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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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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.)

This article presents a systematic review of the existing literature on business longevity by conducting a bibliometric analysis of 142 papers published in the leading business history and management journals during the last three decades. The results show similarities (e.g. in explanatory models) and differences (e.g. in citation patterns, theories, and methods) between the disciplines, thus indicating that the literature is partially segmented into separate domains that prevent business longevity research from representing a truly unified field of study. [ABSTRACT FROM AUTHOR]

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]

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]

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]

The failure of construction companies is quite crucial because it results in unfinished projects and responsibilities that in turn result in many losses to governments, economies, owners, creditors, and surety companies. Previous research on the prediction of construction business failure utilized insolvency causes that were either arbitrary or based on the availability of data. Many scholars have shown the absence of, and need for, a holistic framework for the identification of the causes of construction business failure. As such, this paper reviews previous literature incorporating construction business failure applications, with the objective of identifying existing knowledge, current gaps, and needed future research directions on the different failure factors in a comprehensive approach. To this end, the authors (1) performed a meta-analysis of previous research work for a 30-year period spanning from 1988 to 2018; (2) identified and defined failure factors that impact the business operations of construction firms; and (3) utilized social network analysis to quantitatively identify the overlooked and missing construction business failure factors. Research results indicate that there are 20 factors that could collectively contribute to business failures of construction firms. It is also shown that there is a dire need for future research to better explore the impacts of some understudied critical factors, including the effect of inadequate company organizational structure and human capital on construction business failure. Another important finding is the absence of models that include a holistic incorporation of all 20 construction business failure factors. The findings herein are a significant contribution to the body of knowledge on construction business failure because they integrate the outcomes of previous works and use them to provide robust foundations for knowledge advancement. The presented guidelines are believed to close areas where an abundance of research work occurs and to unveil areas where additional research is necessary. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to find the differences in the impacts of financial factors on business failure and financial distress. Using the traditional logistic regression method, this paper studies the ability of financial indicators to predict business failure and financial distress of small and mid-sized enterprises in Portuguese high and medium-high technology manufacturing sectors. The research results show that: (1) differences between financially healthy firms and failed firms are more obvious than differences between financially healthy firms and financially distressed firms; (2) the accurate rate of failure prediction decreases with time prolonging (from one year to three years prior to the event), whereas that of financial distress prediction maintains stable at a relatively lower level; (3) profitability is the most important indicator, which is negatively related to the probability of both business failure and financial distress; (4) debt-related and liquidity-related factors (especially indebtedness and general liquidity) are also important in predicting business failure and financial distress. This paper enriches the research literature on the predictions of both business failure and financial distress. [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]

Purpose – The purpose of this paper is to help the financial institutions improve the predictability of business failure of supply chain finance (SCF) clients with the use of external big data set. Design/methodology/approach – A prediction model for the business failure of SCF clients was built upon different theoretical perspectives. Logistic regression method was deployed to test the model. Findings – The authors develop a model that illustrates several key determinants to predict the probability of business failure of SCF clients based on several theoretical perspectives. The results show that taxable sales revenue, frequency of making value added tax (VAT) payment, number of counterparty for VAT invoice issuance, frequency of VAT invoice issuance and firm age are negatively correlated with business failure of SCF clients while the VAT paid and industry clockspeed are positively correlated with their business failure. Practical implications – This paper shows how financial institutions can effectively leverage the external information sources through “unconventional” predictor variables in order to reduce the credit risks associated with business failure of SCF clients. Originality/value – This paper is one of the first to focus on the potential use of financial big data set from external sources to improve of predictability of financial institutions on the business failure of SCF clients. In addition, this paper is a pivotal study on the financial client risk assessment based on taxpaying behaviors, tax amount, firm and industry characteristics. [ABSTRACT FROM AUTHOR]

