Download Leapfrogging and profit maximizing new product

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Leapfrogging and profit maximizing
new product preannouncement timing
Joachim Büschken
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Leapfrogging and profit maximizing new product preannouncement timing
Diskussionsbeiträge der Katholischen Universität Eichstätt,
Wirtschaftswissenschaftliche Fakultät Ingolstadt
Nr. 143
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(ISSN 0938-2712)
Ingolstadt, Oktober 2000
Prof. Dr. Joachim Büschken
Lehrstuhl für Allgemeine Betriebswirtschaftslehre, Absatzwirtschaft und Marketing
Wirtschaftswissenschaftliche Fakultät Ingolstadt
der Katholischen Universität Eichstätt
auf der Schanz 49
85049 Ingolstadt
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Leapfrogging and profit maximizing new product preannouncement timing
This paper is concerned with the question when to preannounce the introduction of a
future product when a company whishes to maximize profits across product life cycles. Based on a model proposed by Lilly and Walters (1997) an extended framework
is developed to identify the determinants of new product preannouncement timing.
Attention is focused on individual buyer’s technological leapfrogging and the influence of postponed purchases on optimal new product preannouncement timing. For
that purpose a normative model is developed to analyze the influence of the determinants of new product preannouncement policy on preannouncement timing decisions.
It is shown that optimal preannouncement policy depends on the specific situation of
the company and the market it is operating in. Generally, to maximize profits across
product life cycles dominating players with product quality advantages should preannounce late whereas smaller suppliers should preannounce early to take advantage of
changing market position.
1. Introduction
Deliberately preannouncing the introduction of a new product has become commonplace
for suppliers in many industries (Lilly and Walters 1997). As such, new product preannouncing supplements innovation strategy (Robertson 1993, Singh 1997, Lilly and Walters
1997). Preannouncement timing is an element of strategic planning for technology products, which ranks highly among management issues of new product development (Scott
2000). As a strategic instrument new product preannouncement is used to (Bayus, Jain and
Rao 2000):
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deter potential competitors from developing similar products and/or
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induce buyers to postpone purchases in favor of the suppliers to be introduced product.
Recent research in these areas focuses on two questions: When should a firm preannounce
the later introduction of a new product (new product preannouncement timing: NPPT) (e.g.
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Lilly and Walters 1997) and with regard to competitive reaction to preannouncing what are
incentives for suppliers to preannounce untruthfully and what consequences result from
such behavior (e.g. Bayus, Jain and Rao 2000).
This paper is concerned with the question of optimal preannouncement timing in case of
truthful preannouncements. For the purposes of this paper it is assumed that suppliers do
not intentionally mislead market participants by new product preannouncements. Instead, it
is concerned with the influence of preannouncing new products on buying behavior and the
resulting profit implications. If truthful and successful NPP motivates some buyers in the
market for a “new product” (based on currently available, “new” technology) to postpone
purchase decisions in favor of some future, yet to be introduced product. Rational leapfroggers will perceive waiting to provide more utility than buying immediately. In general, suppliers will engage in NPP if they benefit from such postponed purchases. However, the relationship between the profitability of the resulting leapfrogging behavior and the determinants of NPPT is not clear. Research on that issue is not available.
Why is that issue relevant? Successful NPP results in reduced market volume for the new
product since some buyers postpone purchases. If the supplier considering NPP is a competitor in that market his own sales may immediately suffer due to NPP. The future product
cannibalizes the new product, since buyers may postpone purchasing any product based on
new technology. A trade-off results: NPP resulting in leapfrogging behavior is only beneficial if a suppliers additional future profits – as a result of the purchases of leapfroggers – of
a product based on future technology at least compensate for the reduction of profits from
his product based on new technology. This trade-off becomes relevant if the preannouncing
firm itself is in the market for new technology. Manceau and Bloch (1998) examine the
case of possible cannibalization and show that leapfrogging has a significant impact on a
firm’s innovation strategy.
