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Informal Firms' Adoption and Use of Mobile Money Under Uncertain Times: Evidence From Burkina Faso
Review of Development Economics, EarlyView.ABSTRACT This paper investigates how uncertainty affects mobile money adoption and use by informal businesses. Despite the prevalence of the informal sector in developing countries and the recognized potential of mobile money for financial inclusion, empirical research on its adoption and usage among unregistered businesses is limited.
Serge Stéphane Ky, Clovis Rugemintwari
wiley +1 more source
Moral Tolerance: The Ethics of Social Punishment in Cases of Moral Disagreement
Theoria, EarlyView.ABSTRACT In many practical contemporary contexts, people need to make correct ethical judgements about how to respond to perceived wrongdoing—in particular, whether to punish it or tolerate it. This judgement can be challenging when the wrongdoer does not accept the allegation of wrongdoing at the level of moral principle, holding that the type of ...
Hugh Breakey, Graham Wood
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Personalized Model‐Driven Interventions for Decisions From Experience
Topics in Cognitive Science, EarlyView.Abstract Cognitive models that represent individuals provide many benefits for understanding the full range of human behavior. One way in which individual differences emerge is through differences in knowledge. In dynamic situations, where decisions are made from experience, models built upon a theory of experiential choice (instance‐based learning ...
Edward A. Cranford +6 more
wiley +1 more source
Building centaur responders: is emergency management ready for artificial intelligence?
Disasters, Volume 50, Issue 3, July 2026.Abstract This article examines the preparedness of emergency management (EM) for addressing questions pertaining to artificial intelligence (AI), encompassing its benefits to EM missions, the potential biases, the societal impacts, and more. We pinpoint two key shortcomings in early EM research on AI: (i) insufficient discussion of both AI's history ...
Christopher Whyte +1 more
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A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
Applied AI Letters, Volume 7, Issue 2, June 2026.This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang +3 more
wiley +1 more source
eFood, Volume 7, Issue 3, June 2026.This review synthesizes AI advancements in food systems, leveraging machine learning, computer vision, robotics, and IoT for 96%–100% accurate quality inspection, 30% reduced downtime, and enhanced traceability from farm to fork. It highlights transformative potential in sustainability and SDGs while addressing data, ethical, and scalability challenges
Muhammad Waqar +9 more
wiley +1 more source
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Computer, 2017
Our society increasingly relies on the successful marriage of digital and physical systems to perform advanced automation and control tasks. Engineering these cyber-physical systems to ensure their efficiency, security, and dependability is a research area of tremendous importance.
Letichevsky, A. A. +3 more
openaire +3 more sources
Our society increasingly relies on the successful marriage of digital and physical systems to perform advanced automation and control tasks. Engineering these cyber-physical systems to ensure their efficiency, security, and dependability is a research area of tremendous importance.
Letichevsky, A. A. +3 more
openaire +3 more sources