The Financial Rewards of New Product Introductions in the Personal Computer Industry
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The Financial Rewards of New Product
Introductions in the Personal
Computer Industry
Barry L. Bayus • Gary Erickson • Robert Jacobson
Kenan-Flagler Business School, University of North Carolina, Chapel Hill, North Carolina 27599
School of Business, Box 353200, University of Washington, Seattle, Washington 98195
School of Business, Box 353200, University of Washington, Seattle, Washington 98195
barry_bayus@unc.edu • erick@u.washington.edu • yusho@u.washington.edu
B ased on data from firms in the personal computer industry, we study the effect of new
product introductions on three key drivers of firm value: profit rate, profit-rate persis-
tence, and firm size as reflected in asset growth. Consistent with our theoretical development,
we find that new product introductions influence profit rate and size; however, we find no
effect on profit-rate persistence. Interestingly, we also find that the effect of new product
introductions on profit rate stems from a reduction in selling and general administrative
expenditure intensity rather than through an increase in gross operating return. Notably,
firms decrease their advertising intensity in the wake of a new product introduction. Firm
profitability in this industry apparently benefits from new product introductions because
new products need less marketing support than older products.
(New Product Introductions; Firm Value; Personal Computer Industry; Empirical Analysis)
1. Introduction announcement. Subsequent event studies looking at
Academics, practitioners, and consultants share the the stock market reaction to information associated
belief that new products are important to the long- with new product announcements reinforce this find-
term financial success of a firm. For example, based ing of a positive stock market reaction to new prod-
on results from an annual innovation poll by Fortune ucts (e.g., Koku et al. 1997).
magazine, consultants at Arthur D. Little claim that How new products influence firm value, however, is
innovative companies achieve the highest shareholder less clear. While advantageous in isolating an impact
returns (Jonash and Sommerlatte 1999). Cooper (1998) on firm value, event studies are limited in their abil-
states that new products are vital to the success ity to explain why the effect occurs, i.e., event-study
and continued prosperity of the corporation. Drucker analysis does not address what mechanisms or under-
(1999) maintains that, in the era of “profound transi- lying drivers are influenced by new products. Fur-
tion” that we are entering, only organizations with a ther, previous research studies provide few, and often
systematic policy of innovation are likely to succeed. contradictory, insights concerning how new products
These views are consistent with empirical event- influence the underlying drivers of firm performance.
study research that has found a positive associa- Consequently, our understanding of the effects of new
tion between new product announcements and stock product introductions on the financial rewards of a
return. For example, Chaney et al. (1991) find an aver- firm is very much incomplete.
age daily excess return of 0.25% for new product The argument that new product activity enhances
announcements one day before to one day after the firm value rests on the basic idea that new products
0025-1909/03/4902/0197$5.00 Management Science © 2003 INFORMS
1526-5501 electronic ISSN Vol. 49, No. 2, February 2003 pp. 197–210BAYUS, ERICKSON, AND JACOBSON
The Financial Rewards of New Product Introductions
provide transitory advantages that allow firms to considerations. For example, the effect of profit rate
obtain private (as opposed to public) returns to inno- on market value is accentuated for larger firms and
vation (e.g., Arrow 1962). In the absence of this firms that are growing. This effect is positive for firms
effect, firms would have no incentive to undertake the with profit rates greater than the cost of capital, and
risky investment required for new product develop- negative for firms with profit rates less than the cost
ment and market introduction. Innovating firms can of capital (e.g., McTaggert et al. 1994). Profit-rate per-
take advantage of this transitory advantage via sev- sistence has a similar interactive effect. Higher persis-
eral mechanisms. First, new products incorporating tence results in long-term gains (losses) for firms with
advanced features and capabilities can lead to higher positive (negative) profit rate less cost of capital dif-
sales and firm growth. Second, firms may attempt to ferentials (Kormendi and Lipe 1987, Levonian 1994).
enhance their profits by targeting segments that yield We empirically examine the effect of new product
high margins. Third, new products can allow a firm to introductions on these three key drivers of firm value.
lower its costs by targeting its current customers with We further examine the relationship between new
“new and improved” products instead of having to product introductions and the components of firm
incur the expenses related to finding new customers profitability (gross operating income, selling, general,
for its existing, older products. Fourth, new products and administrative (SG&A) expenditures, and com-
may transform the firm’s capabilities and allow prof- ponents of SG&A). These analyses allow us to gain
its to persist over a longer period of time. insights into how new products influence firm value.
These mechanisms suggest that the study of inno- The context for our study is the personal computer
vation effects (e.g., new product introductions) on (PC) industry, a technologically dynamic market in
firm value requires and provides interdisciplinary which new products have played a critical role in con-
insights. Innovation is not an isolated activity of the tinued industry growth. Consistent with our theoreti-
firm. Rather, it is interrelated with the other busi- cal development, we find that new product introduc-
ness functions—in particular, marketing. These mech- tions in this industry influence profit-rate and firm
anisms also suggest that innovation can influence a size. We find no effect on profit-rate persistence. Our
number of different performance outcomes. As such, empirical results further indicate that the effect of
understanding the effect innovation has on business new product introductions on profit rate stems from a
performance requires assessing its effect on different reduction in SG&A expenditures, most notably adver-
drivers of financial valuation. tising intensity, rather than through an increase in
Financial valuation models differ in their empha- gross operating income.
