi Salehi), G.Z. and M.S. (Maryam Seifzadeh); methodology, M.S. (Mahdi Salehi) and M.S. (Maryam Seifzadeh); software, M.S. (Mahdi Salehi) and M.S. (Maryam Seifzadeh), and G.Z.; formal analysis M.S. (Mahdi Salehi) and M.S. (Maryam Seifzadeh); investigation, M.S. (Mahdi Salehi) and M.S. (Maryam Seifzadeh); resources, M.S. (Mahdi Salehi) and M.S. (Maryam Seifzadeh); data curation, M.S. (Mahdi Salehi) and M.S. (Maryam Seifzadeh); writing—original draft preparation, MahdiSalehi., G.Z. and M.S. (Maryam Seifzadeh); writing—review and editing, MahdiSalehi., G.Z. and M.S. (Maryam Seifzadeh); visualization, MahdiSalehi., G.Z, and M.S. (Maryam Seifzadeh); supervision, MahdiSalehi., G.Z. and M.S. (Maryam Seifzadeh) All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

This does not apply to this article. this is a survey. The results of the surveys are presented in the article. Authors have the polls.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ajina, Aymen, Mhamed Laouiti, and Badredine Msolli. 2016. Guiding Through The fog: Does Annual Report Readability Reveal Earnings Management? Research in International Business and Finance 38: 509–16. [Google Scholar] [CrossRef]
  2. Akbari, Farzana, Mahdi Salehi, and Mohammad Ali Bagherpour Vlashani. 2018. The Effect of Managerial Ability on Tax Avoidance by Classical and Bayesian Econometrics in Multilevel Models: Evidence of Iran. International Journal of Emerging Markets 13: 1656–78. [Google Scholar] [CrossRef]
  3. Amernic, Joel H., and Russel J. Craig. 2010. Accounting as a facilitator of extreme narcissism. Journal of Business Ethics 96: 79–93. [Google Scholar] [CrossRef]
  4. Arena, Marika, and Giovanni Azzone. 2009. Identifying organizational drivers of internal audit effectiveness. International Journal of Auditing 13: 43–60. [Google Scholar] [CrossRef]
  5. Bianchi, Giuliano, and Yong Chen. 2015. CEO compensation and the performance of firms in the hospitality industry: A cross-industry comparison. International Journal of Tourism Sciences 15: 121–38. [Google Scholar] [CrossRef]
  6. Bloomfield, James. 2008. Discussion of Annual Report Readability, Current Earnings, and Earnings Persistence. Journal of Accounting and Economics 45: 248–52. [Google Scholar] [CrossRef]
  7. Bonsall, Samuel B., and Brian P. Miller. 2017. The impact of narrative disclosure readability on bond ratings and the cost of debt. Review of Accounting Studies 22: 608–43. [Google Scholar] [CrossRef]
  8. Burgstahler, David, and Ilia Dichev. 1997. Earnings management to avoid earnings decreases and losses. Journal of Accounting and Economics 24: 99–126. [Google Scholar] [CrossRef]
  9. Campbell, W. Keith, Brian Hoffman, Stacy M. Campbell, and Gaia Marchisio. 2011. Narcissism in organizational contexts. Human Resource Management Review 21: 268–84. [Google Scholar] [CrossRef]
  10. Capalbo, Francesco, Alex Frino, Ming Ying Lim, Vito Mollica, and Riccardo Palumbo. 2018. The impact of CEO narcissism on earnings management. Abacus 54: 210–26. [Google Scholar] [CrossRef]
  11. Carrington, Thomas, and Bino Catasús. 2007. Auditing stories about discomfort: Becoming comfortable with comfort theory. European Accounting Review 16: 35–58. [Google Scholar] [CrossRef]
  12. Chatterjee, Arjit, and Donald C. Hambrick. 2007. It’s all about me: Narcissistic chief executive officers and their effects on company strategy and performance. Administrative Science Quarterly 52: 351–86. [Google Scholar] [CrossRef]
