Andy Norton

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The authors test methods, based on cognitively simple decision rules, that predict which products consumers select for their consideration sets. Drawing on qualitative research, the authors propose disjunctions-of-conjunctions (DOC) decision rules that generalize well-studied decision models, such as disjunctive, conjunctive, lexicographic, and subset(More)
Contents Acronyms 5 Acknowledgements 6 Summary 7 Definition and rationale 7 Why now? The context for contemporary global interest in social protection 7 Lessons from experience 11 Implications for development agencies 14 Future directions in social protection 14 Conclusion – Social protection, the development process and poverty reduction 15
(MIT) for their insights, inspiration, and help on this project. Abstract We propose and test an active-learning algorithm to estimate heuristic decision rules that consumers use to form consideration sets for automobile purchases. The complexity of the product (large number of features and levels) and the non-linearity in models of heuristic decisions lead(More)
teaches in the mathematics department at Virginia Tech in Blacksburg, where he also conducts research on children's mathematical development. He concentrates on building models of students' mathematics and studying how students form mathematical conjectures. Andrea V. McCloskey, amcclosk @indiana.edu, is a doctoral student in mathematics education at(More)
Morphing enables a website to learn (actively and near optimally) which banner advertisements to serve to each cognitive-style segment in order to maximize outcome measures such as click-through, brand consideration, or purchase. Consumer segments are identified automatically from consumers' clickstream choices. Morphing works best on high-traffic websites(More)
Business at MIT (ebusiness.mit.edu), and an unnamed American automotive manufacturer. We would like to thank for their insights, inspiration, and help on this project. Both reviewers and the Area Editor provided excellent comments that improved our paper. Abstract We develop and test an active-machine-learning method to select questions adaptively when(More)
Our Discussion Paper series is available free of charge. We also produce summaries of our research in CASEbriefs, and reports from various conferences and activities in CASEreports. To subscribe to the CASEpaper series, or for further information on the work of the Centre and our seminar series, please Abstract This paper analyses the work of the Nobel(More)
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