Failed Firms Research Articles

Knowledge mobility after tourism entrepreneurial failure: Life after death?

There has been limited conceptualization in tourism of the knowledge consequences of firm failure despite overall high failure rates. There is no simple dichotomy between the lost knowledge of failed firms and knowledge survival in successful firms. This paper therefore elaborates a three-stage conceptual model of the post-failure trajectories of knowledge. The model focusses on the distinctive combination of tacit and codified knowledge in context of impure public goods, their distribution within and beyond the firm, and their micro and macro determinants. Three main post-failure trajectories are identified: cold storage/black hole of knowledge, knowledge recovery, and knowledge recombination. A research agenda is outlined for this neglected aspect of tourism knowledge research which has significant implications for innovation.

Back From the Dead: Exploring the Tension Between Imagination and Custodianship in Revenant Organizations

Organizational actors often look to the past to revive practices of the past. A growing body of research suggests that there is opportunity in the past and highlights how dormant or declining industries have been revitalized. We take this line of research a step further by examining how entrepreneurs (reanimators) revive long-since-failed organizations (revenants), a process we refer to as reanimation. Thus, rather than create a “new” venture, many entrepreneurs are turning to revive defunct or “dead” organizations. On the one hand, the act of reviving a dead organization suggests that reanimators perceive value in the failed organization's past; otherwise, why not start something new? On the other hand, theory predicts organizational actors might likely avoid such associations with the past since they are rooted in failure. As such, understanding what elements of an organization's past an entrepreneur retains or discards and how organizational leaders successfully reanimate failed firms is critical to our understanding of entrepreneurship and tradition. During this reanimation process, we observe a fundamental tension between imagination and custodianship. We find that the entrepreneur's ability to resist the urge to leverage their imagination through innovation and instead act as a custodian by honoring the past influences the organization's prospects for survival post-reanimation. Our theorizing offers guidance for understanding the inherent tensions between innovation and tradition in firms with rich histories, the potential downsides of unchecked imagination, and the importance of gaining stakeholder acceptance before exercising the authority to innovate.

A Novel Political Optimizer-Based Feature Selection with an Optimal Machine Learning Model for Financial Crisis Prediction

In today’s digital environment, business intelligence advances make it difficult to stay competitive and up to date on business trends. Decision-making in the financial industry is increasingly being powered by big data and machine learning. A decision-making process may be thought of as any sequence of processes that an individual goes through in order to select the option or course of action that is most suitable to meet their needs and necessities. The ability to anticipate the onset of a financial crisis is a significant economic phenomenon. A nation’s economic development and strength can be gauged by its capacity to provide an accurate assessment of the number of failed firms and the frequency with which they fail. The economics of the globe have been ravaged by recent global crises like as the COVID-19 pandemic and other recent environmental, financial, and economic disasters, which have marginalized efforts to construct a maintainable economy and civilization. The health and growth of a nation’s economy can be determined by precisely estimating the number of enterprises that will fail and the number that will succeed. Historically, there have been numerous strategies for constructing a successful financial crisis prediction (FPC) method. Effectively predicting business failures is a gauge of a country’s economic health. Several strategies are available for effective FCP. Classification performance, forecast accuracy, and legality are insufficient for practical use. Several of the suggested methods work for some issues. The specific dataset is not expandable. To improve classification, design a good prediction model adaptable to several datasets. An effective financial crisis prediction method (FPC) requires the right qualities. ML models can also be used to classify a company’s financial health. This research presents political optimizer-based feature selection (POFS) with optimal cascaded deep forest (OCDF) for FCP in big data environments. Hadoop Map Reduce handles huge datasets. POFS reduces computing complexity by handling feature selection. POFS is an original FCP algorithm categorization using OCDF. SFO is used to optimize CDF model parameters. A thorough simulation study was performed to evaluate POFS performance on benchmark datasets OCDFs. The results confirmed the POFS-OCDF method’s superiority over state-of-the-art approaches. With an outstanding sensitivity of 0.912, specificity of 0.953, accuracy of 0.944, F-score of 0.930, and Matthews correlation coefficient (MCC) of 0.912, the proposed POFS-OCDF technique has shown optimum results. The experimental results demonstrated that the POFS-OCDF technique outperformed other recently developed strategies on a variety of criteria. As previously stated, Sunflower optimization (SFO) is also used to tune the Cascaded Deep Forest (CDF) parameters. A detailed simulation analysis is performed based on the benchmark dataset to evaluate the higher classification efficiency of the POFS-OCDF technique. The invention of the POFS algorithm for FCP exemplifies the work’s originality.

