دانشگاه اصفهاننشریه پژوهش های حسابداری مالی2322-340518120260522Applying the Best-Worst Method in Ranking the Factors Affecting the Occurrence of Fraud in Financial Statements Based on the Fraud Hexagon Theoryبه‌کارگیری روش بهترین-بدترین در رتبه‌بندی عوامل مؤثر بر وقوع تقلب در صورت‌های مالی بر اساس نظریۀ شش‌ضلعی تقلب1443064910.22108/far.2026.148347.2209FAنوید رضانمازیاستادیار، گروه حسابداری، دانشکده اقتصاد، مدیریت و علوم اجتماعی، دانشگاه شیراز، شیراز، ایران0000-0002-4030-9585مرضیهیوسفی نژاددانشجوی دکتری، گروه حسابداری، دانشکده اقتصاد، مدیریت و علوم اجتماعی، دانشگاه شیراز، شیراز، ایرانJournal Article20260213Financial statements are the most important source of information for making appropriate economic decisions. Therefore, the presence of fraud in such reports with the intention of influencing the decision-making processes of stakeholders and inducing a favorable financial situation is considered a serious threat to the growth and prosperity of the economy. In this regard, identifying the factors affecting the occurrence of fraud in financial statements can restore stakeholders' trust in the capital market and lead to economic development and improved social welfare. The main goal of the present study is to provide empirical evidence of the effectiveness of the fraud hexagon theory in identifying fraudulent financial statements using information from 117 companies listed on the Tehran Stock Exchange during the years 2016 to 2025 using the F-Score fraud measurement model using the structural equation model and the best-worst method for weighting and ranking the elements of the fraud hexagon. The findings from the study of 37 variables in the form of six hypotheses based on the fraud hexagon theory showed that the elements of pressure, opportunity, rationalization, ability, and arrogance have a significant effect on the occurrence of fraud in financial statements, and the pressure element is considered the most important factor in the occurrence of fraud in financial statements. The results of the present study, in addition to expanding the theoretical foundations of the field of fraud, can provide useful information to investors, analysts, suppliers, and managers to make appropriate economic decisions.
<strong>Introduction</strong>
Financial statement fraud involves the intentional distortion or misclassification of items in financial statements with the intention of influencing the decision-making processes of stakeholders and inducing a favorable financial position of the company (Yahaya & Ibrahim, 2024). Therefore, it is considered a targeted manipulation to present a favorable image of the company's performance in order to achieve goals such as receiving compensation based on accounting profit, maintaining or increasing market price and minimizing tax liabilities, achieving projected figures and financing the company at the lowest cost (Bekhradinasb & Khoshdel, 2023).
The importance of identifying and preventing fraud in financial statements can be understood through its widespread consequences on the economy. According to the Association of Certified Fraud Examiners [ACFE], financial statement fraud is one of the most common and costly types of fraud (Association of Certified Fraud Examiners [ACFE], 2024) because it disrupts the fair distribution of wealth and wastes limited economic resources, weakens the reliability and quality of the financial reporting process, imposes huge financial losses on investors and creditors, destroys the value of the company, undermines trust in the business community and the accounting and auditing profession, and ultimately jeopardizes the efficiency of the capital market (Wang et al., 2023). In this regard, there is an urgent need to identify the factors affecting the occurrence of financial statement fraud, as it will increase the ability to predict, prevent, and detect financial statement fraud and provide the opportunity to reduce the heavy material and non-material costs resulting from it.
In recent years, different theories and perspectives have been presented on improving the ability of stakeholders to predict, detect, and prevent fraud in financial statements. However, with the increasing spread of fraud cases in financial statements and their combination with the issue of corporate bankruptcy, there is an urgent need to conduct more research in the field of identifying factors and methods that affect the prediction, detection, and prevention of fraud in financial statements. According to the studies conducted, no research has been conducted so far on identifying and ranking factors that affect the occurrence of fraud in financial statements using the six-sided theory of fraud using the best-worst multi-criteria decision-making method in Iran. Therefore, the present study intends to cover the gap in question as much as possible, so the research questions are empirically posed and examined as follows: 1. Does the six-sided theory of fraud have a significant relationship with the probability of fraud in financial statements? 2. Which element of the six-sided theory of fraud has a significant relationship with the likelihood of fraud in financial statements? 3. Which element of the six-sided theory of fraud has the greatest and the least impact on the occurrence of fraud in financial statements?
