Marketing Spending Models - Innovation and Marketing in the Pharmaceutical Industry - page 566

Table 19.3 Summary of return on investment estimates for pharmaceutical communication activities

ROI in %

Response
function

Journal
advertising Author/s Data Detailing DTC advertising OME ROI deinition

Chintagunta and
Desiraju ( 2005 )

Mixed logit
(share),
Log-log
(category)

Unit sales in one category and
ive countries, 1988-1999

-44-1,833 Short-term

change in
ex factory
sales

Manchanda and
Chintagunta
( 2004 )

Poisson Drug prescriptions at physician

level for one drug in the
USA, 1996-1998

23 Short-term

change in
retail sales

Montoya et al.
( 2010 )

Hidden
Markov

Drug prescription at physician
level for one drug in the
USA, 2 years

20-33 a Long-term

change in
proits

Mizik and
Jacobson
( 2004 )

Linear Drug prescriptions at physician

level for three drugs in the
USA, 2 years

> 0 (1 drug) Long-term

change in
proits

< 0 (2 drugs)

Narayanan et al.
( 2004 )

Mixed logit
(share),
Log-log
(category)

Drug prescriptions at aggregate
level in two US-categories,
1993-2002

665-1,664 179-181 Long-term

change in
retail sales

− Positive
interaction w/
DTCA

− Positive
interaction w/
detailing

− Negative
interaction w/
price and OME

− Negative
interaction w/
OME

Neslin ( 2001 ) Log-linear Drug prescriptions at aggregate

level in the USA,
1995-1999

LB: 134-929 LB: -100-37 LB: 442-579 256 Long-term

change in
retail sales

MB: 78-270 MB: -100-(-41) MB: 347-429

SB: 27-45 SB: -100-(-75) SB: 122-250

Wittink ( 2002 ) Log-linear Drug prescriptions at aggregate

level in the USA,
1995-2000

LB: 210-1,060 LB: -60-30 LB: 210-1,120 LB: 210-1,070 Long-term

change in
retail sales

MB: 20-110 MB: -90-(-80) MB: 130-320 MB: 100-260
SB: -10-0 SB: -100 SB: 520-620 SB: -90
LB Large brands with sales > $200 m/$500 m, MB Medium brands with sales $50-200 m/$100-500 m, SB Small brands with sales $25-50 m/$25-100 m
a ROI is evaluated for optimal allocation policies with respect to detailing and sampling