Today’s business entities face an ever-growing number of laws and regulations due to recent high profile business scandals and failures. Small and medium scale enterprises (SMSE) in developing countries do not have an efficient compliance checking mechanism to make their business processes compliant with these regulatory standards. This checking mechanism is needed to give the enterprises full assurance of complete adherence to regulatory standards, bodies, or Service Level Agreements. Therefore, a structured and efficient compliance management model is needed to aid SMSE in launching their businesses safely and to ensure business processes fit into the classical regulatory standards. This paper presents a business rules compliance checking model and architecture for SMSEs in developing countries to verify and monitor their business process models at design time and at run time. It involves a systematic compliance requirements classification and analysis that employs a goal based requirement engineering approach prior to design time verification. It also introduces the idea and demonstration of network analysis for runtime business processes monitoring. The business process model will be verified at design time using a Simple PROMELA Interpreter model checker through Linear Temporal Logic rules. The approaches were tested on a financial institution in Nigeria, a developing nation in Africa at the time of this research. In order to ensure that the choice of the requirements analysis approach was efficient, a number of standard metrics for evaluating requirements engineering techniques were used and promising results were obtained. We also carried out a comparative analysis of the proposed approach in this paper with the approaches of previous research papers. This approach proved to be effective in terms of clarity, simplicity, flexibility and expressiveness while reducing incomplete adherence of business processes and enhancing the correctness of the business process. [ABSTRACT FROM AUTHOR]

In this paper, we present an integrative perspective on organizational failure by conceptualizing three levels of failure--organizational learning processes (which can give rise to simple failures), organizational planning processes (which can give rise to complex failures), and strategic capacity for organizational agility (which can give rise to catastrophic failures)--as a Guttman-like model of escalating dysfunctions. Simple failures are the result of learning deficiencies stemming from single-loop decision making and weak learning competencies. Complex failures are caused by structural rigidities and intelligence pathologies. Catastrophic failures are a result of weak knowledge inclusiveness and weak organizational platforms, which occur from a downward spiral of events stemming from simple and complex failures. Areas for further study are suggested. [ABSTRACT FROM AUTHOR]

Research Background: The approach is based on theoretical sources and completed studies on business debt, debt level and repayment awareness and how this issue relates to SMEs in the Czech Republic. Purpose of the article: The main purpose of this paper is to examine the attitude of SMEs towards the issue of company debt and its position within the economy. This attitude is an inherent part of the company's risk management. Methods: Three researched issues (How strongly is company debt perceived as a financial risk factor; Does the company consider debt to be a serious matter in their business; What measures does the company take to reduce risk) supported by hypotheses, which verified the thesis, were statistically tested. Finding & Value added: Practical implications confirm the thesis that there is a belief that SMEs do not consider debt to be a critical factor of business risk and do not associate it directly with the major risk of business failure. SMEs do not view debt negatively and do not directly link debt to the risk of failure. Consequently, companies consider the risk of indebtedness as relatively insignificant. Their approach to indebtedness is therefore generally passive and they also believe that it will not jeopardize their business, and they will always somehow manage to solve it through insurance, risk avoidance and through creation of financial reserves. [ABSTRACT FROM AUTHOR]

Drawing on environmental sustainability orientation and business failure literature, we examined a thought‐provoking question: "Can adopting ambitious environmental sustainability initiatives lead to business failures and under what conditions is this more likely?" To address this question, we developed an analytical framework that provides new insights into how voluntary environmental initiatives affect the business environment and firm competitiveness. This paper also yields new insights on the features that emerge at adopting environmental initiatives–business failure nexus: from greening to growing, from greening to sustaining, from greening to constraining, and from greening to collapsing. Accordingly, the study accounts for the conditions under sustainability initiatives, and a variety of complex contextual factors are likely to culminate in closures of small and medium‐sized enterprises (SMEs). Although many top executives, entrepreneurs, and managers view implementation of environmental initiatives as tantamount to superior firm performance, the paper highlighted the effects of resource constraints and vulnerabilities of SMEs and new firms during the early stage of development, and therefore, pursuing aggressive green initiatives could minimize their life chances. Implications for scholars and practising managers are discussed. [ABSTRACT FROM AUTHOR]

