When Does Competitive Learning Occur? The Impact of Alliance Network Embeddedness on Technological Invasion
| Published date | 01 April 2023 |
| Author | Liqing Tang,Tienan Wang,Qianqian Fan,Linlin Liu |
| Date | 01 April 2023 |
| DOI | http://doi.org/10.1111/1467-8551.12636 |
British Journal of Management, Vol. 34, 1023–1041 (2023)
DOI: 10.1111/1467-8551.12636
When Does Competitive Learning Occur?
The Impact of Alliance Network
Embeddedness on Technological Invasion
Liqing Tang, Tienan Wang, Qianqian Fan and Linlin Liu
School of Management, Harbin Institute of Technology, Hei Longjiang, Harbin, China
Corresponding author email: wtn@hit.edu.cn
Firms participate in an alliance network to collaborate for specic goals and common val-
ues; however, the network situation and the interaction between partnering rms enable
them to appropriate their partners’ proprietary knowledgeand adopt competitive actions.
Little is known about whether and when the focal rm would invade its partner’s techno-
logical domains in alliance networks. Weexamined how relational embeddedness and po-
sitional embeddedness inuence the focal rm’s technological invasion behaviour against
its partner, and the moderating role of relative alliance experience. Although previous
studies have emphasized that a central position would enhance rms’ competitiveaggres-
sion, we argue that this central position imposes more constraints on rms’ competitive
behaviour.The empirical results show a U-shaped relationship between relational embed-
dedness and technological invasion, while relativecentrality negatively affects technologi-
cal invasion behaviour and negativelymoderates the U-shaped relationship. Furthermore,
the results indicate that relativealliance experience attenuates the U-shaped relationship
between relational embeddedness and technological invasion, while it enhances the neg-
ative effect of relative centrality on technological invasion. These ndings provide new
insights and perspectives to study the coopetition phenomenon in alliance networks.
Introduction
Firms form a strategic alliance to accomplish spe-
cic goals by sharing knowledge and resources
(Gulati, 1998). Through the shared alliance tasks,
rms can learn from each other to explore
new technologies or sustain their competitive ad-
vantages (Bouncken and Kraus, 2013; Gomes-
Casseres, Hagedoorn and Jaffe, 2006; Lavie, 2006;
Lavie and Rosenkopf, 2006). Firms in a strate-
gic alliance, however, tend to adopt opportunis-
tic behaviour and always engage in competitive
learning by acquiring proprietary resources from
their partners (Ahuja, 2000a; Das and Teng, 2000;
Hamel, 1991; Kale, Singh and Perlmutter, 2000),
This work was supported by the National Natural Sci-
ence Foundation of China (Grants No. N71972061 and
N72172043).
or by expanding to their partners’ areas (Cui,
Yang and Vertinsky, 2015). Park, Srivastava and
Gnyawali (2014b) studied the relationship between
the balance of coopetition and innovation perfor-
mance and noted that one mechanism for improv-
ing innovation performance is acquiring and in-
ternalizing the knowledge of their partners (Luo,
2007), as evidenced by the fact that rms will ap-
ply for patents in their partners’ elds. This nd-
ing leads to an interesting research question: With
further understanding of the partners, whether
and when will the rm initiate competitive be-
haviours against its partners in the technological
domains? Because the cooperation alliances are
always conducted in the shadow of competition
(Greve et al., 2010), and rms are simultaneously
engaged in several individual alliances, thus form-
ing alliance networks (Galvin et al., 2020), rms in
alliance networks always pursue competition and
© 2022 British Academy of Management.
1024 TANG et al.
cooperation simultaneously. Most studies have ex-
amined coopetition from the dyadic relationship.
Recently, scholars have addressed the need to fo-
cus on network coopetition (Andrevski, Brass and
Ferrier, 2016; Bouncken and Fredrich, 2016) and
encouraged further research (Czakon et al., 2020;
Sanou, Roy and Gnyawali, 2016). Ties in coopeti-
tion networks providerms with insights into their
partners and enable them access to network re-
sources, but they simultaneously constrain rms’
behaviours. We consider that the characteristicsof
the relationship between partnering rms and the
position they embedded in the network will be im-
portant factors affecting whether the focal rm in-
vades its partner.
