This paper focuses on the development of both failure prediction models on a paired sample and a random sample of small and medium-sized firms with head offices located in the region of Castilla y León (Spain), in order to prove if the predictive power of the developed models is affected by the...

In the present decade, in emerging economies such as those in Latin-America, mixed logistic models have been started applying to predict the financial failure of companies. However, there are limitations for the methodology linked to the feasibility of predicting the state of new companies that...

This paper aims to contrast the spillover effects in business failure derived from the geographic proximity among firms of the same sector. To get this purpose, we develop an empirical application based on the analysis of the join-count statistics on a sample of firms of service sector located...

Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly financial investment and lending. The potential value of such models is emphasised by the extremely costly failure of high-profile companies in the recent past. Consequently, a...

This paper examines the post-pandemic performance of micro, small, and medium-sized firms using Self-Organizing Maps (SOMs), a type of Artificial Neural Network that groups patterns based on their similarities. The goal is to identify the key characteristics that enable firms to face market...

Given the global attention and attraction of many scholars and researchers to develop prediction models for determining the going concern of businesses, there is a growing need to monitor progress and trends in the field. As such, the study aims to analyse the evolution of prediction models for...

In this paper we intend to substantiate the usefulness of Deep Learning, especially feedforward neuronal networks, in the prediction of business failure. This methodology provides very good results in terms of predictive performance when large sample sizes are available. Therefore, we have...