Purpose: Any business model innovation process involves a certain level of uncertainty, complexity and, in effect, risk. A sloppy approach towards the management of risk may result in catastrophic, sometimes even fatal, consequences to a company's core business. Although risk, risk appetite and risk management are relatively wellestablished concepts, their role in business model innovation is not well understood. The objective of this paper is to investigate how the risk associated with the innovativeness of a business model innovation, an organization's risk appetite, and its risk management approach interact to affect the success or failure of a business model innovation process. Design: Retrospective case studies of business model innovations undertaken by three industrial companies provide the empirical basis for this paper. These companies were selected based on their relatively successful, yet somewhat different, business model innovation experiences over the years, and focused on the, in total four, cases in which they failed to implement their new business model attempts successfully. The reasons that led to these failures are discussed. Findings: Important factors explaining the business model innovation failure of these cases, appear to be the company's risk appetite, the risk associated with the radicality, reach and complexity of the business model innovation, the company's awareness of these risks and their management, and especially the association between these factors. Originality: There are many lessons to be learned from the aftermath of a failed attempt in terms of what not to do and what to improve a next time. The cross-case analysis produced six testable propositions that enhance our understanding of business model innovation success/failure, with particular focus on the characteristics of the business model innovation, overall innovation management, risk, risk awareness, risk appetite and risk management, and the interaction and fit between these six constructs. [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 report is commissioned to analyse strategic position of Sony in market with brief history analyses, core competencies analyses along with strategic recommendations for Sony. Several key models like SWOT, Bowman's Strategy Clock and other related concepts are discussed, the data used for this research paper data gathered form secondary data sources i.e. Annual reports, Journal articles, Book, newspaper articles etc. which are properly declared in "Reference" section. The rational decision for choosing Sony as a research study for this paper is that they have been market leaders and pioneered many markets, however due to lack of ambition and strategic planning failure the company is now on verge of bankruptcy. Towards the end this research paper has given some strategic direction recommendations for the board of directors of Sony Inc. which will help Sony to revive themselves from current position and restore their brand to former glory. [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]

Based on the interpretive structure model of system dynamics, this paper constructs a hierarchical structure model of factors affecting the entrepreneurial learning from failure, which has been also tested through a case of entrepreneurship. The study finds that: (1) there are 15 factors influencing entrepreneurial learning from failure that play different hierarchical roles; (2) the entrepreneurs' self-efficacy, as a key influencing factor of entrepreneurial learning from failure, can be cultivated and improved by enriched the entrepreneurs' successful career experience. In addition, emotion regulation after the entrepreneurial failure is also a key influencing factor of the entrepreneurial learning from failure and the emotion management is deemed as an important part of entrepreneurship education; (3) the entrepreneurial education may affect the entrepreneurship learning from failure indirectly by affecting the entrepreneurs' self-efficacy; (4) the economic conditions, the policy support, the industry characteristics and the cultural sensemaking of failure are the macro factors that may affect the entrepreneurship learning from failure. [ABSTRACT FROM AUTHOR]

The construction industry remains a major player of the Palestinian economy. Business failure is an important issue for companies in the Gaza Strip uncertain environment. This paper aimed to explore the critical factors that have the potential to cause contractor's business failure and to determine their level of severity from contractor's viewpoint. This paper has considered. Critical factors were listed under five groups: financial and political, contractual, managerial, organizational, and economical causes. Contractors have been advised to consider the most critical factors that have the potential to cause business failure. The most critical factors include: cost of materials, lack of resources, delay in collecting dibs from clients, monopoly, changing funding sources, dealing with suppliers and traders and Israeli attacks. [ABSTRACT FROM AUTHOR]

