| dc.description.abstract | The overall purpose of this dissertation is to study interorganizational networks. Firms
are open systems and simultaneously embedded in interorganizational networks of various
kinds. Interorganizational networks consist of a group of organizations and relations between
these organizations, reflecting the allocation and flow of resources among network members.
Conceivably, network structures largely affect involved firms’ different behaviors.
Nevertheless, such knowledge is insufficient without knowing how interorganizational
networks emerge and develop into a specific structure. Using a sociometric structural approach,
this dissertation contributes to two related topics: (1) the influence of network properties on
firms’ behaviors (Articles 1 and 2) and (2) the dynamics of network structures (Article 3).
A firm’s position in a network has implications for its opportunities and constraints
(Brass et al., 2004). The first two empirical articles focus on the influence of network structures
on firms’ behaviors. In Article 1, I demonstrate how firms adapt exploration strategies
according to network properties. Management research has alluded to environmental and
organizational antecedents for firms’ exploration. I complement this knowledge by applying a
network perspective to explain how a firm may adjust its exploration strategy based on its
position within the interorganizational network. I particularly focus on two network constructs:
closeness centrality and local cohesion. Closeness centrality captures a firm’s distance to
network knowledge and resources, and local cohesion shows the connection between a focal
firm’s alters. The findings show positive impacts of closeness centrality and local cohesion on
exploration strategy, and local cohesion has a more significant impact. I offer insights into
antecedents of exploration by underscoring the network drivers.
In Article 2, I study firms’ prosocial behavior in dyads within a broader network context.
Research on relationship marketing has traditionally focused on dyadic properties to explain
behaviors within dyads. This article adds to this body of research by investigating network Abstract
The overall purpose of this dissertation is to study interorganizational networks. Firms
are open systems and simultaneously embedded in interorganizational networks of various
kinds. Interorganizational networks consist of a group of organizations and relations between
these organizations, reflecting the allocation and flow of resources among network members.
Conceivably, network structures largely affect involved firms' different behaviors.
Nevertheless, such knowledge is insufficient without knowing how interorganizational
networks emerge and develop into a specific structure. Using a sociometric structural approach,
this dissertation contributes to two related topics: (l) the influence of network properties on
firms' behaviors (Articles l and 2) and (2) the dynamics of network structures (Article 3).
A firm's position in a network has implications for its opportunities and constraints
(Brass et al., 2004). The first two empirical articles focus on the influence of network structures
on firms' behaviors. In Article l, I demonstrate how firms adapt exploration strategies
according to network properties. Management research has alluded to environmental and
organizational antecedents for firms' exploration. I complement this knowledge by applying a
network perspective to explain how a firm may adjust its exploration strategy based on its
position within the interorganizational network. I particularly focus on two network constructs:
closeness centrality and local cohesion. Closeness centrality captures a firm's distance to
network knowledge and resources, and local cohesion shows the connection between a focal
firm's alters. The findings show positive impacts of closeness centrality and local cohesion on
exploration strategy, and local cohesion has a more significant impact. I offer insights into
antecedents of exploration by underscoring the network drivers.
In Article 2, I study firms' prosocial behavior in dyads within a broader network context.
Research on relationship marketing has traditionally focused on dyadic properties to explain
behaviors within dyads. This article adds to this body of research by investigating network 111
iv
level antecedents of prosocial behaviors in dyadic relations. Prosocial behavior refers to a
firm’s beneficial actions toward another firm beyond formal requirements. Since a contract is
normally incomplete, such behavior is desirable in business relationships. Our findings show
that in-degree centrality (i.e., the number of ties received from other network members) has an
inverted U-shaped relationship with a focal firm’s prosocial behavior. Besides, triadic
embeddedness (i.e., the number of common third parties) is likely to facilitate prosocial
behavior between involved parties, regardless of firms’ in-degree centrality. This study shows
the need to consider the dyadic relationship in a wider network context.
While Articles 1 and 2 implicitly assume network properties are static, Article 3
contributes to knowledge of network development in the interorganizational setting.
Sociologists and management scholars provide explanations mainly for dyadic tie formation,
such as alliance formation and joint ventures. Limited is known about system-level structural
dynamics. Specifically, I focus on two system-level properties: small-world and scale-free
networks. Small-world networks are characterized by dense local clustering and short path
length between actors. Scale-free networks are centralized with a small portion of central actors
spanning the structure and take a skewed degree distribution. Some empirical networks
demonstrate both properties simultaneously, yet few studies have aimed to discuss the
dynamics and interrelation of these properties. In article 3, I retrospectively visualize the annual
structures of two empirical networks to show how small-world and scale-free properties
together explain the development patterns. The results show that the small-world and scale free properties have an inversed dynamic pattern, and the scale-free structure may be less
common in the interorganizational setting. Altogether, this study adds to the understanding of
the dynamics and development of interorganizational networks in terms of small-world and
scale-free structures.
level antecedents of prosocial behaviors in dyadic relations. Prosocial behavior refers to a
firm's beneficial actions toward another firm beyond formal requirements. Since a contract is
normally incomplete, such behavior is desirable in business relationships. Our findings show
that in-degree centrality (i.e., the number of ties received from other network members) has an
inverted U-shaped relationship with a focal firm's prosocial behavior. Besides, triadic
embeddedness (i.e., the number of common third parties) is likely to facilitate prosocial
behavior between involved parties, regardless of firms' in-degree centrality. This study shows
the need to consider the dyadic relationship in a wider network context.
While Articles l and 2 implicitly assume network properties are static, Article 3
contributes to knowledge of network development in the interorganizational setting.
Sociologists and management scholars provide explanations mainly for dyadic tie formation,
such as alliance formation and joint ventures. Limited is known about system-level structural
dynamics. Specifically, I focus on two system-level properties: small-world and scale-free
networks. Small-world networks are characterized by dense local clustering and short path
length between actors. Scale-free networks are centralized with a small portion of central actors
spanning the structure and take a skewed degree distribution. Some empirical networks
demonstrate both properties simultaneously, yet few studies have aimed to discuss the
dynamics and interrelation of these properties. In article 3, I retrospectively visualize the annual
structures of two empirical networks to show how small-world and scale-free properties
together explain the development patterns. The results show that the small-world and scale free properties have an inversed dynamic pattern, and the scale-free structure may be less
common in the interorganizational setting. Altogether, this study adds to the understanding of
the dynamics and development of interorganizational networks in terms of small-world and
scale-free structures.
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Contextually, I investigate two regional industry networks in western Norway, focusing
on the media industry and fintech. Overall, this dissertation provides an in-depth analysis of
these two interorganizational networks by focusing on multiple levels and aspects of a network
and adds to the current literature on management, relationship marketing, and network
dynamics. Moreover, this dissertation combines network data and survey data for hypotheses
testing in Articles 1 and 2, which is unique and increases the validity of the findings. I also
present key findings, discuss the implications and limitations of this work, and suggest future
research directions. | en_US |
