Identifying Business Models of Open Data Intermediaries: A Review

Abstract

Open data has many potential benefits including stimulating innovation, enhancing accountability and transparency, and improving the reproducibility and dissemination of research (Janssen et al., 2012; Uhlir and Schröder, 2007; Zhu et al., 2019). However, there are various shortcomings in the current open data initiatives such as the mismatch between the supply and demand of open data, the lack of appropriate software to process data, and confusion regarding data licenses (Johnson et al., 2017; van Loenen et al., 2021). The role of open data intermediaries is considered important to address these weaknesses. Open data intermediaries facilitate the use of and access to open data (Chattapadhyay, 2014; González-Zapata and Heeks, 2015) and build connections among open data stakeholders (Mayer-Schönberger and Zappia, 2011). It follows that open data intermediaries are regarded as one of the priority areas in open data research (Davies and Perini, 2016). Nevertheless, in-depth studies on open data intermediaries are scarce. Within the limited studies, they are found to face several challenges that may undermine their potential contribution to other open data stakeholders. For example, lack of financial planning (Flores, 2020), over-reliance on volunteers (Reggi and Dawes, 2016), and difficulty in securing data experts (Andrason and van Schalkwyk, 2017). Some of these challenges are associated with the lack of development of open data intermediaries’ business models (Kitsios et al., 2021; Reggi and Dawes, 2016). Before any research-based development of their business models can be carried out, a clear view of the existing business models is needed. Given this, the objective of this extended abstract is to review existing business models of open data intermediaries from the academic literature through a systematic literature review (SLR). Section 2 provides a brief background on the concept of a business model. Section 3 describes the research method. Section 4 presents the findings. Last but not least, Section 5 discusses the findings and proposes considerations for future studies.