While the majority of those who declare bankruptcy do so voluntarily, a significant proportion are forced into bankruptcy as a result of legal action. This paper interrogates data obtained from the Australian Financial Security Authority to explore the attributes of debtors who go bankrupt involuntarily. Based on this analysis, the authors hypothesise that people who go bankrupt involuntarily are those who have more to lose by going bankrupt – such as a family home, a business venture or a managerial or professional occupation – meaning that they are more likely to resist bankruptcy until they are forced into it by their creditors. [ABSTRACT FROM AUTHOR]

Bankruptcy costs depend not only on the laws that govern financial distress but also on the ability of the court to rehabilitate distressed firms. This paper tests whether Chapter 11 restructuring outcomes are affected by time constraints in busy bankruptcy courts. Using the passage of the Bankruptcy Abuse Prevention and Consumer Protection Act as an exogenous shock to caseloads, I find that commercial banks report lower charge-offs on business lending when court caseloads decline, suggesting that the costs of financial distress are lower in less-congested courts. Further, court caseload affects how restructuring takes place. Less-busy bankruptcy judges liquidate fewer small firms, but more large firms. When caseload declines, large firms spend less time in court and firms that are dismissed from court are less likely to refile for bankruptcy. In addition, firms are less likely to sell assets or obtain debtor-in-possession financing in less-busy courts. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2808. This paper was accepted by Amit Seru, finance. [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]

Online product reviews play a major role in the success or failure of an E-commerce business. Before procuring products or services, the shoppers usually go through the online reviews posted by previous customers to get recommendations of the details of products and make purchasing decisions. Nevertheless, it is possible to enhance or hamper specific E-business products by posting fake reviews, which can be written by persons called fraudsters. These reviews can cause financial loss to E-commerce businesses and misguide consumers to take the wrong decision to search for alternative products. Thus, developing a fake review detection system is ultimately required for E-commerce business. The proposed methodology has used four standard fake review datasets of multidomains include hotels, restaurants, Yelp, and Amazon. Further, preprocessing methods such as stopword removal, punctuation removal, and tokenization have performed as well as padding sequence method for making the input sequence has fixed length during training, validation, and testing the model. As this methodology uses different sizes of datasets, various input word-embedding matrices of n-gram features of the review's text are developed and created with help of word-embedding layer that is one component of the proposed model. Convolutional and max-pooling layers of the CNN technique are implemented for dimensionality reduction and feature extraction, respectively. Based on gate mechanisms, the LSTM layer is combined with the CNN technique for learning and handling the contextual information of n-gram features of the review's text. Finally, a sigmoid activation function as the last layer of the proposed model receives the input sequences from the previous layer and performs binary classification task of review text into fake or truthful. In this paper, the proposed CNN-LSTM model was evaluated in two types of experiments, in-domain and cross-domain experiments. For an in-domain experiment, the model is applied on each dataset individually, while in the case of a cross-domain experiment, all datasets are gathered and put into a single data frame and evaluated entirely. The testing results of the model in-domain experiment datasets were 77%, 85%, 86%, and 87% in the terms of accuracy for restaurant, hotel, Yelp, and Amazon datasets, respectively. Concerning the cross-domain experiment, the proposed model has attained 89% accuracy. Furthermore, comparative analysis of the results of in-domain experiments with existing approaches has been done based on accuracy metric and, it is observed that the proposed model outperformed the compared methods. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to study the information content of about 3,300 global bank rating changes before and after the Lehman bankruptcy in September 2008 to assess if differences in stock market reactions for small and big banks emerge. Design/methodology/approach – The analysis of the stock market reactions of rating changes (upgrades and downgrades) and bank’s size (small and big) is conducted by an event study approach. Findings – The authors find that while upgrades are not associated with significant abnormal bank stock returns, downgrades have a significantly negative effect. This result holds for both small and big banks, while negative abnormal returns are considerably stronger for the former. For small banks, the authors observe an increase in negative cumulative abnormal returns post-Lehman. The lack of a reaction to large banks’ rating downgrades in the narrow [−1,+1] event window indicates that their stock prices may, to some extent, be insulated from negative rating information even post-Lehman, which the authors attribute to an implicit “too big to fail” subsidy anticipated by equity investors. Originality/value – This paper provides insights to the differences in the information content of changes in small and big banks’ credit rating on stock returns that is unrelated to the well-known size effect. Compared to small banks, big banks seem to some extent be insulated from negative rating changes even post-Lehman – contributing to the on-going too big to fail debate. [ABSTRACT FROM AUTHOR]

