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The purpose of this paper is to investigate the mechanical behavior and propagation of cracks of numerical granite samples through the Brazilian split test and to provide a reference for predicting the behavior of real granite samples.

The numerical models of granite containing two fissures are established using the parallel bond model (PBM) and the smooth joint model (SJM) in PFC2D. The peak stresses, number of cracks and anisotropic ratios are obtained to study the influence of the mineral composition and the angle of inclination of rock bridge on the strength, failure mode and deformation characteristics.

The numerical results obtained show that the mineral composition has a marginal influence on the peak stress. When the angle of inclination of rock bridge β increases, the peak stress drops to its minimum value at β = 90° and then gradually increases to a relatively low level. The behavior of cracks falls into three categories based on the distribution of cracks. By analyzing the stress–strain curve and the process of crack propagation for sample No. 4 with β = 60°, it is found that the process of failure can be divided into four stages and tensile cracks dominate. The anisotropic ratios of peak stress and a number of cracks obtained show that the peak stress is low anisotropic and the number of cracks is medium anisotropic.

This paper presents a numerical simulation method to analyze mechanical behavior and propagation of cracks under different conditions. The proposed method and the results obtained are useful for predicting the behavior of real granite samples in laboratory and engineering projects.

Continua and discontinua coexist in natural rock materials. This paper aims to present an improved approach for addressing the mechanical response of rock masses based on the combined finite-discrete element method (FDEM) proposed by Munjiza.

Several algorithms have been programmed in the new approach. The algorithms include (1) a simpler and more efficient algorithm to calculate the contact force; (2) An algorithm for tangential contact force closer to the actual physical process; (3) a plastic yielding criterion (e.g. Mohr-Coulomb) to modify the elastic stress for fitting the mechanical behavior of elastoplastic materials; and (4) a complete code for the mechanical calculation to be implemented in Matrix Laboratory (MATLAB).

Three case studies, including two standard laboratory experiments (uniaxial compression and Brazilian split test) and one engineering-scale anti-dip slop model, are presented to illustrate the feasibility of the Y-Mat code and its ability to deal with multi-scale rock mechanics problems. The results, including the progressive failure process, failure mode and trajectory of each case, are acceptable compared to other corresponding studies. It is shown that, the code is capable of modeling geotechnical and geological engineering problems.

This article gives an improved FDEM-based numerical calculation code. And, feasibility of the code is verified through three cases. It can effectively solve the geotechnical and geological engineering problems.

This study aims to evaluate the presence of abnormal returns due to stock splits or reverse stock splits in the Brazilian capital market context.

The event study technique was used on data from 518 events that occurred in a 30-year period (1987–2016), comprising 167 stock splits and 351 reverse stock splits.

The results revealed the occurrence of abnormal returns around the time the shares began trading stock splits or reverse stock splits at a statistical significance level of 5%. The main conclusion is that stock split and reverse stock split operations represent opportunities for extraordinary gains and may serve as a reference for investment strategies in the Brazilian stock market.

This study innovates by including reverse stock splits, as the existing literature focuses on stock splits, and by testing two distinct “zero” dates that of the ordinary general meeting that approved the share alteration and the “ex” date of the alteration, when the shares were effectively traded, reverse split or split.

The purpose of this study is to examine the moderating effect of an exogenous corporate governance shock that curbs Chief Executive Officers’ (CEOs) power on the relationship between CEO narcissism and earnings management practices.

The authors performed a quasi-experiment using a differences-in-differences approach to examine Brazil’s duality split regulatory change on 101 Brazilian public firms during the period 2010–2022.

The main findings indicate that the introduction of duality split curtails the positive influence of CEO narcissism on earnings management, suggesting that this corporate governance regulation may act as a complementary corporate governance mechanism in mitigating the negative consequences of powerful narcissistic CEOs. Further robustness checks indicate that the results remain consistent after using entropy balancing and alternative measures of CEO narcissism.

In emerging markets, where governance systems are frequently perceived as less than optimal, policymakers and regulatory authorities can draw insights from this enforcement to shape governance systems, reducing CEO power and, consequently, improving the quality of financial reporting.

To the best of the authors’ knowledge, this is the first study to examine whether a duality split mitigates the influence of CEO narcissism on earnings management. Thus, this study contributes to the corporate governance literature that calls for research on the effectiveness of external corporate governance mechanisms in emerging markets as well as the CEO narcissism literature that calls for research on moderating factors that could curtail negative consequences of narcissistic CEO behavior.

Accurate presentation of the rock microstructure is critical to the grain-scale analysis of rock deformation and failure in numerical modelling. 3D granite microstructure modelling has only been used in limited studies with the mineral pattern often remaining poorly constructed. In this study, the authors developed a new approach for generating 2D and 3D granite microstructure models from a 2D image by combining a heterogeneous material reconstruction method (simulated annealing method) with Voronoi tessellation.

More specifically, the stochastic information in the 2D image is first extracted using the two-point correlation function (TPCF). Then an initial 2D or 3D Voronoi diagram with a random distribution of the minerals is generated and optimised using a simulated annealing method until the corresponding TPCF is consistent with that in the 2D image. The generated microstructure model accurately inherits the stochastic information (e.g. volume fraction and mineral pattern) from the 2D image. Lastly, the authors compared the topological characteristics and mechanical properties of the 2D and 3D reconstructed microstructure models with the model obtained by direct mapping from the 2D image of a real rock sample.

The good agreements between the mapped and reconstructed models indicate the accuracy of the reconstructed microstructure models on topological characteristics and mechanical properties.

The newly developed reconstruction method successfully transfers the mineral pattern from a granite sample into the 2D and 3D Voronoi-based microstructure models ready for use in grain-scale modelling.

