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This paper is concerned with new formulations of local meshfree and finite element numerical methods, for the solution of two-dimensional problems in linear elasticity.

In the local domain, assigned to each node of a discretization, the work theorem establishes an energy relationship between a statically admissible stress field and an independent kinematically admissible strain field. This relationship, derived as a weighted residual weak form, is expressed as an integral local form. Based on the independence of the stress and strain fields, this local form of the work theorem is kinematically formulated with a simple rigid-body displacement to be applied by local meshfree and finite element numerical methods. The main feature of this paper is the use of a linearly integrated local form that implements a quite simple algorithm with no further integration required.

The reduced integration, performed by this linearly integrated formulation, plays a key role in the behavior of local numerical methods, since it implies a reduction of the nodal stiffness which, in turn, leads to an increase of the solution accuracy and, which is most important, presents no instabilities, unlike nodal integration methods without stabilization. As a consequence of using such a convenient linearly integrated local form, the derived meshfree and finite element numerical methods become fast and accurate, which is a feature of paramount importance, as far as computational efficiency of numerical methods is concerned. Three benchmark problems were analyzed with these techniques, in order to assess the accuracy and efficiency of the new integrated local formulations of meshfree and finite element numerical methods. The results obtained in this work are in perfect agreement with those of the available analytical solutions and, furthermore, outperform the computational efficiency of other methods. Thus, the accuracy and efficiency of the local numerical methods presented in this paper make this a very reliable and robust formulation.

Presentation of a new local mesh-free numerical method. The method, linearly integrated along the boundary of the local domain, implements an algorithm with no further integration required. The method is absolutely reliable, with remarkably-accurate results. The method is quite robust, with extremely-fast computations.

This study aims to analyze the university environment’s role in the intention–action gap (IAG)of highly successful startup founders in an emerging market.

Using multiple regression analysis, this study analyzed data collected from 314 founders representing 99 successful startups (289 valid observations), renowned for their high funding and value operating in an emerging market, Brazil.

The results demonstrate that extracurricular activities and exchange programs lead to a reduced IAG while living in a significant economic center extends it. Computer science and industrial engineering students show reduced IAGs. Studying together with future co-founders also leads to reduced gaps.

The study contributes to the microfoundations theory by presenting new interactions between students and the university environment that influence entrepreneurial action. Limitations are related to the sample, limited to Brazilian founders and selected only through venture capital firms’ filters.

This study also provides practical insights to the universities’ leaders on how they can create programs that improve the rate of startup creation, potentially leading to successful companies.

This study investigates the association between the university role and the entrepreneur’s IAG in emerging markets. The entrepreneur’s IAG is still a relatively new phenomenon explored in entrepreneurship. Even less understanding and limited empirical data exist on successful startups from emerging markets. This study drew on the microfoundations literature to answer how universities in emerging markets could address specific resources and entrepreneurship programs to reduce the IAG among students and alumni.

This article aims at the understanding of specific spaces where entrepreneurship education (EE) happens – inside and outside the classroom.

Building on frameworks such as formal versus non-formal entrepreneurial education and institutional versus non-institutional actors, this research applies structural equation modeling (SEM) to explore which spaces entrepreneurs attended as undergraduate students. Going beyond intentionality, the authors collected data from 175 respondents in Brazil, all of the respondents are entrepreneurs whose companies are at least one year old.

Results demonstrate that student-led activities are as important as institutional ones when training future entrepreneurs, while specific in-classroom activities feature the lowest impact among the institutional ones.

Sample size and characteristics could impact the generalization power, but, since the results fit within research criteria, researchers can benefit by reflecting over new research horizons, going beyond classroom studies and understanding the university as an ecosystem of learning interventions.

Results can be useful to university managers when designing institutional policies, fostering a diverse set of undergraduate experiences towards entrepreneurship training.

Although current literature has focused on classroom education, researchers have been pointing out the need of stepping out of the classroom, analyzing other spaces such as student-led movements, co-curricular programs and more.