The incorporation of the social, environmental, and economic dimensions of sustainability in different aspects of human life and business provides a guarantee for our future. Organizations have shown a great interest in incorporating sustainability into managerial concepts, both at the strategic and operational levels. Sustainable business strategies are being implemented in many projects, which has led to a recent expansion of interest in exploring the potential of integrating sustainability dimensions in project management. With the intention of contributing to a better understanding of sustainable project management, this paper examines whether project management methodologies, applied in different sectors, support the introduction of sustainability dimensions. It also surveys the level of integration of sustainability dimensions in groups of project management processes. Considering that the incorporation of sustainability in project management poses numerous challenges for project managers, this paper examines the necessary knowledge and skills required for sustainable project management in different sectors. As part of this research, an empirical survey was conducted in project-oriented organizations from both the public and private sectors. The findings reveal that the application of project management methodologies promotes the introduction of sustainability dimensions, particularly the social aspect, irrespective of the sector, since the processes in projects managed by a specific methodology are consistent with the social elements of sustainability. In the public sector, there is a noticeable lack of knowledge of the meaning and dimensions of sustainability and, accordingly, an urgent need for project managers to gain knowledge and skills pertaining to sustainable project management.

Scholars have emphasised the importance of green settings in today’s business paradigms. Studies on green behaviour have produced a plethora of noteworthy discoveries, whether focused on financial success, individual capabilities, or development. However, despite significant growth in interest in green business practices, the relationship between individuals’ willingness and green competencies has received little attention. This article used the customised green competencies conceptual model to investigate how green skills influence organisational performance and their relationship with the willingness moment. This article developed an innovative human resource management approach to address these difficulties. A questionnaire was used to perform empirical statistical research with 516 respondents from Serbian universities. Different mathematical and statistical methodologies were used to analyse the results. The findings corroborate the suggested theoretical model, and they suggest that green competencies will influence people’s willingness to participate in green activities. This article gives new information on human behaviour and organisational effectiveness in a green atmosphere. It includes managerial and practical consequences and recommendations for businesses looking to improve their social responsibility and environmental sustainability.

In this paper, we assess the impact of the COVID-19 crisis on the bankruptcy risk of a sample of 100 hotel companies and, consequently, on the hotel industry in the Republic of Serbia. The assessment applies to the period, 2019–2026, with the use of the data on the financial indicators for 2015–2020. Five novel structural time-series models, which have the indicators derived from Altman’s EM Z″-score model as predictors, were used, and a new conceptual framework for assessing bankruptcy risk is provided. The framework expands the applicability of credit-risk-scoring models to multiyear predictions, and it takes into account the dynamism of the transitions of the firms among Altman’s risk zones. The predictions that were obtained when the Springate and Zmijewski scores were applied along with the Altman Z″-scores demonstrate the fair applicability of the scores for the models that are introduced here. The results of the models were confirmed by 270 artificial neural networks and they were compared to the results of the classical time-series models. The crisis started to have a negative effect on bankruptcy risk in 2020, and this effect is expected to rise until 2023; currently, in 2022, the highest number of hotel companies may be headed for bankruptcy. Amelioration in the position of the companies cannot be expected before 2024; however, even in 2026, the risk of bankruptcy will remain high when compared to the pre-COVID-19 period and, thus, the surviving companies will become more fragile to any further exogenous changes. These results provide a basis for the adaption of state-supported measures and business policies in order to withstand the crisis and to ensure sustainability.

Social and environmental responsibility of apparel sector has been drawing rising attention of policymakers and researchers in recent years. One possible solution to curb the detrimental effects caused by the clothing industry is to invoke more responsible demand of its heavy users, such as young clothing customers. This study aims to examine a model of the determinants of environmentally and socially responsible clothing consumption of young adult customers in a developing economy. The study has been performed on a convenience sample of 439 respondents in Serbia, by means of structured online survey. Exploratory factor analysis (EFA), followed by two-step structural equation modeling procedure (SEM)—implying an examination of a measurement model, followed by testing of structural relationships—has been performed within data analysis. Results of the study indicate green consumption values as the most influential determinant of responsible apparel consumption, followed by conscious consumption and receptivity to green communication. Findings of the study contribute to the body of knowledge on responsible consumption and provide directions for practitioners and policymakers. Study limitations are noted and future research directions are provided.

In this paper we demonstrate a new conceptual framework in the application of multilayer perceptron (MLP) artificial neural networks (ANNs) to bankruptcy risk prediction using different time-delay neural network (TDNN) models to assess Altman’s EM Z″-score risk zones of firms for a sample of 100 companies operating in the hotel industry in the Republic of Serbia. Hence, the accuracies of 9580 forecasting ANNs trained for the period 2016 to 2021 are analyzed, and the impact of various input parameters of different ANN models on their forecasting accuracy is investigated, including Altman’s bankruptcy risk indicators, market and internal nonfinancial indicators, the lengths of the learning periods of the ANNs and of their input parameters, and the K-means clusters of risk zones. Based on this research, 11 stability indicators (SIs) for the years under analysis are formulated, which represent the generalization capabilities of ANN models, i.e., differences in the generalization errors between the preceding period and the year for which zone assessment is given; these are seen as a consequence of structural changes at the industry level that occurred during the relevant year. SIs are validated through comparison with the relative strength index (RSI) for descriptive indicators of Altman’s model, and high correlation is found. Special focus is placed on the identification of the stability in 2020 in order to assess the impact of the COVID-19 crisis during that year. It is established that despite the fact that the development of bankruptcy risk in the hotel industry in the Republic of Serbia is a highly volatile process, the largest changes in the analyzed period occurred in 2020, i.e., the potential applications of ANNs for forecasting zones in 2020 are limited.