Invited paper-learning models: : An assessment of progress, challenges, and new developments

• Autores: Andrew T. Ching, Tülin Erdem, Michael P. Keane
• Localización: Marketing science, ISSN 0732-2399, Vol. 32, Nº 6, 2013, págs. 913-938
• Idioma: inglés
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• Resumen

  • Learning models extend the traditional discrete choice framework by postulating that consumers have incomplete information about product attributes and that they learn about these attributes over time. In this survey we describe the literature on learning models that has developed over the past 20 years, using the model of Erdem and Keane as a unifying framework [Erdem T, Keane M (1996) Decision-making under uncertainty: Capturing dynamic brand choice processes in turbulent consumer goods markets. Marketing Sci. 15(1):1�20]. We describe how subsequent work has extended their modeling framework and applied learning models to a wide range of different products and markets. We argue that learning models have contributed greatly to our understanding of consumer behavior�in particular, in enhancing our understanding of brand loyalty and long-run advertising effects. We also discuss the limitations of existing learning models and potential extensions. One key challenge is to disentangle learning as a source of dynamics from other key mechanisms that may generate choice dynamics (inventories, habit persistence, etc.). Another is to enhance identification of learning models by collecting and using direct measures of signals, perceptions, and expectations.