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Forecasting in Business
2009
Journal of Electrical and Electronics Engineering
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We are told only that there are severalforecasting methods and that forecasting is a tool ofstrategic management. ...
After addressing several claimsabout forecasting made in management literature, thispaper presents several forecasting methods used inoperational management. ...
likelihood events that will adversely affect a business. • Attrition models gauge the probability of a customer taking his or her business elsewhere. • Lifetime value models evaluate the overall profitability ...
doaj:84cb288977c9451cba5f6a499a7d90db
fatcat:m6cjxtkjlzaa7etb34ychpe67a
A "User Friendly" Bankruptcy Prediction Model Using Neural Networks
2014
Accounting and Finance Research
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The aim of this paper is to develop a model that predicts bankruptcy using three financial ratios that are simple and easily available, even for small businesses. ...
We used a sample of 3,728 Belgian Small and Medium Enterprises (SME's) including 1,864 businesses having been declared bankrupt between 2002 and 2012 and conducted a neural network analysis. ...
A neural network is then built to determine the probability that bankruptcy occurs for a business. ...
doi:10.5430/afr.v3n2p124
fatcat:6ca4frpxeffwzfat3yqb6jck6q
Analyzing the impact of maintenance on profitability using dynamic bayesian networks
2020
Procedia CIRP
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Abstract In the era of Industry 4.0, predictive maintenance is regarded as a key factor for reaching business objectives. ...
Abstract In the era of Industry 4.0, predictive maintenance is regarded as a key factor for reaching business objectives. ...
Case 1 -Bayesian Network for IMP Case 3 deals with the effect of the occurrence of a failure on availability and profit. ...
doi:10.1016/j.procir.2020.05.008
fatcat:ddkt75e6rva4de4jc7kcckixzu
The improved business valuation model for RFID company based on the community mining method
2017
PLoS ONE
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Although the huge number of papers have addressed the topic of business valuation models based on statistical methods or neural network methods, only a few are dedicated to constructing a general framework ...
for business valuation that improves the performance with network graph (NG) and the corresponding community mining (CM) method. ...
Acknowledgments We thank Yueming Li for her help in collecting the data. ...
doi:10.1371/journal.pone.0175872
pmid:28459815
pmcid:PMC5411069
fatcat:wihqmixvurandoeqk5hdf24x24
Machine Learning Methods of Bankruptcy Prediction Using Accounting Ratios
2018
Open Journal of Business and Management
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The aim of bankruptcy prediction is to help the enterprise stakeholders to get the comprehensive information of the enterprise. ...
The final result can prove the effectiveness of the machine learning method. Thirdly, the accuracy of our experiment is higher than existing studies with 95.9%. ...
Therefore, the probability of accurate prediction is 70.8%. This probability is consistent with the exact probability of the most financial model predictions. ...
doi:10.4236/ojbm.2018.61001
fatcat:ufpdvcrvizcupl4yagmqx7wema
Business Model Risk Analysis: Predicting the Probability of Business Network Profitability
[chapter]
2013
Lecture Notes in Business Information Processing
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In the design phase of business collaboration, it is desirable to be able to predict the profitability of the business-to-be. ...
The paper introduces the prediction and modeling approach, and a supporting software tool. The use of the approach is illustrated by means of a case. ...
To the best of our knowledge, this is the first time a formal business model-based profitability risk analysis method is proposed for business models. ...
doi:10.1007/978-3-642-36796-0_11
fatcat:vq7jkwdknzdhzdlapunphtohpq
Using Bayesian Networks for Bankruptcy Prediction: Empirical Evidence from Iranian Companies
2009
2009 International Conference on Information Management and Engineering
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The aim of this study is model development for financial distress prediction of listed companies in Tehran stocks exchange (TSE) using Bayesian networks (BNs). ...
In order to develop a bankruptcy prediction model, we consider 20 predictor variables including liquidity ratios, leverage ratios, profitability ratios and other factors like firm's size and auditor's ...
UNDERLYING CONCEPTS AND THEORY Bayesian networks are based upon probability theory and the basic measure of our belief in a proposition (say A) will be the function P (A). ...
doi:10.1109/icime.2009.91
fatcat:uj5qvqcowfbgzfjwestx2kma6i
Corporate Bankruptcy Prediction Using the Principal Components Method
2019
Korporativnye Finansy
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This research raises the problem of predicting the probability of bankruptcy using the method of neural network modeling. ...
