Digital relational capital of a company

Purpose - This paper aims to examine how a company can build and develop its relational capital in a digital environment. It searches for proxy-indicators for digital relational capital and explores their impact on company performance. Design/methodology/approach - The paper is designed to sit in the cross-section of two concepts – Big Data and Intellectual Capital. We analyze eight metrics of digital relational capital (SEMrush rank, Trust flow, Domain authority, MozRank, Number of pages indexed in Yandex and Google, Thematic Citation Index by Yandex, Alexa Rank) and examine their impact on company performance by conducting a two-stage fixed-effect regression. The empirical part of the paper is based on a database of more than 1,000 Russian public companies from 2010-2016. Findings - The study justifies eight Big Data-based metrics that enable the estimation of the digital relational capital of a company. Empirical evidence of a significant impact on corporate performance is provided. Moreover, a U-shaped configuration of obtained relationships allows for a better understanding of the phenomenon of digital relational capital and has managerial implications. Originality/value - Companies can indirectly influence the proposed metrics. The study gives specific recommendations regarding these metrics to allow companies to optimize their performance. In addition, to the best of the authors’ knowledge, this is the first empirical research on relational capital through Big Data in Russia.