sis on different considerations, but typically share
common assumptions that lead to similar implica-
tions with respect to key drivers of the stock mar-
ket valuation of firms. Consistently, three key drivers
2. New Product Introductions and
of firm performance emerge from financial valuation Firm Financial Performance
models—profit rate (i.e., size-adjusted earnings), the To gain insight into the underlying mechanisms that
persistence of profit rate (i.e., the length of time that link new product introductions to changes in firm
a firm’s advantage or disadvantage in the market value, in this section we consider how new prod-
place exists, which is commonly captured by the time- uct activity (i.e., the number of new products a firm
series properties of profit rate), and the size of the introduces in a year) might influence the key finan-
firm (i.e., assets). Profit rates are a primary compo- cial drivers of firm value (i.e., profit rate, profit-rate
nent of all valuation models as a firm’s profit rate persistence, and size).
has a direct effect on its market value. That is, all
else being equal, the greater the firm’s profit rate, the 2.1. Firm Profits
greater the firm’s stock market value. The effect of In line with conventional wisdom, we hypothesize
profit rate on valuation, however, depends on other that:
198 Management Science/Vol. 49, No. 2, February 2003BAYUS, ERICKSON, AND JACOBSON
The Financial Rewards of New Product Introductions
Hypothesis 1. Firm profit rate is positively related to While much of the discussion associated with
its new product activity. the effect of new product introductions on profit
rates focuses on gross operating return (i.e., [revenue
Empirically, the work of Geroski et al. (1993) is per-
minus cost of goods sold]/assets), other components
haps most directly related to this hypothesis. In a
of profit also might be influenced. New product intro-
study of product, process, and material innovations
ductions do not occur in isolation, but rather interact
introduced by manufacturers in the United Kingdom
with other activities of the firm, in particular, mar-
from 1945–1983, they find a significant (but what
keting. As such, the effect of new product introduc-
they label as “modest”) positive effect of innovation tions on profits will depend on interrelationships with
on profit margins. A concern, however, which the these other activities whose costs are part of SG&A
authors note, is that commercial success is one of expenditures.
the criteria used to select innovations for their study; One possibility is that SG&A expenditures will
i.e., their data contain only successful innovations. increase because the new product requires additional
Because sample bias is present in their study, the support (e.g., increased advertising) or development
reported results may overstate the true effects of new efforts (e.g., increased R&D). Indeed, the marketing
products on profit rate. literature highlights new product introductions as
Support for this hypothesis might also come from an action requiring increased advertising. Bly (1993,
previous research examining the effect of variables p. 125), for example, notes that “introducing many
such as R&D expenditures and patent activity that are new products to the market dramatically increases
expected to be correlated with new product introduc- your advertising expenditures. In fact, the new prod-
tions. But here we find weak or conflicting evidence. uct innovator will spend more than twice as much on
While a number of studies have reported surpris- advertising and promotion as a business with fewer
ingly large estimated effects of R&D (e.g., Pakes 1985), new products.” Thus, the prevailing view is that it is
others question its size, and report effects consis- necessary to invest heavily in advertising during the
tent with normal returns (e.g., Erickson and Jacobson initial stages of a product introduction and that this
1992). And, even though patent statistics are thought front-end commitment tends to dissipate initial stage
to be closely related to innovation, studies consis- profits.
tently find that patent counts are not associated with While less widely articulated, a competing view
financial performance (e.g., Griliches et al. 1991). about the interrelationship between new products
Although the hypothesis of a positive association and SG&A activity also exists. Under this view, new
between profit rates and new product introductions products may be less costly to market than exist-
is widely presumed, the lack of any strong and direct ing products. Thus, it is products that lag behind
empirical support in the published literature raises the technology frontier or that fail to offer an obvi-
important questions. For example, the costs associated ous reason for purchase that require more intensive
with new product introductions may outweigh any demand-creating marketing activities. Angell (2000),
increase in sales revenues. Consistent with this idea, in the context of pharmaceuticals, takes an even more
Bayus and Putsis (1999) find that personal computer extreme position. She contends that “the less impor-
firms with longer product lines have higher costs as tant the drug, the more marketing it takes to sell it.
well as higher market share. Indeed, their results indi- Important new drugs do not need much promotion.
cate that the cost increases associated with a broader Me-too drugs do” (p. 1903). Further, the new prod-
product line and new product introductions dominate uct can be targeted to current customers, instead of
any potential demand increases in this industry. Con- having to find new customers for the existing prod-
sequently, to understand more fully the relationship ucts. In this case, more efficient use could be made of
of new product introductions and firm profitability, advertising and selling resources; e.g., less advertis-
a closer examination of the components of firm prof- ing and personal selling resources may be needed to
itability is warranted. reach target sales levels for new products.
Management Science/Vol. 49, No. 2, February 2003 199BAYUS, ERICKSON, AND JACOBSON
The Financial Rewards of New Product Introductions
Only by empirically studying the effect of new is modeled as time invariant and the role of other
product introductions on the components of profit potential firm-specific effects are not captured in
rate can we gain insights into these possible phenom- the model—suggest that the issue be more closely
ena. To our knowledge, these issues have not been examined.
explored in the published literature.
2.3. Firm Size
2.2. The Persistence of Firm Profits Consistent with the widespread viewpoint, we
Our working hypothesis concerning the persistence of hypothesize that:
firm profit rate is Hypothesis 3. Growth of firm size, as reflected in asset
Hypothesis 2. The persistence of firm profit rate is growth, is positively related to its new product activity.
positively related to its new product activity. This hypothesis is consistent with Sutton’s (1998) the-
Geroski et al. (1993) note that there are two schools ory of endogenous sunk costs (e.g., R&D expenditures
of thought regarding how an innovation can con- and the resulting new product introductions), in that
tribute to a firm’s superior performance. An inno- a firm can grow in size as it reinvests its profits into
vation contributes either by being the “product of the development of future new products. Further, even
the innovation process” that temporarily enhances though new product introductions may lead to a com-
a firm’s market position, or by the “process of petitive advantage, this may not directly show up as
innovation” that allows profit to persist because a higher profit rate for the firm. The firm may plow
it transforms the firm’s internal capabilities. Both back its profits into expenditures anticipated to influ-
mechanisms are consistent with this hypothesis. The ence longer-term profits or make use of its advantage by
profitability of an innovating firm may exhibit greater increasing market share. In agreement with this, Bayus
and Putsis (1999) find that market share is positively
persistence because the firm does not introduce just
related to firm product line length in the PC industry.
one new product but continues to introduce new
While we strongly expect new product introductions
products over time and, as such, reduces imitation
to be positively associated with firm growth, we are
by competitors. Further, to the extent that innovation
unaware of past research documenting this result.
transforms a firm’s capabilities, this creates an asset
that competitors may find difficult to imitate.
