This article presents a bibliometric analysis of scientific publications investigating technological megatrends at the societal level, through the parallel analysis of 549 documents from Scopus and 291 documents in Web of Science (WoS) using the VOSviewer software and the Excel component of the MS Office 365 package. The main purpose of this study was to obtain an overview of the evolution of the research on the subject of technological megatrends from the perspective of interest, domains, geographical areas, sources, authors and cocitation networks, research clusters of countries, and cluster-related concepts. The results showed that publications on technological megatrends started in 1982, but from a scientific point of view they started in 1983 (Scopus) and 1984 (WoS), and that they display an increasing trend after 2010. Technological Forecasting and Social Change, Nature, SAE Technical Papers, VDI Berichte, Harvard Business Review, Advances in Intelligent Systems and Computing, and Sustainability represent the most important sources, and Gibbs, Kraemer, Dedrick, Kim, Chmiela, Sauceda, Müller, Tkatchenko, Pratt, Sarmiento, Montes, Ogilvie, Marcus, Perez, Brownson, D. Mourtzis, M. Doukas, and Bernidaki are the most notorious researchers in the field. At the societal level, technological megatrends are closely related to foresight, globalization, industry 4.0, the internet of things, digitalization, technology, artificial intelligence, innovation, the future, and sustainability. This study is original and useful for researchers in the context of the lack of similar studies on this subject.

The increasing pressure for transparency in corporate sustainability reporting, especially under frameworks such as the Corporate Sustainability Reporting Directive and the European Sustainability Reporting Standards, has raised the need for sector-specific models to integrate financial, social, and environmental indicators coherently and measurably. This study proposes a composite econometric model to assess the sustainability performance of companies in the construction sector in a digital context, a domain that remains underexplored despite its substantial economic and environmental impact. Drawing on a sample of 1600 Romanian construction companies over ten years (2013–2023), this study develops a multidimensional sustainability score and tests its financial drivers using ordinary least squares regression models. The model incorporates nine financial structure variables as predictors of sustainability outcomes across three dimensions—financial, social, and environmental—while ensuring robustness through heteroscedasticity and multicollinearity diagnostics. The results show that indicators such as the return on assets, debt ratio, and equity structure significantly influence sustainability performance, particularly in the financial and environmental dimensions. In contrast, the social dimension exhibits lower explanatory power. The findings suggest that financial resilience plays a critical role in shaping sustainable practices in the construction industry and support the adoption of integrated models for performance benchmarking and policy alignment.

The increasing pressure for transparency in corporate sustainability reporting, especially under frameworks such as the Corporate Sustainability Reporting Directive and the European Sustainability Reporting Standards, has raised the need for sector-specific models to integrate financial, social, and environmental indicators coherently and measurably. This study proposes a composite econometric model to assess the sustainability performance of companies in the construction sector in a digital context, a domain that remains underexplored despite its substantial economic and environmental impact. Drawing on a sample of 1,600 Romanian construction companies over a ten-year period (2013–2023), the study develops a multidimensional sustainability score and tests its financial drivers using Ordinary Least Squares regression models. The model incorporates nine financial structure variables as predictors of sustainability outcomes across three dimensions - financial, social, and environmental - while ensuring robustness through heteroscedasticity and multicollinearity diagnostics. Results show that indicators such as return on assets, debt ratio, and equity structure significantly influence sustainability performance, particularly in the financial and environmental dimensions. In contrast, the social dimension exhibits lower explanatory power. The findings suggest that financial resilience plays a critical role in shaping sustainable practices in the construction industry and support the adoption of integrated models for performance benchmarking and policy alignment.