Dwelling in the Shadowlands:
Technology Shadowing as a Strategic Choice
I-Chen K. Wang
College of Business
University of Illinois at Urbana-Champaign
350A Wohlers Hall
1206 South Sixth Street
Champaign, IL 61820
E-mail: [email protected]
Hsiao-shan Yang
Institute for Genomic Biology
Business, Economics and Law of Genomic Biology (BioBEL)
University of Illinois at Urbana-Champaign
2122 IGB, MC-195
1206 West Gregory Drive
Urbana, IL 61801
E-mail: [email protected]
April 23, 2012
Dwelling in the Shadowlands:
Technology Shadowing as a Strategic Choice
Abstract
Much of the technology strategy literature focuses on firms at the technology frontier. There is a
need, however, for better theoretical understanding about the circumstances in which a
technological laggard is more likely to shadow the current technological leaders, rather than seek to
become the new technological leader. This study theoretically develops well-grounded hypotheses,
which suggest that an increase in the number of a firm's interfirm relationships with technological
leaders encourages it to choose a shadowing strategy, and an increase in the number of technological
leaders discourages a firm from choosing a shadowing strategy. Furthermore, the negative effect of
the number of technological leaders on a firm’s likelihood of choosing a shadowing strategy is
stronger when it has more interfirm relationships with technological leader. This research study
empirically tests these hypotheses in the context of the flat panel display industry.
Keywords: competitive dynamics, technological shadowing, interfirm relationships
Introduction
Technology competition behind the technology frontier 1 has recently received more
scholar attention, because there are more firms behind the technology frontier than those at the
technology frontier (Grenadier and Weiss, 1997; Robertson, Eliashberg, and Rymon, 1995). As
suggested by firm capabilities literature, firms that at the technology frontier generally have
better capabilities than those behind (Khanna, 1995; Lerner, 1997). Yet, among firms that are
behind the technology frontier, some may be technologically capable of taking the leadership at
the technology frontier but strategically choose a position behind the technology frontier
(Sudharshan, Liu, and Ratchford, 2006). For firms choosing this particular position, we
considered it adopting a technological shadowing strategy. Firms that choose a shadowing
strategy are still technological laggards; however they are very different from other technological
laggards that are further behind the technology frontier (Chatain, 2010; Lee, Kim, and Lim, 2011;
Pacheco-de-Almeida and Zemsky, 2012).
[Insert Table 1 about here]
Table 1 reports how firms change their status from one year to another in the flat panel
display industry. Our focal of analysis is the firms that shadow the technological leaders. Of
firms already choose to shadow the technological leaders, 43% of them continues to do so in the
next year. Although behind the technology leaders, the focal firms are very close to them. The
distance is so close that the focal firm can catch up, or even leapfrog the technological leaders
with the next generation technology (Aghion, Harris, and Vickers, 1997; Encaoua and Ulph,
de Figueiredo and Teece define the technological frontier as "a component or service being procured which
enlists technology that is not ubiquitously employed in the industry. Frontier technologies are those leading
edge innovations being incorporated into subsystems and components" (1996: 545, footnote 5). Thus, the
technology frontier in this study represents the most advanced technology available in the market (Agarwal,
Echambadi, Franco, and Sarkar, 2004; Christensen, 1997; de Figueiredo and Kyle, 2005).
1
1
2004). Even for technological leaders, 35% of them chooses a technological shadowing strategy
in the next year. Psychological sunk cost may be one of the key reasons explains why a firm
changes from technological leading to shadowing (Tang, 1998). Limitations of technological
capabilities can prelude a firm's possibility of maintaining technological leading, or even
leapfrogging the technological leaders (Schilling, 2003). However, technological capabilities
alone may not fully explain the reason why shadowing firms remain shadowing as its response to
technological race (Tsai, Su, and Chen, 2011; Sirmon, Hitt, and Ireland, 2007). Hence, although
technological shadowing is a type of technological lagging, this strategy is special as not all
laggard firms choose it.
Despite the recent attention to technological laggards, studies developed to explain why
some firms choose to shadow the technological leaders have been scarce. This paper is able to
fill the literature gap by focusing on firms who shadow the technological leaders as a strategic
choice. In an attempt to use theories to develop related contingencies, we ask the following
research question: Under what circumstances will a firm be more likely to choose to shadow the
current technological leaders, rather than seek to become a new technological leader?
