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Análisis bibliométrico de la producción científica sobre la aplicación de las ciencias de datos para la toma de decisiones en análisis de riesgos, 2015-2020
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Análisis bibliométrico de la producción científica sobre la aplicación de las ciencias de datos para la toma de decisiones en análisis de riesgos, 2015-2020 (2020)Análisis bibliométrico de la producción c…Statistical Data Analysis in the Era of Big Data (2020)Statistical Data Analysis in …Investigating the adoption of big data analytics in healthcare: the moderating role of resistance to change (2019)Investigating the adoption of…How enterprise architecture improves the quality of IT investment decisions (2019)How enterprise architecture i…Chapter 12: What does the Anthropocene hold for citizenship? (2019)Chapter 12: What does the Ant…Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting (2019)Can deep learning predict ris…Application of Data Mining Technology in Financial Risk Analysis (2018)Application of Data Mining Te…A Framework for Describing Big Data Projects (2017)A Framework for Describing Bi…A Comparative Review of Data Warehousing ETL Tools with New Trends and Industry Insight (2017)A Comparative Review of Data …Process Mining (2016)Process MiningBig data team process methodologies: A literature review and the identification of key factors for a project's success (2016)Big data team process methodo…Editorial —Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research (2014)Editorial —Big Data, Data Sci…Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking (2013)Data Science for Business: Wh…Financial early warning system model and data mining application for risk detection (2011)Financial early warning syste…Toma de decisiones gerenciales (2003)Toma de decisiones gerencialesFinancial Ratios As Predictors of Failure (1966)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)Methodological Issues Related to the Estimation of Financial Distress Prediction Models (1984)Recent Development in Big Data Analytics for Business Operations and Risk Management (2016)Big data techniques in auditing research and practice: Current trends and future opportunities (2018)MACHINE LEARNING METHODS FOR SYSTEMIC RISK ANALYSIS IN FINANCIAL SECTORS (2019)CONJECTURES AND REFUTATIONS (1963)To Explain or to Predict? 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(2003)Factors Determining the Behavioral Intention of Using Food Delivery Apps during COVID-19 Pandemics (2021)Maneuvering through the stormy seas of digital transformation: the impact of empowering leadership on the AI readiness of enterprises (2021)Role of perceived ease of use, usefulness, and financial strength on the adoption of health information systems: the moderating role of hospital size (2024)Business Intelligence and Analytics: From Big Data to Big Impact (2012)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)Deep learning with long short-term memory networks for financial market predictions (2017)Forex exchange rate forecasting using deep recurrent neural networks (2020)Forecasting mid-price movement of Bitcoin futures using machine learning (2021)Stock price prediction with optimized deep LSTM network with artificial rabbits optimization algorithm (2023)Automated Text Analysis for Consumer Research (2017)Using Data Sciences in Digital Marketing: Framework, methods, and performance metrics (2020)Data Science and Analytics: An Overview from Data-Driven Smart Computing, Decision-Making and Applications Perspective (2021)Automated Discovery of Process Models from Event Logs: Review and Benchmark (2018)Outcome-Oriented Predictive Process Monitoring (2019)Examining the interplay between big data analytics and contextual factors in driving process innovation capabilities (2020)Building an inclusive definition of e-learning: An approach to the conceptual framework (2012)Active accessibility: A review of operational measures of walking and cycling accessibility (2015)Learner Engagement in Blended Learning Environments: A Conceptual Framework (2019)
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References

  • 2019Chapter 12: What does the Anthropocene hold for citizenship?11,554 cited
  • 2016Process Mining2,166 cited
  • 2013Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking715 cited
  • 2014Editorial —Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research616 cited
  • 2019Investigating the adoption of big data analytics in healthcare: the moderating role of resistance to change200 cited
  • 2011Financial early warning system model and data mining application for risk detection148 cited
  • 2019Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting120 cited
  • 2016Big data team process methodologies: A literature review and the identification of key factors for a project's success91 cited
  • 2017A Comparative Review of Data Warehousing ETL Tools with New Trends and Industry Insight65 cited
  • 2019How enterprise architecture improves the quality of IT investment decisions64 cited
  • 2003Toma de decisiones gerenciales63 cited
  • 2018Application of Data Mining Technology in Financial Risk Analysis44 cited
  • 2017A Framework for Describing Big Data Projects12 cited
  • 2020Statistical Data Analysis in the Era of Big Data10 cited

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