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Modern businesses routinely capture data on millions of observations across subjects, brand SKUs, time periods, predictor variables, and store locations, thereby generating massive high-dimensional datasets. Predictive choice modeling of such massive databases poses novel computational and modeling issues, and the negligence of academic research to address them will result in a disconnect from the marketing practice and an impoverishment of marketing theory. To address these issues, paper discusses and identifies the challenges and opportunities for both practicing and academic marketers. Thus, an impetus is offered for advancing research in this nascent area and fostering collaboration across scientific disciplines to improve the practice of marketing in information-rich environment.
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