Marketing Letters 1:3, (1989): 187-198
© 1990 Kluwer Academic Publishers, Manufactured in the Netherlands.
When to Lead or Follow? It Depends
MARK PARRY
The Darden School
FRANK M. BASS
The University of Texas at Dallas
[Received November 1989, Revised May 1990]
Key words: Entry Barrier, Pioneer Entry, Mature-Stage Performance
Abstract
Existing studies of entry strategy attribute sustained pioneer advantages to the pioneer's ability to
erect barriers that impede the entry of potential competitors. Because effective entry barriers
imply industry concentration, the entry-barrier explanation of sustained pioneer advantage suggests that pioneers in concentrated industries will experience superior mature-stage performance.
This paper tests this hypothesis by controlling for industry concentration and analyzing the impact
of entry strategy on the mature-stage firm's market share, perceived relative product quality, relative product-line breadth, relative price, and relative direct costs. The analysis suggests that the
presence of effective barriers-to-entry significantly affects the performance poineers in both consumer- and industrial-goods industries. Moreover, the extent to which pioneers receive an incremental share advantage over early followers depends on both industry type and end-user purchase
amounts.
Various studies (Robinson and Fornell 1985; Robinson 1988; see also Urban et al.
1986) have attributed sustained pioneer advantages to the pioneer's ability to erect
barriers that impede the entry of potential competitors. According to Robinson
and Fornell (1985), the entry-barrier literature "is useful because even after entry
has taken place, the factors producing entry barriers can provide poineers with
sustainable competitive advantages" (p. 305). This literature (e.g., Bain 1956,
Scherer 1980) suggests that entry barriers increase concentration, thereby enhancing the performance of incumbent firms (Karakaya and Stahl 1989). Therefore, to the extent that industry concentration is an indicator of effective entry
barriers, the impact of pioneer entry will not be homogeneous across concentrated and nonconcentrated industries (Bass, Cattin, and Wittink 1978). Thus the
entry-barrier explanation of sustained pioneer advantage suggests the following
hypothesis: pioneers in concentrated industries will experience superior maturestage performance relative to pioneers in nonconcentrated industries. In this paper, we test this hypothesis by controlling for industry concentration and
analyzing the impact of entry strategy on the mature-stage firm's market share,
perceived relative product quality, relative product-line breadth, relative price,
and relative direct costs. Further, because increases in concentration benefit all
188
MARK PARRY AND FRANK M. BASS
incumbent firms, we attempt to distinguish the benefits of participation in a concentrated industry from the incremental benefits associated with pioneer entry.
1. Data and methodology
Our analysis used the PIMS SPI4 data base, in which each observation consists
of data averaged over four years [details of the data base are available in Robinson
and Fornell (1985) and Robinson (1988), hereafter denoted as RFR]. From these
data, we selected the most recent observation for each consumer and industrial
firm. Following RFR, we confined our analysis to markets in the mature stage of
the product life cycle. These restrictions generated consumer-goods and industrial-goods samples of 593 and 1,287 observations, respectively.
/./. Econometric model
Our econometric model followed RFR by examining the impact of pioneer entry
with a simultaneous-equation model containing five endogenous variables: market
share, relative product quality, relative product-line breadth, relative price, and
relative direct costs. Market share is defined as share of relevant market, while
relative product quality is defined as the percentage of the firm's product-line that
is superior to that of leading competitors minus the percentage that is inferior.
Relative product-line breadth is a categorical variable indicating whether a firm's
product-line is narrower than, equivalent to, or broader than the product-lines of
the firm's leading competitors. Relative price and relative direct cost are obtained
by dividing the firm's price and direct cost, respectively, by the average prices
and direct costs of its leading competitors.
1.1.1. Entry variables and industry concentration. The PIMS data questionnaire
asks respondents to indicate whether, at the time their firm entered the market, it
was "(1) one of the pioneers in first developing such products or services, (2) an
early follower of the pioneer(s) in a still growing, dynamic market, or (3) a later
entrant into a more established market situation" (PIMS Data Manual 1979, p.
