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HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Computational Intelligence
“A Framework to Investigate the Relationship Between
Employee Embeddedness in Enterprise Social Networks and
Knowledge Transfer” by Janine Viol and Caroline Durst
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Introduction
➢ Knowledge Transfer
● knowledge transfer influences productivity of an organization and is
“crucial for its survival”
● issues of the targeted research
○ knowledge transfer is often informal
○ to handle knowledge transfer in SN, it must be investigated and
understood
○ the process of knowledge transfer is difficult to be managed due to the
human factor (cultural differences, depth of social relationships, …)
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Introduction
➢ Research questions
● Research Questions
○ How are employees embedded in ESN?
○ How is this related to the company’s organigram?
○ How can social capital be identified and measured in ESNs using
methods of Computational Intelligence?
○ How is social capital associated with the knowledge transfer process of
individual employees?
○ How can the knowledge transfer get improved?
● Management Goals
○ Increasing productivity and team performance
○ Improving collaboration and reducing costs
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Definition
“Sharing, interpreting, combining and storing of information.”
Argote et al.
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Informal and formal
● informal
➢ knowledge transfer is not caused by business processes, but by
independent social interaction
● formal
➢ knowledge transfer is caused by business processes (e.g.
documentations, charts, business reports, ...)
➢ can be improved
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Implicit and explicit
● implicit (tacit)
➢ knowledge transfer is caused by experience or observation
➢ “difficult to formalize and to communicate”
● explicit
➢ knowledge is transferred by a formalized, systematic representation
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Table
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Limitation to enterprises
● entities in ESN are employees
● relations between entities can represent immaterial or material resources
● relation/tie strength is depended by
○ amount of time
○ emotional intensity
○ intimacy
○ reciprocal services
● influence of ESN on knowledge transfer
○ strong ties -> more efficient in transferring tacit knowledge ([Hansen])
○ both weak and strong -> explicit knowledge transfer
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Differentiation of ESN
● formal ESN
○ management-directed and unit-based (e.g. wikis)
● informal ESN
○ emergent, user-directed and overlapping units
● working domain ESN
○ knowledge is directly related to the work
● non-working domain ESN
○ knowledge is indirectly related to the work (e.g. talks on company
excursions)
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Differentiation of ESN
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Knowledge Transfer
➢ Seeking and giving advice
● 5 ways (according to Cross et. al.)
○ provision of solutions
○ meta-knowledge
○ problem reformulation
○ validation
○ legitimization
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Social Capital
➢ Definition
“Resources embedded in one’s social network, resources that can
be accessed or mobilized through ties in the network.”
Lin
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Social Capital
➢ Differentiation
● bonding networks
○ homogenous groups
○ similar interests
○ generation of emotional support
● bridging networks
○ heterogenous groups
○ non-redundant resources
○ better access to informational and instrumental resources
strong ties
weak ties
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Social Capital
➢ Examples
bonding
bridging
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Social Capital
➢ ESN influence
Ellison et al.:
● SN encourage both bonding and bridging social capital
● they allow people to generate new social capital (e.g. exchanging information
with new acquaintances)
● they allow to strengthen and maintain offline relationships
● large network of (weak) bridging ties improve the access to diverse
resources
➢ positive outcome
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Knowledge Transfer
Differentiation
● explicit knowledge is measured based on questionnaires or surveys
● implicit knowledge can be measured by observation or text analysis
Aspects
● sinks of knowledge
● sources of knowledge
● velocity
● viscosity
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Data Collection in SN
● approaches for measurements of implicit knowledge transfers
○ Movery et al. used citation patterns to detect the knowledge transfer
between companies
○ Huang and De Sanctis focused on forums and searched for the different
text patterns to categorize posts
➢ information seeking
➢ information providing
➢ explicit knowledge sharing
➢ implicit knowledge sharing
“Where can I find...?”
“Does anybody have...?”
“Do you know…?”