<strong>Methods & Materials</strong>
The present study was considered exploratory research because it identifies and prioritizes factors affecting the likelihood of fraud in financial statements. Since the results can be useful in decision-making by stakeholders, the study is classified as applied research. It is empirical and post-event research because it is based on real information from the financial statements of companies listed on the Tehran Stock Exchange. In order to develop theoretical foundations, library and archival methods have been used, and the information required for calculating variables and testing hypotheses has been collected from reports available on the Tehran Stock Exchange (CODAL) website and the new Rahavard Novin software. With the help of Excel software, variables were calculated from raw data, and then, using the structural equation model based on partial least squares in Smart PLS software, factors affecting the probability of fraud were identified. Finally, in order to rank the hexagonal elements of fraud, the multi-criteria decision-making method of the best-worst model will be used.
<strong>Findings</strong>
According to the test of research hypotheses and t-statistics and the significance level for the elements of pressure, opportunity, rationalization, and ability, it can be concluded that the first, second, third, and fourth hypotheses of the study based on the effect of the elements of pressure (rate of return on assets, rate of return on equity, asset turnover rate, sales growth, gross profit margin, and free cash flow), opportunity (independence of board members, number of audit committee members, and expertise of audit committee members), rationalization (ratio of accruals and restatement of financial statements), and ability (profit management and disclosure of the cost of doubtful receivables and contingent liabilities) on the probability of fraud in financial statements have been accepted. Since the significance level of the t-statistic of the element of arrogance (bonus paid to the manager and earnings per share) is less than 0.1, the fifth hypothesis of the study based on the effect of the element of arrogance on the probability of fraud in financial statements is confirmed at a confidence level of 90 percent. Finally, regarding the sixth hypothesis, the results show that the significance level of the t-statistic of the collusion element (market performance and audit fee) is greater than 0.05, hence, with a significance level of 0.25, it has no effect on the occurrence of fraud in financial statements.
After determining the effects of the elements of pressure, opportunity, rationalization, ability, and arrogance on the occurrence of fraud in financial statements, it is time to prioritize these elements using the best-worst method in five steps, including identifying the factors affecting the occurrence of fraud in financial statements, determining the best (most effective) and worst (least effective) factors without making any comparisons, performing pairwise comparisons of the best factor with other factors, performing pairwise comparisons of other factors with the worst factor, and finally determining the weight of the factors and using a linear model to calculate the optimization of the weight of the factors. The results of weighting and ranking the factors affecting the occurrence of fraud in financial statements showed that the pressure element with a weight of 0.59 ranked first among the most influential factors affecting the occurrence of fraud in financial statements. The opportunity and ability elements ranked second with a weight of 0.12, followed by the rationalization element with a weight of 0.10, and finally the arrogance element ranked last with a weight of 0.06. Also, the consistency rate of 0.0236 indicates that the comparisons have high consistency and stability.
<strong>Conclusion & Results</strong>
With the increasing spread of fraud cases in financial statements and its combination with the issue of corporate bankruptcy, there is an urgent need to conduct more research in the field of identifying factors and methods effective in predicting, detecting, and preventing fraud in financial statements in order to restore stakeholders' trust in capital markets. Therefore, the purpose of the present study is to provide empirical evidence of the effectiveness of the hexagonal theory of fraud in identifying fraudulent financial statements in order to provide stakeholders with solutions to identify fraudulent companies. In order to achieve this, information from 117 companies listed on the Tehran Stock Exchange between 2016 and 2025 was used with the help of the F-Score fraud model to identify and separate fraudulent from non-fraudulent companies, using the structural equation model and the best-worst method as one of the modern multi-criteria decision-making methods to weight and rank the hexagonal elements of fraud.