3-5). From this variable, RFR defined two dummy variables, pioneer and early
follower, and used them as exogenous variables in their consumer- and industrialgoods models. RFR also created a series of interaction variables by multiplying
the pioneer and early-follower variables by various measures of firm or industry
characteristics.
1.1.2. Industry concentration. A well-known measure of industry concentration is
the 4-firm concentration ratio, defined as the cumulative share of the four largest
firms in an industry. Scherer (1980) reported, "The results for a diversity of prof-
WHEN TO LEAD OR FOLLOW?
189
itability indices and U.S. industry samples are remarkably uniform: virtually all
show a distinct upsurge in profit rates as the 4-firm concentration ratio passes
through a range somewhere between 45% and 59%" (p. 280). Consequently, we
chose to distinguish pioneers in industries where the 4-firm concentration ratio
was greater than 55% from pioneers in industries where the same measure was
less than 55%.
The PIMS data base does not report relevant-market 4-firm concentration ratios
but does contain a variable that closely approximates it. PIMS computes the big4
market share variable (B4MS) as the sum of the respondent firm's share and that
of its three largest competitors. If the respondent firm is one of the four largest
firms in its industry, then the B4MS variable equals the 4-firm concentration ratio
for the respondent firm's industry.
Using the B4MS variable, we defined a concentrated-industry dummy variable
that was assigned the value 1 if B4MS was greater than 55 percent and 0 otherwise. The concentrated consumer-goods segment consisted of 437 observations,
the non-concentrated consumer-goods segment of 156 observations, the concentrated industrial-goods segment of 994 observations, and the non-concentrated
industrial-goods segment of 293 observations. We then defined 4 dummy variables
to replace the pioneer and early-follower dummy variables used by RFR:
Concentrated Pioneer (CP) =
Pioneer x Concentrated Industry
Non-Concentrated Pioneer =
Pioneer - CP
Concentrated Early Follower (CEF) = Early Follower x Concentrated
Industry
Non-Concentrated Early Follower = Early Follower - CEF.
1.1.3. Other exogenous variables. With a few exceptions, the remaining exogenous
variables in our model corresponded to those used by RFR. In both samples, we
omitted variables that RFR constructed by combining continuous and categorical
variables. For example, the RFR consumer model contained a dummy variable
that had the value I if the firm was a pioneer and belonged to an industry in which
the industry advertising/sales ratio was greater than 5 percent. Because the PIMS
data base does not report industry advertising/sales ratios, the variable must be
constructed from three other variables: firm market share (MS), firm advertising/
sales ratio (A/S), and competitor advertising/sales ratio (CA/S). Two of these variables (MS and A/S) are in the PIMS data base. The third, CA/S, is not and must
be constructed from A/S and relative advertising (RA). The A/S ratio ranges (in
the PIMS data base) from 0 to 15 (the ratio is multiplied by 100), while RA is a
categorical variable that assumes 1 of 5 values: Much Less (I), Somewhat Less
(2), About the Same (3), Somewhat More (4), and Much More (5). If one assumes
that the RA variable has cardinal properties, then CA/S can be defined as
CA/S = (A/S)[I + a(3 - RA)].
190
MARK PARRY AND FRANK M. BASS
To insure that CA/S is nonnegative, a must be confined to the interval [0, .5], but
any selection of a within that interval appears arbitrary. Unfortunately, neither
the RFR consumer-goods paper (1985) nor the Robinson dissertation (1984) explained how this indeterminacy was resolved.
The 1985 consumer-goods paper contained one interaction term created from a
"constructed" industry variable. The 1988 industrial-goods paper contained three
such interaction terms: pioneer/industry salesforce expenditures, pioneer/industry value added, and late entrant/industry value added. Our reservations concerning the construction of these variables and the lack of direction provided by RFR
in their published papers led us to delete these variables from our analysis.
