Competitive Entry and Pricing

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Review of Marketing Science

Volume 1 2003 Article 3

Competitive Entry and Pricing Responses to

Product Innovation

Barry Bayus

Pradeep Chintagunta

University of North Carolina, Chapel Hill, barry [email protected] of Chicago, [email protected]

Copyright c2003the authors. All rights reserved. No part of this publication may be reproduced,

stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical,

photocopying, recording, or otherwise, without the prior written permission of the publisher, be-

press, which has been given certain exclusive rights by the author. Review of Marketing Science

is produced by The Berkeley Electronic Press (bepress). http://www.bepress.com/romsjournal


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Competitive Entry and Pricing Responses to

Product Innovation

Barry Bayus and Pradeep Chintagunta

Abstract

In this paper, we study competitive response to a product innovation. We consider the dynamic

interaction between a Defender (a firm with a first generation product) and an Attacker (a

firm with a second generation product). The second generation product entry decision of theDefender, as well as the pricing decisions of both firms, are analyzed. Analytical results are

derived by developing a 3-period pricing game, and studying closed-loop policies for a Nash

equilibrium. These results allow us to identify strategies in which the Attacker can prevent (or

delay) a competitive response by the Defender. Some empirical support for our analytical results

is also provided by pricing data and information on the timing of successive product generation

introductions in the semiconductor and personal computer industries.

KEYWORDS: New Products, Pricing, Competition, Entry


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1. Introduction

Understanding the dynamic rivalry between firms is of great importance in the development ofstrategic and tactical plans (Porter 1980; MacMillan, et al. 1985; Chen, et al. 1992; Zhao 2003).A critical variable associated with organizational performance is the response time of a

competitor to a firms action (MacMillan and McCaffery 1982; MacMillan, et al. 1985). Forexample, predicting the response lag to a new product innovation (in the absence of patent protection or high investment requirements) is a key issue since it determines the monopoly period in which sufficient profits must be accumulated to justify the risks associated withdeveloping the new product. As discussed by Porter (1980), the ultimate effectiveness of anycompetitive action depends on whether or not there is a response, and if so, whether theresponse is delayed. A firm generally profits most by actions that prevent or delay a reaction.Preemptive strategies also are likely to lead to a competitive advantage (MacMillan 1983).Thus, knowing the conditions when a competitive action will go unchallenged is highlydesirable.

Descriptive theories of competitive response have been proposed in the strategic

management literature. For example, Porter (1980) provides an extensive discussion of entry barriers that can block competitive countermoves. MacMillan and McCaffery (1982) extendthese ideas by suggesting that other strategic and organizational reasons may also act to delay afirms reaction to a product innovation. Empirical investigations of the strategic andorganizational factors associated with competitive responses in the banking (MacMillan, et al.1985), electronics (Smith, et al. 1989), and the airline (Chen, et al. 1991; Chen and MacMillan1992) industries have been conducted. Marketing mix responses by oligopoly members to theentry of another firm have also been estimated (e.g., Gatignon, et al. 1989). More recently,analytical studies have considered the trade-offs between entry time, product performance, anddevelopment costs (e.g., Bayus, Jain, and Rao 1997; Zhao 2002).

However, generally absent from the literature are analytical studies that take anormative perspective of competitive response to product innovation. Although a fewanalytical efforts have investigated the new product entry timing decision, this research has notdirectly studied competitive response. For example, Wilson and Norton (1989) study themonopoly situation of when (if ever) a firm should introduce a new product designed to replaceits current product entry. Eliashberg and Jeuland (1986) investigate the impact ofexogenousentry by a competitor on dynamic pricing patterns. Bowman and Gatignon (1995) study thefactors related to a competitors response time to a new product introduction. Bayus, Jain, andRao (1997) consider the entry timing for two competitors that each can introduce a newproduct. Zhao (2002) studies the product introduction timing for an incumbent and entrant, butdoes not consider pricing strategies or multiple product generations. In addition, none of thisliterature considers the underlying buying behavior associated with durable products.

