ABSTRACT Social procurement seeks to generate social value and contribute to sustainable development, including community benefits and opportunities for marginalised groups. Achieving these outcomes depends on effective participation, which is often lacking due to limited awareness of construction technologies amongst marginalised communities. Moreover, existing studies have given little attention to technological solutions that address these knowledge gaps. Thus, this study developed an artificial intelligence (AI)‐driven chatbot to examine how to overcome knowledge gaps. Guided by a pragmatist philosophy, a mixed research choice and experimental strategy were adopted. Marginalised community interactions were recorded for accuracy and efficiency, and the results were analysed via the Wilcoxon signed‐rank test and Kruskal–Wallis H test. Moreover, the results were validated through subject matter expert interviews. Findings show that the chatbot significantly improved accuracy and efficiency. As such, the study presented the first ever AI‐driven chatbot designed to reduce knowledge barriers that limit marginalised groups' participation in social procurement and improve stakeholder engagement.
Fernando et al. (Tue,) studied this question.
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