Dynamic Product Portfolio Management Modeling for the Financial Technology Industry

Document Type : Original Article


1 Ph.D. Candidate, Department of Business Management, Faculty of Management, University of Tehran, Tehran, Iran.

2 Associate Prof., Department of Business Management, Faculty of Management, University of Tehran, Tehran, Iran.

3 Prof., Department of Business Management, Faculty of Management, University of Tehran, Tehran, Iran.

4 Prof., Faculty of Information Technology, Sharif University of Technology, Tehran, Iran.


Resource allocation, as the main objective of managerial science, requires analyzing the long- and short-term effects of a policy, although this analysis would be more difficult in dynamic and volatile industries such as financial technology. Moreover, the integration of industries leads to more diverse product categories for a single company and makes it difficult for the implementation of decision making about resource allocation. In this regard, systemic PPM (PPM) models can be applied to balance long- and short-term generated values of the company by adopting policies about resource allocation for different products with respect to risk management concepts. The proposed systemic model should include interrelationships between different products, time relevant, and most importantly the potentials of dynamic analysis of product strategies, which is the main purpose of this research. The research strategy is to conduct a case study on the Iranian financial technology industry, by using systemic PPM modeling. In this research, a dynamic model was used in the payment industry, due to its competitive forces. Thus, system dynamics methodology was the research tool for analyzing data. Further, four cycles of risk management, resource allocation, innovation, and development were identified and then, analyzed in a dynamic approach to evaluating their efficiency for business development. Based on the results, the system dynamics methodology provided great outcomes for this problem. Finally, scenario analysis, focus, deep understandings of the decision-making process with respects to mental models, and stock and flow diagrams were among the most significant findings of this article.


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