With the exceptions noted here, our initial consumer and industrial models corresponded to those analyzed by RFR; however, our initial regressions revealed
that only two of the pioneer interaction terms identified by RFR were significant
at the 10 percent level of confidence: pioneer/low purchase amount in the consumer-goods market share equation and pioneer/purchase amount in the industrial-goods market share equation. We also tested the hypotheses that the
coefficients of the remaining RFR interaction terms were all equal to 0. The relevant
F-statistic was .29 for the consumer-goods MS equation and 1.09 for the industrial-goods MS equation. Because we could not reject the null hypothesis of insignificance, we deleted the insignificant RFR interaction terms from the models.
2. Results
Tables 3 and 4 contain the two-stage least squares estimates for the consumerand industrial-goods models. In general, the signs of the significant exogenous
Table I. Consumer-goods model (592 obs.)
Variable
Constant
Market
share
-79.76'
(41.76)
Relative
product
quality
138.60
(94.00)
Relative
product-line
breadth
3.52"
(1.71)
Market share
Relative product
quality
Relative productline breadth
Relative price
Relative direct cost
.16'^
(.09)
13.17'
(1.95)
.11'
(.41)
2.07"
(.95)
-3.26'
(.74)
- .029'
(.016)
Relative
price
13.82
(26.84)
.13'
(.05)
Relative
direct
cost
113.00"
(2.60)
-.10"
(.04)
.11
.04
(.07)
(.06)
.80'
(.25)
191
WHEN TO LEAD OR FOLLOW?
Table I. (continued)
Variable
Pioneer/
concentrated
industry
Pioneer/nonconcentrated
industry
Early follower/
concentrated
industry
Early follower/nonconcentrated
industry
Pioneer/low
purchase amount
Number of
competitors
Relative
advertising &
promotion
% sales from new
products
Relative customer
type
Relative number of
customers
Relative customer
size
Number of
immediate
customers
Plant & equipment
newness
Capacity utilization
Relative vertical
integration
backwards
Employee
productivity
% employees
unionized
R-square
Market
share
Relative
product
quality
Relative
product-line
breadth
Relative
price
Relative
direct
cost
3.28
(2.38)
1.19
(4.07)
.31"
(.08)
-.96
(1.21)
-1.40
(.97)
-8..S7"
(2.72)
6.90
(4.97)
.40"
(.10)
-.11
(1.43)
-.88
(1.20)
3.76"
(2.16)
3.47
(4.18)
.16'
(.09)
-1.79
(1.17)
-1.01
(.90)
-4.92'
(2.59)
-4.81
(5.26)
.10
(.11)
2.28
(1.48)
-2.43"
(1.09)
5.03"
(1.86)
-5.26"
(.69)
.40
(.50)
.43'
(.24)
-.16
(1.10)
.14
(.10)
-.001
(.002)
.02
(.03)
.27"
(.06)
.28(.04)
.10"
(.05)
.14
(.31)
-.02
(.03)
-.08"
(.02)
-1.26"
(.56)
.56
.10
a = significant at the 1% level of confidence.
b = significant at the 5% level of confidence.
c = significant at the 10% level of confidence.
Note: Numbers in parentheses are standard deviations.
.33
.06
.01
(.01)
.02"
(.01)
.11
192
MARK PARRY AND FRANK M. BASS
Table 2. Industrial-goods model (1287 obs.)
