Gurumurthy Kalyanaram on Entry Effect in Pharma in IJPHM

The order of entry effect in prescription (Rx) and over-the-counter (OTC) pharmaceutical drugs

GK Associates, UT Dallas, Texas, USA

Effect in Rx and
OTC drugs

Abstract : Purpose – This paper aims to study the effects of order of market entry on market share in prescription (Rx) and over-the-counter (OTC) pharmaceutical drugs market.

Design/methodology/approach – Data on sales, price, direct-to-physicians (DTP) advertising, and direct-to-consumers (DTC) advertising for three Rx drugs categories and two OTC drugs categories were obtained for the period, January 1998 to December 1999. A log-log statistical model was estimated using OLS methodology.

Findings – There is a significant order of entry effect on market share in both Rx and OTC drugs categories. This effect is higher in magnitude in the OTC category than in the Rx category. The effects of price, and DTP and DTC advertising are also significant. The differential effects of DTP and DTC advertising in the Rx and OTC categories are intuitive.

Originality/value – This study is unique in studying the differential effects of order-of-entry, and DTP and DTC advertising on market share in Rx and OTC drugs product categories.

Keywords Market system, Market entry, Pharmaceuticals industry, Drugs

Paper type Research paper

Introduction

Firms grow in revenues, profits and market shares through development of new products (product innovation) and/or development of new markets (market development). Product innovation and market development are expensive and require careful planning and execution. For example, the cost of product innovation and development in the pharmaceutical industry can be as high as $200 million even for incremental product innovations and much more for radical product innovations.

In market development, a firm has to make the consumers aware of its product (and educate them about the product, particularly in the drugs market), and persuade the distributors to carry the product. In case of pharmaceutical drugs market, these costs are even higher. The firm has to educate and persuade not only the end consumers but also the physicians. Furthermore, quite often the regulation requires that the firm informs the consumers and physicians about the efficacy and potential side-effects of the product.

It can be even more expensive and risky to be a pioneering brand, i.e. a first-entrant in a market (Urban and Hauser, 1995). Why? Obviously, the first firm in a market has to invest substantially higher resources in market development than later market entrants. Couple this with the fact that the risk of failure of product innovations is high because the potential demand is not known with certainty. In pharmaceutical drugs market, the uncertainty comes not only from the potential market demand but also.

International Journal of – Pharmaceutical and Healthcare

Marketing

Vol. 2 No. 1, 2008

pp. 35-46

q Emerald Group Publishing Limited

1750-6123

DOI 10.1108/17506120810865415

IJPHM from the regulatory approval process (e.g. the FDA approval process). Therefore, the
2,1 commitment for the first entrant in the pharmaceutical drugs market is very steep.
So the question simply is: are there rewards (such as higher market share or profit) to being the first entrant (pioneer or an early entrant) than a later entrant in the pharmaceutical drugs market?
Why? A firm’s innovation strategy depends on the level of expected rewards. If a later entrant and the first-entrant (pioneer) were to achieve equal market shares, a later entry strategy is clearly more profitable for a firm. The costs for the later entrant are likely to be lower because the pioneer and the early entrants would have created the primary demand for the product and educated the consumers and distributors. If, on the other hand, as a result of being the first entrant in a market, a dominant market share is achieved and maintained, the innovation/pioneering strategy may be superior.

The purpose of this paper is to investigate the market share effects of being a pioneering brand and/or an early entrant. After all, if the market grants a long-run market share reward to early entrants, this would encourage product innovation. Innovation is most critical in the pharmaceutical industry.

This paper examines the effects of order of market entry in the pharmaceutical drugs industry. There are different taxonomies of categories/classes of drugs. Two of them are prescription (Rx) drugs and over-the counter (OTC) drugs. RX drugs require physicians’ Rx for sale to end-consumers. Some pharmaceutical drugs, after being prescribed by physicians for several years, could become off-patent or get approved (by the FDA) for OTC purchase. However, there are also many occasions when the FDA permits a pharmaceutical drug to be directly sold to the consumers (OTC) without requirements of any Rx. Innovation is in both situations – be it when the drug introduced as Rx drug or directly as OTC drug. This paper studies the entry effect in both the categories – Rx and OTC categories – of drugs.