Poison pills adoption, real earnings management and IPO failure

PurposeThis paper examines the relationship between poison pills, real earnings management and initial public offering (IPO) failure.Design/methodology/approachThe authors sampled 2,997 IPO firms that went public during 1993-2015.FindingsThe authors find that IPO firms manipulate earnings upward using real earnings management. The authors also find that IPO firms exhibiting a higher level of real earnings management have a higher probability of IPO failure. In addition, the authors find that weak shareholders' governance is positively associated with IPO failure.Practical implicationsThese results suggest that poor governance structures in failed firms open the door to manipulating real activities and increasing operational risk.Originality/valueThe study findings are of most significant interest to potential investors and other stakeholders affiliated with a firm going public, an auditor, an underwriter, the lawyers who consult with the firm and employees or executives who might consider joining that firm.

Do NBFCs propagate real shocks?

Notwithstanding a smaller share of total loans vis-à-vis commercial banks, we investigate a possible role of Non-banking financial companies (NBFCs) in propagating a real shock to the rest of the economy. Our two-sector model captures emerging economy characteristics such as NBFC borrowings from commercial banks, heterogeneities in financial constraints, and labour market friction faced by firms. Our theoretical and simulation results, using Indian parameters, indicate that an idiosyncratic shock (i.e., higher realization of the failed firms) and a sectoral productivity shock (in the sector financed by NBFCs) increase the interest rate charged by the banks, and the unemployment rate while reducing the real wages and per capita capital formation. However, the reverse happens given a structural shock, assumed as an increase in the average number of failed firms. Early detection of such shocks and quick policy intervention are required to provide a cushion for capital formation and job creation.

Estonia ∙ Failing Firm Defence: There Is a First Time for Everything

Estonia ∙ Failing Firm Defence: There Is a First Time for Everything

Influence of earnings management on forecasting corporate failure

This paper studies the relationship between corporate failure forecasting and earnings management variables. Using a new threshold model approach that separates samples into different regimes according to a threshold variable, the authors examine regimes to evaluate the prediction capacities of earnings management variables. By proposing this threshold model and applying it innovatively, this research reveals boundaries within which earnings management variables can yield superior corporate failure forecasting. The inclusion of earnings management variables in corporate failure models improves failure prediction capacities for firms that manipulate substantial earnings. Furthermore, an accruals-based variable improves predictions of failed firms, but the real activities-based variable improves predictions of non-failed firms. These findings highlight the importance of indicators of the magnitude of earnings management and the tools used to improve the performance of corporate failure models. The proposed model can determine the predictive power of particular explanatory variables to forecast corporate failure.