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Data Collection in SN
● assumptions in the paper
○ focus on explicit knowledge
○ knowledge transfer can occur in formal, informal networks in the
working and non-working domain
● steps for knowledge analysis
○ manually find knowledge areas (e.g. by functions)
○ (automatically) figure out levels of expertise by positions of employees
(extraction from SN profile pages)
○ find knowledge flow, sources and sinks e.g. by wall posts and comments
using pattern matching similar to the approach of the previous slide
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Data Collection in SN
● further steps
○ publishing of material (documents, links, ...) as an indicator for a
knowledge source
○ rating system for posted information to figure out usefulness and/or
quality
➢ What could be possible criterias for this? How could a reasoner
decide?
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
● short introduction into ego networks
ego
alter
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
network size
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
hierarchical positions/occupations in
ego’s network
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
measurement of social resources in ego’s network
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
● structural measures
○ How are actors in the network connected to each other?
○ analyze network size
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
ego
3
5
2
6
4
1
● small network size
● mostly egocentric
network
● network is constrained
by alters
bonding
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
● positional measures
○ reflect ego’s position in the (overall) network
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
ego
3
5
2
6
4
1
● ego is central
● ego has 5 connections,
one is bridging
➢ betweenness
● ego is close to each alter
● ego is well-connected to 2,
3, 5, 6
➢ eigenvector
● ego has two bridges, but
to single alters
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
ego
3
5
2
6
4
1
● example for a bridge to
other groups
➢ generate social capital
➢ diversity increases
opportunity of getting
new capital
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
● functional measures
○ focusses on network resources provided by specific ties
○ tie strength may be difficult to be extracted in ESN
➢ there are different approaches
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
● measuring tie strength - different approaches
○ Granovetter: measures amount of time, emotional intensity, intimacy,
reciprocal services
➢ How can we measure emotional intensity and intimacy?
○ other approaches include the analyzation of comments and messages in
SN
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
● measuring tie strength - fuzzy-logic approach
○ Arnaboldi et al.: analyzed twitter tweets using fuzzy logic with fuzzy set
➢ very low
➢ low
➢ medium
➢ high
➢ very high
○ on input parameters
➢ reply message percentage
➢ common follower percentage
➢ normalized mean reply delay
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Measurement
➢ Network-Based Social Capital
“Due to the similar functionalities of online social networks or
Twitter and ESN, the discussed tie strength indicators and the use
of a fuzzy logic approach can be assumed to be equally applicable
in ESN.”
Viol, Janine and Durst, Carolin
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
“Knowledge transfer processes are (...) the effects of different
social capital types”
Viol, Janine and Durst, Carolin
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network structure
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network structure
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network structure
● high ratio means ego has access to many colleagues
➢ good access to social capital
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network structure
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Cliques and components
ego
3
5
2
6
clique
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Cliques and components
ego
3
5
2
6
component
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network structure
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Brokerage
ego
3
5
2
6
● not connected
○ (2, 5)
○ (5, 6)
○ (3, 6)
● brokerage = 3
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network structure
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Effective size
ego
3
5
2
6
● number of colleagues: 4
● average number of alter
ties:
● effective size: 3.25
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network structure
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network ties
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network ties
● fuzzy-logic approach adapting Fazeen et al.
○ fuzzy-sets (very low, low, medium, high, very high)
○ four parameters
➢ common colleagues percentage
➢ shared project groups percentage
➢ reply message percentage
➢ normalized mean reply delay
○ best case: value of all parameters is very high
➢ high tie strength
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of network members
➢ find similarity between colleagues
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Analysis of social capital
● fuzzy-logic can be used
● indicators for bonding social capital
○ high network closure
○ strong ties
○ high degree of network homogeneity
● bridging
○ establish new links to more diverse resources and knowledge
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Knowledge transfer
● finding sinks and sources of knowledge
○ suggestion: text-mining approach by searching for patterns
○ Critics: Different people communicate differently.
“Where can I find...?”
“Does anybody have...?”
“Do you know…?”
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Final embeddedness
● embeddedness in the ESN influences social capital
● social capital influences knowledge transfer
● Han and Hovav: “bonding social capital positively affects knowledge sharing
and project performance”
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Theoretical Framework
➢ Achieved knowledge transfer
● approach is to calculate ratio of
○ number of information requests (information seeking posts)
○ number of responses (information providing posts)
● Can each response be seen as information providing?