The rest of this paper is organized as follows. First, we describe important issues relating to Rx and OTC drugs, the role of advertising and the regulatory context. Then we provide a brief overview of the relevant literature. Next we describe the data, and the statistical model. We follow this with presentation of the empirical results. We close with a discussion of the managerial implications of the results, and identification of future research needs.

Marketing efforts in the pharmaceutical drugs industry

In the study of the order of entry effect on market share, it is important to consider the effects of other marketing and product variables. Apart from price which is always an important determinant of market share in any product category, advertising/promotion effects have also proved to be significant. So the extant literature on order-of-entry effect (Urban et al., 1986; Kalyanaram and Urban, 1992; Berndt et al., 1995) has always included both price and advertising in the examination of entry effects. Consistent with this, our goal in this study is to include the effects of price and advertising as moderating variables.

However, advertising/promotion in the pharmaceutical drugs category has a unique history. The audience consists of two very different but significant groups (physicians and end-consumers), and the content of advertisement has been subject to regulations which have evolved over time. So, in this section, we briefly describe the evolution of marketing efforts in the pharmaceutical drugs market.

The modern distinction between Rx and OTC drugs began with the 1938 Federal Food, Drug, and Cosmetic Act. This act defined different labeling guidelines for Rx and OTC drugs. The 1962 Kefauver-Harris amendments to the Federal Food, Drug, and Cosmetic Act gave the FDA its current responsibility to monitor Rx drug promotional materials, and set the parameters required for Rx marketing efforts: Rx promotional materials cannot be false or misleading; they must provide a “fair-balance” coverage of risks and benefits of using the drug; they must provide a summary of contraindications, side effects, and effectiveness; and they must also meet specific guidelines for readability and size of print.

Since, then, Rx drugs have been marketed not only direct-to-physicians (DTP), but also more directly to consumers (DTC). For example, in March 1988, Tagamet Rx launched “Tommy Tummy” and “stomach TLC” DTC marketing campaigns, and soon after Glaxo initiated an extensive television and print DTC effort for Zantac.

These restrictions on DTC marketing (not on DTP marketing) were relaxed in 1997 when the FDA issued new draft guidelines. A manufacturer is now permitted to advertise an Rx drug’s name and the condition for which it is indicated without needing to issue as fully detailed a summary regarding the product’s side effects and other risks. This is why we see a whole host of advertising campaigns directly targeted to the end consumers – be it, for example, for Rogaine or Celebrex or Prilosec or Bayer.

The FDA requirements for risk disclosure in advertisements can now be fulfilled simply by providing a source (e.g. positioned toll-free phone number or web address) for information. Usually, there is explicit encouragement for readers and viewers of DTC advertisements to discuss the product with their physicians.

Prior to 1997, regulatory requirements made TV advertising prohibitively expensive, and DTC advertising was largely limited to newspapers and magazines. However, since the regulatory changes in 1997, the DTC marketing efforts have expanded monumentally. For example, DTC advertising expenditures increased from $800 million in 1996 to $2.5 billion in 2000. As of 2000, DTC advertising accounted for 2.5 percent of the overall mass media ad spending in the USA. The top promoted drug – Vioxx – spent $146 million in DTC marketing efforts, beating Pepsi Cola, Budweiser Beer, and most automobile manufacturers. According to IMS Health, DTC marketing expenditures for Rx medications increased from $1.1 to 2.5 billion between 1997 and 2000.

Brief overview of relevant literature

Bond and Lean (1997), Berndt et al. (1995) and King (2000) have documented strong order-of-entry effects in the branded Rx drugs markets. Within OTC and other non-drugs consumer markets, there is a large literature documenting the importance of order of entry for early entrants (Kalyanaram et al., 1995; Robinson, 1988; Kardes et al., 1993; Kalyanaram and Urban, 1992). Many economic (Schmalensee, 1982) and behavioral (Kardes and Kalyanaram, 1992; Carpenter and Nakamoto, 1989) explanations have been given for order of entry advantages.