  13. Chen, Shimin, Bingbing Hu, Donghui Wu, and Ziye Zhao. 2020. When Auditors Say ‘No’, Does the Market Listen? European Accounting Review 29: 263–305. [Google Scholar] [CrossRef]
  14. Cheng, Jinfeng, Jixin Zhao, Chang Xu, and Haocheng Gong. 2018. Annual Report Readability and Earnings Management: Evidence from Chinese Listed Companies. Advances in Social Science, Education and Humanities Research 181: 794–97. [Google Scholar] [CrossRef] [Green Version]
  15. Church, Bryan K., Narisa Tiajing Dai, Xuejaio Liu, and Xi Kuang. 2019. Auditor Narcissism and Auditor-Client Negotiations. Contemporary Accounting Research 37: 1756–87. [Google Scholar] [CrossRef]
  16. Cohen, Daniel A., and Paul Zarowin. 2010. Accrual-based and real earnings management activities around seasoned equity offering. Journal of Accounting and Economics 50: 2–19. [Google Scholar] [CrossRef] [Green Version]
  17. Conger, Jay A. 2002. Danger of delusion, the qualities that make leaders great can also cause their downfall, success and self-confidence often breed narcissism and a sense of infallibility. Financial Times, November 29. [Google Scholar]
  18. Coram, Paul J., Theodore J. Mock, Jerry L. Turner, and Glen L. Gray. 2011. The communicative value of the auditor’s report. Australian Accounting Review 21: 235–52. [Google Scholar] [CrossRef]
  19. Daft, Richard L. 1989. Organization Theory and Design. Tehran: Cultural Research Bureau. [Google Scholar]
  20. Davidson, Ryan, Jenny Goodwin-Stewart, and P. Pamela Kent. 2005. Internal governance structures and earnings management. Accounting & Finance 45: 241–68. [Google Scholar]
  21. Duréndez Gómez-Guillamón, Antonio. 2003. The usefulness of the audit report in investment and financing decisions. Managerial Auditing Journal 18: 549–59. [Google Scholar] [CrossRef]
  22. Endaya, Khaled Ali, and Mustfa Hanefah. 2013. Internal Audit Effectiveness: An Approach Proposition to Develop, the Theoretical Framework. Journal of Finance and Accounting 4: 92–103. [Google Scholar]
  23. Ertugrul, Mine, Jin Lei, Jiaping Qiu, and Chi Wan. 2017. Annual report readability, tone ambiguity, and the cost of borrowing. Journal of Financial and Quantitative Analysis 52: 811–36. [Google Scholar] [CrossRef] [Green Version]
  24. Frankel, David, and P. J. Kelly. 2019. Entrenched Management, Stakeholders, and Capital Structure: Project Summary. Available online: https://www.dmfrankel.com/projDesc.pdf (accessed on 20 November 2019).
  25. Goicoechea, Estibaliz, Fernando Gómez-Bezares, and Joe Vincente Ugarte. 2021. Improving Audit Reports: A Consensus between Auditors and Users. International Journal of Financial Studies 9: 25. [Google Scholar] [CrossRef]
  26. Guénin-Paracini, Henri, Bertrand Malsch, and Anne Marché Paillé. 2014. Fear and risk in the audit process. Accounting, Organizations and Society 39: 264–88. [Google Scholar] [CrossRef]
  27. Ham, Charles, Nicolas Seybert, and Sean Wang. 2017. CFO narcissism and financial reporting quality. Journal of Accounting Research 55: 1089–135. [Google Scholar] [CrossRef]
  28. Ham, Charles, Nicolas Seybert, and Sean Wang. 2018. Narcissism is a bad sign: CEO signature size, investment, and performance. Review of Accounting Studies 23: 234–64. [Google Scholar] [CrossRef]
  29. Hasan, Mostafa Monzur. 2017. Managerial Ability, Annual Report Readability and Disclosure Tone. Available online: https://www.tandfonline.com/loi/rear20 (accessed on 27 November 2018).