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Contents
● Introduction
● Knowledge Transfer
○ informal and formal
○ implicit and explicit
○ Limitation to enterprises
● Social Capital - bonding and bridging SN
● Measurement and data collection
○ Approaches to measure Knowledge Transfer
○ Strategies of Data Collection in SN
● Theoretical Framework
● Conclusion and Discussion
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Conclusions
● framework enables researchers and practitioners to investigate knowledge
transfer process using social network analysis and methods of computational
intelligence
○ e.g.: identify “knowledge key individuals” and check if they match those in
the enterprise’s “key positions”
● outlook
○ analyze dynamics in ESN using swarm-intelligence and neuro-fuzzy
systems
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Conclusions
Thank you for your attention!
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Sources
● [Primary] [tables on slides 11, 14, 27-30, 32, 35, 41-46, 49, 51, 53, 55, 57-60, 62]
A Framework to Investigate the Relationship Between Employee Embeddedness in Enterprise Social
Networks and Knowledge Transfer. Janine Viol and Carolin Durst. pp. 259–287
in Witold Pedrycz, Shyi-Ming Chen (Eds). Social Networks: A Framework of Computational Intelligence.
Studies in Computational Intelligence Band 526. Berlin: Springer. 2014.
● http://www.britannica.com/EBchecked/topic/287895/information-system, retrieved on: 25.06.2014.
● Konar, Amit: Computational Intelligence : Principles, Techniques and Applications. Berlin Heidelberg: Springer Science
& Business Media, 2006.
● http://www.unc.edu/~sunnyliu/inls258/Introduction_to_Knowledge_Management.html, retrieved on: 24.06.2014.
● Wasserman, Stanley ; Faust, Katherine: Social Network Analysis : Methods and Applications. New.. Cambridge:
Cambridge University Press, 1994.
● [Hansen] Hansen, M.T.: The search-transfer problem: the role of weak ties in sharing knowledge across organization
subunits. Adm. Sci. Q. 44(1), 82 (1999).
● [Boyd and Ellison] Boyd, D.M, Ellison, N.: Social network sites: definition, history, and scholarship. J. Comput.-Mediat.
Commun. 13(1), 210-230 (2007)
● [Argote et al] Argote, L., Ingram, P.: Knowledge transfer: a basis for competitive advantage in firms. Organ. Behav.
Hum. Decis. Process. 82(1), 150-169 (2000).
● [Lin] Lin, N.: Social Capital: A Theory of Social Structure and Action. Cambridge University Press, Cambridge (2001)
● [Ellison et al.] Elisson, N., Steinfield, C., Lampe, C.: The benefits of facebook friends: social capital and college students
use of online social network sizes. J. Comput.-Mediat. Commun. 12(4), 1143-1168 (2007).
● [Steinfield et al.] Steinfield, C., DiMicco, J., Elisson, N.: Bowling online: Social networking and social capital within the
organization. In: Proceedings of the Fourth Communities and T echnologies Conference, pp. 245-254 (2009).
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Sources
● [Fritsch and Kauffeld-Monz] Fritsch, M., Kauffeld-Monz, M.: The impact of network structure on knowledge transfer: an
application of social network analysis in the context of regional innovation networks. Ann. Reg. Sci. 44(1), 21-38
(2008).
● [Chan and Liebowitz] Chan, K. Liebowitz, J.: The synergy of social network analysis and knowledge mapping: a case
study. Int, J. Manag. Decis, Mak. 7(1), 19 (2006).
● [Helms and Buijsrogge] Helms, R., Buijsrogge, K.: Knowledge network anlysis: A technique to analyze knowledge
management bottlenecks in organizations. In: 16th international workshop on database and expert systems
applications (DEXA ‘05), pp. 410-414. IEEE (2005).
● [Granovetter] Granovetter, M.S.: The strength of weak ties. Am. J. Sociol, 78(6), 1360-1380 (1973).
