IRANIAN JOURNAL OF INSURANCE RESEARCH (SANAAT-E-BIMEH)
Year:2012 | Volume:26 | Issue:4 (104)|Papers Count:9

The aim of this paper is to measure technical and allocative efficiency as well as productivity of public and private insurance companies that are active in Iranian insurance industry, using Data Envelopment Analysis (DEA). We assess technical and allocative efficiencies and the productivity of public and private insurance companies from 1384 (2005) to 1387 (2008). Our results show that the average measures of technical efficiency for the Iranian insurance industry in constant returns to scale model, is 0.944, and the corresponding value in variable returns to scale model is 0.972.The results also show that public insurance companies have been operating under decreasing returns to scale and only two private insurance companies, namely Parsian and Mellat have had constant returns to scale in production. In addition, variations in total productivity, using the Malmquist index, was increasing for Asia, Moallem, Parsian, Razi and Pasargad and decreasing or undetermined for all other insurance companies.

This paper is the result of field research that looked at an integrated model of Balanced Scorecard (BSC) and the European Foundation for Quality Management (EFQM) model. It is suggested that this integrated model, is an effective model for performance evaluation in insurance industry.Having studied the advantages and disadvantages of these two models, we designed two sets of questionnaires put before middle managers and senior experts in the Iranian insurance industry, both in public and private sector. Responses were collected as our main required data. Statistical tests were carried out to suggest an integrated model to evaluate the performance of the Iranian insurance industry that conform to the EFQM and BSC models’ criteria separately. Using this integrated model, we can show that all aspects of organizational success can be seen as the main performance indicators.

In this paper we use time series analysis focused on the relationship between per capita income, rate of inflation, rate of unemployment, literacy, price of insurance and demand for supplementary health insurance (premiums received) thorough the period 1369-1387 (1990-2008). We examine the long term relationship between independent variables and demand for supplementary health insurance and use Engle-Granger co-integration tests. For this purpose, we collected information and statistics on four insurance companies. Our results show that there is a long term relationship between economic factors and the demand for supplementary health insurance.These findings indicate that the national per capita income and the rate of literacy have a positive and significant effect on the demand for supplementary health insurance, while price of insurance, the rates of inflation and unemployment do not have any significant effect on the demand for supplementary health insurance.

Conventional theories of demand under asymmetric information do not emphasize the effects of risk aversion on insurance demand and do not consider negative correlation between risk aversion and risk level. In this paper we focus on the effects of risk aversion on life insurance demand.We use logistic regressions and apply dummy variables to show whether independent variables such as education, occupation, sex, age, income, wealth of household and other factors as criteria for risk aversion, have significant effects on the demand for insurance. Our results show that age, gender, and employment don' t have any significant effect on the demand for life insurance. But education, marital status, care, health, premium levels, future uncertainty, income level and life expectancy have significant effects on the demand for life insurance in Iran.Since individuals with high level of risk aversion purchase more life insurance than high risk individuals (lower risk averse individuals), we conclude that adverse selection doesn’t exist in Iranian life insurance market. In other words, the Iranian life insurance market faces an advantageous selection situation rather than adverse selection.

Insurance companies are influential financial entities and need powerful risk analysis methods in order to manage risks. Risk analysis could be used for risk management in various ways as in pricing products, marketing and identifying costumers.In this paper, we first collected data from costumers and after a pre-processing step, various risk classification algorithms are utilized. At the end, the results of each algorithm are compared with each other and the C5 is selected as our proposed algorithm for risk classification of customers. This algorithm has the highest accuracy among nine algorithms used.

Insurance industry is part of financial sector and has a significant impact on economic growth. With regards to the concurrent liberalization and privatization in this important industry and the increasing competition between insurance companies, there is a need for a re-examination of insurance processes, especially in sales and marketing networks.We define unethical sales behavior as a salesperson’s short-term conduct that enables him/her to gain at the expense of customers. This behavior is measured by lies about availability in order to make a sale, lies about competition in order to make the sale, answers that he/she does not really know, applies sales pressure even though he/she knows that the product is not right for the customer and paints rosy pictures of products to make them sound as good as possible. To address these issues, we use the Mei-Fang Chen and Liang-Hung Mau (2009) model. Our paper is both descriptive and empirical. Regression analysis and correlation test are carried out to tests our hypotheses and we have used factor analysis for the general goodness of fit of our model.Our main results show that the relationship between ethical sale behavior and customer loyalty is confirmed. We further propose implementation of marketing ethics through courses and workshops, establishing an ethics society for controlling ethics in the field of life insurance, keeping sales people up-to-date, paying more attention to selection of sales people, updating mortality tables, television advertising, diversifying life insurance and paying more attention to after sale services.

The aim of this paper is to investigate the relationship between the “Big Five” personality traits (Neo-IPIP 120 item scale) with job performance among insurance company executive management. Managerial performance scales with 40 items, is developed according to managerial tasks, roles and evidence of good psychometric criteria. Using Pearson correlation criteria and regression analysis, our results show that job performance has a positive correlation with extraversion, conscientiousness, agreeableness, openness to experience and a negative correlation with neuroticism.Regression analysis indicates that extraversion could predict job performance. While principle components analysis shows that assertiveness, friendliness and gregariousness were predictors of performance among extroversion facets. The results are discussed according to socio-cultural aspects of Iranian organizations, and the importance of personality measures in managerial selection and development.