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Firm characteristics and the adoption of data analytics in performance management: a critical analysis of EU enterprises

Chun Tung Thomas Kiu (Faculty of Business, University of Greenwich, Greenwich, UK)
Jin Hooi Chan (Faculty of Business, University of Greenwich, Greenwich, UK)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 12 December 2023

Issue publication date: 30 January 2024

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Abstract

Purpose

This study aims to investigate the factors influencing the adoption of data analytics in performance management. By examining the role of organizational and environmental contexts, this study contributes to the existing literature by proposing a novel and detailed technology-organization-environment (TOE) model for the complex interplay between firm characteristics and the adoption of data analytics. The results offer valuable insights and practical implications for organizations seeking to leverage data analytics for effective performance management.

Design/methodology/approach

The research draws upon a data set encompassing over 21,869 companies operating across all European Union member states. A multilevel logistic regression model was developed to evaluate the influence of organizational and environmental factors on the likelihood of adopting performance analytics in organizations.

Findings

The findings indicate that the lack of awareness of the benefits of data analytics and its practical application to address specific business challenges is a significant barrier to its adoption. Organizational contexts, such as variable-pay systems, employee training, hierarchical structures and frequency of monetary rewards, also influence the adoption of data analytics.

Research limitations/implications

The study informs managers about the strategic role of data analytics capabilities in performance management for improved business intelligence and driving data culture.

Practical implications

The study helps managers understand the strategic role of data analytics capabilities in performance management, leading to improved business intelligence and fostering a data-driven culture in five key areas: structural alignment, strategic decision-making, resource allocation, performance improvement and change management.

Originality/value

The study advances the TOE theory, making it a more detailed and complete framework, particularly applicable to the adoption of performance analytics. It identifies the main factors of adoption that play a crucial role in this process.

Keywords

Acknowledgements

Since submission of this article, the following author(s) have updated their affiliation(s): Chun Tung Thomas Kiu is at the School of Business and Administration, Hong Kong Metropolitan University, Hong Kong, China.

Citation

Kiu, C.T.T. and Chan, J.H. (2024), "Firm characteristics and the adoption of data analytics in performance management: a critical analysis of EU enterprises", Industrial Management & Data Systems, Vol. 124 No. 2, pp. 820-858. https://doi.org/10.1108/IMDS-07-2023-0430

Publisher

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Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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