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Ready-mix concrete delivery problem (RMCDP), a specific version of the vehicle routing problem (VRP), is a relevant supply-chain engineering task for construction management with various formulations and solving methods. This problem can range from a simple scenario involving one source, one material and one destination to a more challenging and complex case involving multiple sources, multiple materials and multiple destinations. This paper presents an Internet of Things (IoT)-supported active building information modeling (BIM) system for optimized multi-project ready-mix concrete (RMC) delivery.

The presented system is BIM-based, IoT supported, dynamic and automatic input/output exchange to provide an optimal delivery program for multi-project ready-mix-concrete problem. The input parameters are extracted as real-time map-supported IoT data and transferred to the system via an application programming interface (API) into a mixed-integer linear programming (MILP) optimization model developed to perform the optimization. The obtained optimization results are further integrated into BIM by conventional project management tools. To demonstrate the features of the suggested system, an RMCDP example was applied to solve that included four building sites, seven eligible concrete plants and three necessary RMC mixtures.

The system provides the optimum delivery schedule for multiple RMCs to multiple construction sites, as well as the optimum RMC quantities to be delivered, the quantities from each concrete plant that must be supplied, the best delivery routes, the optimum execution times for each construction site, and the total minimal costs, while also assuring the dynamic transfer of the optimized results back into the portfolio of multiple BIM projects. The system can generate as many solutions as needed by updating the real-time input parameters in terms of change of the routes, unit prices and availability of concrete plants.

The suggested system allows dynamic adjustments during the optimization process, andis adaptable to changes in input data also considering the real-time input data. The system is based on spreadsheets, which are widely used and common tool that most stakeholders already utilize daily, while also providing the possibility to apply a more specialized tool. Based on this, the RMCDP can be solved using both conventional and advanced optimization software, enabling the system to handle even large-scale tasks as necessary.

This study aims to analyse the influence of the pillars (hard and soft skills) of digital academic entrepreneurship on students' entrepreneurial intention.

This was done by adopting a quantitative methodology involving empirical research with a sample of 761 university students from two countries and adopting structural equation analysis to validate the theoretical model proposed.

The results indicate a direct influence between hard and soft skills and entrepreneurial intention, and a positive, indirect influence between these and entrepreneurial intention mediated by the dimensions of the theory of planned behaviour (TPB) – entrepreneurial attitude, subjective norms and perceived behavioural control. Therefore, the pillars of digital academic entrepreneurship have a direct and indirect influence on university students' entrepreneurial intention.

This study also contributes to better operationalization of entrepreneurial education in university environments, since the development of hard and soft skills can be planned better based on the model proposed here. Considering the relations between the dimensions of hard and soft skills and those of TPB, this study shows there can be an influence on students' entrepreneurial intention.

In this study, a new and innovative construct is inserted in the model of entrepreneurial intention: “structural pillars of digital academic entrepreneurship” through structural equation modelling, to determine the degree of influence of these pillars (hard and soft skills) constructs on HEI students' entrepreneurial intention.

This study aims to analyze the configuration of the board of directors of the five largest banks operating in Brazil, which are members of a financial elite that directly influences the socioeconomic life in Latin America.

This assessment is inspired by Bourdieu's sociological approach and in the discussion on his work in organization studies and economic sociology. It addresses the organization as a field and investigates its associated field of power. The authors conducted qualitative research and relationally analyzed data related to the trajectory and the social properties of the councilors using the statistical technique called multiple correspondence analysis (MCA).

The results show that forms of social and cultural capital are particularly influential in the production of distinctions among banks' board members. Moreover, councils' priorities and configurations are diverse: some idealized and based on knowledge, others pragmatic and based on customs, others still anchored in a double logic of market satisfaction and family wealth preservation.

Understanding the objective power relations among these top agents may be crucial for effectively regulating certain aspects of their activities. Furthermore, understanding how different forms of capital affect the relative position of the board members may help us reduce representative bias in what seems today an inner circle.

This study is relevant because it makes an in-depth analysis of the composition of one of the most influential financial elites in Latin America, combining sociological theory and advanced statistical techniques for qualitative grouping (MCA).