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The purpose is to investigate whether Brazilian e-commerce nonusers all have the same reasons not to purchase online or whether different behavior patterns might lead them to cluster in different groups.

This study carried out cluster analyses on a large sample (N = 9,065) from a nationwide survey on the use of information and communication technology in Brazil.

Three clusters of e-commerce nonusers were identified: the first cluster is quite reluctant; the second is characterized by disbelief in e-commerce; and the last cluster includes members who must see a product to believe it. Overall, nonusers have different reasons not to shop online, but they also share some similarities in this regard. Furthermore, socioeconomic factors do not seem to affect their behavior. The findings suggest that merchants’ failure to attract customers’ attention and tangibility are the major barriers to e-commerce use.

Even though nonusers have different reasons not to shop online, the key pattern that emerges is the value of tangibility for these individuals, which is a barrier present in all three clusters. This suggests that current marketing strategies and advertisements are ineffective to reach these consumers. Vendors should therefore try different approaches.

The findings contribute to the information systems (IS) literature by bringing a new perspective to the understanding of e-commerce rejection in addition to having managerial implications that involve strategies to attract potential users based on their specificities.

The present study aims to identify the practices employed to bring heirs into family businesses as successors.

We conducted an exploratory, qualitative investigation using a case study approach. Semi-structured face-to-face interviews were conducted with external consultants and with incumbent leaders, next-generation heirs working in the firm (and likely to become successors) and employees from three family firms from different industries and under ownership and control of different generations of their respective families (first, second and third and fourth generations). In addition to surveying their general perceptions of the succession processes in their firms, each informant was asked to rate the degree of importance of 12 succession practices identified in the literature and the extent to which they exist in their respective firms.

Our results showed that heirs typically enter the family business after a development process outside of the family business, which we have termed as coming back to the nest. This process was enacted through practices that we allocated to the following categories: continued development of heirs, developing relationships in the succession process, separation of roles and attitude of the successor heirs. Overall, 8 of the 12 practices derived from the theoretical framework were endorsed as important by representatives of the family businesses and 9 were endorsed by the consultants, 7 of which coincided in both groups. However, only 5 of the practices were identified as present in the firms’ succession processes by the representatives of the family businesses, while the consultants did not identify any of the 12 practices as present.

We present additional important practices, the adoption of which would be beneficial for family business succession, such as adapting external learning to the family business, acquiring leadership skills and experience and developing emotional intelligence. Our study advances the prior literature since we do not merely discuss succession planning but analyze in an applied manner how succession actually takes place in family businesses.

This study aims to examine the price and income elasticities of short- and long-run industrial electricity demand in Brazil between 2003 and 2020. The research also examines the impacts of COVID-19 in Brazil’s industrial electricity sector, including an analysis in states more and less industrialized.

Dynamic adjustments models in panel data are used to present robust estimates and analyze the impact of different methodologies on reported elasticities.

The short-run price elasticity is estimated at −0.448, while the long-run values are around −1.60. Regarding income elasticity, the value is 0.069 in the short-run and is concentrated in 0.25 in the long-run. The inelastic results of income show that the industrial demand for electric energy follows the trend of loss of competitiveness of the Brazilian industry in the past years. In addition, the price of natural gas, the level of employment, and, in specific cases, the level of imports also influence industrial electricity demand.

The research is a pioneer in the investigation of the industrial behavior of electricity of the Brazilian industrial branch, using as control variables, the average temperature, and the level of rainfall, this one, so important for a country whose main source is hydroelectric. In addition, to the best of the authors’ knowledge, it is the first study, which is prepared to analyze the effects of COVID-19 on electric consumption in the industrial sector, investigating these impacts, including in the states considered more and less industrialized. The estimates generated may help in the design of the Brazilian energy policy.

The aim of this paper was to analyze the role of the Cooperative of Farmers and Fishermen of the Lago do Cuniã Extractive Reserve (COOPCUNIÃ) in the inclusion of residents in the caiman meat value chain in Porto Velho, Brazil.

A total of six interviews were conducted with key actors to investigate the research problem in the Lago do Cuniã EXRES, namely the president and project advisor of the cooperative, two extractivist members of the cooperative and two non-member residents. The key actors were selected based on the following criteria: being over 18 years old, residing within the reserve and having participated in some stage of the caiman meat value chain.