● [Marsden and Campbell] Marsden, P.V., Campbell, K.E.: Measuring tie strength. Soc. Forces 63(2), 482-501 (1984).
● [Matthews] Matthes, K.M., White, M.C., Long, R.G:: Soper, B., Von Bergen, C.W.: Association of indicators and
predictors of tie strength. Psychol. Rep. 83(3), 1449-1469 (1998).
● [Hassan] Hassan, S., Salgado, M., Pavón, J.: Friendship dynamics: modelling social relationships through a fuzzy agent-
based simulation. Discret Dyn Nat Soc. 2011, 1-19 (2011).
● [Xiang et al.] Xiang, R., Neville, J., Rogati, M.: Modeling relationship strength in online social networks. In: Proceedings
of the 19th International Conference on World Wide Web - WWW’ 10, p. 981 (2010).
● [Arnaboldi et al.] Arnaboldi, V., Guazzini, A., Passarella, A.: Egocentric online social networks: Analysis of key features
and prediction of tie strength in Facebook. Comput. Commun. 36, 1130-1144 (2013).
HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann
Discussion
● What do you think? Do employees in higher positions tend to provide more
knowledge than others?
● What kind of social capital is more useful in software projects? Bonding or
bridging? Is the capital in the analyzed network the only important factor for
knowledge transfer?
● What do you think? Can you measure similarity between colleagues by
comparing their public ESN profiles?

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Semantic Modelling - Paper presentation

  • 1. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Computational Intelligence “A Framework to Investigate the Relationship Between Employee Embeddedness in Enterprise Social Networks and Knowledge Transfer” by Janine Viol and Caroline Durst
  • 2. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Contents ● Introduction ● Knowledge Transfer ○ informal and formal ○ implicit and explicit ○ Limitation to enterprises ● Social Capital - bonding and bridging SN ● Measurement and data collection ○ Approaches to measure Knowledge Transfer ○ Strategies of Data Collection in SN ● Theoretical Framework ● Conclusion and Discussion
  • 3. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Contents ● Introduction ● Knowledge Transfer ○ informal and formal ○ implicit and explicit ○ Limitation to enterprises ● Social Capital - bonding and bridging SN ● Measurement and data collection ○ Approaches to measure Knowledge Transfer ○ Strategies of Data Collection in SN ● Theoretical Framework ● Conclusion and Discussion
  • 4. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Introduction ➢ Knowledge Transfer ● knowledge transfer influences productivity of an organization and is “crucial for its survival” ● issues of the targeted research ○ knowledge transfer is often informal ○ to handle knowledge transfer in SN, it must be investigated and understood ○ the process of knowledge transfer is difficult to be managed due to the human factor (cultural differences, depth of social relationships, …)
  • 5. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Introduction ➢ Research questions ● Research Questions ○ How are employees embedded in ESN? ○ How is this related to the company’s organigram? ○ How can social capital be identified and measured in ESNs using methods of Computational Intelligence? ○ How is social capital associated with the knowledge transfer process of individual employees? ○ How can the knowledge transfer get improved? ● Management Goals ○ Increasing productivity and team performance ○ Improving collaboration and reducing costs
  • 6. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Contents ● Introduction ● Knowledge Transfer ○ informal and formal ○ implicit and explicit ○ Limitation to enterprises ● Social Capital - bonding and bridging SN ● Measurement and data collection ○ Approaches to measure Knowledge Transfer ○ Strategies of Data Collection in SN ● Theoretical Framework ● Conclusion and Discussion
  • 7. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Knowledge Transfer ➢ Definition “Sharing, interpreting, combining and storing of information.” Argote et al.
