2014.02.26 Network Data Analytics ..Organizing intra-organizational networks for innovation
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Transcript of 2014.02.26 Network Data Analytics ..Organizing intra-organizational networks for innovation
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NUI Galway 2014 Workshop on network analytics Part 1: Organizing Intra-Organizational Networks for Innovation: introducing the basic concepts Hendrik Leendert (Rick) Aalbers* PhD
(*) Assistant Professor Strategy & Innovation Radboud University - Institute for Management Research // Centre for Organization Restructuring [email protected]
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Objective of today
• Introduction to social network analysis, including:
• Relevance • Core concepts • Core methodology • Main tools and visualization (Ucinet) • Large online networks • Reflection on future research possibilities • Wrap up
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Rick Aalbers, Phd
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Research agenda:
Reorganization
&
Innovation
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Introducing a network view of the world
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• People are represented as nodes.
• Relationships are represented as edges (or ties) • (Relationships may be
acquaintanceship, friendship, co-authorship, etc.)
• Allows analysis using tools of
mathematical graph theory
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Timeline / history of networks (based on Freeman, 2000) • 1736: Euler's paper on “Seven Bridges of Königsberg” ?
• 1937: J.L. Moreno pioneered sociometry
• Sociogram
• 1948: A. Bavelas established the group networks laboratory at MIT
• Centrality
• 1949: A. Rapaport developed a probability based model of information flow
• 50s and 60s: Social Networks studied by researchers in graph theory
• Cohesion, power, cooperation, triads (a.o. Harary et al. 1950s).
• 70s: Field of social network analysis emerged.
• New features in graph theory – more general structural models
• Better computer power – analysis of complex relational data sets
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What is an industry or interfirm network?
• $�FROOHFWLRQ�RI�ILUPV��1����WKDW�SXUVXH�repeated, enduring exchange relations with one another and, at the same time, lack a legitimate organizational authority to arbitrate and resolve disputes that may
arise during the exchange.
Podolny and Page (1998: 59)
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What is a business or intrafirm network?
A collection of individuals, teams or business units�1����WKDW�SXUVXH�repeated, enduring exchange relations with one another.
Knowledge exchanged trough a shared social context. Intra
organizational networks facilitate the creation of new knowledge within organizations (e.g., Kogut &
Zander, 1992; Tsai, 2000; Tsai, 2001)
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Source: Aalbers and Dolfsma 2014
Networks of innovation (intra firm)
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An example of a modern network: 9-11 Hijackers Network
SOURCE: Valdis Krebs http://www.orgnet.com/
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Building blocks of an inter/ intra firm network • Abstract level:
- Nodes - Ties
• Interorganizational network (between firms)
- Firm level - Examples: alliances, long-term buyer-supplier relationships - Relationship is a connection between two firms that can be used
to transfer both tangible and intangible resources such as assets, knowledge, money, and information.
• Intraorganizational network (within a firm) - Employees - Formal, informal - Advice relationships, innovation, gossip, daily routines/ tasks - Mandated, unmandated
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Transaction cost economics (Williamson) Adopts an undersocialized view of human being
• Human being as an atomistic entity • Human beings are bounded rational • Risk of moral hazard • Risk of opportunistic behavior
Sociology
Adopts an oversocialized view of human being
• Environment determines human behavior • No room for individual discretion
Economic Sociology (Granovetter, Uzzi) Adopts an embeddedness perspective
• Economic relationships are embedded in social relationships • Environment constrains humans but there is room for agency
Networks as alternative lens to the firm
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Comparing markets, hierarchies and networks (Powell,1990)
Governance forms
Key features Market Hierarchy Network
Normative basis Contracts / property rights
Employment relationship / authority
Complementary strengths
Means of communication
Prices Routines Relational
Degree of flexibility
High Low Medium
Commitment Low Medium to high Medium to high
Actor choices Independent Dependent Interdependent
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A network perspective to the firm • Roots in graph theory • Network is stored in a
matrix
A B C D E F G H I J
A 1 0 0 1 1 1 1 0 0 1
B 0 0 1 1 1 1 0 1 0 1
C 1 1 0 0 1 1 1 0 0 1
D 0 1 0 0 1 1 1 1 1 0
E 0 0 0 0 0 0 1 0 0 1
F 1 0 0 1 0 1 1 0 0 0
G 1 0 1 0 1 1 0 0 0 0
H 0 1 0 1 1 0 0 1 0 0
I 0 0 0 0 1 1 1 0 0 0
J 0 1 1 1 0 0 1 0 0 0
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In general, a relation can be: (1) Binary or Valued (2) Directed or Undirected
a
b
c e
d
Undirected, binary Directed, binary
a
b
c e
d
a
b
c e
d
Undirected, Valued Directed, Valued
a
b
c e
d 1 3
4 2 1
Alright, so where to start? The value (and direction) of a tie
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Why does it matter? Different perspectives to study a network
• Structural embeddedness
- Looks at the quantity and configuration of interfirm relationships - 1HWZRUN�VWUXFWXUH�ĺ�QHWZRUN�SRVLWLRQ�ĺ�FRQGXFW�ĺ�SHUIRUPDQFH
(Structure – Conduct – Performance) - Ignores firm/ individual characteristics
• Relational embeddedness
- Looks at the quality and contents of interfirm relationships - Interfirm relationships are viewed as source of competitive
advantage/ intra firm relationships as source of innovation - Invisible - Causal ambiguous - Inimitable
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Structural embeddedness terminology
• Network structure: the collection of actors and their relationships at any given point in time.