Bankruptcy prediction using multivariate grey prediction models

PurposeIn the face of complex and challenging economic and business environments, developing and implementing approaches to predict bankruptcy has become important for firms. Bankruptcy prediction can be regarded as a grey system problem because while factors such as the liquidity, solvency and profitability of a firm influence whether it goes bankrupt, the precise manner in which these factors influence the discrimination between failed and non-failed firms is uncertain. In view of the applicability of multivariate grey prediction models (MGPMs), this paper aimed to develop a grey bankruptcy prediction model (GBPM) based on the GM (1, N) (BP-GM (1, N)).Design/methodology/approachAs the traditional GM (1, N) is designed for time series forecasting, it is better to find an appropriate permutation of firms in the financial data as if the resulting sequences are time series. To solve this challenging problem, this paper proposes GBPMs by integrating genetic algorithms (GAs) into the GM (1, N).FindingsExperimental results obtained for the financial data of Taiwanese firms in the information technology industries demonstrated that the proposed BP-GM (1, N) performs well.Practical implicationsAmong artificial intelligence (AI)-based techniques, GBPMs are capable of explaining which of the financial ratios has a stronger impact on bankruptcy prediction by driving coefficients.Originality/valueApplying MGPMs to a problem without relation to time series is challenging. This paper focused on bankruptcy prediction, a crucial issue in financial decision-making for businesses, and proposed several GBPMs.

International Accounting and Earnings Quality in Ex-post Failed Firms

The study analyses whether sales manipulation in failed firms that adopted the International Financial Reporting Standards (IFRS) differ from that of failed firms non-adopters. The inquiry is motivated by a paucity of research on the consequences of IFRS reporting for failed firms. Using a sample of UK bankrupt firms, it finds that IFRS adopters exhibit earnings management as opposed to non-adopters of IFRS by implementing real operating actions. The results show that failed firms adopters have, on average, negative abnormal cash flows, given their reported levels of sales while this is not the case for non-adopters. The study explores the motivation for these observations by analysing the setting of the UK GAAP and IFRS. The contribution of this study is that while failed firms have been reported to manage earnings, this appears to persist with IFRS failed firms when compared to non-IFRS firms. It indicates that high-quality IFRS standards may have the unintended consequence of assisting failed firms adopters in exploring real earnings management options when compared to non-IFRS failed firms.

A new tool for failure analysis in small firms: frontiers of financial ratios based on percentile differences (PDFR)

ABSTRACTThis paper proposes an innovative methodology based on the use of differences between percentiles to compute the scores and distances to failure of a specific firm or group of firms. This approach is based on significant differences between the group of failed firms and the population to which the failed firms belong (meaning the same industry, period and geographical zone selected) and eliminates the effects of correlation between the factors selected to compute the scores. The use of accounting ratios, which can be computed using data available in the mandatory financial statements, and the homogenisation of these variables using percentiles make percentile difference frontier of ratios a tool specially oriented to small and medium-sized enterprises (SMEs). Our results for the selection of the most discriminant variables are consistent with those of previous studies, and the hit rates of failed and non-failed firms outperform those of the commonly used traditional methodologies. In addition, the proposed methodology enables us to compute distances to failure of both individual firms and groups of firms. Finally, this methodology identifies which of the financial drivers used are strengths or weaknesses for the specific firm or group of firms under study for purposes of a potential reorganisation.

Rescuing Icarus: the European Commission's approach to dealing with failing firms and sectors in distress

In Greek mythology, Icarus is given wings made of feathers and wax by his father as a means to escape exile. Experiencing flight for the first time ashe makes his escape, Icarus dares to fly too near the sun despite his father's warnings not to do so. His wax wings melt in the heat and Icarus consequently plunges to his death in the sea. The Commission is faced with a challenging task when dealing with firms in financial distress, some of them with falls befitting Icarus. This article focuses on three such concrete situations that the Commission has to manage: the “Failing Firm Defence” in merger control cases, restructuring agreements in declining sectors (also called “crisis cartels”) assessed under Article 101 TFEU, and undertakings’ inability to pay fines under point 35 of the Fining Guidelines. In all three situations, the Commission carries out a similar assessment of the financial health of the “failing” firm or sector, and in each case, the Commission's approach is rather formalistic. While the Commission advocates the same public policy concern across the board, namely to protect competition in a market, the criteria aimed at doing this are set out slightly differently in each of the three situations. The aim of this article, however, is not to argue for a more relaxed approach to competition policy as the standard, but rather for a more refined pragmatism that would also be more aligned to the effects-based competition enforcement adopted by the Commission in recent years.

