Researchers from University of Texas-Austin and Copenhagen Business School published a new paper in the Journal of Marketing that offers actionable guidance to managers on the deployment of algorithms ...

Although they are computationally efficient, their suboptimal nature introduces extra algorithmic errors that can obscure true hardware performance. The theoretical alternative—maximum-likelihood ...

Consumers are less forgiving of brand failures when algorithms are anthropomorphized, use machine learning, or are used for subjective or interactive tasks. Researchers from University of Texas-Austin ...