Evaluating implementation cost of blockchain through system dynamics

One of the main obstacles to the adoption of blockchain is the cost of its adoption. The application of this technology in an organization requires the costs of development, design, maintenance, hardware, software and energy consumption according to its adoption rate. In this study, the system dynamics (SDs) and machine learning (ML) methods have been used to predict final cost of blockchain implementation. Compared to mathematical programming, simulation techniques in the estimating the costs are scarce, although SD modeling is suitable to account for the complexity and dynamic of systems and support long-term, strategic decision-making. To better understand the system behavior, it is necessary to formulate the relationships between the variables and simulate the values of the variables over time. The relationships between these variables are analyzed using the qualitative SD modeling method with stakeholders through questionnaires and ۱۵ interviews. Thus, it provides a reasonable basis for estimating the cost of blockchain implementation. After identifying the variables, their effect on each other and the implementation cost are investigated. Since the diagrams obtained from the SD give us the behavior of state and flow variables for time, linear regression applying cross-validation, as one of the ML methods is used to get a graph showing the system's state as a rate function. Thus, this research provides a reasonable basis for estimating the cost function of blockchain implementation. The results of this research can be of great help to decision-makers in the development and application of blockchain technology in organizations.

کلیدواژه ها:

System dynamic ، Blockchain ، Cost management ، Transaction