سنجش کارایی موسسات حسابرسی با استفاده از تحلیل پوششی داده ها

شعبان, رضوان; بنی مهد, بهمن; حسین زاده لطفی, فرهاد; نیکومرام, هاشم

doi:10.22105/dmor.2020.236384.1160

نوع مقاله : مقاله پژوهشی

نویسندگان

¹ دانشجوی دکتری حسابداری، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.

² گروه حسابداری، واحد کرج ، دانشگاه آزاد اسلامی، کرج، ایران.

³ گروه ریاضی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.

⁴ گروه حسابداری، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران ، ایران.

https://doi.org/10.22105/dmor.2020.236384.1160

چکیده

امروزه تحلیل پوششی داده‌ها تکنیکی مناسب و سودمند برای سنجش و ارزیابی کارایی واحدهای تصمیم‌گیرنده می‌باشد. این تکنیک در ارزیابی کارایی واحدها در حسابرسی نیز ابزاری کارامد محسوب می‌شود. از این‌رو، هدف این مقاله آن است تا با به‌کارگیری تحلیل پوششی داده‌ها، کارایی موسسات حسابرسی را از نظر کیفیت حسابرسی مورد بررسی قرار دهد. مبانی نظری و داده‌های پژوهش حاضر براساس مطالعات کتابخانه‌ای از صنعت داروسازی شرکت‌های فعال در بورس اوراق بهادار تهران جمع‌آوری شده است. در این پژوهش، متغیر خروجی کیفیت حسابرسی و متغیرهای ورودی شامل تعداد شرکای موسسات حسابرسی، حق‌الزحمه حسابرسی و نفر ساعات کار حسابرسی در هر شرکت می‌باشد. نتایج با استفاده از روش کارایی متقاطع تحلیل پوششی داده‌ها، نشان می‌دهد موسسات حسابرسی بهمند، آزموده کاران و آروین ارقام پارس رتبه‌های اول تا سوم را از لحاظ کارایی برخوردار هستند. شواهد این پژوهش تایید می‌نمایند که تحلیل پوششی داده‌ها می‌تواند به‌عنوان روشی مناسب برای تجزیه‌و‌تحلیل کارایی موسسات حسابرسی در سیاست‌گذاری‌های بازار سرمایه به‌منظور ارزیابی کیفیت کار حسابرسان در راستای حمایت از سرمایه‌گذاران توسط تحلیل‌گران مالی و سیاست‌گذاران بازار سرمایه قرار گیرد.

کلیدواژه‌ها

موضوعات

تحلیل پوششی داده ها

عنوان مقاله [English]

Evaluate the efficiency of audit firms using data envelopment analysis

نویسندگان [English]

Rezvan Shaban ¹
Bahman Banimahd ²
Farhad Hosseinzadeh Lotfi ³
Hashem Nikoumaram ⁴

¹ Phd Student of Accounting, Science and Research Branch, Islamic Azad University, Tehran, Iran.

² Department Accounting, Karaj Branch, Islamic Azad University, Karaj, Iran.

³ Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran.

⁴ Department of Accounting, Science and Research Branch, Islamic Azad University, Tehran, Iran.

چکیده [English]

Data envelopment analysis is a suitable and useful technique for measuring and evaluating the efficiency of decision-making units. This technique is also an effective tool in evaluating the efficiency of units in auditing. Therefore, the purpose of this paper is to evaluate the efficiency of audit firms in terms of audit quality by using data envelopment analysis. Theoretical foundations and data of this study are based on library studies of the pharmaceutical industry of companies listed in the Tehran Stock Exchange. In this study, the output variable is audit quality and input variables include the number of partners of auditing firms, audit fees and auditing hours. The results, using the cross-functional method of data envelopment analysis, show that Behmand, Azmoodeh Karan and Arvin Argham Pars have the first to third ranks in terms of efficiency. Evidence from this study confirms that data envelopment analysis can be used as an appropriate method for analyzing the efficiency of audit firms in in order to assess the quality of auditors' work to support investors by financial analysts and capital market policymakers.

کلیدواژه‌ها [English]

Audit firms
Data envelopment analysis
Audit quality and efficiency

مراجع

Agyeman, A. S., Gyimah, A. G., & Adu-Asare, S. (2020). Assessing the impact of operational flaws on the performance of microfinance institutions in Ghana: a case study of selected microfinance institutions. Journal of applied research on industrial engineering, 7(1), 92-108.

Banker, R. D., Chang, H., & Natarajan, R. (2005). Productivity change, technical progress, and relative efficiency change in the public accounting industry. Management science, 51(2), 291-304.

Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.

Barros, C. P., Couto, E., & Samagaio, A. (2014). Productivity analysis of UK auditing firms. Australian accounting review, 24(4), 381-393.

Chang, H., Choy, H. L., Cooper, W. W., & Ruefli, T. W. (2009b). Using Malmquist Indexes to measure changes in the productivity and efficiency of US accounting firms before and after the Sarbanes–Oxley Act. Omega, 37(5), 951-960.

Chang, H., Choy, H. L., Cooper, W. W., Parker, B. R., & Ruefli, T. W. (2009a). Measuring productivity growth, technical progress, and efficiency changes of CPA firms prior to, and following the Sarbanes–Oxley Act. Socio-economic planning sciences, 43(4), 221-228.

Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.

Cheng, T. W., Wang, K. L., & Weng, C. C. (2000). A study of technical efficiencies of CPA firms in Taiwan. Review of pacific basin financial markets and policies, 3(01), 27-44.

