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This paper explores predicting early signals of business failure using modern models for bankruptcy prediction. It reviews how continuous operations enhance market value, strengthening competitiveness and reputation among stakeholders. The study involves medium and large companies in the Montenegrin market from 2015 to 2020, comprising 30 bankrupt and 70 financially stable firms. Logistic regression is also employed to create a logit model for early detection of bankruptcy signals in companies. This research establishes the empirical validity of modern models in predicting business failure in the Montenegrin market, particularly through logistic regression. Significant indicators, such as the Degree of Indebtedness (DI) and turnover ratio of business assets (TR), exhibit strong predictive power with a p-value less than 0.001 according to Likelihood ratio tests. The paper underscores the potential benefits of bankruptcy prediction for both internal and external stakeholders, especially investors, in enhancing the competitiveness of Montenegro's large and medium-sized companies. Notably, the research contributes by bridging the gap between theory and practice in Montenegro, as bankruptcy prediction models have not been extensively applied in the market. The authors suggest the possible applicability of the created logit model to neighboring countries with similar economic development levels. In that sense, the concept of predicting bankruptcy is positioned as integral to corporate strategy, impacting the overall reduction of bankruptcies. The paper concludes by highlighting its role as a foundation for future research, addressing the literature gap in the application of bankruptcy prediction models in Montenegro. The created logit model, tailored to the specific needs of Montenegrin companies, is presented as an original contribution, emphasizing its potential to strengthen the competitiveness of companies in the market. [ABSTRACT FROM AUTHOR]

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In this paper, we used data from publicly traded restaurant firms between 2000 and 2019 to test the effectiveness of multiple discriminant analysis (MDA) and logistic regression (logit) in predicting the probability of bankruptcy in the restaurant industry. We constructed various financial ratios extracted from the financial information and analyzed them to determine the optimal models. Our results show that liquid ratios (particularly the quick ratio), operating cash flow, and working capital emerge as the most crucial indicators of potential bankruptcy filings for restaurant firms. The results also show that the logit model performs better within the sample. However, both models exhibit similar predictive capacities with out-of-sample data. [ABSTRACT FROM AUTHOR]

Purpose: 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. Design/methodology/approach: 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. Findings: 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. Research limitations/implications: The authors identify several gaps in the literature which this research does not address but could be the focus of future research. Practical implications: 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. Social implications: 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. Originality/value: 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. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Estudios Empresariales Segunda Época is the property of Editorial de la Universidad de Jaen and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: To the best of the authors' knowledge, this paper is a first attempt to deal with the phenomenon of new venture failure from the business network perspective of the Industrial Marketing and Purchasing (IMP) Group. In particular, this study aims to explore the post-failure phase of a new venture to investigate what happens to the new venture's resources and relationships in the aftermath of its failure and the role of the entrepreneur in this process. Design/methodology/approach: The paper builds on an explorative multiple case study of two failed new ventures, unfolding the failure and post-failure phase: evidence from both cases is confronted and discussed. Findings: This study shows that the post-failure is a complex phase of recombination of activities and residual resources that may lead to new business opportunities. It is discussed that residual resources influence the direction and extent of post-failure activities in terms of restrictions as well as opportunities to restart new projects or ventures. It is also shown how the entrepreneur deals with the "business remains". Originality/value: While much attention has been devoted to new ventures' failure, the paper focuses on the post-failure phase, an almost neglected topic in industrial marketing research. This study sheds some new light upon the journey through which entrepreneurs come to develop the set of resources, activities and relationships that are not only key to the establishment of the venture but also relevant in the complex and intricate trajectories of post-failure. [ABSTRACT FROM AUTHOR]

Due to operating in the mining and iron sectors with fierce competition and encountering more financial obstacles compared to larger enterprises, SMEs (small and medium-sized enterprises) become more likely to face business failures, have lower financial performance and have high financial risk. To overcome those financial impediments and become more competitive against their rivals, social media usage might be a solution. This is because even under the conditions of the covid-19 pandemic, social media has also stimulated online purchasing behaviours of customers and has been used as an effective tool by SMEs for marketing purposes. However, SMEs' usage of these channels might differ depending on the countries where they are located, so their impacts on financial obstacles might be different. In this regard, this research examines whether the impacts of social media usage on the financial problems of SMEs differ depending on their location. To achieve this goal, the researchers employ an online survey and direct it to the executives of 1156 Czech, Slovakian and Hungarian SMEs. The researchers apply Ordinal Logistic Regression with the Logit function in SPSS statistical tool for analyzing purposes. The results confirm the fact that while differences do not exist among countries regarding the impact of social media usage on business failures, the effects of social media usage on financial performance and financial risk differ between Hungarian and Czech-Slovakian SMEs. Czech and Slovakian SMEs show similar attitudes in all of the analyzed variables. [ABSTRACT FROM AUTHOR]

