Abstract

The commitment of organisations to physical assets management (PAM) has recently received considerable attention in theory and practice. Indeed, PAM plays a key role in asset-intensive organizations and is also considered as a principal actor within Industry 4.0. Therefore, this paper aims to examine the PAM core practices and the performance implications of integrating these practices into business, in particular by assessing their impact on operational performance. Survey data were collected from managers in 138 international and local organisations. The data was analysed using Partial Least Squares Path Modeling (PLS-PM). The study validates the second-order construct consisting of PAM latent variables, namely Strategy and Planning, Risk management, Lifecycle Delivery, Asset Information, and Asset Review. The results have shown that PAM core practices directly influence operational performance. This paper is a response to recent calls for empirical studies on the organisational approaches that can increase the success of organisations.

Highlights

  • Physical asset management (PAM) has recently been considered as one of the most important sources of competitive advantage [1,2,3]

  • Our study focuses on physical assets, it should be noted that asset management (AM) considers any type of asset that has an actual or potential value for the company

  • Our study contributes to the exploration of the underlying PAM mechanisms and complements the few studies that focus on the role of PAM in enhancing operational performance

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Summary

Introduction

Physical asset management (PAM) has recently been considered as one of the most important sources of competitive advantage [1,2,3]. The advent of industrial digitalization and the Industry 4.0 revolution offers industrial companies opportunities to holistically manage the costs, risks and performance of assets [15] To this end, they can use advanced technologies such as predictive analytics, artificial intelligence and digital twins as a means of monitoring and predicting the performance of assets and processes [16]. Great efforts have been made to identify new competitive factors and issues that are important for excellence in asset intensive environments [21]. The latter can be supported by various theories. More recent research [3,4]

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