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This paper aims to examine the Brazilian stock market behavior and volatility term structure of two portfolios that, theoretically, the companies that comprise them have different degrees of idiosyncratic risk: one portfolio consists of firms with good corporate governance and the other comprises firms with poor corporate governance.

The sample comprises corporate firms listed in the Brazilian stock market during the period from January 2008 to December 2017. Generalized autoregressive conditional heteroskedasticity models were applied.

The results show that the portfolio of firms with good corporate governance practices presents fluctuations that are more often temporary and reactive, with trends’ persistence of shorter durations, when considering the punctual volatility of the parameters estimated. This opposed expectation that the portfolio comprised of companies with good governance practices are better protected from short-term movements. However, over time and with standard error measures in consideration, both portfolios’ volatilities behave in similar ways. These findings may be related to Brazilian market characteristics, such as ownership concentration, ineffective corporate boards and the ever-developing nature of the stock market in Brazil. Any one of these characteristics present challenges to effective enforcement of the corporate governance practices in the Brazilian context.

The findings are potentially to the interest of researchers and practitioners for several reasons. First, this paper contributes to the growing literature on the relationship between corporate governance and market volatility. Second, it informs that volatility in the Brazilian context is likely only partially, if at all, influenced by corporate governance practices. Third, longitudinally, both indices follow the same pattern and converge to the same place.

Risk management has been crucial to investors and regulators for pursuing market diversification opportunities and developing strategies to ensure market stability. This study examines the dependence structures of volatility, related to co-movements and macroeconomic effects, among Latin American stock markets and the risk–return spectrum benefits in the Latin American market using time-varying returns and volatility forecasts within a multivariate structure.

The sample comprised the largest stock markets in Latin America during the period from January 2000 to December 2017 and copulas and multivariate models were applied.

The results indicated that the copula with the best fit for modeling the dependence structure of the markets was symmetric Joe-Clayton with time-varying parameters. The dependence volatility structure was higher in the positive (upper tail) than in the negative (lower tail) returns, which may indicate that the Latin American markets had diversification benefits during downturns. Evidence of market coupling was found during times of the global crisis (subprime crisis) in Latin America. The presence of monetary and temporal effects over the dependence structures suggests that investors may obtain gains in a multivariate structure with copula distributions.

The findings will be of interest to researchers and practitioners for several reasons. First, this study contributes to the growing literature on the relationship between market dependence and volatility. Second, it indicates that the Latin American markets may present diversification advantages during downturns. Third, it informs the influence of macroeconomic effects on Latin American markets. The models that included the nonnormal and asymmetric characteristics of the financial market yielded better results in terms of less information loss and data adherence.

The purpose of this paper is to investigate what board characteristics affect companies in periods of financial distress (FD) among non-financial Brazilian firms and examine which model best fits to predict FD.

The sample comprises data from 2010 to 2016 of the non-financial Brazilian firms listed on the Brazilian Stock Exchange. To measure this relationship, a conditional logistic regression is performed.

A U-shaped relationship between the size of the board of directors (BD) and FD is found in all models, indicating an optimal number of six members in the BD during the period of FD. However, board characteristics (related to composition and directors’ independence) are insufficient to align the shareholders’ interests and unsuitable for avoiding or even reducing FD in firms when other factors are neglected. Furthermore, the results reveal what variables provide the best-fitting models to predict FD.

To the best of the authors’ knowledge, this is the first study that investigates how the composition of the BD affects the FD likelihood in the Brazilian context. The findings are potentially of interest to researchers and practitioners since this paper contributes to the growing literature on the influence of corporate governance mechanisms in periods of FD and the understanding of its prediction models.

To develop an analysis methodology to evaluate the dynamic behaviour and fatigue assessment of highway bridges due to vehicle passage on irregular pavement surfaces. The approach considers the non-deterministic nature of the parameters of the vehicle-bridge system using Monte Carlo simulations.

In the proposed approach, 11 vehicle-bridge system parameters are modelled as random variables with predefined probability distributions. The dynamic analysis considers the vehicle-structure-pavement interaction, in which road surface roughness is defined based on the use of the power spectral density function, as an expression of the road surface random irregularities. Based on the results of the dynamic analysis, a fatigue assessment is performed. To demonstrate the applicability of the methodology, a case study of a 40-m-span steel-concrete composite highway bridge was selected, considering two levels of pavement quality.

The results reveal that vehicle speed, sprung masses, bridge mass and rear axle and tire stiffness are the parameters that most influence vertical displacement, bending stress and fatigue life. Numerical simulations showed that the pavement deterioration reduced fatigue life by up to 98.6%, increasing the failure probability.

The dynamic behaviour and fatigue of a highway bridge are evaluated by means of vehicle-structure interaction analyses, in which the randomness of 11 parameters of the vehicle-bridge system is simulated. This includes dynamic parameters of the suspension and tires, whose variability is rarely considered due to the difficulty in obtaining sample data.

This study uses the antecedents, decisions and outcomes (ADO) framework to identify how perceived risks and benefits relate to the omnichannel strategy and influence consumer behavior.

A systematic review was conducted on 111 articles (2014–2023) on Scopus using NVivo® software for content analysis.

The literature on omnichannel is fragmented between journals and lines of research, making it difficult to identify influential journals in the area and preventing effective convergence. When the perception of risk is greater than the perception of benefits, companies must understand how to mitigate the risk, so that the adoption of an omnichannel strategy is not canceled.

The review is limited to one database and does not consider specific products/services or consumer profiles.

