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The implementation of BIM in the construction industry requires the coevolution of the various aspects of the BIM ecosystem. The human dimension is a very important dimension of the ecosystem necessary for BIM implementation. It is imperative to study this aspect of the BIM ecosystem both from the employer perspective and employee availability to provide insights for stakeholders (job seekers, employers, students, researchers, policymakers, higher education institutions, career advisors and curriculum developers) interested in the labour market dynamics.

To understand the BIM actor roles through the employer lens and the actual BIM actors in the construction industry, this study employed data mining of job adverts from LinkedIn and Mncjobs website. Content analysis was employed to gain insights into the data collected. Also, through a quantitative approach, the existing BIM actor roles were identified.

The study identified the employers' expectations of BIM actors; however, it is noted that the BIM actor recruitment space is still a loose one as recruiters put out open advertisements to get a large pool of applicants. From the data analysed, it is concluded that the BIM actor role is not an entirely new profession. However, it simply exists as construction industry professionals with BIM tool skills. Also, the professional development route is not well defined yet.

This study presents a realistic angle to BIM actor roles hence enhancing BIM implementation from the human perspective. The findings present an insight into the preferred against the actual.

This study aims to investigate the effects of mineral rents, conflict and population growth on countries' growth, with a specific interest in 13 selected economies in Sub-Saharan Africa.

This paper uses a combination of research methods: the pooled ordinary least squares (OLS), the fixed effect and the system generalized method of moment (GMM). The consistent estimator (system GMM), which provides the paper's empirical findings, remedies the inherent endogeneity bias in the model formulation. The utilized panel dataset for the study spans from 1980 to 2022.

The study suggests that mineral rents positively affect countries' growth by about 0.407 percentage points in the short run. The study further demonstrates the long-run negative impacts of population growth rates and prevalence of civil war on economic growth. The empirical work of the study reveals that an increase in the number of international borders within the group promotes mineral conflicts, which impedes economic growth. Evidence from the specification tests performed in the study confirmed the validity of the empirical results.

Mineral rents, if well managed and conditioned on good institutions, are a blessing to an economy, contrary to the assumptions that mineral resources are a curse. The utilization of mineral rents in Sub-Saharan Africa for economic growth depends on several factors, notably the level of mineral conflicts, population growth rates, institutional factors and the ability to contain civil war, among others.

This study is the first attempt in the post-coronavirus disease 2019 (COVID-19) era to revisit the investigation of the impacts of mineral rents, conflict and population growth rates on the countries' growth while controlling for the potential implications of the qualities of institutions. One of the significant contributions of the study is the identification of high population growth rates as one of the primary drivers of mineral conflicts that impede economic growth in the states with enormous mineral deposits in Sub-Saharan Africa. The crucial inference drawn from the study is that mineral rents positively impact countries' growth, even with inherent institutional challenges, although the results could be better with good institutions.

The purpose of this study is to shed light on the twin transition in China in the organization of innovation processes in artificial intelligence (AI) and green technology (GT) development and to understand the role of foreign multinationals in Chinese innovation systems.

A qualitative research approach is used by interviewing executives from German multinationals with expertise in AI and GT development and organization of innovation processes in China. In total, 11 semi-structured interviews were conducted with companies, and the data were analysed with a thematic qualitative text analysis.

The findings show that AI applications for GT are primarily developed in cross-company projects that are led by local and regional authorities through the organization of industrial districts and clusters. German multinationals are either being integrated, remaining autonomous or being excluded from these twin transition innovation processes.

This paper aims to fill the gap in the literature by providing one of the first qualitative approach towards twin transition innovation processes in China and exploring the integration of multinational enterprises in cluster organizations. To the best of the author’s knowledge, this is one of the first twin transition studies from this perspective in emerging economies.