The purpose of this paper is to analytically study competitive response to a productinnovation. In contrast to the existing literature, our analysis begins at the point when acompetitor has already introduced a product innovation. We consider a two firm, two productgeneration situation in which a Defender currently offers a first generation product and anAttacker offers a second generation product. Key aspects of our model are: (1) competition(i.e., an Attacker has already introduced a next generation product), (2) the Defender firmsdecision of whether to introduce the second generation product, and (3) endogenous pricingover time for the first and second generation products of both firms. A dynamic model for

Bayus and Chintagunta: Competitive Entry and Pricing

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consumer sales of a second generation product (i.e., using new technology) is developed byincorporating the replacement behavior of a first generation product (i.e., which uses oldtechnology). Analytical results for this situation are derived by studying equilibrium closed-loop policies in a 3-period game. This model is used to determine conditions when theDefender responds to the Attacker by introducing a next generation product. These results also

allow us to identify the circumstances under which the Attacker can prevent (or delay) acompetitive response by the Defender.Although this paper complements some existing modeling efforts, we examine a

different competitive situation. We do not study the monopoly situation in which a single firmexpands its product line to include old and new technologies (e.g., as in Wilson and Norton1989; Moorthy and Png 1992, Fishman and Rob 2000). Nor do we study the case in which afirm is faced with a competitive entry into its current market (e.g., as in Hauser and Shugan1983; Eliashberg and Jeuland 1986; Gatignon, et al. 1997). And we do not study the diffusionof a single new technology among competing firms, including patent races amongcompetitors (e.g., as in Reinganum 1983; Fudenberg and Tirole 1985; Connor 1988; Ghemawat1991). Prima facie, our analysis appears to be related to the literature on disruptive

technologies (Bower and Christensen 1995). In that case, the Attackers product is initiallyinferior to that of the Defender. However, the improvement in both products over time is suchthat the Attackers product fulfills consumer needs at some point in the future whereas theDefender over provides quality at that point. Now consumers are willing to purchase theAttackers product. By contrast, we look at a situation in which the Attackers initial quality is,ceteris paribus, higher than that of the Defender.

The situation we study is representative of cases in which an incumbent firm is facedwith a rival firms introduction of a competing technology (sometimes it is a firm outside theestablished industry, called invisible competitors by Kodama 1992). Examples of firms thathave had to face the threat of a product innovation include piston aircraft engines (vs.turbojets), mechanical (vs. electric) typewriters, vacuum tubes (vs. transistors), discretetransistors (vs. integrated circuits), and traditional camera film processing (vs. electronicimaging). See Cooper and Schendel (1976) for other examples. The competition between Netscape and Microsoft in the Internet browser war is a well known setting with thesecharacteristics (e.g., Windrum 2001). Another example in the personal computer industry isthe IBM PC XT (based on Intels 8088 CPU technology) which was faced with the entry of theCompaq Deskpro personal computer (based on Intels more powerful 8086 CPU chip) in 1984(e.g., see Sultan 1989). In all these cases, predictions of the Defender firms likely responsesare expected to be a part of the strategic and tactical plans of the Attacker.

The remainder of this paper is organized as follows. In the next section, a 3-periodmodel for two competing firms is developed. In Section 3, closed-loop Nash equilibrium pricepatterns are determined and their consistency with empirical data from the personal computermarket is discussed. In Section 4, the entry decision of the Defender is analyzed and strategiesin which the Attacker can prevent a response are discussed. Information on the timing ofsuccessive technology introductions in the semiconductor and personal computer markets arealso used to lend empirical support to the analytical results. Implications and conclusions arediscussed in the final section.

2 Review of Marketing Science Vol. 1 [2003], Artic

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2. Model Formulation

Two firms are considered in our analysis, termed the Defender and the Attacker. In the basicmodel we consider three time periods: period 1 in which the Defender offers a first generation product and the Attacker introduces a second generation product; period 2 in which the

Defender introduces a second generation (resulting in three products on the market); and period3 in which the Defender phases out the first generation product, leaving only the two competingsecond generation products on the market. This 3-period model structure gives us theflexibility to examine alternative entry decisions for the Defender (e.g., no second generationproduct, a second generation product with immediate withdraw of its first generation product). Note that with respect to timing decisions, we will focus on the entry decision and not aspecific phase out strategy that might be implemented by the Defender. Considering anendogenous phase out and entry decision is a potential topic for future research.

Initially, we assume that there is an installed base of the first generation product. Forsimplicity, we further assume that the market potential for the product innovation is constantand is a function of the installed base (see Bayus 1992 for a discussion of these assumptions

and development of a monopoly model). This allows us to focus on the purchase behavior (i.e.,replacement and substitution behavior) for competing product generations. If a productinnovation expands the market, there is an even greater motivation for the Defender to respondwith a matching product entry. However, the qualitative nature of our findings will not beaffected. Of course, the market potential for a next generation product will depend on theproduct category, and may be larger or smaller than the installed base of an earlier generationproduct (e.g., see Norton and Bass 1992). A complete analysis of the effects associated with adynamic market potential are left for future research.

