Dynamic efficiency: intellectual capital in the Chinese non-life insurance firms

Purpose – This paper aims to investigate the effect of intellectual capital (IC) on the operating efficiency of non-life insurance firms in China. Design/methodology/approach – The authors use a dynamic data envelopment analysis model called dynamic slacks-based measure (DSBM) model to estimate the operating efficiency of 32 Chinese non-life insurance firms. Using a panel data set for the period from 2006 to 2010, the authors run ordinary least squares (OLS) regressions to find the relationship between IC and efficiency performance. Findings – The authors find that the insurers have almost monotonically decreasing efficiency for the period from 2006 to 2010. Regression results show that human capital, structural capital and relational capital are significantly and positively related to operating efficiency. Research limitations/implications – This study suggests that managers of the Chinese non-life insurers should devote attention to the investments in IC to stay sustainable. Originality/value – This is ...

[1]  Abdel-Aziz Ahmad Sharabati,et al.  Intellectual capital and business performance in the pharmaceutical sector of Jordan , 2010 .

[2]  M. Malone,et al.  Intellectual Capital: Realizing Your Company's True Value by Finding Its Hidden Brainpower , 1997 .

[3]  Gerald A Klopp,et al.  THE ANALYSIS OF THE EFFICIENCY OF PRODUCTIVE SYSTEMS WITH MULTIPLE INPUTS AND OUTPUTS. , 1985 .

[4]  Shujie Yao,et al.  On technical efficiency of China's insurance industry after WTO accession , 2007 .

[5]  Ayoe Hoff,et al.  Second stage DEA: Comparison of approaches for modelling the DEA score , 2007, Eur. J. Oper. Res..

[6]  Gene C. Lai,et al.  Ownership Structure, Agency Costs, Specialization, and Efficiency: Analysis of Keiretsu and Independent Insurers in the Japanese Nonlife Insurance Industry , 2005 .

[7]  Hsihui Chang,et al.  First Financial Restructuring and operating efficiency: Evidence from Taiwanese commercial banks. , 2010 .

[8]  R. Hosnavi,et al.  Linking intellectual capital and intellectual property to company performance , 2016 .

[9]  N. Bontis.  Intellectual capital: an exploratory study that develops measures and models , 1998 .

[10]  Chiang Kao,et al.  Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan , 2008, Eur. J. Oper. Res..

[11]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[12]  M. Eling,et al.  Frontier Efficiency Methodologies to Measure Performance in the Insurance Industry: Overview, Systematization, and Recent Developments , 2010 .

[13]  Athanasios G. Noulas,et al.  Non-Parametric Production Frontier Approach to the Study of Efficiency of Non-Life Insurance Companies in Greece , 2001 .

[14]  Martin Eling,et al.  The Performance of Microinsurance Programs: A Data Envelopment Analysis , 2011 .

[15]  F. Fecher,et al.  Efficiency and Productivity of the Insurance Industry in the OECD Countries , 1997 .

[16]  P. Pestieau,et al.  Productive performance of the French insurance industry , 1993 .

[17]  The Implications of Absorption Cost Accounting and Production Decisions for Future Firm Performance and Valuation , 2010 .

[18]  Qian Long Kweh,et al.  Intellectual capital and productivity of Malaysian general insurers , 2014 .

[19]  Peter E. Kennedy.  A Guide to Econometrics , 1979 .

[20]  Mark A. Huselid.  The Impact of Human Resource Management Practices on Turnover, Productivity, and Corporate Financial Performance , 1995 .

[21]  Randy I. Anderson,et al.  Production Efficiency in the Austrian Insurance Industry: A Bayesian Examination , 2004 .

[22]  Ali Emrouznejad,et al.  An alternative DEA measure: a case of OECD countries , 2003 .

[23]  H. White.  A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity , 1980 .

[24]  Rajiv D. Banker,et al.  Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis , 2008, Oper. Res..

[25]  John McDonald,et al.  Using least squares and tobit in second stage DEA efficiency analyses , 2009, Eur. J. Oper. Res..

[26]  M. Goto,et al.  Measurement of Dynamic Efficiency in Production: An Application of Data Envelopment Analysis to Japanese Electric Utilities , 2003 .

[27]  L. Vogt.  Intellectual Capital The New Wealth Of Organizations , 2016 .

[28]  Pierre Ouellette,et al.  Technological change and efficiency in the presence of quasi-fixed inputs: A DEA application to the hospital sector , 2004, Eur. J. Oper. Res..

[29]  M. Eling,et al.  Efficiency in the international insurance industry: A cross-country comparison , 2010 .

[30]  K. Tone,et al.  Dynamic DEA: A slacks-based measure approach , 2010 .

[31]  Quey-Jen Yeh.  The Application of Data Envelopment Analysis in Conjunction with Financial Ratios for Bank Performance Evaluation , 1996 .

[32]  J. Cummins,et al.  The effect of organizational structure on efficiency: Evidence from the Spanish insurance industry , 2004 .

[33]  Qian Long Kweh,et al.  Intellectual capital and performance in the Chinese life insurance industry , 2014 .

[34]  R. Ahangar.  The relationship between intellectual capital and financial performance: An empirical investigation in an Iranian company , 2011 .

[35]  J. Cummins,et al.  Evidence From the Spanish Insurance Industry By , 2001 .

[36]  Pierre Ouellette,et al.  Investment and dynamic DEA , 2008 .

[37]  Carlos Pestana Barros,et al.  Evaluating the Efficiency and Productivity of Insurance Companies with a Malmquist Index: A Case Study for Portugal , 2005 .

[38]  Yaakov Roll,et al.  An application procedure for DEA , 1989 .

[39]  Kaoru Tone,et al.  Dynamic DEA with network structure: A slacks-based measure approach , 2013 .

[40]  R. Färe,et al.  Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries , 1994 .

[41]  William L. Weber,et al.  Efficiency and Productivity Change of Non‐Life Insurance Companies in Japan , 2001 .