In the age of digital transformation, enterprises are becoming increasingly aware of the value of external data, which originates beyond their four walls. Despite the growing number of datasets and their potential value, external data is sourced in an ad-hoc manner without clear guidelines. This leads to inconsistent sourcing decisions, characterized by a lack of clarity on the object of sourcing and the underlying data sourcing practices. Existing studies showcase scenarios of enterprises using external data, which are fraught with obstacles. A crucial challenge confronting companies that intend to use external data is to identify suitable datasets supporting specific business scenarios and to prepare them for use. In the context of a specific external data type – open data in our case – researchers have developed several data assessment techniques. Unfortunately, these techniques are limited in scope, do not consider the use context, and are not embedded in the complete set of activities required for open data consumption in enterprises. The emerging field of data sourcing also displays a notable absence of comprehensive research, prompting a clarion call for action in Information Systems (IS) research to address this gap. Considering the abovementioned research opportunities, this thesis – through three interrelated research streams – provides foundations for, analyzes, and improves data sourcing practices in the enterprise context. The first stream lays the foundations for the topic and investigates the company-wide sourcing and managing of external data. The second stream reflects on sourcing practices concerning open data, as one of the most prominent external data types, and challenges the widespread perception that open data is easily accessible and readily available. Focusing on one of the most pressing topics facing present-day companies, the third stream provides a foundation for the academic conceptualization of data sourcing in the context of sustainability.
The outcomes of this thesis project enable the transition from ad-hoc acquisition to well- informed, professional data sourcing approaches in the enterprise context. The contributions of the first research stream are an external data sourcing taxonomy (Essay 1), which informs sourcing decisions in an enterprise context, and a reference process to source and manage external data (Essay 2), which is accompanied by explicit prescriptions in the form of design principles. The second research stream proposes a use case-driven assessment of open corporate registers (Essay 3) and, building on the subsequent findings, a method to screen, assess, and prepare open data for use in support of companies’ open data activities (Essay 4). Finally, the third research stream reveals and elaborates on three data sourcing practices developed by companies in response to institutional pressures in the sustainability context (Essay 5).