Cook, W. D., & Seiford, L. M. (2009). Data envelopment analysis (DEA)–Thirty years on. European journal of operational research, 192(1), 1-17.

De Martinis, M., & Houghton, K. (2019). The business risk audit approach and audit production efficiency. Abacus, 55(4), 734-782.

Doyle, J., & Green, R. (1994). Efficiency and cross-efficiency in DEA: derivations, meanings and uses. Journal of the operational research society, 45(5), 567-578.

Edalatpanah, S. A. (2020). Data envelopment analysis based on triangular neutrosophic numbers. CAAI transactions on intelligence technology, 5(2), 94-98.

Ehrgott, M. (2005). Multicriteria optimization (Vol. 491). Springer Science & Business Media.

Ghaziyani, K., Ejlaly, B., & Bagheri, S. F. (2019). Evaluation of the efficiency by DEA a case study of hospital. International journal of research in industrial engineering, 8(3), 283-293.

Gong, Y., Zhu, J., Chen, Y., & Cook, W. D. (2018). DEA as a tool for auditing: application to Chinese manufacturing industry with parallel network structures. Annals of operations research, 263(1-2), 247-269.

Jerris, S. I., & Pearson, T. A. (1997). Benchmarking CPA firms for productivity and efficiency: an update. The CPA journal, 67(3), 58.

Kaffash, S., Azizi, R., Huang, Y., & Zhu, J. (2020). A survey of data envelopment analysis applications in the insurance industry 1993–2018. European journal of operational research, 284(3), 801-813.

Kaviani, M., & Fakhr Hosseini, S. F. (2018). Application of operations research techniques in financial research. Decision and operations research, ‌3(2), 164-177. (In Persian). 10.22105/DMOR.2018.67216

Kothari, S. P., Leone, A. J., & Wasley, C. E. (2005). Performance matched discretionary accrual measures. Journal of accounting and economics, 39(1), 163-197.

Kuo, K. C., Lu, W. M., & Dinh, T. N. (2020). Firm performance and ownership structure: dynamic network data envelopment analysis approach. Managerial and decision economics, 41(4), 608-623.

Lee, C. C. (2009). Analysis of overall technical efficiency, pure technical efficiency and scale efficiency in the medium-sized audit firms. Expert systems with applications, 36(8), 11156-11171.

Lee, C. C. (2018). Efficiency evaluation of accounting firm partnerships from the perspective of operating difficulties, strategies, and practices in Mainland China. Benchmarking: an international journal, 25(8), 2968-2996.

Lee, S. Y. (2015). The impact of non-audit services on accounting firm productivity. International journal of u-and e-service, science and technology, 8(10), 41-52.

Liang, L., Wu, J., Cook, W. D., & Zhu, J. (2008). Alternative secondary goals in DEA cross-efficiency evaluation. International journal of production economics, 113(2), 1025-1030.

Mao, X., Guoxi, Z., Fallah, M., & Edalatpanah, S. A. (2020). A neutrosophic-based Approach in data envelopment analysis with undesirable outputs. Mathematical problems in engineering, 1(1), 1-8.

Matsumoto, K. I., Makridou, G., & Doumpos, M. (2020). Evaluating environmental performance using data envelopment analysis: The case of European countries. Journal of cleaner production, 272, 1-44.

Moeini, M., Karimi, B., & Khorram, E. (2015). A cross-efficiency approach for evaluating decision making units in presence of undesirable outputs. In Modelling, computation and optimization in information systems and management sciences (pp. 487-498). Springer, Cham.

Rahnamay Roodposhti, F., Imeni, M., & Sayadmanesh, Sh. (2019). Application of BSC and innovative methods developed in management accounting and strategic performance measurement decisions. Decisions and operations research, 4(3), 246-261. (In Persian). 10.22105/DMOR.2020.215116.1135

Refahi Bakhsh, S., Banimahd, B., Kheradyar, S., & Ooshaksaraei, M. (2020). The ranking of fraudulent financial reporting by using data envelopment analysis: case of pharmaceutical listed companies.Advances in mathematical finance & applications, 5(1), 69-80.

Sexton, T. R., Silkman, R. H., & Hogan, A. J. (1986). Data envelopmentanalysis: critique and extensions. In R. H. Silkman(Ed.), Measuring efficiency: an assessment of data envelopment analysis (pp. 73-105).Jossey-Bass, San Francisco.

Tavakoli, M. M., Molavi, B., & Shirouyehzad, H. (2017). Organizational performance evaluation considering human capital management approach by fuzzy-dea: a case study. International journal of research in industrial engineering, 6(1), 1-16.

Wang, W., Lu, W., Kweh, Q. L., & Cheng, I. T., (2014) Does intellectual capital matter? assessing the performance of CPA firms based on additive efficiency decomposition DEA. Knowledge-based systems, 65(3), 38–49.

Wanke, P., Barros, C., & Azad, M. A. K. (2017). Measuring efficiency drivers and productive slacks in UK auditing firms. Benchmarking: an international journal, 24(3), 806-823.

تصمیم گیری و تحقیق در عملیات

سنجش کارایی موسسات حسابرسی با استفاده از تحلیل پوششی داده ها

مراجع

مراجع

دوره 5، شماره 3
آذر 1399
صفحه 402-413

سنجش کارایی موسسات حسابرسی با استفاده از تحلیل پوششی داده ها

مراجع

مراجع

دوره 5، شماره 3آذر 1399صفحه 402-413

دوره 5، شماره 3
آذر 1399
صفحه 402-413