The purpose of this study is to highlight contingencies that affect a firm’s decision
whether to shadow the technological leaders. At the firm-level, interfirm relationships with
technological leaders allow a firm to appropriate the frontier technology with lower
technological uncertainties (Ahuja, 2000; Chatain, 2010; Dyer and Singh, 1998; Singh and
Mitchell, 2005). In order to carry on appropriating value of frontier technology, a firm with
interfirm relationships with technological leaders is more likely to shadow the technological
leader. At the environment-level, the number of technological leaders is likely to influence the
economic value that the focal firm can appropriate from the technological leaders’ technology.
2
Market uncertainties are high because the variability of technology acceptance in the market is
high (Huchzermeier and Loch, 2001; Oriani and Sobrero, 2008). When the number of firms
commercializing the technology increases, positive externality not only incentivizes incumbent
participation (Andreoni, 1995), but also might motivates more entries to the technological
frontier. As such, a firm is thus less likely to shadow the technological leader. When both firmand environment-level characteristics are considered, the number of technological leaders is
likely to negatively moderate the effect of interfirm relationships with technological leaders on a
firm’s likelihood of choosing a shadowing strategy. The competition at the technology frontier is
likely to lower the technological and market uncertainties that discourage a firm to shadow the
technological leader.
Contributions
The extant literature is largely silent about phenomenon behind the technology frontier,
and hence overlooks strategic sweet spots that are rarely related to the technological leadership
(Fudenberg and Tirole, 1985; Jensen, 2003; Macierira, 2006). This study contributes to the
technology management literature by giving attention to the region of the shadowlands in which
a firm strategically remains behind the technology frontier. More specifically, this paper
contributes to technology competition studies. In building the theory for technology race, we
highlight factors that that inhibit a firm from racing to the technology frontier (Chen et al., 2010).
It explains why, despite strategic advantages of having technological leadership, the trade-off of
technological and market uncertainties become strategic advantages of being behind the
technology frontier. Lastly, this paper connects two streams of literature--interfirm relationships
and technology management studies. Research on the impact of interfirm relationship upon a
firm's behavior in technology race has been scarce, and is mostly conceptual or empirical study
3
using cross-sectional study design (Cui, Calantone, and Griffith, 2011; Doz, 1996). This study
employs a panel dataset to test hypotheses on how interfirm relationships alter firm behavior in
technology race. Now that the contributions have been stated, the next paragraph provides key
definitions of the building blocks of this study.
Model
To simplify the model of technological race among firms in the leading group, we focus
on two firms, i.e. Firm 1 and Firm 2. We assume that technological capabilities are homogeneous
among these two firms, and they are both technologically capable to compete at the
technological frontier. Furthermore, market technological uncertainties in the product market are
exogenously given. There are two positions for firm to pick when they move forward in the
technological race, which includes positions to lead (L) or to shadow (S). Let firm ’s action be
, and firm ’s payoff equals revenue,
, for
, minus cost,
, for
. The revenue
, is not only determined by actions of both firms, but also we assume that
the revenue is a function of market uncertainties, , which measure the consumer’s acceptance
of the product.
includes the fixed and production cost, as well as R&D expenditure that is
paid in order to lead, and
is the cost to shadow. Following the assumptions, Table 1 lists the
payoff matrix for the technology race in the leading group. Firm 1’s payoff is at the up-left
corner, while Firm 2’s payoff is at the lower-right corner in the box.
[Insert Table 2 about here]
In this model, the market structure is exogenously determined by the state of all firms in
the market. According to the payoff matrix in Table 1, two conditions would guarantee
shadowing to be the dominant strategy when a firm’s opponent decides to lead.
4
(1)
(2)
Technological uncertainties are typically an important factor in a technology race. Higher
technological uncertainties would be more likely to cause higher cost, especially in R&D
expenditure. The interfirm relationships allow a technological laggard an access to the
technological leader's innovation. Through the interfirm relationships, such as technological
licensing and joint venture, a technological laggard can appropriate the innovation of
technological leader without develop the same technology internally, that is, being a shadower
allows a firm to use the interfirm relationship to reduces its costs. Henceforth, a common
assumption can be made that
.
