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Journal articles on the topic 'Financial business failure'
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Flores-Jimeno, Rocío, and Inmaculada Jimeno-García. "Dynamic analysis of different business failure process." Problems and Perspectives in Management 15, no. 2 (2017): 486–99. http://dx.doi.org/10.21511/ppm.15(si).2017.02.
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This work is framed in the research of business failure. We examine a method of analyzing the dynamics of financial failure. The authors examine a method of analyzing the dynamics of financial failure, because our goal is to analyze how the economic and financial indicators show the risk of failure in a group of companies. Using a sample of 163 companies declared bankrupt or dissolved, the authors show how to depict company trajectories of behavior and movement to terminal failure. They analyze these trajectories to find and describe empirical evidence of the different dynamics of bankruptcy. The authors also show that the estimation of failure risk is more accurate when these different failure trajectories are defined. In conclusion, the authors can see that there are different failure trajectories. One can use these different trajectories to identify more efficiently the indicators warning of the failure risk of the companies analyzed.
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Yip, Angela Y. N. "Business Failure Prediction: A Case-Based Reasoning Approach." Review of Pacific Basin Financial Markets and Policies 09, no. 03 (2006): 491–508. http://dx.doi.org/10.1142/s021909150600080x.
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Case-based reasoning (CBR) is a problem-solving paradigm that uses past experiences to solve new problems. Nearest neighbor is a common CBR algorithm for retrieving similar cases, whose similarity function is sensitive to irrelevant attributes. Taking the relevancy of the attributes into account can reduce this sensitivity, leading to a more effective retrieval of similar cases. In this paper, statistical evaluation is used for assigning relative importance of the attributes. This approach is applied to predict business failures in Australia using financial data. The results in this study indicate it is an effective and competitive alternative to predict business failures in a comprehensible manner. This study also investigates the usefulness of non-financial data derived from auditor's and directors' reports for business failure prediction. The results suggest that the particular non-financial attributes identified are not as effective as the financial attributes in explaining business failures.
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Maricica, Moscalu, and Vintila Georgeta. "Business Failure Risk Analysis using Financial Ratios." Procedia - Social and Behavioral Sciences 62 (October 2012): 728–32. http://dx.doi.org/10.1016/j.sbspro.2012.09.123.
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Restaino, Marialuisa, and Marco Bisogno. "A Business Failure Index Using Rank Transformation." International Journal of Economics and Finance 11, no. 1 (2018): 56. http://dx.doi.org/10.5539/ijef.v11n1p56.
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The global financial crisis entails a renewed attention from financial institutions, academics, and practitioners to corporate distress analysis and its forecasting. This study aims to propose a model for predicting default risk based on a business failure index using rank transformation. The procedure suggested is able to capture firms’ financial difficulties and forecast bankruptcy through the construction of a failure index based on some relevant financial ratios. By means of the estimation of failure probability, it allows to classify and predict business distress in time to take mitigating action. This procedure is evaluated by some accuracy measures on a sample of Italian manufacturing firms, and is found to be a suitable instrument for preventing financial distress.
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Nkwinika, Eugine, and Olawale Olufemi Akinrinde. "An investigation into the financial challenges affecting the success of entrepreneurs in South Africa." Technology audit and production reserves 6, no. 4(74) (2023): 36–44. http://dx.doi.org/10.15587/2706-5448.2023.292555.
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The object of this study is the financial difficulties that impacted the success of business owners in Hatfield, Gauteng province, South Africa. Compared to a global failure rate of 50 %, five out of every seven entrepreneurs in Hatfield, South Africa fail during the first year of operation. This study aimed at looking into the relationship between entrepreneur failure and financial literacy. The methodology employed in this study is interpretive philosophy-based qualitative research. An ethnographic research technique was also used to analyze the current economic condition of business owners in Hatfield. The population was sampled using non-probability purposive sampling techniques. Semi-structured interviews were used to gather the study's leading source of data. The primary research results are thematically examined while also considering the secondary sources. Eliminating financial and liquidity constraints was listed as a goal of financial literacy. Findings garnered revealed that financial, liquidity and credit restrictions are the primary causes of business failures in Hatfield. The lack of financial resources for new businesses in Hatfield, as revealed, prompted several liquidity issues in Hatfield, and further lowers the growth rate of Hatfield businesses. It was discovered that Hatfield's entrepreneurs usually experienced premature failure due to inadequate financial education and training. Impliedly, Hatfield business owners possessed poor cash management, defaulting on loan payments due to lack of financial education. Conversely, only few entrepreneurs and business owners in Hatfield, South Africa possess financial literacy competence with the necessary skills needed to better analyze their financial statements appropriately and increase profitability of their business. The practical implication of this finding is that, most entrepreneurs have high possibility to experience premature business liquidity when they have low or no financial literacy.
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Kušter, Denis. "Financial ratio indicators as early predictors of business failure: Evidence from Serbia." Anali Ekonomskog fakulteta u Subotici, no. 00 (2022): 5. http://dx.doi.org/10.5937/aneksub2200005k.
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The problem of corporate bankruptcies has intrigued the scientific community for years due to its practical significance. There is no country whose economic well-being is not affected by business failures. The research problem stems from the lack of analyses related to the issue of business failures in the the Republic of Serbia. The main aim of this research paper is to determine whether ratio indicators are relevant in predicting business failure one, two and three years before bankruptcy proceedings start. The research was conducted on a sample of 100 companies from the territory of Serbia. The data for ratios calculation was taken from the official website of the Business Registers Agency. Statistical analysis is based on Mann-Whitney test, which is used to identify differences between two groups with respect to a variable (ratio). The test was conducted in IBM's SPSS v.26 tool. Results of the research indicate that financial ratios can be useful for business failure prediction even three years before bankruptcy proceedings start, since there are statistically significant differences in ratio values between bankrupt and solvent companies.
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Kantar, Lokman, and Ayşegül Ertuğrul Ayrancı. "Estimating Financial Failure in Businesses Using Artificial Neural Networks: Turkish Manufacturing Industry Model Study." Journal of Corporate Governance, Insurance, and Risk Management 9, no. 2 (2022): 327–40. http://dx.doi.org/10.56578/jcgirm090203.
