The Role of Data Broker in the New Data Economy

Description

With the surge of data analytics and machine learning usage in business, data has become a critical asset for firms. Owing to the abundance of diverse data that firms can collect and use, how firms interact with the data has significant strategic implications. Such changes have brought new competitive landscapes in which data can be collected and shared at unprecedented speed and scale. At the heart of the development, data brokers play an essential role in facilitating the sharing of competitive business intelligence amongst firms. Furthermore, individual firms can also rely on technologies to gather the relevant data and make an adjustment to the competition strategies based on the knowledge generated from the data. Hence, the emergence of the new data-centric era has created profound impact on firms’ data collection and competitive strategies.In prior studies, information between competitive firms may have been shared through a third party (such as a supplier), but not in the form facilitated by a data broker. In this study, we focus on the strategic interactions amongst two competitive firms and a data broker, where we examine a host of data-related strategies by the data broker. It includes how to set the data sharing price and what is the degree to which the data broker chooses to improve the information quality when they are provided to the firms. As far as the firm is concerned, the availability of data and market intelligence will have implications to its strategies on pricing and product quality. Thus, the collective strategic actions considered in this study are novel and have not been discussed before.In recent years, there have been increased scrutinization regarding how firms utilize consumer data to advance their interests which may turn out to be detrimental to the consumers. A typical concern is related to the violations of privacy concerns of the consumers. In this study, we aim at another issue which may also have a negative consequence to the consumers whereby the presence of data broker can potentially steer the market competition towards some kind of collusive outcomes. Indeed, there has been much debate on whether data-driven pricing models (e.g., algorithmic pricing) facilitate tacit collusion among firms. Therefore, in addition to understanding the competitive interactions amongst the focal firms, our study will provide insights on the consumer welfare implications, which may provide critical insights to policy-makers in this new data-centric era.