Besides technological uncertainties, intensifying market competition usually reduces the
revenue that a firm can gain from its innovation. The market competition often leads to price war
that a firm tends to price its innovation at lower rate in order to maintain its presence in the
market. Hence, the leading firm would be better off if its opponent is shadowing, comparing to
the outcome that both firms decide to compete at the leading position or shadowing position.
Thus, this implies the inequality,
, given
the same. In addition,
there would be no firms competing in the technology race with the absence of potential
economic rent. Therefore, we should be able to further assume that
However, whether
or
.
holds is not clear without
considering the market condition. For instance, if the technological frontier is still with high
market uncertainties, then competing at the technological frontier not only induces high costs,
but also ends up with an unsure revenue. Therefore, with high market uncertainties, a firm is
likely to shadow the technological leader, rather than to lead, i.e.
5
. On the
other hand, it is possible that
if the low market uncertainties could guarantee
enough market shares to profit better than shadowing.
In a market with high market uncertainties, Inequality (1) holds because
and
. In addition, Inequality (2) should also be true. If no so, then no firms
have incentives to compete at the technology frontier. We find that theoretically shadowing is a
dominant strategy under certain market conditions. In Table 2, four types of market
environments are shown by considering both dimensions of technological and market
uncertainties. Firms is likely to be benefitted from shadowing when the market is at the high
innovation technological regime, and under high market uncertainties,
[Insert Table 3 about here]
Hypothesis development
Technological uncertainties
Technological uncertainties are high when it is unclear whether the technology can
deliver the expected performance (Tushman and Rosenkopf, 1992; Tegarden, Hatfield, and
Echols, 1999; Anderson and Tushman, 2001). The interfirm relationships with technological
leaders often allow the focal firm to reduce technological uncertainties, at least in a shorter time
(Lin and Chen, 2002). First, the interfirm relationships with technological leaders usually
provide a channel from with the focal firm can source the frontier technology (Hagedoorn, 1993).
The focal firm is able to use the knowledge from the technological leaders, and perhaps produces
few mistakes so that it can move down the learning curve quicker than other firms without such
an access (Eeckhout and Jovanovic, 2002; Lieberman and Montgomery, 1988). Second,
technological uncertainties are even higher when a firm develops the new innovation. Innovation
is usually a costly process of trial and error. The interfirm relationships with the technological
6
leaders can lower technological uncertainties that the focal firm may face (Dussauge et al., 2000;
Dyer and Singh, 1998; Eisenhardt and Schoonhoven, 1996; Mowery et al., 1996). Based on the
technological leaders’ experience with the frontier technology, the focal firm usually can source
technologies that have been tested and proven to achieve expected performance. This second
mover advantage allows the focal firm to have a less costly innovation process (Dutta et al., 1995;
Hoppe, 2000).
That is, an interfirm relationship allows the focal firm to appropriate the value of
technology that the technological leader owns (Ahuja, 2000; Chatain, 2010; Dyer and Singh,
1998; Eisenhardt and Schoonhoven, 1996; Kumar, 2010; Singh and Mitchell, 2005). If the
interfirm relationships cease to continue, the focal firms may encounter technological difficulties.
The technological challenge is, after years' reliance on technological leaders’ technology, the
focal firm may lack technological capabilities and routines to develop similar technologies inhouse (Cui et al., 2011; Nelson and Winter, 1982; Sirmon et al., 2010). Hence, in order to
continue the value appropriation, the focal firm is reluctant to perform a conduct that would put
its relationship with the technological leaders in jeopardy (Borys and Jemison, 1989; Markman,
Gideon, and Phan, 2009). A high number of interfirm relationships that the focal firm has with
the technological leaders suggest high value dependency that the focal has towards the
technological leaders. Because of value dependency, the focal firm is likely to shadow the
technological leaders.
