Search results

Previous research features the international experience of managers in the decisions regarding internationalisation speed. However, the vitality of the role a chairperson plays in shaping the internationalisation decisions of small and medium-sized enterprises (SMEs) from emerging economies is intriguing. Moreover, the decision-making process and leadership context of SME internationalisation are not fully understood. Drawing upon the upper echelons decision-making theory and the cognitive perspectives of decision, this paper examines the impact of a chairperson's previous experience on the post-entry speed of internationalisation, highlighting the conditioning effects of leadership contingencies – the functional variety and power of the chairperson.

The study uses a panel data set of Chinese SMEs active from 2010 to 2019 to test the research hypotheses. A feasible generalised least-squares estimator was applied to test the hypotheses.

The results show that the international experience of a chairperson speeds up the depth and breadth of the post-entry speed of internationalisation. However, the strength of these relationships depends on the leadership context. The chairperson's functional variety alleviates the influence of international experience, whilst the power of the chairperson reinforces its impact.

The results show that the international experience of a chairperson speeds up the depth and breadth of the post-entry speed of internationalisation. However, the strength of these relationships depends on the leadership context. The chairperson's functional variety alleviates the influence of international experience, whilst the power of the chairperson reinforces its impact.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

The purpose of this study is to explore whether different board diversity attributes (corporate governance aspect) can be used to predict financial distress. This study also aims to identify what type of prediction models are more applicable to capture board diversity along with conventional predictors.

This study used Chinese A-listed companies during 2007–2016. Board diversity dimensions of gender, age, education, expertise and independence are categorized into three broad categories; relation-oriented diversity (age and gender), task-oriented diversity (expertise and education) and structural diversity (independence). The data is divided into test and validation sets. Six statistical and machine learning models that included logistic regression, dynamic hazard, K-nearest neighbor, random forest (RF), bagging and boosting were compared on Type I errors, Type II errors, accuracy and area under the curve.

The results indicate that board diversity attributes can significantly predict the financial distress of firms. Overall, the machine learning models perform better and the best model in terms of Type I error and accuracy is RF.

This study not only highlights symptoms but also causes of financial distress, which are deeply rooted in weak corporate governance. The result of the study can be used in future credit risk assessment by incorporating board diversity attributes. The study has implications for academicians, practitioners and nomination committees.

To the best of the authors’ knowledge, this study is the first to comprehensively investigate how different attributes of diversity can predict financial distress in Chinese firms. Further, this study also explores, which financial distress prediction models can show better predictive power.

While the Chinese securities market is booming, the phenomenon of listed companies falling into financial distress is also emerging, which affects the operation and development of enterprises and also jeopardizes the interests of investors. Therefore, it is important to understand how to accurately and reasonably predict the financial distress of enterprises.

In the present study, ensemble feature selection (EFS) and improved stacking were used for financial distress prediction (FDP). Mutual information, analysis of variance (ANOVA), random forest (RF), genetic algorithms, and recursive feature elimination (RFE) were chosen for EFS to select features. Since there may be missing information when feeding the results of the base learner directly into the meta-learner, the features with high importance were fed into the meta-learner together. A screening layer was added to select the meta-learner with better performance. Finally, Optima hyperparameters were used for parameter tuning by the learners.

An empirical study was conducted with a sample of A-share listed companies in China. The F1-score of the model constructed using the features screened by EFS reached 84.55%, representing an improvement of 4.37% compared to the original features. To verify the effectiveness of improved stacking, benchmark model comparison experiments were conducted. Compared to the original stacking model, the accuracy of the improved stacking model was improved by 0.44%, and the F1-score was improved by 0.51%. In addition, the improved stacking model had the highest area under the curve (AUC) value (0.905) among all the compared models.

Compared to previous models, the proposed FDP model has better performance, thus bridging the research gap of feature selection. The present study provides new ideas for stacking improvement research and a reference for subsequent research in this field.

The aim of this study is to examine the effect of financial leverage impact on customer satisfaction and marketing costs including research and development (R&D) and advertisement costs. Furthermore, the authors aim to investigate whether customer satisfaction as well as financial distress moderates the effect of financial leverage impact on customer satisfaction and marketing costs including R&D and advertisement costs.

The statistical population of this study consists of listed companies on the Tehran Stock Exchange manually obtained from different industries in 2017. Multivariate regression based on data compilation methodology is used to test research hypotheses.

The results indicate that financial leverage is negatively and significantly associated with customer satisfaction and this negative relationship is more pronounced in companies with lower sale growth. Furthermore, the authors' results suggest that customer satisfaction negatively (positively) and significantly affects firm value in companies with lower (higher)-financial leverage. The authors also demonstrate that there is no significant relationship between financial leverage caused by financial flexibility and firm value caused by customer's satisfaction (CS). The authors' findings also suggest that financial distress significantly affects the relationship between financial leverage and customer satisfaction. Finally, the authors' find that financial leverage significantly affects firms' R&D and advertisement costs.

Since the fundamental institutional assumptions underpinning the Western and even East Asia financial models are not valid in the institutional environment of Iran, the authors' findings could provide substantial implications for the authors' understanding of the relationship between finance and R&D costs and contribute substantially to customer satisfaction and firm value literature as well. The sample country of the present paper has recently experienced a spate of financial collapses that somewhat contributes, indirectly, to financial distress incurred by the Iranian firms. Moreover, R&D costs are growing among the Iranian quoted firms.

Since the fundamental institutional assumptions underpinning the Western and even East Asia financial models are not valid in the institutional environment of Iran, the authors' findings could provide substantial implications for our understanding of the relationship between finance and R&D costs and contribute substantially to customer satisfaction and firm value literature as well. The sample country of the present paper has recently experienced a spate of financial collapses that somewhat contributes, indirectly, to financial distress incurred by the Iranian firms. Moreover, R&D costs are growing among the Iranian quoted firms.

