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A highlighted issue relating to the financial distress of public companies raises more debate from both academic and current practice perspectives as financial markets are currently a key source of growth for the local and international economies. In the context of advanced technology and the digital revolution, forecasting and early detection of financial distress are important methods that contribute to increasing confidence between investors and the market and help to make sound decisions promptly to avoid reaching bankruptcy (Fuentes et al., 2023). This study employs machine learning algorithms to measure the probability of financial distress of listed firms on the Vietnam Stock Exchange by using a dataset with 4,936 observations from 2009 to 2020. The research has identified internal determinants such as debt-to-equity ratio, asset turnover ratio, and profit margin ratio as indicators that have the greatest impact on financial distress under different models. The results reveal that Model 1 — Altman and Model 3 — Zmijewski predict financial distress with an accuracy rate of 98%. In addition, we have determined the threshold when using the decision tree algorithm, which has an important impact on the financial distress of listed firms. This finding contributes to the existing literature review and is consistent with previous studies of Chen et al. (2021) and Martono and Ohwada (2023).

Green and sustainable development is a common trend in the world, in which firms are not only interested in socio-economic development, but also environmental protection and environmental indicators in the production process. Green accounting, an important tool to assess the environmental impact on the economy, is considered a transition towards green and sustainable economic development (Gray, 1992). This study is conducted to assess the impact of all factors on the application of green accounting in Vietnamese construction firms, of which data is collected from 243 survey questionnaires of managers and accountants of Vietnamese construction firms. By using Cronbach’s alpha test, exploratory factor analysis (EFA) test, and multiple regression analysis to check and forecast information, there are five determinants affecting the application of green accounting in Vietnamese construction firms as staff levels and resources, legal and regulatory systems, customer demands, legal and educational systems, stakeholder, managers’ perceptions, internal resources. Based on the findings, some suggestions are proposed to management businesses and agencies to compensate for the shortcomings in the process of applying green accounting, contributing to making green accounting one of the most effective tools. It is important to appraise the environmental impact on the economy and is acknowledged as a transition towards sustainable development and green economic development.