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Businesses need to be financially successful to achieve sustainable growth and maximise firm value. The financial failure of businesses is a situation that is carefully monitored by business managers, shareholders of the business, financial institutions that lend to the business, and the government. For this reason, in this study, the financial failure of 153 manufacturing companies operating in Turkey and traded on Borsa Istanbul has been tried to be estimated. In the research, the annual financial statements between the years 2009-2021 were used and artificial neural networks were preferred as the estimation method. Altman's Z score was used to define financial failure. In the artificial neural network model, 13 financial ratios were used as input variables. As the output variable, the firms that were below the value of 1.81 calculated as the Z score by Altman were considered unsuccessful, and the unsuccessful firms were assigned a value of 1 and the others a value of 0. This dummy variable consisting of 0 and 1 values is accepted as the output variable. According to the findings of the study, 1427 of 1631 observations that were initially considered to be financial failures were correctly estimated and a very high success rate of 87.49% was achieved. The findings will provide an important advantage to businesses and all stakeholders in terms of determining the causes of financial failure in advance.
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Laitinen, Erkki K. "Financial and non-financial variables in predicting failure of small business reorganisation." International Journal of Accounting and Finance 4, no. 1 (2013): 1. http://dx.doi.org/10.1504/ijaf.2013.053111.
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Dvorský, Ján, Zora Petráková, and Vendula Fialová. "PERCEPTION OF BUSINESS RISK BY ENTREPRENEURS ACCORDING TO EXPERIENCE WITH THE BUSINESS FAILURE." International Journal of Entrepreneurial Knowledge 8, no. 1 (2020): 76–88. http://dx.doi.org/10.37335/ijek.v8i1.104.
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The aim of the article is to compare the attitudes to business risks and business failure among entrepreneurs that have experience with bankruptcy and entrepreneurs that do not have experience with bankruptcy in the business environment of small and medium-sized enterprises. The main objective of the article is to evaluate business risks: market, economic, financial, strategic, personnel, legal, and operational risk; and statements about the experience with business failure. Questionnaires of 454 small and medium-sized enterprises were collected and prepared for evaluation in 2020. Statistical hypotheses were rejected through the statistical method Z- test. The results showed interesting findings. The most important business risks are the market, financial, and personnel risk according to entrepreneurs. Entrepreneurs without the experience of business failure have more positive attitudes (66.7%), and there is no risk of bankruptcy to their company for 5 years than entrepreneurs with experience of business failure (45.2%). The next finding is that entrepreneurs without the experience of business failure have more positive attitudes (60.6%) to the rate of the market risk (lack of sales for my company) as adequate than entrepreneurs with experience with business failure (38.4%). Also, it was shown that entrepreneurs without experience with business failure have more positive attitudes (59.8%) to the error rate of employees, which is low and has no negative impact on my (our) business than entrepreneurs with experience of business failure (53.4%).
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Chen, Jianguo, Ben R. Marshall, Jenny Zhang, and Siva Ganesh. "Financial Distress Prediction in China." Review of Pacific Basin Financial Markets and Policies 09, no. 02 (2006): 317–36. http://dx.doi.org/10.1142/s0219091506000744.
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We use four alternative prediction models to examine the usefulness of financial ratios in predicting business failure in China. China has unique legislation regarding business failure so it is an interesting laboratory for such a study. Earnings Before Interest and Tax to Total Assets (EBITTA), Earning Per Share (EPS), Total Debt to Total Assets (TDTA), Price to Book (PB), and the Current Ratio (CR), are shown to be significant predictors. Prediction accuracy achieves a range from 78% to 93%. Logit and Neural Network models are shown to be the optimal prediction models.
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Huang, Shi-Ming, Chih-Fong Tsai, David C. Yen, and Yin-Lin Cheng. "A hybrid financial analysis model for business failure prediction." Expert Systems with Applications 35, no. 3 (2008): 1034–40. http://dx.doi.org/10.1016/j.eswa.2007.08.040.
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Terceño, Antonio, Hernán Vigier, and Valeria Scherger. "Prediction of Business Failure with Fuzzy Models." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 26, Suppl. 1 (2018): 21–38. http://dx.doi.org/10.1142/s0218488518400020.
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This paper extends the theory of fuzzy diseases predictions in order to detect the causes of business failure. This extension is justified through the advantages of the reference model and its originality. Moreover, the fuzzy model is completed by this proposal and some parts of it have been published in isolated articles. For this purpose, the fuzzy theory is combined with the OWA operators to identify the factors that generate problems in firms. Also, a goodness index to validate its functionality and prediction capacity is introduced. The model estimates a matrix of economic- financial knowledge based on matrices of causes and symptoms. Knowing the symptoms makes it possible to estimate the causes, and managing them properly, allows monitoring and improving the company’s financial situation and forecasting its future. Also with this extension, the model can be useful to develop suitable computer systems for monitoring companies’ problems, warning of failures and facilitating decision-making.
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Arzou, Nabil, and Miloudi Kobiyh. "Analysis of the legal, financial, and organizational determinants of business failure: A case of an emerging market." Corporate Law and Governance Review 7, no. 2 (2025): 50–62. https://doi.org/10.22495/clgrv7i2p5.
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The research examines the financial, legal, and organizational factors of business failure in Moroccan companies. It highlights the importance of understanding these determinants for formulating effective preventive measures and supporting business stability. The literature review explores the definition of business failure in Moroccan companies, legal determinants such as the legal framework and bankruptcy procedures, and financial determinants such as financial ratios and factors specific to Moroccan companies (Sami, 2013). The research methodology proposes using financial, legal, and organizational data, along with statistical analyses, to obtain relevant results using the structural equation modeling (SEM) method through SmartPLS 3.3.2 software. It detects a significant involvement of legal, financial, and organizational factors. The article acknowledges the limitations in analyzing the determinants of business failure in Moroccan companies due to incomplete and unreliable data. It emphasizes the need for in-depth studies on specific factors and the importance of external factors such as the economic and political context. Legal, financial, and organizational determinants are identified as important, but a broader consideration of internal and external factors is recommended to better understand business failure. Extensive research could lead to more effective preventive measures and interventions.
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Abdel Kader MOULAYE ISMAIL, Dr Moulaye. "ENTERPRISE BANK RELATIONSHIP: ISLAMIC FINANCE AND THE FINANCIAL FAILURE OF COMPANIES IN MAURITANIA." RIMAK International Journal of Humanities and Social Sciences 06, no. 02 (2024): 194–210. http://dx.doi.org/10.47832/2717-8293.28.12.
