ResumoMotivadas pelo aumento do consumo online, as plataformas de vendas virtuais ganharam destaque e cada vez mais públicos consumidores em âmbito mundial. Este trabalho tem como objetivo caracterizar o comportamento do consumidor em compras online e o que o influencia nas decisões de consumo, gerando o perfil do cliente no e-commerce. A pesquisa é descritiva de cunho quantitativo, envolvendo uma amostra de 390 respondentes. Os dados foram analisados por meio de análise estatística multivariada, constituída por análise descritiva, cruzamento de dados, análise de correlação e análise de variância. Os achados mais contundentes estão associados às principais motivações, preço, variedade e qualidade de produtos e pouco esforço/conveniência, para realizar compras pela internet. A tomada de decisão para compra pela internet, um dos constructos do modelo da pesquisa, está vinculada ao fato do público consumidor ter recursos de internet, bem como conhecimento e capacidade para usá-la. O perfil obtido é o de um público consumidor jovem que gasta menos de R$ 500,00 em uma compra e que adquire principalmente passagens aéreas, calçados e eletroeletrônicos. A amostra revelou um público bastante ativo nas compras virtuais e que utiliza esse modelo de consumo em função, principalmente, da comodidade e de vantagens financeiras. Esta pesquisa comprovou que o perfil do consumidor só é estruturado ao final do processo de compra e não a priori, como postulado pela maioria dos estudos.Palavras-chave: Compras online. E-commerce. Perfil do consumidor online. Tomada de decisão para compra. Motivação para compra.
The manufacturing industry operates in a constantly changing environment, whether internal or external. Revolutionary shifts in demand and technology are becoming more common. As a result, organizations must be prepared to absorb or mitigate the impact that these changes may have on their outcome, thereby becoming resilient. The aim of this study is to identify which skills and competencies manufacturing companies must develop to become resilient and resist these sudden changes. In order to achieve the proposed goal, this article conducts a systematic literature review. Two databases, Science Direct and SpringerLink, were searched, as well as articles published at the Resilience Engineering Symposium between 2015 and 2020, using the search term "resilience engineering in manufacturing." A total of 64 relevant articles were obtained. The analysis of the articles yielded 23 skills and competencies that companies use to be resilient, with organizational flexibility being the most mentioned skill. As a result, these skills were classified using the four theoretical skill profiles for a resilient system (monitor, anticipate, respond, and learn). There was practically a balance between the four skills mentioned by the authors in the articles, with a higher tendency for the ability to respond to variability, interruptions, disturbances, and opportunities presented in a manufacturing system.Because of the incorporation of organizations into this dynamic environment, people engaged in system activities Lucas de Carvalho Borella et al.
A sustainable supply chain, beyond green, must operate within a suitable financial structure, as well as contribute value to the society (Cuthbertson, 2011), being the three main sustainable dimensions for any organization. The aim of this work is to verify to what extent organizations configured in supply chains (SC) are aligned with sustainability and with each other, in the triple bottom line context. We analyzed the sustainability of supply chain of four organizations positioned in the condition of governance of their supply chain belonging to the commerce, industry, service, and public service sectors, all of which are recognized in the region and in the state, they are located by their social, financial, or environmental performances. We used mathematical alignment calculations based on the theoretical profile and profile deviation techniques to obtain indices of alignment with sustainability. The main finding was the medium‐ to high‐level alignment among SC members, whose practices are moderately sustainable. In addition, the work has an educative role while proposing a sustainability matrix in which it is possible to position the supply chain governance and its members and infer about the convergence of the sustainable practices between them.
The aim of this study is to conduct climate forecasting with models of artificial neural networks as a tool in the decision-making process for the planting of some types of agricultural products. A database with the main climate elements was built from the National Institute of Meteorology (INMET), and those elements that influenced the average temperature value the most were found at a significance level of 0.05. Models of Artificial Neural Networks were developed and tested using Mean Absolute Deviation (MAD), Mean Squared Error (MSE), Root-Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE), before being linked to the best agricultural cultivation forecast value. Twelve neural networks were elaborated, eight of them are related to the temperature forecast and the other four are related to the precipitation forecast. The networks that showed the best performance are those that consider all the elements of climate. It is possible to conclude that the artificial neural networks showed an adequate performance in predicting chaotic time series, and that their results were therefore linked to the optimum cultivation to use for each forecast. A schedule is supplied at the end, indicating the ideal time to plant each of the crops evaluated. Carrot is found to be the best suited crop for the forecasted range over the next five years.
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