ارزیابی شرکت سهامی بیمة ایران با استفاده از نسبت‌های مالی و مدل‌سازی ریاضی

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 استاد گروه مدیریت صنعتی دانشکدة مدیریت دانشگاه تهران، تهران، ایران

2 دانشیار گروه مدیریت صنعتی دانشکدة مدیریت دانشگاه تهران، تهران، ایران

3 کارشناس ارشد مدیریت صنعتی، دانشکدة مدیریت، دانشگاه تهران، تهران، ایران

چکیده

 صنعت بیمه یکی از قوی‌ترین و مهم‌ترین نهادهای اقتصادی و پشتیبان سایر نهادهای اقتصادی و خانوارها تلقی می‌شود. صنعت بیمه با تحولاتی مواجه بوده که آن را به سوی رقابتی‌شدن پیش می‌برد. بنابراین، می‌توان گفت شرکت‌های بیمة فعال در صنعت بیمة ایران باید همواره به پایش عملکرد شعب و نمایندگی‌های خود بپردازند. از جمله مشکلات روش‌های ارزیابی سازمان‌ها، تأکید بر شاخصی اصلی، همچنین قضاوت‌های ذهنی است. لذا، در ارزیابی باید جامعیت آن در فراگیری تمام زوایای کاری لحاظ شود. همچنین، خطاهای ذهنی را باید تا حد امکان کاهش داد. در این پژوهش ارزیابی شعب شرکت سهامی بیمة ایران به وسیلة تکنیک تحلیل پوششی داده‌ها انجام شده است. در به‌کارگیری مدل‌های کلاسیک تحلیل پوششی داده‌ها معمولاً مباحث خروجی‌های نامطلوب و ورودی‌های غیراختیاری نادیده گرفته می‌شود. در این پژوهش به خروجی‌های نامطلوب و ورودی‌های غیراختیاری پرداخته شده است. نتایج این پژوهش نشان می‌دهد که با درنظرگرفتن ورودی غیراختیاری در حالت بازده به مقیاس متغیر و ثابت به ترتیب 50 و 36 درصد از شعب کاراست.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Performance assessment of branches of Iran Insurance Corporation using data envelopment analysis

نویسندگان [English]

  • Mohammad Reza Mehregan 1
  • Hossein Safari 2
  • Abdol Hossein Jafarzadeh 3
1 Prof., Faculty Management, University of Tehran, Tehran, Iran
2 Associate Prof., Faculty Management, University of Tehran, Tehran, Iran
3 MSc., Faculty Management, University of Tehran, Tehran, Iran
چکیده [English]

Insurance industry is one of the most influential economic institutions and is considered to support other economic institutions and families. Insurance industry has been facing changes that lead it to becoming a competitive industry. Therefore, we can say insurance companies that are active in Iran insurance industry must constantly monitor performance of their branches and agencies. Ongoing problems in existing assessing methods of organizations are their emphasis on a single index and subjective judgment. Therefore, the assessment should comprehensively take all aspects into account. Subjective judgment should be reduced as much as possible. Thus, in this study we evaluate the performance of Iran Stock Corporation and its branches by using data envelopment analysis (DEA) technique. Meanwhile, in the classical applications of DEA models typically problems occur such as ignoring undesirable outputs and non-discretionary inputs. Accordingly, in this study undesirable outputs and non-discretionary inputs have been investigated. The results show that 50 and 36 percent of the branches are efficient under variable and constant returns to scale respectively in the presence of non-discretionary inputs and undesirable outputs.

کلیدواژه‌ها [English]