The correlations between mechanical behaviour, tensile strength, and rock parameters of metasedimentary rock samples in Karak, Pahang’s New Austrian Tunnelling Method (NATM) were statistically evaluated from the rock mechanic laboratory works at the selected sections around 2,000 m of the tunnel (named as NATM-1). According to a statistical analysis, lithotypes, geological structures, and region geology have a significant impact on the mechanical behaviour of the metasedimentary rock. In the Brazilian test, the fracture behaviour of the disc specimens was highly related to the reliability and precision of the experimental data by validations of methods. In this work, the impact of different loading methods and rock lithotypes on the failure mechanism of Brazilian discs was examined utilising five different metasedimentary rock types and three different loading methods. During the loading operation, the strain and displacement fields of the specimens were recorded and evaluated using a computerised strain gauge system. The rock types, according to experimental data, have a significant impact on the peak load and deformation properties of Brazilian discs. With the method below, tensile strength point of a disc specimen is clearly regulated by the material stiffness and tensile–compression ratio. Seismic occurrences have had a substantial impact on changing the rock and exerting forces that may affect its mechanical characteristics as well as its vulnerability to weathering effects or discontinuities. As a result, the goal of this study is to look into the connection between rock mechanics and metasedimentary rock stress analysis in NATM-1, Karak, Pahang.

Given the importance of credit rating agencies’ (CRAs) assessment in affecting international financial markets, it is useful for policymakers and investors to be able to forecast it properly. Therefore, this study aims to forecast sovereign risk perception of the main agencies related to Brazilian bonds through the application of different machine learning (ML) techniques and evaluate their predictive accuracy in order to find out which one is best for this task.

Based on monthly data from January 1996 to November 2018, we perform different forecast analyses using the K-Nearest Neighbors, the Gradient Boosted Random Trees and the Multilayer Perceptron methods.

The results of this study suggest the Multilayer Perceptron technique is the most reliable one. Its predictive accuracy is relatively high if compared to the other two methods. Its forecast errors are the lowest in both the out-of-sample and in-sample forecasts’ exercises. These results hold if we consider the CRAs classification structure as linear or logarithmic. Moreover, its forecast errors are not statistically associated with periods of changes in CRAs’ opinion of any sort.

To the best of the authors’ knowledge, this study is the first to evaluate the performance of ML methods in the task of predicting sovereign credit news, including not only the sovereign ratings but also the outlook and credit watch status. In addition, the authors investigate whether the forecasts errors are statistically associated with periods of changes in sovereign risk perception.

The purpose of this paper is to study the impact of the real exchange rate on investment in the Brazilian manufacturing industry.

The authors develop an investment model that considers the effect of changes in the real exchange rate, taking into account that the effect of the real exchange rate on the Brazilian manufacturing investment operates through demand and cost channels. The composition of these effects varies across manufacturing sectors, with different repercussions on investment decisions, depending on sectoral characteristics. A panel data analysis is applied to estimate the model for the Brazilian manufacturing sectors from 1996 to 2010.

One main result is that the responsiveness of the Brazilian manufacturing investment to real exchange rate varies considerably across manufacturing sectors. Overall, the results contribute to a better understanding of the relationship between exchange rate dynamics, manufacturing investment and industrial development, thus unveiling important empirical elements for the debate on industrial policies to stimulate manufacturing investment and production.

As the (scant) empirical literature on real exchange rate and investment in Brazil has invariably been using aggregate data, this paper contributes to the literature by obtaining sectoral estimates of the responsiveness of manufacturing investment to exchange rate fluctuations that further the understanding of the complex relationship between these economic variables.

The purpose of this paper is to compare the factors that can influence the tacit knowledge sharing (KS) in two different cultures by investigating information technology professionals (IT) in Brazil and Indonesia.

A survey method was used and a standard questionnaire was applied. The sample size comprised 115 respondents from Brazil and 86 participants from Indonesia. A partial least squares analysis was used to assess the structural and confirmatory models and test the hypotheses.

The results indicate that, in both cultures, IT workers who are committed to the organization are more likely to engage in tacit KS behavior. Similarly, strong social ties play an important role in the willingness to share tacit knowledge. Also, there are major differences between the organizational cultures; for instance, whereas Brazilians seem to be influenced by team-oriented cultures, Indonesians seem to be indifferent.

Limitations include the small sample size as only two cultures were chosen to assess the differences and the representation of just one professional category (IT).

This paper provides theoretical contributions as the literature lacks a macro-level analysis on the KS comparison between countries. The results advance the comprehension of tacit KS phenomenon by testing in a cross-country comparison the mediation effect of organizational commitment. To practitioners, this research presents important empirical contributions indicating how organizational culture, social environment, personality traits and employee commitment impact an individual’s willingness to share tacit knowledge with their coworkers.

This paper seeks to identify collaboration elements and evaluate their intensity in the Brazilian supermarket retail chain, especially the manufacturer‐retailer channel.

A structured questionnaire was elaborated and applied to 125 representatives from suppliers of large supermarket chains. Statistical methods including multivariate analysis were employed. Variables were grouped and composed into five indicators (joint actions, information sharing, interpersonal integration, gains and cost sharing, and strategic integration) to assess the degree of collaboration.

The analyses showed that the interviewees considered interpersonal integration to be of greater importance to collaboration intensity than the other integration factors, such as gain or cost sharing or even strategic integration.

The research was conducted solely from the point of view of the industries that supply the large retail networks. The interviews were not conducted in pairs; that is, there was no application of one questionnaire to the retail network and another to the partner industry.

Companies should invest in conducting periodic meetings with their partners to increase collaboration intensity, and should carry out technical visits to learn about their partners' logistic reality and thus make better operational decisions.

The paper reveals which indicators produce greater collaboration intensity, and thus those that are more relevant to more efficient logistics management.