This dissertation investigates three issues on business failure causality and prediction. First, a nonlinear model for mathematical programming based discriminant analysis is studied. This study proposes a nonlinear model that builds on the existing linear and quadratic models and allows for a more flexible degree of nonlinearity through a set of power parameters. The proposed nonlinear model is solved using a genetic algorithm and is tested against linear and quadratic models using real financial data. The results show that each model is better in certain cases, but the nonlinear model turns out to be the best overall among the three. Better performance of this nonlinear model appears likely, but a more robust solver would be required. Second, the relationship between aggregate business failures and macroeconomic conditions is studied from a causality perspective. A structural Vector Autoregression (VAR) is used while incorporating the recently developed causal inference method Directed Acyclic Graph (DAG). Particularly, DAG is used to provide a contemporaneous causal structure and the VAR results are summarized using innovation accounting techniques. The results show that during the period from 1980 to 2004 in the U.S., aggregate business failures were influenced by interest rates, but overall these failures appear to be far more exogenous than was found previously. Third, the effect of incorporating macroeconomic variables into business failure prediction models is investigated with a focus on the U.S. airline industry from 1995 to 2005. The attention is placed on prediction accuracy, parameter stability, and the effect of particular macroeconomic variables. The results show that the stability of parameters in the prediction model is improved when macro variables are added. In terms of prediction accuracy, the model augmented with a macro variable performed better in a jackknife prediction, but not in out-of-sample predictions. The macroeconomic variable found to be significant is the change of interest rate, which is probably related to the high level of leverage common in this particular industry. Also, the results demonstrate that a probability score can be used as a more informative evaluation measure than the current one based on cutoff probabilities.

This dissertation investigates three issues on business failure causality and prediction. First, a nonlinear model for mathematical programming based discriminant analysis is studied. This study proposes a nonlinear model that builds on the existing linear and quadratic models and allows for a more flexible degree of nonlinearity through a set of power parameters. The proposed nonlinear model is solved using a genetic algorithm and is tested against linear and quadratic models using real financial data. The results show that each model is better in certain cases, but the nonlinear model turns out to be the best overall among the three. Better performance of this nonlinear model appears likely, but a more robust solver would be required. Second, the relationship between aggregate business failures and macroeconomic conditions is studied from a causality perspective. A structural Vector Autoregression (VAR) is used while incorporating the recently developed causal inference method Directed Acyclic Graph (DAG). Particularly, DAG is used to provide a contemporaneous causal structure and the VAR results are summarized using innovation accounting techniques. The results show that during the period from 1980 to 2004 in the U.S., aggregate business failures were influenced by interest rates, but overall these failures appear to be far more exogenous than was found previously. Third, the effect of incorporating macroeconomic variables into business failure prediction models is investigated with a focus on the U.S. airline industry from 1995 to 2005. The attention is placed on prediction accuracy, parameter stability, and the effect of particular macroeconomic variables. The results show that the stability of parameters in the prediction model is improved when macro variables are added. In terms of prediction accuracy, the model augmented with a macro variable performed better in a jackknife prediction, but not in out-of-sample predictions. The macroeconomic variable found to be significant is the change of interest rate, which is probably related to the high level of leverage common in this particular industry. Also, the results demonstrate that a probability score can be used as a more informative evaluation measure than the current one based on cutoff probabilities.

No description available.

This thesis offers an explanation of the statistical modelling of corporate financial indicators in the context where the life of a company is terminated. Whilst it is natural for companies to fail or close down, an excess of failure causes a reduction in the activity of the economy as a whole. Therefore, studies on business failure identification leading to models which may provide early warnings of impending financial crisis may make some contribution to improving economic welfare. This study considers a number of bankruptcy prediction models such as multiple discriminant analysis and logit, and then introduces survival analysis as a means of modelling corporate failure. Then, with a data set of UK companies which failed, or were taken over, or were still operating when the information was collected, we provide estimates of failure probabilities as a function of survival time, and we specify the significance of financial characteristics which are covariates of survival. Three innovative statistical methods are introduced. First, a likelihood solution is provided to the problem of takeovers and mergers in order to incorporate such events into the dichotomous outcome of failure and survival. Second, we move away from the more conventional matched pairs sampling framework to one that reflects the prior probabilities of failure and construct a sample of observations which are randomly censored, using stratified sampling to reflect the structure of the group of failed companies. The third innovation concerns the specification of survival models, which relate the hazard function to the length of survival time and to a set of financial ratios as predictors. These models also provide estimates of the rate of failure and of the parameters of the survival function. The overall adequacy of these models has been assessed using residual analysis and it has been found that the Weibull regression model fitted the data better than other parametric models. The proportional hazard model also fitted the data adequately and appears to provide a promising approach to the prediction of financial distress. Finally, the empirical analysis reported in this thesis suggests that survival models have lower classification error than discriminant and logit models.

No description available.