  • 8. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Knowledge Transfer ➢ Informal and formal ● informal ➢ knowledge transfer is not caused by business processes, but by independent social interaction ● formal ➢ knowledge transfer is caused by business processes (e.g. documentations, charts, business reports, ...) ➢ can be improved
  • 9. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Knowledge Transfer ➢ Implicit and explicit ● implicit (tacit) ➢ knowledge transfer is caused by experience or observation ➢ “difficult to formalize and to communicate” ● explicit ➢ knowledge is transferred by a formalized, systematic representation
  • 10. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Knowledge Transfer ➢ Table
  • 11. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Knowledge Transfer ➢ Limitation to enterprises ● entities in ESN are employees ● relations between entities can represent immaterial or material resources ● relation/tie strength is depended by ○ amount of time ○ emotional intensity ○ intimacy ○ reciprocal services ● influence of ESN on knowledge transfer ○ strong ties -> more efficient in transferring tacit knowledge ([Hansen]) ○ both weak and strong -> explicit knowledge transfer
  • 12. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Knowledge Transfer ➢ Differentiation of ESN ● formal ESN ○ management-directed and unit-based (e.g. wikis) ● informal ESN ○ emergent, user-directed and overlapping units ● working domain ESN ○ knowledge is directly related to the work ● non-working domain ESN ○ knowledge is indirectly related to the work (e.g. talks on company excursions)
  • 13. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Knowledge Transfer ➢ Differentiation of ESN
  • 14. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Knowledge Transfer ➢ Seeking and giving advice ● 5 ways (according to Cross et. al.) ○ provision of solutions ○ meta-knowledge ○ problem reformulation ○ validation ○ legitimization
  • 15. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Contents ● Introduction ● Knowledge Transfer ○ informal and formal ○ implicit and explicit ○ Limitation to enterprises ● Social Capital - bonding and bridging SN ● Measurement and data collection ○ Approaches to measure Knowledge Transfer ○ Strategies of Data Collection in SN ● Theoretical Framework ● Conclusion and Discussion
  • 16. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Social Capital ➢ Definition “Resources embedded in one’s social network, resources that can be accessed or mobilized through ties in the network.” Lin
  • 17. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Social Capital ➢ Differentiation ● bonding networks ○ homogenous groups ○ similar interests ○ generation of emotional support ● bridging networks ○ heterogenous groups ○ non-redundant resources ○ better access to informational and instrumental resources strong ties weak ties
  • 18. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Social Capital ➢ Examples bonding bridging
  • 19. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Social Capital ➢ ESN influence Ellison et al.: ● SN encourage both bonding and bridging social capital ● they allow people to generate new social capital (e.g. exchanging information with new acquaintances) ● they allow to strengthen and maintain offline relationships ● large network of (weak) bridging ties improve the access to diverse resources ➢ positive outcome
  • 20. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Contents ● Introduction ● Knowledge Transfer ○ informal and formal ○ implicit and explicit ○ Limitation to enterprises ● Social Capital - bonding and bridging SN ● Measurement and data collection ○ Approaches to measure Knowledge Transfer ○ Strategies of Data Collection in SN ● Theoretical Framework ● Conclusion and Discussion
  • 21. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Knowledge Transfer Differentiation ● explicit knowledge is measured based on questionnaires or surveys ● implicit knowledge can be measured by observation or text analysis Aspects ● sinks of knowledge ● sources of knowledge ● velocity ● viscosity
  • 22. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Data Collection in SN ● approaches for measurements of implicit knowledge transfers ○ Movery et al. used citation patterns to detect the knowledge transfer between companies ○ Huang and De Sanctis focused on forums and searched for the different text patterns to categorize posts ➢ information seeking ➢ information providing ➢ explicit knowledge sharing ➢ implicit knowledge sharing “Where can I find...?” “Does anybody have...?” “Do you know…?”
  • 23. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Data Collection in SN ● assumptions in the paper ○ focus on explicit knowledge ○ knowledge transfer can occur in formal, informal networks in the working and non-working domain ● steps for knowledge analysis ○ manually find knowledge areas (e.g. by functions) ○ (automatically) figure out levels of expertise by positions of employees (extraction from SN profile pages) ○ find knowledge flow, sources and sinks e.g. by wall posts and comments using pattern matching similar to the approach of the previous slide
  • 24. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Data Collection in SN ● further steps ○ publishing of material (documents, links, ...) as an indicator for a knowledge source ○ rating system for posted information to figure out usefulness and/or quality ➢ What could be possible criterias for this? How could a reasoner decide?