  30. Ianniello, Giuseppe, and Giuseppe Galloppo. 2015. Stock market reaction to auditor opinions—Italian evidence. Managerial Auditing Journal 30: 610–32. [Google Scholar] [CrossRef]
  31. Johnson, Erin N., John R. Kuhn, Barbara Apostolou, and John M. Hassell. 2013. Auditor perceptions of client narcissism as a fraud attitude risk factor. Journal of Practice & Theory 32: 203–19. [Google Scholar]
  32. Kausar, Asad, and Clive Lennox. 2017. Balance sheet conservatism and audit reporting conservatism. Journal of Business Finance & Accounting 44: 897–924. [Google Scholar]
  33. Kazan, Emre. 2016. The Impact of CEO Compensation on Firm Performance in Scandinavia. IBA Bachelor thesis, University of Twente, The Faculty of Behavioural, Management and Social Sciences, Enschede, The Netherlands; pp. 1–10. [Google Scholar]
  34. Köhler, Annette, Nicole Ratzinger-Sakel, and Jochen Theis. 2020. The effects of key audit matters on the auditor’s report’s communicative value: Experimental evidence from investment professionals and non-professional investors. Accounting in Europe 17: 105–28. [Google Scholar] [CrossRef]
  35. Krishnan, Gopal V., Gnanankumar Visvanathan, and Nancy Su. 2009. Does Accounting and Financial Expertise in the C-Suite Aid or Mitigate Earnings Management? Bentley University. Available online: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1420182 (accessed on 22 August 2021).
  36. Lari Dashtbayaz, Mahmoud, Mahdi Salehi, Alieyh Mirzaei, and Hamideh Nazaridavaji. 2020. The impact of corporate governance on intellectual capitals efficiency in Iran. International Journal of Islamic and Middle Eastern Finance and Management 13: 749–66. [Google Scholar] [CrossRef]
  37. Lawrence, Alstair. 2013. Individual investors and financial disclosure. Journal of Accounting and Economics 56: 130–47. [Google Scholar] [CrossRef] [Green Version]
  38. Levy, Marc, and Ariane Szafarz. 2016. Cross-Ownership: A Device for Management Entrenchment? Review of Finance 21: 1–25. [Google Scholar] [CrossRef] [Green Version]
  39. Li, Feng. 2008. Annual report readability, current earnings, and persistence. Journal of Accounting and Economics 45: 221–47. [Google Scholar] [CrossRef]
  40. Li, Leon, and Chi-Shyan Kuo. 2017. CEO equity compensation and earnings management: The role of growth opportunities. Finance Research Letters 20: 289–95. [Google Scholar] [CrossRef]
  41. Lo, Kin, Felipe Ramo, and Rafael Rogo. 2017. Earnings management and annual report readability. Journal of Accounting and Economics 63: 1–25. [Google Scholar] [CrossRef] [Green Version]
  42. Lobo, Gerald J., and Jihan Zhou. 2001. Disclosure Quality and Earnings Management. Asia-Pacific Journal of Accounting and Economics 8: 1–20. [Google Scholar] [CrossRef]
  43. Martins, Henrique Castro. 2019. Investor protection, managerial entrenchment, and cash holdings: Cross-country evidence. International Finance 22: 422–38. [Google Scholar] [CrossRef]
  44. Matsunaga, Steven R., and Eric Yeung. 2008. Evidence on the Impact of a CEO’s Financial Experience on the Quality of the Firm’s Financial Reports and Disclosures. SSRN Electronic Journal. Available online: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1014097 (accessed on 22 August 2021). [CrossRef]
  45. Meo, Fabrizio D., Juan Manuel Garcia Lara, and Jordi A. Surroca. 2017. Managerial entrenchment and earnings management. Journal of Accounting and Public Policy 39: 399–414. [Google Scholar] [CrossRef] [Green Version]
