The Role of Ego Network Structure in Facilitating Ego Network Innovations

Date01 April 2015
Published date01 April 2015
DOIhttp://doi.org/10.1111/jscm.12075
THE ROLE OF EGO NETWORK STRUCTURE IN
FACILITATING EGO NETWORK INNOVATIONS
STEVEN CARNOVALE
Portland State University
SENGUN YENIYURT
Rutgers University
A great deal of research on innovation implicitly relies upon the network
in which a firm is embedded to explain its innovative capabilities. Inter-
estingly, however, most research examines innovation at the firm level,
rather than at the network level. Thus, there is a significant gap in the lit-
erature regarding the effects of network structure on innovation within a
firm's network. In this research, we contribute to the literature of supply
chain innovations by developing and testing theoretically derived hypoth-
eses regarding the effect of network structure on innovation output and
distribution, as measured by the aggregate count and variance in the dis-
tribution of patents of the ego network in which a firm exists. Utilizing a
manufacturing joint venture network dataset, we identify effects of various
ego network constructs such as betweenness, density, brokerage, and
weakness on ego network innovation. We find support for the idea that
innovation in a supply chain is highly dependent upon the network struc-
ture of the interfirm relationships. Thus, it is not just what you know or
how well you individually innovate, but also how well the firm can lever-
age its supply network connections that engender superior innovation
outcomes.
Keywords: supply chain innovation; network innovation; joint ventures;
ego network; archival data; time series analysis
INTRODUCTION
Innovation is generally regarded as the creation or
adoption of new ideas for processes or products
(Damanpour & Gopalakrishnan, 2001) and is a vital
component to a firm’s strategy (Azadegan, Dooley,
Carter & Carter, 2008). Accordingly, research in the
supply chain management domain has identified sev-
eral dimensions of innovation that play vital roles in
its generation and success. One key element in the
success of innovation is supply chain integration, both
internally and externally, as research suggests that it
plays a large role in the service innovation process
(Stank, Keller & Daugherty, 2001). Additionally, col-
laboration with suppliers (Kim, 2000) and the
increases in customer service that can arise from the
innovation process (Flint, Larsson & Gammelgaard,
2008) have all been noted.
A striking commonality to the research on innova-
tion within supply chains is that it all implicitly relies
upon the network in which a firm is embedded to
explain its innovative capabilities. Yet, the level of
analysis in most of this research is at the firm level,
rather than from the broader perspective of the firm’s
network. Thus, there is a significant gap in the litera-
ture regarding the effects of network structure on
innovation within a firm’s network. Accordingly, a
more appropriate level of analysis through which to
study innovation is at the network level. Hence, this
study contributes to the extant literature by examining
the role that network structure plays in generating
innovations for the network members. We thus
develop a framework for supply chain innovations
using social network theory. Social network theory
has recently made quite a profound ascendency and
impact in supply chain research. Generally, social net-
work theory examines relational dynamics through
the lens of structure. That is to say it leverages the
connections between and among entities to explain
Volume 51, Number 222
future behavior or actions (Choi & Kim, 2008; Choi &
Wu, 2009). For example, scholars have studied the
effect that supplier network size has on performance
and trust within business relationships (Terpend &
Ashenbaum, 2012) and developed conceptual frame-
works that have advanced the effects of power within
various network configurations (Bastl, Johnson & Choi,
2013). Particularly germane to the present research
context is Kim, Choi, Yan and Dooley (2011)’s work
wherein they have empirically disentangled the struc-
ture of the automotive supply network of major auto-
motive manufacturers and find that, among other
things, leveraging social network theory is useful in
determining key players in various networks.
