Abstract
AbstractAccurately identifying potentially failing companies is beneficial to stakeholders of the companies. This paper uses a case-based reasoning (CBR) approach to predict business failure. CBR is a problem-solving paradigm that uses past experiences to solve new problems. Nearest neighbor (NN) is a common CBR algorithm for retrieving similar cases, but its similarity function is sensitive to irrelevant attributes. To ensure the effective retrieval of similar cases, statistical evaluations are used for automatically assigning relative importance of the attributes for the NN retrieval. The results of this study indicate that this approach is an effective and competitive alternative to predict business failure in a comprehensible manner.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