• Network position: the pattern of relations to and from an actor within a network structure. Burt (1980: 893)
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9 Degree: most likely to influence and be influenced directly 9 Closeness: most likely to find out first 9 Betweenness: most likely to broker and synthesize diverse info 9 Bonachich power: When your centrality depends on your neighbors’
centrality
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indegree
In each of the following networks, X has higher centrality than Y according to a particular measure:
outdegree betweenness closeness
Centrality measures
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When degree is not everything In what ways does degree fail to capture centrality in the following graphs?
• ability to broker between groups • likelihood that information originating anywhere in the network reaches you
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Betweenness
• Intuition: how many pairs of individuals would have to go through you in order to reach one another in the minimum number of steps?
• who has higher betweenness, X or Y?
X Y
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• degree - number of connections - denoted by size
• closeness
- length of shortest path to all others
- denoted by color
How closely do degree and betweenness correspond to closeness?
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Extreme diversity channel of broad and diverse information
Combination diverse ties provide the
perspective at which knowledge held in specialized parts
can be interpreted
Extreme similarity repository of high-quality, specialized
information
Relational embeddedness Diversity vs. similarity (ter Wal 2013)
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Brokerage • Centrality only captures part of knowledge brokering
• Centrality does not take division membership of the nodes into account
• Different brokerage roles exist . . .
Gould + Fernandez (1989):
(1) coördinator (2) gatekeeper (3) representative (4) itinerant broker (5) Liaison Same centrality, different roles
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Conducting a social network analysis in the context of the firm
• Identify a Strategically Important Community
– Channeling creative ideas towards market ready innovations – Integrating networks that cross core processes – Facilitating post-merger integration and large-scale
organizational change – Supporting communities of practice – Identifying change agents for a reorganization to come – Forming strategic partnerships and alliances – Improving learning and decision making in top leadership
networks – Crowd sourcing – Building political cloud
... Each benefits from a particular form of network configuration
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Assess meaningful relationships and network constructs that connect and define these communities
• Relationships that reveal collaboration in a network
9 e.g., Communication, Information, Problem solving, Innovation
• Relationships that reveal information sharing potential
9 e.g., access, blockades
• Relationships that reveal rigidity in a network
9 e.g., decision making, influence, interdependencies
• Relationships that reveal well-being and supportiveness in a network 9 e.g., liking, friendship, trust
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How to get to this kind of data Network survey procedure
• Roster vs snowball method
• Snowball sampling method: - Useful when boundaries of the network cannot be determined a priori /
particularly relevant for knowledge sharing
- Initial round of 8-10 ‘seeds’ (with different backgrounds); network measures collected via interviews
- All contacts mentioned by first-round respondents become ‘targets’ for the second round - electronic network survey asking them about their network contacts
- Second-round targets: same thing until boundary is reached
- Y-round targets already included or only peripherally involved in the theme)
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Possible name generator questions (individual level)
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Source: Aalbers, H.L., Dolfsma. W. Koppius, O. (2013). Rich Ties and Innovative Knowledge Transfer within a Firm. British Journal of Management, DOI:10.1111/1467-8551.12040
Business unit level example: Which units provide your unit with new knowledge or expertise when your unit is seeking technical advice inside your organization?" (Tsai 2001)
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The innovation network
Source: Aalbers, Dolfsma & Koppius 2014
So we got the network(s) and the key concepts... Now what?
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Combining network methodology into relevant propositions
Possible angles 9 Hierarchy 9 Diversity 9 Multiplexity • Actor attributes • Brokerage • Longitudinality • Interventions • Multi level networks
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Horizontal cross unit ties • The ties that team members have directly with other organization members
across unit boundaries.
Advantages • Access to alternative ideas and insights relevant for a firm’s existing strategy, goals,
interests, time horizon, core values and emotional tone (Sethia 1995; Floyd and Lane 2000).
• Creativity (Burt 2004). • Complementary functional expertise (Aalbers et al. 2013; Haas 2010; March 1991). • Team anticipation and prevention of potential weaknesses in technical and
marketing solutions (Leenders et al. 2003). • Project performance (Cohen and Levinthal 1990; Obstfeld 2005; Tortoriello and
Krackhardt 2010).