Finally, we do not consider any fixed costs associated with introducing a productinnovation. Since these costs are constant, a parallel and downward shift in the optimal profitpaths will occur as these costs increase. Of course, large fixed entry costs make it more likelythat the Defender will not introduce a next generation product.

2.1 The Demand Model

Figures 1 (a), (b) and (c) depict the key components of our model in each of the three timeperiods of interest. The model structure depends on the Defenders decision of whether to enterwith the new technology, and whether to phase out the product with old technology. Atany point in time, some proportion of the installed base of the first generation product will benormal replacements (i.e., households owning an older unit, and thus having a highreplacement probability under any circumstances, that replaced their first generation productwith a new unit); the remaining proportion (1-) are potential discretionary replacers (i.e.,households owning a first generation product that accelerate their replacement decision andpurchase a second generation unit in advance of the normal replacement decision)1.

1In general, the household durable replacement decision is related to the age of a currently owned unit, and thusaggregate replacements will be a function of the underlying age-based distribution of units in use. However, inorder to simplify the formulation, replacement demand is modeled as a constant proportion of the installed base(i.e., cumulative sales; see also Jeuland and Dolan 1982; Thepot 1988; Bayus 1992). Although this is a restrictiveassumption, empirical evidence suggests that this is a reasonable starting point.




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Figure 1(a)

The Model Structure for the 3-Period Game: Period 1

Installed Base

DiscretionaryReplacements

NormalReplacements

Do NotBuy

Buy SecondGeneration

FirstGeneration

Attacker Defender

(1-)

(1-f1) f1 (1-g1) g1




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Figure 1(b)


Installed Base


NormalReplacements

Do NotBuy

Buy SecondGeneration

FirstGeneration

Attacker Defender

(1-)

(1-f2) f2(1-g2)

g2

Defender

f2A

g2A

g2D

f2D




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Figure 1(c)


Installed Base


NormalReplacements

Do NotBuy

BuySecond

Generation

Attacker Defender

(1-)

(1-f3) f3

f3A (1-g3)

f3D

g3




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The number of consumers making a discretionary replacement is modeled using theusual diffusion process for a single product that has been studied by several researchers. Theseconsumers buy a second generation product because of some inherent preference for a nextgeneration product and its associated price point. A widely analyzed model of first time buyer(FTB) sales is the diffusion model in which demand is a function of the cumulative number of

adopters, x(t): dx/dt = (1-x/M)( + x/M), where M is the market potential that is assumed tobe constant, and and are the coefficients of external and internal influence (e.g., see thereview in Mahajan, et al. 1990). A related demand model in which the diffusion effect is afunction of the time since introduction is y(x,t) = dx/dt = (M-x) W(t) (e.g., see Jain and Rao1990 for a detailed discussion)2. In line with this literature, second generation product salesdue to discretionary replacements are modeled as a function of time since introduction.

The demand behavior we study in each of the three time periods is discussed next.Period 1 (see Figure 1a): Of the consumers facing a normal replacement decision,

some proportion g1 will purchase a second generation product from the Attacker; and theproportion (1-g1) will buy another first generation product from the Defender. We model thefraction g1 s a function of the price of the first generation product, q1, the second generation

product price for the Attacker, p1A

, and the intrinsic preferences for the first and secondgeneration products (the specific formulation is discussed later). Of the consumers that are potential discretionary replacers, some proportion f1 will purchase a second generation product from the Attacker. The fraction f1 is a function of the price of the Attackers secondgeneration product.

Period 2 (see Figure 1b): Of the fraction of consumers making a normalreplacement, a fraction g2 purchases the second generation product and the remainder (1-g2),buys the first generation product. Thus, g2 is a function of the prices of all three products (q2,p2

D, p2

A) on the market in period 2. The normal replacement sales of the second generation

product, g2 are divided into g2D and g2

A for the Defender and the Attacker, respectively. Thissplit depends upon the prices charged by the two firms for the second generation product. Ofthis, the sales accruing to the Defender and Attacker are f

2

D and f2

A, respectively.Period 3 (see Figure 1c): In this period, all normal replacements result in the

purchase of a second generation product. These sales are divided between the two firmsaccording to the proportion g3 (the fraction of consumers buying the Attackers secondgeneration product), which is a function of the second generation product prices for theDefender and Attacker, p3

D, and p3

A. The fraction f3 makes a discretionary replacement for a

second generation product, with this fraction depending upon the process of the Defender andAttacker. Of these discretionary replacements, f3

D go to the Defender and f3A to the Attacker.