Hypothesis 1: A firm’s likelihood of choosing a shadowing strategy increases with its
number of relationships with technological leaders
7
Market uncertainties
When there are a handful of firms commercializing the latest technology, the market
uncertainties are likely to be very high because the industry collectively knows little about the
technology's market acceptance. When there are more technological leaders commercializing the
frontier technology, the industry as a whole is likely to accumulate more market knowledge and
information about the frontier technology, such as how to market it, who is target user, what are
product applications 2 . The knowledge and information about commercializing the frontier
technology is likely to increase the positive externality. Given the increase in positive externality,
the focal firm is more likely to commercialize the frontier technology (Andreoni, 1995).
Furthermore, the focal firm can learn how to market the frontier technology from observing the
technological leaders. When there are more technological leaders commercialize the frontier
technology, the focal firm is better able to conclude the pattern of competition, and hence
accumulate more knowledge about managing market uncertainties (Gans and Stern, 2003;
Khanna, 1995; Smith et al., 2001). In addition to generating knowledge by observing
technological leaders, the focal firm can directly gain knowledge from technological leaders
(Eeckhout and Jovanovic, 2002; Jovanovic and MacDonald, 1994; McGahan and Silverman,
2006).
Knowledge spillovers at the technology frontier are likely to increase when there are
more technological leaders commercializing the frontier technology. The knowledge spillovers
can be done intentionally by technological leaders. Market competition at the technology frontier
is likely to be more intense when there are more technological leaders. In order to strengthen its
For instance, Eli Lilly introduces a supreme breakthrough insulin product in 1980 that receives poor
market acceptance. Not only customers do not like it but retailers are also reluctant to add it to their already
crowded shelf.
Source: Eli Lilly and Company: Innovation in Diabetes Care, Harvard Business case 9-696-077 by C.
M. Christensen, 2004.
2
8
market position, technological leaders are more willing to release its frontier technology to rival
firms so as to deter entry (Gallini, 1984; Pacheco-de-Almeida and Zemsky, 2012), and increase
the adoption of the leader’s frontier technology (Arora and Fosfuri, 2003). Therefore, the focal
firm is more likely to transfer the frontier technology from the technological leaders (Hagedoorn,
1993). Knowledge spillovers at the technology frontier can be unintentional as well. When there
are more firms commercializing the same (or very similar) technology of the highest generation,
knowledge are more likely to leaks out to other firms. Unintentional knowledge spillovers may
allow the focal firm to have second mover advantages to quickly move down the learning curve
(Dutta et al., 1995; Hoppe, 2000). Also, suppliers who participate in technological leaders’
innovation can be another source of leakage. Suppliers usually serve many firms in the industry,
including technological leaders and non-leaders. The focal firm can pick up the knowledge from
the suppliers of technological leaders (Acemoglu, Aghion, and Zilibotti, 2003).
Lastly, the increase in the number of technological leaders often suggests that an
increasing number of technological laggards change to a leading position by moving to a new
position that is at the technology frontier. The focal firm may change its behavior as suggested
by herd behavior (Debruyne and Reibstein, 2005; Livengood and Reger, 2010). In this sense, the
focal firm may follow its peer to the technology frontier. Hence, the increase in the number of
technological laggard encourages the focal firm to obtain a leading position.
Hypothesis 2: A firm’s likelihood of choosing a shadowing strategy decreases with the
number of technological leaders
9
Competitive dynamics
In Hypothesis1, the potential losses of appropriable technology value are the key factor
that encourages the focal firm to shadow the technological leaders. If the focal firm moves to the
technology frontier, technological leaders may competitively respond to it by ceasing the
interfirm relationships, stopping the focal firm to continue appropriate the value of the
technological leaders’ technology. To better reflect competitive dynamics, Hypothesis 3
considers the scenario in which the number of technological leaders increases. When there are
more technological leaders, the focal firms potentially have more sources to acquire the frontier
technology, and consequently bargaining power of supplier (i.e., technological leaders) is likely
to be lower (Kogut, 1988). The focal firm is less likely to be deterred by retaliation made by the
technological leader with whom it has interfirm relationships (Quintana-Garcia and BenavidesVelasco, 2004). Furthermore, the competitive response literature suggests that undertaking a
leading status is a visible action that is especially well received by technology leaders. Usually,
the visibility increases the competitive response that deters the focal firm from moving to the
technology frontier (Chen and Hambrick, 1995; Chen, 1996). Yet, when the number of
technological leaders increases, competition at the technology frontier is more intense and the
economic gain of initiating competitive responses decreases (Hoppe, 2000; Katz and Shapiro,
1987). The reason being when there are already a number of firms presenting at the technology
frontier, the economic loss due to new rivals is likely to be marginal. Hence, the technological
leaders may not have enough economic gains from initiating competitive responses (Chen et al.,
2010). Additionally, when competition at the technology frontier increases, the technological
leaders may be more inclined to maintain interfirm relationships with rival firms in order to
enhance its market power (Hagedoorn, 1993; Park and Russo, 1996).
