Organizational sustainability (OS) has been guiding the decision-making process of managers in order to generate competitive advantage. This paper aims to identify the sustainable practices performed by large corporations in the implementation of OS. Reports with actions performed by large organizations and their reach in the three pillars of sustainability-environmental, economic, and social dimensions-are disclosed to their main stakeholders, based on short, medium and long-term sustainable goals. These reports often reflect the progress of OS or the progress made toward them. However, few studies investigate the sustainable practices adopted by firms and their reproducibility. A search was performed in reports selected from the firms listed by the Corporate Sustainability Index (CSI) from 2012-2016, belonging to the Brazilian stock market in services sector of the economy and employed the Global Reporting Initiative (GRI) methodology. The results showed the strategic planning involving infrastructure, environment, human resources, product innovation, organizational management and deadline setting acted as the baseline for the implementation of the practices found. The findings will guide the managers´decisions in the development of their strategic planning, based on practical and objective results.
Smart cities (SC) promote economic development, improve the welfare of their citizens, and help in the ability of people to use technologies to build sustainable services. However, computational methods are necessary to assist in the process of creating smart cities because they are fundamental to the decision-making process, assist in policy making, and offer improved services to citizens. As such, the aim of this research is to present a systematic review regarding data mining (DM) and machine learning (ML) approaches adopted in the promotion of smart cities. The Methodi Ordinatio was used to find relevant articles and the VOSviewer software was performed for a network analysis. Thirty-nine significant articles were identified for analysis from the Web of Science and Scopus databases, in which we analyzed the DM and ML techniques used, as well as the areas that are most engaged in promoting smart cities. Predictive analytics was the most common technique and the studies focused primarily on the areas of smart mobility and smart environment. This study seeks to encourage approaches that can be used by governmental agencies and companies to develop smart cities, being essential to assist in the Sustainable Development Goals.
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