Copyright of Ekonomika is the property of Society of Economists 'Ekonomika' and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the context of public administrations after COVID-19, this paper formulates and validates a digital model of tutoring (e-tutoring) for small and medium enterprises (SMEs) by public administrations or PAs to help the former reduce their risks to fold in their first few years of existence and with the support of private professionals (economists, accountants, business advisors, managers, etc.). The model draws on ideas about relational administration (RA), a concept that is yet to be fully exploited or assessed in the literature. Several hypotheses derived from the model are formulated and tested using a polytomic-nominal logistic regression. A questionnaire was sent to and returned by 236 small and medium entrepreneurs in Spain facing insolvency proceedings to identify main reasons for business failure and if or how they would accept online tutoring from private professionals associated with PAs. Findings suggest that SM entrepreneurs agree with receiving selected forms of tutoring, requiring public administrations to enhance capabilities for joint information provision and decision making through the use of information and communication technologies or ICTs. These findings have important implications for the potential restructuring of public administrations, their collaborations with professionals, and the future co-design and implementation of e-government services by PAs [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) proves decisive in today's rapidly developing society and is a motive force for the evolution of financial technology. As a subdivision of artificial intelligence research, machine learning (ML) algorithm is extensively used in all aspects of the daily operation and development of the supply chain. Using data mining, deductive reasoning, and other characteristics of machine learning algorithms can effectively help decision-makers of enterprises to make more scientific and reasonable decisions by using the existing financial index data. At present, globalization uncertainties such as COVID-19 are intensifying, and supply chain enterprises are facing bankruptcy risk. In the operation process, practical tools are needed to identify and opportunely respond to the threat in the supply chain operation promptly, predict the probability of business failure of enterprises, and take scientific and feasible measures to prevent a financial crisis in good season. Artificial intelligence decision-making technology can help traditional supply chains to transform into intelligent supply chains, realize smart management, and promote supply chain transformation and upgrading. By applying machine learning algorithms, the supply chain can not only identify potential risks in time and adopt scientific and feasible measures to deal with the crisis but also strengthen the connection and cooperation between different enterprises with the advantage of advanced technology to provide overall operation efficiency. On account of this, the paper puts forward an artificial intelligence-based corporate financial-risk-prevention (FRP) model, which includes four stages: data preprocessing, feature selection, feature classification, and parameter adjustment. Firstly, relevant financial index data are collected, and the quality of the selected data is raised through preprocessing; secondly, the chaotic grasshopper optimization algorithm (CGOA) is used to simulate the behavior of grasshoppers in nature to build a mathematical model, and the selected data sets are selected and optimized for features. Then, the support vector machine (SVM) performs classification processing on the quantitative data with reduced features. Empirical risk is calculated using the hinge loss function, and a regular operation is added to optimize the risk structure. Finally, slime mould algorithm (SMA) can optimize the process to improve the efficiency of SVM, making the algorithm more accurate and effective. In this study, Python is used to simulate the function of the corporate business finance risk prevention model. The experimental results show that the CGOA-SVM-SMA algorithm proposed in this paper achieves good results. After calculation, it is found that the prediction and decision-making capabilities are good and better than other comparative models, which can effectively help supply chain enterprises to prevent financial risks. [ABSTRACT FROM AUTHOR]

Assessing the risk of financial distress is an important component of effective management because it helps companies make right financial decisions, avoid potential risks and improve business operations. This study provides more empirical evidence on the role of the Z-Score model in predicting financial distress of companies in emerging markets like Vietnam. This research paper uses data from 30 companies that delisted on UPCOM due to financial distress and 30 companies with Z-score greater than 4.35 on Ho Chi Minh City Stock Exchange (HoSE) for 5 years from 2018 to 2022, corresponding to 300 observations. The selected companies have enough audited financial statement data during the research period which are collected from websites such as cafef.vn, vietstock.vn, and websites with data on companies' financial statements. The financial factors are taken from the balance sheet and income statement by the authors to calculate the Z-Score. The authors use the Independent-samples T-test with data collected delisted companies due to financial distress and stably listed firms on the Vietnam Stock Market to test whether there is a difference in Z-score and independent variables in the Z-score model between these two groups of companies. The research results show that, there is a significant difference in the Z-score and the factors in the Z-Score model between the group of listed companies and the group of delisted companies, and between companies with low level of financial distress and those with high level of financial distress. From the findings obtained, the authors have made suggestions and recommendations for relevant parties such as the State Securities Commission of Vietnam, users of financial statements, and companies in order to contribute to preventing and limiting the risk of corporate financial distress in the most effective way. [ABSTRACT FROM AUTHOR]