  46. Mihret, Dessaleng Getie, and Aderajew Wondim Yismaw. 2007. Internal audit effectiveness: An Ethiopian public sector case study. Managerial Auditing Journal 22: 470–84. [Google Scholar] [CrossRef] [Green Version]
  47. Moardi, Mahdi, Mahdi Salehi, Simin Poursasan, and Homa Molavi. 2019. Relationship between earnings management, CEO compensation, and stock return on Tehran Stock Exchange. International Journal of Organization Theory & Behavior 23: 1–22. [Google Scholar] [CrossRef]
  48. Olsen, Kari Joseph, and James Stekelberg. 2016. CEO narcissism and corporate tax sheltering. Journal of the American Taxation Association 38: 1–22. [Google Scholar] [CrossRef]
  49. Olsen, Kari Joseph, Kelsey Kay Dworkis, and S. Mark Young. 2014. CEO narcissism and accounting: A picture of profits. Journal of Management Accounting Research 26: 243–67. [Google Scholar] [CrossRef] [Green Version]
  50. Pentland, Brian T. 1993. Getting comfortable with the numbers: Auditing and the micro-production of macro-order. Accounting, Organizations and Society 18: 605–20. [Google Scholar] [CrossRef]
  51. Regazzi, John. H. 1974. Why aren’t financial statements understood? The Journal of Accountancy. Available online: https://www.proquest.com/openview/095ab4e977ad77ce1128ed2c71bb7541/1.pdf?pq-origsite=gscholar&cbl=41064 (accessed on 22 August 2021).
  52. Salehi, Mahdi, and S. Mohhamad Moghadam. 2019. The relationship between management characteristics and firm performance. Competitiveness Review 29: 440–61. [Google Scholar] [CrossRef]
  53. Salehi, Mahdi, Mahbubeh Mahmoudabadi, Mohammed Sadagh, and Mohammad Adibian. 2018. The relationship between managerial entrenchment, earnings management and firm innovation. International Journal of Productivity and Performance Management 67: 2089–107. [Google Scholar] [CrossRef]
  54. Salehi, Mahdi, Ali Daemi, and Farzana Akbari. 2020a. The effect of managerial ability on product market competition and corporate investment decisions: Evidence from Iran. Journal of Islamic Accounting and Business Research 11: 49–69. [Google Scholar] [CrossRef]
  55. Salehi, Mahdi, Lari DashtBayaz, Somayeh Hassanpour, and Hossein Tarighi. 2020b. The effect of managerial overconfidence on the conditional conservatism and real earnings management. Journal of Islamic Accounting and Business Research 11: 708–20. [Google Scholar] [CrossRef]
  56. Salehi, Mahdi, Mahbubeh Mahmoudabadi, Mohammad Sadegh Adibian, and Hossein Rezaei Ranjbar. 2020c. The potential impact of managerial entrenchment on firms’ corporate social responsibility activities and financial performance: Evidence from Iran. International Journal of Productivity and Performance Management. ahead-of-print. Available online: https://www.emerald.com/insight/content/doi/10.1108/IJPPM-06-2019-0259/full/html (accessed on 20 June 2021). [CrossRef]
  57. Schrand, C. M., and S. L. Zechman. 2012. Executive overconfidence and the slippery slope to financial misreporting. Journal of Accounting and Economics 53: 311–29. [Google Scholar] [CrossRef] [Green Version]
  58. SEC. 2007. Speech by SEC Chairman: Closing Remarks to the Second Annual Corporate Governance Summit. Available online: https://www.sec.gov/news/speech/2007/spch032307cc.htm (accessed on 22 August 2021).
