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Environmental changes require resources that are able to adapt. This condition requires a special strategy to remain competitive. This can be realized from real resources and employee skills that match market needs (Dubey et al., 2019). Therefore, continuous training is the “way” to face business scenarios (Santana-Domínguez et al., 2022). So, employee training is the best solution to maintain company sustainability. This study aims to explore the importance of training to maintain the stability of the company’s future. This research is qualitative research with in-depth interviews as the main data collection method. The analytical method uses Foucault’s (1980) power-knowledge with three main focuses as a tool for data reduction, namely sharing, generating and using knowledge. The results of the study show that training is important to be carried out by companies due to three main reasons, namely training as a place to transfer knowledge, training to produce employee/company performance, and training as an inseparable part of the company’s sustainability process. In addition, the results show that continuous learning is a necessity that must be carried out to deal with environmental change. It is important to know that everything will change except the change itself. The next research approach is to examine the training section with a quantitative approach. [ABSTRACT FROM AUTHOR]

This study examines if there are variations among financial crisis models. It is intended to investigate whether it has the most significant level of accuracy in predicting potential corporate bankruptcies. This is a quantitative study; Secondary information from financial reports serves as the data source. The study population is public and non-public companies in the construction sector listed on the Indonesia Stock Exchange (IDX) for 2014--2020. In order to obtain a sample of eight businesses, targeted selection was used for sampling. The results of this study show that the conditions differ from those of financial distress models for public and non-public companies. For public companies, the most accurate models are Grover and Lavin's (2001), Karas and Srbová's (2019), Fulmer's (1984), and Ohlson's (1980) models proven to be 100 percent. In contrast, only Fulmer's model is entirely applicable to non-public companies. Forecast results and best-fit models can provide positive information or warnings for external and internal parties. [ABSTRACT FROM AUTHOR]