Using Glow-worm algorithm to predict companies’ financial distress by Ali Mayeli, Erfan Mehregan, Mohsen Manna

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Empirical study on the usage of cash flow statement as a tool to predict company financial distress / Shariful Amran Abd Rahman by Abd Rahman, Shariful Amran

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Determining the Tiers of a Supply Chain Using Machine Learning Algorithms by Kyoung Jong Park

“…The experimental results showed that LR and MLP accurately predicted companies (tiers), but NB, DT, RF, SVM, and K-NN did not accurately predict companies. …”
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R&D Product Development KPIs and Performance of Companies in Serbia by Jelena Tadić, Ivana Medved, Ranko Bojanić, Nemanja Tasić

“…The main intent of the article is to explore whether assumed research and development (R&D) product development key performance indicators (KPIs) are in relationship with a company’s performance, as well as to determine the impact of R&D product development KPIs to predicting company performance. The presented research was carried out on a sample of 196 manufacturing food companies in the Republic of Serbia. …”
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Annual report readability and firms’ investment decisions by Nam Huong Dau, Duy Van Nguyen, Hai Thi Thanh Diem

“…As such, reports’ readability can serve as a signal significant to predict companies’ future investments. Our findings are consistent with signaling theory and contribute significantly to the literature for empirical investigations on the relationship of annual reports’ readability and firms’ investment decisions.…”
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The Effect of Audit Report Type and Audit Report Paragraphs on Financial Distress among Firms Listed on the Tehran Stock Exchange by Javad Forouzandeh, Naser Izadinia, Saeed Daei-Karimzadeh

“…Considerable researches have been devoted to predicting financial distress by using financial ratios and there is a little knowledge about this issue and how report paragraphs and information may contribute to predict companies’ insolvency. The major purpose of this study is to explore the effects of audit report types, pre-opinion paragraphs, special emphasis paragraphs, and other explanatory paragraphs on financial distress among firms listed on the Tehran Stock Exchange. …”
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Predicting the Financial Status of Companies Using Content Analysis the Reports of the Board of Directors by Jamal Barzegari Khanagha, habib ansari samani, lida razzazzadeh

“…In this regard, This research is intended by examining the relationship between financial ratios and the content of the board's reports open a new way to predict company status. For this purpose, were extracted frequency of words and phrases with positive and negative semantic load using the word extraction algorithm, From the text of the board's reports 219 non helpless companies and 81 helpless companies. …”
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Ability of combinations of cash flow components to predict financial distress by Gholamreza Kordestani, Mehrdad Bakhtiari, Vahid Biglari

“…The aim of this research is to provide a model that predicts company’s financial distress on the basis of the operational, investment and financing components of its cash flow statement. …”
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Determining financial indicators with rough sets based feature selection techniques – a review by Zaini, Bahtiar Jamili, Shamsuddin, Siti Mariyam, Jaaman, Saiful Hafizah

“…Therefore, this study will investigate and identify financial indicators that will give the most significance impact in predicting company's performance. A hybrid of soft computing and hard computing techniques, i.e., rough set method and statistical approach will be explored for pre-analysis and post-analysis in identifying the most significant indicators for the classification of the company's performance. …”

Determining financial indicators with rough sets based feature selection techniques – A review by Zaini, Bahtiar Jamili, Shamsuddin, Siti Mariyam, Jaaman, Saiful Hafizah

“…The firm’s performance can be analyzed based on financial indicators as reported in company’s annual report, balance sheet, and income statement.As a result, many financial indicators or ratios need to be considered for classifying the performance of each firm.Therefore, this study will investigate and identify financial indicators that will give the most significance impact in predicting company’s performance.A hybrid of soft computing and hard computing techniques, i.e., rough set method and statistical approach will be explored for pre-analysis and post-analysis in identifying the most significant indicators for the classification of the company’s performance.This study will also investigate the impact of employing difference indicators in predicting high performance and failure of the firms.…”
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Design and Implement Machine Learning Tool for Cyber Security Risk Assessment by Omar I. Sheet, Laheeb M. Ibrahim