Entrepreneurs in the agribusiness sector in Ghana encounter numerous challenges due to the weak institutional framework in the country. This often leads to business failure and poor performance of agribusiness ventures. In this paper, we aim to highlight the significance of institutional support for agribusiness entrepreneurs and its crucial role in creating more opportunities for farm entrepreneurs and ensuring the success of farm ventures. The study analyzes empirical data collected from 246 maize farm entrepreneurs in Ghana using the Structural Equation Modelling technique (PLS-SEM). The findings show that regulatory and cognitive institutions have a more positive significant influence on the opportunity recognition and exploitation strategies of maize farm entrepreneurs. Both opportunity recognition and exploitation partially mediate the effects of regulatory, normative and cognitive institutional pressures and farm business performance. The study suggests that maize farm entrepreneurs appear to benefit from regulatory and cognitive institutions. The findings, therefore, have strong policy relevance. The results of this study contribute significantly to food policy aimed at boosting maize supply chain business and food security. [ABSTRACT FROM AUTHOR]

Harmonizing Member States' insolvency frameworks has been a goal for the European Union for the past years, dating back to 2016, when the European Commission issued a Proposal for a Directive on preventive restructuring frameworks, second chance and measures to increase the efficiency of restructuring, insolvency, and discharge proceedings [COM (2016) 723 final], based on the Commission's Recommendation regarding a new approach to business failure and insolvency [C(2014) 1500 final]. This led to the Directive (EU) 2019/1023 on preventive restructuring frameworks, on discharge of debt and disqualifications, and on measures to increase the efficiency of procedures concerning restructuring, insolvency, and discharge of debt, and amending Directive (EU) 2017/1132. One key topic addressed by the "Directive proposal" [COM(2022) 702 final] is the "pre-pack proceeding", meant to offer an efficient alternative for safeguarding businesses. Underlining the achievements of this Directive proposal by regulating pre-packed administrative proceedings is our scope in this paper. [ABSTRACT FROM AUTHOR]

This paper extends prior scholarly works on entrepreneurial failure, entrepreneurial resilience and learning from failure by examining how the effects of prior experiences of entrepreneurial business failure (EBF) manifest in the entrepreneurial process of subsequent venture formation. We elucidate the pre‐founding and post‐founding effects of prior EBF via insights drawn from 25 serial entrepreneurs in Nigeria. The findings demonstrate that entrepreneurs were often motivated to start another venture as a result of the economic hardship and social stigmatization that occurs after business closure. We identified a three‐stage fine‐grained process perspective of successive entrepreneurial engagement (e.g. pre‐founding, formation and development, and post‐founding conditions and effects on subsequent entrepreneurial ventures). These stages shed light on entrepreneurial fragility, entrepreneurial resiliency and the development of anti‐fragility capabilities that are conducive to subsequent venture formation and survival. We shed light on how individual‐level factors shape how prior failure experiences can shift from liability immediately after business collapse and at pre‐founding to become an asset during and after new‐venture formation. Such learning from past failure is vital in adapting to dynamic environmental changes, especially those observed in emerging‐market settings. Taken together, we demonstrate how entrepreneurs bounce back from errors, failures and setbacks. [ABSTRACT FROM AUTHOR]

Providing the microfinance to rural women is the prime concern of the government at central and state level in which the best microfinance programme is the Self Help Group Bank Linkage Programme. However, the Delinquency rate of the SHGBLP loan is on the higher side. As, borrowers do not make their loan repayments on time. The purpose of this research is to examine which types of self-help groups make timely repayments of an old loan. Also, to find out the different aspects of the loan delinquency rate which affect them and to find out the impact of self-help group maturity on loan repayment. For this a total of 300 members were selected from the Udaipur and Banswara district of Rajasthan. Further, Tobit Regression has been applied to find out the factors which affect the loan delinquency percentages in the Self Help Group Bank Linkage Programme. The results highlighted that the maturity of the SHG group affects their repayment performance as old SHGs are functioning well in terms of repayment. The reason for the high delinquency rate is that the members had no surplus Income to repay back because of the failure of Business, natural calamities and medical issues. The members who are repaying the loan back on time are giving from their agriculture and enterprise profits. A lot of research has been carried out on the Impact of SHGBLP on many other factors but there is no research that has been done to find out why the programme has high loan delinquencies after being the best together with the impactful microfinance programme. [ABSTRACT FROM AUTHOR]

