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.

Due to the lack of awareness and poor cybersecurity practices that pose cyber threats during COVID-19 time, this research aims to explore user's attitude toward engaging in proactive cybersecurity awareness behavior.

Based on the theory of planned behavior, the relationship between multiple factors and their influence on the attitude is explored. A survey-based approach was utilized to collect responses and a model was proposed and tested on 229 respondents from the University of Petra-Jordan.

The attitude was significantly influenced by peers' influence and the individuals' cybersecurity threats awareness, especially threats that emerged during the COVID-19 time.

The research benefits decision makers in educational institutions who intend to develop cybersecurity awareness programs and helps them to assess user cybersecurity background weaknesses.

The research is the first to explore users' knowledge dimensions including organizational, information systems and social media as well as peers' influence on cybersecurity awareness. Also, it sheds light on the users’ perception of major cybersecurity hazards in COVID-19 time.

This study aims to introduce a new instrument to assess the perception of the university community after the Climate Emergency Declaration (CED) and its application at the Universidad de Salamanca (USAL) in Spain. This CED includes a comprehensive program to reduce the carbon footprint and the introduction of the education for sustainable development in the curriculum. This study aims to understand the gap between perception and reality in the program's implementation and verify whether the student organization's initial push translates into higher approval ratings.

The authors conducted a cross-sectional analytical study. In this research, the authors used a sample of 731 people from the USAL community (67% students, 20% academics and the rest administrative and service staff).

The findings revealed that PhD students are the group with the highest perception of the policies implemented by the university to fight climate change, even higher than academics. In addition, the perception of the food, energy and sustainable mobility aspects of the program are good predictors: of the knowledge of the indicators and of the policy dimensions within the CED.

The university community perception survey for a CED process provides a gateway into the gaps between perception, expectations and reality. Moreover, it is helpful to engage its members in action plans to fight climate change and its impacts.