Search results

This study aims to develop an assessment methodology using a Bayesian network (BN) to predict the failure probability of oil tanker shipping firms.

This paper proposes a bankruptcy prediction model by applying the hybrid of logistic regression and Bayesian probabilistic networks.

The proposed model shows its potential of contributing to a powerful tool to predict financial bankruptcy of shipping operators, and provides important insights to the maritime community as to what performance measures should be taken to ensure the shipping companies’ financial soundness under dynamic environments.

The model and its associated variables can be expanded to include more factors for an in-depth analysis in future when the detailed information at firm level becomes available.

The results of this study can be implemented to oil tanker shipping firms as a prediction tool for bankruptcy rate.

Incorporating quantitative statistical measurement, the application of BN in financial risk management provides advantages to develop a powerful early warning system in shipping, which has unique characteristics such as capital intensive and mobile assets, possibly leading to catastrophic consequences.

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.

In this paper, the authors study the failure of Russian banks between 2012 and 2019.

The authors analyze the entire population of Russian banks and combine a logit model with the survival analysis.

In addition to the usual determinants, the authors find that not-failed banks have higher levels of fulfillment of the Central Bank requirements of solvency, liquidity, provide fewer loans to their shareholders and own more shares of other banks. The results of this study suggest an asymmetric effect of the strategic orientation of banks: whereas the proportion of deposits from firms is negatively related to the probability of failure, the loans to firms are positively related to bankruptcies. According to this research, the fact of being controlled by a foreign bank has a significant negative relationship with the likelihood of failure and moderates the effect of bank size, performance and growth on the bankruptcy likelihood.

On the whole, the results of this study support the new Central Bank rules, but show that the thresholds imposed by the Russian regulator actually do not make a difference between failed and not failed banks in the short and medium term.

The authors specially focus on the effectiveness of new rules issued by the Central Bank of Russia in 2013.

Born-again global internationalization is a rarely researched topic. Especially process-oriented studies are largely missing. In loss modes concerning their socioemotional wealth (SEW), family businesses take more risks and can be informative examples of born-again global internationalization.

This article analyzes the process of born-again global internationalization of a mature family business triggered by succession in an SEW loss mode. The interplay of dynamic capabilities (DCs) as drivers and SEW preservation guides the in-depth analysis based on an interpretative single case study design.

The analysis reveals a model with (1) the personal and familial level of the business family, (2) the bonding and transfer level between the business family and the family business and (3) the organizational level as three levels of DCs as drivers of born-again global internationalization in family businesses and SEW preservation as a continuously influencing context.

The article contributes to push forward the fragmented level of knowledge in the field of born-again global internationalization of family businesses. It brings together the triggering phase of born-again global internationalization with the later phases (driving successful rapid internationalization). In particular, it explores how the triggering factors on the family level can be translated into the development of capabilities on the firm level to drive successful internationalization. Based on these insights, the article offers novel implications for research and practice.

The unique dynamics of family firms (FFs) shape the management of financial crises. Religious and secular reasons, as a defining characteristic of this type of firm, provide a reference system for key management decisions. This paper aims to explore the under-researched topic of differences in FFs' crisis management between religious and secular family decision-makers (FDMs), considering secularization in developed countries.

The paper draws on a qualitative-empirical study of 14 large FFs from the DACH region (Germany, Austria and Switzerland), through both a media analysis and semi-structured interviews with FDMs who have significant influence on key management decisions.

Despite secularization, religion continues to influence managerial decisions such as crisis management in the DACH region. The findings show that crisis management differs across religious and secular FDMs, demonstrating the substantial impact of religious and secular reasons on operational and financial measures. Thus, religious and secular reasons may partially explain the complex and ambivalent crisis management of FFs. This indicates that religion shapes FF's key management decisions in the increasingly secularized DACH region. Religious FDMs are accountable to both the firm and to God, which fosters their own personal and financial resources during crisis management.

This paper contributes to the existing literature by exploring the impact of religion and secularization within developed countries. Further, it offers deeper insights into FF's crisis management and is one of the first studies to assess the impact of religion and secularization on operational and financial measures. This research derives five propositions for further research and discusses a broad range of original implications for theory and practice.

This research investigates the top five pharmaceutical companies in India to determine whether their financial structures are sound and if they face the risk of bankruptcy, highlighting the potential contribution of intellectual capital (IC) to financial stability.