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2. Leapfrogging and the determinants of NPPT
Technological leapfrogging in markets with high technological dynamics has attracted attention in various fields. A significant part of leapfrogging research has focused on technological leapfrogging of nations (e.g. Soete 1985, Sharif 1989, Brinkerhoff 1990, Hwang
and Tilton 1990, Mody and Sherman 1990). Although the actor under investigation is not
an individual – as in this paper – but an economy or nation, the notion of leapfrogging is
clearly the same. Some actor, e.g. deciders in a developing country, deliberately decide
against the adoption or repeated purchase of some new technology in favor of some future
and superior technology.
Prince (1997) provides an example of technological leapfrogging by nations referring
to the case of telecommunication infrastructure: “Leapfrogging the old technology and
familiar infrastructure developed over the past century developing countries are simply
skipping coaxial and copper cables. Customers will never know telephone poles, rotary
dials, interminable waits, and the old-fashioned “rinnnnnng” – the ancestor of today’s
blips and bleeps. That’s great news for the makers of cellular phones – or about anyone
else in the world from meat packers to bicycle manufacturers to insurers to purveyors
of fertilizers” (p. 12). He adds: “Leapfrogging has opened up worlds of opportunities,
but solid business intelligence and strategic planning will be required to take advantage
of them. Leapfrogging has also opened a can of worms that might just create competition from quarters heretofore unimagined” (p. 13).
The latter remark refers to the relevance of leapfrogging for competitive dynamics. Brezis,
Krugman and Tsiddon (1993) analyze the relevance of leapfrogging for the competitive
advantage of nations and show that leapfrogging process and product technology may explain the change of nations competitive position in the world economy. Former technological laggers adopt a new technology and surpass the current leaders. Brezis, Krugman and
Tsiddon (1993) conclude from their observations that this is possible if former leaders
wrongfully believe the future technology to be inferior based on their extensive and superior experience with the current technology and, thus, failing to see the true potential behind
it.
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Although nations and their whole economies differ in many respects from individual actors
researchers interested in individual buying behavior have soon realized the importance of
individual leapfrogging from supplier perspective. Weiss and John (1985) are among the
first to address this issue. Tang and Zannetos (1992) coin the term “leapfrog competition”
to underline the importance of its influence on innovation strategy. They show that leapfrogging – among other factors – can impose a significant barrier to investing in new technologies. With regard to the rapidly increasing competitiveness of third-world corporations
Young, Huang, and McDermott (1996) show that leapfrogging the stages of the internationalization process explains the success of Chinese multinational enterprises.
Lilly and Walters (1997) are the first to present a comprehensive NPPT framework and
address technological leapfrogging behavior in the context of competitor-related (potential
for damaging competitive reaction), product-related (cannibalization, stimulating development of supplements by competitors, innovativeness, and complexity), buyer-related
(switching costs, length of buying process, loyalty), and firm-related (timing of feature
freezing) NPPT determinants. With regard to possible cannibalization they note that it “can
dampen the sales and profit of the existing products” (p. 12). Accordingly, in their empirical study they find managers to preannounce late if they fear negative effects of leapfrogging to be significant. Their hypotheses suggest that the factors determining NPPT give rise
to a situation specific approach to optimal preannouncement timing.
Possible leapfrogging highlights the necessity to analyze the factors driving NPPT more
closely. The abovementioned trade-off between today’s and tomorrow’s profits in the event
of leapfrogging is driven by a multitude of factors. Besides the factors suggested by Lilly
and Walters (1997) the following additional factors seem to be relevant:
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as element of market-related factors:
The size of the market for products based on new as well as future technology. The
size of these markets depends on the number of units to be sold and the prices that
can be achieved. Together they determine the size of the markets in dollars. Market
size matters because the economic results from leapfrogging depend on the magni-
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tude of profit losses in the “new” market and the profit gains in the “future” market.
Possible price decay in both markets is relevant.
