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From Decision Support to Decision Automation: A 2020 Vision
Authors:Bucklin  Randolph  Lehmann  Donald  Little  John
Institution:(1) Anderson School at UCLA, Los Angeles, CA, 90095;(2) Graduate School of Business, Columbia University, New York, NY, 10027;(3) Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, 02139
Abstract:The authors discuss the long-run future of decision support systems in marketing. They argue that a growing proportion of marketing decisions can not only be supported but may also be automated. From a standpoint of both efficiency (e.g., management productivity) and effectiveness (e.g., resource allocation decisions), such automation is highly desirable. The authors describe how model-based automated decision-making is likely to penetrate various marketing decision-making environments and how such models can incorporate competitive dynamics. For example, the authors foresee that close to full automation can ultimately take place for many decisions about existing products in stable markets. Partial automation could characterize decision making for new products in stable markets and existing products in unstable markets.
Keywords:Decision support  automation  competition
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