The purpose of the paper is to propose two new procedures that deal with overfitting problem using neural techniques for variable selection and business failure prediction. The first procedure, called HVS-AUC, is based simultaneously on (i) the backward search, (ii) the HVS measure (Heuristic for Variable Selection), and (iii) the AUC criterion (Area Under Curve). The second procedure, called forward-AUC, is based on (i) the forward search and (ii) the AUC criterion. Using a sample of bankrupt and non-bankrupt firms in France, the implementation of the procedures using neural networks shows that the profitability, the repayment capacity, the taxation, and the importance of investment have a strong explanatory power in bankruptcy prediction. These procedures also provide more parsimonious and more efficient models compared to Linear Discriminant Analysis. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to identify the configurations of working capital and customer and supplier diversification employed by successful small and medium-sized enterprises (SMEs) before and during the COVID-19 pandemic. Design/methodology/approach: This study employed a combinatory methodology to analyze how 124 Brazilian SMEs configured – before and during the pandemic – the size of their working capital and their levels of dependency on clients and suppliers. Findings: High levels of working capital and supplier diversification were found to be key to SMEs' ability to thrive before and during the pandemic. However, while SMEs that were growing prior to the pandemic depended on a few major customers, firms flourishing during this time have divided their sales among many clients. Research limitations/implications: This study focuses on what configurations SMEs have adopted during the crisis. Qualitative studies are needed to identify how SMEs reconfigure themselves in the face of a major crisis. Practical implications: The results of this study indicate that SMEs hit by the pandemic should avoid retrenchment strategies. They might have better chances of success if they embrace their vulnerability and take risks to foster growth. Social implications: The results of the study can help SMEs respond to the economic crisis caused by COVID-19, which has already caused the failure of millions of businesses worldwide. Originality/value: This is the first empirical investigation of SMEs that are weathering the pandemic, and in this study, the authors have analyzed the three aspects of their operations, which have been struck the hardest by the crisis. [ABSTRACT FROM AUTHOR]

This paper presents a novel method that uses online ratings to predict business failures. The success, if not survival, of service businesses depends on their ability to satisfy their customers. Yet, businesses often recognize slumping customer satisfaction too late and ultimately fail. To prevent this, marketers require early warning tools. In this paper, we build upon online ratings as a direct measure of customer satisfaction and, based on this, predict business failures. Specifically, we develop a variable-duration hidden Markov model; it models the rating sequence of a service business in order to predict the likelihood of failure. Using 64,887 ratings from 921 restaurants, we find that our model detects business failures with a balanced accuracy of 78.02%, and this prediction is even possible several months in advance. In comparison, simple metrics from practice have limited ability in predicting business failures; for instance, the mean rating yields a balanced accuracy of only around 50%. Furthermore, our model recovers a latent state ("at risk") with an elevated failure rate. Avoiding the at-risk state is associated with a reduction in the failure rate of more than 41.41%. Our research thus entails direct managerial implications: we assist marketers in monitoring customer satisfaction and, for this purpose, offer a data-driven tool that provides early warnings of impending business failures. [ABSTRACT FROM AUTHOR]

The aim of this paper is to review the impact of entrepreneurs' attitudes toward the defined business risks on the perception of the future of small and medium-sized enterprises (SMEs). 454 SMEs from the Czech Republic (CR) participated in the research and completed an online questionnaire. Structural equation modelling and factor analysis were used to identify the causal relationships between the examined variables. Entrepreneurs' attitudes toward business failure also have a positive effect on the future of the SME. The perception of financial risk in positive indicators of financial performance and the perception of financial risk as part of the company's everyday life have the most significant impact on future business. Operational risk is reflected in the utilisation of corporate resources, reducing customer complaints about the quality of the company's products and the company's independence of a limited number of suppliers. The company's sales volume adequacy provides a source of market risk. It has the third strongest positive impact on the future business in the SME segment. The research results provide a valuable platform for the authors of national and regional development strategic plans looking for SME support and development as well as the authors of the relevant policies. [ABSTRACT FROM AUTHOR]

This paper identifies the relative importance of human and physical capital for entrepreneurship. Microfinance clients were offered business training and a loan lottery of up to seven times the average loan size. Business training increased business knowledge, reduced business failure, improved business practices, and increased household expenditures by US$82 per year. It also improved financial and labor allocation decisions. These effects are concentrated among male clients, however. Access to larger loans, in contrast, had little effect, perhaps because current loan sizes already meet the demand of most clients. Despite these positive impacts, business training was not cost-effective for the lender. [ABSTRACT FROM AUTHOR]