Variable
Constant
Market share
Relative product
quality
Relative productline breadth
Relative price
Market
share
-60.10
(43.55)
Relative
product
quality
Relative
product-line
breadth
Relative
price
155.30"
(39.50)
1.72'
(.97)
58.24"
(9.29)
-.06"
(.03)
.21"
(.03)
2.22
(3.03)
- 1.42"
(.37)
3.66
(2.31)
-.01
(.01)
.18"
(.05)
.39"
(.09)
(.62)
-7.97"
(3.21)
2.66
(3.14)
.24"
(.07)
(.72)
7.30"
, (1.42)
-4.12'
(2.48)
-.03
(.06)
(.66)
-2.84
(1.87)
-.27
(3.22)
.13'
(.08)
(.73)
.002
(.002)
.53"
(.18)
-.037"
(.019)
.23"
(.10)
11.58"
(1.66)
Relative
direct
cost
86.86"
(3.29)
- .06"
(.03)
-.03
(.03)
.63
(.43)
Relative direct cost
Pioneer/
concentrated
industry
Pioneer/nonconcentrated
industry
Early follower/
concentrated
industry
Early follower/nonconcentrated
industry
Pioneer/purchase
amount
Number of
competitors
Relative salesforce
expenditures
% sales from new
products
Product patent
Relative customer
type
Relative number of
customers
Relative customer
size
Number of
immediate
customers
Capacity utilization
.82
.31
.46
.36
-.27
(.69)
-.17
(.81)
- .36
(.72)
-.71
(.83)
.91'
(.47)
-6.30"
(.47)
.01
.83
(.55)
(.80)
.30"
(.07)
9.65"
(2.07)
.28"
(.04)
.33"
(.03)
.11"
(.03)
AQ
( 13)
-.05"
(.01)
WHEN TO LEAD OR FOLLOW?
193
Table 2. (continued)
Variable
Relative vertical
integration
backwards
% employees
unionized
Relative
compensation
R-square
Market
share
Relative
product
quality
Relative
product-line
breadth
Relative
price
3.32"
(L37)
.47
.09
Relative
direct
cost
- L36"
(.34)
,35
-.001
(.001)
.25"
(03)
.08
.09
a = significant at the 1% level of confidence.
b = significant at the 5% level of confidence.
c = significant at the 10% level of confidence.
Note: Numbers in parentheses are standard deviations.
variables were consistent with theory. We will begin our discussion with the market share equation and will then turn to the marketing mix equations.
2.1. The market share equation
In both the consumer-goods and the industrial-goods market share equation, the
concentrated pioneer coefficients were positive (3.28 and 2.22) and insignificant,
while the non-concentrated pioneer coefficients were negative (-8.57 and -7.97)
and significant. These estimates confirm the hypothesis that the presence of effective entry barriers has a substantial influence on the long-run share advantage
enjoyed by pioneers. The coefficients ofthe concentrated early-follower variables
(3.76 and 7.30) were also significant, suggesting that the presence of entry barriers
benefits early followers as well as pioneers.
The market share equations also indicate that, in certain industries, entry barriers appear to yield little incremental benefit to pioneers beyond that enjoyed by
early followers. In consumer goods industries, the pioneer/purchase amount interaction effect was either 0 (average purchase amount of $10.00 or more) or 5.03
(average purchase amount under $10.00). Thus concentrated pioneers with a retail
purchase amount above $10.00 did not receive any incremental share benefit relative to later entrants; however, concentrated pioneers with a retail purchase
amount under $10.00 experienced an incremental share benefit of 4.55 share
points. These results are consistent with those reported by Kalyanarum (1989), as
well as with the reasoning of Lieberman and Montgomery (1988), who hypothesized that pioneers may benefit from consumer uncertainty about product quality:
194
MARK PARRY AND FRANK M. BASS
"Brand loyalty of this sort may be particularly strong for low-cost 'convenience
goods' where the benefits of finding a superior brand are seldom great enough to
justify the additional search costs that must be incurred" (p. 46).
The industrial-goods purchase-amount interaction varied directly with purchase
amount and ranged from .91 to 8.19, because the purchase-amount variable
ranged from 1 (under $1.00) to 9 (over $10 million). Using the mean of the purchase amount variable in the industrial-goods sample, the share benefit generated
by the average purchase-amount interaction was 4.85 (.91*5.34). Thus concentrated industrial-goods pioneers on average received a share benefit of 2.22 -I4.85 = 7.07 share points, virtually equivalent to the 7.30 share benefit enjoyed by
concentrated industrial-goods early followers.