This review broadens understanding of omnichannel from a perspective neglected by researchers, namely risks and benefits and their impacts on organizational results. The model will clarify how the literature on omnichannel has evolved and instigate new research.

This paper aims to deepen the understanding of the service design concept by critically analyzing the existing servitization literature. The paper’s main purpose is to structure service design and offer a clear understanding of how it should be applied.

A systematic literature review was conducted within servitization literature to understand the evolution of the service design concept. The authors use service design pillars (i.e. user-centered, co-creative, sequencing, evidencing and holistic) as a theoretical framework to explain how service design should be effectively incorporated into the servitization journey.

The findings expose a discordant interpretation of the pillars underpinning service design, revealing a paradoxical comprehension that jeopardizes its practical advancement within the servitization literature. The authors propose that service design should first be seen holistically, then target user-centered practices for sequencing service development steps, and finally, co-creating with partners to make the service evident to users. Furthermore, the authors contextualize service design within contemporary and traditional service-related issues such as servitization innovation, customer experience, service-dominant logic, service ecosystems and digital transformation.

This research pinpoints the service design concept’s shortcomings in the servitization literature. The study promotes a critical reflection on the service design concept and its current application, providing avenues for future research.

This study aims to analyze the phenomenon of entrepreneurial spawning in the new context of software startups, revisiting theory and identifying patterns within the emergence of startups/spin-offs in Brazil.

A study of two cases of startups recognized for generating several spin-offs founded by former employees. The authors based the data collection on the following triangulation: 11 in-depth interviews, systematic analysis of 33 resumes from entrepreneurs in spawned firms and document analysis.

Six skills developed in startups were identified: (1) structuring a company, (2) people management, (3) strategic/operational planning, (4) commercial/sales, (5) product development, and (6) behavioral traits. In addition, points of contradiction concerning the literature were found, such as the absence of the location effect, different professional experiences and new local agents to support startups.

The present study covers only two cases in the context of software startups, which requires caution and discretion in extrapolating to other contexts.

The understanding of the phenomenon may reflect in: university programs focused on internships in startups, corporate training programs for entrepreneurs and the design of public policies based on entrepreneurial spawning.

The present study stands out for its access to data from high-impact startups in Brazil, in addition to revisiting the literature bringing a new perspective to the specificities of high-growth software companies.

This paper aims to examine the relationship between the main decisions for designing distribution centers (DCs) and the contextual characteristics of the distribution networks.

Experts were surveyed and responses analyzed quantitatively through multivariate data techniques. This study considered four contextual characteristics that were deemed as influential for DC design: types of routes in the distribution network, quantity of DCs, distribution network levels and company size.

This paper evidenced which decisions are affected by each contextual characteristic encompassed in this study. This paper identified that the characteristic types of route in the distribution network must be carefully considered, as it had the greatest amount of associations with the decisions for designing a DC.

Despite its importance, most studies on design of DCs disregard the effect of the context in which DCs are inserted. This research provides arguments to support decision-making process of DCs design, increasing assertiveness of their planning. This work fulfills a literature gap by empirically examining the effect of contextual variables on the decisions related to DC design. Regarding practice, this paper addressed a fundamental issue for managers looking to design a DC, as it evidenced how contextual characteristics impact the decision-making.

The purpose of this research is to establish a robust numerical framework for the calibration of macroscopic constitutive parameters, based on the analysis of polycrystalline RVEs with computational homogenisation.

This framework is composed of four building-blocks: (1) the multi-scale model, consisting of polycrystalline RVEs, where the grains are modelled with anisotropic crystal plasticity, and computational homogenisation to link the scales, (2) a set of loading cases to generate the reference responses, (3) the von Mises elasto-plastic model to be calibrated, and (4) the optimisation algorithms to solve the inverse identification problem. Several optimisation algorithms are assessed through a reference identification problem. Thereafter, different calibration strategies are tested. The accuracy of the calibrated models is evaluated by comparing their results against an FE2 model and experimental data.

In the initial tests, the LIPO optimiser performs the best. Good results accuracy is obtained with the calibrated constitutive models. The computing time needed by the FE2 simulations is 5 orders of magnitude larger, compared to the standard macroscopic simulations, demonstrating how this framework is suitable to obtain efficient micro-mechanics-informed constitutive models.

This contribution proposes a numerical framework, based on FE2 and macro-scale single element simulations, where the calibration of constitutive laws is informed by multi-scale analysis. The most efficient combination of optimisation algorithm and definition of the objective function is studied, and the robustness of the proposed approach is demonstrated by validation with both numerical and experimental data.

This paper aims to explore the impacts of a blockchain network implementation to support purchasing processes of a Brazilian public organization.

The Grumbach method was used to build the scenarios. Five experts with knowledge in blockchain and experience in public procurement were consulted on 20 possible preliminary events, defining their probability of occurrence and relevance. The data obtained were processed in Puma software, which returned a selection of ten definitive events, based on probability, relevance and standard deviation indicators, generating a map of prospective scenarios.

Three following scenarios are shown, the ideal scenario, the one with greater implantation benefits and fewer complications; the trend scenario, more likely to occur under current conditions; and the most likely scenario of occurrence, according to experts. The results indicated which simulated events are drivers (motives), and which are influenced (dependent). They were categorized as opportunities or threats to the deployment of the technology.

Although public procurement processes are standardized by Brazilian legislation, new events may arise from the replication of the model in different organizations. The research revealed the need for practical testing in a simulated public procurement environment.

The article explores the interaction between disruptive network technology and processes linked to public sector efficiency. Studies on electronic government point to the future of public management.