Effects of digital readiness on digital competence of AEC companies: a dual-stage PLS-SEM-ANN analysis

Abstract

ABSTRACT To what extent does a firm’s digital readiness influence its competence in implementing digital initiatives? This study employs a deep-learning-based dual-stage approach using Partial Least Squares Structural Equation Modelling (PLS-SEM) and Artificial Neural Network (ANN) to demonstrate and quantify this relationship. Data were sourced from a questionnaire survey involving 428 architecture, engineering and construction (AEC) firms in New Zealand. The PLS-SEM analysis confirmed the positive correlation between the digital readiness of an organization and its competence towards seven types of DT, including immersive technologies, sensing technology, robotics, 3D printing, digital fabrication, artificial intelligence and big data. The ANN analysis further quantified the importance of the investigated readiness indicators in influencing digital competence. The results highlighted four most significant readiness attributes influencing the digital competence of AEC firms: (1) organizational culture, (2) perception of the leadership team, (3) hardware & software systems and (4) strategy plans. The findings can serve as a baseline for developing effective change management strategies and contribute to reducing the digital divide within AEC organizations, facilitating the effectiveness of organizational digital transformation.