The notation used to develop our analytical model is summarized below:Xt: Cumulative FTB sales of second generation product up to

period t = 1,2,3. (x0 = initial sales level)

Wt: Diffusion effect on discretionary replacement demand inperiod t = 1,2,3.

N: Initial installed base of first generation product.

2 Defining F(t) = [1-e-(+)t]/[1+(/)e-(+)t], which is the solution to the Bass-type diffusion model, sales at time tcan be calculated in discrete-time as [M-x(t-1)][F(t)-F(t-1)]/[1-F(t-1)]. Thus, W(t) is a function of F(t) and F(t-1),and dW(t)/dt > 0.




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: Proportion of the installed base of the first generationproduct that will make a normal replacement each period.

ptD: Second generation product price for Defender, t = 2,3.

ptA: Second generation product price for Attacker, t = 1,2,3.

qt: First generation product price for Defender, t = 1,2.

f1(p1A): Proportion of households making a discretionary

replacement that purchase a second generation product inperiod 1.

g1(p1A, q1): Proportion of households making a normal replacement

that purchase a second generation product in period 1.

f2(p2A, p2

D): Proportion of households making a discretionary

replacement that purchase a second generation product in period 2. Of these, f2

D buy from the Defender and f2A buy

from the Attacker (f2D

+ f2A

= f2).

g2(p2A, p2

D, q2): Proportion of households making a normal replacementthat purchase a second generation product in period 2. Ofthese, g2

Dbuy from the Defender and g2

Afrom the Attacker

(g2D + g2

A = g2).

f3(p

3

A, p3

D): Proportion of households making a discretionaryreplacement that purchase a second generation product in period 3. Of these, f3

Dpurchase from the Defender and f3

A

from the Attacker (f3D + f3

A =f3).

g3(p3A, p3

D): Share of second generation product sales by normal

replacement buyers for the Attacker in period 3.

k: Marginal cost of the first generation product.

cD,cA: Marginal cost of second generation product for Defenderand Attacker, respectively.

Second generation product sales in each of the three time periods are given by thefollowing equations.

x1 x0 = (N- x0) [(1-) W1f1 + g1)] (Period 1)

x2 x1 = (N- x1) [(1-) W2f2 + g2)] (Period 2)




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x3 x2 = (N- x2) [(1-) W3f3 + )] (Period 3)

where the subscripts refer to the time periods and W1, W2 and W3 are such that 0


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The proportion of households making a normal replacement that purchase a secondgeneration product in period 2 is

g2(p2A, p2

D,q2) = m + n(p2A+ p2

D) + oq2

where 0


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3A = (p3

A cA) (N- x2) [(1-) W3f3A + g3)]

Note that in order to isolate the impact of demand for the successive productgenerations on the entry decision and pricing policies, possible cost declines due to experiencecurve effects are not considered.

3. Dynamic Pricing Strategies

To derive optimal equilibrium prices for the 3-period game described in the previous section,the first-order conditions associated with the profit functions are solved via backward recursion(for brevity, details are not reported here). Although closed form expressions for the closed-loop Nash equilibrium prices can be obtained, it is analytically impossible to establish anyrelationship between qt, pt

D and ptA. Therefore, we examine the nature of the price paths

numerically over a wide range of parameter values that are feasible4.In Figure 2, the nature of the equilibrium price paths for a typical situation from the

numerical analysis is diagrammed5. Note that the period 1 price for the first generation product

(q1) can also be between p1D

and p1A

. However, even in this case q2 is generally below p2D

andp2A.

Thus, we obtain the following (see also Figure 2).

Result 1

The price paths for both old and new technology products decline over time.

Result 2

The Attacker responds to a competitive product entry with a sharp drop in its price.

Result 1 extends the findings reports in Bayus (1992) for a monopoly situation, and Result 2extends the findings reported in Eliashberg and Jeuland (1986) for exogenous product entry.

