294 Finance, Accounting and Business Analysis Volume 7 Issue 2, 2025 http://faba.bg/ ISSN 2603-5324 DOI: https://doi.org/10.37075/FABA.2025.2.12 From Rules to Reason: A Cognitive Framework for Evaluating the Differential Impact of ISA Compliance on Audit Report Quality Abdelbasset Midoune1* , Khaireddine Serdani2 Department of Accounting and Finance, Illizi University Center, Illizi, Algeria 1 Department of Management Sciences, Illizi University Center, Illizi, Algeria 2 * Corresponding Author Info Articles Abstract History Article: Submitted: 24 July 2025 Revised: 17 November 2025 Accepted: 28 November 2025 Purpose: This study aims to deconstruct the concept of ISA compliance to understand why certain auditing standards have a more significant impact on audit report quality than others. It introduces and empirically tests a novel cognitive framework that distinguishes between standards based on the intellectual task they impose on auditors. Design/Methodology/Approach: The study employs a quantitative, cross-sectional survey design. Data was collected from a sample of 398 external auditors in Algeria, a jurisdiction that has adopted the ISAs. The framework reclassifies core evidence-gathering standards into ‘Verificational Evidence Standards’ (X1) and ‘Evaluative Evidence Standards’ (X2). The relationships were tested using Pearson correlation and multiple linear regression. Findings: The results show that while both dimensions are significant predictors of audit report quality (explaining 29.9% of its variance), compliance with Evaluative Evidence Standards (β = 0.395, p < 0.001) has a substantially stronger impact than compliance with Verificational Evidence Standards (β = 0.213, p < 0.001). Practical Implications: The findings suggest that audit firms, educators, and regulators should shift their focus from ensuring rote compliance to strategically cultivating the sophisticated evaluative competencies demanded by standards like ISA 540 and ISA 520. This implies a need for changes in training, performance incentives, and quality control reviews. Originality/Value: This study is one of the first to move beyond administrative or monolithic views of ISA compliance by providing a theoretically grounded and empirically tested cognitive framework. It offers a new, more insightful lens for understanding the drivers of audit quality, with relevance for the global auditing profession. Keywords: Audit Report Quality, Audit Evidence, Professional Judgment, Verificational Evidence, Evaluative Evidence JEL: M42 Address Correspondence: E-mail : abdelbasset.midoune@cuillizi.dz 1 kh.serdani@cuillizi.dz 2 http://faba.bg/ https://doi.org/10.37075/FABA.2025.2.12 https://orcid.org/0000-0002-2510-9905 https://orcid.org/0009-0008-0945-9332 A. Midoune and K. Serdani/ Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025 295 INTRODUCTION In the architecture of modern capital markets, the external auditor serves as a crucial pillar of trust. By providing an independent opinion on the fairness of financial statements, auditors mitigate information asymmetry between corporate management and external stakeholders, a central theme in auditing research since the seminal work of DeAngelo (1981). The quality of the audit report is the tangible output of a complex process involving professional judgment and the critical evaluation of evidence (Bonner 2008). Consequently, understanding the determinants of audit report quality is not merely an academic exercise but a matter of profound importance for economic stability and corporate governance. To ensure consistency and a high baseline of quality across global engagements, the International Auditing and Assurance Standards Board (IAASB) promulgates the International Standards on Auditing (ISAs). While the link between ISA compliance and enhanced audit quality is a foundational assumption in the profession (Francis 2011), the mechanisms of this relationship remain underexplored. Research often treats compliance as a monolithic concept, implicitly suggesting that adherence to a standard on procedural sampling carries the same weight as a standard governing the complex evaluation of accounting estimates. This approach overlooks a fundamental duality within the standards themselves: the distinction between tasks that require adherence to rules and those that demand sophisticated professional reason. This leaves a critical question unanswered: are all standards created equal in their contribution to audit quality? This paper moves beyond the monolithic view of compliance. We argue that the journey to achieving the auditor's overall objectives—obtaining reasonable assurance (ISA 200)—is not uniform but is shaped by the cognitive nature of the standards applied. To operationalize this argument, this study introduces and empirically tests a novel Cognitive Framework that deconstructs ISA compliance into two distinct dimensions: 'Verificational' tasks, which emphasize procedural accuracy and factual confirmation, and 'Evaluative' tasks, which demand deep judgment and skeptical reasoning. By connecting this framework to the perceived quality of the audit report, we aim to