In order to measure the effect of the pressure element on the occurrence of fraud in financial statements, the first hypothesis was tested, and the results showed that managers unable to achieve predetermined goals, unstable companies involved in external pressures, and finally, managers with financial needs under internal and external pressures are encouraged to manipulate financial statements, which supports the hexagonal theory of fraud based on the effect of the pressure element on the occurrence of fraud in financial statements.
Accepting the second hypothesis based on the effect of the opportunity element on the occurrence of fraud in financial statements showed that by strengthening the supervisory mechanism and having a maximum number of non-executive board members, the opportunity to commit fraud can be reduced. Rationalization is a type of management self-justification in which the manager believes that he has worked more for the company than the owners, therefore encouraging the owners to take steps to maximize their personal interests (Jannah et al., 2021). This claim was proven by the results of the test of the third hypothesis based on the effect of the rationalization element on the occurrence of fraud in financial statements.
As the legal representative of shareholders, the manager has the ability not to always act in accordance with the interests of the owners and to seek to maximize his own interests. In order to prove this claim, the fourth hypothesis, that the element of ability affects the occurrence of fraud in financial statements, was tested. The results of the test proved the existence of an effect. The result of the fifth hypothesis that the element of arrogance affects the probability of fraud in financial statements is in line with the six-sided theory of fraud; because the view of superiority and entitlement encourages managers to carry out activities in order to maximize their interests and creates in them the feeling that they have power that internal controls are unable to limit and that their fraud will never be revealed or that there will be no punishment if it is revealed (Siregar, 2019). The result of the test of the sixth hypothesis indicates that the element of collusion does not affect the occurrence of fraud in financial statements.
After identifying the elements that affect the occurrence of fraud in financial statements, including pressure, opportunity, justification, ability, and arrogance, it is time to prioritize them. One of the innovative aspects of the present study is the use of the best-worst method to rank the elements affecting the occurrence of fraud in financial statements, because according to the studies conducted, most of the studies have used the hierarchical approach (AHP) to rank the factors affecting fraud in financial statements. The implementation of the best-worst method showed that among the elements affecting the occurrence of fraud in financial statements, the pressure element with a coefficient of 0.59 is the most influential element among other elements affecting the occurrence of fraud in financial statements, which is supported by the results of the study by Masoumi et al. (2020) that the pressure element is important among the elements of the fraud triangle (pressure, opportunity, and justification) and by Apriliani et al. (2024) that the pressure element is important among the elements of the fraud pentagon (pressure, opportunity, justification, ability, and arrogance). However, this result is contrary to the findings of the study by Kimasi and Soleimani-Amiri (2024), in which the pressure element has a weak effect and the opportunity element has a strong effect on the dimensions of the fraud triangle.صورت‌های مالی مهم‌ترین منبع اطلاعاتی برای اتخاذ تصمیم‌های مناسب اقتصادی به شمار می‌آیند؛ از این رو، وجود تقلب در این دست گزارش‌ها با قصد تأثیرگذاری بر فرایندهای تصمیم‌گیری ذی‌نفعان و القای وضعیت مالی مطلوب تهدیدی جدی برای رشد و شکوفایی اقتصاد به حساب می‌آید. در این راستا، شناسایی عوامل مؤثر بر وقوع تقلب در صورت‌های مالی می‌تواند اعتماد ذی‌نفعان به بازار سرمایه را بازگرداند و توسعۀ اقتصادی و بهبود رفاه اجتماعی را به دنبال داشته باشد. هدف اصلی پژوهش حاضر ارائۀ شواهد تجربی از تأثیرگذاری نظریۀ شش‌ضلعی تقلب بر شناسایی صورت‌های مالی متقلبانه به کمک اطلاعات 117 شرکت پذیرفته‌شده در بورس اوراق بهادار تهران در طول سال‌های 1394 تا 1403 به کمک مدل سنجش تقلب F-Score با بهره‌گیری از مدل معادلات ساختاری و روش بهترین-بدترین برای وزن‌دهی و رتبه‌بندی عناصر شش‌ضلعی تقلب است. یافته‌های حاصل از بررسی 37 متغیر در قالب شش فرضیه بر مبنای نظریۀ شش‌ضلعی تقلب نشان داد عناصر فشار، فرصت، منطقی‌سازی، توانایی و تکبر تأثیری معنادار بر وقوع تقلب در صورت‌های مالی دارند و عنصر فشار مهم‌ترین عامل بروز تقلب در صورت‌های مالی محسوب می‌شود. نتایج پژوهش حاضر علاوه بر گسترش مبانی نظری حوزۀ تقلب می‌تواند اطلاعاتی سودمند در اختیار سرمایه‌گذاران، تحلیلگران، تأمین‌کنندگان و مدیران برای اتخاذ تصمیم‌های مناسب اقتصادی قرار دهد.