10
In sum, an increase in the number of technological leaders is likely to negatively
moderate the effect of interfirm relationships with technological leaders on the focal firm’s
likelihood of choosing a shadowing strategy.
Hypothesis 3: The number of technological leaders negatively moderates the relationship
between the number of relationships with technological leader that a firm has and its
likelihood of choosing a shadowing strategy
Methodology
We test our hypotheses using data from the flat panel display industry. Some studies have
adopted the flat panel display industry to study innovation (Eggers, 2009; Linden, Hart, and
Lenway, 1997; Mathews, 2005; Spencer, 2003). The flat panel display industry provides several
empirical advantages. First, plant generation is a proper proxy for a technological laggard's
technological capabilities. Such a classification also facilitates the operationalization on the
technology frontier, defined by the highest generation of the industry. Second, the flat panel
display industry is one of the fastest growing industries. The fast pace in innovation enables
researchers to capture more observations in a relative short period of time. (Cho, Kim, and Rhee,
1998; Christensen, 1997). Third, with rapid speed of technology advancement, there are more
firms positioning behind the technology frontier, providing the dataset enough variances in terms
of technological capabilities.
We collect data from industry reports published by Japanese and Taiwanese research
houses. The data range from 1991 to 2010, and are comprised of global flat panel display makers.
This part of dataset includes firm-level information such as plant generation and production
value. In addition, we collect patent data from Delphion database. Interfirm relationships data are
11
collected by using key word 3 search from Lexis-Nexis and information contained in annual
reports. Within Lexis-Nexis, the major sources reporting interfirm relationship announcements
are Digital Times (Taiwanese news source), Korea Times (Korean news source), and The Nikkei
Weekly (Japanese news source).
Because the flat panel display industry does not have the second generation until 1995,
the firms before 1995 all have zero distance to the technology frontier, and hence are all
technological leaders by definition. Hence we decide to limit the dataset observations that are
after 1995, because a shadowing strategy is not possible in practice before 1995.
Our dependent variable is binomial, equal to 1 when the focal firm shadows the
technological leaders; otherwise it is equal to 0. We define firms that are equal or less than one
generation behind the technology frontier as technological leaders. Behind the technological
leaders, firms that are equal or less than two generations are considered shadowing the
technological leaders-- our focal firms. Firms whose generation is more than two generations
behind the technology frontier are considered technological laggards 4 . In order to address
endogeneity issue, we forward the dependent variable by one year.
The first independent variable is the number of interfirm relationships with the
technological leaders. It is the number interfirm relationships that the focal firm has with
technological leaders in a given year. The second independent variable is the number of firms at
Key words we use include: acquisition, alliance, cross licensing, joint development, joint venture, licensing,
partnership, patent sharing, plant sold, and technology transfer.
3
Each plant generation has its market segment. For instance, the higher generations plant produce larger
panels for home entertainment TV and outdoor display; while the lower generations plant produce smaller
panels for mobile devices. Technically, larger panels can be divided into smaller panels, and hence a higher
generation plant can compete with a lower generation plant. A higher generation plant usually has lower yield
than a lower generation. The high yield of a lower generation plant allows a firm to produce small displays
more cost effectively. Although the yield for higher generation plant tends to be lower, a higher generation
can produce larger displays that have better price margin.
4
12
the technology frontier. It is the number of technological leaders in a given year. The third
variable is the interactive term of the first and second variable.
