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The Influence of IT Investment on Business Performance: A Comparative Study of Regression Analysis and Artificial Neural Networks

Shin-Yuan Hung, Ya-Han Hu, Chin-Shyh Chin-Shyh Ou, Kuanchin Chen, Chun-Chuan Lu
2013 Pacific Asia Journal of the Association for Information Systems  
of IT investment on business performance, artificial neural networks are superior to regression analysis for their explanatory power.  ...  To address the aforementioned symptoms, this study developed a system to examine the influence of IT investment on two categories of performance indicators, namely cost efficiency and profit effectiveness  ...  More specifically multiple regression analysis and artificial neural networks (ANN) are used for their popularity in modeling financial performance.  ... 
doi:10.17705/1pais.05402 fatcat:pufj7h5ckfdptezfjaatne55nq

COMPOSITE FINANCIAL PERFORMANCE INDEX PREDICTION – A NEURAL NETWORKS APPROACH

Diana Claudia Sabău Popa, Dorina Nicoleta Popa, Victoria Bogdan, Ramona Simut
2021 Journal of Business Economics and Management  
In a competitive environment, the performance measurement model allows performing comparative analysis in the same industry and between industries.  ...  This paper aims to design a composite financial index to determine the financial performance of listed companies, further used in predicting business performance through neural networks.  ...  Author contributions VB, DNP and RS conceived the study, DNP collected the data, VB and RS designed the research methodology and developed the first analysis of the data.  ... 
doi:10.3846/jbem.2021.14000 fatcat:guqknpnelfehxo4i3doj3boh3q

Predicting the Performance and Survival of Islamic Banks in Malaysia to Achieve Growth Sustainability

Noraina Mazuin Sapuan, Suzaida Bakar, Hamidah Ramlan, M.Y. Jaaffar, A. Abdullah Sani, A. Muhammad
2017 SHS Web of Conferences  
By employing multi -layer perceptron neural network and pooled regression, we found that total assets/ size of the Islamic banks (GROWTH) have high weightage and significantly influence in predicting the  ...  performance and the survival of Islamic banks in Malaysia.  ...  ACKNOWLEDGEMENTS A special thanks to Universiti Tenaga Nasional as for being our sponsor for this Internal Grant Scheme and this is a part of the findings from this research grant.  ... 
doi:10.1051/shsconf/20173600016 fatcat:ddqublstl5gr3gqzmnslqulzjm

Hybrid Corporate Performance Prediction Model Considering Technical Capability

Joonhyuck Lee, Gabjo Kim, Sangsung Park, Dongsik Jang
2016 Sustainability  
We propose a quantitative corporate performance prediction model that applies the support vector regression (SVR) algorithm to solve the problem of the overfitting of training data and can be applied to  ...  Many studies have tried to predict corporate performance and stock prices to enhance investment profitability using qualitative approaches such as the Delphi method.  ...  and performed the entire research steps.  ... 
doi:10.3390/su8070640 fatcat:45gnszqovffbpj3rf3236xg5ia

Research on Performance Prediction of Technological Innovation Enterprises Based on Deep Learning

Huan Liu, Yuanpeng Zhang
2021 Wireless Communications and Mobile Computing  
neural network model for performance prediction of scientific and technological innovation enterprises.  ...  This article uses the Naive Bayes model, logistic regression model, support vector regression model, and other mainstream methods to predict and compare the performance of technological innovation enterprises  ...  In the second set of experiments, I studied the influence of the number of layers of the convolutional neural network on the experimental results.  ... 
doi:10.1155/2021/1682163 fatcat:bxkk5i46svfkjaqctvvfg3mksa

Key Technical Performance Indicators for Power Plants [chapter]

Simona Vasilica Oprea, Adela Bâra
2017 Recent Improvements of Power Plants Management and Technology  
The BI solution contains a data level for data management, an analytical model with KPI framework and forecasting methods based on artificial neural networks (ANN) for estimating the generated energy from  ...  We will also present a case study of a business intelligence (BI) dashboard developed for renewable power plant operation in order to analyze the KPIs.  ...  Acknowledgements This paper presents some results of the research project: Intelligent system for predicting, analyzing and monitoring performance indicators and business processes in the field of renewable  ... 
doi:10.5772/67858 fatcat:mfjp6immg5hv7lyhvej7o7nzxe

Economic and Financial Performance of the Brazilian Pulp and Paper Industry

Daiane Rodrigues dos Santos, Pedro de Moraes Rocha, Vitória Gomes da Costa, Yasmin Leão Sodré Soares
2019 International Journal of Advanced Engineering Research and Science  
The objective of this paper is to determine the influence of GDP (Gross Domestic Product), Exchange Rate, SELIC Rate (Brazil's interest base rate) and in flation rate on the performance of four publicly  ...  For this analysis, two models were applied to the database, one using only the past data of the indicators themselves and another using past both data and macroeconomic variables.  ...  As for the main objective of this article, it was verified that the 16 indexes of economic-financial performance analyzed by the neural networks performed better when it was also used GDP, SELIC Rate,  ... 
doi:10.22161/ijaers.6770 fatcat:pqgykwzkzfg33csrhr3fumex2m

Performance Prediction of Listed Companies in Smart Healthcare Industry: Based on Machine Learning Algorithms