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Building a strong business-bank relationship involves clear communication, transparency about your company's financial needs, and understanding the services offered by the bank. Regularly review and update your financial strategy with your bank to ensure it aligns with your business goals. Islamic finance in Mauritania operates in compliance with Sharia principles, avoiding interest-based transactions. While it can provide ethical financial solutions, business failure can still occur due to various factors such as economic instability, mismanagement, or external market conditions. Evaluating risks, adhering to Islamic financial principles, and implementing sound business practices are crucial to mitigate the potential for failure. Financial failure can result from a variety of factors, including poor financial management, excessive debt, economic downturns, or inadequate market research. It's essential for businesses to maintain financial discipline, regularly assess their financial health, and adapt strategies to changing circumstances to minimize the risk of financial failure. Seeking professional advice, managing cash flow effectively, and maintaining transparency in financial reporting are key practices to safeguard against financial setbacks. This research addresses the bank-business relationship by emphasizing the role of Islamic finance in the fight against business failure. The outline of our article is as follows: 1) A literature review on microfinance and its role in financing SMEs and also its role in the fight against unemployment among young graduates. It will be a literature that sweeps from the regional context to an international context. 2) Identification of research hypotheses and development of a questionnaire 3) Analysis of quantitative data using SPSS software and validation of hypotheses. Proposal for a modeling for the relationship between microfinance and the fight against youth unemployment in Mauritania. 4) Discussions of scientific results and recommendations for future research avenues
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Purves, Nigel, Scott Niblock, and Keith Sloan. "Are organizations destined to fail?" Management Research Review 39, no. 1 (2016): 62–81. http://dx.doi.org/10.1108/mrr-07-2014-0153.
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Purpose – The purpose of this paper is to explore the non-financial causes of organizational success or failure, provide a better understanding of the symptoms of financial distress and improve the predictive capacity of financial failure models. Design/methodology/approach – The paper utilizes exploratory case studies in investigating the relationship of non-financial factors to organizational success or failure across a sample of sector-specific Australian firms listed on the Australian Stock Exchange. A two-tailed study was designed, in which seven cases from both extremes were chosen from three Australian business sectors: finance, property and manufacturing. Findings – Non-financial factors associated with the organizations studied impacted their success or failure. These factors included management skill, experience and involvement in organizational strategy, feedback and resultant activity, together with board of director composition. The identification of financial and non-financial factors and sound internal processes could be utilized for the development of an early warning predictor of organizational success or failure. Research limitations/implications – The use of this method is very time-consuming but is highly valuable in case study research, providing a more in-depth understanding of how non-financial factors impact organizational success or failure. Practical implications – The research will provide a better understanding of the symptoms of financial distress and improve the predictive capacity of financial failure models. The improvement in prediction of organizational failure will reduce the costs of failure to all areas affected, from the large corporation to the small business. The inter-connectivity of all businesses to each other often results in a knock-on effect of failure with the cost being borne by all members of the community in some manner. The level of social impact and cost of failure can only be seen by the enormous costs of the Global Financial Crisis failures. Originality/value – This paper contributes to the literature on effective qualitative research and explores important areas of consideration for those conducting qualitative multiple-case studies. It is intended to be of use to researchers investigating the area of predictors of organizational failure or success.
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Souza, Ashley D., and Chandrashekhar R. "Application of Altman’s Z-score model in predicting business failures of selective hospitality companies in India." BOHR International Journal of Finance and Market Research 2, no. 1 (2023): 44–49. http://dx.doi.org/10.54646/bijfmr.2023.20.
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Business failure and bankruptcy are the two words that create panic among stakeholders of the organization. However, with a challenging environment, businesses feel the heat and struggle to make big in the long run. It is recommended to foresee the warning signs and predict business failures to avoid company-specific catastrophes. Numerous predictive models were developed over the last six to seven decades, and among many, Altman’s Z-score model is considered one of the highly reliable models in predicting business failure. The purpose of the research is to find out the financial performance of the companies selected for the study and to identify whether business failure can be predicted in advance to manage future risks. This paper considers Altman’s Z-score model that is used to predict business failures of public companies. A total of 10 hospitality organizations listed in the National Stock Exchange of India are considered for the study. The study analyzes the 5-year financial data from the 2018 to 2022 period. The study reveals that hospitality companies in India are undergoing a difficult phase post-pandemic. Nine out of ten companies selected for the study showed signs of bankruptcy as Altman’s Z-score of companies considered for the study is lower than 1.8 which is in the distress zone.
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R, Seenivasan. "The successful and failure of entrepreneurs of small industrial business with emphasis on their level of education and training." Journal of Management and Science 10, no. 1 (2020): 56–63. http://dx.doi.org/10.26524/jms.2020.7.
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This paper examines the determinants of business start-up, long and short-term success, and failure of small businesses. Entrepreneurs and small firm success and failure have been the subject of extensive research. It is important to understand the external, internal, and motivational factors responsible for business start-up, the barriers faced during the initial and continuous stages of trading and the advice and assistance available to entrepreneurs. This paper is aiming in explaining the main factors are related to successful and failure of entrepreneurs in small industrial business in Ahvaz city. Based on a random sampling 51 enterprisers marked as successful and failures are selected. The data collected based on a triangulation method (interview, questionnaire, and observation). The results show that: a- from the failure entrepreneurs point of view the following issues were important effects on their weak performance and failure their business: weak managing technical skills, financial issues, planning and organizing of their business, economic issues, informal issues, weak managingconceptual skills, personnel skills, education and low training, and weak human relation. b- from the successful entrepreneurs point of view the following issues were important effects on their high performance in their business: suitable managing technical skills, selecting appropriate personnel with relevant skills, education and paying more attention to personnel training,application of management conceptual skills, financial issues, better human relation, recognizethe economic situation, planning and organizing of their business and informal issues.
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Romero Martínez, Mariano, Pedro Carmona Ibáñez, and José Pozuelo Campillo. "The Impact of Environmental Risk on Business Failure: A Fuzzy-Set Qualitative Comparative Analysis Approach with Extreme Gradient Boosting Feature Selection." Algorithms 18, no. 4 (2025): 225. https://doi.org/10.3390/a18040225.
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Corporate performance is increasingly impacted by environmental issues, but their specific role in business failure remains underexplored, which leads to a gap in research that is often focused exclusively on financial metrics. By investigating the relationship between environmental financial exposure and business failure, this study addresses this gap, integrating financial ratios and environmental variables to understand how environmental performance affects financial viability. A novel dual-stage methodology was employed, first using Extreme Gradient Boosting (XGBoost) for feature selection to identify the most significant predictors of failure from a dataset of Spanish companies (N = 38,456) using 2022 ORBIS data. Next, a fuzzy-set qualitative comparative analysis (fsQCA) was applied to analyze the sufficient causal configurations leading to a high propensity for business failure. The analysis identified three distinct causal configurations associated with failure. All highlighted poor financial performance indicators, such as low results per employee and low profit per employee. Notably, one configuration identified high environmental risk (measured by TRUCAM) as a core condition contributing significantly to financial distress. These findings highlight the critical link between environmental responsibility and financial health, demonstrating the benefits of combining fsQCA with machine learning to identify intricate causal configurations and providing information to companies and governments who want to support long-term financial stability and corporate sustainability.
