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珞珈营销科学学术论坛第55期
时间:2018-05-07    点击数:

  讲座主题:Comparative Marketing Communication: The Case of Drug Detailing

  主讲人:刘强

  讲座地点:B226

  讲座时间:2018年5月16日(周三)上午9:30-11:00

  摘要:

  Comparative marketing communication has emerged as an important area of managerial and scholarly inquiry. In the pharmaceutical industry, it has been practiced in detailing, the personal selling to physicians. With physician-level panel data of detailing and prescriptions, we examine the effectiveness of comparative detailing versus noncomparative detailing. In particular, we investigate whether a brand’s comparative detailing directly damages competing brands or provides them free exposure to physicians. The Bayesian hierarchical probit model with reduced-form detailing policy functions allows us to examine comparative detailing at both aggregate level and individual physician level, while controlling for possible simultaneity issues in noncomparative detailing and comparative detailing. We find that (1) comparative detailing is less or equally effective than noncomparative detailing at the aggregate level, but there is strong heterogeneity across individual physicians; (2) some brands strategically focus their comparative detailing efforts on physicians who are less responsive to noncomparative detailing but more responsive to comparative detailing than others; (3) the market leader faces a denigrating loss if underdog brands compare against it in their detailing visits, but a generic brand enjoys a free-exposure benefit when other brands in the category compare against it in their detailing visits. Our estimates provide rich managerial implications by identifying physicians who are more profitable for comparative detailing. Finally, our policy simulation shows that a ban of comparative detailing can reduce the market share of generic drugs by 1.76% in statin market.

  个人简介:

  刘强,北京大学理学士,经济学双学位,公共管理硕士,伯克利加州大学统计学硕士,康奈尔大学管理学博士。 普渡大学克兰特管理学院市场学副教授。刘强教授在普渡大学讲授市场模型,市场营销管理,和数字和社交媒体市场营销等课程。主要研究方向为离散选择模型,动态结构模型,应用贝叶斯统计,医药市场研究,共享经济,以及机器学习在市场营销中的应用。研究成果发表于 Marketing Science, Management Science, Inernational Journal of Research in Marketing 等国际一流学术期刊