However, past research has rarely investigated, and 3. The Personal Computer Industry
thus has yet to produce consistent results regarding, The empirical setting for our study is the PC industry.
the possible effects of new product introductions on A PC can be defined as a general purpose, single-
the persistence of firm profit rates. Roberts (1999) user machine that is microprocessor based and can be
investigates the issue, but reports findings that we programmed in a high-level language. The historical
are cautious to build upon. His study looks at the reviews by Langlois (1992) and Steffens (1994) suggest
effect of the relative proportion, which is assumed to that the PC industry is a rich and dynamic setting in
be fixed across time, of sales derived from innova- which to study how new product introductions influ-
tive products on the persistence of profits for firms in ence firm value. Many, but not all, firms were active in
the pharmaceutical industry. He finds that this inno- introducing new products, and products based on old
vation measure is positive and significantly related and new technology were in the market contempora-
to profit persistence for firms with previous period’s neously throughout this period. Frequent new prod-
profits below the mean, but is insignificant for firms uct introductions, ease of firm entry and exit, and the
with previous period’s profits above the mean. These inability by any single firm to establish a long-term
results are somewhat surprising in that they imply competitive advantage are prominent features of this
that innovative activity lengthens the time period industry.
for negative returns, but not for positive returns. As shown in Figure 1, the PC industry has wit-
Some methodological concerns—firm innovativeness nessed rapid growth since its inception in 1974. PC
200 Management Science/Vol. 49, No. 2, February 2003BAYUS, ERICKSON, AND JACOBSON
The Financial Rewards of New Product Introductions
Figure 1 The U.S. Personal Computer Industry, 1974–1994 Figure 2 Marketing Activities in the U.S. Personal Computer Industry
20 1200
18
16 1000
14 Average Price (x10)
12 800
Dollars
10
Unit Sales (x106) 600
8 Total Advertising
Expenditures (x106)
6 400
4
New Product
2 Introductions (x102) 200
0
1974 1978 1982 1986 1990 1994 0
Year 1976 1979 1982 1985 1988 1991 1994
Source. IDC Processor Installation Census. Year
Source. Average price is from the IDC Processor Installation Census; Total
advertising expenditures are from Leading National Advertising Ad$ Sum-
unit sales grew from under 500,000 units in 1980 to mary reports for B311: Computers & data processing equipment.
over 18 million units in 1994. Both hardware and soft-
ware technology has improved substantially over this
period. For example, the microprocessors1 used in the technological sophistication. As distribution channels
first-generation personal computers (e.g., Intel’s 8080 and served-customer segments expanded over time,
and Zilog’s Z80) have been continuously superseded firm marketing activities included the development
by later technology generations (e.g., Intel’s 80286, and implementation of integrated and coordinated
80386, 80486, Pentium). Each new microprocessor is marketing campaigns as well as corporate image pro-
associated with increased processing speed, enabling grams (Steffens 1994). Figure 2 shows that the adver-
the development and use of more sophisticated oper- tising expenditures for computers increased during
ating systems, graphics, and application packages. the early 1980s and were relatively stable through the
Not surprisingly, the proliferation of advanced tech- 1990s.2 Steffens (1994) appropriately sums up the mar-
nology has encouraged frequent new product intro- keting situation for firms in this industry:
ductions in this industry (see Figure 1).
For whilst it is accepted that “brand name” in some
While it is apparent that technology advances and market sectors that are heavily price dependent will
new product introductions continue to be a driv- count for little, it still remains true to say that in his-
ing force in the PC industry, firm success is also torical terms, as the market for personal computers
heavily dependent on its marketing activities (e.g., continues to segment across an increasingly complex
Steffens 1994). As shown in Figure 2, prices dra- range of customer groups, it is important for competi-
tors and entrants to recognize that having a “brand
matically declined over the first eight years in this
name” in general purpose computers or indeed even
industry due to the continuous downward cost tra- in general purpose personal computers, will not be
jectory of critical components such as memory chips sufficient to guarantee an effective brand presence in
and hard disk drives (e.g., Curry and Kenney 1999). another market segment. (p. 257)
More recently, average prices have been relatively
Thus, it is evident that firms undertake substantial
stable as products have been enhanced with greater
investments in advertising in this industry.
1
As discussed in Steffens (1994), the most parsimonious way to
2
describe the technology generations of personal computers is to Although these advertising expenditure data are for all computers
compare their microprocessors or CPUs (central processing unit). and data-processing equipment, we note that the top three com-
The CPU is the brain of the computer because it contains the puter advertisers in 1981 sold PCs, the top seven computer adver-
arithmetic and logic component, as well as the core memory and tisers in 1982 sold PCs, and for 1983 forward, the top ten computer
control unit for the computer. Thus, CPU design determines the advertisers sold PCs. As such, advertising expenditures for PCs
computer’s overall power and performance. mirror this same pattern as that presented in Figure 2.
