Although the importance of supply chain management in the construction sector has been recognized in recent years, its implementation still faces significant challenges. For the long-term evaluation of this creative sector, numerous intricate sustainability components, such as environmental, social, and financial, are necessary. The study focuses on longterm sustainability considerations in the supply chain in the construction sector. This work aims to address this information and examine sustainable supply chain management (SSCM) research in the construction sector in this manner. More than 95 publications were studied from the beginning of 2017 to the end of 2021 using both in-depth content analysis and bibliometric methodologies. Several issues of SSCM in construction have been found including environmental, economic and social patterns which are most commonly known as the triple bottom line, typically enhanced by artificial intelligence. Many challenges were discovered including inefficiencies in the logistics system and a shortage of funding, environmental issues in demolition procedures and difficulties in applying sustainability measures due to high skill, data, and time requirements. The article offers a broad list of potentials for improving the current situation in the construction sector by using various types of supply chains such as increasing investment in energy conservation and emission reduction technologies to drive sustainable development, establishing strong green supply chain relationships, and forming a Covid-19 financial support group for small construction companies among other things. The study’s findings suggested that due to the significance of long-term relationships between construction companies, suppliers and customers, smart technology could make it simpler to reach every supply chain link. After an exhaustive literature review 59 research questions were formulated for the future research. In the future, the importance of these questions could be determined using expert questionnaires and multi-criteria evaluation.