Analysis of Scientific Production on the Use of Big Data Analytics in Performance Measurement Systems

Authors

Keywords:

Bibliometric Analysis, Performance Measurement Systems, Performance Measures, Industry 4.0, Big Data Analytics

Abstract

Performance measurement systems have a critical role in organizations’ management, transforming data into relevant information for decision makers. In recent decades, the amount of data and information generated and shared has increased immensely, providing unprecedented opportunities and challenges for such systems. Faced with this scenario, this article aims to analyze the use of big data analytics in performance measurement systems to clarify the nexus between them. Furthermore, the aim is also to identify the trends and opportunities for future research. To achieve that, we carried a scientific map out using bibliometric analysis. The major results of the research show that the use of big data analytics in PMS has increased in recent years without considering the performance measurement systems’ characteristics. Incorporating artificial intelligence technologies such as machine learning and deep learning could improve the domain, creating opportunities for empirical works such as the use of unstructured data and applications in Industry 4.0.

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Author Biographies

Junior Assandre, Universidade Federal de São Carlos, São Carlos, SP, 13565-905, Brasil

Bachelor's Degree in Business Administration and Master's in Management and Public Systems (2015). He is currently a doctoral candidate in Industrial Engineering at the University Federal of Sao Carlos. His research interest are: Measurement System Performance and Big Data Analytics for Performance Measurement.

Roberto Martins, Universidade Federal de São Carlos, São Carlos, SP, 13565-905, Brasil

Bachelor, Master Science, and Doctorate degress in Industrial Engineering from University of Sao Paulo. He is currently a Full Professor at the Industrial Engineering Department of the Federal University of Sao Carlos. His research interests are: performance measurement systems for sustainable supply chain management, business performance analytics.

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Published

2023-01-05

How to Cite

Assandre, J., & Martins, R. (2023). Analysis of Scientific Production on the Use of Big Data Analytics in Performance Measurement Systems. IEEE Latin America Transactions, 21(3), 367–380. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/6992