A unified framework of explanations for strategic persistence in the wake of others’ failures

Purpose– Although strategic persistence remains a key issue in change management and strategy literature, the understanding of strategic persistence in the face of other businesses’ failure remains limited. The purpose of this paper is to examine factors that determine strategic persistence in the face of other businesses’ failures.Design/methodology/approach– Through a review and synthesis of the multiple streams of research, the paper provides a number of explanations for strategic persistence. The study complements the analysis with illustrative cases of failed companies. These led to development of an integrated framework of explanations for strategic persistence in the wake of other businesses’ failures.Findings– The analysis led to identification of individual, firm-specific and environmental factors rooted in past events (i.e. past successes, prior commitment and decisions by the top-management team), present circumstances (i.e. nature of the failure) and future outlook (i.e. paradox of success, looming threats and opportunities), which foster strategic persistence. The paper uncovered that persistence may also stem from factors such as “paradox of success” and “too much invested to quit”.Research limitations/implications– The paper suggests that organisations can learn from others’ failures without compromising their values by drawing on the expertise released by failed firms. The study also identified various mechanisms through which organisations can learn from the failure of others and factors that constrain them from doing so.Originality/value– The theorisation and conceptualisation of the literature accommodates the multiple and contrasting perspectives of the subject such as the environmental buffers and paradox of success.

Finance company failure in New Zealand during 2006–2009: Predictable failures?

Over 31 finance companies (non-bank deposit takers) failed in New Zealand over the 2006–2009 period. With an estimated loss of over NZ$3 billion, there was public outcry and a parliamentary inquiry into the causes of the failures, but few have asked if this was a predictable event. We find that failed finance companies have lower capital adequacy, inferior asset quality, more loans falling due, higher earnings and lower cash flows. Furthermore, failed companies have a longer audit lag and some trustees appear to have a greater percentage of failed firms than others. Our logistic model can successfully classify failure one year before for 88.7% of companies. Our logistic model (neural network) can also correctly classify up to 87.5% (83.3%) of a holdout sample. Our results are of interest to regulators and practitioners, as we show that publicly available data could distinguish between failed and non-failed finance companies.

Merger Incentives and the Failing Firm Defense

The merger incentives between profitable firms differ fundamentally from the incentives of a profitable firm to merge with a failing firm. We investigate these incentives under different modes of price competition and Cournot behavior. Our main finding is that firms strictly prefer exit of the failing firm to acquisition. This result may imply that other than strategic reasons, like economies of scale, must be looked for to understand why firms make use of the failing firm defense. However, when products are sufficiently heterogenous, we find that (i) the failing firm defense can be welfare enhancing and (ii) a government bail‐out increases total welfare when the number of firms is sufficiently low.

Corporate Bankruptcy: Assessment, Analysis and Prediction of Financial Distress, Insolvency, and Failure

This paper is divided into three sections that address the various elements of understanding, predicting and analyzing corporate failure and bankruptcy. Part I covers the definitions of corporate failure, explains the bankruptcy process and then classifies various potential causes of failure into broad categories. The causes are bifurcated into company-specific versus external factors. The company-specific factors include an in depth discussion and analysis of business causes versus financial causes, as well as the interrelation between the two. The most important factors, such as financial and operating leverage, are explored in great detail to gain a better understanding of their implications and impact on corporate failure. Part II covers various approaches for analyzing corporate risk and predicting corporate failure. It first details the credit analysis process from the perspective of lenders and credit agencies as a method for credit evaluation and prediction of default. Then, it provides an in depth explanation of financial ratio analysis as a prediction method and provides an overview of the main statistical prediction models. It concludes with a discussion of the implications of the model findings with respect to the causes detailed in Part I. Lastly, Part III describes the outcome of the study performed to analyze the causes of failure as described in Part I by using a combination of the methods highlighted in Part II. The purpose of the study is to identify the sequence and magnitude of relative ratio deterioration in failed firms in order to establish the relative frequency of the various categories of causes of failure. Various ratios and metrics were used as proxies for relative liquidity complications, profitability issues, business problems, and leverage concerns. The impact of macroeconomic events is also evaluated by isolating the impact of the 2008-2009 recession on the relative ratio measures.