  59. Seifzadeh, Maryam, Mahmed Salehi, Bizhan Abedini, and M. H. Ranjbar. 2020. The relationship between management characteristics and financial statement readability. EuroMed Journal of Business. ahead-of-print. [Google Scholar] [CrossRef]
  60. Seifzadeh, Marym, Mehdi Salehi, M. K. Khanmohammadi, and Bizhan Abedini. 2021. The relationship between management attributes and accounting comparability. Journal of Facilities Management. ahead-of-print. [Google Scholar] [CrossRef]
  61. Smulders, Rick. 1973. Managerial Entrenchment and Capital Structure. Ph.D. thesis, Department of Finance, Tilburg, The Netherlands. [Google Scholar]
  62. Soper, Fred, and Roberth Dolphin. 1964. Readability and Annual Corporate Reports. The Accounting Review 39: 358–62. [Google Scholar]
  63. Still, Nancy D. 1972. The Readability of Chairmen’s Statements. Accounting and Business Research 3: 36–39. [Google Scholar] [CrossRef]
  64. Sultan, Mohammad. 2016. Annual Report Readability and the Audit Function. Ph.D. thesis, University of Leeds, Leeds, England. [Google Scholar]
  65. Surroca, Jordi A., Ruth Aguilera, Kurt Desender, and Joseph A. Tribó. 2020. Is managerial entrenchment always bad and corporate social responsibility always good? A cross-national examination of their combined influence on shareholder value. Strategic Management Journal 41: 891–920. [Google Scholar] [CrossRef]
  66. Tamborski, Michael, Ryan Brown, and Karolyn Chowning. 2012. Self-serving bias or simply serving the self? Evidence for a dimensional approach to narcissism. Journal of Personality and Individual Differences 52: 942–46. [Google Scholar] [CrossRef] [Green Version]
  67. Tan, Hun-Tong, Elaine Ying Wang, and Bo Zhou. 2015. How Does Readability Influence Investors’ Judgments? Consistency of Benchmark Performance Matters. American Accounting Association 90: 371–93. [Google Scholar] [CrossRef] [Green Version]
  68. Wallace, Harry, and Roy Baumeister. 2002. The performance of narcissists rises and falls with perceived opportunity for glory. Journal of Personality and Social Psychology 82: 819–34. [Google Scholar] [CrossRef]
  69. Wong, Elaine, Margaret Ormiston, and Michael Haselhuhn. 2011. A face only an investor could love, CEOs’ facial structure predicts their firms’ financial performance. Psychological Science 22: 1478–83. [Google Scholar] [CrossRef]
  70. You, Haifeng, and Xio You Zhang. 2009. Financial reporting complexity and investor underreaction to 10-K information. Review of Accounting Studies 14: 559–86. [Google Scholar] [CrossRef]
  71. Zang, Amy Y. 2012. Evidence on The Trade-off between Real Activities Manipulation and Accrual-Based Earnings Management. The Accounting Review 87: 675–703. [Google Scholar] [CrossRef]
  72. Zhang, Yan, and Margarethe Wiersema. 2009. Stock market reaction to CEO certification: The signaling role of CEO background. Strategic Management Journal 30: 693–710. [Google Scholar] [CrossRef] [Green Version]
  73. Zhou, Yi. 2017. Narcissism and the art market performance. European Journal of Finance 23: 1197–218. [Google Scholar] [CrossRef]
  74. Zimon, Grzegorz, and Halina Chlodnicka. 2019. Innovation in Financial Reporting: The Aspect of the Capital Group. Marketing and Management of Innovations 2: 33–41. [Google Scholar] [CrossRef]
Table 1. The number of firms in the statistical population.
Table 1. The number of firms in the statistical population.
DescriptionEliminated Firms in Total PeriodsTotal No. of Firms
Total listed firms on the Tehran Stock Exchange 395
Eliminating financial intermediaries, financial supply, insurance, and investment firms88
Eliminating firms entered the Stock Exchange during the study period24
Eliminating due to lack of access to information 133
Statistical population 150
Table 2. Descriptive statistics.
Table 2. Descriptive statistics.