“…This study presents a risk assessment method based on Machine Learning, an approach used to assess and predict companies' exposure to cybersecurity risks. For this purpose, four algorithm implementations from Machine Learning (Light Gradient Boosting, AdaBoost, CatBoost, Multi-Layer Perceptron) were implemented, trained, and evaluated using generative datasets representing the characteristics of different volumes of data (for example, number of employees, business sector, and known vulnerabilities and externel advisor). …”
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ANALISIS FINANCIAL DISTRESS DENGAN METODE ALTMAN, ZMIJEWSKI, GROVER, SPRINGATE, OHLSON DAN ZAVGREN UNTUK MEMPREDIKSI KEBANGKRUTAN PADA PERUSAHAAN RITEL by Yoga Taufan Fahma, Nina Dwi Setyaningsih

“…There are various methods to predict company bankruptcy, namely the Altman, Zmijewski, Grover, Springate, Ohlson, and Zavgren methods. …”
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A Rule-based Model for Predicting Airline Financial Performance from Environmental, Social, and Governance Data by Josiah Kurt B. Aviso, Jonna C. Baquillas, Kathleen B. Aviso, Tsai-Chi Kuo, Hsiao-Min Chen, Raymond R. Tan

“…This work uses ESG performance indicators to develop a rule-based model for predicting company financial performance as measured by return on assets (ROA). …”
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Predicting Business Innovation Intention Based on Perceived Barriers: A Machine Learning Approach by Carolina Rojas-Córdova, Boris Heredia-Rojas, Patricio Ramírez-Correa

“…In this context, this study aims to examine the impact of perceived barriers to innovation to predict companies′ innovative intentions in an emerging economy. …”
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Predicting Fintech Innovation Adoption: the Mediator Role of Social Norms and Attitudes by A. Irimia-Diéguez, F. Velicia-Martín, M. Aguayo-Camacho

“…Our findings support the TRA and TPB models and confirm their robustness in predicting companies’ intention and use of Fintech services. …”
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PENGARUH FAKTOR KECERDASAN, KEPRIBADIAN DAN KAPASITAS KERJA TERHADAP PERFORMANSI DALAM TUGAS BERGANDA by , NI MADE SWASTI WULANYANI, , Dr. Rahmat Hidayat, M.Sc.

“…If this proficiency can be predicted, companies will be able to reduce their expenses by appropriate selection or potential review to their human resources. …”

Development of Marketing Strategy on the Example of it Company by Iryna Boryshkevych, Nataliia Hoi, Olha Zhuk, Dariusz Sala

“…In modern conditions, when market factors have gained even more influence, and the behavior of business structures has become less predictable, companies have to rethink their activities and focus on using the concept of marketing as a management tool. …”
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The importance of bankruptcy prediction and methods by Daiva Rugenytė, Vida Menciūnienė, Lina Dagilienė

“…Scientists tried to find integral method, which credibly allows to predict companies financial problems in time. Applying bankruptcy prediction models is one of the most simple as well as accurate ways for predicting bankruptcy of enterprises. …”
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Predicting bankruptcy of firms using earnings call data and transfer learning by Hafeez Ur Rehman Siddiqui, Beatriz Sainz de Abajo, Isabel de la Torre Díez, Furqan Rustam, Amjad Raza, Sajjad Atta, Imran Ashraf

“…Methodologies and strategies have been investigated in the research domain for predicting company bankruptcy more promptly and accurately. …”
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Retained Earnings, and Book-to-market in the Cross Section of Expected Returns in Tehran Stock Exchange Market by Gholam Reza Keshavarz Haddad, Iman Sharifi

“…This stream of works aim to answer the question of whether the "book to market value" is able to predict companies' returns in capital markets or the returns is caused by other sources including random noise. …”
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