Management Science/Vol. 49, No. 2, February 2003 201BAYUS, ERICKSON, AND JACOBSON
The Financial Rewards of New Product Introductions
4. Data and NASDAQ stock exchanges. We make use of both
One of the main barriers to research on this topic the industrial and industrial research files to capture
is the availability of appropriate, objective data on not only firms that survived through the end of the
new product introductions and matching informa- data period, but also those that did not survive. Merg-
tion on financial performance at the firm level. For- ing the IDC data with COMPUSTAT data restricts the
tunately, suitable data for the PC industry can be PC firms that can be studied. For instance, our sam-
obtained by merging information from two sources. ple includes only publicly traded companies. Further,
Details on product introductions by PC manufactur- we only include firms for which their primary busi-
ers come from International Data Corporation’s (IDC) ness is the manufacture of PCs. Thus, for example,
Processor Installation Census. Financial data, including IBM is not considered in our analysis as the financial
information on assets, income, sales, cost of goods data reported by COMPUSTAT aggregate across its
sold, advertising, R&D, and other SG&A expenses, substantial non-PC businesses. Our matching process
are obtained from Standard and Poor’s COMPUSTAT yields a panel of 16 firms who were in the PC market
annual data files. for all or some of the period 1974 to 1994, generating
The IDC Processor Installation Census database pro- a total of 141 pooled cross-section time-series obser-
vides a listing of all new PC products introduced vations. In the data, there is a broad range of years of
between 1974 and 1994. IDC is the oldest among data available per firm; 13 firms have over 5 years of
the various firms that track the American computer data, with 6 of these having over 10 years of data.
industry and is widely respected as having a very Because our analysis is restricted to publicly traded
accurate picture of activity in this industry. The IDC firms and only those that do not have substantial
data include details about the manufacturer name, activity in markets other than PCs, our sample of
brand name, CPU, and introduction date for each PC firms (and thus our results) may not be representative
product introduced.3 Following prior research with of the population of all companies in the PC indus-
these data (e.g., Bayus and Putsis 1999), we consider try. Also, because the number of firms in the sample
a new product to be any new, unique brand-CPU is relatively small, 16, the influence of the practices
combination because manufacturers generally incur of individual firms may be influential. Nonetheless,
significant expenses associated with the production firms included in our analysis are important in their
and launch of each brand model (e.g., Apple Com- own right, e.g., the 16 firms in our sample account for
puter’s Lisa and Macintosh are each considered to be almost one-third of PC industry sales in every year
a new product although they use the same Motorola during our data period. Further, our sample includes
68000 CPU).4 large firms (e.g., Apple, Compaq, Dell, Gateway) as
The COMPUSTAT database provides financial data well as smaller firms, early market entrants (3 firms
for publicly traded firms on the New York, American, in 1977, 1 in 1978) as well as later entrants (2 in 1987,
1 in 1988), and survivors as well as nonsurvivors (7 of
3
the 16 firms in the sample disappeared from the mar-
This level of detail is only available through 1994 because IDC
ket by the end of the data period). Altogether, there
changed its data collection procedure to a more aggregate format
in 1995. Also, products with CPUs that could not be identified due are 1,070 new product introductions represented in
to proprietary technology are excluded from our analysis. the data, with a per-firm range of 2 to 136 new prod-
4
As part of our empirical analysis to be discussed in the next sec- ucts. Finally, we note that the pattern of sales and new
tion, we also considered other “new product” definitions. These product introductions for these 16 firms parallels the
included new product technologies (the first introduction of a industry patterns in Figure 1.
PC based on a new microprocessor generation, e.g., 8-bit, 16-bit,
32-bit, 64-bit) and new product models (the first introduction of a
product based on a unique CPU, e.g., Intel’s 80286, 80386DX, etc.).
Because the variables based on these various definitions are highly
5. Empirical Analysis
correlated, our estimation results are very similar for all of these To empirically estimate the effect of new product
measures. introductions on the business performance of firm i
202 Management Science/Vol. 49, No. 2, February 2003BAYUS, ERICKSON, AND JACOBSON
The Financial Rewards of New Product Introductions
in year t (Perfit , we begin with a base model of the model, this specification allows for serial correlation
form (current-effects) as well as a state-dependent (persist-
ing) dynamic relationship. As such, this model allows
Perf it = i + 1 Introit + 2 Introit−1 for a wide range of possible effects and influences.
T
Because of the firm-specific fixed effects i in (1),
+ Perf it−1 + t Timet + (1)
t=1
it
empirical estimation requires taking first differences
of the data, which removes the firm-specific intercept.
Perfit is the performance of firm i in period t, Introit is This, in turn, necessitates the use of instrumental vari-
the number of new product introductions for firm i in able estimation to obtain a consistent estimate of the
period t, and Timet , t = 1 T , are annual dummy persistence parameter , because differencing induces
variables where each variable takes on the value 1 if correlation of Perfit−1 with the error term of the differ-
year = t 0 otherwise. We make use of two measures enced model. Following Anderson and Hsiao (1982),
of performance, i.e., return on assets (ROA) and asset we use lagged values of firm performance at time
growth, as dependent measures.5 The coefficients 1
period t − 2 as instruments.
and 2 depict the effect that product introductions
have on performance. The coefficient captures the
5.1. Profit Rate
autoregressive pattern of performance and, as such,
Model 1.1 in Table 1 presents the results of estimat-
its persistence.
ing Equation (1) with ROA as the dependent measure.
In addition to including variables reflecting the
We find positive effects for new product introduc-
effects of current and lagged new product introduc-
tions. The estimated effects for current and lagged
tions (Introit , Introit−1 , Equation (1) allows for unob-
served, time-invariant firm-specific effects via the
intercept i .6 Dynamic firm effects are modeled by Table 1 The Effect of Product Introductions on Drivers of Business
Performance
including lagged performance Perfit−1 in the model.
