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 r.aalbers@fm.ru.nl Objective of today • Introduction to social network analysis, including: • • • • • • • 2 Relevance Core concepts Core methodology Main tools and visualization (Ucinet) Large online networks Reflection on future research possibilities Wrap up Rick Aalbers, Phd Research agenda: Reorganization & Innovation 3 Introducing a network view of the world • 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 4 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 5 What is an industry or interfirm network? • 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) What is a business or intrafirm network? A collection of individuals, teams or business units 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) 8 9 Networks of innovation (intra firm) Source: Aalbers and Dolfsma 2014 An example of a modern network: 9-11 Hijackers Network SOURCE: Valdis Krebs http://www.orgnet.com/ 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) - 12 Employees Formal, informal Advice relationships, innovation, gossip, daily routines/ tasks Mandated, unmandated Networks as alternative lens to the firm 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 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 A network perspective to the firm • Roots in graph theory • Network is stored in a matrix 15 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 Alright, so where to start? The value (and direction) of a tie In general, a relation can be: (1) Binary or Valued (2) Directed or Undirected b b d a c e a 1 a 1 3 c d c e Directed, binary Undirected, binary b d b d 2 4 Undirected, Valued e a c Directed, Valued e Why does it matter? Different perspectives to study a network • Structural embeddedness - Looks at the quantity and configuration of interfirm relationships (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 17 18 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) Centrality measures Degree: most likely to influence and be influenced directly Closeness: most likely to find out first Betweenness: most likely to broker and synthesize diverse info Bonachich power: When your centrality depends on your neighbors’ centrality In each of the following networks, X has higher centrality than Y according to a particular measure: indegree 20 outdegree betweenness closeness 21 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 22 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? Y 23 X How closely do degree and betweenness correspond to closeness? • degree - number of connections - denoted by size • closeness - length of shortest path to all others - denoted by color 24 Relational embeddedness Diversity vs. similarity (ter Wal 2013) Extreme diversity Combination Extreme similarity channel of broad and diverse information diverse ties provide the perspective at which knowledge held in specialized parts can be interpreted repository of highquality, specialized information 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 26 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 Assess meaningful relationships and network constructs that connect and define these communities • Relationships that reveal collaboration in a network e.g., Communication, Information, Problem solving, Innovation • Relationships that reveal information sharing potential e.g., access, blockades • Relationships that reveal rigidity in a network e.g., decision making, influence, interdependencies • Relationships that reveal well-being and supportiveness in a network e.g., liking, friendship, trust 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) 29 Possible name generator questions (individual level) 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) 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 30 So we got the network(s) and the key concepts... Now what? The innovation network Source: Aalbers, Dolfsma & Koppius 2014 Combining network methodology into relevant propositions Possible angles • • • • • 32 Hierarchy Diversity Multiplexity Actor attributes Brokerage Longitudinality Interventions Multi level networks 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). 33 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). 34 Fostering support Delivery of innovative project outcomes Vertical cross ties Fostering diversity Horizontal cross ties Source: JPIM - Aalbers, Dolfsma & Leenders 2015 Figure 1: Horizontal cross-ties Figure 1A (under-performing) Figure 1B (performing) = Conceptual projectteam composition Source: JPIM - Aalbers, Dolfsma & Leenders 2015 Figure 2: Hierarchical cross-ties Figure 2A (under-performing) Figure 2B (performing) = Conceptual projectteam composition Source: JPIM - Aalbers, Dolfsma & Leenders 2015 Informal ties matter for knowledge sharing • 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 39 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 40 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 41 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 Pure F M Pure I Source: BJoM - Aalbers, Dolfsma & Koppius 2013 42 An example of network intervention – network expansion at a financial services firm Measurement 1 – Summer time Innovation Source: Aalbers 2012 Measurement 2 – Winter time Innovation 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! r.aalbers@fm.ru.nl Objective of today – Part 2 • Introduction to social network analysis, including: • • • • • • • 46 Relevance Core concepts Core methodology Main tools and visualization (Ucinet) Large online networks Reflection on future research possibilities Wrap up Propositions for discussion Certain network positions offer an advantageous opportunity structure, but whether this opportunity is seized, depends on the motivation of the actor (Burt, 2010) 47