In this thesis we develop a new model that explains the overall grief recovery process for abusiness failure on a family group level. The model builds on, and expands the theories ofanticipatory grief as presented by Shepherd, Wiklund, and Haynie (2009) and the dual processof coping presented by Shepherd (2003). The qualitative method used for this thesiswas a multiple case study approach, with an in-depth focus. Our main findings was the importanceof aligning the entrepreneurs anticipatory grief stage with the family’s coping process,by maintaining transparent and open relationships where information could easily beexchanged. In addition we found that maintaining this transparency was often difficult forthe entrepreneur due to a series of factors, which we refer to as a “barrier to informationflow”, which include everything from stress to societal interference. Finally we proposehow our model can be applied and used to generate further knowledge and additional researchon the emotional aspects of a business failure.

Thesis (PhD) -- AUT University, 2009. / Includes bibliographical references. Also held in print ( xi, 268 leaves : ill. ; 30 cm.) in the Archive at the City Campus (T 658.022 YOU)

<p> This research paper investigates the factors on business failure in the Maritime region of Canada via a sample study of Bricklin Canada Ltd. This sample illustrates· the effects of regionalism and geographic location on the manufacturing industry. This company's failure will be examined as how it arose from reasons including geographic isolation, regional disparities, externalities, scale economies and external forces. A study of this particular industrial failure will lend insights regarding the needs of future regional policy. Although businesses from these marginalized regions of Canada have realized success, there are still a great many steps yet to take. A means must be found to reintroduce a self-sustaining economy to these regionalized areas of Canada where it is lacking. </p> / Thesis / Bachelor of Arts (BA)

June 22, 1918, Alonzo Sergent fell asleep while conducting a train that plowed into another train killing 86 passengers and injuring another 187. 17 days later, July 9, 1918, two passenger trains collided head on in what became known as The Great Train Wreck of 1918, killing 101 people and injuring 171 people. The investigations and analysis of failure in both accidents can be attributed to a single person. During this month, the single person failed to operate the company’s train properly, which lead to a colossal disaster which affected numerous lives, loss of business revenue, loss of credibility, and had a huge social impact. Similar to an analysis of a colossal train wreck, this report focuses on the complexities behind colossal business failures, analyzes the reasons for failure and the role of the CEO, and proposes recommendations that can be used to guard future businesses against colossal failure. / text

O objetivo deste estudo é compreender como as características de um negócio anterior e as condições de seu fechamento impactam no recomeço empreendedor no Brasil. O mercado e a própria academia há muito se dedicam à compreensão do êxito empreendedor, todavia, apesar da alta frequência de insucessos, existe uma quantidade menor de estudos centrados nesta questão e menos ainda no recomeço. Através de uma pesquisa bibliográfica que percorreu os principais conceitos de empreendedorismo, elencou as mais destacadas barreiras ao sucesso empreendedor no Brasil e abordou as visões mais relevantes sobre o insucesso empresarial e o recomeço empreendedor, buscou-se a formação do alicerce de conhecimento deste trabalho. Metodologicamente a presente dissertação caracteriza-se como uma pesquisa empírica, de caráter exploratório e correlacional, que se apoiou em uma pesquisa de campo de natureza quantitativa para atingir seus objetivos. Sobre a amostra pode-se defini-la como intencional, voluntária e não-probabilística. A partir destes elementos conduziu-se a análise dos resultados que mostraram que, para esta amostra pesquisada, existe uma significativa influência dos fatores dos negócios anteriores nos novos empreendimentos. Em termos gerais estes fatores apontaram para uma evolução das condições de recomeço empreendedor, porém quando elementos mais ligados a experiências de fracasso (como dívidas, processos trabalhistas e outros) se fazem presentes no negócio anterior, as condições para recomeçar a empreender tornam-se mais difíceis. Além disso, constatou-se que aspectos mais ligados ao ambiente de negócios como acesso a recursos financeiros, relacionamento com o Estado e interesse em ampliar a mão de obra tendem a evoluir menos no recomeço do que indicadores mais internos como capacitação e espírito empreendedor. / The objective of this study is to understand how the characteristics of a previous business and the conditions of its closure impact on the entrepreneurial restart in Brazil. The market and the academy have long been engaged in the understanding of entrepreneurial success. However, despite the high frequency of failures, there is a smaller number of studies centered on this issue and still less in the act of restarting. Through a bibliographical research that covered the main concepts of entrepreneurship, highlighted the most relevant barriers to entrepreneurial success in Brazil and addressed the most relevant visions of business failure and entrepreneurial resumption, the foundation of knowledge of this work was carried out. Methodologically the present dissertation is characterized as an empirical research, of exploratory and correlational nature, that was based on a quantitative field research to reach its objectives. Regarding the sample, it can be defined as intentional, voluntary and non-probabilistic. From all these elements the analysis of the results showed that, for this sample surveyed, there is a significant influence of the factors of the previous businesses in the new ventures. In general terms, these factors pointed to an evolution of the conditions of entrepreneurial restart, but when elements more related to experiences of failure (such as debts, labor lawsuits and others) are present in the previous business, the conditions to start again become more difficult. In addition, it was found that aspects more related to the business environment such as access to financial resources, relationship with the State and interest in expanding the workforce tend to evolve less in the restart than more internal indicators such as capabilities and entrepreneurial spirit.