demonstrate that while both dimensions are necessary, it is the mastery of evaluative reasoning that ultimately forges the most credible and reliable audit outcomes. LITERATURE REVIEW The Multifaceted Nature of Audit Quality Audit quality is a complex construct, often defined as the joint probability that an auditor will both discover and report a material misstatement DeAngelo (1981). More recent frameworks, such as the IAASB's Framework for Audit Quality (2014), describe it as a result of interactions between various elements, including the inputs, processes, and outputs of the audit. For the purpose of this study, we focus on the perceived quality of the audit report from the perspective of practitioners, as it represents the ultimate communication of the audit process's value to stakeholders and the tangible outcome of the overall audit engagement. Existing Perspectives on ISA Compliance and Audit Quality A comprehensive review of the extant literature reveals three primary, yet largely disconnected, research streams. First, the "Monolithic View" treats the ISA framework as a single, undifferentiated intervention. Studies in this stream often examine the macro-level impact of adopting international standards. For example, a major cross-country study by Francis, Michas, and Seavey (2013) examined the economic consequences of globalized auditing standards across 42 countries. They found that while the standards aim to create a uniform high-quality environment, their effectiveness is highly dependent on a country's institutional features, such as legal enforcement and investor protection regimes. While crucial for confirming the overall value of standardization, this approach inherently treats the entire set of ISAs as a "black box," assuming, implicitly, that compliance with a standard on audit sampling has the same quality implication as compliance with a standard on auditing complex estimates, an assumption we challenge. Attempting to open this "black box," a second stream of research can be termed the "Administrative Classification View". This line of inquiry categorizes standards based on their function or application area. Research has often focused on specific procedures or components of the audit report. For instance, the introduction of Key Audit Matters (KAMs) or Critical Audit Matters (CAMs) has spurred a wave of research. Christensen, Glover, and Wolfe (2014) investigated the impact of communicating CAMs on investor decisions, finding that they can influence nonprofessional investors' judgments. Other studies have examined the impact of standards related to fraud detection (ISA 240), going concern assessments (ISA 570), or communication with those charged with governance (ISA 260). This line of research highlights that the structure and content of audit tasks matter. However, its classification remains procedural and A. Midoune and K. Serdani/ Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025 296 administrative. It tells us what auditors do (e.g., assess going concern) but fails to provide a deep theoretical reason for why certain tasks might be more critical than others from a fundamental cognitive standpoint. Third, the "Auditor Cognition View" operates in a parallel stream, focusing on the auditor's internal traits, skills, and mental processes. This rich body of literature has robustly demonstrated that cognitive skills are fundamental to audit quality. In a comprehensive review, Nelson (2009) synthesized the literature on professional skepticism, establishing it as a critical and enduring component of audit quality. More recently, Griffith, Hammersley, Kadous, and Young (2015) demonstrated that auditor mindsets—specifically, having a more deliberative rather than implemental mindset—are a key determinant of the quality of auditing complex estimates. This research often draws on psychological theories, such as dual-process theory, which distinguishes between intuitive, automatic "System 1" thinking and deliberate, analytical "System 2" thinking. However, this research stream often treats these cognitive skills as independent variables without systematically linking them back to the specific standards that are designed to guide, structure, and arguably develop these very skills in practice. The Research Gap and a New Cognitive Framework The critical research gap emerges at the intersection of these three streams. The literature lacks a unifying framework that classifies ISAs based on the fundamental cognitive demands they place on the auditor. To address this gap, this study proposes a new Cognitive Framework for Audit Evidence, which is theoretically grounded in dual-process theory. We reclassify core evidence-gathering standards not by what they apply to (e.g., inventory, estimates), but by the type of thinking they require. This moves beyond a purely procedural classification to a more profound, cognitive one. Our framework has two core dimensions:  Verificational Evidence Standards (X1): This dimension includes standards whose primary purpose is to guide the auditor in confirming objective, verifiable facts. The cognitive task is one of matching, tracing, and confirming within a "closed system." These tasks primarily trigger System 1 (fast, intuitive) or highly structured System 2 (rule-based, procedural) thinking. We place standards such as ISA 501 (regarding physical inventory counts) and ISA 530 (Audit Sampling) as archetypes for this category.  