VariableOBSMeanStd.devMinMax
Fog100421.7480.23420.19623.801
Textindex10047.1550.3046.4218.268
Flashindex100499.81618.43254.921177.105
Me100417.0166.4490.11128.229
Over con10040.50.501
Ceonar10040.0110.02200.364
Rem1004−2.54 0.178−0.8370.691
Aem10040.0660.05500.378
Bef100414.7435.592160
Age100438.89613.1231067
Roa10040.1040.161−0.7890.9
Lev10040.6230.2590.1052.626
Grw10040.2310.45−0.7393.579
Size100414.2351.44710.53219.773
Own10040.510.2090.0210.994
Iinv10040.5940.32300.994
Intang10040.0050.00700.057
Seg100414.2353.414732
Busy10040.7260.44501
Current10041.3990.7260.1647.405
Rest10040.730.44301
Loss10040.1390.34601
mtb10044.4057.514−59.59453.464
Table 3. The collinearity model.
Table 3. The collinearity model.
Model (1)
VariableVIF1/VIF
Roa2.250.445
Lev2.230.447
Current1.810.551
Loss1.630.615
Iinv1.590.629
Own1.380.723
Size1.380.725
Seg1.330.751
Bef1.220.820
Age1.120.896
Busy1.110.901
Aem1.090.918
Intang1.070.930
Rest1.070.931
Grw1.070.935
Ceonar1.060.940
Overcon1.060.946
Mtb1.050.950
Me1.050.951
rem1.030.974
Mean VIF1.33
Table 5. FOG model estimation.
Table 5. FOG model estimation.
Variable
(FOG)
coefStd. Err.zProb.
ME−0.0160.004−4.180.000
Overcon0.1140.0562.040.042
Ceo_nar0.0420.0094.380.000
REM−0.0960.148−3.720.000
AEM−0.2170.109−1.980.048
BEF0.0030.0022.020.043
Age0.0380.0172.180.029
ROA0.0930.0293.200.002
LEV−0.0080.004−1.770.076
GRW0.0730.0441.660.098
Size0.0050.0080.710.481
OWN−0.0140.005−2.800.005
IINVE−0.0490.021−2.350.019
Intange0.0950.0491.920.056
SEG−0.0030.003−1.000.316
Busy−0.0700.026−2.640.008
current−0.0380.019−1.900.0057
REST0.1440.0552.610.010
Loss0.0980.0323.060.002
MTB0.0010.0011.650.099
_Con21.8190.119182.070.000
R-SQ0.8568
R-SQ20.3107
F-LimerF(149,834) = 2.81
Prob. > F = 0.000
Hausman Chi2(20) = 33.54
Prob. > chi2 = 0.0294
Prob. ModelWald chi2(20) = 38.28
Prob. > chi2 = 0.0082
Table 6. Indext model estimation.
Table 6. Indext model estimation.
Variable
(Indext)
coefStd. Err.zProb.
ME−0.0190.007−2.700.007
Overcon−0.0460.021−2.250.024
Ceo_nar0.1060.0283.760.000
REM−0.0860.044−1.970.049
AEM−0.0420.012−3.360.001
BEF0.0230.0082.740.006
Age0.0580.0232.490.013
ROA−0.0030.013−1.920.054
LEV0.0420.0094.380.000
GRW0.0590.0331.750.080
Size0.0310.0132.360.018
OWN−0.0920.069−1.350.178
IINVE0.0930.0293.200.002
Intange−0.0350.015−2.310.021
SEG0.0180.0044.200.000
Busy0.0340.0340.990.321
Current−0.0010.001−1.790.074
REST−0.0240.019−1.200.230
Loss−0.0130.008−1.650.098
MTB−0.0140.005−2.810.005
_Con6.4520.23028.040.000
R-SQ0.8105
R-SQ20.3359
F-LimerF(149,834) = 5.66
Prob. > F = 0.000
Hausman Chi2(20) = 21.76
Prob. > chi2 = 0.35.37
Prob. ModelWald chi2(20) = 44.32
Prob. > chi2 = 0.0014
Table 7. Flesch model estimation.
Table 7. Flesch model estimation.