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Pereira, José Manuel, Mário Basto, Cláudia Cunha, and Amélia Silva. "Modelling business bankruptcy for audit purposes." Dutch Journal of Finance and Management 7, no. 1 (2024): 27080. http://dx.doi.org/10.55267/djfm/14568.
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To facilitate informed decision-making and foster transparency, stakeholders require access to reliable financial information. Financial audits serve the purpose of assisting companies in achieving success by assuring the accuracy and transparency of their financial statements. However, due to the evolving and increasingly competitive nature of markets, companies may exhibit indicators of financial vulnerability, commonly referred to as "red flags." These warning signs could potentially lead to business failure and bankruptcy. To mitigate such risks, predictive models for assessing the likelihood of business failure have been developed. Such models offer valuable decision-making support for auditors, enabling them to identify and mitigate risks associated with financial distress. The primary objective of this study is to develop a predictive model based on logistic regression and compare its effectiveness with traditional audit opinions. The sample comprises Portuguese small and medium-sized enterprises from the textile sector. Data were collected from the SABI database (Iberian Balance Analysis System). For the years 2017 and 2018, 371 insolvent SMEs and 2412 active SMEs were obtained. Through empirical analysis, it was found that regression models possess greater predictive capability compared to conventional audits. The application of these models significantly enhances the accuracy of assessing a company's financial status, thereby enabling professionals to provide more informed and appropriate opinions.
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Dvorský, Ján, Aleksandr Ključnikov, and Jiří Polách. "Business risks and their impact on business future concerning the entrepreneur’s experience with business bankruptcy: case of Czech Republic." Problems and Perspectives in Management 18, no. 2 (2020): 418–30. http://dx.doi.org/10.21511/ppm.18(2).2020.34.
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The article aims to determine the difference in the perception of selected business risks and their impact on the future of business concerning the entrepreneur’s experience with business bankruptcy. The case study involved 73 small and medium-sized enterprises (SMEs) with experience of business bankruptcy and 381 SMEs without the experience of business bankruptcy from the Czech Republic (CR). Linear regression models were used to verify statistically significant causal relationships between selected indicators of the most significant business risks and respondents’ perceptions of the future of business. The results brought interesting findings. The attitudes of entrepreneurs show that personnel, market, and financial risk are among the three most significant business risks. Experience with business failure is not a significant factor in determining the impact of market indicators on the business’s perceived future. The adequacy of sales of services and products has the greatest impact. The experience of the bankruptcy of SMEs is important in financial risk attitudes. According to entrepreneurs who have no experience with bankruptcy, the perception of financial performance has the greatest direct impact on the future of business. Conversely, for entrepreneurs who have experienced bankruptcy, the ability to properly manage financial risk on the company’s future has the greatest direct impact.
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Durica, Marek, Katarina Valaskova, and Katarina Janoskova. "Logit business failure prediction in V4 countries." Engineering Management in Production and Services 11, no. 4 (2019): 54–64. http://dx.doi.org/10.2478/emj-2019-0033.
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Abstract The paper presents the creation of the model that predicts the business failure of companies operating in V4 countries. Based on logistic regression analysis, significant predictors are identified to forecast potential business failure one year in advance. The research is based on the data set of financial indicators of more than 173 000 companies operating in V4 countries for the years 2016 and 2017. A stepwise binary logistic regression approach was used to create a prediction model. Using a classification table and ROC curve, the prediction ability of the final model was analysed. The main result is a model for business failure prediction of companies operating under the economic conditions of V4 countries. Statistically significant financial parameters were identified that reflect the impending failure situation. The developed model achieves a high prediction ability of more than 88%. The research confirms the applicability of the logistic regression approach in business failure prediction. The high predictive ability of the created model is comparable to models created by especially sophisticated artificial intelligence approaches. The created model can be applied in the economies of V4 countries for business failure prediction one year in advance, which is important for companies as well as all stakeholders.
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Hermawan, Zakaria Khori. "Financial Feasibility of Service-Based Business." Journal Integration of Social Studies and Business Development 2, no. 2 (2024): 77–85. http://dx.doi.org/10.58229/jissbd.v2i2.241.
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In Indonesia, over 6,300,000 toddlers are affected by stunting. Research indicates that the prevalence of stunting among children of working mothers is 30.6%. Despite the associated health risks, many working mothers prefer formula milk as a substitute for breast milk. Mengasihi, a health technology start-up providing breast milk powdering services for personal use, aims to offer babies a simple and effective nutritional solution. This study investigates the financial feasibility of Mengasihi as an early-stage start-up. It was found that cash flow plays a crucial role in start-up failure, impacting long-term organizational success. A feasibility study assessed Mengasihi's financial viability, analyzing internal and external financial conditions using criteria such as Payback Period, Net Present Value (NPV), and Internal Rate of Return (IRR) based on five-year financial projections. The results indicate that the Mengasihi project is financially viable, and an implementation plan was provided as part of the study.
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Zhai, Shan‐Shan, Jeong‐Gil Choi, and Francis Kwansa. "A Financial Ratio‐Based Predicting Model for Hotel Business Failure." GLOBAL BUSINESS & FINANCE REVIEW 20, no. 1 (2015): 71–86. http://dx.doi.org/10.17549/gbfr.2015.20.1.71.
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Liou, Fen‐May, and Chien‐Hui Yang. "Predicting business failure under the existence of fraudulent financial reporting." International Journal of Accounting & Information Management 16, no. 1 (2008): 74–86. http://dx.doi.org/10.1108/18347640810887771.
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Alifia Marchellina and Satrio Bhamakerti. "Evaluasi Kinerja Finansial Sebagai Langkah Antisipasi Terhadap Potensi Kegagalan Keuangan." Jurnal Kewirausahaan Cerdas dan Digital 1, no. 1 (2024): 14–25. http://dx.doi.org/10.61132/jukerdi.v1i1.27.
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This research aims to investigate the importance of financial performance evaluation in predicting the potential financial failure of a business entity. Financial performance evaluation is a critical step in assessing a company's financial stability and health and in identifying early signs of potential bankruptcy. In this research, the financial performance analysis method is used to measure the company's financial health holistically. The research results highlight that proper financial performance evaluation can provide a clear view of potential future financial failures, enabling management to take appropriate anticipatory steps.
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Freeman, Willoe, Peter Wells, and Anne Wyatt. "Insights from the failure of the Countrywide Financial Corporation." International Journal of Managerial Finance 10, no. 1 (2014): 115–36. http://dx.doi.org/10.1108/ijmf-12-2012-0131.