Evaluative Evidence Standards (X2): This dimension includes standards that require the auditor to engage in complex professional judgment, assess reasonableness, and navigate high levels of uncertainty. The cognitive task is one of reasoning, analyzing relationships, and critiquing assumptions within an "open system." These tasks demand the deep, deliberate engagement of System 2 thinking. We place standards such as ISA 540 (Auditing Accounting Estimates) and ISA 520 (Analytical Procedures) as archetypes for this category. While the survey uses these standards as clear archetypes, the framework is broadly applicable. For instance, ISA 330 (The Auditor's Responses to Assessed Risks), which requires designing audit procedures based on risk assessment, would be predominantly Evaluative. Conversely, ISA 320 (Materiality) presents a hybrid nature: the initial calculation is largely Verificational, whereas its adjustment during the audit is highly Evaluative. This classification is based on the dominant cognitive demand of the standard, recognizing that some standards may contain elements of both. Hypothesis Development Based on this new framework, we can formulate a more sophisticated set of hypotheses. A quality audit requires both factual accuracy and sound judgment; therefore, we expect both types of evidence standards to be important.  H1: Compliance with Verificational Evidence Standards (X1) has a significant positive impact on audit report quality (Y).  H2: Compliance with Evaluative Evidence Standards (X2) has a significant positive impact on audit report quality (Y). However, our core thesis is that the value-add of the modern auditor lies increasingly in their ability to handle judgment and uncertainty. Evaluative tasks represent the pinnacle of professional service. Therefore, we hypothesize that the impact of evaluative standards will be substantially greater.  H3: The impact of compliance with Evaluative Evidence Standards (X2) on Audit Report Quality (Y) is significantly greater than the impact of compliance with Verificational Evidence Standards (X1). METHODS Research Philosophy and Design This study is situated within a post-positivist research paradigm, which acknowledges that while an objective reality exists, our ability to perceive it is imperfect and subject to bias. This aligns well with survey research that captures perceptions of complex social phenomena like audit quality. A. Midoune and K. Serdani/ Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025 297 A quantitative, cross-sectional survey design was deemed most appropriate for several reasons. First, it allows for the collection of data from a large and diverse sample of professionals, enhancing the generalizability of the findings. Second, it enables the statistical testing of hypothesized relationships between our defined variables (X1, X2, and Y). While a longitudinal design could track changes over time, a cross-sectional approach provides a robust snapshot of the current state of the profession, which is sufficient for testing our theoretical framework. Sample and Data Collection Procedure To test our internationally relevant framework in a practical setting, the target population for this study was defined as the 3,641 external auditors officially registered and practicing in Algeria. The sample was purposefully structured to be diverse, comprising three key groups: (1) Statutory Auditors, (2) Accounting Experts, and (3) Practicing Academics. An electronic questionnaire was distributed, and after screening, a final usable sample of 398 valid responses was obtained. The 11% response rate is modest, a common challenge in surveys of elite professionals, and the single-country focus are limitations that will be discussed further in Section 5.2. However, the final sample size provides sufficient statistical power for the analysis. The demographic profile of the sample is detailed in Table 1. Statutory auditors constitute the largest group (61.6%), complemented by accounting experts (15.1%) and practicing academics (23.4%). The high levels of experience (58.6% with over 11 years) and education lend significant credibility to the findings. This table summarizes the key characteristics of the study sample. Table 1. Demographic Profile of Respondents (N=398) Characteristic Category Frequency (n) Percentage (%) Profession Statutory Auditor 245 61.6 Accounting Expert 60 15.1 Practicing academics 93 23.4 Years of Experience < 5 Years 67 16.8 5 - 10 Years 98 24.6 11 - 15 Years 109 27.4 > 15 Years 124 31.2 Highest Education Level Bachelor's Degree 159 39.9 Master's Degree (Master & Magister) 131 32.9 PhD 97 24.4 Other 11 2.8 Source: Author's own elaboration from survey data. Measures and Instrumentation The survey instrument was developed using multi-item scales measured on a 5-point Likert scale, with items grounded in established literature to ensure content validity.  