We draw inspiration from two main streams
of literature. The rst is the research on the
antecedents and effects of coopetition from an
individual alliance perspective (Hoffmann et al.,
2018). Scholars agree that rms always cooper-
ate for common interests and compete for more
private interests (Arslan, 2018; Gulati and Singh,
1998; Hamel, Doz and Prahalad, 1989; Lavie,
2007). They have studied many factors that can
affect competitive behaviours within an individual
alliance, such as learning capabilities (Cohen and
Levinthal, 1990; Hamel, 1991; Yang, Zheng and
Zaheer, 2015), similarities (Darr and Kurtzberg,
2000; Dussauge, Garrette and Mitchell, 2000) and
alliance characteristics (Andrevski, Brass and Fer-
rier, 2016). Others have addressed the benets or
consequences when allying with the competitors,
such as the impact on performance or inno-
vation (Park, Srivastava and Gnyawali, 2014a,
2014b; Schilling, 2015), alliance termination
(Asgari et al., 2016) and alliance formation (Park,
Kim and Kang, 2015).
The second important research area is to study
the coopetition phenomenon from the network
perspective (Andrevski, Brass and Ferrier, 2016;
Bouncken and Fredrich, 2016; Cui, Yang and
Vertinsky, 2018; Gnyawali, He and Madhavan,
2006; Gnyawali and Madhavan, 2001; Gulati,
1998; Polidoro, Ahuja and Mitchell, 2011). A set
of rms are simultaneously engaged in several
individual alliances, which arelinked by direct and
indirect alliance ties, forming an alliance network
(Galvin et al., 2020). Previous studies have inves-
tigated the characteristics of the alliance network
– such as the network size on competitive learning
(Bouncken and Fredrich, 2016), and other studies
have focused on the impact of embedded rela-
tionships on allying r ms’ competitive incentives
(Polidoro, Ahuja and Mitchell, 2011) or industry-
level competition without specifying a particu-
lar target (Andrevski, Brass and Ferrier, 2016;
Gnyawali and Madhavan, 2001). Only a few stud-
ies have focused on the competitive behaviours
adopted by rms against alliance partners. For
example, Cui, Yang and Vertinsky (2018) investi-
gated how the relative exploratory alliance ratios
affect rms’ competition against partners in the
product market and how the network embed-
dedness moderates this relationship. Our study
focuses on competitive behaviours initiated by
the focal rm against its partners in the techno-
logical domains. Firms that have the opportunity
to appropriate knowledge and invade their part-
ners’ domains may avoid such actions because
of the expected reactions of network partners
and the negative impact on the rms’ reputation.
So, we enrich previous studies by focusing on
how the allying rms embedded in the alliance
network affect the competitive behaviours in the
technological domains.
The two types of coopetition relationship be-
tween alliance partners are (1) rivals that initiate
an alliance and (2) alliance partners that begin to
compete (Czakon et al., 2020; Hoffmann et al.,
2018). Most of the existing studies focus on the
former relationships, regarding alliance coopeti-
tion mainly based on the alliance with competi-
tors (Ann Peng, Yen and Bourne, 2018; Bouncken
et al., 2018; Chetty and Wilson, 2003; Gnyawali
and Park, 2011); however, the partners in the al-
liances are not only competitors but also non-
competitors (Gimeno, 2004). Although these stud-
ies still focus on the performance or survival of
the alliances, and the coopetition in the alliances
between long-time rivals, our research focuses on
the case of alliance partners beginning to com-
pete. We examine the factors that affect the focal
rm’s invasion behaviour into its partner’s tech-
nological domains from the network perspective,
which have rarely been studied. To date, the re-
search on technological invasion between alliance
partners has focused on relational embeddedness
(Cui, Yang and Vertinsky, 2015). Cui, Yang and
Vertinsky (2015) used data from the US biophar-
maceutical industry to investigate and validate a
U-shaped relationship between the repeated re-
search and development (R&D) alliances and tech-
nological competition. Our study amplies recent
work by integrating coopetition and networks and
© 2022 British Academy of Management.
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