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Purpose – This paper aims to evaluate the business activities, financial reports, and management compensation practices of Countrywide Financial Corporation (Countrywide) in the period preceding the company's financial distress and leading to its eventual takeover by Bank of America in 2008. This analysis provides a number of insights into the risks that Countrywide was exposed to which may guide future research and financial management. Design/methodology/approach – Case study evaluating the failure of Countrywide Financial Corporation. Findings – First, Countrywide was highly reliant upon the securitization of mortgage loans to finance its activities and this was apparent in the financial reports. Second, these securitization transactions exposed Countrywide to significant financial risks, including the risk inherent in the uncertain values of residual interests and warrantees. Problematically, these risks were not transparently reflected in the financial reports, as confirmed by the lag in the timing of stock price responses. This untimely market response suggests the equity market was not aware of Countrywide's risk exposures until shortly before the company's solvency crisis. Third, the compensation practices of Countrywide encouraged and rewarded management for exposing the firm to significant risks. Practical implications – This paper provides insights into financial management that are relevant for researchers and professionals. Originality/value – This paper provides insights for researchers and practitioners relating to the impact of asset securitization on business risk and how these business activities and risks are disclosed in the financial reports.
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Svabova, Lucia, Lucia Michalkova, Marek Durica, and Elvira Nica. "Business Failure Prediction for Slovak Small and Medium-Sized Companies." Sustainability 12, no. 11 (2020): 4572. http://dx.doi.org/10.3390/su12114572.
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Prediction of the financial difficulties of companies has been dealt with over the last years by scientists and economists worldwide. Several prediction models mostly focused on a particular sector of the national economy, have been created also in Slovakia. The main purpose of this paper is to create new prediction models for small and medium-sized companies in Slovakia, based on real data from the Amadeus database from the years 2016–2018. We created prediction models of financial difficulties of companies for 1 year in advance and also a model for 2 years prediction. These models are based on the combination of two methods, discriminant analysis and logistic regression that belong, among others, to the group of the most commonly used methods to derive prediction models of financial difficulties of the companies. The overall prediction powers of the combined model are 90.6%, 93.8% and 90.4%. The results of this analysis can be used for early prediction of the financial difficulties of the company, that could be very useful for all the stakeholders.
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Tjiptono, Fandy. "KEWIRAUSAHAAN, KINERJA KEUANGAN, DAN KELANGGENGAN BISNIS." Jurnal Manajemen Indonesia 15, no. 1 (2017): 17. http://dx.doi.org/10.25124/jmi.v15i1.389.
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Predicting business longevity using financial performance is one of the interesting topics in accounting and financial management studies. Incorrect prediction of a distressed firm may cause losses to investors, management, creditors and bankers, and inaccurate prediction of a non-distressed company may result in the loss of opportunities. This paper aims to review previous studies using financial performance as the predictor of business longevity in a number of countries. The sources of data include published articles in top international journals. The results indicate that the most dominant approach was bankruptcy prediction models using single and multiple financial ratios. The current paper also identified three main problems in using financial performance as the predictor of business longevity: inconsistent definitions of 'business failure', inconsistent predictive power of financial ratios, and an emphasis on financial symptoms rather than on the more fundamental causes of failure. Managerial implications and research agenda were formulated at the end of this paper
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McKinnon, Brian J., and Kenneth W. Brace. "The MD, MBA: Key to Cochlear Implant Program Survival?" Otolaryngology–Head and Neck Surgery 139, no. 2_suppl (2008): P110. http://dx.doi.org/10.1016/j.otohns.2008.05.550.
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Problem Despite the well established clinical efficacy of cochlear implantation in children and adults, many cochlear implant programs face daunting financial challenges. This presentation reports how the application of business principles achieved a successful financial resurrection of a cochlear implant closed due to excessive financial losses. Methods Using currently accepted business practices of financial analysis, supply chain and cost management, and market assessment, the economic data leading up to the program's financial failure were methodically assessed. Financial assessment of a cochlear implant program performed by an implant surgeon formally trained in business methodology. Results Identified during the financial exam were poor cost controls, little standardization of financial reporting, little understanding of actual and potential sources of revenue and cost, and a failure of the all parties to establish a suitable business model that would allow for the formal and accurate assessment of the program. Improved financial performance based on appropriate supply chain management, revenue enhancement, and accurate program financial reporting allowed for the cochlear implant program to reduce costs, increase revenue, and ultimately become financially viable. Conclusion Not understanding the business management of the cochlear implant program had a profoundly detrimental effect on the program's survival, despite the clinical success. Physicians must develop a business acumen that matches their clinical acumen, and use those tools to ensure that clinical success is not threatened by economic failure. Significance Understanding of the financial aspects of a cochlear implant program is as important as understanding the clinical aspects of cochlear implantation, and emphasis should be placed on developing those skills in the process of developing and managing cochlear implant programs.
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GÜROL, Burcu, and Gerçek ÖZPARLAK. "FİNANSAL BAŞARISIZLIK İLE PERFORMANS İLİŞKİSİ: BORSA İSTANBUL ŞİRKETLERİ ÜZERİNE BİR ARAŞTIRMA." SOCIAL SCIENCE DEVELOPMENT JOURNAL 7, no. 33 (2022): 244–56. http://dx.doi.org/10.31567/ssd.716.
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Financial failure refers to the situation in which the company changes or terminates its activities due to the inability to fulfil its financial obligations. Many studies have been carried out in order to predict this undesirable situation. Various models have been created in accounting-based studies using financial ratios. The most widely used of these models are Altman (1968), Springate (1978), Ohlson (1980), Fulmer (1984), Zmijewski (1984) and Grover (2001). The results obtained by using these models are followed by many stakeholders and accepted as the risk indicator of the enterprise. In this study, the relationship between the financial failure scores of 39 companies traded in the industrial sector in Borsa Istanbul between 2017 and 2021 and their market performance is analyzed separately. As a result of the study, it is seen that there is a positive and significant relationship between the Z-score value of the Altman (1968) model, which is an accounting-based financial failure model, and the Market Value/Book Value (M/B) ratio, which is a market-based performance indicator. These results show that investors invest more in companies with a low risk of financial failure since an increase in the Z-score means a decrease in the probability of financial failure of the business. However, in the research, no significant relationship is found between the scores of other financial failure models and the market-based indicator M/B. Keywords: Financial Failure Forecast Models, Financial Performance, Financial Failure, Borsa İstanbul, Bankruptcies
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Durica, Marek, Jaroslav Frnda, and Lucia Svabova. "Decision tree based model of business failure prediction for Polish companies." Oeconomia Copernicana 10, no. 3 (2019): 453–69. http://dx.doi.org/10.24136/oc.2019.022.
