The close relationship between collateral value and bank stability has led to a considerable need to a rapid and economical appraisal of real estate. The greater availability of information related to housing stock has prompted to the use of so-called big data and machine learning in the estimation of property prices. Although this methodology has already been applied to the real estate market to identify which variables influence dwelling prices, its use for estimating the price of properties is not so frequent. The application of this methodology has become more sophisticated over time, from applying simple methods to using the so-called ensemble methods and, while the estimation capacity has improved, it has only been applied to specific geographical areas. The main contribution of this article lies in developing an application for the entire Spanish market that fully automatically provides the best model for each municipality. Real estate property prices in 433 municipalities are estimated from a sample of 790,631 dwellings, using different ensemble methods based on decision trees such as bagging, boosting, and random forest. The results for estimating the price of dwellings show a good performance of the techniques developed, in terms of the error measures, with the best results being achieved using the techniques of bagging and random forest.

The impact of crises on the long-term sustainability of small and medium-sized enterprises (SMEs) has been attracting growing interest in the literature and from governments due to the significance of such companies with respect to economic growth, innovation, and employment. Although failure prediction models have been proposed based on accounting and other qualitative information, little is known regarding the influence of stakeholders on the failure process of SMEs. From the perspective of long-term sustainability, this article analyzes the role of the financial influence of stakeholders on the likelihood of business failure. An empirical study was carried out on a sample of 2352 Spanish SMEs, examining the differences between failed and non-failed SMEs and using a classification tree methodology to investigate the role played by each type of stakeholder in overcoming crisis events. The study provides empirical evidence regarding the relative importance of stakeholders to SMEs under conditions of financial distress, and proposes their categorization on the basis of their control over firms’ financial resources. Specifically, the analysis reveals that the capacity of the firm to generate sustainable wealth over time and to overcome critical situations is dependent on the most critical stakeholders. Workers, customers, and suppliers are the most important in ensuring the long-term sustainability of SMEs during the first stages of a crisis. Following the initial operational problems, other creditors (financial institutions) become relevant. In this sense, the results of this study encourage firms and governments to develop cooperation strategies with stakeholders (co-responsibility) in line with the proposed conceptual models of business sustainability.