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as element of buyer-related factors
The individual propensity of buyers to postpone purchase is relevant with regard to
the potential market reduction in new technology. This propensity is driven by factors such as risk taking behavior, information, and purchasing objectives. A risk
averse buyer can be expected to rely more on what is currently available and proven
than promises from suppliers. A risk prone buyer may actively search for opportunities to put investment dollars to a more effective but later use than investing into
proven technology today and tying up his or her limited investment budget. Furthermore, the individual situation of each buyer determines the acceptance of postponing purchases. An industrial buyer’s broken down equipment must be replaced
immediately. Otherwise, in search for cost reductions in an otherwise perfectly
working production line another buyer may wait “just a bit” to achieve significant
process improvements with future technology otherwise impossible.
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as element of firm-related factors
The supplier’s share in the two markets in question determines his individual losses
and gains from leapfrogging. The smaller his share in the market for “new” products
and the larger his prospective share in the market for “future” products the more
there is to gain from leapfrogging and vice versa.
Based on these consideration and the framework developed by Lilly and Walters (1997) the
following extended model of NPPT is suggested:
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Competitor-related factors
Potential for damaging competitive reaction
Product-related factors
Cannibalization of firm‘s existing products
Ability to stimulate developments of complements
Innovativeness of new product
NPPA objectices
Complexity of new product
Propensity to leapfrog to future technology
Timing of new
product
preannouncement
Buyer-related factors
Avoidable consumer switching costs
Length of consumer buying process
Target audience
of NPPA
Category product loyalty
Firm-related factors
Timing of feature freezing
Market share in new and future technology
Market-related factors
Volume of market for new and future
technology
Introduction price and price decay of new
and future technology
Figure 1: Extended framework of the determinants of NPPT
based on Lilly and Walters (1997)
This model allows to differentiate between cause and effect of leapfrogging. Buyer’s propensity to postpone purchases and the innovativeness of the product – driving possible utility advantages – determine the extent of leapfrogging and, thus, the extent to which the
supplier’s own product is cannibalized. The market share (in units) and the prices that can
be achieved in both markets determine the profit of new and future products. Leapfrogging
shifts demand from the new to the future market and changes profits if market shares and
prices differ for the shifted volume. The following section of this paper is dedicated to
quantify the relationship between optimal NPPT and selected factors (shaded areas) in this
model. The objective is to analyze the influence of these factors on profit maximizing
NPPT.
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3. Model and Analysis
The following model is based on the assumption that suppliers wish to maximize profits
from a product based on “new technology” succeeded by a product based on “future technology”. For convenience, life cycles of these products do not overlap. To isolate the influence of leapfrogging the markets for both technologies are assumed to be identical. Specifically, the market size measured in units sold at each point in time of their life cycle is equal
if leapfrogging does not occur. For simplicity, the length of both products life cycles is assumed to be equal. This leads to the following result: if buyers leapfrog then the resulting
reduction in unit size for the “new” market” is equal to the total increase in unit size for the
“future” market. Let market size in units sold for “new products” be
M n (t) = t
( r1 )
1
for t<t1 and
M n (t) = (1 - a ) × t
( r1 )
1
for t³t1 with r1 being the growth rate of this market. The supplier selects preannouncing
time t1. Variable a denotes the percentage of leapfroggers that postpone purchases after the
future product is announced. Leapfrogging (a>0) occurs if the supplier preannounces the
introduction of the future product at t1<t2 with t2 being the end of the life cycle of the new
product. Leapfrogging is assumed to increase with the quality advantages that the future
product provides over the current alternative:
a = 1- e
(- )
Qz
Qn ×l
Variable l indicates the propensity of buyers to engage in leapfrogging. Note that for higher
values for l propensity to postpone purchases decreases. The supplier’s product quality is
given by Qz (future product) and Qn (new product). Future product quality is assumed to be
certain. Leapfrogging (a) increases with the quality of the supplier’s future product for any
positive l. However, leapfrogging cannot increase beyond the total market.