4Recall that the parameters , , a, , , m and are bounded between 0 and 1 by definition. For these parameters

we examined values in the range [0.10, 0.90] at intervals of 0.05. Values below 0.1 and above 0.9 couldpotentially result in shares that fall below zero and exceed one in magnitude and are, therefore, not included in the

analysis. The parameters , , b, n, -o and are all bounded from above the zero. In choosing values for theseparameters, it was important not to violate the [0,1] range for the share numbers of the linear probability rules.Accordingly, for these parameters the ranges examined were [-1.4, -0.6] for b, , n, and , and [1, 2.8] for o,again in increments of 0.05. Finally, using the same considerations (and the empirical finds in Bayus 1992), the parameter was varied in the range [0.05, 0.50]. For the cost parameters, the following (fixed) values were chosen:cD = cA = 0.2. For k, we analyzed values in the range 0


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Figure 2

Equilibrium Price Patterns

Intuitively, our results may be explained by interpreting the market as consisting of twosegments: the normal replacers and the discretionary replacers. While the Attackersupplies both segments, the Defender competes only in the normal replacer segment. If theAttacker could price discriminate, it would charge the monopoly price to discretionaryreplacers and the competitive price to normal replacers in period 1. As this is not possible,the Attacker sets an intermediate price to the market. Clearly, this price would exceed theDefenders first period competitive price (even when marginal costs for both generation products are identical). In period 2, the Defender introduces the second generation product.The attacker no longer enjoys monopoly power in the discretionary replacer segment and,consequently, has to drop prices to competitive levels. Further, the new product introductionalso increases competition for consumers in the normal replacer segment as these consumerscan now choose from among three product offerings. Hence, the Defender has to drop the priceof its first generation product along with introducing the new technology product. Finally, phasing out the first generation product by the Defender in period 3 eases the competitivepressure in the normal replacer segment and precludes any sharp price declines. However,

1 2 3

Time Period

PriceAttacker(2

ndGeneration)

Defender(2nd Generation)

Defender

(1st Generation)




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prices continue to decline due to the diffusion effect6.These intuitive explanations notwithstanding, are these dynamic pricing strategies

consistent with actual firm behaviors? Unfortunately, identifying appropriate data whichexactly matches the model structure and parameters considered is extremely difficult. To provide some empirical support these results however, the historically implemented pricing

strategies of two, large competitors (IBM and Compaq) for their various competing personalcomputer models were statistically analyzed. We note that this industry has two keycharacteristics which do correspond to the analytical model: (1) the product is a durable goodwhich involves overlapping technological advancements (and thus discretionary and normalreplacements are important), and (2) two firms with relatively large market shares (IBM with a1990 market share of around 17% and Compaq with a market share of almost 5%) competewith the same Intel microprocessor technology (and thus a duopoly is a reasonable structure toconsider for the time period we analyze). Although the specific features and options of personal computer models can vary considerably, industry analysts generally agree that themicroprocessor in a machine determines its computing power. Thus, we identify technologygenerations based on the installed CPU chip (see also Bayus 1998).

Unit sales and average prices over the period 1984-1990 for models in the IBM PS/2and Compaq Deskpro lines were obtained from the International Data Corporation ProcessorInstallation Census (see also Bayus 1998). These two personal product lines are directcompetitors (Johnson and Radding 1992), sales of each product model follow the usual lifecycle pattern (sales are initially small, increasing to a peck, and then declining), and IBMdominates Compaq in sales for each period. Further, for each product generation IBM is theDefender and Compaq is the Attacker. For example, the IBM XT (with an 8088 CPU) wasavailable a year before Compaqs first product entry using Intels new X86 CPU technology.In 1984, Compaq entered with a DeskPro PC (with the faster 8086 CPU). IBM eventuallyintroduced its PS/2 Model 30 (with an 8086 CPU) in 1987.

Figure 3 shows the average prices of the IBM XT (the Defenders first generationproduct), the IBM PS/2 Model 30 (the Defenders next generation product), and the CompaqDeskpro 8086 (the Attackers next generation product). Consistent with Result 1, the first andsecond generation product prices of IBM and Compaq are declining over time. In addition, theAttacker (Compaq) sharply drops its price when the Defender (IBM) enters with a competingproduct (see Compaqs price pattern between 1986-1987) which is consistent with Result 2.

As estimate of the effects of a competitive product entry on prices was also obtained byusing the Compaq price data (PRICE) across three CPU technology generations (8086, 286,386). Defining the following dummy variables:

ENTRY= 1 when IBM enters with a competing product (0 otherwise)

G1 = 1 if PC uses 8086 CPU (0 otherwise)

6 Detailed comparative statics analyses of the various model parameters on equilibrium prices are not reportedhere. Generally speaking, changes in the intrinsic preference or price sensitivity parameters result in intuitivemovements in the absolute price values. Importantly, the dynamic patterns discussed in this section are notaffected.