Variable
(Flesch)
coefStd. Err.zProb.
ME−0.0280.004−6.970.000
Overcon−0.0190.008−2.430.016
Ceo_nar0.0940.0481.950.051
REM−0.0740.034−2.180.030
AEM−0.0280.004−6.960.000
BEF0.0240.0082.890.004
Age0.0260.0092.880.004
ROA1.5600.9091.720.086
LEV−0.0990.036−2.750.006
GRW−0.2330.061−3.820.000
Size0.1070.0156.930.000
OWN0.0130.0062.280.023
IINVE−2.6341.923−1.370.171
Intange111.87744.8542.490.013
SEG0.1830.0951.920.055
Busy3.6892.2451.640.100
current−0.3720.197−1.890.059
REST0.1650.0335.040.000
Loss0.1070.0156.930.000
MTB0.0380.0351.070.283
_Con93.5378.91410.490.000
R-SQ0.8543
R-SQ20.3779
F-LimerF(149,834) = 53.26
Prob. > F = 0.000
Hausman Chi2(19) = 6.24
Prob. > chi2 = 0.9973
Prob. ModelWald chi2(20) = 66.21
Prob. > chi2 = 0.0000
Table 8. FOG model estimation.
Table 8. FOG model estimation.
VariableFEGMMt + 1
coefProb.coefProb.coefProb.
FOG--−0.0050.041--
ME−0.0460.0240.0570.028−0.0340.001
Overcon0.1280.0010.0580.0130.0460.024
Ceo_nar0.0440.054−0.0420.0010.0370.052
REM−0.0120.015−0.0860.049−0.0030.054
AEM−0.0370.0240.0930.002−0.2140.036
BEF0.1100.0020.0040.0000.0370.088
Age0.0160.0500.0600.0980.0010.068
ROA0.0180.0000.0280.5460.0020.071
LEV−0.0750.2170.0200.057−0.0460.386
GRW0.0690.0080.0690.0080.0130.057
Size0.0130.0570.0790.1380.0030.000
OWN−0.2190.040−0.0730.018−0.0640.000
IINVE0.0780.3570.1480.022−0.1040.088
Intange0.1140.042−0.0670.0271.0680.374
SEG−0.0050.090−0.0390.057−0.0120.000
Busy−0.0210.029−0.0190.147−0.0330.000
current−0.0610.0020.1630.003−0.0140.385
REST0.0040.069−0.0010.0870.0160.017
Loss0.0020.0140.0010.1780.0390.000
MTB0.0010.2250.3440.0000.0030.000
_CON21.8500.00014.2510.0000.0250.837
R-SQ0.8325 0.7664
R-SQ20.3572 0.7396
Prob. ModelF(20,834) = 1.51 F(20,833) = 17.75
Prob. > F = 0.0704 Prob. > F = 0.0000
Table 9. Indext model estimation.
Table 9. Indext model estimation.
Variablet + 1Fixed AffectMethod ABB
coefProb.coefProb.coefProb.
Indext----0.6980.000
ME−0.0030.001−0.0110.000−0.0160.000
Overcon−0.0030.054−0.0030.000−0.0030.004
Ceo_nar0.0460.0240.0420.0290.0360.042
REM−0.0070.004−0.0610.022−0.0970.043
AEM−0.7870.067−0.0430.054−0.0190.000
BEF0.0440.0540.0570.0280.0690.008
Age0.0290.0010.0160.0120.0150.104
ROA−0.0950.119−0.0340.001−0.0050.041
LEV0.0800.0220.0620.3420.0370.052
GRW0.0360.0760.2810.0000.0420.064
Size−0.0060.1980.2970.0000.0410.006
OWN−0.0290.360−0.1630.158−0.2020.134
IINVE0.0470.0640.0980.2800.0420.097
Intange−0.0260.047−0.0140.007−0.0050.041
SEG0.0060.0080.0150.0000.0180.000
Busy−0.0120.3720.0920.5950.0270.847
current−0.0030.000−0.0360.089−0.0510.068
REST−0.0010.084−0.0190.353−0.0020.941
Loss−0.0360.188−0.0530.097−0.0680.061
MTB−0.0010.044−0.0960.000−0.0330.002
_CON0.1910.0126.1890.0001.7590.050
R-SQ0.81050.7943-
R-SQ20.33590.2133-
Prob. ModelWald chi2(20) = 41.39F(20,834) = 2.97Wald chi2(21) = 141.62
Prob. > chi2 = 0.0033Prob. > F = 0.0000Prob. > chi2 = 0.0000
Table 10. Flesch model estimation.
