Predicting customer-supplier relationships using network-based features

Business development is vital for any firms. However, globalization and the rapid development of technologies have made it difficult to find appropriate business partners such as suppliers, customers and outsources. In this contribution, we propose a new computational approach to find business partner candidates based on firm profiles and transactional relationships among them. We employ machine learning techniques to build prediction models of future customer-supplier relationships. We applied our approach to Japanese firms and compared our prediction results with the actual business data. The results showed that our approach successfully found plausible candidates, and can be a new powerful tool to develop one´s own business in the complicated, specialized and rapidly changing business environments of recent years.