Results 141 to 150 of about 6,446,404 (186)

Cognitive Load in the Age of Artificial Intelligence: A Bibliometric Analysis (2021-2025). [PDF]

Ann Neurosci
Gupta S, Mishra BN, Gore R, Singh SK, Awasthi A, Mishra A, Kishore R, Singh V.   +7 more
europepmc   +1 more source

Giving as repaying: towards an embodied ethics of living donor liver transplantation. [PDF]

Med Health Care Philos
Lin YP, Chen HY.
europepmc   +1 more source

Indebtedness, Over-Indebtedness and Wellbeing

, 2019
The indebtedness and possible over-indebtedness of households have attracted attention in academic research and in society at large. In this chapter, we summarize current research on indebtedness and over-indebtedness with especial emphasis on efforts and attempts to derive a more precise and applicable definition of the concept of over-indebtedness ...
Viktor Elliot, Ted Lindblom, Elliot Viktor   +2 more
exaly   +3 more sources

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The gender gap in over-indebtedness

Finance Research Letters, 2019
Abstract We document a significant gender gap in over-indebtedness, as we find women to be less likely to become over-indebted even after controlling for risk attitude, financial literacy and socio-demographic characteristics. However, once we account for loan purposes the gender gap diminishes.
Tobias Meyll, Thomas Pauls
exaly   +2 more sources

Over-Indebtedness in the Finnish Consumer Society

Journal of Consumer Policy, 2010
The incurring of debts continues to be a major problem in European economies despite the legislative and other preventive policies introduced over the past 10 years. This article discusses the problem of over-indebtedness in the Finnish consumer society.
Anu Raijas, Anna-Riitta Lehtinen, Johanna Leskinen   +2 more
openaire   +2 more sources

PRODUCING OVER-INDEBTEDNESS

Journal of Cultural Economy, 2012
exaly   +2 more sources

Predicting over-indebtedness on batch and streaming data

2017 IEEE International Conference on Big Data (Big Data), 2017
Detecting over-indebtedness, the difficulties meeting household payment commitments, poses multiple Big Data challenges for banking institutions. We present a novel data-driven framework for predicting over-indebtedness on real-world data. A warning mechanism that generates predictions 6 months ahead, improving the chances of financial recovery.
Jacob Montiel, Albert Bifet, Talel Abdessalem   +2 more
openaire   +1 more source