Table 10. Flesch model estimation.
Variablet + 1GMMFE
coefProb.coefProb.coefProb.
Flesch --−0.0140.007--
ME−0.0270.026−0.0280.000−0.0110.000
Overcon−0.0060.0000.1610.000−0.0190.000
Ceo_nar0.1640.000−0.0150.0270.1060.000
REM−0.0960.000−0.0020.004−0.0110.000
AEM-0.0030.0040.0020.012−0.0030.000
BEF0.0020.0140.0220.0260.0230.006
Age0.0690.0080.0010.0400.0020.000
ROA−1.8300.226−1.7350.2250.0090.000
LEV−0.0010.027−0.0010.040−0.1240.000
GRW−0.0010.0000.0130.001−0.5430.279
Size0.0780.0211.3870.3650.7120.091
OWN1.0310.224−0.0010.0200.0220.000
IINVE−0.0580.0050.1200.010−1.6570.507
Intange0.0040.0000.0330.000126.9560.004
SEG0.0560.355−0.3900.5280.1900.041
Busy−0.7010.025−0.7020.0022.6650.574
current−0.0010.0000.0070.023−0.8870.121
REST0.0570.0280.0120.0970.0090.000
Loss0.2180.0000.0430.2490.0020.071
MTB0.0560.1580.9270.0000.0390.191
_CON−0.9240.6506.0330.09990.4360.000
R-SQ0.7727 0.7589
R-SQ20.3858 0.2355
Prob. ModelWald chi2(20) = 30.01 F(20,834) = 1.47
Prob. > chi2 = 0.0698 Prob. > F = 0.0823
Table 11. Summary of the results.
Table 11. Summary of the results.
HypothesisResultsDetails
H1: There is a significant relationship between real earnings management and audit report readability.ConfirmThere is a negative and significant relationship between real earnings management and audit report readability.
H2: There is a significant relationship between accrual-based earnings management and audit report readability.ConfirmThere is a negative and significant relationship between accrual-based earnings management and audit report readability.
H3: There is a significant relationship between board effort and audit report readability.ConfirmThe relationship between board effort and audit report readability is positive and significant.
H4: There is a significant relationship between management entrenchment and audit report readability.ConfirmThere is a negative and significant relationship between management entrenchment and audit report readability.
H5: There is a significant relationship between CEO narcissism and audit report readability.ConfirmThe relationship between managers’ narcissism and audit report readability is positive and significant.
H6: There is a significant relationship between managers’ overconfidence and audit report readability.ConfirmThe FOG index shows a positive and significant relationship between managers’ overconfidence and audit report readability.
The Flesch index shows a negative and significant relationship between managers’ overconfidence and audit report readability.
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Salehi, M.; Zimon, G.; Seifzadeh, M. The Effect of Management Characteristics on Audit Report Readability. Economies 2022, 10, 12. https://doi.org/10.3390/economies10010012

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Salehi M, Zimon G, Seifzadeh M. The Effect of Management Characteristics on Audit Report Readability. Economies. 2022; 10(1):12. https://doi.org/10.3390/economies10010012

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Salehi, Mahdi, Grzegorz Zimon, and Maryam Seifzadeh. 2022. "The Effect of Management Characteristics on Audit Report Readability" Economies 10, no. 1: 12. https://doi.org/10.3390/economies10010012

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