統計学輪講（第３３回）

日時    2004年 11月 30日(火)　15時〜16時40分
場所    経済学部新棟３階第３教室
講演者  Peter E. Rossi(University of Chicago)
演題    Response Modeling with Non-Random Marketing Mix Variables
概要：
  Sales response models are widely used as the basis for optimizing 
the marketing mix or for allocation of the sales force. Response 
models condition on the observed marketing mix variables and focus 
on the specification of the distribution of observed sales given 
marketing mix activities. These models usually fail to recognize 
that the levels of the marketing mix variables are often chosen with 
at least partial knowledge of the response parameters in the conditional 
model. This means that, contrary to standard assumptions, the marginal 
distribution of the marketing mix variables is not independent of 
response parameters. We expand on the standard conditional model to 
include a model for the determination of the marketing mix variables. 
We apply this modeling approach to the problem of gauging the effectiveness 
of sales calls (details) to induce greater prescribing of drugs by 
individual physicians. We do not assume, a priori, that details are set 
optimally but, instead, infer the extent to which sales force managers 
have knowledge of responsiveness and use this knowledge to set the level 
of sales force contact. We find that physicians are not detailed optimally; 
high volume physicians are detailed to a greater extent than low volume 
physicians without regard to responsiveness to detailing. In fact, it 
appears that unresponsive but high volume physicians are detailed the most.

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Tokyo University