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Developing and validating a service robot integration willingness scale

Lu, Lu; Cai, Ruiying; Gursoy, Dogan - In: International journal of hospitality management 80 (2019), pp. 36-51

Persistent link: https://www.econbiz.de/10012058602

A conversation with ChatGPT about digital leadership and technology integration : comparative analysis based on human-AI collaboration

Karakose, Turgut; Demirkol, Murat; Yirci, Ramazan; … - In: Administrative Sciences : open access journal 13 (2023) 7, pp. 1-19

Artificial intelligence (AI) is one of the ground-breaking innovations of the 21st century that has accelerated the digitalization of societies. ChatGPT is a newer form of AI-based large language model that can generate complex texts that are almost indistinguishable from human-generated text....

Persistent link: https://www.econbiz.de/10014319371

Development of machine learning-based real time scheduling systems : using ensemble based on wrapper feature selection approach

Shiue, Yeou-ren; Guh, Ruey-shiang; Lee, Ken-chun - In: International journal of production research 50 (2012) 20, pp. 5887-5905

Persistent link: https://www.econbiz.de/10009670323

Machine learning-based classifiers ensemble for credit risk assessment

Pandey, Trilok Nath; Jagadev, Alok Kumar; Choudhury, D.; … - In: International journal of electronic finance : IJEF 7 (2013) 3/4, pp. 227-249

Persistent link: https://www.econbiz.de/10010400393

Artificial neural network and decision tree-based modelling of non-prosperity of companies

Durica, Marek; Frnda, Jaroslav; Svabova, Lucia - In: Equilibrium : quarterly journal of economics and … 18 (2023) 4, pp. 1105-1131

Persistent link: https://www.econbiz.de/10014492220

Predicting mortgage early delinquency with machine learning methods

Chen, Shunqin; Guo, Zhengfeng; Zhao, Xinlei - In: European journal of operational research : EJOR 290 (2021) 1, pp. 358-372

Persistent link: https://www.econbiz.de/10012436411

A hybrid ensemble machine learning model to predict success of Bollywood movies

Verma, Garima; Verma, Hemraj; Dixit, Sushil Kumar - In: World review of entrepreneurship, management and … 17 (2021) 2/3, pp. 343-357

Persistent link: https://www.econbiz.de/10012515249

Deus ex machina? : a framework for macro forecasting with machine learning

Bolhuis, Marijn A.; Rayner, Brett - 2020

We develop a framework to nowcast (and forecast) economic variables with machine learning techniques. We explain how machine learning methods can address common shortcomings of traditional OLS-based models and use several machine learning models to predict real output growth with lower forecast...

Persistent link: https://www.econbiz.de/10012251288

Machine learning and multiple abortions

Kumar, Pradeep; Nicodemo, Catia; Oreffice, Sonia; … - 2024

Boosting, and an Ensemble - alongside registry data on abortions in Spain from 2011-2019 to predict multiple abortions and … assess monetary savings through targeted interventions. We find that Random Forest and an Ensemble method are most effective … in the highest risk decile, capturing about 55% of cases, whereas linear models and Extreme Gradient Boosting excel in …

Persistent link: https://www.econbiz.de/10014545133

Data analytics for non-life insurance pricing

Wüthrich, Mario V.; Buser, Christoph - 2017 - Draft lecture notes, version January 27, 2017

regression trees, bagging, random forest, boosting machines and neural networks. Finally, we provide methodologies for analysing …

Persistent link: https://www.econbiz.de/10011625588