Competitor identification with memory in a dynamic financial transaction network

Abstract

Competitor identification (CI) is an essential step in establishing an effective competitive business strategy. For complex business environments, network-based CI methods have been studied in the literature, aiming to shed light on the blind spots in managers’ radars. Typically, CI is based on networks without temporal information, despite the dynamic changes in business environments. Alternatively, the temporal information is considered in CI by simply accumulating the intensities of synchronous interfirm competition evaluated over time. As a result, competitors’ actions in the past are overlooked in evaluations of interfirm competition, although such actions remain in managers’ memories. In this study, we propose a new method for CI incorporating memories of the past transactions of competitors in a dynamic network. The proposed method measures the interfirm competition between firms based on their resource similarity and market commonality in a dynamic financial transaction network. The proposed method facilitates capturing the asynchronous competition from suppliers and demanders taken by competitors. We evaluate the proposed method on a toy network and on a case of interfirm transactions in Korea from 2011 to 2014. The results show that the temporal information in dynamic networks and memory about past transactions improves the predictive accuracy in CI with the proposed method.