The case illustrates the application of the prospect theory to risk-seeking investor behavior. It also provides an example that standard valuation methods such as discount cash flow), discount divided model and price multiples are not always applicable to value a stock. The students are exposed to a real situation where investors turn risk-seeking. The case offers insights into why irrational investors are attracted to risky assets and their probable socio-demographics.

This case illustrates a case when investors become risk-seeking and how the prospect theory explains the investors’ risk appetite. Energy Earth PCL is a coal importer and distributor incorporated in Thailand. Its shares had been suspended for trading before the Stock Exchange of Thailand allowed temporary trading in July 2019. A series of unfavorable events leading up to the temporary trading period suggest that the company’s financial health was severely distressed. Its book value was presumably negative and its going concern was threatened. However, investors still bought the shares with the hope of hitting the jackpot. The case presents an example of the psychological aspects of humans when investing in a stock market. With an application of the prospect theory, irrational risk-seeking behavior explains the motivation to invest in risky stocks.

Introductory finance course.

Teaching notes are available for educators only.

CSS: 1 Accounting and Finance.

The purpose of this paper is to explain the multi-stage dynamic process of financial distress. An attempt is made to explore multiple adverse heterogeneous events of financial distress leading a firm closer to bankruptcy progressively.

Sample comprises 321 ongoing, 54 suspended and 91 delisted non-financial firms from Pakistan Stock Exchange. Financial distress is segregated into three stages, i.e. profit reduction, mild liquidity (ML) and severe liquidity (SL). Flow diagrams are used to explain the transition of healthy firms through proposed stages of financial distress.

Results showed that firms liquidated/winding-up by court documented SL problems and closed their operations well before the delisting year. It is found that healthy firms are more likely to face SL when faced ML problem at first stage. Distressed firms can recover to a healthy position at any stage, however after approaching to SL, recovery is less expected.

The proposed process will provide a foundation for future studies to develop more relevant, robust and accurate early warning system of corporate failure that will help stakeholders to respond potential crisis accordingly and timely.

Previously, most of the studies used the ex post definition of bankruptcy that is criticized due to the contextual application, sample bias and non-segregation by the degree of liquidity problems. The originality of the proposed ex ante model is its segregation into a three-stage process that can be generalized regardless of specific bankruptcy law.

The purpose of the study is to systematically review the literature of indirect cost of financial distress to understand its scope, measurements, impact size and determinants to synthesis with future research agenda.

Five-step process of systematic literature review (SLR) as applied by Opoku et al. (2015) is used. SLR extracted 47 studies of indirect cost after applying specified search criteria. Data regarding measurement, impact size and determinants are presented and summarised in specified tables.

SLR showed that the study of indirect cost in developing countries is a literature gap. It is also found that opportunity loss, operating profit loss, market loss and risk premium are most studied indirect costs using legal definition or ex ante proxy of financial distress. However, future studies are recommended to use both non-linear leverage and ex ante proxy of financial distress. Future studies are also suggested to use the moderation technique while studying the determinants of indirect cost.

Literature selection is based on specific search criteria that can miss some of the other related literature.

The indirect cost of financial distress is more costly and difficult to measure due to its complex concealed effects. A detailed literature of indirect cost is needed to understand the construct that eventually will help to define the future research agenda. To the best of the authors’ knowledge, no SLR of indirect cost is provided yet. Therefore, the outcome of this research will be valuable for both academicians and practitioners.

This study aims to analyze the trends manifested in literature from the area of knowledge management and performance, with emphasis on bibliometric analysis.

To explore the studies focused on the area under investigation, the authors performed a search in ISI Web of Science and Scopus using the combination of keywords such as “Knowledge management” AND “Performance.” Generally, this study covered a period of 33 years, from 1988 to 2021 because the first study was published in 1970 and the databases have not covered all the journals and studies which date back to the early 1970s or 1980s. The final data set comprised 1,583 publications with 40 articles removed during the screening and eligibility process.

The results of the bibliometric analysis indicate that the interest in the area of knowledge management and performance has significantly increased, especially from 2000 to 2021. The application of bibliometric analysis on the relationship between knowledge management and performance uncovered various themes, productive authors and widely cited documents. The study highlighted how the knowledge management–performance relationship has evolved over the years and how the interplay between knowledge management and performance may help the firms in gaining the sustainable competitive advantage.

To the best of the author’s knowledge, this study is the first of its kind to conduct the bibliometric analysis on knowledge management and performance. This study can be a starting point for scholars interested in understanding how knowledge management is related to performance.

Considering food waste as a global problem resulting from the wastage of valuable resources that could fulfil the requirements of malnourished people, the current research focusses on understanding consumerism’s impact on this phenomenon. Additionally, the circular economy (CE) approach can be critical in reducing food waste and promoting sustainability.

A systematic literature review was conducted using bibliometrics and network analysis. The study reviewed 326 articles within 10 years, from 2013 to 2023.

The findings reveal four prominent factors – behavioural, environmental, socioeconomic and technological – in managing food waste (FW). Reducing FW at a holistic level can benefit individuals and the environment in several ways.

Consumers are encouraged to be more responsible for their food consumption by reducing food waste, as it affects societies and businesses both economically and environmentally. This can help promote a responsible consumption culture that values quality over quantity and encourages people to make more informed choices about what they eat and how they dispose of it post-consumption. All stakeholders, including firms, the government and consumers, must examine the motives behind inculcating pro-environmental behaviour.

Addressing consumerism and the ability to decrease FW behaviour are complex issues that require a multidimensional approach. This study seeks to fill the gap in understanding consumerism and the capacity to reduce FW using the CE approach and understand the research gaps and future research trends.