By including annual dummy variables in the model, Model 1.1 Model 1.2 Model 1.3
we control for yearly factors that affect all firms Return on assets Return on assets Asset growth
in the sample, which includes macroeconomic con- New product 085 078 063
ditions and industrywide influences. These dummy introductionst 395 333 246
variables remove unrelated variation, allowing us to New product 114 129 121
better isolate the effects of new product introduc- introductionst−1 585 483 497
tions and the potential for spurious correlation that
Dependent 006 025 022
would be generated by any possible time-based com- variablet−1 036 090 235
mon associations among the variables, e.g., industry
Dependent — −046 —
life-cycle effects. Because we include both current-
variablet−1 ∗ −084
term and lagged new product introductions in the New product
introductionst
5
We use ROA and asset growth (as opposed to, in particular, ROE
N∗ 109 109 109
and equity growth) in that we wish to focus on operating returns,
F -statistic, P -value [2.67, 0.0009] [2.57, 0.001] [2.65, 0.0009]
which depend on the total resources (i.e., assets) that the firm has
deployed. Note. Each model also includes annual dummy variables not reported here
6
This is only necessary when ROA is the dependent measure. For (t-statistic in parentheses).
the asset growth relationship, parameter estimates from the model Definitions. Return on assets: Operating incomet /assetst . Asset growth:
allowing for fixed effects and those from the model constraining i log(assetst -log(assetst−1 . New product introductions: number of brand
to be the same across firms are in very close correspondence. As a models introducedt /assetst .
∗
Hausman (1978) specification test cannot reject the null hypothesis The number of observations available for analysis is less than the total
of no firm-specific differences in growth rates, we make use of the number of observations in the data sample because of the use of first dif-
more efficient estimator constraining the intercept for asset growth ferences and the presence of a lagged explanatory factor, i.e.; we “lose” two
to be constant across firms. years of data for each firm in our sample.
Management Science/Vol. 49, No. 2, February 2003 203BAYUS, ERICKSON, AND JACOBSON
The Financial Rewards of New Product Introductions
new product introductions are 0.85 and 1.14, respec- words, we find no evidence to suggest the presence
tively, and each is significant at the 1% level. We also of simultaneous feedback.
tested for longer-term effects, but found no evidence This absence of simultaneity is consistent with the
of an effect lasting beyond one year. For example, the advanced time commitment necessary for product
estimated effect of new product introductions lagged introductions; i.e., they are planned well in advance.
two years was 0.16 with a t-statistic of 0.73. This lim- We do, however, observe an effect of lagged profits on
ited duration of effect is consistent with the dynamic introductions. Profits lagged one year are negatively
and highly competitive nature of the PC industry. correlated with a product introduction. This negative
In industries where isolating mechanisms and barri- association is consistent with firms not wishing to
ers to imitation are more substantial, e.g., in phar- cannibalize successful existing products, but instead
maceuticals where patent protection plays a key role, bringing in new products when the profit-generating
we would expect new product introductions to have capabilities of their existing products has been dimin-
longer-term effects. ished. As this feedback effect is nonsimultaneous, the
As a sensitivity check, we also explored the role model is recursive. Thus, unbiased estimates of the
of new product introductions on an ROA measure effect of product introductions on firm profit rate can
based on net income as opposed to operating income. be obtained without incorporating instrumental vari-
Our conclusions are the same in that we find a able estimates for new product introductions.
highly significant association between the net-income-
based ROA measure and both current and lagged 5.2. Profit-Rate Persistence
new product introductions. Analyses based on ROE Profits in this market appear to display little, if any,
(return on stockholders equity) also generate similar persistence. The estimated autoregressive coefficient
conclusions. in Model 1.1 (0.06) is both small in magnitude and sta-
A possibility is that new product introductions are tistically insignificant.8 This estimated effect is below
not exogenous, but rather are influenced by current- what we, and others, observe for ROA persistence
term firm profitability. Further, both new product across the spectrum of publicly traded firms (i.e.,
introductions and firm profit may be jointly influ- around 0.6). However, this finding is consistent with
enced by a contemporaneous shock. These two possi- the PC industry being very dynamic with ease of com-
bilities would generate biased coefficient estimates in petitor entry and exit. Low persistence is not unique
our analysis. To assess these cases, we constructed an to a few firms in our sample, but rather a common
instrumental variable estimate for the change in new characteristic across the firms. PC manufacturers had
product introductions (based on values of the series their profit rates buffeted throughout the period. This
lagged two periods, which gave rise to a first-stage lack of persistence serves to highlight some of the
R2 of 0.28) and undertook a Hausman (1978) specifi- unique characteristics of the PC marketplace. Firms in
cation test. This test assesses whether the estimated the industry have been unable to erect isolating mech-
parameter generated from instrumental variable esti- anisms and barriers to imitation that restrict the dissi-
mation is significantly different from the least squares pation of abnormal returns. As a point of comparison,
estimate. We obtain a test statistic of 0.19, compared
to a 2 1 5% critical value of 3.84. Thus, we cannot 8
The first stage R2 in obtaining the instrumental variable estimate
reject the null hypothesis that product introductions for ROAit−1 is 0.4. This is well above the value where issues per-
are not influenced by current-term profits.7 In other taining to instrumental variable estimation in the presence of “weak
instruments” come into play, i.e., where R2 is less than the inverse
of the sample size (Bound et al. 1995). As such, the finite-sample
7
See, for example, Hausman (1978) and Maddala (2001) for dis- bias associated with the instrumental variable estimator will be
cussions of the Hausman test and its properties. We also tested minimal. Further support for the use of the Anderson-Hsiao estima-
for possible effects of growth on product introductions. We found tion procedure is provided by Arrellano (1989), who notes that the
no evidence of either a contemporaneous or lagged effect of firm method can be expected to produce “well determined estimates”
growth on product introductions. of the autoregressive parameter.