We suspect that the positive interaction between purchase amount and pioneer
entry in industrial-goods firms has two explanations. First, the "brand loyalty"
explanation advanced above for consumer-goods industries is less relevant for
industrial-goods firms: "imperfect information effects should be greater for individual consumers than corporate buyers, since the latter's larger purchase volume
justifies greater investment in information acquisition activities" (Lieberman and
Montgomery 1988). Second, as purchase amount rises, industrial-goods manufacturers may benefit from buyer switching costs, as well as from a technology franchise and the formation of strategic alliances with customers. These latter explanations for pioneer performance advantages appear more relevant to expensive
industrial goods.
2.2. The marketing-mix equations
The remaining equations in the RFR models permit an assessment of four additional performance measures: perceived relative product quality, relative productline breadth, relative price, and relative direct costs. In the equation for relative
product-line breadth, the concentrated-pioneer coefficients (.31 and .18) and the
non-concentrated-pioneer coefficients (.40 and .24) were all positive and significant. Moreover, in both consumer-goods and industrial-goods industries, pioneering resulted in relatively broader product lines for non-concentrated pioneers.
This suggests that entry deterrence through spatial preemption within the productcharacteristics space (Lieberman and Montgomery 1988) assumes greater importance when alternative entry deterrence strategies are unavailable or ineffective.
Table 3 reports the maximum-likelihood estimates of the effect on share of
entry-driven line-breadth advantages. Regardless of the level of industry concentration, broader product lines endowed pioneers with a substantial share advantage over early followers. Moreover, relative to late entrants, the share benefit
enjoyed by consumer-goods pioneers was approximately twice that enjoyed by
industrial goods pioneers. These results are consistent with an enhanced ability
of umbrella branding to reduce information acquisition activities among individual
consumers relative to corporate buyers (Lieberman and Montgomery 1988).
WHEN TO LEAD OR FOLLOW?
195
Table 3. Summary of results: Estimated impact of pioneer and early follower entry
Consumer goods
Pioneer
Market share
Product quality
Product line
breadth
Relative price
Relative direct
cost
Total
Early follower
Market share
Product quality
Product line
breadth
Relative price
Relative direct
cost
Total
Concentrated
3.28'
.19
4.08
Non-concentrated
Industrial goods
Concentrated
Non-concentrated
-8.57'
1.01
5.27
7.07^
.84
2.08
-.74
.40
-.08
.25
.52
.05
.29
.03
7.22'
-2.03'
10.57=
.50=
3.76
.56
2.11
-4.92
-.77
1.32
7.30
-.95
-.35
-1.38
.29
1.76
.70
.29
.07
.23
.14
5.33
-1.92
6.37
-1.03
-5.75=
2.78
-2.84
— .06
1.51
'Estimates assume retail purchase amounts greater than $10.00. Add 5.03 for pioneers in low-purchase amount industries.
^Estimates assume retail purchase amounts equal to the sample mean.
In the consumer-goods relative-product-quality equation, none of the entry
coefficients was significantly distinguishable from 0. In the corresponding industrial-goods equation, the concentrated pioneer coefficient (3.66) was positive and
significant, while the concentrated early follower coefficient (-4.12) was negative
and significant. Table 3 indicates that, in one case (concentrated consumer-goods
industries), pioneers suffered a small quality-driven share disadvantage relative
to early followers. The situation was reversed in the remaining cases. Possibly the
combination of (1) effective entry barriers and (2) consumer uncertainty (relative
to mdustrial buyers) regarding product quality lead concentrated consumer-goods
pioneers to place relatively less emphasis on product quality as a differentiation
strategy.