This paper extends and complements the base of empirical knowledge in the study of order of entry effect in pharmaceutical drugs. The paper provides comparative statistics of the estimates of the order of entry effects in Rx and OTC drug markets.

There are a few other findings that are relevant in the context of pharmaceutical drugs category. Berndt et al. (1995) also found that the sum of the elasticity of DTC promotion at the category level is about 0.76, suggesting decreasing returns to scale to

Effect in Rx and
OTC drugs

IJPHM overall advertising at the product category level. They examined the branded
2,1 anti-ulcer (H2-antagonist) RX drugs up through May 1994.
Additionally, two relatively recent studies – (Wosinska, 2001; Ling et al., 2002) –

have studied the effect of marketing efforts DTC. They have incorporated data after
the FDA’s 1997 clarification of DTC guidelines. Wosinska (2001) found that the DTC
advertising efforts positively impact total therapeutic class sales, but only impact an
individual brand positively if that brand has a preferred status on the third party
payer’s formulary.

Ling et al. (2002) found that DTC marketing efforts of an OTC brand have no spillover to the same brand in the Rx market. Within the Rx market, own-brand physician-oriented detailing and advertising (DTP) have positive and long-lived impacts on own Rx market share, while DTC marketing of the Rx brand has no significant impact on own Rx market share. Within the OTC market, not only are own-brand impacts of DTC marketing on the OTC brand significantly positive and long-lived, but also physician-oriented Rx marketing efforts have positive own-brand spillovers to the OTC share. DTC marketing efforts for Rx brands have no significant impact on same-brand OTC shares.

Data
Rx drug markets

We examine monthly data from January 1998 to December 1999 for three therapeutic classes of drugs: recent anti-depressants (SSRIs plus serotonin/norepinephrine reuptake inhibitors), proton pump inhibitors (PPI), and antihistamines drugs. These drugs are fairly general in application: they treat a large variety of ailments, are indicated for different patient populations and are prescribed by a number of different clinical specialties. Data were collected on all of the drugs in each of these three classes.

The anti-depressants category consists of six brands. The brands and their FDA approval dates are Celexa (1998), Serzone (1994), Effexor XR (1993), Paxil (1992), Zoloft (1991) and Prozac (1987). The PPI category consists of three brands. The brands and their FDA approval dates are Aciphex (1999), Prevacid (1995) and Prilosec (1989). The antihistamines category consists of five brands. The brands and their FDA approval dates are Astelin (1996), Allegra (1996), Zyrtec (1995), Semprex-D (1994) and Claritin (1993).

Monthly price, quantity, and DTP marketing data for Rx drugs were obtained from IMS Health, a health care consulting firm. Market shares were constructed from product-level data on sales for the drugs in each of the three classes.

There are at least two major components to DTP marketing (we secured this data also from the healthcare consulting firm). The first component is detailing to the physicians. This data are produced from the records of a panel of physicians, and estimates of cost per detailing visit by the sales representative. The second component is targeted advertising to physicians. This is measured through an audit of medical journals on a monthly basis. So the DTP expenditures are aggregation of detailing expenditures and targeted medical journal advertising expenditures.

Separate from, and in addition to DTP, there is also advertising and promotion directed to the end-consumer (DTC – direct-to-consumer advertising). Data on DTC marketing of Rx brands from Leading National Advertisers (LNA)/Media Watch Multi-Media Service is published on a quarterly basis by Competitive Media Reporting. This service reports Rx brand advertising expenditure estimates in ten major media:

consumer magazines, Sunday magazines, newspapers, outdoor, network television, spot television, syndicated television, cable television, network radio, and national spot radio. The LNA/Media Watch Multi-Media Service includes only brands of companies spending a total of $25,000 or more year-to-date in the ten media measured. We gathered the quarterly data, and transformed the quarterly data into monthly data simply by apportioning the total expenditures equally to each of the three months in the quarter.

