Coping with the Double-Edged Sword of Data Sharing in Ecosystems - Petra Kugler; Thomas Plank (Technology Innovation Management Review, 2021)
Researchers and practitioners agree upon the huge potential of Big Data Analytics (BDA) for firms' competitive advantage. Capitalizing on Big Data (BD) often requires sharing firms' data with their stakeholders in an ecosystem. Sharing data, however, is a double-edged sword, because firms might also risk losing their competitive advantage by doing so. This conceptual paper uses extant literature on data analytics to introduce a comprehensive data sharing strategy framework that helps firms decide which data can be shared in an ecosystem, which should be kept secret, or if additional rules and regulations are required for sharing the data. The framework combines two distinct categorizations of data, and it relates the data categories to firms' strategic competitive advantage by employing the Resource-Based View (RBV). Firstly, the framework is grounded in the stages of the data analytics process and secondly, it distinguishes between operative, strategic and monetizable data, a new categorization introduced by this paper. Depending on the categories of data a company intends to share, the framework recommends five distinct data sharing strategies that help mitigating the risk of losing their competitive advantage.
Keywords: Big Data Analytics Capabilities; competitive advantage; data sharing; ecosystem; Resource-Based View

Approaching a Data-Dominant Logic - Petra Kugler (Technology Innovation Management Review, 2020)
This paper introduces the construct of "data-dominant logic". The findings of a multi-step exploratory study indicate that SME have an established mindset (dominant logic) that often hinders these firms from turning data in innovative products, services, and business models. The availability of large amounts of data and the use of this data through data science-driven practices has reached a stage when it now enables new and promising possibilities for firms to innovate. However, the actual use of data and data science insights has proven to be difficult for many companies. The firms under consideration in this paper recognize that the availability of data fundamentally changes their businesses. But also, they lack the appropriate culture, mindset, and business repertoire that would enable them to act by turning data into innovation. The paper concludes that firms first need to establish a new mindset in which data plays a central role. Here I term this mindset "data-dominant logic" (DDL). Future research is required to further concretize the construct beyond this introduction.
Keywords: Data science; data-dominant logic; dominant logic; empirical study; organizational and managerial requirements; SMEs