The analysis outlines operating ratios, profitability ratios, possibility of bankruptcy (through Z-scores) and attractiveness of the financial structure (through the F-score), with consequent focus on (IC).

The financial structure of the selected companies seems stable. Changes in the Indian pharmaceutical scenario, above all, regarding the patent system, will force the companies to consider the impact of IC carefully.

Indian pharmaceutical companies need sustainability and development, with increasing focus on patent issues. To enhance innovation capabilities and overcome international competition, they should redesign their business orientation towards IC, mainly when impacting patents.

Using established approaches for predicting potential bankruptcy, this study focuses on the financial performance of top Indian pharmaceutical companies. IC can support financial stability, and this study provides further perspectives for managing their financial structure, both statically and dynamically.

The purpose of this study is to develop a model of a starting situation for relationship initiation in turbulent business networks.

The study is designed as an extreme single case study that takes its point of departure in a company’s bankruptcy in the Swedish automotive industry.

This study illustrates how a new business relationship can start from a resource combination previously controlled by one actor (i.e. a single company) in a turbulent business network, thereby bringing nuances to the common understanding that new relationships start in stable business networks where resource combinations are developed between actors in established business relationships.

Previous studies have stated that the development of a mutual orientation between actors leads to the formation of a business relationship. The business relationship then leads to resource adaptations between the two companies. The developed model, however, illustrates that this pattern can be reversed in situations of turbulence. Hence, previously adapted resources might lead to the formations of a business relationship. Based on this observation, the authors argue that there are reasons to question if previous models of business relationship initiation and development in business networks are adequately equipped for analysis in turbulent business networks.

This study aims to examine the dimensions of organisational failure in the Brazilian sugarcane and ethanol refineries, as reported in judicial recovery plans.

This paper follows a qualitative, inductive approach that uses content analysis to examine the details of recovery plans. Besides, a cause-and-effect relationship diagram is proposed, making it possible to identify the interconnections between the identified variables.

There is evidence that organisational failures are not a linear outcome. Organisational failures are complex and occur because of several factors, often interdependent and operating at different levels.

Organisational failures basically have three interrelated levels: the macro-level (external environment), the meso-level (organisational environment) and the micro-level (associated with the decision-maker). The relationship between these levels is not trivial and involves coordinated research efforts.

Organisations must consider all types of failure levels when developing business reorganisation plans. Reorganisation plans are more than a formal document to achieve judicial recovery, as they should incorporate strategic factors.

Organisational failures are regularity in organisations’ day-to-day. Understanding failure’s sources is vital to design firms’ strategies and public policies.

The study of organisational failure involves the analysis of complex and multidimensional phenomena. Judicial recovery plans are the means for companies to get a second chance. To that end, this paper addresses the sources of organisational failures through the lens of judicial plans.

The paper aims to identify the differences between developed and developing country firms with respect to firm-specific and country-level determinants of their capital structure. For this purpose, all constituent firms in one of the oldest Islamic equity indices, Dow Jones Islamic Market World Index (DJIM), are considered and the Muslim-majority status of each firm's domicile country is recognized.

The study employs Hausman–Taylor random effects regression with endogenous covariates to explain the debt ratios of firms in DJIM by separating them into developed and developing country subsamples in an unbalanced panel data setting. Developing country subsample is further split into two based on the Muslim-majority status of each firm's domicile country.

Consistent with the previous literature, this study finds that firm-specific characteristics are the main determinants of their capital structure. Additionally, the paper shows that country-level characteristics have an impact on the debt ratio, however, the types of factors vary across developed and developing countries. Debt ratios in developing country firms are lower than those in developed country firms, largely due to the significantly smaller leverage ratios of firms in Muslim-majority countries. Although the debt ratios of DJIM firms are higher in “non-Muslim” countries, the set of firm-level capital structure determinants are not statistically explained by operating in a “Muslim” country. The study also documents that, before the global financial crisis of 2008, companies in developing countries have gradually become less leveraged worldwide.

This paper provides a new perspective into the differences between developed and developing country firms' capital structures by focusing on a relatively homogeneous data set restricted by leverage screening rules of an Islamic equity index and recognizing the Muslim-majority status of each firm's domicile country.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.