Artificial Intelligence and Green Innovation in Small and Medium-Sized Enterprises and Competitive-Advantage Drive Toward Achieving Sustainable Development Goals

A significant portion of small and medium-sized enterprises (SMEs) are usually allocated to the construction sector, which plays a vital role in many economies. SMEs currently face serious concerns regarding the pursuit of sustainability. Limited financial resources (FRs) frequently prevent SMEs from implementing sustainable practices. Therefore, these enterprises should mitigate expenses to invest in environmentally friendly initiatives. Enhancing resources and developing ways to accelerate Turkish SMEs’ shift toward sustainability is vital. Moreover, adopting artificial intelligence (AI) and green innovation strategies (GISs) can boost sustainable competitive advantage (SCA) and lead them to success. This study utilized the natural resource-based view theory (NRBV), developed to compensate for the RBV’s shortcomings by incorporating the natural environment into the RBV’s framework. This study uses structural equation modeling (SEM) to examine the causal effect between the study variables based on the responses received from 228 executives within SMEs in Turkey’s construction sector. The findings of this study reveal that FRs significantly impact the SCA among SMEs, while GIS serves as a mediator in the relationship. Additionally, the moderating impact of AI adoption promotes sustainability development in this industry. This study is significant because it contributes to the body of knowledge regarding the relationship between the study’s constructs that align with Sustainable Development Goal 9 (Industry, Innovation, and Infrastructure), presented by the United Nations in 2015. This goal promotes robust infrastructure, encourages sustainable and inclusive industrialization, and stimulates innovation in the SME construction industry. Although these variables have been studied individually in previous studies, this study integrates them into a thorough framework that emphasizes the function of GIS as a mediator in the relationship between FRs and SCA, and the interaction effect of AI adoption. This study offers useful information to managers, stakeholders, politicians, and SME leaders, enabling them to make well-informed decisions about sustainable practices.