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Figure 3

Selected PC Prices

0

1

2

3

4

5

6

7

1983 1984 1985 1986 1987 1988 1989 1990

YEAR

AveragePrice($000)


and using OLS, the following regression results are obtained (t-statistics in parentheses):

PRICE= 7859.11 463.28ENTRY 3173.69 G1 2590.36 G2 502.34 TIME(-1.96) (-11.63) (-9.49) (-8.47)

R2=0.97 F=80.33 (p=0.00)

Here, TIMEis a time trend variable (e.g., 1,2,3,within each product generation)7.

As indicated by the high R2 value and significant F-value, this model provides a verygood fit to Compaqs implemented pricing policies. All coefficients are statistically significantat the 0.05 level. As expected, the coefficients ofG1 and G2 are negative, indicating that the base price of successive product generations increases. Consistent with Result 1, the

coefficient of the TIMEis negative, suggesting that prices decline over time. However, we notethat this result might also be due to cost declines associated with experience effects. Given thelimited data available, these two complementary effects cannot be empirically separated. Mostimportant is the finding that the coefficient ofENTRYis negative and statistically significant.This implies that a competitive product entry is met with a decrease in prices. This providessupport for Result 2.

7 The regression results also hold for other simple formulations such as a quadratic time trend variable.

Attacker

(Compaq 8086)

Defender(IBM 8088)

Defender(IBM 8086)




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4. The Product Entry Response

To investigate the Defenders entry decision, we examine the complete model structure inwhich the Defender introduces a second generation product in period 2 and phases out its firstgeneration product by period 3, along with two other scenarios:

i). The Defender does not introduce a second generation product in any of the threetime periods; and

ii). The Defender introduces a second generation product in period 2, butimmediately withdraws its first generation product.

A comparison of the total profits accrued over the three time periods from each of thethree scenarios will enable the Defender to decide whether or not to introduce the nextgeneration product in period 2, and also whether to immediately withdraw its first generationproduct or phase it out. Since out results indicate that the Defender never maximizes profit by

immediately withdrawing its first generation product (profits under the complete modelstructure dominate those when the Defender only competes with a second generation product),we only discuss the phase out scenario (i.e., the next generation product is introduced) withthe no introduction strategy.

Our analyses generally indicate that the Defender maximizes profits by introducing thenext generation product. However, there are four conditions when the Defender does notintroduce a next generation product.

Result 3

The Defender does not respond if the market is preempted by the Attacker.

Large values of the intrinsic propensity for a discretionary replacement () and smallvalues of the price sensitivity for discretionary replacements () are associated with theDefender not introducing the next generation product. Since both of these parameters involvediscretionary replacements in period 1, the Attacker may be able to steal the market if the

new product is truly superior (either due to product technology, represented as large values of,

or due to lower price, represented as small values of) to the first generation product.

Result 4

The Defender does not respond when the threat posed by the Attackers product innovationis small.

The Defender does not introduce the nest generation product when the intrinsic propensity for a normal replacement () and the intrinsic propensity for a discretionaryreplacement in periods 2 or 3 (a) are small. Thus, if the new product does not offer anadvantage compared to the existing first generation product, the Defender finds that it isoptimal to keep its monopoly of the old product. If households are sensitive to the price ofthe new product (represented as large values of b and ), it is not profitable for the Defender tointroduce a next generation product.




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Result 5

The Defender does not respond if the Attacker establishes a large pioneering advantage.

Large values of the intrinsic preference for the Attackers next generation product over

the Defenders () are associated with the Defender not introducing the new product. Since the

parameter involves period 3 normal replacements where all buyers must decide between theAttacker and the Defender, a pioneering advantage by the Attacker results in an unattractiveentry proposition for the Defender.

Result 6

The Defender does not respond if there is a large base of customers for the first generationproduct.

Large values of the normal replacement proportion () are associated with theDefender not introducing a next generation product. When a relatively high proportion ofhouseholds make a replacement, the Defender maximizes profits by maintaining its monopoly

of the first generation product.Results 3 through 6 give the general conditions when a product innovation will gounchallenged by an incumbent. But, are these results consistent with actual firm behaviors? To provide empirical support for some of these results, we have assembled information on thetiming of entry for successive product technologies in the semiconductor and personalcomputer industries.