Changing Mind in Changed Circumstances: Aegean/Olympic II and the Failing Firm Defence

For the first time, the Commission cleared a concentration it had rejected a few years before. This signals that the Commission sometimes changes its mind in the assessment of concentrations and that, as a result, counsel may consider re-notifying, with new arguments, an operation that had earlier been blocked. In the case at issue (Aegean/Olympic II), the failing firm defence, which was previously unsuccessful, was finally accepted because of changed circumstances. The case raises the question whether the conditions for a successful application of the failing firm defence may be too stringent, thus leading to some unintended negative consequences. Another question is the extent to which the Commission should rely on competitors' views when analysing the possibility of entry in a specific market.

Financial Institution Failure Prediction Using Adaptive Neuro-Fuzzy Inference Systems: Evidence from the East Asian Economic Crisis

This paper introduces the use of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) into the area of finance for Thai firms. This study started with collecting financial data from 82 finance companies and 15 commercial banks operating in the period 1992-1997, before the East Asian economic crisis occurred. Financial data on failed and non-failed firms were then examined to develop fuzzy rules based on CAMEL variables. ANFIS is applied to the area of finance for Thai firms for constructing failure prediction models. These models show that prediction accuracy is greater than 90 percent for one to five years prior to failure, indicating the robustness of models over time. In experiments, models yield more accurate forecasting than a logistic model that has been used in the area of finance for Thai firms. The purpose of this study is to present thatmodels using ANFIS are better suited for financial data sets with high nonlinearity than a logistic model.

Dupes or Incompetents? An Examination of Management's Impact on Firm Distress

AbstractThis article examines whether managers impact firm performance. We conservatively define managerial ability as the manager's capacity to deploy the firm's resources. We verify the validity of our metric using a manager–firm matched panel data set that allows us to track managers (CEOs) across different firms over time. We find managerial ability is inversely related to the amount of time a firm spends in distress, the likelihood of a firm's failure, and the cost of failure. These results suggest that the managers of failed firms are less skilled than their counterparts. But even within failed firms there is heterogeneity in the talents of managers.

Corporate Governance and Corporate Failure

The purpose of this research is to examine the influence of corporate governance characteristics on the corporate failure of listed companies in Sri Lanka. This study utilized publicly available data from annual reports of a sample of 70 failed firms and a sample of matched 70 non failed firms listed on Colombo stock market for a period covering the 2002 to 2008 financial years with logistic regression analysis. Corporate governance characteristics comprises with board size, CEO duality, outside directors, outsiders’ ownership, audit opinion, presence of an audit committee and remuneration of board members. Outside director ratio, presence of an audit committee and remuneration of board members turn out to be negatively associated with the probability of corporate failure, While CEO duality is positively related with the likelihood of corporate failure. Board size, auditor's opinion and outside ownership do not appear to be significant determinants. The paper offers evidence on the extent to which corporate failure associated with corporate governance. It would be educational to investors, financial analysts, accounting professionals, management and be helpful for regulatory authorities in making decisions, evaluations and policies.

Duration analysis of corporate bankruptcy in the presence of competing risks

The bankruptcy duration of reorganized firms should be different from that of failed firms. Adopting a competing risk model and using the Korean corporate bankruptcy data, we confirm the differences in reorganized and failed cases. We find that the failure decision of bigger firms seems delayed (the too-big-to-fail-too-early hypothesis). In systemic bankruptcy, the bankruptcy period is shortened and the reorganization bias is increased (Super Chapter 11 principle). Also, if bankruptcy is filed in a poor business environment, reorganization may occur faster and failure slower for that company (handicapped signal theory).