204 Management Science/Vol. 49, No. 2, February 2003BAYUS, ERICKSON, AND JACOBSON
The Financial Rewards of New Product Introductions
consider that the persistence for firms in the pharma- are positively associated with sales growth, with the
ceutical industry averages around 0.75. Advantage is lagged effect being of greater magnitude.
short-lived for PC firms.
A possible reason for a lack of profit persistence 5.4. The Effect of New Product Introductions on
may stem from the role of new product introductions. the Components of ROA
In particular, the persistence parameter may not be a The results reported in Table 1 show that new
constant, but instead it may vary depending on new product introductions influence business performance
product introductions. To allow for this possibility, we through two of the three drivers of business perfor-
expand Equation (1) to allow the autoregressive coef- mance we considered. That is, new product introduc-
ficient to vary systematically depending on firm prod- tions influence profit rate and asset growth, but do
uct introductions, i.e., = 0 + 1 Introit . Model 1.2 not influence profit rate persistence. Having found
in Table 1 presents the estimation results with this that new product introductions influence profit rate,
interaction term. We see no evidence that persistence we now turn our attention to empirically isolating the
does in fact depend on new product introductions. source(s) of this association. That is, we empirically
The estimated effects for persistence (0.25) and the assess why the observed associations found in Model
interaction term (−0 46) are individually, and jointly, 1.1 exist. We do so by splitting operating income, the
statistically insignificant. numerator in the ROA measure, into separate com-
ponents and assessing which components are or are
5.3. Asset Growth not influenced by new product introductions. We first
As we discussed previously, a firm’s market value separate operating income into two fundamental ele-
increases not just with increases in its profitability, but ments, operating income gross of SG&A (“gross oper-
also (as long as it has a positive profitability to cost of ating income,” simply sales less cost of good sold)
capital spread) with increases in size. As such, another and SG&A expenses, and report the empirical results
way that new product introductions can affect firm for this separation in Table 2. We then further decom-
value is through an impact on size.9 Here, too, we pose SG&A into some of its primary components, in
see positive effects of new product introductions. As particular, we separate out advertising expenditures
reported in Model 1.3, the estimated effects for both and R&D expenditures from SG&A expenditures, and
current (0.63) and lagged new product introductions report the results in Table 3.
(1.21) are positive and statistically significant. The As shown in Tables 2 and 3, we use two differ-
fact that asset growth exhibits positive persistence ent kinds of analyses to expand our understanding
(0.22) suggests that the effects of product introduc- of the phenomenon. One form of analysis considers
tion on growth will persist a bit beyond one year, and the effects of new product introductions on operat-
decay fairly rapidly beyond this point. As a sensitiv- ing income component intensities (operating income
ity check, we also explored the relationship between
component/assets). The second form of analysis esti-
new product introductions and another size measure,
mates the effects of new product introductions on
sales growth. This analysis provided results consis-
growth rates of the operating income components. The
tent with those observed in Model 1.3. We find that
two separate analyses provide an enhanced picture
both current and lagged new product introductions
of how the introduction of new products influences
profit rate.
9
It would be interesting to assess which asset components are most
affected by new product introductions. We are, however, limited in Gross Operating Income. Interestingly, we see
our ability to undertake this type of analysis as missing values are no evidence from the estimation of Model 2.1 in
reported in the Compustat database for a number of asset compo-
Table 2 that new product introductions have a pos-
nents for a number of firms and years. Nonetheless, and not unex-
pectedly, we find strong evidence that firms are increasing their
itive effect on gross operating return, i.e., gross
inventories in the wake of an introduction, and this is one source operating income/assets. Both current and lagged
of asset growth. new product introductions are estimated to have
Management Science/Vol. 49, No. 2, February 2003 205BAYUS, ERICKSON, AND JACOBSON
The Financial Rewards of New Product Introductions
Table 2 The Effects of New Product Introductions on Income Components
Model 2.1 Model 2.2 Model 2.3 Model 2.4
Gross operating Gross operating SG&A SG&A
return income growth intensity growth
New product −004 021 −085 −033
introductionst −026 057 −437 −174
New product −014 049 −129 −025
introductionst−1 −113 144 −715 −139
Dependent 053 012 −020 002
variablet−1 218 113 −142 160
N 109 105∗ 109 109
F -statistic, P -value [1.65, 0.059] [2.14, 0.00] [3.65, 0.0001] [2.73, 0.0007]
Note. Each model also includes annual dummy variables not reported here (t-statistic in parentheses).
Definitions. Gross operating return: (Salest –Cost of good soldt )/assetst . SG&A intensity: Selling, general, and
administrative expenditurest /assetst . Gross operating income growth: log(salest –cost of good soldt )–log(salest−1 –
cost of good soldt−1 ). SG&A growth: log(selling, general, and administrative expenditurest –log(selling, general,
and edministrative expenset−1 ).
∗
The number of observations in the gross operating income equation differs from the gross operating return
equation because of the presence of negative gross operating income, which generates missing data once loga-
rithms are taken.
small (−0 04 and −0 14, respectively) and statisti- ence the numerator in the gross operating return mea-
cally insignificant effects on gross operating return. sure, they also influence asset growth, and, as such,
Model 2.2 shows that new product introductions the denominator in the measure; see Model 1.3 in
exhibit some positive (albeit statistically insignificant) Table 1. The net result is that there is no significant
association with growth in gross operating income. impact of new product introductions by the firms in
However, while new product introductions may influ- our sample on gross operating return.
