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This work aims to develop a web platform for inspecting roof structures for technical assistance supported by drones and artificial intelligence. The tools used were HTML, CSS and JavaScript languages; Firebase software for infrastructure; and Custom Vision for image processing.

This study adopted the design science research approach, and the main stages for the development of the web platform include (1) creation and validation of the roof inspection checklist, (2) validation of the use of Custom Vision as an image recognition tool, and (3) development of the web platform.

The results of automatic recognition showed a percentage of 77.08% accuracy in identifying pathologies in roof images obtained by drones for technical assistance.

This study contributed to developing a drone-integrated roof platform for visual data collection and artificial intelligence for automatic recognition of pathologies, enabling greater efficiency and agility in the collection, processing and analysis of results to guarantee the durability of the building.

For better mapping the path of intellectual capital (IC) research, the purpose of this paper is to selectively review empirical studies of IC published, and identify theories, components and three dimensions of analysis: national IC (NIC), regional IC (RIC) and organizational IC (OIC).

The systematic literature review (SLR) subject to analysis is based on empirical studies made between 1960 and 2016, and focuses on three dimensions of analysis: NIC, RIC and OIC. Four research questions were designed, using the following databases, namely, Web of Science, Scopus and Google Scholar, for data collection purposes.

The SLR unveils a multidimensional taxonomy for measuring and classifying the type of IC applicable to the different levels of analysis and provides some recommendations for future studies of NIC, RIC and OIC, by outlining the need for clear definitions of components and measures of IC and identifying strengths, limitations and future research avenues.

In order to fill the gap found in the literature and the non-existence of a study clarifying the multiple dimensions of analysis of IC, this SLR makes a twofold, original contribution to the literature on management: providing an SLR of the main empirical studies dealing with different units of analysis; and identifying a multidimensional taxonomy for measuring and classifying the type of IC applicable to the different levels of analysis.

Through a literature review, a gap has been identified regarding the role of competition as a driver of social network (SN) usage. This study aims to design to address this gap, seeking motivators for SN usage based on how SN consumption may be related to users’ experience of competition. Therefore, the purpose of this study is to investigate the influence of competition in social media usage.

The authors used an exploratory qualitative approach, conducting a set of focus groups with young social media users. Data was analyzed with software.

Two new drivers for SN use are proposed, namely, competition and collective narrative.

This is an exploratory study, and it does not seek to generalize results or quantify causal relationships among variables.

This paper offers SN managers a deeper understanding of key growth drivers for these media.

This research can help society understand and debate the impacts of SNs on users’ lives, providing insights into drivers of excessive usage.

This paper proposes the following two SN usage drivers yet to be described in the literature: competition and collective narrative.