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Analogous to the market for new products the size of the market for future products in units
sold is given by
M z (t ) = t
1
r2
To ensure that both markets are initially identical consider that after t1 only (1-a) of new
product buyers remain in the market reducing market size after t1. Leapfroggers (a) transfer
their purchases into the market for future products. The growth rate of Mz (r2) must be
modified accordingly (see figure 2).
Units sold
New product
market without
leapfrogging
Future product market with
leapfrogging
A
New product
market with
leapfrogging
after t1
B
time
t1
t2
Figure 2: Market growth and leapfrogging
Since life cycles for new and future products are assumed to be of equal length we can limit
the analysis to a single life cycle if the supplier does not discount profits. The growth rate
for the future market (r2) must accommodate the demand shift from leapfroggers. Thus,
area B must be equal to area A in figure 2. If the shifted demand from new to future technology due to leapfrogging is the only difference between the two markets we can write:
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t2
òt
t1
1
r1
1
r1
t2
1
r2
1
r1
- (1 - a)t dt = ò t - t dt
0
Integration and solving this equation for r2 with t2=1 leads to:
r2 = -
1
r1
r1 ( - a +t1t1 a -1)
1
r1
- r1a +t1r1t1 a +1
The market share of the supplier in the market for future products is assumed to be determined by relative quality and the supplier’s marketing activities g (Cooper and Nakanishi
1988, Bayus 1997):
sz = g ×Qg z×Q+Qz zc
This market share is constant over the life cycle. Prices do not affect market share here because of competitors price taking. Product margin d is assumed to decline exponentially
over time (Bayus 1997):
d = m × e -e ×t
with decay rate e and market introduction price m. Price decay rates may differ between the
two markets.
For simplicity the length of both life cycles is set to t2=1. Fixed production and development costs are assumed to be irrelevant. The supplier maximizes profits by selecting preannouncement time t1. The following supplier’s profit maximization problem results:
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t1
1
r1
ò t × s n × mn × e
-e n ×t
0
1
1
r1
dt + ò (1 - a ) × t × s n × mn × e
t1
-e n ×t
1
1
dt + ò t r2 × s z × m z × e -e z ×t dt ® Max!
0
t1
Note that assumptions with regard to the life cycles of the two technologies as well as the
size of the two markets were made to isolate the influence of profit changes due to NPPT.
Thus, the model is designed to highlight the profit trade-off associated with NPPT. Shifting
demand from new to future products is always profitable if – all other influences being
equal – the market share in the future market and the average price for future products is
higher.
However, even this rather simple model shows that the profitability of demand shifts depends on a variety of factors that simultaneously determine optimal NPPT and the resulting
profits. The remaining part of this paper is dedicated to quantify the influences of the determinants of NPPT within the framework of the model. The goal is to explore how profitmaximizing NPPT is influenced by this model’s variables for two scenarios.
Scenario A:
Your company tends to dominate the market for products based on new technology.
Your only competitor is significantly smaller in terms of units sold. Your company
competes on the basis of strong quality and will either match but more probably exceed the competitor’s quality of future products. The market tends to be stable. The
introduction price for future products may vary, but not greatly. Marketing has a relatively small influence on your market share. Customers are quality driven.
Scenario B:
Your company tends to be dominated by your competitor. The quality of your product based on future technology may match or exceed the competitor’s product but you
may end up with quality disadvantages with equal probability. The market for future
products is less stable. Introduction prices can vary greatly as well as the influence
marketing has on your market share. Thus, perceptions play a greater role than in
scenario B.
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For both scenarios it is assumed that buyers propensity to leapfrog to future products varies.
Growth rate and price decay rate in the market for new products as well as the price decay
rate for future products can vary greatly. In both scenarios market share does not change
within the life cycle of each technology. Both competitors will introduce products based on
future technology at the same time. No player has a monopoly at any time. This places
leapfrogging always in a competitive situation. If a monopoly for some time (until the
competitor follows your company) is possible the following model underestimates profits.