We control for other firm and environment characteristics that may affect a firm’s
likelihood of choosing a shadowing strategy. First, we control firm age, the number of year that
the focal firm has spent in the flat panel display industry. Second, in order to control a firm's
organizational capabilities and market power, we add control market share, the percentage of the
focal firm’s annual production value of the industry total in a given year. Third, current
generation is the highest generation that the focal firm has in a given year. Forth, patent stock is
the accumulated patent count that the focal firm has since its entry to the flat panel display
industry. The patents are limited to International Patent Class F21V, G02F, G09G, G09F, H01J,
H01L, H04N, H05B, and H05H (Hoetker 2001; Spencer, 1997). Fifth, a firm’s experience at the
technology frontier is likely to affect its willingness to shadow the technology leaders. We
control this firm characteristic by adding a variable, defined by the number of months that the
focal firm shared the same generation as the industry’s highest generation. Sixth, firm size often
represents the focal firm’s market power (Adner and Zemsky, 2005; Demsetz, 1973; Mas-Ruiz
and Ruiz-Moreno, 2011). We add a variable, defined by the focal firm’s production value in a
given year. Seventh, we add a dummy recently gained leadership, to control aspiration effect
(Audia and Greve, 2006; Greve, 1998); the variable is equal to 1 if the focal firm recently gained
a position that is equal or less than one generation behind the technology frontier. Eighth, we add
two control variables to capture the focal firm’s experience with technological leaders.
Relationship duration with the same technological leader is defined as the number of year that
the focal firm has had with a given leader in a given year. Relationship experience with
technological leaders is a dummy equal to one if the focal firm has experience in interfirm
13
relationship in the past; 0 otherwise. Ninth, we add recent move to control the effect of
psychological sunk costs due to recently built plant on a firm's next plant building decision (Lee
et al., 2011; Livengood and Reger, 2010). Lastly, and the tenth, is an environment characteristic.
Firm behavior may change with the industry’s demand (Derfus et al., 2008). Hence we control
for industry growth, defined as the percentage change that industry’s total production value has
from the last year.
Our empirical model is a two-stage random effect logistic model. In order to discern the
move that shadowing as a strategic choice (rather than due to the capability limitation), we first
control firm i’s capabilities that may decide its position behind the technology frontier. In the
first stage, we have the following model for the focal firm i:
Lagging equals to 1 when firm i is more than two generations behind the technology frontier;
otherwise it is equal to 0. The result is listed as Model 1 in Table 5.
Using the first-stage model, we are able to generate Inverse Mill ratio, and use it to the second
stage as a control for the focal firm’s capabilities. In the second stage, we have the following
model for the focal firm i:
Shadowing equals to 1 when firm i is equal or less than one generation behind the technological
leaders; it equals to 0 when firm i is a technological leader with no more than one generation
behind the technology frontier. This is Model 2 in Table 5.
14
Results
[Insert Table 4 about here]
Table 4 reports summary statistics. Please be noted that only 22.16% of firms has
interfirm relationships with technological leaders, and about 8% of firms has more than one
interfirm relationships with technological leaders.
[Insert Table 5 about here]
Model 1 is the first-stage model controlling a firm’s capabilities. Accord with the extent
research literature, an old firm shows inertia in terms of innovating. Firm age has a significant
effect on increases its likelihood of choosing a shadowing strategy. The coefficient of market
share is negative and significant, suggesting that a high market share encourage a firm to become
the technological leader. Indeed, a firm with high market share is typically more likely to
innovate because of better return on investment than one with low market share. Furthermore,
the coefficient of current generation is negative and significant, suggesting that a firm with high
generation is more likely to choose a leading position than a shadowing strategy. Indeed, firm
capabilities literature maintains that firms at the technology frontier tend to be more
technologically capable. To our surprise, the coefficient of patent stock is not significant.
Perhaps not every patent is for developing and commercializing the frontier technology. Even for
firms that are behind the technology frontier, they can still develop incremental innovation, and
patent them.
Hypothesis 1 posits that the number of interfirm relationship with technological leaders is
likely to increase the focal firm’s likelihood of choosing a shadowing strategy. Results from
Model 2 fail to lend statistical support. One possible explanation is that skewness and kurtosis
15
are high for this variable. Also, even for firms that do have the interfirm relationships, the
number is low, ranging from 1 to 4.
As hypothesized, a firm is less likely to choose a shadowing strategy when the number of
firms at the technology frontier increases. Model 2 is the simple effect model. In Model 4, the
coefficient number of firms at the technology frontier is negative and significant, lending
statistical support for H2.