Independent Variable 1 (X1): The 5-item scale for Verificational Evidence Standards was adapted from foundational concepts in practitioner guides such as Lessambo (2018) and Flood (2023) to capture the core procedural requirements of ISA 501 and ISA 530.  Independent Variable 2 (X2): The 5-item scale for Evaluative Evidence Standards was adapted from influential frameworks on auditor judgment, drawing on seminal research by Griffith et al. (2015) and validated scales like the Hurtt (2010) skepticism scale, to measure the application of judgment required by ISA 520 and ISA 540. Dependent Variable (Y): The 16-item scale for Audit Report Quality was developed to reflect the key attributes of a high-quality audit, drawing on both the IAASB (2021) quality management framework and established academic proxies discussed in research by Francis (2011) and Knechel et al. (2013). The instrument's overall internal consistency was high (Cronbach's alpha of 0.864). The full survey instrument is provided in Appendix A to ensure transparency and facilitate replicability. Analytical Strategy The collected data were analyzed using SPSS Version 28. The analysis proceeded in three stages: Descriptive Analysis, Bivariate Correlation Analysis using Pearson's correlation coefficient, and Multiple Linear Regression. The model is specified as: Y = β₀ + β₁(X1) + β₂(X2) + ε (1) A. Midoune and K. Serdani/ Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025 298 Where Y is Perceived Audit Report Quality, X1 is Verificational Compliance, X2 is Evaluative Compliance, and ε is the error term. RESULT AND DISCUSSION Result This section presents and discusses the results of the data analysis. Descriptive statistics for the key variables are presented in Table 2. All three constructs scored high means (all > 4.0 on a 5-point scale), suggesting strong agreement among respondents regarding the importance of these dimensions for audit quality. The standard deviations are relatively small, indicating a strong degree of consensus. Table 2. Descriptive Statistics Variable N Mean Std. Deviation Verificational Compliance (X1) 398 4.0985 0.46732 Evaluative Compliance (X2) 398 4.1181 0.46718 Audit Report Quality (Y) 398 4.2282 0.40408 Source: Author's own elaboration from survey data. The Pearson correlation matrix is presented in Table 3. As hypothesized, both Verificational Compliance (X1) and Evaluative Compliance (X2) are positively and significantly correlated with Audit Report Quality (Y). The correlation between Evaluative Compliance and Audit Quality (r = 0.518, p < 0.01) is notably stronger than the correlation for Verificational Compliance (r = 0.441, p < 0.01), providing strong preliminary support for all three hypotheses. Table 3. Pearson Correlation Matrix Variable Verificational (X1) Evaluative (X2) Audit Report Quality (Y) 0.441** 0.518** Source: Author's own elaboration from survey data. A multiple linear regression was conducted to test the unique predictive power of each evidence dimension. The overall model was statistically significant (F (2, 395) = 84.247, p < 0.001), indicating that the framework as a whole is a strong predictor of audit report quality. The model summary in Table 4 shows an R Square value of 0.299, meaning that our two independent variables collectively explain 29.9% of the variance in perceived audit report quality. Table 4. Regression Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 0.547 0.299 0.295 0.33917 Source: Author's own elaboration from survey data. The regression coefficients are detailed in Table 5. The results provide clear support for all three hypotheses.  H1 is supported: Compliance with Verificational Evidence Standards (X1) is a significant positive predictor of audit report quality (β = 0.213, p < 0.001).  H2 is supported: Compliance with Evaluative Evidence Standards (X2) is a significant positive predictor of audit report quality (β = 0.395, p < 0.001).  H3 is supported: A comparison of the standardized beta coefficients shows that the magnitude of the impact from Evaluative Compliance (β = 0.395) is substantially larger—nearly double—that of Verificational Compliance (β = 0.213). Table 5. Regression Coefficients Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta (β) (Constant) 2.065 0.169 12.190 0.000 Verificational Compliance (X1) 0.184 0.045 0.213 4.131 0.000 Evaluative Compliance (X2) 0.342 0.045 0.395 7.661 0.000 Dependent Variable: audit report quality (Y) Source: Author's own elaboration from survey data. A. Midoune and K. Serdani/ Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025 299 Discussion This study set out to deconstruct the concept of ISA compliance, moving beyond traditional classifications to a more conceptually profound framework based on the cognitive demands of audit evidence. The empirical results provide a clear and compelling narrative: while both verificational and evaluative evidence are crucial pillars of a quality audit, compliance with standards that mandate evaluative reasoning is a significantly more powerful driver of perceived audit report quality. The central finding—that