Abstract
This literature review highlights some Social Network Analysis (SNA) concepts applicable to the study of organizational knowledge and, more particularly, to knowledge heterogeneity. Knowledge being all at the same time decentralized and distributed, knowing up to what point knowledge can be heterogeneous or homogeneous across organizational units becomes as important as the question of knowing how to structure the organization. SNA applied to knowledge management thus seems a stimulant for future research in the fields of management.
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References
Agresti A and Agresti B (1978) Statistical analysis of qualitative variation. In Sociological Methodology (SCHUESSLER KF, Ed), pp 204–237, Jossey-Bass, San Francisco.
Ahuja G (2000) Collaboration networks, structural holes, and innovation: a longitudinal study. Administrative Science Quarterly 45 (3), 425–455.
Allan M (2004) A peek into the life of online learning discussion forums: implications for web-based distance learning. The International Review of Research in Open and Distance Learning 5 (2), http://www.irrodl.org/content/v5.2/allan.html (accessed 26 June 2007).
Allen TJ and Cohen SI (1969) Information flow in research and development laboratories. Administrative Science Quarterly 14 (1), 12–19.
Anand V, Manz CC and Glick WH (1998) An organizational memory approach to information management. The Academy of Management Review 23 (4), 796–809.
Ancona DG and Caldwell DF (1992) Demography and design: predictors of new product team performance. Organization Science 3 (3), 321–341.
Argote L and Ingram P (2000) Knowledge transfer: a basis for competitive advantage in firms. Organizational Behavior and Human Decision Processes 82 (1), 150–169.
Argote L, McEvily B and Reagans R (2003) Managing knowledge in organizations: an integrative framework and review of emerging themes. Management Science 49 (4), 571–582.
Argyres NS (1996) Capabilities, technological diversification and divisionalization. Strategic Management Journal 17 (5), 395–410.
Baba ML, Gluesing J, Ratner H and Wagner KH (2004) The contexts of knowing: natural history of a globally distributed team. Journal of Organizational Behavior 25 (5), 547–587.
Barnes J (1954) Class and committees in a Norwegian Island Parish. Human Relations 7 (1), 39–58.
Batjargal B (2005) Software entrepreneurs in China and Russia: knowledge networks, product development, and venture performance. William Davidson Institute Working Paper No. 751 [WWW Document] http://www.people.hbs.edu/jsiegel/Batjargal_HBSFeb12007.doc(accessed 31 May 2007).
Beckman CM and Hauschild P (2002) Network learning: the effects of partners' heterogeneity of experience on corporate acquisitions. Administrative Science Quarterly 47 (1), 92–124.
Blackler F (1995) Knowledge, knowledge work and organizations: an overview and interpretation. Organization Studies 16 (6), 1021–1046.
Blau PM (1977) Inequality and Heterogeneity. The Free Press, New York.
Boland R and Tenkasi R (1995) Perspective making and perspective taking in communities of knowing. Organization Science 6 (4), 350–372.
Bonifacio M, Bouquet P and Cuel R (2002) Knowledge nodes: the building blocks of a distributed approach to knowledge management. Journal of Universal Computer Science 8 (6), 652–661.
Bonner JM and Walker Jr. OC (2004) Selecting influential business-to-business customers in new product development: relational embeddedness and knowledge heterogeneity considerations. Journal of Product Innovation Management 21 (3), 155–169.
Borgatti SP (2002) NetDraw: Graph Visualization Software. Analytic Technologies, Harvard.
Borgatti SP and Everett MG (1997) Network analysis of 2-mode data. Social Networks 19 (3), 243–269.
Borgatti SP and Foster PC (2003) The network paradigm in organizational research: a review and typology. Journal of Management 29 (6), 991–1013.
Borgatti SP, Everett MG and Freeman LC (2002) UCINET for Windows: Software for Social Network Analysis. Analytic Technologies, Harvard.
Brown JS and Duguid P (1991) Organizational learning and communities of practice: toward a unified view of working, learning and innovation. Organization Science 2 (1), 40–57.
Burkhardt ME and Brass DJ (1990) Changing patterns or patterns of change: the effects of a change in technology on social network structure and power. Administrative Science Quarterly 35 (1), 104–127.
Buskens V (1998) The social structure of trust. Social Networks 20 (3), 265–289.
Burt R (1992) Structural Holes. Harvard University Press, Cambridge, MA.