For each scenario a total of 8,748 cases were simulated with the following values for independent variables:
Scenario B
Scenario A
Variable
Quality of future
product
Qz
Propensity of buyers to
leapfrog
l
Growth rate of market for
new product
r1
Price decay of new product
en
1; 2; 3
1; 2; 3
Price decay of future
product
Market share of new product
ez
1; 2; 3
sn
0,6; 0,7; 0,8
0,2; 0,3; 0,4
Marketing support
g
0,8; 1; 1,2
0,5; 1; 1,5
Introduction price for
Future product
mz
0,8; 1; 1,2
0,5; 1; 1,5
8748
8748
Number of cases
1; 2; 3
0,5; 1; 1,5
10; 15; 20; 25
Figure 3: Computed values for determinants of NPPT
For each of the resulting 17,496 cases the profit maximizing NPPT decision and resulting
profits were calculated. For all simulations mn, Qn and Qzc were set to 1. Independent variables were then regressed on optimal NPPT and resulting profit with a standard linear regression model for both scenarios. With 87 % (76 %) of the variance of NPPT and 93 %
(86 %) of the variance of profit explained the linear regression model reasonably fits the
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model for scenario A (B) (see figures 4 and 5). All coefficients are significant at the 0 level.
According to the F-values the model cannot be rejected.
The mean (median) optimal NPPT for scenario A is 0.434 (0.4). That means that after 43 %
of the life cycle of the new product it is optimal for the supplier in scenario A to preannounce the introduction of the product based on future technology. This result may explain
why it is commonplace in dynamic industries even for larger players to preannounce early.
Even moderate price decay gives rise to the necessity to shift demand to future products for
which higher prices can be achieved. However, the wide range of values for variables in
scenario A creates significant variance in optimal NPPT. In 5.4 % of all cases in scenario
A a simultaneous introduction of the new product and preannouncing the future product is
profit maximizing. No preannouncement is optimal in 10.2% of all cases in scenario A.
Variable
Optimal NPPT (t1opt)
Quality of future
product
Qz
Propensity of buyers to
leapfrog
Profit
- 0,341 (-89,72)****
0,250 (90,65)****
l
0,022 (5,86)****
- 0,031 (-11,13)****
Growth rate of market for
new product
r1
- 0,154 (-40,47)****
0,599 (216,90)****
Price decay of new product
en
- 0,628 (-165,23)****
- 0,447 (-161,96)****
Price decay of future
product
Market share of new product
ez
0,416 (109,53)****
- 0,483 (-174,76)****
sn
0,226 (59,39)****
0,145 (53,53)****
Marketing support
g
- 0,111 (-29,24)****
0,078 (28,35)****
Introduction price for
future product
mz
- 0,319 (-89,94)****
0,226 (81,77)****
r2
0,87
0,93
F
7,555.66 ****
15,601.07 ****
Figure 4: Regression results for scenario A
(t-statistics for standardized regression coefficients in brackets)
Standardized regression coefficients for scenario A show that for a dominant player in a
stable market the price decay rate in the market for new products is by far the strongest
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determinant of NPPT. Higher price decay leads to smaller values of NPPT, i.e. earlier
NPPT. This is because larger players are hurt more by reduced margins in total profit dollars. To a lesser extent this is also true for price decay in the market for future products.
However, high price decay of future products suggests later preannouncement (higher values of NPPT) to secure profit potentials in the market for new products. High future product quality and introduction price – ranking number 3 and 4 in importance as determinants
of NPPT respectively – suggest earlier preannouncement to shift demand to the more profitable market for future products.
Looking at profits we find that the “new” market’s growth rate and price decay rates for
both technologies are the strongest determinants of the supplier’s profits in scenario A. It is
interesting to note that as long as the supplier maintains a competitive advantage in terms of
product quality this quality ranks not among the strongest determinants of NPPT and profits. This means that larger quality advantages do not influence both optimal NPPT as well
as profits greatly. The latter result may change with variable costs of quality.
To summarize results we find that for a dominant player in a stable market early preannouncement inducing buyers to postpone purchases and to leapfrog to the future technology
is profit maximizing if:
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the growth rate of the market for new technology is small,
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the price decay rate of future products is high,
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the quality of the suppliers future product is high,
-
the introduction price of future products is high,
and vice versa.