Copyright of Çankırı Karatekin University Journal of the Faculty of Economics & Administrative Sciences is the property of Cankiri Karatekin University, Faculty of Economics & Administrative Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Financial institutions use business failure forecasting models to manage their investments. The accuracy of the forecast is an important factor in determining how much capital is needed to cover credit losses. The majority of studies use traditional statistical methods to model business failures (e.g., discriminant analysis and logistic regression). Models constructed are usually quite inaccurate, however. It is due to the imbalance between the classes of training samples (bankruptcies account for a small percentage of all firms) that are used to construct the models. Currently, various machine learning methods such as the random forest method and the gradient boosting method are widespread. In this study, the main focus is on using extreme gradient growth to predict bankruptcy. Extreme gradient boosting, using LASSO or Ridge regularization, penalizes complex models to avoid overfitting. Also, during training, extreme gradient boosting fills in the missing values in the data set depending on the amount of loss. In this article, in order to increase the efficiency of extreme degree growth, it is proposed to use SMOTE technology to improve class balance. The quality values of the solutions obtained by the improved extremal degree increase are compared with the solutions obtained by other methods. [ABSTRACT FROM AUTHOR]

Although filing for bankruptcy is the primary form of economic relief for U.S. consumers in financial distress, pro se debtors lack access to the consumer bankruptcy system. An individual debtor faces many challenges when filing for bankruptcy without an attorney, since the debtor must rely on free access to the information provided by the U.S. Courts website. However, that information is vague and presented in complex legalese and dissuasive diction. On the other hand, U.K. debtors who need financial relief can file for bankruptcy through a clear and accessible bankruptcy filing process. U.K. debtors also have access to free consumer debt advice from a government-funded nonprofit organization, Citizens Advice. This paper discusses the differences in filing processes for U.S. and U.K. debtors. It ultimately concludes that the U.S. should implement similar filing processes to those in the U.K. to create a more accessible bankruptcy system, especially in the aftermath of the Covid-19 pandemic. [ABSTRACT FROM AUTHOR]

This article examines how passion affects an entrepreneur's business failure experiences. Our study explores the link between the type of passion an entrepreneur exhibits and the effect this has on the entrepreneurs' attitudes and reactions to business failure. We analyse the way in which passion type informs entrepreneurs identification with their business, and the entrepreneurial process. Entrepreneurs who experienced harmonious passion maintained an emotional distance from their business failure. Harmoniously passionate entrepreneurs had a rational perspective and were reflective, self-aware, adaptive and future oriented. Entrepreneurs who experienced obsessive passion, were defensive and reactionary about their business failure. Obsessively passionate entrepreneurs attached contingencies and experienced increased stress and conflict. Our findings suggest promising opportunities for future research on the interplay between heterogeneous passions, adaptive/maladaptive entrepreneurial action and regulated goal pursuit. [ABSTRACT FROM AUTHOR]

Decades into the digital era, publicly available data on Black, indigenous, and people of color (BIPOC) owned businesses are still remarkably lacking. In this commentary piece, the authors cover recent literature on the importance of BIPOC-owned businesses for equitable growth and BIPOC wealth-building. The authors then examine the sources of data that are available – public and private – for tracking the success or failure of such businesses. A BIPOC business database was constructed from a variety of sources and used by the authors to examine the potential pitfalls of such exercises. The authors close with a call for better data collection on BIPOC businesses. [ABSTRACT FROM AUTHOR]

In this paper we intend to substantiate the usefulness of Deep Learning, especially feedforward neuronal networks, in the prediction of business failure. This methodology provides very good results in terms of predictive performance when large sample sizes are available. Therefore, we have developed a business failure prediction model for European companies, based on this algorithm on a sample of 61,624 companies, of which 12,128 were declared bankrupt in 2016. As independent variables were considered ratios, and economic and financial data obtained from the financial statements for the year preceding the date of failure. Deep Learning achieves a predictive performance of 94%, where companies with larger size and lower solvency are more prone to failure. The obtained results have been tested on an independent test sample, different from that used to estimate and train the model. [ABSTRACT FROM AUTHOR]

Research has shown that most ventures fail, yet there has been limited work on investors' views of entrepreneurs who have failed in the past. We address this gap and call attention to an innate asymmetry between past failure and success. This asymmetry arises because success requires skill and luck jointly, whereas failure materializes due to either lack of skill (mistakes) or bad luck (misfortune). We ask: Are investors "failure-averse" and discount a failed entrepreneur even in the presence of additional information about entrepreneurial skill? Or do they make "rational inferences" in light of the additional skill information and proceed to fund the new startup? To test whether investors are failure-averse or engage in rational inference, we use experiments in the context of equity crowdfunding. The results suggest that prospective crowdfunding investors rationally integrate informational cues regarding past outcomes and entrepreneurial skill. [ABSTRACT FROM AUTHOR]