  • 25. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital ● short introduction into ego networks ego alter
  • 26. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital network size
  • 27. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital hierarchical positions/occupations in ego’s network
  • 28. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital measurement of social resources in ego’s network
  • 29. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital ● structural measures ○ How are actors in the network connected to each other? ○ analyze network size
  • 30. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital ego 3 5 2 6 4 1 ● small network size ● mostly egocentric network ● network is constrained by alters bonding
  • 31. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital ● positional measures ○ reflect ego’s position in the (overall) network
  • 32. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital ego 3 5 2 6 4 1 ● ego is central ● ego has 5 connections, one is bridging ➢ betweenness ● ego is close to each alter ● ego is well-connected to 2, 3, 5, 6 ➢ eigenvector ● ego has two bridges, but to single alters
  • 33. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital ego 3 5 2 6 4 1 ● example for a bridge to other groups ➢ generate social capital ➢ diversity increases opportunity of getting new capital
  • 34. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital ● functional measures ○ focusses on network resources provided by specific ties ○ tie strength may be difficult to be extracted in ESN ➢ there are different approaches
  • 35. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital ● measuring tie strength - different approaches ○ Granovetter: measures amount of time, emotional intensity, intimacy, reciprocal services ➢ How can we measure emotional intensity and intimacy? ○ other approaches include the analyzation of comments and messages in SN
  • 36. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital ● measuring tie strength - fuzzy-logic approach ○ Arnaboldi et al.: analyzed twitter tweets using fuzzy logic with fuzzy set ➢ very low ➢ low ➢ medium ➢ high ➢ very high ○ on input parameters ➢ reply message percentage ➢ common follower percentage ➢ normalized mean reply delay
  • 37. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Measurement ➢ Network-Based Social Capital “Due to the similar functionalities of online social networks or Twitter and ESN, the discussed tie strength indicators and the use of a fuzzy logic approach can be assumed to be equally applicable in ESN.” Viol, Janine and Durst, Carolin
  • 38. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Contents ● Introduction ● Knowledge Transfer ○ informal and formal ○ implicit and explicit ○ Limitation to enterprises ● Social Capital - bonding and bridging SN ● Measurement and data collection ○ Approaches to measure Knowledge Transfer ○ Strategies of Data Collection in SN ● Theoretical Framework ● Conclusion and Discussion
  • 39. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework “Knowledge transfer processes are (...) the effects of different social capital types” Viol, Janine and Durst, Carolin
  • 40. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework
  • 41. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework
  • 42. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Analysis of network structure
  • 43. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Analysis of network structure
  • 44. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Analysis of network structure ● high ratio means ego has access to many colleagues ➢ good access to social capital
  • 45. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Analysis of network structure
  • 46. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Cliques and components ego 3 5 2 6 clique
  • 47. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Cliques and components ego 3 5 2 6 component
  • 48. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Analysis of network structure
  • 49. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Brokerage ego 3 5 2 6 ● not connected ○ (2, 5) ○ (5, 6) ○ (3, 6) ● brokerage = 3
  • 50. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Analysis of network structure
  • 51. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Effective size ego 3 5 2 6 ● number of colleagues: 4 ● average number of alter ties: ● effective size: 3.25
  • 52. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Analysis of network structure
  • 53. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework
  • 54. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Analysis of network ties
  • 55. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Analysis of network ties ● fuzzy-logic approach adapting Fazeen et al. ○ fuzzy-sets (very low, low, medium, high, very high) ○ four parameters ➢ common colleagues percentage ➢ shared project groups percentage ➢ reply message percentage ➢ normalized mean reply delay ○ best case: value of all parameters is very high ➢ high tie strength
  • 56. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework
  • 57. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Analysis of network members ➢ find similarity between colleagues
  • 58. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework
  • 59. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework
  • 60. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Analysis of social capital ● fuzzy-logic can be used ● indicators for bonding social capital ○ high network closure ○ strong ties ○ high degree of network homogeneity ● bridging ○ establish new links to more diverse resources and knowledge
  • 61. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework
  • 62. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Knowledge transfer ● finding sinks and sources of knowledge ○ suggestion: text-mining approach by searching for patterns ○ Critics: Different people communicate differently. “Where can I find...?” “Does anybody have...?” “Do you know…?”