  • Insurance
  • Efficiency
  • Data Envelopment Analysis
  • undesirable outputs and non-discretionary inputs
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.
Charnes, A., Cooper, W.W., Golany, B., Seiford, L. & Stutz, J. (1985). Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions. Journal of econometrics, 30(1), 91-107.
Charnes, A., Cooper, W.W. & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
Cooper, W.W., Park, K.S. & Pastor, J.T. (1999). RAM: a range adjusted measure of inefficiency for use with additive models, and relations to other models and measures in DEA. Journal of Productivity Analysis, 11(1), 5-42.
Cooper, W.W., Seiford, L.M. & Tone, K. (2006). Introduction to data envelopment analysis and its uses: with DEA-solver software and references. Springer Science & Business Media.
Cummins, J.D. & Rubio-Misas, M. (2006). Deregulation, Consolidation, and Efficiency: Evidence from the Spanish Insurance Industry. Journal of Money, Credit, and Banking, 38(2), 323–355.
Cummins, J.D., Turchetti, G. & Weiss, M.A. (1996). Productivity and technical efficiency in the Italian insurance industry. Working Paper 96-10, Wharton School.
Cummins, J.D. & Weiss, M.A. (2013). Analyzing firm performance in the insurance industry using frontier efficiency and productivity methods. InHandbook of insurance. Springer New York, 795-861.
Cummins, J.D., Weiss, M.A. & Zi, H. (1999). Organizational form and efficiency: The coexistence of stock and mutual property–liability insurers. Management Science, 45(9), 1254-1269.
Cummins, J.D. & Xie, X. (2013). Efficiency, productivity, and scale economies in the US property-liability insurance industry. Journal of Productivity Analysis, 39(2), 141-164.
Daneshvar, M., Azar, A.  & Zali, M.R. (2007). Designing a performance assessment model of insurance branches using DEA technique (Case study: Dana Insurance Company). Journal of Executive Management, 6(1), 37-62. (In Persian).
Deprins, D. & Simar, L., Tulkens, H. (1984). Measuring labor inefficiency in post offices. The Performance of Public Enterprises: Concepts and measurements. M. Marchand, P. Pestieau and H. Tulkens (eds.), Amsterdam, North-Holland, 243-267.
Diacon, S.R., Starkey, K. & O’Brien, C.O. (2002). Size and efficiency in European long term insurance companies: An international comparison. Geneva Papers on Risk and Insurance, 27(4), 444-466.
Ebadi J. & Bagherzadeh, H.A. (2008). Examination of Efficiency and Economies of scale in the parametric and Non-parametric approaches (case study: Iran, Asia, Alborz and Dana Insurance Companies). TAHGHIGHAT-E-EGHTESADI, 43(3), 205-229. (In Persian).
Emami Meibodi, A. (2005). Principles of efficiency and productivity measurement (scientific-practical).Tehran: The Institute for Trade Studies & Research. 2eds edition. (In Persian).
Farjadi, M. (1996). Principles and concepts of Commercial Insurance. Tehran, Alborz Insurance Company Press. (In Persian).
Fecher, F., Kessler, D., Perelman, S. & Pestieau, P. (1993). Productive performance of the French insurance industry. Journal of Productivity Analysis, 4(1-2), 77-93.
Hannah, E. & Yeung, V. (1998). Report of the task force on the future of the Canadian financial services sector. Financial Regulation Report, London.
Jafarzadeh, A.H., Safari, H. & Mehregan, M.R. (2014). Efficiency and Productivity evaluation of Iran Insurance Stock Company's branches based on Data Envelopment Analysis and Malmquist Index in the presence of Weight Restrictions. Journal of Modiriat-E-Farda, 13(4), 109-135. (In Persian).
Jafarzadeh, A.H. (2013). Evaluating and Ranking the Branches of Iran Insurance Company Based on Malmquist Index and Data Envelopment Analysis-Free Disposal Hull (DEA-FDH) In the Presence of Weight Restrictions. Tehran University. Faculty of Management. Tehran, Master Thesis. (In Persian).
Javadipour, A., Safari, H. & Arbatani, T.R. (2014). Efficiency Evaluation of the Agencies of Iran Insurance Company based on Data Envelopment Analysis Technique with Weight Restrictions (AR-DEA) and Goal Programming. Asian Journal of Research in Business Economics and Management, 4(3), 241.
Javadipour, A. (2013). Efficiency Evaluation and Ranking of the Agencies of Iran Insurance Company based on Data Envelopment Analysis Technique with Weight Restrictions (AR-DEA) and Goal Programming (GP). Tehran University. Aras International Campus. East Azerbaijan Province-Jolfa, Master Thesis. (In Persian).

Khajavi, Sh., Ghayouri Moghadam, A. & Ghafari, M.J. (2010). Data Envelopment Analysis Technique: A complementary Method for Traditional Analysis of Financial Ratios. Journal of the Accounting and Auditing Review, 17(2), 41-56. (In Persian).

Mahlberg, B. (2000). Technischer Fortschritt und Produktivitätsveränderungen in der deutschen Versicherungswirtschaft/Efficiency Progress and Productivity Change in Germany Insurance Industry. Jahrbücher für Nationalökonomie und Statistik, 565-591
Mahotra, D.K. & Malhotra, R. (2008). Analyzing Financial Statements Using Data Envelopment Analysis. Com. Lending Rev., 23, 25.
Mathur, T. & Paul, U.K. (2014). Performance Appraisal of Indian Non-Life Insurance Companies: A DEA Approach. Universal Journal of Management, 2(5), 173-185.
Mehregan, M.R. (2004). Quantitative model for organizational performance evaluation (Data Envelopment Analysis). Tehran, Faculty of Management University of Tehran Press. (In Persian).
Mirghaffari, S.H., Shafiei Roodposhti, M. & Naddafi, Gh. (2013). Financial Performance Evaluating by Grey Relational Analysis (Case Study: Province Telecommunication Companies). Financial Knowledge of Security Analysis (Financial Studies), 5(4): 61-75. (In Persian).
Nemati, M. & Kazemi. A. (2014). Ranking of insurance companies using multi attribute decision making methods. Journal of financial research, 16(1), 1163-1180. (In Persian).
Norman, M. & Stoker, B. (1991). Data envelopment analysis: the assessment of performance. John Wiley & Sons, Inc.
Pourkazemi, M.H., Samsami, H. & Ebrahimi Ghavam-Abadi, Kh. (2012). Measuring efficiency and productivity of public and private insurance companies using Data Envelopment Analysis and Malmquist index. The Quarterly Journal of Insurance Industry (SANAAT-E-BIMEH), 26(4): 1-26. (In Persian).
Safari, H. & Jafarzadeh, A.H. (2012). Performance assessment of the branches of Iran Insurance Company using data envelopment analysis (DEA). Research Project. (In Persian).
Soltanpanah, H., Moradi, F. & Bakhsha, N. (2007). Evaluation of Relative Efficiency of Alborz Insurance Branches Using Data Envelopment Analysis. The Quarterly Journal of Insurance Industry (SANAAT-E-BIMEH), 22(4), 151-177. (In Persian).
Tavakkoli-Moghaddam, R., Amal-nik, M.S. & Rafati, M.A. (2004). Methodology using data envelopment analysis (DEA) in research organization. Journal of the College of Engineering, 38(1), 175-185. (In Persian).
Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European journal of operational research, 130(3), 498-509.
Xie, X. (2010). Are publicly held firms less efficient? Evidence from the US property-liability insurance industry. Journal of Banking & Finance, 34(7), 1549-1563.
Yang, Z. (2006). A two-stage DEA model to evaluate the overall performance of Canadian life and health insurance companies. Mathematical and computer modelling, 43(7), 910-919.