Family firms have continued to register low survival rates. Across the world, research puts the survival rate of family businesses beyond the third generation at a mere single digit. The dilemma is also that despite the high failure rate of family-owned firms, the world’s most enduring companies also belong to this class. What do they do differently from the majority of their peers? Succession planning tops the list of the 21st century’s paradoxical challenges facing family business enterprises. Past studies have been barely conclusive on whether and how succession planning, or the lack of it, affects business economic performance. The current study assesses the effect of succession planning on business economic performance. The study used a deductive approach, a survey research strategy, and an explanatory research design to fulfil its objectives. Data analysis was done through descriptive as well as inferential analyses. Regression analysis results indicated that succession planning is a statistically significant determinant of business economic performance. The study recommends that firms should improve their measures targeted towards the prior identification of roles and leadership positions that require successors. The study also recommends the enhanced preparation, grooming, and development of identified successors. [ABSTRACT FROM AUTHOR]

The article shares the commercial career of Abraham Salaman, an English Jewish merchant from London, England who migrated to California during the gold rush. It highlights the experiences of Salaman in trading goods and mining gold in mountains in Monterey, California, his business success in Grass Valley as gold mining operations became highly capitalized quartz mills, the failure of his ostrich-feather business and eventual return to London. Also noted is the absence of Jewishness in Salaman.

In the era of Industry 4.0, online entrepreneurship is gradually seen as an essential tool that brings innovative values to the integration and development of a country. The rapid failure of nascent businesses stemming from a lack of human capital directed this study to explore the role of students' knowledge and technological innovativeness in motivating students to form e-entrepreneurial intentions. Information collected from 405 students from universities in Vietnam via online questionnaires was analysed using SmartPLS 4 to test the relationships among seven factors proposed in the research model. The results show that entrepreneurial education and prior experiences are the foundation for improving students' perceived feasibility and usefulness, forming their entrepreneurial motivation. Next, entrepreneurial motivation becomes an important premise for promoting students' entrepreneurial intentions more effectively. Furthermore, the study found that students' technological innovativeness moderated the relationship between their entrepreneurial motivation and intention to set up a digital business. [ABSTRACT FROM AUTHOR]

This article presents a comparative analysis of machine learning models for business failure prediction. Bankruptcy prediction is crucial in assessing financial risks and making informed decisions for investors and regulatory bodies. Since machine learning techniques have advanced, there has been much interest in predicting bankruptcy due to their capacity to handle complex data patterns and boost prediction accuracy. In this study, we evaluated the performance of various machine learning algorithms. We collect comprehensive data comprising financial indicators and company-specific attributes relevant to the Pakistani business landscape from 2016 through 2021. The analysis includes AdaBoost, decision trees, gradient boosting, logistic regressions, naive Bayes, random forests, and support vector machines. This comparative analysis provides insights into the most suitable model for accurate bankruptcy prediction in Pakistani companies. The results contribute to the financial literature by comparing machine learning models tailored to anticipate Pakistani stock market insolvency. These findings can assist financial institutions, regulatory bodies, and investors in making more informed decisions and effectively mitigating financial risks. [ABSTRACT FROM AUTHOR]

The impact of coastal water quality and its interaction with business results is still an unexplored field. This study uses a probit model and estimates marginal effects to investigate the impact of chlorophyll a concentration in the Mar Menor (Spain) coastal waters on the probability of business failure of firms located in this area. This coastal area has been in a critical ecological condition since 1980 when intensive irrigation agriculture expanded to the surroundings of this salted lagoon. Therefore, identifying the most damaging productive activities is crucial to convince companies and policymakers to overcome this situation. The most remarkable findings of our study are the following. First, we find opposing geographical impacts on the probability of business failure for companies located on the Mar Menor coast: A location effect showing a decreasing probability of business failure for companies located near the Mar Menor and a pollution effect indicating an increased probability of failure due to proximity to water pollution. Second, we further identify the economic sectors in which the pollution effect outweighs the location effect. We find that most of the examined productive activities seem to be negatively affected by the pollution effect , overcoming the positive effect of being located near the Mar Menor. Third, marine eutrophication increases the probability of business failure for some economic activities but not for others. Concretely, agricultural and transport activities benefit from being near the coast despite the quality of the water. These firms' probability of failure decreases when they are located near the sea), whereas a 1 mg/m3 increase of chlorophyll a raises the probability of business failure for accommodation services (8.4%), minor trade (9.5%), financial and real estate services (11%), and industrial and building activities (14.4%). This paper highlights the need to design effective environmental regulations to preserve the area of Mar Menor, considering the specific productive characteristics of the different agents. We highlight the sectors requiring additional incentives to implement pro-environmental strategies and reduce their contribution to environmental pollution. The main insights from this analysis are applicable to other coastal areas around the world that suffer from marine eutrophication due to human activities. • This study provides evidence about the relevance of environmental characteristics on business behaviour. • Two opposing and significant effects have been found: geographical location and marine water pollution. • This study helps evaluate the sectors impacted by the deterioration of water pollution in Mar Menor. • These sectors require additional incentives to implement strategiesc to reduce environmental pollution. [ABSTRACT FROM AUTHOR]

