IRANIAN JOURNAL OF INSURANCE RESEARCH (SANAAT-E-BIMEH)
Year:2018 | Volume:33 | Issue:2 (130) |Papers Count:7

Efficiency measurement of firms operating in a competitive environment has always been a concern. The purpose of this study is to evaluate the efficiency of Iranian insurance companies using Data Envelopment Analysis (DEA), ranking of insurance companies using the DEA model and comparing results with multi-factor decision-making models. In order to achieve this goal, in addition to a library comprehensive study, we have investigated about the previous studies results related to the inputs and outputs of the DEA model. Then, content analysis technique is used in order to screen the variables which are identified by Shannon Entropy. In the next step, using the DEA model, efficient and inefficient insurance companies are identified and after that, we rank efficient insurance companies according to the AP model. Then, using multi-criteria decision making models, insurance companies were ranked and in the end, Copeland method was used to present the unit rank.

This study is seeking to assess the customer satisfaction of the Iranian insurance industry. Our study is a questionnaire-based survey. Hence, we distributed 6580 questionnaires among customers of 19 active companies in the insurance industry in 2014. Model parameters are determined based on service marketing mix. The results indicate that the lowest and highest levels of satisfaction related to the marine insurance and oil and energy insurance, respectively. In terms of satisfaction indices, simplicity and the speed of policy issuing have the greatest satisfaction. On the other hand, the lowest satisfaction is associated with the compensation amount. In addition, our finding show that insurance company history affects customer satisfaction. The research indicates no significant relationship between customer satisfaction with insurance company’ s size (capacity for risk retention) and its shareholder status (private/public). Detailed results of this study can also be used to shed a light for identifying weaknesses of insurance companies in terms of customer satisfaction and suggesting solutions to fix them.

This research studies life insurance customers data in order to construct a clustering model for providing services. According to our estimations for sample size, our sample consists of 1000 life insurance policyholders who bought their policies in 2013 from an Insurance Company. Using clustering data mining models, effective factors and their relationships are examined. Finally, the results of different clustering models are compared to each other. According to the results, insurance companies can categorize life insurance customers into two main groups, including "profitable customers" and "risky customers". Hence, insurance company is able to offer suitable service packages to each group of customers. Some demographic indices, such as “ gender” and “ age” , and insurance indices, such as “ annual premium” and “ death rate due to accident” are considered as effective factors for identifying groups of customers.

As we are moving into the new millenniumand due to rapid changes in the IT industry around the world, an organization’ s competitiveness and survival depends on its ability to develop and produce new and innovative products. In a new era of global competition, countries rely on innovation in order to increase productivity and improve the economy. With reference to the subject mentioned above, the goal of this study is to identify and prioritize factors affecting open innovation in an insurance company. Considering related literature and according to the model which is used in this study, 38 indicators have been identified. After designing a questionnaire based on 38 indicators and approving its validity by experts, 134 questionnaires were distributed. Reliability is confirmed by Cronbach's alpha test. We consider EXCELL, SPSS and PLS software’ s output in order to determine open innovation factors in the organization.

Today’ s highly competitive business environment makes accessing to the accurate, effective and updated information as an instrument of power that any company uses for decision-making and choosing competitive strategies at the firm and national level. Hence, business intelligence implementation, knowledge management establishment and improving critical success factors play a vital role in Iranian insurance industry. The aim of this study is to design a model for successful business intelligence using knowledge management establishment for Iranian insurance industry. Important variables affecting the success of business intelligence and knowledge management are identified according to literature and have been used for the Delphi method. We gathered data using questionnaires. We have identified micro and macro variables. Finally, after classifying 34 variables into groups, such as knowledge management, business intelligence and mediator, we have designed and validated the model using structural equation model.

One of the prevailing principles in life insurance law is the existence of an insurable interest. This principle is related to the public policy and life insurance contracts without insurable interest raises the possibility of moral hazard and deliberate harm to people’ s lives and property. Therefore, it is truly necessary to ensure existence of this principle and determine some factors to identify it. Hence, two criteria are presented for identifying insurable interest, including spiritual factor and economic factor. Former factor mentions each person has an insurable interest in his life and loved ones, including wife, parents, children and other members of family. Latter factor refers to financial dependency between two persons, two business partner, key employees of a company and the debtor. Therefore, it is necessary to find out the intricacies of insurable interest through study of legal cases raised in the common law. This study analyzes these complexity and the precision of legal opinions.