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https://far.ui.ac.ir/article_30649_29b9b08097c2ac96d70afed2828a310f.pdfدانشگاه اصفهاننشریه پژوهش های حسابداری مالی2322-340518120260522Testing Capital Asset Pricing Models with Single Stocks: An Instrumental Variable Approachآزمون مدل‌های قیمت‌گذاری دارایی‌های سرمایه‌ای با تک‌سهام؛ رویکرد متغیرهای ابزاری45783065010.22108/far.2026.148364.2210FAمهدیخرم آبادیاستادیار، گروه حسابداری، دانشگاه پیام نور، تهران، ایرانسیده زهرامیراشرفیاستادیار، گروه حسابداری، دانشگاه پیام نور، تهران، ایرانمنامیررضائیکارشناسیارشد حسابداری، دانشگاه پیام نور، تهران، ایرانJournal Article20260214The primary objective of this study was to evaluate the explanatory power of risk-adjusted excess returns in single-stock capital asset pricing models (CAPM) using an instrumental variable approach, compared to portfolio-based factor models, with the aim of identifying the superior pricing model. The models assessed include single-factor CAPM, the three-factor and five-factor Fama-French models, the Carhart four-factor model, the Hou, Xue, and Zhang q-factor model, and the modified q-factor model by Hou et al. These models were examined under three specifications: constant beta, time-varying beta, and single-stock characteristics. Data from 196 companies listed on the Tehran Stock Exchange from 2015 to 2024 were analyzed using Ordinary Least Squares (OLS) and Generalized Method of Moments (GMM). The findings indicate significant differences in the explanatory power of risk-adjusted excess returns between multifactor models and the single-factor model, as well as between models with time-varying betas and those with constant betas. Among the six models with constant betas and no single-stock characteristics, the Fama-French five-factor model demonstrated the highest explanatory power. In contrast, the time-varying beta specification of the Hou, Xue, and Zhang q-factor model exhibited the greatest ability to explain risk-adjusted excess returns. Moreover, factor models incorporating single-stock characteristics showed significantly higher explanatory power than those without such characteristics. Additionally, models estimated via OLS provided more accurate predictions of risk-adjusted excess returns compared to those estimated using GMM. The sensitivity analysis using the GMM approach indicates that while some complex models face overfitting risks within the instrumental variables framework, the augmented q-factor model with time-varying beta and single-stock characteristics remains the superior model and demonstrates high robustness across both OLS and GMM estimation methods, thereby confirming the main findings of the study.
<strong>Introduction</strong>
This study examines the explanatory power of six prominent asset pricing models in the Tehran Stock Exchange, employing a novel single-stock instrumental variable (IV) approach to address inherent empirical limitations. Traditional linear factor models including the CAPM, Fama-French three-, four-, and five-factor models, the q-factor model, and its enhanced version (q5) are known to face significant challenges such as time-varying systematic risk and errors-in-variables (EIV) bias when estimated betas are used. These issues can distort risk-return relationships and weaken statistical inferences. To overcome these shortcomings, an IV methodology at the individual stock level is applied and contrasted with conventional portfolio-based factor models. The TSE provides a compelling setting for this investigation due to its high volatility, sensitivity to macroeconomic shocks, and evolving market structure. The primary objective is to identify the most robust model for explaining risk-adjusted excess returns in this emerging market context. The findings are expected to contribute to more accurate risk estimation, improved investment decision-making, and enhanced market efficiency. This research underscores the necessity of adapting advanced econometric techniques to address measurement errors and multicollinearity in asset pricing applications within dynamic and complex market environments like Iran's.