For scenario B we find different results. The mean (median) profit maximizing NPPT in
this scenario is 0.265 (0.14). Thus, compared to scenario A earlier preannouncement is optimal. In 42 % of all cases analyzed for scenario B we find that simultaneous introduction
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of the new product and preannouncing the later introduction is optimal. In 7.4 % of the
cases no preannouncement is the profit maximizing strategy.
This rather extreme result highlights that leapfrogging can be a profitable option for smaller
companies. However, the introduction price for future products becomes highly critical as
the regression result show (see figure 5). The higher the introduction price the earlier is the
introduction of the future product to be announced. One might say that for a small player it
is worthwhile to bet on the future market. His overall profit potential increases if he can
shift demand to a market in which a high introduction price can be expected. High future
product quality and high price decay in the market for new products support early NPPT
strategy.
Optimal NPPT (t1opt)
Variable
Quality of future
product
Qz
Propensity of buyers to
leapfrog
l
Growth rate of market for
new product
Profit
0,292 (73,27)****
- 0,305 (-58,49)****
0,008 (1,6)****
- 0,023 (-5,87)****
r1
- 0,104 (-19,88)****
0,430 (107,99)****
Price decay of new product
en
- 0,318 (-60,84)****
- 0,252 (-63,29)****
Price decay of future
product
Market share of new product
ez
0,249 (47,66)****
- 0,427 (-107,14)****
sn
0,311 (59,5)****
0,187 (46,89)****
Marketing support
g
- 0,294 (-56,34)****
0,269 (67,48)****
Introduction price for
future product
mz
- 0,558 (-106,94)****
0,488 (122,65)****
r2
0,76
0,86
F
3,492.63 ****
6,792.78 ****
Figure 5: Regression results for scenario B
(t-statistics for standardized regression coefficients in brackets)
The difference between scenarios A and B lies in the profitability of the market for new
products. The smaller player has less to loose and more to win if he is successful in inducing buyers to postpone purchases. Future products offer the chance to increase market share
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on the basis of higher quality and if this market share goes along with higher prices – until
price decay hits the market severely – leapfrogging becomes a veritable option. The contrary is true for the dominant supplier. He has more to loose than to win, especially if prices
in the “new” market to not decline rapidly and he can expect his market position in the
market for future products also to be strong because of high product quality. In such a position early NPPT reduces profits.
Thus, for a smaller supplier in a market with less stability and the possibility of quality disadvantages we find that early NPPT is profit maximizing if:
-
the introduction price for products based on future technology is high,
-
the quality of future products is high,
-
price decay in the market for new products is high,
-
and his marketing support for future products is high,
and vice versa.
Looking at profit drivers we find that the quality of future products has a positive influence
in both cases. Surprisingly, the propensity of buyers to postpone purchases itself is a marginal profit driver. It seems that not the demand shift alone is crucial for profits but the degree to which a company can participate profitably in that shifted demand. This participation is driven by market share and prices. For both scenarios market growth rates – note
that r2 is determined by r1 in the model – are crucial profit determinants (even more so for
the larger supplier because of his larger participation in the market). The smaller competitor
is considerably less hurt by high price decay in the “new” market. We might say that under
such circumstances smallness can be a virtue if that smallness can be transformed into a
better market position in the future market. Both types, however, are hurt massively by
price decay in the – more profitable – “future” market. Even the smaller player placing a
bet on that market by inducing buyers to leapfrog will then find his strategy to fail. In order
not to let his aggressive preannouncing strategy fail he must be reasonably sure that the
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future products introduction price is high enough to compensate him for the lost demand in
the “new” market. To achieve that an introduction price two to three times higher than the
introduction price of the new product is necessary. He may support his preannouncement
strategy by emphasizing marketing support for the future product. Marketing, however, is
of considerably smaller influence than price.
