This paper presents an empirical investigation to study the impact of the implementations of the recent advances on technology on total factor productivity improvement (TFP) of some Iranian insurance firms over the period 2008-2012. The study considers the number of information and communication technology (ICT) employees, insurance treaty and the number of computers used together with online users as technology advancement. Using generalized least square technique, the study has determined a positive and meaningful impact of the number of research and development employees as well as the number of personal computers together with online users on TFP improvement. However, the numbers of ICT employees and insurance treaty have no significant impact on TFP improvement.

This paper presents an empirical investigation to study the effects of corporate governance on risk taking of private insurance firms and banks in Iran. The proposed study of this paper considers the financial information of 13 banks and 19 private insurance firms over the period 2006-2011 in Iran. The study investigates the effects of five variables including size, CEO duality task, composition of the board of directors, ownership concentration and having an internal auditing system on risk taking of private banks and insurance firms in Iran. Using some panel data and regression analysis, the study confirms the positive effect of the ownership concentration as well as negative impact of non-bound board members on risk taking.

Insurance industry includes a significant part of economy and it is important to learn more about the capabilities of different firms, which are active in this industry. In this paper, we present an empirical study to rank the insurance firms using analytical hierarchy process as well as factor analysis. The study considers four criteria including capital adequacy, quality of earning, quality of cash flow and quality of firms’ assets. The results of the implementation of factor analysis (FA) have been verified using Kaiser-Meyer-Olkin (KMO=0.573) and Bartlett & apos; s Chi-Square (443.267 P-value=0.000) tests. According to the results FA, the first important factor, capital adequacy, represents 21.557% of total variance, the second factor, quality of income, represents 20.958% of total variance. In addition, the third factor, quality of cash flow, represents 19.417% of total variance and the last factor, quality of assets, represents 18.641% of total variance. The study has also used analytical hierarchy process (AHP) to rank insurance firms. The results of our survey indicate that capital adequacy (0.559) is accounted as the most important factor followed by quality of income (0.235), quality of cash flow (0.144) and quality of assets (0.061). The results of AHP are consistent with the results of FA, which somewhat validates the overall study.

One of the primary concerns with data envelopment analysis arises when the number of inputs and outputs increases. In such a case, required computations will become time consuming and there is a concern on developing some hybrid methods to increase the capability of this method. In this paper, a combination of data envelopment analysis and multi-layer neural network is proposed, in a case study, for predicting the performance of Alborz insurance subsidiaries in large cities in Automobile insurance firms. This research can be used in the future databases for performance prediction. On the other side, these results can aid Alborz insurance in its future investments as well as the performance index usage.