Finding business partners and building reciprocal relationships - A machine learning approach

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 and build reciprocal relationships among them, while it simultaneously offers many opportunities. 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 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 reciprocity among them whose accuracy is about 80%. Using machine learning approach, we have the accuracy of predicting a customer-supplier relation of 84%, and the accuracy of predicting a reciprocal customer-supplier relation is about 75-79%. These results show that our approach can be a new powerful tool to develop one´s own business in the complicated, specialized and rapidly changing business environments of recent years.