This paper illustrates the importance of referring to a dynamic approach when forecasting firms bankruptcies, paying a particular attention to French SMEs. Based on Shummay’s (J Bus 74:101–124, 2001), we build a duration model and extend it by incorporating unobservable heterogeneity. Moreover, we resort to a dynamic dichotomous specification in which “right side” censored data are taken into account. We emphasize the complexity of the calculations of integrals that must be implemented and show how to overcome this challenge by applying the Geweke, Hajivassiliou and Keane algorithm which involves the technique of the simulated maximum likelihood. The findings prove that our dynamic approach, which integrates macroeconomic variables and takes account of both random effects and exogenous shocks, provides credible results. Besides, our method provides the predictive content of macroeconomic variables and the unobservable heterogeneity, which is helpful in forecasting firms bankruptcies. [ABSTRACT FROM AUTHOR]

The paper deals with the issue of analyzing the financial failure of businesses. The aim was to select key performance indicators entering the DEA model. The research was carried out on a sample of 343 Slovak heat management companies. When addressing the research problem, we made use of multidimensional scaling (MDS) and principal component analysis (PCA), which pointed out the areas of financial health of companies that may predict their financial failure. The core of our interest and research was the data envelopment analysis (DEA) method, which represents a more exact approach to the assessment of financial health. The important finding is that the statistical graphical methods--PCA and MDS--are very helpful in identifying outliers and selecting key performance indicators entering the DEA model. The benefit of the paper is the identification of companies that are at risk of bankruptcy using the DEA method. The originality is the selection of key inputs and outputs to the DEA model by the PCA method. [ABSTRACT FROM AUTHOR]

Much evidence from recent antitrust cases casts doubt on the ability of conventional remedies to restore competition in digital markets. This paper considers three untested remedies for antitrust enforcement in digital markets: mandatory sharing of algorithmic learning (rather than the data itself); subsidization of competitors; and temporary shutdowns. All three remedies are radical from several perspectives. First, they go beyond halting specific anticompetitive conduct by actively seeking to restore structural conditions favoring competition. Second, they entail government interference with freedom of enterprise and property rights to a substantially higher degree than the market-driven process which normally governs antitrust remedy design. Third, all three remedies create complex tradeoffs, in that they could lead either to competitive benefits (e.g., the entry of new firms) or to harms (e.g., consumer losses in cases of platform shutdowns or anticompetitive coordination in cases of algorithmic sharing). All three thus require careful balancing before implementation. [ABSTRACT FROM AUTHOR]

Many prior studies on minority entrepreneurship have found that some consumers display a strong bias against products from minority ventures. Not surprisingly, discrimination against products sold by minority-owned businesses increases the failure rate for such ventures. This paper seeks to verify the extent of consumer discrimination for minority products, and investigates whether it varies among different products. Building on insights from the theory of consumer discrimination, we conducted a comparative behavior experiment on 155 subjects for the expected pricing of two new products (common products and products with ethnic characteristics). Consistent with prior literature, we found that potential consumers held a bias against common products from minority ventures and offered a lower price. However, the theory of consumer discrimination could not be applied to the products with ethnic characteristics. Instead, potential consumers viewed ethnic characteristics products from minority ventures as being high quality and offered higher prices. This finding complements the theory of consumer discrimination and provides useful knowledge for minority entrepreneurs: minority entrepreneurs can employ price discrimination to strengthen the ethnic brand's impression by integrating ethnic cultural features into new products. [ABSTRACT FROM AUTHOR]