As hypothesized, when the number of firms at the technology frontier increases, the
effect of the number of interfirm relationships with technological leaders on a firm’s likelihood
of choosing a shadowing strategy is likely to weaken. Model 3 is the complete model with
interaction term. In Model 5, the coefficient of the interactive term is negative and significant at
90% confidence interval, lending statistical support for H3. The post estimation reports, for each
unit increase in the number of technological leaders, one interfirm relationship with
technological leader reduces the focal firm's likelihood of choosing a shadowing strategy by
0.097.
Discussion and Conclusion
In an attempt to determine contingencies that encourage the adoption of a technological
shadowing strategy, we ask the following research question: Under what circumstances will a
firm be more likely to choose to shadow the current technological leaders, rather than seek to
become a new technological leader? Our empirical results suggest that the number of
technological leaders reduces the focal firm's likelihood of choosing to shadow the technological
leaders. The theoretical implications are that an increase in the number of technological leaders
often decreases market uncertainties at the technology frontier, which encourage the focal firm to
choose a leading position rather than shadowing strategy. Furthermore, hypothesis testing
16
suggests the interfirm relationships with technological leaders have a moderating, not a direct
effect on the focal firm's likelihood of choosing a technological shadowing strategy. The
theoretical implications are that, technological uncertainties may not be able to affect the focal
firm's shadowing decision; when market uncertainties are low, technological uncertainties further
negatively moderate the relationship of market uncertainty and the focal firm's likelihood of
choosing a technological shadowing strategy.
Extant research literature has covered a firm's motivation to form interfirm relationships
(Kale, Singh, and Perlmutter, 2000; Kogut, 1988). To further develop the literature, this study
proposes and empirically tests the relationship of how interfirm relationships affect firm behavior
(Kale et al., 2000; Lin and Chen, 2002). With model support we posit that interfirm relationships
is likely to have a moderating effect on influencing firm behavior. More specifically, we focus
on the firm behavior regarding its decision of technology deployment. One of the key
implications from our study is that a firm may delay or refrain from deploying the most advanced
technology in order appropriating more from technological leaders' technology (Khanna, Gulati,
and Nohria, 1998).
This study also makes theoretical implications to competitive dynamics literature
(Aghion et al., 2005; Dutta, Lach, and Rustichini, 1995; Graevenitz, 2005). The studies of
competitive dynamics usually focus on the effect of competition within a pre-defined set of
competitors (Askenazy, Cahn, and Irac, 2008; Rindova, Ferrier, and Wiltbank, 2010). We
develop the theory by looking at firms that are outside of the set, and explain how the
competition out of their market affects their behavior. A more intense competition among
technological leaders may be a gain for others firms behind the technology frontier.
17
This study contributes to the research literature by giving attention to the region of the
shadowlands in which technological laggards remain behind the technology frontier by
strategically choosing a technological shadowing strategy. Not all mangers are at the “winning”
firms and thus this work will be meaningful to many practitioners. Furthermore, this study
contributes to the theory building of technology management because it analyzes factors that
inhibit a firm from racing to the technology frontier (Chen et al., 2010). It explains why, despite
strategic advantages of having technological leadership, a technological laggard may not have
sufficient economic incentives to move there.
In sum, becoming a technological leader may be not always a good strategy. In light of
increasing intensity of technology competition, this study suggests a different strategy for
technologically capable firms---that they can not only survive the technology competition but
also continue appropriating economic value of technological leaders' technology.
18
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Appendix
Table 1. Industry dynamics
Leading Shadowing Lagging Total
Leading
141
35
7
183
(77%)
(19%)
(4%) (100%)
Shadowing
12
39
39
90
(13%)
(43%)
(43%) (100%)
Lagging
2
11
441
454
(0%)
(2%)
(97%) (100%)
Table 2. Payoff matrix for technological race in the leading group
Firm 2
Lead
Firm 1
Shadow
Lead
,
Shadow
,
,
,
Table 3. Types of market environment and best strategies
Market Uncertainties
Technological Uncertainties
Creative Destruction
Routinized Regime
23
High
Low
Shadow
Lead
Lead
Lead
Table 4. Summary statistics.