Table 3 Effects of New Product Introductions on SG&A Components
Model 3.1 Model 3.2 Model 3.3 Model 3.4 Model 3.5 Model 3.6
“Other” SG&A “Other” SG&A R&D R&D Advertising Advertising
intensity growth intensity growth intensity growth
New product −129 −189 004 054 −009 −284
introductionst −628 −565 091 144 −235 −395
New product −066 −073 −032 −030 −010 −004
introductionst−1 −424 −265 −561 −083 −334 −007
Dependent 013 043 069 006 021 005
variablet−1 071 452 368 043 077 040
N 98 98 106 106 98 98
F -statistic, P -value [4.09, 0.0001] [4.83, 0.0001] [4.20, 0.0001] [1.22, 0.259] [2.64, 0.001] [3.26, 0.0001]
Note. Each model also includes annual dummy variables not reported here (t-statistic in parentheses).
Definitions. “Other” SG&A intensity: (Selling, general, and administrative expenditurest –research and development expenditurest –advertising
expenditurest /assetst . R&D intensity: Research and development expenditurest /assetst . Advertising intensity: Advertising expenditurest /assetst . “Other”
SG&A growth: log(gross SG&A expenditurest – log(gross SG&A expenditurest−1 . R&D expenditure growth: log(research and development expenditurest –
log(research and development expenditurest−1 . Advertising expenditure growth: log(advertising expenditurest –log(advertising expenditurest−1 .
206 Management Science/Vol. 49, No. 2, February 2003BAYUS, ERICKSON, AND JACOBSON
The Financial Rewards of New Product Introductions
SG&A. Combined with the results for gross oper- product introductions, but firms are also decreasing
ating return, Models 2.3 and 2.4 show that the pos- the growth in their other SG&A expenditures, as is
itive effect of new product introductions on profit shown by Model 3.2. This decrease is most dramatic
rate arises through an impact on SG&A. Model 2.3 at the time of the introduction (−1 89), but continues
shows that current and lagged new product introduc- into the subsequent year as well (−0 73).
tions are associated with decreases in SG&A intensity
R&D. One reason that the effect of new product
(−0 85 and −1 29, respectively). While its role is often
introductions is more substantial for Other SG&A
overlooked or excluded from analysis, SG&A plays
than for SG&A is that firms are not cutting back on
an important part in firm profitability, as the median
R&D expenditure growth in the wake of a new pro-
SG&A intensity for our data is 0.4, compared to
duction introduction. That is, we see from Model 3.4
median gross operating return of 0.5. Model 2.4 shows
that the estimated effects for both current and lagged
that some of this decrease in SG&A intensity might be
new product introductions on R&D growth (0.54 and
coming from firms cutting back on SG&A growth in
−0 30, respectively) are statistically insignificant.
the wake of product introduction; SG&A expenditure
We see from Model 3.3 that while current R&D
growth is negatively related, although the coefficients
are not significant, to both current and lagged new intensity is unrelated to new product introductions—
product introductions. Any cutbacks in SG&A growth the estimated effect is 0.04 and statistically
would have an accentuated effect on SG&A intensity, insignificant—R&D intensity is negatively associated
as product introductions also generate an increase in with lagged introductions—the estimated effect is
asset growth (Model 2.3). While these results cannot −0 32 and highly significant. While Model 3.4 per-
pinpoint the effect on SG&A growth, clearly SG&A is haps suggests that firms increase contemporaneous
not growing as rapidly as assets when a product intro- R&D expenditure growth with new product introduc-
duction occurs (and, indeed, may even be declining), tions (i.e., the estimated effect of 0.54 has a t-statistic
so SG&A intensity and product introductions will be of 1.44), its effect on R&D intensity is counterbal-
negatively correlated. anced by the positive contemporaneous effect on
As shown in Table 3, we can gain some insight into asset growth. These offsetting influences explain the
the underlying sources of the SG&A association with absence of a contemporaneous association between
new product introductions by separately analyzing R&D intensity and new product introductions. The
some of the components of SG&A. In particular, we absence of an effect (or perhaps even a negative
separate SG&A into R&D expenditures, advertising effect) of lagged new product introductions on R&D
expenditures, and “Other” SG&A expenditures (i.e., growth reported in Model 3.4, combined with the
SG&A expenditures other than R&D and advertising). positive lagged effect of new product introductions
Analysis of the advertising measure, which includes on asset growth, accounts for the significant negative
the cost of both media advertising and promotional association between R&D intensity and lagged new
expenditures, while not inclusive of all marketing product introductions.
expenditures, can be expected to provide funda- Advertising. Counter to the conventional wisdom
mental insights into the interactions taking place that new product introductions require an increase in
between new product introductions and marketing advertising, Model 3.5 shows that both current and
activities. lagged new product introductions have statistically
Other SG&A Expenditures. We see from Model significant negative effects on advertising intensity,
3.1 a strong negative relationship between Other −0 09 and −0 1, respectively. Indeed, Model 3.6 shows
SG&A expenditure intensity (SG&A expenditures that new product introductions have a negative con-
other than advertising and R&D) and both cur- temporaneous association with advertising expendi-
rent (−1 29) and lagged new product introductions ture growth. As such, contemporaneous to a product
(−0 66). The reason for this negative relationship is introduction, PC firms tend to both cut back adver-
that not only is a firm’s asset base growing with new tising growth and increase in size. This accounts for
Management Science/Vol. 49, No. 2, February 2003 207BAYUS, ERICKSON, AND JACOBSON
The Financial Rewards of New Product Introductions
the significant negative contemporaneous association New products introduced into the PC market
between advertising intensity and new product intro- increase sales, but also come at an increased cost.
ductions reported in Model 3.5. We see no association These effects appear to “cancel out” so that operat-
between lagged product introductions and advertis- ing profit margin remains about the same. However,
ing growth (i.e., the coefficient −0 04 in Model 3.6 our results show that new products in this indus-
is small and insignificant), but asset growth is posi- try have lower selling expenses than the older, more
tively correlated with lagged new product introduc- established products. The decrease in SG&A intensity
tions. This increase in size, therefore, seems to account induced by new product introductions indicates, for
for the negative lagged effect of new product intro- example, that firms do not have to spend as much on
ductions on advertising intensity. advertising and other marketing activities to sell new
products as opposed to older products.
