Presenting a Data-Driven Value Creation Model for Insurers with an Interpretive Structural Approach

This research aims to design a data-driven value-creation model for insurance policyholders. It uses a mixed methodology (qualitative-quantitative). The statistical population was university professors in insurance and marketing and senior managers of Iran's insurance industry, including Asia Insurance, and Alborz Insurance. The saturation was reached with 12 university professors. To identify the influential factors in the data-driven value creation model for insurance policyholders, the Delphi technique was used in the form of theoretical consensus. The interpretative structural method was used for modeling. The studied structures to design and explain the value creation model for insurance policyholders in Iran's insurance industry include factors related to employees, policyholders, training, organization, management, and branding. Based on structural-interpretive modeling calculations, it was determined that the factors related to employees are external independent variables unaffected by any variable in the model. The factors related to employees and training are endogenous independent variables, and the factors related to the brand are dependent. Also, the factors related to insurance policyholders plays a mediating role. Researchers believe that the more organizations can gain a better understanding of customer needs, as well as the activities of competitors and factors affecting market conditions and distributing information at all levels of the organization, the more ability they will have to survive in the competitive market.