A huge number of articles and papers devoted to the study of bankruptcy prediction problems. ...
Aggregation of indicators for prediction of bankruptcy probability of Russian small, medium and large companies using the principal components method has a better effect from the point of view of predictive ...
doi:10.17323/j.jcfr.2073-0438.13.4.2019.20-38
fatcat:w4s2lj4vvvfjba4lvr3urnxzle
A research on the comparison of classification algorithm in finance
2019
Contaduría y Administración
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As a result of the study conducted on stock marketing, the classification of enterprises of decision tree models with artificial neural networks has also been found to be more successful than other methods ...
With developments in the Internet and technology, it makes a warehouse that changes the data more rapidly and in volume. This situation increases the importance of data mining every day. ...
An investor or business owner is advised to choose these two methods when they want to predict whether a business is profitable or not. ...
doi:10.22201/fca.24488410e.2020.2497
fatcat:tcfklxp5ljeu7ek5uflp5oal3q
A Neural Network Approach to Financial Forecasting
2016
International Journal of Computer Applications
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This calls for a system that could simulate and predict financial positions based on financial market trends in order to manage and identify the best package to invest in. ...
The paper is aimed at developing a neural network application to predict interest rate on loan investment in Nigerian bank using the back propagation neural network.It forecastinterest rate on loan investment ...
The Business of lending is gradually becoming a major target for many banks; as a result there is high competition among the financial institutions. ...
doi:10.5120/ijca2016908463
fatcat:rmrqpkpypvhzjoixxauc45tsfa
Application of neural networks in CRM systems
2017
ITM Web of Conferences
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The paper presents several business applications of neural networks in software systems designed to aid CRM, e.g. in deciding on the profitability of building a relationship with a given customer. ...
It is the sheer amount of gathered data as well as the need for constant updating and analysis of this breadth of information that may imply the suitability of neural networks for the application in question ...
Algorithms for calculating the probability of such occurrences have been quite well developed, and are therefore capable of predicting whether and when the customer will leave the company. ...
doi:10.1051/itmconf/20171504001
fatcat:5imqn46dfracjnog772txz74cq
Estimation of Possible Profit/ Loss of a New Movie Using "Natural Grouping" of Movie Genres
2013
International Journal of Information Engineering and Electronic Business
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Thus if the production houses have an option to know the probable profit/loss of a completed movie to be released then it will be very helpful for them to reduce the said risk. ...
Film industry is the most important component of entertain ment industry. A large amount of money is invested in this high risk industry. Both profit and loss are very high fo r this business. ...
In this paper we have proposed a training method to train backpropagation neural network for p rediction of possible business of a movie [36] . ...
doi:10.5815/ijieeb.2013.04.04
fatcat:or25e7lghbejlpvy66jllad2vi
Financial Crisis Warning for Listed Manufacturing Companies in China
2022
Computational Intelligence and Neuroscience
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The study is of significance for guiding the research of related issues in the manufacturing sector and can also provide reference for the early warning of other industries. ...
In addition, through our study on the dynamic early warning of BP neural network, we intend to convey the concept of constantly updating the model to both managers and stakeholders. ...
Acknowledgments is study was supported, in part, by the funds for "Undergraduate Teaching Reform and Innovation Project" of Beijing Higher Education in 2020 and "Undergraduate Teaching Reform and Research ...
doi:10.1155/2022/1439057
pmid:35498193
pmcid:PMC9054417
fatcat:qlgzc5twr5dgtfpnl3rhsq6xfa
The Risk Management of Commercial Banks——Credit-Risk Assessment of Enterprises
2016
International Journal of Economics and Finance
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a good prediction. ...
In this paper, we apply our risk assessment model, which is established on the basis of GRNN neural network model, to make an empirical analysis with the selected sample data. ...
GRNN neural network is excellent when applied as a modeling method. ...
doi:10.5539/ijef.v8n9p69
fatcat:55euwumpxzaebfs5snfsicryuu
Logit business failure prediction in V4 countries
2019
Engineering Management in Production and Services
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The main result is a model for business failure prediction of companies operating under the economic conditions of V4 countries. ...
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. ...
There is a potential of this model to become a commonly used tool for the prediction of the business failure of companies. The model presented in the paper has a high predictive ability. ...
doi:10.2478/emj-2019-0033
fatcat:deabyt34pnazno7f2ogkioy544
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