Over-the-counter drug markets

We examined monthly data from the same time-period – January 1998 to December 1999 – for two therapeutic classes of drugs: anti-ulcer (heartburn) and smoking-cessation drugs. The two classes also are fairly general – they are indicated for different patient populations and are prescribed by a number of different clinical specialties. Data were collected on all of the drugs in each of these two classes.

The anti-ulcer (heartburn) category consists of four brands. The brands and their FDA approval dates are Tagamet (1982-1983), Zantac (1984), Pepcid (1986) and Axid (1988).

The smoking-cessation category consists of three brands. The brands and their FDA approval dates are Nicorette (1996), Nicotrol (1996) and Nicoderm (1996).

The quantity, price, and revenue data used to analyze the OTC market are taken from Info Scan and are based on store-level optical scanner data that are purchased and collected from multiple retail outlets by IRI. These scanner data are collected weekly from more than 29,000 chain drugstores, mass merchandisers, food stores, and chain convenience stores located in major metropolitan areas and rural areas. They are then projected to national levels for these chains.

The IRI data provide detailed information on sales, and pricing. The weekly data are aggregated to the monthly level.

To obtain DTP promotion efforts, we again employ data from the healthcare consulting firm.

To obtain measures of DTC monthly advertising of OTC drugs, we again employ data from LNA/Media Watch Multi-Media Service. LNA distinguishes consumer-oriented OTC brand advertising from that for Rx brands. Quarterly data on media advertising over the ten media mentioned earlier for the OTC brands are taken, and then transformed into monthly data simply by apportioning the total expenditures equally to each of the three months in the quarter.

Statistical model and calibration

We model overall market share in each period as a function of price and advertisement efforts and modified by order of entry effect. All variables except order of entry are expressed as ratios to the first brand to enter the category. The formal equation is:
Sit Eia Qil Pitb DTPitd DTCith 1
¼ ð Þ

where, Sit represents the market share of the ith entrant as a ratio of the market share of first entrant in the category i at time t, Ei represents the order of market entry (2, 3, 4, 5 . . .) of the brand i, Qi represents a measurement of the perception of the quality of the brand i, Pit represents the price of the ith entrant as a ratio of the price of first

Effect in Rx and
OTC drugs

IJPHM 2,1

entrant in the category i at time t, DTPit represents the advertising effort directly to the physicians of the ith entrant as a ratio of the advertising effort (DTP) of first entrant in the category i at time t, DTCit represents the advertising effort DTC of the ith entrant as a ratio of the advertising effort (DTC) of first entrant in the category i at time t.

This multiplicative form of share model allows for non-linear response and interaction effects between the variables.

Obviously, initially the pioneer has 100 percent of the market but loses share as the second brand enters. This is the constant ratio model assumption of competitive interaction and it has the attractive property in our case that when we ratio the share of the ith brand to enter the market to the first entrant in the category, the curves of relative share versus time become smooth. One reason why we ratio the ith brand share to the first brand to enter the category is now evident, but another reason results from our desire to estimate equation (1) with time series and cross sectional data. Ratios allow reasonable comparisons across categories with different numbers of brands. In a three brand as well as in a two brand category, we posit that the share ratio will be the same between the second and first entrants even though the absolute share may be very different (e.g. 40 percent vs 60 percent in a two brand market and 33.3 percent vs 50 percent in a three brand market). A third reason is that the ratios are an appropriate way of eliminating cross category differences in marketing instruments, e.g. some categories have higher prices or promotional or advertisement expenditures and others have lower levels.