<strong>Methodology</strong>
This applied, descriptive, and quantitative study employs a comparative approach to test the explanatory power of asset pricing models. Data are gathered from financial statements, the Codal website, and the Rahavard Novin software. The analysis is performed using Ordinary Least Squares (OLS) and Instrumental Variable (IV) regression methods in Excel and EViews. The sample consists of 196 companies listed on the Tehran Stock Exchange, selected through systematic screening based on continuous listing from 2015 to 2024, data availability, exclusion of financial intermediaries, no trading suspension exceeding three months in any year, and consistent fiscal year-end (March 20).
<strong>Findings</strong>
The Fama-French five-factor model (2015) with constant beta and no firm-specific characteristics demonstrates the highest explanatory power and lowest forecast error among its category, confirming the first hypothesis. Among models with time-varying beta, the q-factor model (Hou et al., 2015) shows superior performance. Comparative tests confirm that time-varying beta models have significantly higher predictive accuracy than constant-beta models, supporting the second hypothesis. The inclusion of firm-specific characteristics is found to significantly enhance the predictive accuracy of both constant-beta and time-varying beta models. The strongest models within these enhanced categories are identified as the Fama-French five-factor model and the augmented q-factor model (Hou et al., 2021), respectively, confirming the third hypothesis. Regarding estimation methodology, models using Ordinary Least Squares (OLS) provide greater predictive accuracy than those using the Generalized Method of Moments (GMM), confirming the fourth hypothesis. However, sensitivity analysis using GMM (Table 12) reveals that the augmented q-factor model exhibits only borderline validity in the GMM framework (p=0.066), highlighting the importance of cautious interpretation and the need for stronger instrumental variables in future research. A final comprehensive comparison establishes the augmented q-factor model (Hou et al., 2021) with time-varying beta and firm-specific characteristics, estimated via OLS, as the overall superior model for explaining and predicting excess returns in the Tehran Stock Exchange.
<strong>Conclusion and Implications</strong>
This study demonstrates the superiority of multi-factor models over the single-factor CAPM for the Tehran Stock Exchange. Models with time-varying beta significantly outperform constant-beta specifications, and the inclusion of firm-specific characteristics further enhances explanatory power. The augmented q-factor model (Hou et al., 2021) with these dynamic and firm-level features, estimated via OLS, is identified as the most robust model. However, its borderline validity in the GMM framework highlights the need for stronger instrumental variables in future research. Therefore, investors and analysts are advised to adopt such dynamic, multi-factor frameworks that integrate both systematic and idiosyncratic risks for more accurate pricing and risk management. Future research should explore alternative instrumental variables, apply machine learning techniques, and incorporate investor sentiment factors to further refine asset pricing models in emerging market.