Business failure often leads entrepreneurs to craft public narratives. Taking a performative storytelling perspective of such narratives, we investigate how entrepreneurs jointly reevaluate their ideas and identities, and how this relates to their subsequent career paths. We theorize that the stories entrepreneurs tell shape who they become, changing not only how others see them but also how they see themselves. This broadens theoretical understanding of how failed entrepreneurs navigate their transition to a diverse array of subsequent careers, including different forms of serial entrepreneurship (same industry; new industry) and exit (startup employee; established business employee; exit with reentry). [ABSTRACT FROM AUTHOR]

Doubtlessly, the primary goal of every construction company is to maximise profitability. Without this, construction companies cannot survive. Incidentally, Ugandan local construction contractors (LCCs) continue to collapse in a short period, despite enormous public and private investments in the construction sector. This study investigates the profitability of LCCs in Uganda. An investigation was conducted to develop a regression model that would enable LCCs to enhance their profitability and minimise business failure. A questionnaire survey was conducted to collect primary data from 47 local construction companies registered with the Uganda National Association of Building and Civil Engineering Contractors (UNABCEC) and secondary data were collected from audited books of accounts covering from year 2016 to 2018. Thirty-five valid responses were received, representing a response rate of 74%. Data were coded into SPSS version 25, analysed and displayed using the relative importance index (RII), statistical correlation and regression analysis. The findings indicated that the profitability of LCCs was unsatisfactory when compared to the profitability ratios recommended for the construction industry and those of contractors in other countries. The results also indicate that the profitability of LCCs is significantly affected by the timeliness of payments, cost of finance, competitive bidding environment, project delays, price fluctuations and corruption tendencies, in that order. The findings of this study will benefit construction industry players by providing awareness about the factors affecting the profitability of LCCs. A regression model to enhance profitability was developed using regression analysis. This will help LCCs enhance their profitability by developing mitigation strategies that prevent low profitability; consequently, business failure will be minimised. [ABSTRACT FROM AUTHOR]

The Cattle Livestock Business Insurance Program aims to provide protection for cattle from the risk of death and loss of cattle. This study aimed to determine the level of satisfaction of farmers with cattle business insurance in Gowa Regency, South Sulawesi Province. This research was conducted in May 2022. The population is all cattle farmers who follow cattle business insurance in Gowa Regency. The sample is farmers who follow cattle business insurance in Pattalassang sub-district, Gowa Regency amounted 45 people. The research method used was the interview method and FGD (Focus Group of Discussion). The type of data used is qualitative data, namely data in the form of words and quantitative data in the form of numbers or numbers Analysis of the data used with the CSI model. The results show that farmers feel much helped by the existence of AUTS which can minimize the risk of failure in the cattle business, namely the death of the cattle they receive, so that at least it can relieve and not be confused in looking for business capital again. It can also motivate and eliminate the worries of farmers to increase the scale of their business. Farmer satisfaction with AUTS is in the excellent category, which means very satisfied and in accordance with the expectations of farmers, both in terms of service characteristics, personal relationships, service arrangements and customer strength. [ABSTRACT FROM AUTHOR]

Micro and small enterprises (MSEs) are important to the local economy and are the most crucial source of employment in Thailand. Using the three-round survey data, we assess the impact of COVID-19 on the survival probability of MSEs in the tourism and manufacturing sectors. Enterprise characteristics such as owner characteristics, employment and business strategies are examined as potential factors to mitigate or stimulate business failures. The Cox proportional hazards model and Kaplan--Meier estimator are employed. Our findings reveal that the survival probability paths from the three rounds of survey show a gradual decrease of survival probability from the first week of interview and approximately 50% of MSEs could not survive longer than 52 weeks during the COVID-19 pandemic. We also find that the survival of MSEs mainly depends on location, number of employees, and business model adjustment, namely operation with social distancing and online marketing. Particularly, retaining employees and not reducing the working hours are one of the key factors increasing the survivability of MSEs. However, the longer length of the crisis reduces the contribution of these key factors. The longer the period of the COVID-19 pandemic, the lower the chance of MSEs survivability. [ABSTRACT FROM AUTHOR]