The share model developed above is a linear time series cross-sectional model from the estimation point of view. We linearize the basic terms of equation by taking logs of both sides of them. Taking log on both sides of the above model, we have the following specification:

logðSit Þ ¼ ðaÞlogðEiÞ þ ðlÞlogðQiÞ þ ðbÞlogðPitÞ þ ðdÞlogðDTPitÞ þ ðhÞlogðDTCit Þ ð2Þ

Note that this is a linear regression with no additive constant. The additive constant would confound the interpretation of the magnitude of coefficients because with an additive constant in equation (2), the share index will not equal to one for the first brand in the market as is required for logical consistency.

However, since we do not have quality measurement for the brands, we use brand-specific constants to account for the quality measure. Of course, the brand-specific constants would also account for other (other than the quality measure) variations unique to the brand:

logðSit Þ ¼ ðaÞlogðEiÞ þ ðliÞlogðQiÞ þ ðbÞlogðPitÞ þ ðdÞlogðDTPit Þ þ ðhÞlogðDTCitÞ ð3Þ

where Qi now represents the brand-specific constants for each of the brands. However, we now have an individual parameter associated with each brand-specific constant.

Since, there are a total of 14 brands in the Rx product class in the three categories, the total number of brands with the ratio data are 11 brands (one brand is the pioneer in each one of the three categories). Hence, we incorporate ten brand-specific constants (11 brand-specific constants would lead to singularity).

There are two categories and a total of seven brands in the OTC product class. Hence, the total number of brand-specific constants in the OTC product class is 4.

We employ OLS estimation to calibrate the model. We estimate the model separately for both the cases/classes – Rx drugs and OTC drugs – to examine if there was an order of entry effect.

Empirical results

The statistical results of estimating the share equation are shown in Tables I and II. The fits are good with R 2 values of 0.89 and 0.71. Of course, some of this fit comes from time-series data.

Since, the model is a log-log model, the parameter estimates represent elasticities of the variables. Therefore, it is quite appropriate to compare the parameter estimates of the share model for the Rx and OTC drugs categories.

The a parameter is negative and significant at the five percent level in both the cases. This indicates that later entrants achieve lower market share. This is a significant empirical result. Consistent with the results in other product categories – consumer packaged goods, industrial goods – we find that the order of entry effect is present in the pharmaceutical drugs too.

The magnitudes of the order of entry effects and penalties for the two classes of drugs are different. While the late entry penalty for the OTC drugs is 20.62, the late entry penalty for the Rx drugs is 20.45. That difference in order-of-entry penalty is substantial.

Effect in Rx and
OTC drugs

Variable Parameter (coefficient) Value T-statistic

Order of entry effect (E )   a
Price effect (P )   b
Effect of direct advertising to physicians (DTP)   d
Effect of direct advertising to consumers (DTC)   h
Brand-specific constant 1   L1
Brand-specific constant 2   L2
Brand-specific constant 3   L3
Brand-specific constant 4   L4
Brand-specific constant 5   L5
Brand-specific constant 6   L6
Brand-specific constant 7   L7
Brand-specific constant 8   L8
Brand-specific constant 9   L9
Brand-specific constant 10   L10

2   0.45   26.9
2   0.52   22.1
þ0.81   þ2.9
þ0.12   þ3.8
þ4.9   þ5.9
þ1.1   þ1.9
þ2.9   þ2.1
2   0.95   23.1
þ3.3   þ7.1
þ2.4   þ1.8
2   4.1   26.1
þ2.5   þ2.8   Table I.
þ4.3   þ1.4   Empirical results: Rx
2   0.8   21.4   drugs market

Variable Parameter (coefficient) Value T-statistic

Order of entry effect (E )   a   2   0.62   2   5.6
Price effect (P )   b   2   1.92   2   6.9
Effect of direct advertising to physicians (DTP)   d   þ0.69   þ2.2
Effect of direct advertising to consumers (DTC)   h   þ0.31   þ3.1
Brand-specific constant 1   L1   24.95   2   3.72
Brand-specific constant 2   L2   þ2.7   þ7.1   Table II.
Brand-specific constant 3   L3   þ1.1   þ1.76   Empirical results: OTC
Brand-specific constant 4   L4   20.83   2   1.92   drugs market

