Search results

The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.

The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.

This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.

The authors identify several gaps in the literature which this research does not address but could be the focus of future research.

The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.

Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.

To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.

This study aims to develop a conceptual model to understand how customer knowledge management (CKM) affects fitness club membership renewal through the mediation of relationship quality.

Data were collected outside of fitness clubs using a systematic sampling method. A total of 224 valid responses were collected. Structural equation modelling was used to evaluate the relationship between the constructs of the research model.

The results indicate that both knowledge from customers and knowledge for customers have a positive influence on customer satisfaction and customer trust. Among them, knowledge for customers has a stronger influence on customer satisfaction while knowledge from customers has a greater influence on customer trust. Additionally, three dimensions of relationship quality (customer satisfaction, customer trust and customer commitment) positively influence membership renewal intention with customer commitment exhibiting the greatest influence on it.

This study combines the theories of CKM and relationship quality management to explain why members will renew their service contracts. By using fitness clubs as an example, this research extends the authors' understanding of how knowledge from and for customers can influence customers' attitudes and behavioural intentions towards service companies.

The purpose of this paper is to examine the evolution of interconnectedness of European insurers among themselves, as well as with other non-financial firms, for the period 2000–2021 and to analyze the stock return movements around the costliest catastrophic events (hurricanes) in the past two decades.

This paper follows the “simple” approach of Patro et al.(2013) and examines the daily stock return correlations of the largest 30 insurers and the largest 30 non-financial firms headquartered in Europe. In addition, the study uses event study methodology to examine stock return movements around the costliest hurricanes.

We find that the European insurance sector has become highly interconnected during the past two decades; however, its increasing connectedness with non-financial firms is limited to a few firms. In addition, we find weak evidence of the destabilizing effects of catastrophic events on European insurers and non-financial firms; however, the potential for cat risk contagion effects exists as the insurance industry becomes heavily interconnected.

The extant literature is largely concerned with the contribution of the insurance sector to the systemic risk of the financial sector. We focus on a specific region (Europe) and analyze the evolution of interconnectedness of the largest insurers within the insurance sector as well as with the largest non-financial firms encapsulating important crisis periods. In addition, we relate to the literature that examines the market reactions around catastrophic events to test the relevance of traditional insurance activities in instigating potential contagion shocks.