Failure to holistically manage risk in Small Medium Enterprises (SMEs) is one of the major causes of small businesses failure. To answer the research question as to what supports the adoption of Enterprise Risk Management (ERM) in SMEs, this research aims to analyse Risk Management (RM) in SMEs and develops a framework to facilitate the adoption of ERM. In achieving the primary objective, the research establishes for SMEs: the sources of information for RM; the importance of information governance in managing risk; the fundamentals of RM; and the pillars of RM. Previous research conducted on RM in SMEs reviewed the challenges of the successful implementation of ERM in SMEs and proposed different ways to address these challenges. The common ground reached by the research is that there is a need for the simplification of ERM in SMEs. We followed an interpretive philosophy with an inductive research approach and employed a qualitative methodological choice with a cross-sectional time horizon through data collection, employing a review of the scholarly literature, to, in the end, develop a conceptual Small Medium Enterprises Risk Management Framework (SMERMF). The limitation of the research is that the empirical part of the research has not been concluded yet. To present the results, that will be compared to the theory and conclude the research. [ABSTRACT FROM AUTHOR]

The going concern (GC) assumption forms the basis for preparing financial statements unless liquidation becomes imminent. ASU 2014-15 requires management to evaluate GC uncertainties quarterly and provide disclosures in the notes. I compare management GC disclosures between the pre-standard and post-standard regimes. I find that the market reacts negatively to substantial doubt in GC only after ASU 2014-15. Next, I find the effect of ASU 2014-15 for quarterly reports, but not annual reports. More importantly, by employing detailed textual analysis to extract and categorize mitigation-plan discussions, I show that certain types of management mitigation plans are interpreted more positively by investors after ASU 2014-15, thereby alleviating the negative market reaction. These plans include issuing debt, debt restructuring, increasing revenue, and selling assets. Finally, I demonstrate that management GC conclusions are more indicative of corporate failures after ASU 2014-15 and that mitigation-plan discussions are associated with firms' future viability. [ABSTRACT FROM AUTHOR]

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In case of failure, entrepreneurs could endure various financial, psychological, and social costs. These intertwined costs could affect their learning from failure. All individuals do not react in the same way when dealing with adversity. Rather than focusing on (negative) consequences of business failure, we took a more positive approach by using the Conservation of Resources (COR) model theory to build our conceptual model. Psychological capital, which refers to "an individual's positive psychological state of development characterized by high levels of self-efficacy, optimism, hope , and resilience," could be considered as a resource to recover from entrepreneurial setbacks. We suggest that a high level of psychological capital plays a mediating role in the relationship between the negative consequences of failure and learning from failure. By learning from this experience, failed entrepreneurs will increase their intention to re-create a venture and pursue their entrepreneurial career. This theoretical research, by building a conceptual model based on resources, offers a more positive approach of entrepreneurial failure and investigates key psychological assets, such as psychological capital, that support the development of entrepreneurial resilience rather than the prevention of business failure. [ABSTRACT FROM AUTHOR]

Innovation is often seen as essential for ventures to succeed. High business failure rates in entrepreneurship, however, suggest that innovations are frequently driven by entrepreneurs blinded by overconfidence. Thus, anticipating when and why entrepreneurs will be motivated to innovate is fundamental for entrepreneurial success. Using a large sample obtained from population surveys conducted in 77 countries, this study analyzes the variables that are significantly associated with innovative behaviors. The research tests a model proposing that the joint effects of hubris, growth aspirations, and an entrepreneur's level of entrepreneurial experience have a crucial impact on innovative endeavors. It finds that hubris is significantly related to entrepreneurs' growth aspirations and that ambition, in turn, is positively related to innovative behaviors. In addition, the study finds that both relationships are moderated by the level of entrepreneurial experience. These findings highlight the need to wise up amateur entrepreneurs before they embark on innovative endeavors. [ABSTRACT FROM AUTHOR]

Business failure and poor business results over a long period of time represent a sure path to crisis. In such conditions, the postulates of the so-called crisis management (Crisis management) are accepted as a necessity and the need for strategic restructuring imposes in the long run. Managers are often not able to recognize the symptoms and causes of the company’s crisis in time. This leads to a weakening of the business performance and business results of the company and eventually to the company’s entry into the business crisis. The strategic approach to restructuring encompasses a broader aspect of the activities that need to be carried out in order for a company to emerge from the crisis, survive and thrive. Which restructuring strategies to apply in times of corporate crisis largely depends on the current position of the company, goals, needs and ways out of the crisis. Also, we tested the statistical impact and comparison, types of restructuring of large enterprises in Bosnia and Herzegovina in relation to European Union enterprises. The results showed that our managers understand the importance of a strategic approach to corporate restructuring. In this respect, we do not statistically diff er signifi cantly from the countries of Western Europe, Central Europe, Eastern Europe, and Serbia. [ABSTRACT FROM AUTHOR]