IJPHM 2,1

The magnitude of order of entry effect is higher in the OTC drugs than in Rx drugs suggesting that the impact on later entry on experts (e.g. physicians) is likely to be less than on non-experts (e.g. end-consumers) in OTC. This is consistent with intuition and theories discussing the reasons for entry penalty. For example, one important theory relates to “uncertainty.” Uncertainty about a product performance drives users to earlier (and successful) entrants. In case of pharmaceutical drugs, there is much higher level of uncertainty about the performance of a drug for the consumer-patients than for the prescriber-physicians. Therefore, the late entry penalty is likely to be higher in the OTC purchase situation than in the Rx situation.

Assuming parity in all other variables (e.g. price, advertising/promotion efforts directly to the physicians and consumers, and perceptions of brand quality), the comparative penalties are shown for the Rx and OTC drugs categories in Tables III and IV.

The other parameters also provide interesting insights. All the estimates are significant at 5 or 10 percent level. The price estimates show greater elasticity for the OTC drugs category (21.92) than the Rx drugs category (20.52). This is intuitive. Given that the OTC drugs are likely to face more competition (from generics and others), the price elasticity estimate of 21.92 is comparable to estimates of price elasticity in competitive product categories. Since, Rx drugs can be bought and consumed only on the recommendations of the physicians, and since we are talking about a product category (drugs) where the choices are limited, if any (alternative therapies), it is not surprising that the price effect is less than one.

Understandably, the estimate for advertising/promotion directly to physicians is higher for the Rx drugs category (þ0.81) than in the OTC drug category (þ0.69). However, the advertising to physicians has substantial impact in the OTC drugs category too Gurumurthy Kalyanaram LawSuit

Market share
Entry relative to the
order first entrant

Market share Market share of first of second entrant entrant (percent) (percent)

Market share   Market share   Market share
of third   of fourth   of fifth
entrant   entrant   entrant
(percent)   (percent)   (percent)

First   1.0   100
Second   0.73   58   42
Table III.   Third   0.61   43   31   26
Order of entry penalty in   Fourth   0.54   35   25   21   19
Rx drugs market   Fifth   0.48   30   22   18   16   14

Market share
Entry relative to the
order first entrant

Market share Market share of first of second entrant entrant (percent) (percent)

Market share   Market share   Market share
of third   of fourth   of fifth
entrant   entrant   entrant
(percent)   (percent)   (percent)

First   1.0   100
Second   0.65   61   39
Table IV.   Third   0.51   47   30   23
Order of entry penalty in   Fourth   0.42   39   25   20   15
OTC drugs market   Fifth   0.37   34   22   17   14   13

because of the nature of the product category – drugs – where the impact of advice of the experts – physicians – is large. Finally, the estimate for advertising/promotion directly to consumers is higher for OTC drugs category (þ0.31) than in the Rx drug category (þ0.12). This estimate, too, is consistent with expectations.

Most of the brand specific constants are statistically significant at 5 or 10 percent level. The fact that these brand specific constants are significant suggests that there are effects other than those specified in the model, i.e. there are effects other than those of price, advertising/promotion DTP and DTC, and the order-of-entry effect. However, the inclusion of brand-specific constants makes the parameter estimates of order-of-entry effect and the price and marketing efforts unbiased and reliable.

Discussion of managerial insights and future research

There are strategic implications from this study for both later entrants and first mover/entrants, i.e. pioneers. Based on the results of this study and other studies, it is reasonable to generalize that later entrants should plan on achieving lesser share than the pioneering brand if they enter the market with a parity product and parity marketing efforts. In Tables III and IV, the fifth brand market share potentials are reported to be as 13 (OTC drugs market) and 14 (Rx drugs market) share points if the firm offers equal product and marketing efforts at the level of the pioneer. In many cases, the fifth firm would not find it profitable to compete at the level of the pioneer who has almost 2.5 (OTC) – 2.0 (Rx) times as much market share.