From the network perspective, innovations within
the network often implicitly arise from components
of the “ego network” of a particular firm. An ego net-
work is comprised of an ego (i.e., a social unit such
as a manufacturer), the ego’s immediate ties (i.e., first-
degree connections), and the connections among the
nodes to which the ego is connected (Borgatti & Hal-
gin, 2011; Burt, 1980; Freeman, 1982). Ego networks
have been applied to various contexts such as power
and influence in networks (Burt, 1992), innovation
adoption (Ahuja, 2000b), and the role that ego net-
works have on new joint venture formations (Carno-
vale & Yeniyurt, 2014).
As noted above, however, most research operational-
izes innovation at the firm level, rather than a net-
work level. Thus, a primary goal of this research was
to reconcile this issue and study innovation at the net-
work level. We do so by generating the overall net-
work structure of manufacturing-based joint ventures
(JVs) in the automotive industry over a 19-year per-
iod. A joint venture can be described as the formation
of a separate, autonomous entity derived from the col-
laboration of two or more parent organizations (Ko-
gut, 1988). Joint ventures have long been identified as
sources of positive effects on innovation (Inkpen,
1996). We then generate the ego network structures
for all firms in the network, including their innova-
tion output over the 19-year period of observation.
Thus, in this study, we address the following research
question: What role does network structure play in
generating innovations for network members and
what characteristics of network structure facilitate
innovation in global supply chain networks?
The rest of the article is organized as follows. First,
we review the relevant literature surrounding innova-
tion. We then articulate several hypotheses that con-
nect network structure to network innovations by
examining ego networks in the global automotive
industry. Afterward, we describe the empirical context
of our study. Finally, a discussion of the results is pre-
sented followed by the limitations and future research
directions.
LITERATURE REVIEW AND HYPOTHESIS
DEVELOPMENT
Innovation Networks
Innovation has long been studied in the manage-
ment and supply chain management domains.
Broadly, innovation is generally regarded as the crea-
tion or adoption of new ideas for processes or prod-
ucts (Damanpour & Gopalakrishnan, 2001). Dowling
and Midgley (1978) highlight the first-mover advanta-
ges to innovation, as they consider a firm to be inno-
vative when they adopt a product or process earlier
than other firms in the network. Delbecq and Mills
(1985) develop a more precise definition, stating that
innovation is a significant change within the organiza-
tion or its line of services or products that requires a
substantial adjustment in functions and/or structures,
and is incorporated into the organization. Similarly,
Autry and Griffis (2008:159) define the innovation
orientation of a firm as “the capacity to make
improvements to business processes or outcomes by
leveraging new or specialized ideas, methods, or
advancements.” Furthermore, Soosay, Hyland and Fer-
rer (2008) highlight a firm’s collaborative capabilities
(i.e., its potential to interact within the network) as
antecedents to innovation output. Accordingly, inno-
vation is a vital component of a firm’s overall strategy
(Azadegan et al., 2008) and can be dichotomized into
process and product innovation. A product innovation
refers to a new product that serves to fill an external
unmet need, whereas a process innovation refers to
the integration of new elements into a firm’s opera-
tions that are used to produce a product or service
(Damanpour & Gopalakrishnan, 2001). Innovation in
supply chain management has recently been defined
as, “the process of making changes to products, pro-
cesses, and services that results in new value creation
to the organization and its customers by leveraging
knowledge efforts of the firm and (or) that of its sup-
ply network partners” (Narasimhan & Narayanan,
2013:28). This definition highlights that innovation is
an organizational process that leverages knowledge.
Cohen and Levinthal (1990) articulate that a firm’s
ability to leverage prior knowledge significantly
impacts its ability to innovate in the future; they term
this as absorptive capacity.
Another vital component of the above definition of
innovation (Narasimhan & Narayanan, 2013) is the
potential peripheral or network effects on innovation.
It has been suggested that “networks with a superior
capacity for learning and knowledge transfer are able
to ‘out-innovate’ single firms or networks with less
effective knowledge-sharing routines” (Billington &
Davidson, 2013:1464). Extending beyond the focal
firm, Azadegan (2011) examines supplier operational
innovativeness and the positive impact it has on
April 2015
Ego Network Structure and Innovations
23

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