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Research background: The issue of predicting the financial situation of companies is a relatively young field of economic research. Its origin dates back to the 30's of the 20th century, but constant research in this area proves the currentness of this topic even today. The issue of predicting the financial situation of a company is up to date not only for the company itself, but also for all stakeholders.
 Purpose of the article: The main purpose of this study is to create new prediction models by using the method of decision trees, in achieving sufficient prediction power of the generated model with a large database of real data on Polish companies obtained from the Amadeus database.
 Methods: As a result of the development of artificial intelligence, new methods for predicting financial failure of the company have been introduced into financial prediction analysis. One of the most widely used data mining techniques in this field is the method of decision trees. In the paper, we applied the CART and CHAID approach to create a model of predicting the financial difficulties of Polish companies.
 Findings & Value added: For the creation of the prediction model, a total of 37 financial and economic indicators of Polish companies were used. The resulting decision trees based prediction models for Polish companies reach a prediction power of more than 98%. The success of the classification for non-prosperous companies is more than 83%. The created decision tree-based prediction models are useful mainly for predicting the financial difficulties of Polish companies, but can also be used for companies in another country.
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Renli, Aeron, and Andi Wijaya. "WHAT STOPS YOU FROM STARTING YOUR OWN BUSINESS? A STUDY CONDUCTED ON STUDENTS OF THE ECONOMY AND BUSINESS FACULTY AT UNIVERSITAS TARUMANAGARA." International Journal of Application on Economics and Business 1, no. 4 (2023): 2736–53. http://dx.doi.org/10.24912/ijaeb.v1i4.2736-2753.
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The purpose of this research is to find the effect of perceived loss of financial resources, perceived loss of customer demand, and perceived loss of social support on fear of failure and negative emotion and the influence of fear of failure and negative emotion on entrepreneurial behavior tendency. This research uses non-probability sampling with purposive samples method to obtain 75 students of Faculty of Economics and Business in Universitas Tarumanagara as respondents in this research. The data is collected online through Google Forms. Data collected is processed with partial least square structural equation modeling (PLS-SEM) using SmartPLS 4 software. This research shows that perceived loss of financial resources is positively and significantly influenced both fear of failure and negative emotion, perceived loss of customer demand is positively and insignificantly influenced both fear of failure and negative emotion, perceived loss of social support positively and significantly influenced fear of failure, perceived loss of social support positively and insignificantly influenced negative emotion, fear of failure positively and significantly influenced negative emotion, and both fear of failure and negative emotion are positively and insignificantly influenced entrepreneurial behavior tendency.
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Balasubramanian, Senthil Arasu, Radhakrishna G.S., Sridevi P., and Thamaraiselvan Natarajan. "Modeling corporate financial distress using financial and non-financial variables." International Journal of Law and Management 61, no. 3/4 (2019): 457–84. http://dx.doi.org/10.1108/ijlma-04-2018-0078.
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Purpose This paper aims to develop a corporate financial distress model for Indian listed companies using financial and non-financial parameters by using a conditional logit regression technique. Design/methodology/approach This study used a sample of 96 companies, of which 48 were declared sick between 2014 and 2016. The sample was divided into a training sample and a testing sample. The variables for the study included nine financial variables and four non-financial variables. The models were developed using financial variables alone as well as combining financial and non-financial variables. The performance of the test sample was measured with confusion matrix, sensitivity, specificity, precision, F-measure, Types 1 and 2 error. Findings The results show that models with financial variables had a prediction accuracy of 85.19 and 86.11 per cent, whereas models with a combination of financial and non-financial variables predict with comparatively better accuracy of 89.81 and 91.67 per cent. Net asset value, long-term debt–equity ratio, return on investment, retention ratio, age, promoters holdings pledged and institutional holdings are the critical financial and non-financial predictors of financial distress. Originality/value This study contributes to the financial distress prediction literature in different ways. First, there have been, until now, few studies in the area of financial distress prediction in the Indian context. Second, business failure studies in the past have used only financial variables. The authors have combined financial and non-financial variables in their model to increase predictive ability. Thirdly, in most earlier studies, variable institutional holdings were found to affect financial distress negatively. In contrast, the authors found this parameter to be positively significant to the financial distress of the company. Finally, there have hitherto been few studies that have used promoter holdings pledged (PHP) or pledge ratio. The authors found this variable to influence business failure positively.
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Pozuelo Campillo, José Ana, Julián Martínez Vargas, and Pedro Carmona Ibáñez. "Estudio de la insolvencia empresarial en las cooperativas mediante técnicas multivariantes." Studies of Applied Economics 30, no. 3 (2020): 1067. http://dx.doi.org/10.25115/eea.v30i3.3619.
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One of the consequences of the current economic crisis is a significant rise in business failures, which is fueling the interest of researchers and users for its analysis, review and update of the traditional models.In reviewing the financial literature on business failure in our country, we noticed that the are very few studies focusing exclusively on cooperative enterprises, although this kind of companies have a broad presence in our country. This significant lack of studies on this kind of business, the recent availability of large databases and the current economic circumstances have influenced us to undertake this work. The main paper objective focuses on the estimation of appropriate models to predict business failure in cooperative enterprises, using statistical techniques.
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Deo, Arpit, Manish Korde, Anant Tiwari, Anant Jain, and Akash Choudhary. "Enhancing Business Success Prediction: A Data-Driven Machine Learning Mode." EPJ Web of Conferences 328 (2025): 01022. https://doi.org/10.1051/epjconf/202532801022.
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Business failure yields considerable economic and social repercussions, affecting employees, investors, and communities. Conventendeavorslure prediction models predominantly depend on financial measurements, restricting their relevance across many businesses and overlooking essential non-financial elements. This study presents a machine learning model for predicting company failure, utilizing logistic regression, random forest, and neural networks. The model incorporates both financial and non-financial characteristics, solving research deficiencies concerning cooperative societies, governance, market rivalry, and external economic factors. Data preprocessing methods, including outlier detection, feature selection, and dimensionality reduction, improve model accuracy. The suggested methodology attains an accuracy over 94%, offering an early warning system for enterprises at risk of collapse. This study enhances financial risk evaluation by providing a flexible, sector-specific forecasting model. The methodology facilitates proactive decision-making, assisting organizations in risk mitigation, sustainability enhancement, and financial crisis prevention. Future endeavors involve augmenting datasets and investigating deep learning methodologies to improve predictive accuracy.
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Ihionu, Marcellinus, Iyke Maureen, and Alexander Aneke. "Causes of Failure Among Family Owned Businesses." International Journal of Economics, Finance and Management Sciences 12, no. 5 (2024): 276–83. http://dx.doi.org/10.11648/j.ijefm.20241205.15.
