Presenting the model of business intelligence capabilities and its role on innovation considering the effect of network learning and performance (case study of insurance industry)

Abstract

Introduction and purpose: In the knowledge-oriented perspective, the main asset of a company is knowledge in the formulation of its competitive advantage. Increased knowledge can result from business intelligence. The purpose of the research was to provide a model of business intelligence capabilities and its role on innovation, considering the effect of network learning and performance in the insurance industry. Methods: The current research was applied in terms of its purpose and qualitative in terms of method with the approach of foundational data theory. In this research, the methodological angle was observed using different methods of data collection, such as the method of library study and review of sources and specialized texts, as well as semi-structured interviews. Based on targeted sampling, 14 managers and experts of the insurance industry were interviewed in 2002. The conducted interviews were coded in ATLAS.TI software. To confirm the results obtained based on three strains, the data were evaluated and qualitatively analyzed. Results: Research findings in five categories of causal conditions (management procedure, technical procedure, systemic procedure, organizational procedure, human resources procedure), contextual (policy and laws, insurance industry), intervening (financing, security interventions, cultural conditions) and social), strategy (incentive policy, training and specialization, smartening and strategic review) and consequences (increasing the efficiency of the insurance industry, improving customer management, improving the strategic situation and improving project management) were determined separately. A model was identified in 6 categories, 18 core codes based on 82 open codes. This model has identified one of the most comprehensive models of business intelligence capabilities and its role on innovation, considering the impact of network learning and performance. Conclusion: Providing a model that uses the combination of business intelligence and network learning can play a very important role in creating innovation and growth of the insurance industry. These models help companies to more accurately analyze risks, offer new products and services, and provide a better experience to their customers. Therefore, the development and use of these models is of great importance and can be effective in determining success strategies and advancing this industry.