  • 63. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Final embeddedness ● embeddedness in the ESN influences social capital ● social capital influences knowledge transfer ● Han and Hovav: “bonding social capital positively affects knowledge sharing and project performance”
  • 64. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Theoretical Framework ➢ Achieved knowledge transfer ● approach is to calculate ratio of ○ number of information requests (information seeking posts) ○ number of responses (information providing posts) ● Can each response be seen as information providing?
  • 65. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Contents ● Introduction ● Knowledge Transfer ○ informal and formal ○ implicit and explicit ○ Limitation to enterprises ● Social Capital - bonding and bridging SN ● Measurement and data collection ○ Approaches to measure Knowledge Transfer ○ Strategies of Data Collection in SN ● Theoretical Framework ● Conclusion and Discussion
  • 66. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Conclusions ● framework enables researchers and practitioners to investigate knowledge transfer process using social network analysis and methods of computational intelligence ○ e.g.: identify “knowledge key individuals” and check if they match those in the enterprise’s “key positions” ● outlook ○ analyze dynamics in ESN using swarm-intelligence and neuro-fuzzy systems
  • 67. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Conclusions Thank you for your attention!
  • 68. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Sources ● [Primary] [tables on slides 11, 14, 27-30, 32, 35, 41-46, 49, 51, 53, 55, 57-60, 62] A Framework to Investigate the Relationship Between Employee Embeddedness in Enterprise Social Networks and Knowledge Transfer. Janine Viol and Carolin Durst. pp. 259–287 in Witold Pedrycz, Shyi-Ming Chen (Eds). Social Networks: A Framework of Computational Intelligence. Studies in Computational Intelligence Band 526. Berlin: Springer. 2014. ● http://www.britannica.com/EBchecked/topic/287895/information-system, retrieved on: 25.06.2014. ● Konar, Amit: Computational Intelligence : Principles, Techniques and Applications. Berlin Heidelberg: Springer Science & Business Media, 2006. ● http://www.unc.edu/~sunnyliu/inls258/Introduction_to_Knowledge_Management.html, retrieved on: 24.06.2014. ● Wasserman, Stanley ; Faust, Katherine: Social Network Analysis : Methods and Applications. New.. Cambridge: Cambridge University Press, 1994. ● [Hansen] Hansen, M.T.: The search-transfer problem: the role of weak ties in sharing knowledge across organization subunits. Adm. Sci. Q. 44(1), 82 (1999). ● [Boyd and Ellison] Boyd, D.M, Ellison, N.: Social network sites: definition, history, and scholarship. J. Comput.-Mediat. Commun. 13(1), 210-230 (2007) ● [Argote et al] Argote, L., Ingram, P.: Knowledge transfer: a basis for competitive advantage in firms. Organ. Behav. Hum. Decis. Process. 82(1), 150-169 (2000). ● [Lin] Lin, N.: Social Capital: A Theory of Social Structure and Action. Cambridge University Press, Cambridge (2001) ● [Ellison et al.] Elisson, N., Steinfield, C., Lampe, C.: The benefits of facebook friends: social capital and college students use of online social network sizes. J. Comput.-Mediat. Commun. 12(4), 1143-1168 (2007). ● [Steinfield et al.] Steinfield, C., DiMicco, J., Elisson, N.: Bowling online: Social networking and social capital within the organization. In: Proceedings of the Fourth Communities and T echnologies Conference, pp. 245-254 (2009).
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  • 70. HTW - WT2 Semantic Modelling - SoSe 2014 Sascha Feldmann Discussion ● What do you think? Do employees in higher positions tend to provide more knowledge than others? ● What kind of social capital is more useful in software projects? Bonding or bridging? Is the capital in the analyzed network the only important factor for knowledge transfer? ● What do you think? Can you measure similarity between colleagues by comparing their public ESN profiles?