Burt RS (2004) Structural holes and good ideas. American Journal of Sociology 110 (2), 349–399.
Carley KM and Reminga J (2004) ORA: Organization risk analyzer. Center for Computational Analysis of Social and Organizational Systems (CASOS) Technical Report, CMU-ISRI-04-106, Carnegie Mellon University, Pittsburgh http://reports-archive.adm.cs.cmu.edu/anon/isri2004/CMU-ISRI-04-106.pdf (accessed 12 February 2008).
Chan K and Liebowitz J (2006) The synergy of social network analysis and knowledge mapping: a case study. International Journal of Management and Decision Making 7 (1), 19–35.
Cohen W and Levinthal D (1990) Absorptive capacity: a new perspective on learning and innovation. Administrative Science Quarterly 35 (1), 128–152.
Conrath DW (1973) Communication environment and its relationship to organizational structure. Management Science 20 (4), 586–603.
Contractor N, Carley K, Levitt R, Monge P, Wasserman S, Bar F, Fulk J, Hollingshead A and Kunz J (2000) Co-evolution of knowledge networks and 21st century organizational forms: computational modeling and empirical testing. Working Paper TEC2000-01, University of Illinois at Urbana-Champaign.
Cooke NJ, Salas E, Cannon-Bowers JA and Stout RJ (2000) Measuring team knowledge. Human Factors 42 (1), 151–173.
Cross R and Parker A (2004) The Hidden Power of Social Networks: Understanding How Work Really Gets Done in Organizations. Harvard Business School Press, Boston.
Cross R, Parker A, Prusak L and Borgatti SP (2001) Knowing what we know: supporting knowledge creation and sharing in social networks. Organizational Dynamics 30 (2), 100–120.
Cross R, Nohria N and Parker A (2002) Six myths about informal networks – and how to overcome them. Sloan Management Review 43 (3), 66–76.
D'Adderio L (2003) Configuring software, reconfiguring memories: the influence of integrated systems on the reproduction of knowledge and routines. Industrial and Corporate Change 12 (2), 321–350.
DeSanctis G and Poole MS (1982) Capturing the complexity in advanced technology use: adaptive structuration theory. Organization Science 5 (2), 121–147.
Downs GW (1976) Bureaucracy, Innovation, and Public Policy. Lexington Books, Lexington.
Earley PC and Mosakowski E (2000) Creating hybrid team cultures: an empirical test of transnational team functioning. Academy of Management Journal 43 (1), 26–49.
Espinosa JA, Carley KM, Kraut RE, Lerch FJ and Fussell SR (2002) The effect of task knowledge similarity and distribution on asynchronous team coordination and performance: empirical evidence from decision teams. In Second Information Systems Cognitive Research Exchange (IS CoRE) Workshop. Barcelona, Spain. http://www.cs.cmu.edu/~kraut/RKraut.site.files/articles/Espinosa02-KnowledgeSimilarityDistribCoordSubmitted.pdf (accessed on 27 January 2008).
Everett MG and Borgatti SP (1999) The centrality of groups and classes. Journal of Mathematical Sociology 23 (3), 181–201.
Festinger L, Schachter S and Back K (1950) Social Pressures in Informal Groups: A Study of a Housing Project. Harper & Row, New York.
Freeman LC (1979) Centrality in social networks: conceptual clarification. Social Networks 1 (3), 215–239.
Freeman LC (2000) Social network analysis: definition and history. In Encyclopedia of Psychology (KAZDAN AE, Ed), pp 350–351, Oxford University Press, New York.
Galunic DC and Rodan SA (1998) Resource recombinations in the firm: knowledge structures and the potential for Schumpeterian innovation. Strategic Management Journal 19 (12), 1193–1201.
Gibbons M, Limoges C, Nowotny H, Schwartzman S, Scott P and Trow M (1994) The New Production Knowldege: The Dynamics of Science and Research in Contemporary Societies. Sage, London.
Goodman PS and Darr ED (1998) Computer-aided systems and communities: mechanisms for organizational learning in distributed environments. MIS Quarterly 22 (4), 417–440.
Granovetter M (1973) The strength of weak ties. The American Journal of Sociology 78 (6), 1360–1380.