Variable
Obs
Mean
Std. Dev.
Min
Max
1
1
Shadowing
194
0.43
0.5
0
1
1
2
2
Number of interfirm relationships with leader
194
0.34
0.74
0
4
-0.09
1
3
Number of firms at the technology frontier
194
12.77
5.75
1
20
0.02
0.09
1
4
Firm age
194
5.59
3.68
0
18
-0.09
0.13
-0.29
1
5
Market share
194
0.05
0.06
0
0.27
-0.35
0.16
-0.42
0.5
1
6
Current generation
194
3.73
1.97
1
10
-0.24
0.2
-0.67
0.49
0.62
1
7
Patent stock (in 1000)
153
2186
2883
0
144.12
-0.2
0.08
-0.12
0.47
0.48
0.34
8
Experience at the technology frontier
194
5.19
4.02
0
19
-0.27
0.15
-0.31
0.92
0.62
0.56
0.55
1
9
Industry growth
194
0.22
0.18
-0.41
0.45
-0.1
-0.21
0.07
-0.23
-0.13
-0.2
-0.19
-0.24
1
10
Firm size (in 1000)
194
2492
4274
0
18.62
-0.17
0.21
-0.58
0.55
0.75
0.84
0.45
0.59
-0.16
1
11
Recently gained leadership
194
0.14
0.35
0
1
-0.14
-0.01
0.03
-0.24
-0.14
0.05
-0.1
-0.25
0.1
-0.08
1
12
Inverse Mill Ratio
151
1756.93
19444.87
0
237803
0.11
-0.04
0.09
0.08
-0.09
-0.12
-0.04
0
-0.02
-0.06
-0.03
1
13
Relationship duration with the same technological leader
194
1.7
3.17
0
19
-0.14
0.47
-0.28
0.47
0.25
0.48
0.16
0.46
-0.16
0.4
-0.03
-0.05
1
14
Relationship experience with technological leaders
194
0.46
0.5
0
1
-0.24
0.48
-0.33
0.21
0.38
0.53
0.24
0.31
-0.12
0.45
-0.03
-0.08
0.44
1
15
Recent move
194
0.45
0.50
0
1
-0.15
0.07
-0.23
-0.06
0.13
0.32
0.02
-0.01
-0.01
0.15
0.43
-0.08
0.06
0.17
24
3
4
5
6
7
8
9
10
11
12
13
14
15
1
1
Table 5. Random-effect Logistic model. Dependent variable is shadowing or not (sample
limited to non-lagging technological laggards)
Model 1
Model 2
Model 3
Number of interfirm
relationships with leader
(H1)
0.276
(0.78)
2.010+
(1.85)
Number of firms at the
technology frontier (H2)
-0.132*
(-2.27)
-0.0970
(-1.50)
Number of interfirm
relationship*number of
firms at the technology
frontier (H3)
Firm age
-0.117+
(-1.70)
0.708***
(5.12)
0.578**
(3.08)
0.608**
(2.97)
-64.48***
(-3.82)
-17.80+
(-1.89)
-12.53
(-1.23)
Current generation
-0.569*
(-2.10)
-0.375
(-1.46)
-0.354
(-1.22)
Patent stock (in 1000)
0.142
(0.86)
0.00349
(0.04)
0.0368
(0.31)
Experience at the
technology frontier
-0.689***
(-3.46)
-0.747***
(-3.35)
Industry growth
-2.766+
(-1.94)
-3.861*
(-2.35)
Firm size (in 1000)
0.205+
(1.74)
0.0981
(0.71)
Recently gained leadership
-1.533+
(-1.98)
-1.556+
(-1.91)
Inverse Mill ratio
0.00796
(1.00)
0.00942
(1.04)
Relationship duration with
the same technological
leader
-0.0603
(-0.65)
-0.0809
(-0.75)
Relationship experience
with technological leaders
-0.532
(-0.91)
-0.291
(-0.42)
Recent move
-0.0063
(-0.01)
-0.0354
(-0.06)
4.477**
(3.11)
151
4.142**
(2.64)
151
Market share
Constant
-0.799
(-1.01)
420
Observations
z statistics in parentheses
+ p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
25