Table 1 contains the introduction dates of various competing IBM and Compaq personalcomputers discussed in the pricing section. This table also reports the calculated time betweenCompaqs introduction of a next generation product and IBMs subsequent introduction of acompeting product. Across four technology generations IBM always enters with a nextgeneration product, albeit several months after Compaqs product introduction. With each

advance in technology, IBMs response time decreases. Although several considerations(including production constraints, software and component availability, and internal politics)certainly influenced the specific launch time of the PS/2 product line, the information in Table1 is consistent with Results 4 and 6. As noted previously, Compaq did not initially preemptIBM for any product generation (i.e., the Attacker did not preempt the market due to a drasticinnovation) since sales for each next generation product were relatively small. In addition,Compaq (even though it beat IBM to market in several technologies) did not have a superiorityover IBM in market share, distribution, or advertising (i.e. the Attacker did not gain apioneering advantage). What is true however, is that IBM believed it was not too critical to befirst in the market with the next generation technology (Hooper 1992). IBM also consistentlyunderestimated the industry demand for personal computers. This suggests that IBM did not see

too much of a threat for successive personal computer technologies. In addition, IBM had thedominant market share position (and thus a relatively large customer base) in the previousproduct technology.




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Table 1

Entry Timing in the Personal Computer Industry

8086(available June 1978)

286(available February 1982)

386(available October 198

Compaq

(The Attacker)

June 1984 April 1985 September 1986

IBM

(The Defender)

April 1987 April 1987 June 1988

Difference

(in months)

34 24 21



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Further statistical estimation was conducted using data from International DataCorporation on 29 of the largest manufacturers and across four CPU technology generations(8088, 286, 386, 486). A proxy for response time ( RESPONSE TIME) was constructed bycalculating the time (in months) between the date at which a CPU technology was available and

the date that product technology was first introduced by each manufacturer. The first productentry by each firm was excluded from the analysis since variables outside the scope of this paper may explain market entry by a firm. Using the same technology generation dummyvariables defined earlier, and defining



SHARE= manufacturer market share in the year before its product entry,

the following OLS regression results are obtained (t-statistics in parentheses):

RESPONSE= 67.79 - 0.27 SHARE- 18.63 G2 - 39.08 G3 - 54.71 G4

TIME (-0.69) (-3.18) (-7.08) (-9.42)

R2=0.68 F=30.81 (p=0.00)

Here, SHAREis used to represent the relative size of the existing customer base of a previousproduct technology.

As indicated by the large R2

value and significant F-value, this model provides a very

good fit to the actual response times for this set of personal computer manufacturers. Thecoefficients of the technology generation dummy variables are negative and statisticallysignificant at better than the 0.05 level. These coefficients indicate that quicker response timesare associated with each successive product generation. Consistent with Result 4, this findingsuggests that more advanced technology (i.e., faster processing speed) poses a greater threat to previous generation products. The coefficient associated with SHARE is insignificant,suggesting that the customer base of a previous product generation does not affect responsetime. One possible explanation for this finding is that market share may capture aspects of twoopposite effects: the "pioneering advantage" described in Result 5 (e.g., firms with smallmarket shares take longer to respond since the larger share companies are more likely to haveintrinsic advantages) and the "customer base of first generation product" described in Result 6

(e.g., firms with small market share respond quickly since the larger share companies prefer notto cannibalize their current customer base). Unfortunately, the limited data which are availabledoes not allow us to empirically separate these effects.

However, empirical support for Result 6 comes from a related industry---semiconductors. Table 2 reports the world market share rankings of the leading U.S.manufacturers of semiconductors (see Soukup and Cooper 1983; Dorfman 1987). These dataimply that firms with large market shares in one technology tended to respond slowly (if at all)to newer technologies. For example, the vacuum tube companies generally underestimated the




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threat of transistors, and before they could recover, new entrants had gained a strong foothold.It was not until 1959 that the sales value of semiconductors exceed that of receiving tubes.Even then, receiving tubes remained more than a $300 million a year business. A robustreplacement market also meant that sales did not fall off drastically until the 1970's (Dorfman1987). Thus, consistent with Result 6, the large existing customer base of tube manufacturers

gave them little incentive to pursue newer technologies.

