Due to its intricate production processes, complex supply chains, and industry-specific characteristics, the construction industry faces unique challenges in adopting circular economy (CE) principles that promote resource equity. To address this issue, this study aims to delve into identifying stakeholders’ opinions and perceptions regarding key CE strategies across different stages of the building life cycle (BLC). Both European and non-European stakeholders within the “CircularB” COST Action network and beyond participated in this research. Three methods were employed to assess stakeholders’ opinions: an online survey, a structured survey with a semi-guided workshop, and creative thinking round table discussions. Natural language processing (NLP), specifically topic modelling and sentiment analysis, was used to analyse the data collected from the online survey, which gathered text-based opinions from 209 participants on the cost-benefit aspects of circularity strategies. The structured survey, which collected data from 43 workshop participants, evaluated the perceived importance of CE strategies across various BLC phases and assessed the adoption of selected CE strategies in current or past projects. Finally, the Six Thinking Hats^® activity, employed in the round table discussions, generated ideas from 25 professionals regarding the broader implementation challenges and opportunities of CE in construction. The research findings highlight the need to bridge the gap between theory and practice by fostering active industry stakeholder involvement in the transition to a CE model. The analyses of the collected stakeholder opinions through the three activities contribute to proactive and collaborative efforts aimed at advancing resource equity in the construction sector and promoting just and inclusive resource use. In summary, this research offers a comprehensive understanding of stakeholders’ opinions on CE strategies and provides guidance for the development of targeted policies and strategies to accelerate the integration of CE principles in the construction industry.

This paper introduces an open-source dataset for speech synthesis in the Tatar language. The dataset comprises approximately 70 hours of transcribed audio recordings, featuring two professional speakers (one male and one female). Notably, it is the first large-scale dataset of its kind that is publicly available, aimed at promoting Tatar text-to-speech (TTS) applications in both academic and industrial contexts. The paper describes the procedures for developing the dataset, discusses the challenges faced, and outlines important future directions. To demonstrate the reliability of the dataset, baseline end-to-end TTS models were built and evaluated using the subjective mean opinion score (MOS) measure. The dataset, training recipe, and pre-trained TTS models are publicly available.