With one exception, the entry variables were not significant in either the relative-price or relative-direct-cost equations. The exception involved the consumergoods relative-direct-cost equation, in which the non-concentrated early follower
coefficient (-2.43) was negative and significant. Table 3 suggests that, in consumer-goods industries, non-concentrated early followers enjoyed a price-driven
share advantage of 1.84 share points relative to non-concentrated pioneers. In
addition, both concentrated consumer-goods pioneers and industrial-goods pioneers enjoyed a small price-driven share advantage over early followers. In only
196
MARK PARRY AND FRANK M. BASS
one case, concentrated consumer-goods industries, did pioneers have a costdriven share advantage over early followers. In every case, however, the difference between the cost-driven share advantages of pioneers and early followers
was small.
2.3. Summary
Table 4 contains a cross-table that reports market share by industry type, industry
concentration, and entry strategy and suggests that pioneers have substantially
higher shares than later entrants. A comparison of Table 4 with Table 3, however,
reveals that the simple cross-tables confound the effect of entry strategy with the
influence of omitted variables. According to Table 4, the average share of concentrated consumer-goods pioneers is 9.30 share points higher than that of concentrated early followers; however. Table 3 indicates that, when omitted variables
are accounted for, the actual share advantage attributable to pioneer entry is 6.92
share points for firms with retail purchase amounts under $10.00 and 1.89 share
points otherwise. Similarly, the cross-tables suggest that the average difference
between the shares of non-concentrated consumer-goods pioneers and early followers is 4.88 share points, but Table 3 indicates that the actual share advantage
attributable to pioneer entry is positive (4.92 share points) only for firms with low
retail purchase amounts.
Turning to industrial-goods firms, the average share of concentrated pioneers
is 7.45 share points higher than that of concentrated early followers. Once again,
the cross-table overstates the actual share advantage (4.20 share points). Finally,
although the average difference between the shares of non-concentrated pioneers
and early followers is 3.87 share points, the actual share advantage attributable to
pioneer entry is 1.53 share points.
3. Discussion
We have examined the hypothesis that pioneers experience mature-stage performance advantages through their ability to erect barriers to entry. Our results are
Table 4. Average market share by industry, concentration. and entry strategy
Consumer goods
Industrial goods
Entry strategy
Concentrated
Non-concentrated
Concentrated
Non-concentrated
Pioneer
Early Follower
Late Entrant
33.75
24.45
17.39
12.06
7.18
5.82
33.18
25.73
19.63
13.70
9.83
7.63
WHEN TO LEAD OR FOLLOW?
197
subject to certain caveats identified by others, including the representativeness of
PIMS respondents (primarily Fortune 500 companies; see Anderson and Paine
1978) and the absence of nonsurvivors (Robinson 1984). Despite these limitations,
our analysis has direct relevance for PIMS-based explanations of mature-stage
pioneer advantages. We have shown that the presence of effective barriers-toentry significantly affects the performance of pioneers in both consumer- and industrial-goods industries. Thus, to maximize long-run share benefit from their
entry strategy, pioneers in growth-stage markets should emphasize the development of effective entry barriers. Moreover, firms considering pioneer entry
should carefully evaluate the projected success of potential entry-deterrence strategies.
The extent to which pioneers receive an incremental share advantage over early
followers depends on both industry type and end-user purchase amounts. On one
hand, low-purchase-amount consumer-goods pioneers appear to benefit from the
conjunction of (1) consumer uncertainty regarding quality and (2) low marginal
returns to incremental information search. On the other hand, high-purchaseamount industrial-goods pioneers appear to benefit from buyer switching costs,
technology franchises, and the formation of strategic alliances with customers.
These contingencies suggest that certain disadvantages linked with pioneer entry
(e.g., free-rider effects, subsequent shifts in technology or consumer needs; see
Lieberman and Montgomery 1988) assume greater importance in the entry decision of consumer-goods firms with high retail purchase amounts and industrialgoods firms with low retail purchase amounts.
Acknowledgments
The authors thank the Strategic Planning Institute for providing access to the
PIMS data base. The authors also thank John Norton, Don Lehmann, and two
anonymous reviewers for helpful comments on an earlier version of this paper.
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