5. Discussion and Conclusions

The purpose of this paper has been to analytically identify conditions when the introduction ofa product innovation will go unchallenged. As extensively discussed in the strategicmanagement literature, we assume that a firm profits most by actions that prevent or delay areaction. We have considered the situation in which an established firm is faced with thecompetitive entry of a next generation product. Our model and analyses incorporatecompetition (an Attacker has already introduced a second generation product), the Defender'sdecision of whether to introduce the second generation product, and endogenous pricing over

time for the competitors and two product generations. The dynamic model for sales of thesecond generation product includes replacement behavior associated with the first generation product. Analytical results are derived by studying equilibrium closed-loop policies in a 3- period game. The pricing and product entry results are also shown to be consistent withimplemented firm decisions in the personal computer and semiconductor industries.

Several of our results merit further discussion. For the situation we study, price is notused as a weapon to delay a competitive response. As shown in Figure 2, prices of the productinnovation generally start high and decrease over time (i.e., a "skimming" policy is followed).This declining price pattern results from our demand model (i.e., we assume an installed baseof the first generation product, and sales come from replacements).

It is not surprising that our analyses indicate that the Defender usually maximizes

profits by responding with a competitive product entry. More interesting is that there are fouranalytically derived conditions in which the Defender maximizes profits by not challenging theproduct innovation. These conditions suggest approaches that an Attacker might use to prevent(or delay) a competitive response. One strategy is to preempt the market with a "breakthrough"product. On the other hand, an "incremental" strategy in which the initial product entry does not pose a strong threat (at least as perceived by the incumbent firms) to the existing producttechnology is viable. Interestingly, U. S. companies seem to follow the breakthrough approachto product development and the Japanese tend to use the incremental strategy (Gomory 1989).Despite the fact that revolutionary products can dramatically improve a company's profitability,it seems that the Japanese approach has been very successful (Rosenberg and Steinmueller1988).

Other possible strategies in which an Attacker can prevent a competitive responseinclude entering markets where the Defender has a large customer base in the previous producttechnology, and establishing a foothold in the new market quickly (due to the pioneeringadvantage) making it unattractive for a competitor to respond. Incumbent firms are generallyreluctant to respond to a product innovation if it would mean cannibalizing an existing profitable product. Several firms in the computer industry have had to face this difficultproblem recently. Finally, there is a large literature discussing the advantages associated withpioneering (e.g., see the review in Kerin et al. 1992).




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Table 2

Leading U.S.Semiconductor Manufacturers Ranked by Share of World Market(Source: Dorfman 1987)

Transistors Semiconductors Integrated CircuitsCOMPANY Tubes (1955) (1965) (1975)

RCA 1 7 6 8Sylvania 2 4G E 3 6 5Raytheon 4 10Westinghouse 5 8Amperex 6 National Video 7Ranland 8Eimac 9Landsdale Tube 10

Hughes 1Transitron 2 9Philco 3 8Texas Instruments 5 1 1Motorola 9 2 5Clevite 10

Fairchild 3 2General Instrument 4 7Sprague 7

National Semiconductor 3Intel 4Rockwell 6Signetics 9American Microsystems 10




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In our model formulation, several assumptions have been made which representavenues for future research. Two potential topics are briefly outlined here. So as to simplify ouranalysis, we have only indirectly addressed the strategies an Attacker can use to prevent (ordelay) a competitive response. Besides price, the model can be extended to directly consider theAttackers other marketing mix decisions. For example, advertising expenditures can be

modeled as affecting the intrinsic propensities to buy from the Attacker (and in particular, the period 3 parameters). The tradeoff between costs and obtaining a pioneering advantage canthen be studied more closely. In addition, product development efforts of the Attacker can bedirect1y incorporated into the model. In this way, the Attacker's decision of the productinnovation "level" can be direct1y studied (e.g., should the Attacker introduce a productdesigned to preempt the market, or a product that does not pose a threat to the Defender?).

Finally, another relevant and interesting direction for future research is to model thesituation in which the Defender can respond to a product innovation by improving its firstgeneration product (instead of only introducing a second generation product). In fact, thedevelopment of "hybrid" or "bridging" technologies has been widely used by firms faced withthe competitive entry of a new technology. For example, Kodak initially took this approach to

the threat of electronic imaging technology (Mossberg 1991). See Tang (1988) for some initialsteps in this direction.

6. Colophon

Barry L. BayusKenan-Flagler Business SchoolUniversity of North CarolinaChapel Hill, NC 27599(919)[email protected]

Pradeep ChintaguntaGraduate School of BusinessUniversity of Chicago1101 East 58th StreetChicago, IL 60637(773)[email protected]




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