How accountants judge and use big data as an information source for business decision-making

In the context of pressure to ensure real-time reporting, accounting professionals must increasingly make judgments about using unfamiliar information sources such as big data. In contrast to prior studies that typically focus on data analytics rather than how big data is judged and used, this study investigates how accounting professionals use big data for business-related decision-making. In our 24 semi-structured interviews, we use a vignette for a consistent context as our accounting professionals make six decisions requiring use of two information sources – accounting information and social media as a form of big data. By applying valence theory to quantify the data, findings show how their propositional judgments positively value accounting information and negatively value most characteristics of this big data. Next, when invoking a practical judgment about whether and how to use big data for decision-making, they apply a heuristic, and weigh its ‘relevant-value-to-context’ (RVC) by anchoring their judgment in accounting information. In correlating findings with their expressed trust and preference to rely on experience when decision-making, this practical judgment appears to be informed by experience. As both judgments value accounting information, this expressed trust in big data appears related to participants’ willingness to accept risk rather than assurance about its trustworthiness. Theoretically, findings suggest need to revisit the role of experience and trust in the extended valence framework. Further, whereas practitioner resources focus on how big data’s management value chain affects accountants’ roles and skills, findings show the importance of existing capabilities, particularly their training and experience.