Estimation of Transactional Network Data Between Branch Offices using Transactional Big Data Throughout Japan

When conducting agent economic simulation for supply chains, inter-company transaction data are essential. However, the current inter-firm transaction data are network data in which branch office information is aggregated into headquarters transaction data. This study proposes a method to estimate branch office transactions from inter-company transaction data aggregated among headquarters by using a gravity model. We also confirm the method's reliability by comparing the estimated transaction data with the inter-regional input-output tables. We analytically considered the transition for all network configurations, demonstrating that the transaction quantity depends on the amount of labor and distance. We also demonstrated that our model fits well with data from business transactions, implying that the whole network structure can be used to model money flow in the real world.