Baobao Dong, Xiangming Wang, Qi Cao, Weiwei Cai
2022 Journal of Healthcare Engineering  
In this study, machine learning algorithm is used to predict performance, which can not only deal with a large amount of data and characteristic variables but also analyse different types of variables  ...  and predict their classification, increasing the stability and accuracy of the model and helping to solve the problem of poor performance prediction in the past.  ...  Acknowledgments is paper was financially supported by the Soft Science Project of Science and Technology Department of Jilin Province entitled "Research on the Factors and PATH of Ambidexterous Innovation  ... 
doi:10.1155/2022/8091383 pmid:35035859 pmcid:PMC8759903 fatcat:rhvf6xydhvek5p7axyjxvwau24

Deep Learning-Based Corporate Performance Prediction Model Considering Technical Capability

Joonhyuck Lee, Dongsik Jang, Sangsung Park
2017 Sustainability  
Many studies have predicted the future performance of companies for the purpose of making investment decisions.  ...  In this study, we propose a deep neural network-based corporate performance prediction model that uses a company's financial and patent indicators as predictors.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/su9060899 fatcat:vop3n73zejabjmvijzxfvwn3gu

Assessing Bank Performance with Operational Research and Artificial Intelligence Techniques: A Survey

Meryem Duygun Fethi, Fotios Pasiouras
2009 Social Science Research Network  
This paper presents a comprehensive review of 179 studies which employ operational research (O.R.) and Artificial Intelligence (A.I.) techniques in the assessment of bank performance.  ...  Then we discuss applications of other techniques such as neural networks, support vector machines, and multicriteria decision aid that have also been used in recent years, in bank failure prediction studies  ...  We use a combination of various keywords such as "bank efficiency", "bank and data envelopment analysis", "bank performance", "bank and neural networks", "bank and artificial intelligence", "bank and operational  ... 
doi:10.2139/ssrn.1350544 fatcat:u7ryevbq2za6bbsyed3t3hmaeu

Application of Data Mining Technique in the Performance Analysis of Shipping and Freight Enterprise and the Construction of Stock Forecast Model

ChangShu Tu, ChingTer Chang, KeeKuo Chen, HuaAn Lu
2011 Journal of Convergence Information Technology  
From the analysis result, it can be seen that after the signing of ECFA, the business operation performance of shipping and freight enterprises is significantly enhanced, and the forecast capability of  ...  of ECFA; later on, decision tree analysis is used to investigate the major causes affecting the business operation performance; finally in this study, shipping enterprises with the best performances are  ...  Since general regression neural network is enlightened from probabilistic model, it is not needed to assume a clear functional format first as the traditional regression analysis, and it only needs to  ... 
doi:10.4156/jcit.vol6.issue3.3 fatcat:4oawqa2terhxdb3cpvk3jgfovm

STUDENTS' ACADEMIC PERFORMANCE AND DROPOUT PREDICTION

Ahmed O. Ameen, Moshood Alabi Alarape, Kayode S. Adewole
2019 MALAYSIAN JOURNAL OF COMPUTING  
It allows the instructors and other education managers to get an accurate evaluation of the students in different courses in a particular semester and also serve as an indicator to the students to review  ...  This paper presents a comprehensive review of related studies that deal with SAP and dropout predictions.  ...  These techniques include Statistics, Business Intelligence, Web Analytics, Operational Research, Artificial Intelligence, Social Network Analysis, and Information Visualization.  ... 
doi:10.24191/mjoc.v4i2.6701 fatcat:a6wjepeczjehlhibj3bbxy2qly

Financial Performance Analysis in European Football Clubs

David Alaminos, Ignacio Esteban, Manuel A. Fernández-Gámez
2020 Entropy  
Through these factors, the present study analyzes the financial performance of European football clubs using neural networks as a methodology, where the popular multilayer perceptron and the novel quantum  ...  neural network are applied.  ...  [8] proposed a two-stage method to conduct a multicriteria analysis to rank clubs on their financial and business performance dimensions.  ... 
doi:10.3390/e22091056 pmid:33286825 fatcat:2oinwfzzg5cq5bncihbxvpmwb4

Energy Performance Modelling and Consumption Forecasting in Built Environments

2020 International journal of recent technology and engineering  
The building sector accounts for a staggering 30% of the world's energy use and one-third of associated greenhouse gas (GHG) emissions worldwide.  ...  A critical assessment of various models is also provided based on their composition, input-output relationships, strengths, and weaknesses to define study gaps and provide directions for future studies  ...  Nowadays, models based on artificial intelligence such as neural network and support vector machines are extensively used because of their high performance, accurate nonlinear mappings, and their capability  ... 
doi:10.35940/ijrte.f8350.079220 fatcat:c5c3kx2jnnbj3a5663wvi5456a

What Causes Non-Performing Loans? The Case of Greece Using Primary Accounting Data

Vasilios Giannopoulos
2018 Open Journal of Accounting  
In this paper we study the effect of independent variables in identifying non-performing loans during crisis period, using a binomial logistic regression.  ...  We use a unique data of 2591 loans granted by one of the four systemic banks of Greece in 2005.  ...  Among these the neural networks are very promising (Goonatilake & Treleaven, 1995 [33] ) and the alternative to the linear discriminant analysis and logistic regression analysis, due to the possible complex  ... 
doi:10.4236/ojacct.2018.74013 fatcat:2f5kbbxyv5evvpm3jzgbz3o7ea
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