Knowledge Management-Based Artificial Intelligence (AI) Adoption in Construction SMEs: The Moderating Role of Knowledge Integration
Abstract
Small and medium enterprises (SMEs) in the construction sector play a pivotal role in any emerging market economy. These construction SMEs provide ancillary services to various industries, increase employment opportunities, and contribute to maintaining regional economic equilibrium. Technological innovations, particularly those based on artificial intelligence (AI), can significantly benefit SMEs by enhancing competitiveness and improving sustainability. However, the adoption of AI is slow among construction SMEs, and the factors that influence these enterprises’ adoption of AI-based technology are not well understood, creating a critical research gap. In this article, we present a theoretical model grounded in knowledge management theory and the unified theory of acceptance and use of technology to explore the factors that affect SMEs’ adoption of AI-based technology in developing countries. The data were collected from 422 construction SMEs, and structural equation modeling was employed to examine the hypotheses. The analysis of data collected from construction SMEs reveals that openness to innovation impacts perceived knowledge, which in turn influences performance expectations, ultimately affecting the adoption of AI-based technology in construction SMEs. Additionally, knowledge integration moderates the adoption and actual usage of AI-based technology.
Cite this
Ali Nawaz Khan, Khalid Mehmood, Mohsin Ali Soomro (2024). Knowledge Management-Based Artificial Intelligence (AI) Adoption in Construction SMEs: The Moderating Role of Knowledge Integration. IEEE Transactions on Engineering Management. https://doi.org/10.1109/tem.2024.3403981
@article{nawaz2024knowledge,
title = {Knowledge Management-Based Artificial Intelligence (AI) Adoption in Construction SMEs: The Moderating Role of Knowledge Integration},
author = {Khan, Ali Nawaz and Mehmood, Khalid and Soomro, Mohsin Ali},
year = {2024},
journal = {IEEE Transactions on Engineering Management},
doi = {10.1109/tem.2024.3403981}
}Citations in this library
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