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The study investigated the causes of failure among family owned businesses in South-East, Nigeria. Specific objectives were to; evaluate major family business enterprises that have failed in South-eastern states, Nigeria; investigate the causes of failure of these family owned business enterprisesidentified in South-eastern states in Nigeria; explore strategies that will help prevent such failures in other family owned business enterprises in Nigeria. The study adopted a qualitative approach in analyzing the causes. Historical analysis of ten indigenous family owned business situated in South-eastern, Nigeria that have gone into extinction, were thoroughly carried out to identify factors that contributed to their extinction. It was found out that; death of founder(s), financial constraint, poor management, market complexity and competitions are the main contributors to family business failures and extinctions in Southeastern, Nigeria. Thus, it was recommended family business owners should be liberal, open-minded, flexible and inclusive in making business decisions that will propel their enterprises to greater height. More so, competent hands, professional business consultants and advisors should be incorporated in managing the business. This will ensure the success and fecundity of the business. Though, the study encountered a slight challenge as regards to the availability of resources, because relevant information that would have enriched the result, were not documented or uploaded on the internet. However, the findings of the study contributed immensely to the body knowledge of family successes, growths and failures in Nigeria.
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Downs, John, Richard J. Cebula, Doug Johansen, and Maggie Foley. "U.S. small bank failures and the Financial Crisis of 2007–2009." Banks and Bank Systems 17, no. 4 (2022): 50–60. http://dx.doi.org/10.21511/bbs.17(4).2022.05.
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This study utilizes logistic regression to identify annual financial statement and performance ratio factors that influenced the failure rate of U.S. small banks before and after the Financial Crisis identified during December 2007 through June, 2009. The study includes rates of small bank failure before and Financial Crisis spanning the years 2001 through 2014. The aim of the paper is to describe in large increase in U.S. small bank failure after the Financial Crisis. The Financial Crisis created drastic sustained changes of the financial system that were designed for large financial institutions. These changes may have created undue hardship for small banks and elevated the rate of small bank failures in the post-Financial Crisis period. Post-Financial Crisis bank failures had lower capital ratios and increased loan portfolio risk relative to the prior period. The combined effect of expansionist monetary policy, increased regulatory costs, and possession of illiquid real estate assets contributed to the higher rate of failure. The identification of factors that contribute to the increase in small bank failures after the Financial Crisis should assist bank managers, policy analysts, and scholars in developing alternative solutions for the future.
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Lisnurasiyah and Utami Wiwik. "Determinants of the Business Sustainability of MSMEs Businesses in West Jakarta." International Journal of Innovative Science and Research Technology 7, no. 6 (2022): 352–63. https://doi.org/10.5281/zenodo.6789567.
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The large contribution of MSMEs to the Indonesian economy, it was recorded that in 2019 MSMEs were able to contribute to Indonesia's GDP, which was around 60.3%. However, in reality, MSMEs often experience delays in their development and experience failure. This study aims to determine the effect of the quality of financial statements, business risk, and human resource competence on business sustainability. Researchers conducted a survey on 120 small and medium-sized businesses in West Jakarta as research samples. SEM PLS was used as an analytical tool in this study. The research data used came from questionnaires which were collected using a survey method. The results show that the quality of financial reports has a positive and significant effect on business sustainability, business risk has a negative and significant effect on business sustainability, and human resource competence has no positive and significant effect on business sustainability.
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Karpac, Dusan, and Viera Bartosova. "Prediction of Financial Health of Business Entities of Selected Sector Using Balance Analysis II. by Rudolf Doucha and Verification of Its Predictive Ability through ROC." SHS Web of Conferences 91 (2021): 01006. http://dx.doi.org/10.1051/shsconf/20219101006.
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Forecasting business failure is a worldwide known term, in a global notion, and there is a lot of prediction models constructed to compute financial health of a company and, by that, state whether a company inclines to financial boom or bankruptcy. A healthy financial management of a business entity is very important for the proper operation of the business, and it is therefore very important to know how to assess financial health and to anticipate possible problems that will be easier to eliminate in advance. Globalized prediction models compute financial health of companies, but the vast majority of models predicting business failure are constructed solely for the conditions of a particular country or even just for a specific sector of a national economy. Predictive models can indicate whether an entity tends to prosper or bankruptcy, and so we can assess the financial health of the business. This paper provides a description of the balance analysis II. by Rudolf Doucha, discusses its application to a sample of 266 Slovak subjects and points to its prediction in the given field. The verification of the ability to forecast bankruptcy or financial stability has been evaluated through ROC analysis.
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Kozarević, Emira, and Dženita Pirić. "Evaluation of the revised Z'-score model as a predictor of a company's financial failure." BH Ekonomski forum 16, no. 1 (2022): 11–29. http://dx.doi.org/10.5937/bhekofor2201011k.
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Under contemporary business conditions, there are numerous models used for the assessment of a company's financial situation and the prediction of the likelihood of its bankruptcy. These models have been mainly developed using the company's financial information. One of them is the Altman Z-score model. The model separates financially successful and stable companies from those having difficulties in business and headed for bankruptcy. This paper explains the importance of prudential information, basic financial statements and financial indicators and presents the research aimed at evaluating the applicability of the revised Altman Z'-score model in the Federation of Bosnia and Herzegovina (FBiH). Based on financial information, the paper analyzes the business activities of 50 large manufacturing companies in FBiH. The revised Z'-score model achieved a relatively good result in assessing the companies with business difficulties as it correctly classified 10 out of 20 companies; the other 10 companies were not incorrectly classified into the companies with the stable business but they were placed in the grey zone. The model proved completely reliable in the classification of all 30 companies with stable businesses. The research results indicate that the revised Altman Z'-score may be used as the predictor of the financial failure of manufacturing companies in FBiH. This model is definitely the tool that may assist while making business decisions. However, due to the specific business environment in FBiH, the model is recommended to be used as an additional rather than the basic indicator for predicting financial failure.
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Sugiyanto, FX, Prasetiono Prasetiono, and Teddy Hariyanto. "MANFAAT INDIKATOR-INDIKATOR KEUANGAN DALAM PEMBENTUKAN MODEL PREDIKSI KONDISI KESEHATAN PERBANKAN." JURNAL BISNIS STRATEGI 18, no. 1 (2017): 11–26. http://dx.doi.org/10.14710/jbs.10.7.11-26.
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Financial distress prediction is an essential issue in finance. Especially in emerging economies, predicting the future financial situation of individual corporate entities is even more significant, bearing in mind the general economic turnrr.oil that can be caused by business failures. Following this discrimination approach this study explores the usefulness of financial ratios in constructing the discrimination models as an early waring system. Theratios used in the models were compiled from financial report: of 11 oIndonesian banks that listed in Indonesian Banking Directory. The result ofthis investigation show that financial ratios ara significant within 5% for one year before failure and 10% for two years before failure as bankruptcy prediction variable of a bank. Those ratios also explain that asset quality, management earning power and liquidity are the determines of the Indonesian banks banckruptcy.