This paper studies the effects of the recent housing crash on small business survival and household geographic mobility. Although a number of other works have studied these issues, our analysis differs from these because we do not focus only on underwater mortgages (less than 0% home equity), but also those slightly above water (0-10% equity). Homeowners with little or no equity face considerable constraints regarding moving, starting a business or keeping a current business open. They are more like underwater homeowners, but they differ enough to deserve a separate categorization in comparative studies, rather than being conflated with all other homeowners that have positive equity. We use the Federal Reserve’s Survey of Consumer Finances panel data for 2007 and 2009, which allows us to track the exact same households during this critical time in the housing crisis. [ABSTRACT FROM PUBLISHER]

Purpose In business, the failure to engage difficult conversations productively can prevent winning in the market and invite the competition to forge ahead. This study aims to identify areas in business where avoiding difficult conversations can put winning out of reach and present guidelines for handling difficult conversations in these domains.Design/methodology/approach This is a conceptual paper that presents guidelines on how to manage difficult conversations effectively.Findings This study shows how to manage difficult conversations with regards to the areas of compensation, performance, strategy and implementation.Originality/value This paper catalogs sources of lost value. Furthermore, this study outlines what is needed to capture such value, and briefly explains the principles for how to transform an organization to build such capability as a core competence. [ABSTRACT FROM AUTHOR]

The experience of the global financial crisis revealed that while many financial institutions were allowed to take excessive risks, the auditors failed in their duties to reasonably evaluate those risks as well as to inform the investing public about them. The issues of statutory auditors' liability and their public role are particularly relevant in Lithuania, considering the fact that over just the past few years the third and the fourth largest banks in Lithuania turned out to be insolvent. Analysis of legal actions against auditors of these banks highlighted certain shortcomings in the audit market and auditors' liability regulation, related to the quality and transparency of audit reports, auditors' accountability and independence requirements, and insurance of auditors' liability. In the first part of the paper the case analysis of Ernst & Young Baltic's responsibility for Snoras bankruptcy as well as Deloitte's responsibility for Ūkio bankas' insolvency, and discussion of the cases, are presented. The second part of the paper deals with the changes in regulation of the audit market in Lithuania and Europe, and issues left outside the reform. [ABSTRACT FROM AUTHOR]

Purpose: Based on theories related to coopetition, the purpose of this paper is to examine the patterns of business-to-business digital referrals inscribed in businesses' digital content. Design/methodology/approach: A complete industry-wise digital data set is formed by extracting digital referrals in all the content pages. The authors outline how digital referrals are strategically used among peer businesses in the peer-to-peer digital network and in the augmented digital network, taking into consideration geographical framing and physical distance. Findings: The authors reveal how geographical framing and physical distance influence peer-to-peer referral patterns in the digital space. Quite counter-intuitively, businesses are more likely to give digital referrals for peers residing in the same region, as well as for peers located in closer proximity. Further, results from the augmented digital network show that peer businesses in closer proximity exhibit greater strategic similarity in their digital referring strategy. Research limitations/implications: The findings extend the understanding of business-to-business coopetition to the digital space and suggest that geographical framing and physical distance can induce reciprocated relationships between peers by offering each other digital referrals. Practical implications: The findings shed light on the formation of a business-to-business digital coopetition strategy using digital referral marketing. Originality/value: This study highlights the impact of digital referrals in business-to-business relationship management, especially in the digital coopetition context. [ABSTRACT FROM AUTHOR]

