Big data for business modeling: Towards the next generation of performance measurement systems?

Abstract

The IX Workshop of the Management Control journal provided a great opportunity and platform for constructive discussions on the evolution of management control systems.Coherently with the core theme of the SIDREA national conference, "From crisis to sustainable development: principles and solutions from the perspective of Business Economics", the objective of the Workshop was to promote a debate on the design and adoption of management control systems that are more resilient in times of crisis and thus, more useful in the governing of companies' development process.It is along these lines that this Special Issue was designed and created.Its point of departure was the call for a substantial innovation in the design, implementation, and use of performance measurement systems (Marchi, 2015), especially in view of the digital revolution that is affecting the way companies operate and compete (Sardi et al., 2020).One of the main implications that arises from the ongoing digital revolution is the tremendous growth of data available to companies, which has led to the phenomenon known as big data, a term that describes a large volume of data, both structured and unstructured, that comes from different sources and grows at ever-increasing rates (Gemmo and Isari, 2018).Big data cannot be analyzed through traditional applications and methodologies, but it requires ad hoc software, called big data analytics, in order to be converted into useful information that can be used to support the managerial decision making process (Petrosino et al., 2018).As stated by Marchi (2003), data has no value by itself but rather, the value is created when it is processed, organized, presented in a given context, and connected to other relevant data in order to obtain information that can be interpreted and used proactively and intentionally by decision makers.

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