4. Discussion and Conclusions
This paper identifies conditions associated with optimal NPPT decisions. The findings are
limited to the assumptions of the underlying normative model. The main purpose was to
quantify the influence of determinants of optimal preannouncement timing. Preannouncement timing is relevant if demand shifts as a result of leapfrogging effect the firm’s profit
position across product life cycles. Certain assumptions (identical life cycles and market
size) were made to isolate the influence of demand shifts on profit maximizing NPPT.
The results of the simulations are based on the assumption that competitors announce truthfully. The resulting demand shift from the “new” to the “future” market also implies that
credibility of supplier’s preannouncements is not a problem. However, early preannouncement may not have the same effect as late preannouncement. Quality promises made by
preannouncing suppliers may be more credible to buyers and, thus, relevant to purchasing
behavior if actual product introduction is near reducing the number of leapfroggers with
earlier leapfrogging. This effect is not modeled here. If perceived credibility plays a role
later NPPT results. The tendencies found here, however, are not affected. Also the magnitude of that demand shift is assumed to be independent from NPPT. This assumption seems
somewhat unrealistic if life cycles are long. Longer life cycles force leapfroggers to forsake
benefits derived from the new technology – whether initially adopted or repeatedly purchased – for a longer time. However, in markets with rather short life cycles such forsaken
benefits are smaller and therefore less important.
To increase profit by intentionally inducing buyers to leapfrog through NPP implies that
managers are long-term profit oriented. The model presented here is based on the assump-
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tion that the firm maximizes profits over the life cycles of both technologies. Short-term
profit orientation changes NPP strategy. On the short run leapfrogging always reduces market size and profits. The market for future products may be too far “away” to provide necessary profit compensation. Thus, a short-term view will lead to either late or no preannouncements. On the other hand if a firm introducing an innovation can create a monopoly
situation until it is followed by a competitor this will lead to earlier preannouncements. The
firm can then extract higher unit sales from the market for future products in stages of relatively higher prices.
The results derived from the model suggest that optimal NPPT is a situation-specific problem. Figure 6 highlights the results:
Dominant player
No NPP
Late NPP
Fluid Market
Stable market
Early NPP
Sim. NPP
Small player
Figure 6: Simulation results
Being a dominant player strongly suggests a “Now-is-Now-Strategy” in which emphasis is
on current profits derived from the “new” market. This strategy is consistent with late or no
preannouncing. If the market for the future product promises to be stable in terms of price
decay and in terms of the influence of product quality on market share then this supports
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late NPPT. “Now-is-now” highlights that there is less to win from leapfroggers than to
loose.
For the smaller player with ambitions to grow into the role of a dominant player by innovation that surpasses the competitor’s quality a “Placing-the-Bet-Strategy” is suggested.
Placing the bet means to accept the initial losses due to leapfroggers leaving the market for
new products and to bet on their reentry into the market for future products. The smaller
player can profit from that greatly. These profits are to a large degree subject to the introduction price of future products that this player may not control. If that innovation offers,
however, the opportunity to raise prices significantly then early preannouncing is a veritable option. This can even lead to simultaneously introducing a new product and announcing
the later introduction of a future product even if this strategy takes large numbers of leapfroggers out of the current market for a long time.
Simulation results show that buyers’ propensity to leapfrog and the resulting demand shift
are not crucial determinants of optimal NPPT. Crucial are the profit implications. They
depend on the profit potential shifting from the “new” to the future” market. Suppliers’
market share and prices at earlier stages of the future market and later stages of the new
market seem to be more important than the degree to which buyers are ready to postpone
purchases.
Note that results are derived from a model in which credibility of suppliers’ preannouncements – specifically in terms of the preannounced quality of future products – and NPPT
lead-time are irrelevant. If relevant, both would reduce NPPT lead-time (i.e. later NPPT).
Also competitive reaction to other supplier’s preannouncements is not considered here. The
more successful the smaller player’s (early) NPPT strategy is the more we must assume that
larger competitors will react. It would be interesting to look at the question what kind of
reaction is necessary to keep potential leapfroggers in the “new” market.
22
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