This paper examines ownership equity as a predictor of future business failure within the tourism and hospitality sectors. The main goals of this study were to examine which ratios are the most important for a tourism business failure forecasting model and how significant is the "total percentage of equity ownership by company directors" ratio compared with other ratios associated with the probability of bankruptcy. A stepwise weight assessment ratio analysis (SWARA) was applied, and 12 tourism bankruptcy experts evaluated key ratios. Total percentage of equity ownership by company directors is considered a psychological factor, and it was identified as the fourth most important ratio for a business failure forecasting model. Academicians and practitioners can use the findings of this study whenever developing a forecasting model for tourism and hospitality enterprises. [ABSTRACT FROM AUTHOR]

In this paper, using primary data collected from business owners, we examine the nature and obstacles in the informal sector of Uganda. We find that education level matters in the selection of enterprises. The bulk of businesses, like eating kiosks, fish selling, shoe shining among others that require no specialized skill to operate were mainly run by primary school dropouts and those with no formal level of education. Furthermore, we find evidence of a strong entrepreneurial spirit among secondary school dropouts than at any other education level. Across all businesses surveyed, secondary school dropouts run a high number of informal enterprises. Evidence suggests that their motivation is driven by two key factors, namely, wanting to take advantage of an existing business opportunity and failure to find employment in the formal sector. The empirical results show that access to finance, crime, theft and disorder, electricity, water, taxes, burdensome inspections, and informal gifts are robust and significant obstacles to the operations of the informal sector in Uganda. Policies should focus on a regulatory framework that supports the sector to create secure livelihoods and generate employment opportunities for the unemployed rather than viewing the sector as a source of "illegality." Improving access to finance, providing regular power and water supply, and improving the tax regime would mitigate the obstacles faced by informal businesses leading to possible formalization. Informal sector businesses should not be perceived as "illegal entities" but rather complementary effort by an increasingly enterprising population in the country. [ABSTRACT FROM AUTHOR]

This paper aims identify the ways in which the risk generally and specifically operating the risk can compete in the failure or success of a business. For awareness phenomena, actions and events that can generate losses for the adoption of prudent behavior it is necessary in a first step to identify the types of risk that a company may face. For the company that makes the subject of this paper have revealed a risk of exploitation by means of operating leverage, expressing elasticity operating result of the company in relation to its turn over. Analysing the evolution of the society we found that increasing the volume of activity on the period under study led to an increase in operating leverage which means that society has become more risky because it involves revenue growth and increased operating costs. [ABSTRACT FROM AUTHOR]

This paper presents a new combined forecasting method that is guided by the soft set theory (CFBSS) to predict business failures with different sample sizes. The proposed method combines both qualitative analysis and quantitative analysis to improve forecasting performance. We considered an expert system (ES), logistic regression (LR), and support vector machine (SVM) as forecasting components whose weights are determined by the receiver operating characteristic (ROC) curve. The proposed procedure was applied to real data sets from Chinese listed firms. For performance comparison, single ES, LR, and SVM methods, the combined forecasting method based on equal weights (CFBEWs), the combined forecasting method based on neural networks (CFBNNs), and the combined forecasting method based on rough sets and the D-S theory (CFBRSDS) were also included in the empirical experiment. CFBSS obtains the highest forecasting accuracy and the second-best forecasting stability. The empirical results demonstrate the superior forecasting performance of our method in terms of accuracy and stability. [ABSTRACT FROM AUTHOR]

While considered uncommon in relation to U.S. corporate bankruptcies, an increasing number of Chapter 9 municipal defaults have occurred in the past twenty-five years. Bankruptcy has been voluntarily sought and, in most cases, successfully executed to overcome fiscal stress in U.S. cities of all sizes. This paper recounts the complex tale of the three largest U.S. public fiscal crises within the early 21st century: the City of San Diego, California, Jefferson County, Alabama, and the City of Detroit, Michigan. Fiscal stress in a local government threatens the quality of municipal services and diminishes citizen confidence in their local leadership. The cases illustrated in this paper highlight the continued importance of studying the reasons for and solutions deployed to overcome fiscal stress conditions in local government. The research findings are of particular relevance to fiscal officers hoping to avert similar emergencies today. [ABSTRACT FROM AUTHOR]

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]