هدف اصلی پژوهش حاضر آزمون قدرت تبیین بازده مازاد بر ریسک مدل‌های قیمت‌گذاری دارایی‌های سرمایه‌ای با تک‌سهام با استفاده از رویکرد متغیر ابزاری در مقایسه با مدل‌های عاملی مبتنی بر پرتفوی‌های مبنا به منظور انتخاب مدل قیمت‌گذاری برتر است. مدل‌های تک‌عاملی قیمت‌گذاری دارایی‌های سرمایه‌ای، سه‌عاملی فاما و فرنچ، چهارعاملی کارهارت، پنج‌عاملی فاما و فرنچ، q عاملی هو و همکاران (2015)، q عاملی تعدیل‌شدۀ هوو و همکاران (2021)، با بتای ثابت، بتای متغیر با زمان و دارای ویژگی‌های تک‌سهام ارزیابی شدند. داده‌های 196 شرکت پذیرفته‌شده در بورس اوراق بهادار تهران طی سال‌های 1394 تا پایان 1403 با روش حداقل مربعات معمولی و روش گشتاورهای تعمیمیافته تجزیه‌وتحلیل شد. نتایج پژوهش حاکی از آن است که قدرت تبیین بازده مازاد بر ریسک بین مدل‌های چندعاملی و مدل تک‌عاملی، همچنین بین مدل‌های عاملی با بتای متغیر با زمان و مدل‌های عاملی با بتای ثابت، تفاوتی معنادار وجود دارد. مدل پنج‌عاملی فاما و فرنچ، در بین شش مدل، دارای بتای ثابت و بدون ویژگی‌های تک‌سهام، و مدل q عاملی هو و همکاران (2015) با بتای متغیر با زمان، بیشترین توانایی را در تبیین بازده مازاد بر ریسک سهام شرکت‌ها دارند. قدرت توضیحی بازده مازاد بر ریسک در مدل‌های عاملی دارای ویژگی‌های تک‌سهام و مدل‌های عاملی بدون ویژگی‌های تک‌سهام تفاوتی معنادار دارد و قدرت تببین مدل‌های عاملی دارای ویژگی‌های تک‌سهام بیشتر است. همچنین، مدل‌های برآوردشده به روش OLS دقت بیشتری در پیش‌بینی بازده مازاد بر ریسک سهام نسبت به روش گشتاورهای تعمیمیافته دارند. نتایج آزمون تحلیل حساسیت با روش GMM نیز نشان می‌دهد اگرچه در چارچوب متغیرهای ابزاری، برخی از مدل‌های پیچیده با ریسک بیش‌برازش مواجه هستند، مدل q عاملی تعدیل‌شده با بتای متغیر با زمان و ویژگی‌های تک‌سهام، به عنوان مدل برتر پژوهش، از پایداری زیادی در هر دو روش OLS و GMM برخوردار است.
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https://far.ui.ac.ir/article_30650_602f5eef80ebbbbb8a5d9ce915108010.pdfدانشگاه اصفهاننشریه پژوهش های حسابداری مالی2322-340518120260522Designing a Framework to Evaluate Researchers’ Satisfaction with Peer-Review Quality and to Propose Improvement Strategiesطراحی و اعتبارسنجی چارچوب سنجش میزان رضایت پژوهشگران از کیفیت داوری همتا و ارائۀ پیشنهادهایی برای بهبود791043072610.22108/far.2026.148337.2208FAغلامرضاکردستانیاستاد، گروه حسابداری، دانشگاه بین‌المللی امام خمینی (ره)، قزوین، ایرانحسینرجب دریپژوهشگر پسادکتری، گروه حسابداری، دانشگاه بین‌المللی امام خمینی (ره)، قزوین، ایرانJournal Article20260210Peer review plays a critical role in ensuring the quality and credibility of scientific publications. Despite its importance, researchers’ satisfaction with the peer-review process has received limited systematic attention, particularly in the fields of accounting and finance. This study aims to develop a comprehensive framework for assessing researchers’ satisfaction with peer-review quality and to propose effective strategies for improving the review process. Using an exploratory mixed-methods approach, key satisfaction constructs were identified through qualitative content analysis of prior literature and subsequently prioritized using survey data collected from 170 accounting and finance researchers. The findings highlight reviewer expertise, ethical behavior, impartiality, and timely yet accurate evaluation as the most influential factors shaping researchers’ satisfaction. The proposed framework provides journal editors with a practical tool for evaluating and enhancing peer-review quality.
<strong>Introduction</strong>
The peer-review process is widely recognized as the cornerstone of academic publishing, ensuring scientific rigor, credibility, and knowledge advancement. However, increasing concerns about review delays, reviewer bias, and inadequate subject-matter expertise have raised questions about the effectiveness of peer review and researchers’ satisfaction with this process. In accounting and finance journals, where methodological rigor and domain-specific expertise are essential, the absence of a standardized framework for evaluating researchers’ satisfaction represents a significant research gap. This study addresses this gap by developing a structured framework to assess researchers’ satisfaction with peer-review quality and by identifying practical strategies for improving the peer-review process. The study seeks to answer the following research questions: (1) What are the key constructs influencing researchers’ satisfaction with peer-review quality? and (2) Which improvement strategies are perceived as most effective by researchers?
