Which Characteristics Predict the Survival of Insolvent Firms? An SME Reorganization Prediction Model

Corporate Crisis and Sustainable Reorganization: Evidence from Bankrupt Austrian SMEs

“…This study repeatedly observed all firms (393 SMEs) that filed for bankruptcy in the Federal State “Upper Austria” in 2004. Like many other studies that focused their analyses on a single state or region (for example, Camacho‐Miñano, Segovia‐Vargas, and Pascual‐Ezama ; Carter and Van Auken ), we restricted our sample to one Austrian region in order to ensure efficiency of data collection and to minimize extraneous effects. The sample, however, can be regarded as representative of Austria, as it includes a one‐year cohort of bankrupt firms that reflect the Austrian population in a number of parameters (for a similar approach see Laitinen ).…”

“…However, not all firms succeed in seizing this opportunity. The vast majority of firms going bankrupt are small and medium‐sized enterprises (SMEs), and in most cases they do not survive (Camacho‐Miñano, Segovia‐Vargas, and Pascual‐Ezama ; Feldbauer‐Durstmüller and Mitter ; Laitinen ). Since SMEs typically face resource constraints, it is more difficult for them to cope with and overcome a crisis event (Geroski, Mata, and Portugal ; Thornhill and Amit ).…”

“…The consequence is either discontinuance of ownership (business ownership changes) or business discontinuance (the business ceases to exist) (Carter and Van Auken ). Bankruptcy can be defined as a legal procedure designed to either solve the financial problems of insolvent firms that are on the brink of ruin (Camacho‐Miñano, Segovia‐Vargas, and Pascual‐Ezama ) or liquidate a firm in order to distinguish viable and unviable distressed firms (Leyman, Schoors, and Coussement ). Companies can be reorganized either within the formal bankruptcy procedure or outside of court via private settlements.…”

Business Failure and Entrepreneurship: Emergence, Evolution and Future Research

“…Improved econometric techniques along with the increasing availability of data allowed bankruptcy prediction techniques to grow during the 1980s and 1990s [Lee and Choi, 2013]. Prediction models are still widely used today and technology advances in recent decades have allowed for increasingly complex algorithms to develop into sophisticated artificial intelligence (AI) models [Camacho-Miñano et al, 2015]. AI models have been applied to bankruptcy prediction since the 1990s, however it, alongside all previous models they are not without criticism.…”

Financial Capacities and export success: Evidence from Small and Medium-Sized Estonian Firms

“…To ensure the viability of our results, we have performed a robustness check with another artificial intelligence rule induction algorithm: rough set theory that has been used to solve other financial problems Camacho-Miñano et al, 2015). The rough set theory was firstly introduced by Pawlak (1991).…”