A number of factors can account for this reduc-
6. Discussion
tion in advertising intensity in the presence of a
Our results indicate that new product introductions in
new product introduction. Certainly, new product
the PC industry influence two of the three core drivers
of firm value, profit rate, and firm size (as reflected introductions are commonly viewed as “news” and
in asset growth), but not profit-rate persistence. As receive “free” media attention (e.g., important new
such, our analyses support Hypotheses 1 and 3, but pharmaceuticals often receive more press attention;
not Hypothesis 2. Angell 2000). This attention from alternative sources
The lack of an effect of new product introduc- lessens the need for paid promotional activities by
tions on profit persistence is not so surprising in the a firm. Further, rather than incurring the additional
context of the industry we study. Sustaining above- expenses associated with selling its older products to
normal profits from any source would be difficult to new customers, a firm has lower SG&A expenses by
achieve in an industry like the PC industry, in which selling new products to its current customers. Con-
frequent technological advances and disruptive new sistent with Grossman and Shapiro (1984), advertis-
product introductions by competitors are the norm. ing in the PC industry may be informative rather
We find that profits from new products are reinvested than persuasive, suggesting that firms targeting cur-
into building up the firm’s asset base. As long as rent customers with new generations of an existing
the firm has a positive profit rate to cost of capital product will have less advertising expenditure than
spread, this growth induced by new product intro- firms attempting to expand their customer bases.
ductions will increase market value. Market value is A possible alternative explanation for our findings
additionally enhanced as new product introductions is that a reduction in advertising is justified by gen-
increase profit rates for a two-year period. Particularly erally increasing brand reputation and stature over
in industries with low rates of profitability, activities time. This, however, does not appear to be the case.
that enhance return are of fundamental importance in When we include a firm longevity variable (i.e., the
influencing firm value. number of years the firm has been in the PC indus-
Our empirical finding that the introduction of new try at the time of the introduction) in our adver-
products enhances firm profitability by increasing tising equations, its effect is small and insignificant
firm size and profit rates is important because of the (−0 0005, with a t-statistic of −0 37). Further, the esti-
lack of solid evidence elsewhere in the literature. At mated effects of product introductions are indistin-
the same time, these results are not all that surprising. guishable from those reported in Table 3.
What is surprising, however, is what our results say Another possibility is that our findings result from
about the manner by which new product introduc- a commoditization of PC products. That is, due to
tions increase firm profit rates. Our analysis shows the inherent characteristics of this industry—i.e., short
that new product introduction activity enhances prof- product life cycles, a rapid pace of technological
itability through reduced SG&A expenditure intensity, change, and increasing competitive pressure due to
and not through gross operating return. reduced margins—the way PC companies maintain
208 Management Science/Vol. 49, No. 2, February 2003BAYUS, ERICKSON, AND JACOBSON
The Financial Rewards of New Product Introductions
profits is to cut advertising but not R&D. While all petitive. Quality-adjusted prices have fallen at a rate
such industrywide trends would be captured by the of 25% per year. Imitators with low prices have few
annual dummy variables in our models and thus not barriers to entry. In such a market environment, it is
affect the estimated coefficients for product introduc- natural to question how firms are able to realize tan-
tions, it is also the case that the data do not support gible financial rewards from their new product activ-
a commoditization hypothesis. Under this view, we ities. We find that firms in the PC industry achieve
would expect to see declining advertising intensity, financial rewards from their new product introduc-
but not R&D intensity, over time. Our data, how- tions because this activity allows them to increase in
ever, show just the opposite: Mean advertising inten- size and increase their profit rate through lowered
sity does not decline over time (which is consistent SG&A intensity. More specifically, we find that new
with the overall industry pattern in Figure 2), while product introductions influence profit rate and asset
mean R&D intensity shows a systematic decline.10 growth, but not profit-rate persistence.
The effects of product introductions on advertising Caution should be exercised in generalizing our
reported in Models 3.5 and 3.6 stem not from a gen- findings beyond the specific industry, time period,
eral industry trend, but rather are tied to firm-specific and data sample used in this study. These limita-
product introductions. tions, however, suggest various directions for future
Some characteristics of the PC industry help to research. In particular, future studies might attempt
explain why this phenomenon is present in this indus- to generalize our results to other industry settings,
try. In particular, this industry combines rapid tech- including dynamic as well as more stable product
nological development with the existence of buyers technologies and products in the maturity and decline
who know what is available (Langlois 1992). Techno- stages of their industry life cycle. In addition, recent
logically advanced, or at least technologically com- signs of a slowdown in the PC industry raise the ques-
petitive, new products thus have a ready demand
tion of whether firms will continue to be able to rely
from knowledgeable and discriminating customers.
on new products to lower their selling and advertis-
Because customers are able to tell the difference
ing expenditures (e.g., Hannon 2001). Thus, continu-
between new and older products, older products
ing to increase our understanding of how and why
with out-of-date technology are more difficult to sell.
firms benefit from new product activity is an impor-
Moore (1995) and others contend that in technology-
tant area for future research.
based industries characterized by rapid growth, tech-
nological advancement, and buyers empowered by
choice and access to information, the appropriate References
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Management Science/Vol. 49, No. 2, February 2003 209You can also read
