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Recognizing the importance of sustainable development, environmental economic practices have gained significant attention globally as effective measures to mitigate environmental degradation and promote resource conservation. Therefore this study identifies and evaluates the barriers hindering the implementation of environmental economic practices in the Nigerian construction industry.

A quantitative research approach, utilizing a well-structured questionnaire, was employed to collect data from construction professionals. The Shapiro-Wilk normality test was utilized to assess the normality of the data, while the Kruskal-Wallis H-test was employed to investigate potential significant differences in opinions among various categories of respondents. Subsequently, exploratory factor analysis was conducted to identify underlying patterns and relationships within the collected data.

The top five barriers were: prioritization of short-term financial gain over long-term benefits, inefficient and unreliable energy supply systems, inadequate disposal and management of waste, insufficient funding and investment and high costs associated with sustainable construction practices. Furthermore, four critical clusters of barriers were revealed, which are regulatory-related, financial and economic-related, technical and logistical-related and knowledge-related.

These clusters can guide policymakers, industry professionals and educators in developing tailored strategies to overcome barriers within each specific category, fostering a more holistic and effective approach toward sustainable practices in the construction sector.

The findings of this study were compared with results from similar cases in Iran, China and New Zealand to provide a cross-cultural perspective on challenges faced by different regions. This comparative analysis aims to identify both commonalities and unique factors, contributing to a much deeper understanding of sustainable construction practices on a global scale.

Teleworking, working from home and flexible work have gained popularity over the last few years. A shift in policies and practices in the workplace is required owing to the COVID-19 pandemic accelerating current trends in work-from-everywhere (WFE) research. This article presents a systematic literature review of WFE research from 1990 to early 2023 to understand the transformation of the field.

The Web of Science database was used to conduct this review based on rigorous bibliometric and network analysis techniques. The prominence of the research studied using SPAR-4-SLR and a collection of bibliometric techniques on selected journal articles, reviews and early access articles. Performance and keyword co-occurrence analysis form the premise of cluster analysis. The content analysis of recently published papers revealed the driving and restraining forces that help define and operationalize the concept of WFE.

The major findings indicate that the five established and accelerated trends from cluster analysis are COVID-19 and the pandemic, telework(ing), remote working, work from home and well-being and productivity. Driving and restraining forces identified through content analysis include technological breakthroughs, work–life integration challenges, inequality in the distribution of jobs, gender, shifts in industry and sector preferences, upskilling and reskilling and many more have been published post-COVID in the restraining forces category of WFE.

A key contribution of this pioneering study of “work from everywhere” is the linking of the bibliometric trends of the past three decades to the influencing and restraining factors during the pandemic. This study illustrates how WFE could be perceived differently post-COVID, which is of great concern to practitioners and future researchers.

A wide range of publications on WFE and multiple synonyms can create confusion if a systematic and effective system does not classify and associate them. This study uses both bibliometric and scientometric analyses in the context of WFE using systematic literature review (SLR) methods.