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Vertical cross hierarchical ties
• The ties that the team maintains with organization members at higher hierarchical levels (Jaworski and Kohli 1993; Sheremata 2000). - Received limited attention – with focus on the project team leader specifically
(Shim and Lee 2001)
Advantages • Access to higher status positions brings:
- Desirable resources (e.g. funding, prestige, power) (Pfeffer & Salancik, 1978) - Positive publicity - Managerial attention & championing (Markham 1998)
- Legitimacy (Brass, 1984; Cross, Rice & Parker 2001; Feldman & March, 1981).
- Blocking off competing projects (Kijkuit & Van den Ende 2007).
- Perspective of how the team output fits in the overall firms objectives and goals - Stocktaking of what is relevant within the rest of the organization (Hansen et al.
2001; Subramaniam and Youndt 2005; Mom et al. 2009).
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Fostering diversity
Fostering support
Horizontal cross ties
Verti
cal c
ross
ties
Delivery of innovative project outcomes
Source: JPIM - Aalbers, Dolfsma & Leenders 2015
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Figure 1: Horizontal cross-ties Figure 1A (under-performing) Figure 1B (performing)
= Conceptual projectteam composition
Source: JPIM - Aalbers, Dolfsma & Leenders 2015
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Figure 2: Hierarchical cross-ties Figure 2A (under-performing) Figure 2B (performing)
= Conceptual projectteam composition
Source: JPIM - Aalbers, Dolfsma & Leenders 2015
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Informal ties matter for knowledge sharing
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• Informal networks: “interpersonal relationships in the organization that affect decisions within it, but are either omitted from the formal scheme or are not consistent with that scheme”(Simon, 1976, p.148) - Informal ties are discretionary and emergent (Monge & Contractor,
2001) - Affective component stronger than instrumental component
(Ibarra, 1993) - Primary basis for formation of interpersonal trust, which is
necessary for knowledge transfer (Szulanski et al., 2004)
Source: BJoM - Aalbers, Dolfsma & Koppius 2013
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Formal ties matter for knowledge sharing • Formal networks: “the planned structure for an
organization”(Simon, 1976, p.147) - Formal ties are designed or mandated by corporate management
(Monge & Contractor, 2001) - Not just the org chart, also includes ‘quasi-structures’ such as
committees, task forces, teams and other workflow relations mandated by the firm (Schoonhoven & Jellinek, 1990)
- Instrumental component stronger than affective component (Ibarra, 1993)
- Builds shared understanding (Gabarro, 1990; Tiwari, Koppius & van Heck, 2011) and relative absorptive capacity (Lane & Lubatkin, 1998) as basis for more complex knowledge transfer
Source: BJoM - Aalbers, Dolfsma & Koppius 2013
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Multiplex ties matter for knowledge sharing • Multiplexity: Combination of multiple relational contents in a
single tie (Burt 1983; Ibarra, 1993; Rank et al., 2010)
- Ties in an organization are not either formal or informal, many are a combination of the two, i.e. multiplex ties. (Gulati & Puranam, 2009)
- Multiplex ties are qualitatively different: more intimate (Minor,
1983), more stable (Ibarra, 1995), reduce uncertainty (Albrecht & Ropp,
1984), more supportive (McAllister, 1995) and improve performance (Roberts & O’Reilly, 1989)
- Multiplex ties create transfer synergy between willingness and ability: shared understanding from formal ties (ability) and trust from informal ties (willingness) (Hansen, 2001)
Source: BJoM - Aalbers, Dolfsma & Koppius 2013
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When studying networks in knowledge sharing, we need to be aware about what is really driving the results...
• Formal networks matter at least as much as informal networks
• Multiplex ties matter much more than just formal or informal ties
• Most results ascribed to informal networks should probably be ascribed to multiplex networks instead
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M Pure F
Pure I
Source: BJoM - Aalbers, Dolfsma & Koppius 2013
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Measurement 1 – Summer time
Innovation Innovation
Measurement 2 – Winter time
Source: Aalbers 2012
An example of network intervention – network expansion at a financial services firm
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Wrap up part 1 – core concepts and relevance
» Social network analysis is a different way of looking at organization structures
» Networks exist on different levels, which intertwine – thereby creating different layers to analyse and influence an organisations performance
» Network analysis can help in multiple contexts, including R&D/ innovation, process redesign and reorganisations
» Network modeling helps in simplifying complex relations
» Different modes of analysis can be identified; including roles, behavior, clustering, and affiliation
» Measuring the behavior of a network requires both statistic as well as organisational process knowledge
» A common methodology is needed to secure an objective analysis
» Networks can be altered – governing is an option
» SNA is fun!
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Objective of today – Part 2
• Introduction to social network analysis, including:
• Relevance • Core concepts • Core methodology • Main tools and visualization (Ucinet) • Large online networks • Reflection on future research possibilities • Wrap up
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Propositions for discussion
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9Certain network positions offer an advantageous opportunity structure, but whether this opportunity is seized, depends on the motivation of the actor (Burt, 2010)
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