Evaluative Evidence Standards (β = 0.395) have nearly double the statistical impact of Verificational Evidence Standards (β = 0.213) — demands a deeper explanation than mere statistical significance. We argue that this differential impact stems from the fundamental nature of the cognitive tasks involved, which can be framed using dual-process theory. Verificational tasks, guided by standards like ISA 501 and 530, operate largely within a "closed system". Here, the auditor's goal is to confirm a fact against a known, objective criterion. This is a critical but essentially algorithmic process that requires diligence and precision, aligning with more structured, rule- based System 1 or procedural System 2 processing. While essential for establishing a factual baseline of reliability, the contribution of these tasks to overall quality is ultimately bounded by the facts themselves; they confirm what is, but offer little insight into what it means. In stark contrast, evaluative tasks, guided by standards like ISA 540 and 520, operate within an "open system" characterized by uncertainty and ambiguity. When an auditor assesses a complex accounting estimate, they are navigating a "zone of reasonableness" by critiquing a web of interconnected assumptions. Similarly, when investigating an anomaly identified through analytical procedures (ISA 520), the auditor is not just identifying a variance; they are forming a hypothesis about its cause. This is an act of abductive reasoning — inferring the most plausible explanation from a set of observations (Hammersley 2011). It is this deep engagement with higher-order cognitive processes, which are at the heart of professional judgment (Bonner, 2008), that elevates the quality of the audit from a technical, compliance-driven exercise to a professional service that adds true value. The greater beta coefficient for evaluative compliance is, therefore, an empirical reflection of the greater value added by these complex cognitive skills. It is crucial to acknowledge that this cognitive classification is not a rigid dichotomy but rather a continuum. As insightfully noted during the review process, certain standards possess elements of both categories. For example, while ISA 501 is predominantly verificational, its guidance on litigation and claims requires significant evaluative judgment. Our framework, therefore, classifies standards based on their dominant cognitive demand — the primary intellectual challenge they pose to the auditor. The nearly doubled statistical impact of Evaluative Standards suggests that while both System 1 (verificational) and System 2 (evaluative) processes are essential, it is the mastery of the deliberate, analytical System 2 thinking that truly differentiates a high-quality audit in complex situations. The primary theoretical contribution of this study lies in its ability to synthesize the three previously disconnected streams of literature. First, we provide a causal mechanism for the findings of the "Administrative View," showing that it is the evaluative nature of the procedure, not just its classification, that matters. Second, we provide a practical context for the "Auditor Cognition View." The literature on professional skepticism and judgment has long established their importance (Nelson 2009). Our study demonstrates that ISAs are not merely a compliance burden but are the very scaffolding that prompts their application. ISA 540, for example, can be seen as a "cognitive checklist" that forces the auditor to engage in specific acts of skepticism (Hurtt 2010). Finally, by bridging these views, we challenge the "Monolithic View." Our findings extend the work of researchers like Francis et al. (2013) by deconstructing which standards matter most. This implies that regulators should adopt a more targeted approach, recognizing that strengthening standards related to evaluation will likely yield the greatest returns in overall audit quality (Knechel et al. 2013). The practical implications of these findings are significant. The results strongly advocate for a move from technical training to a "cognitive apprenticeship." Audit firms must evolve their programs from focusing on rule-application to fostering evaluative reasoning. The complexity of modern standards (Flood 2023) necessitates a move beyond simple compliance to deep understanding, aligning with foundational research on expertise by Libby and Luft (1993). As Big Data and AI (Brown-Liburd and Vasarhelyi 2015) automate many verificational tasks, the human auditor's value will increasingly reside in their evaluative capabilities, making the high-level judgments that remain beyond the scope of current technology (Nwadialor and Obi 2020). CONCLUSION, LIMITATIONS, AND FUTURE RESEARCH Conclusion The journey from compliance to quality is a journey from rules to reason. This study, by filling a critical gap in the literature, demonstrates that the apex of audit quality is reached not through the meticulous A. Midoune and K. Serdani/ Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025 300 verification of established facts, but through the rigorous and skeptical evaluation