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Romero Martínez, Mariano, Pedro Carmona Ibáñez, and Julián Martínez Vargas. "Predicting Business Failure with the XGBoost Algorithm: The Role of Environmental Risk." Sustainability 17, no. 11 (2025): 4948. https://doi.org/10.3390/su17114948.
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This study addresses the increasing emphasis on sustainability and the importance of understanding how environmental risk influences business failure, a factor unexplored in traditional financial prediction models. Environmental risk, or environmental financial exposure, refers to the potential percentage of a company’s revenue at risk due to the environmental damage it causes. Previous research has not sufficiently integrated environmental variables into failure prediction models. This study aims to determine whether environmental risk significantly predicts business failure and how it interacts with conventional financial indicators. Utilizing data from 971 Spanish cooperative companies in 2022, including financial ratios, the VADIS bankruptcy propensity indicator, and the TRUCAM environmental risk score, the study employs the Extreme Gradient Boosting (XGBoost) machine learning algorithm, chosen for its robustness in handling multicollinearity and nonlinear relationships. The methodology involves training and validation samples, cross-validation for hyperparameter tuning, and interpretability techniques such as variable importance analysis and partial dependence plots. Results demonstrate that the variable related to environmental risk (TRUCAM) ranks among the top predictors, alongside liquidity, profitability, and labor costs, with higher TRUCAM values correlating positively with failure risk, underscoring the importance of sustainable cost management. These findings suggest that firms facing substantial environmental risk are more prone to financial distress. By incorporating this environmental variable into a machine learning framework, this work contributes to the interaction between sustainability practices and corporate viability.
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Polsiri, Piruna. "Concentrated ownership and prediction of financial institution failures." Corporate Ownership and Control 8, no. 4 (2011): 84–95. http://dx.doi.org/10.22495/cocv8i4p5.
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In an emerging economy where ownership concentration is common and legal protection of outside investors is weak, financial and economic factors that are widely documented might not have been sufficient in constructing sound models to predict financial institution failures. Using the data of financial institutions listed in the Thai stock exchange during the 1997 East Asian financial crisis, this study showed that to develop sound prediction models that are robust across time to failure models, ownership variables should be incorporated in the models. Specifically, in the logit models that include both financial and ownership variables, 85.45%, 85.41%, and 91.49% of financial institutions were correctly classified in the models using the data of one, two, and three years prior to failure, respectively. It was also find that the presence of family as the largest shareholder increases the probability that a financial institution was closed. This evidence supports the expropriation effects of controlling families. Finally, the results suggested evidence of a “too-big-to-fail” policy in the closure procedures of Thai financial institutions during the East Asian financial crisis.
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Arshad, Roshayani, Sharinah Mohamed Iqbal, and Normah Omar. "Prediction of Business Failure and Fraudulent Financial Reporting: Evidence from Malaysia." Indian Journal of Corporate Governance 8, no. 1 (2015): 34–53. http://dx.doi.org/10.1177/0974686215574424.
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Liou, Fen‐May. "Fraudulent financial reporting detection and business failure prediction models: a comparison." Managerial Auditing Journal 23, no. 7 (2008): 650–62. http://dx.doi.org/10.1108/02686900810890625.
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Mures‐Quintana, Maria‐Jesús, and Ana García‐Gallego. "On the non‐financial information's significance in the business failure models." International Journal of Organizational Analysis 20, no. 4 (2012): 423–34. http://dx.doi.org/10.1108/19348831211268616.
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Xu, Wei, Zhi Xiao, Xin Dang, Daoli Yang, and Xianglei Yang. "Financial ratio selection for business failure prediction using soft set theory." Knowledge-Based Systems 63 (June 2014): 59–67. http://dx.doi.org/10.1016/j.knosys.2014.03.007.
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Shepherd, Dean A., Johan Wiklund, and J. Michael Haynie. "Moving forward: Balancing the financial and emotional costs of business failure." Journal of Business Venturing 24, no. 2 (2009): 134–48. http://dx.doi.org/10.1016/j.jbusvent.2007.10.002.
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Sinaga, Devi. "Analysis of Factor That Affect The Closure of JD.ID Ecommerce Platform." Inovbiz: Jurnal Inovasi Bisnis Seri Manajemen, Investasi dan Kewirausahaan 4, no. 1 (2024): 39–46. http://dx.doi.org/10.35314/inovbizmik.v4i1.4064.
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There is a steady increase in platform start-ups. Despite this, many newly established companies fail within the first five years, with the majority going out of business in a shorter period of time. The cause of this kind of failure still needs to be investigated methodically. This study attempts to investigate the causes behind the failure of  JD.ID e-commerce platform to close its market in Indonesia, despite the fact that there are many independent investigations that have offered various explanations regarding the definition of failure in jd.id general. The theoretical framework will identify the factors that affect products, finances, and markets in organizations that make start-up platforms jd.id fail. An extensive review of library research was conducted to uncover and examine the failures of the jd.id platform. His research uses websites to collect research data. The results of this study reveal that what makes the jd.id platform fail and close its market in Indonesia are product factors, market factors, and financial factors. and the jd.id business failure category falls into the inadequate earnings category.Keywords : E-Commerce, Business Failure, Factors Business Failure
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Situm, Mario. "Inability of Gearing-Ratio as Predictor for Early Warning Systems." Business Systems Research Journal 5, no. 2 (2014): 23–45. http://dx.doi.org/10.2478/bsrj-2014-0008.
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AbstractBackground: Research in business failure and insolvency prediction provides numerous potential variables, which are in the position to differentiate between solvent and insolvent firms. Nevertheless, not all of them have the same discriminatory power, and therefore their general applicability as crisis indicators within early warning systems seems questionable. Objectives: The paper aims to demonstrate that gearing-ratio is not an appropriate predictor for firm failures/bankruptcies. Methods/Approach: The first and the second order derivatives for the gearing-ratio formula were computed and mathematically analysed. Based on these results an interpretation was given and the suitability of gearing-ratio as a discriminator within business failure prediction models was discussed. These theoretical findings were then empirically tested using financial figures from financial statements of Austrian companies for the observation period between 2008 and 2010. Results: The theoretical assumptions showed that gearing-ratio is not a suitable predictor for early warning systems. This finding was confirmed with empirical data. Conclusions: The inclusion of gearing-ratio within business failure prediction models is not able to provide early warning signals and should therefore be ignored in future model building attempts.