<strong>Methods & Materials</strong>
This research adopts an exploratory mixed-methods design. In the first phase, a qualitative content analysis of domestic and international peer-review literature was conducted to extract core components and constructs related to researchers’ satisfaction. In the second phase, a structured questionnaire based on the identified constructs was developed. Data were collected from 170 researchers in the fields of accounting and finance using a purposive sampling approach. The collected data were analyzed using descriptive and prioritization techniques to rank satisfaction constructs and validate the proposed framework.
<strong>Findings</strong>
The results indicate that three primary constructs are critical determinants of researchers’ satisfaction with peer review: (1) reviewers’ scientific expertise in the manuscript’s subject area, (2) ethical conduct and impartial evaluation, and (3) timely review accompanied by sufficient accuracy and depth. Among these, reviewers’ subject-matter expertise received the highest priority. Furthermore, transparent ethical guidelines, systematic evaluation of reviewers by editors, and reviewer training programs were identified as the most effective strategies for improving peer-review quality.
<strong>Conclusion & Results</strong>
The findings suggest that enhancing researchers’ satisfaction with peer review requires a strong emphasis on reviewers’ scientific competence and professional ethics, supported by institutional and educational mechanisms. Financial incentives alone are insufficient to improve review quality. The proposed framework offers journal editors and publishers a practical instrument for assessing and improving peer-review performance. This study contributes to the accounting and finance literature by addressing a critical knowledge gap and providing actionable insights to strengthen academic publishing processes.
هدف اصلی این پژوهش طراحی و اعتبارسنجی چارچوب سنجش میزان رضایت پژوهشگران از کیفیت داوری همتا و ارائۀ راهکارهایی برای بهبود فرایند داوری در حوزۀ حسابداری و مالی است. نبود چارچوب منسجم و استاندارد برای ارزیابی رضایت پژوهشگران و تأثیر مستقیم آن بر کیفیت انتشار علمی انجام این پژوهش را ضروری کرد. روش پژوهش آمیخته و اکتشافی است. در گام نخست، تحلیل محتوای کیفی اسناد و ادبیات علمی داخلی و خارجی انجام شد تا مؤلفه‌ها و سازه‌های رضایت پژوهشگران استخراج شوند. در گام دوم، جامعۀ آماری پژوهشگران حوزۀ حسابداری و مالی با سابقۀ ارسال مقاله بودند که از میان آنها، نمونه‌ای ۱۷۰نفره با روش تصادفی ساده انتخاب شد. روایی محتوایی نیز با روش لاوشه و نظر ۹ خبره و پایایی با آلفای کرونباخ تأیید شد. همچنین، اولویت‌بندی مؤلفه‌ها با آزمون ناپارامتریک فریدمن انجام شد. یافته‌ها نشان داد تسلط علمی داوران بالاترین اولویت را دارد، رفتار اخلاقی در رتبۀ دوم و ارزیابی به‌موقع در رتبۀ سوم قرار گرفت. در میان راهکارها، تدوین دستورالعمل اخلاقی شفاف مؤثرترین راهکار شناخته شد و انگیزه‌های مالی کمترین اثر را داشت. چارچوب ارائه‌شده می‌تواند به سردبیران و مدیران نشریه‌ها ابزار عملیاتی برای سنجش و بهبود کیفیت داوری ارائه دهد. برخلاف پژوهش‌های پیشین که عمدتاً بر حوزههای غیرحسابداری متمرکز بودند، این پژوهش دیدگاه پژوهشگران را در حوزۀ حسابداری و مالی ایران مرکز تحلیل قرار داده است. این پژوهش افزون بر پرکردن شکاف دانشی در حوزۀ حسابداری، به غنی‌سازی ادبیات علمی دربارۀ رضایت پژوهشگران از داوری همتا کمک و ابزاری برای بهبود فرایندهای انتشار علمی فراهم می‌کند.
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https://far.ui.ac.ir/article_30726_3d07b2e322bc094212918b4442f2fb15.pdf