of inherent uncertainties. Our cognitive framework provides a new, more insightful lens for the profession, showing that the standards that challenge auditors to think critically are the same standards that forge the most credible and reliable reports. The empirical evidence is clear: while both verificational and evaluative tasks are significant pillars of a quality audit, the latter carries nearly double the weight in determining the final quality of the audit report. This finding is not merely academic; it is a strategic imperative for a profession at a crossroads. To thrive in an era of increasing complexity and automation, the focus of training, methodology, and culture must shift decisively towards cultivating the sophisticated evaluative skills that represent the true art and science of auditing. The future-proof auditor is not one who can follow a checklist better, but one who can think better when there is no checklist to follow. Limitations and Future Research The findings of this study should be interpreted in light of several limitations which provide avenues for future research:  Generalizability and Sample Limitations: The data was collected from a single country (Algeria), which may limit the generalizability of the findings to different institutional and cultural contexts. Furthermore, the 11% response rate, while not atypical for surveys of senior professionals, raises the possibility of non-response bias, where the views of respondents may differ systematically from those of non-respondents. Future research should replicate this study in different jurisdictions (e.g., developed vs. developing markets) to test the framework's external validity.  Perceptual Data: The study relies on self-reported perceptions of compliance and quality, which may not perfectly align with actual audit practices. Future research could triangulate these findings using archival data, such as analyzing regulatory inspection reports (e.g., from the PCAOB or FRC) to code deficiencies based on whether they relate to verificational or evaluative tasks and linking them to audit outcomes like audit failures or financial restatements.  Cross-Sectional Design: The cross-sectional design establishes strong association but not definitive causality. An experimental design using vignettes, where auditors are presented with either a factual error or a questionable judgment, could provide stronger causal evidence. REFERENCE Bonner, S. 2008. Judgment and Decision Making in Accounting .illustrated ed. Pearson/Prentice Hall. Brown-Liburd, H., and M. A. Vasarhelyi. 2015. Big Data and Audit Evidence. Journal of Emerging Technologies in Accounting, 12(1):1-16. https://doi.org/10.2308/jeta-10468 Christensen, B. E., S. M. Glover, and C. J. Wolfe. 2014. Do Critical Audit Matter Paragraphs in the Audit Report Change Nonprofessional Investors' Decision to Invest? AUDITING: A Journal of Practice & Theory, 33(4): 71-93. https://doi.org/10.2308/ajpt-50793 DeAngelo, L. 1981. Auditor size and quality. Journal of Accounting and Economics, 3(3): 183-199. Retrieved from https://doi.org/10.1016/0165-4101(81)90002-1 Lessambo, F. I. 2018. Auditing, Assurance Services, and Forensics. Palgrave Macmillan. https://doi.org/https://doi.org/10.1007/978-3-319-90521-1 Flood, J. 2023. Practitioner's Guide to GAAS 2023: CoveringAll SASs, SSAEs, SSARSs, and Interpretations 2nd ed. Wiley. https://doi.org/10.1002/9781394152735 Francis, J. 2011. A Framework for Understanding and Researching Audit Quality. AUDITING: A Journal of Practice & Theory, 30(2): 125-152. https://doi.org/10.2308/ajpt-50006 Francis, J., P. Michas, and S. Seavey. 2013. Does Audit Market Concentration Harm the Quality of Audited Earnings? Evidence from Audit Markets in 42 Countries. Contemporary Accounting Research, 30(1): 325-355. https://doi.org/10.1111/j.1911-3846.2012.01156.x Griffith, E., J. Hammersley, K. Kadous, and D. Young. 2015. Auditor Mindsets and Audits of Complex Estimates. Journal of Accounting Research, 53(1): 49-77. https://doi.org/10.1111/1475-679X.12066 Hammersley, J. 2011. A Review and Model of Auditor Judgments in Fraud-Related Planning Tasks. AUDITING: A Journal of Practice & Theory, 30(4): 101–128. https://doi.org/10.2308/ajpt-10145 Hurtt, R. 2010. Development of a Scale to Measure Professional Skepticism. AUDITING: A Journal of Practice & Theory, 29(1): 149–171. https://doi.org/10.2308/aud.2010.29.1.149 IAASB. 2021. Handbook of International Quality Management, Auditing, Review, Other Assurance, and Related Services Pronouncements. IFAC. Retrieved from https://www.iaasb.org/publications/2021- A. Midoune and K. Serdani/ Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025 301 handbook-international-quality-control-auditing-review-other-assurance-and-related-services Knechel, W., G. Krishnan, M. P-evzner, L. Bhaskar, and U. Velury. 2013. Audit Quality: Insights from the Academic Literature. Auditing: A Journal of Practice & Theory, 32(1): 1-68. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2040754# Libby, R., and J. Luft. 1993. Determinants of judgment performance in accounting settings: Ability, knowledge, motivation, and environment. Accounting, Organizations and Society, 18(5): 425-450. https://doi.org/10.1016/0361-3682(93)90040-D Nelson, M. 2009. A Model and Literature Review of Professional Skepticism in Auditing. AUDITING: A Journal of Practice & Theory, 28(2): 1-34. https://doi.org/10.2308/aud.2009.28.2.1 Nwadialor, E., and T. Obi. 2020. Effect of big data on the quality of audit reports in Anambra. International Journal of Advanced Academic Research (Social and Management Sciences), 6(10): 48-65. https://doi.org/10.46654/ij.24889849.s6107 A. Midoune and K. Serdani/ Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025 302 Appendix A: Full Research Questionnaire Introduction Greetings, We invite you to participate in an academic study aiming to understand the differential impacts of compliance with International Standards on Auditing (ISAs) on audit report quality. This survey will take approximately 10-12 minutes to complete. Your participation is entirely voluntary, and all collected data will be treated with strict confidentiality and used only for aggregated academic research purposes. We highly appreciate your time and valuable contribution. Part 1: Demographic Information 1. Current Profession: ( ) Statutory Auditor ( ) Accounting Expert ( ) Practicing Academic 2. Years of professional experience in audit and assurance: ( ) Less than 5 years ( ) 5 to 10 years ( ) 11 to 15 years ( ) More than 15 years 3. Highest educational qualification obtained: ( ) Bachelor's Degree ( ) Master's Degree ( ) PhD ( ) Other (Please specify): __________ Part 2: Independent Study Constructs To what extent do you agree that the following practices are essential for achieving a high-quality audit? (1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree) Statement 1 2 3 4 5 A. Verificational Evidence Standards (X1) 1. Attending the physical inventory count to inspect inventory and perform test counts. 2. Designing and selecting an audit sample in a way that provides a representative basis for drawing conclusions about the entire population. 3. Performing audit procedures on each item selected for the sample to gather appropriate evidence. 4. Obtaining evidence regarding litigation and claims by communicating directly with the entity's external legal counsel. 5. Projecting misstatements found in an audit sample to the entire population to evaluate their overall effect. B. Evaluative Evidence Standards (X2) 1. Assessing the reasonableness of significant and complex accounting estimates made by management. 2. Critically evaluating the underlying assumptions and models used by management in fair value measurements. 3. Investigating the root causes of significant or unexpected relationships and variances identified through analytical procedures. 4. Evaluating the adequacy and clarity of financial statement disclosures for complex transactions and areas of uncertainty. 5. Challenging management’s judgments and assessing the potential for management bias when evaluating their intent and future plans. A. Midoune and K. Serdani/ Finance, Accounting and Business Analysis, Volume 7, Issue 2, 2025 303 Part 3: Dependent Variable - Audit Report Quality To what extent do you agree that the following attributes are essential characteristics of a high- quality audit report? (1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree) Attribute of Audit Report Quality 1 2 3 4 5 Dimension 1: Credibility and Reliability 1. The auditor's opinion is stated in a clear, unambiguous, and conclusive manner. 2. The report provides a credible and well-supported basis for its conclusions, reflecting that sufficient and appropriate audit evidence was obtained. 3. The "Basis for Opinion" section explicitly states adherence to International Standards on Auditing (ISAs). 4. The report clearly affirms the auditor’s independence from the audited entity. 5. The reasoning presented throughout the report is logical and internally consistent. 6. The report provides a high level of assurance to users about the fairness of the financial statements. Dimension 2: Informative Value and Transparency 7. The report is written in clear, concise language, avoiding excessive technical jargon. 8. The discussion of Key Audit Matters (KAMs) is specific to the entity, not boilerplate. 9. The KAMs section clearly links the identified risk to the specific audit response. 10. The report effectively distinguishes between the responsibilities of management and the auditor. 11. If applicable, any material uncertainty related to going concern is explained with sufficient clarity. 12. The report provides valuable context about the entity's industry or specific circumstances that influenced the audit. Dimension 3: Professionalism and Quality Indicators 13. The tone and content of the report reflect a professionally skeptical mindset. 14. The report is presented with an objective and neutral tone, free from any apparent management influence. 15. The content of the report reflects a deep understanding of the entity's business model and its specific risks. 16. Emphasis of Matter or Other Matter paragraphs are used appropriately to highlight crucial information without modifying the opinion.