For example, if the second entrant in the Rx drugs market desires to achieve parity market share with the first entrant, and the second firm desires to achieve this through increased direct advertising to physicians, then the second firm has to spend almost 1.5 times more than the first entrant. In many cases, this level of investment may not make the entry profitable for the second entrant. Further, if the advertising increases by the second entrant are (defensively) matched by the first entrant, the later entrant may never gain share parity with the pioneer.

As shown in theoretical and empirical studies (Urban et al., 1986), a preferred strategy for a later entrant may be to develop a superior product with either unique benefit features and/or a lower price (i.e. better positioning). When such a product is backed by aggressive marketing efforts, a higher share can be achieved. However, the pioneer should consider strategies to preempt this. The pioneer can minimize the later entrant’s threat by occupying the consumers’ preferred positioning space. However, if the pioneer does not carefully design its product, and an improved product is subsequently introduced and aggressively promoted by a competitor, the market share reward for innovation may be lost. The pioneer also should consider aggressively defending its brand with advertising and thereby preventing competition from gaining an advertising dominance. Pharmaceutical firms aiming at developing pioneering brands should be encouraged by the availability of a long run market share reward for their innovation. Although the pioneer’s share does decrease as each new firm enters, the pioneer retains a substantial share differential. However, creative product innovation and positioning remain central to a pioneer’s continued long-term market success.

The size of this reward depends upon the presence and strategies of later entrants. The values in Tables III and IV show the innovator’s market share in the Rx Gurumurthy Kalyanaram LawSuit

Effect in Rx and
OTC drugs

IJPHM 2,1

category (OTC category) dropping from 100 to about 58 (61) percent after the second brand enters, to 43 (47) percent after the third entrant, to 35 (39) percent after the fourth brand enters, and to 30 (34) percent after the fifth brand enters. Consistently, the market shares for the first entrant are higher by 3-5 points in the OTC drugs category than in the Rx drugs category.

Given the enormous implications for innovation and public policy, this topic of entry effect in the pharmaceutical drugs deserves serious attention from scholars and practitioners. In this effort, we identify at least two caveats and important directions of future research that can complement and expand the empirical results and managerial insights presented in this paper.

First, the number of categories used in this study is somewhat limited. We have three categories in the Rx drugs market and two categories in the OTC drug market. The concern about relatively smaller number of product categories is substantially alleviated by the robust number of brands in both the categories (14 in the prescription category and seven in the OTC category), and adequate time-series data (24 monthly data). However, an evident direction for future research is to replicate this study in larger number of product categories, and examine if the magnitudes of the entry effect change in the prescription and OTC drug markets.

Second, there are at least two other competitive dynamic elements that must be included in such empirical studies. These two elements are the timing of the expiry of patents and the number of generic brands. These elements are somewhat unique to the pharmaceutical drugs market. While the brand-specific constants make the current parameter estimates unbiased, the brand-specific constants do not provide useful empirical and managerial insights into the dynamics of the drugs market.

There are other evident fruitful directions for future research. One of them is a more sophisticated estimation methodology. We can, for example, estimate equation (1) using varying-parameter approach. In this methodology, the parameter estimates are dynamically and more flexibly estimated and therefore, the estimates would be theoretically superior. Another estimation methodology that could be productively employed is incorporation of heterogeneity in the parameter estimates, and, of course, this is a powerful approach that would produce unbiased estimates.

While it is likely that more sophisticated estimation methodologies would provide slightly better estimates, many empirical studies have shown the OLS estimates to be quite robust. The OLS estimates have been found to be within a few percentage points of the most precise estimates, and have also been directionally correct. Therefore, we are very confident of our empirical results.

We finally want to point to a few issues related to the data. An important distinction between the IMS and IRI data sources is that the IMS data reflect inventory stocking behavior by, for example, chain drugstore warehouses, while the IRI data include only actual sales to final consumers. To make the quantity units of the various OTC brands comparable to each other and comparable to the Rx brands, we had to normalize the data using the prescription dosage measures of the drug.

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