The results demonstrate that the cooperative contributes to the inclusion of extractivist residents in the value chain, income generation and poverty reduction, enabling the production and marketing of caiman meat. Additionally, it overcomes challenges and improves the quality of life of the local population.

This study emphasizes the social and economic benefits for isolated regions with low productive development. For public policymakers, the results demonstrate that inclusion has enabled access to technology and markets. For the cooperative, it showcases actions oriented towards development, social inclusion and quality of life.

The originality of the article lies in the analysis of the role of a value chain within an environmental protection area in the Amazon, balancing economic, social and environmental factors.

O objetivo foi analisar o papel da Cooperativa dos Agricultores e Pescadores da Reserva Extrativista Lago do Cuniã (COOPCUNIÃ) na inclusão dos moradores na cadeia de valor da carne de jacaré em Porto Velho, Brasil.

Foram realizadas 06 (seis) entrevistas com atores-chave para investigar o problema de pesquisa na RESEX Lago do Cuniã, a saber: o presidente e o assessor de projetos da cooperativa, dois extrativistas cooperados e dois moradores não cooperados. Os atores-chave foram selecionados com base nos seguintes critérios: ser maior de 18 anos, residir na reserva e ter participado de alguma etapa da cadeia de valor da carne de jacaré.

Os resultados demonstram que a cooperativa contribui para a inclusão dos extrativistas na cadeia de valor, com a geração de renda e redução da pobreza, viabilizando a produção e comercialização da carne de jacaré. Além disso, supera desafios e melhora a qualidade de vida da população local.

Este estudo enfatiza os benefícios sociais e econômicos para regiões isoladas e com baixo desenvolvimento produtivo. Para os formuladores de políticas públicas, os resultados demonstram que a inclusão possibilitou o acesso à tecnologia e aos mercados. Para a cooperativa, mostra ações voltadas para o desenvolvimento, inclusão social e qualidade de vida.

A originalidade do artigo está na análise do papel de uma cadeia de valor dentro de uma área de proteção ambiental na Amazônia, equilibrando fatores econômicos, sociais e ambientais.

This study aims to propose an approach to assess the security of supply (SS) in a coal-fired electricity generation supply chain subject to public price regulation in Brazil. This study characterizes the Brazilian scenario of coal-fired electricity generation, which represents less than 3.5% of the energy sources.

Data from six mining companies that supply a coal plant were analyzed in a case study. The risks were characterized and objectively estimated through a synthetic multidimensional index. Structural changes in the earnings before interest, taxes, depreciation, amortization and exploration indicator time series of coal companies (CC) were statistically detected.

Empirical evidence demonstrates that the supply chain has a low disruption risk (SS index equal to 0.74). However, when suppliers are individually analyzed, 48.64% of all coal shows moderated disruption risk, and 2.51% is under high risk. In addition, this study finds a drop in the financial results of CC related to public regulation of coal prices. This impacts the security of coal supply.

This study discusses the influence of legal and regulatory policy risks in a coal power generation supply chain and the implications of the SS index as a management tool.

A novel SS index is presented and empirically operationalized, and its dimensions – environmental, occupational, operational, economic-financial and supply capacity – are analyzed.

This study aims to develop a machine learning model to detect structure fire fatalities using a dataset comprising 11,341 cases from 2011 to 2019.

Exploratory data analysis (EDA) was conducted prior to modelling, in which ten machine learning models were experimented with.

The main fatal structure fire risk factors were fires originating from bedrooms, living areas and the cooking/dining areas. The highest fatality rate (20.69%) was reported for fires ignited due to bedding (23.43%), despite a low fire incident rate (3.50%). Using 21 structure fire features, Random Forest (RF) yielded the best detection performance with 86% accuracy, followed by Decision Tree (DT) with bagging (accuracy = 84.7%).

Limitations of the study are pertaining to data quality and grouping of categories in the data pre-processing stage, which could affect the performance of the models.

The study is the first of its kind to manipulate risk factors to detect fatal structure classification, particularly focussing on structure fire fatalities. Most of the previous studies examined the importance of fire risk factors and their relationship to the fire risk level.