Hamilton MA (2002) Heterogeneous organizational learning: overcoming the paradox. In Managing the Complex IV: Conference on Complex Systems and the Management of Organization (LISSACK M and STEELE D, Eds) Institute for the study of Coherent Emergence, Fort Myers, FL. http://isce.edu/ISCE_Group_Site/web-content/ISCE_Events/Naples_2002/Naples_2002_Papers/Hamilton.pdf (accessed 28 January 2008).
Hanneman RA and Riddle M (2005) Introduction to Social Network Methods, Riverside. University of California, Riverside, CA.
Hansen MT (1999) The search-transfer problem: the role of weak ties in sharing knowledge across organizational subunits. Administrative Science Quarterly 44 (1), 82–111.
Hansen MT (2002) Knowledge networks: explaining effective knowledge sharing in multiunit companies. Organization Science 13 (3), 232–248.
Herfindahl OC (1950) Concentration in the U.S. steel industry. PhD Thesis, Columbia University, New York.
Hood GM (2005) PopTools version 2.7.1. [WWW Document] http://www.cse.csiro.au/poptools (accessed 11 September 2006).
Hutt MD, Reingen PH and Ronchetto Jr JR (1988) Tracing emergent processes in marketing strategy formation. Journal of Marketing 52 (1), 4–19.
Jaccard P (1901) Distribution de la florine alpine dans la Bassin de Dranses et dans quelques régions voisines. Bulletin de la Société Vaudoise des Sciences Naturelles 37, 241–272.
Jensen MC and Meckling WH (1992) Specific and general knowledge and organizational structure. In Contract Economics (WERIN L and WIJKANDER H, Eds), p 251. Blackwell, Oxford.
Kao J (1996) Jamming: The Art and Discipline of Business Creativity. Harper Collins, New York.
Kitaygorodskaya N (2006) Measurement of team knowledge: transactive memory system and team mental models. In Proceedings of the Research Forum to Understand Business in Knowledge Society (MAULA M, Ed), pp 1–6, ICEB+eBRF, Tampere, Finland. http://www.ebrc.fi/kuvat/Kitaygorodskaya_paper.pdf (accessed 28 November 2007).
Klein KJ, Dansereau F and Hall RJ (1994) Levels issues in theory development, data collection, and analysis. The Academy of Management Review 19 (2), 195–229.
Klimoski R and Mohammed S (1994) Team mental model: construct or metaphor? Journal of Management 20 (2), 403–437.
Kogut B and Zander U (1996) What firms do? Coordination, identity, and learning. Organizational Science 7 (5), 502–518.
Krackhardt D (1990) Assessing the political landscape: structure, cognition, and power in organizations. Administrative Science Quarterly 35 (2), 342–369.
Krackhardt D and Hanson J (1993) Informal networks: the company behind the chart. Harvard Business Review 71 (4), 104–111.
Krackhardt D and Porter LW (1985) When friends leave: a structural analysis of the relationship between turnover and stayers' attitudes. Administrative Science Quarterly 30 (2), 242–261.
Krebs V (1998) Knowledge networks-mapping and measuring knowledge creation. [WWW Document] http://www.knetmap.com/knowledge-networks-mapping.html (accessed 26 June 2007).
Krebs V (2007) Social network analysis: a brief introduction, orgnet.com [WWW Document] http://www.orgnet.com/sna.html (accessed 23 June 2007).
Kuhn T and Corman SR (2003) The emergence of homogeneity and heterogeneity in knowledge structures during a planned organizational change. Communication Monographs 70 (3), 198–229.
Laseter T and Cross R (2007) The craft of connection. enews, January 31 http://www.strategy-business.com/media/file/enews-01-31-07.pdf (accessed 26 June 2007).
Levesque LL, Wilson JM and Wholey DR (2001) Cognitive divergence and shared mental models in software development project teams. Journal of Organizational Behavior 22 (2), 135–144.
Leydesdorff L (2007) Betweeness centrality as an indicator of the “Interdisciplinary” of scientific journals. Journal of the American Society for Information Science and Technology 58 (9), 1303–1319.
Liang DW (1994) The effects of top management team formation on firm performance and organizational effectiveness. PhD Thesis, Carnegie Mellon University, Pittsburgh, PA.
Liebowitz J (2007) Social Networking: The Essence of Innovation. Press/Rowman & Littlefield, Scarecrow.
Marengo L (1998) Knowledge distribution and coordination in organisations. In Trust and Economic Learning (LAZARIC N and LORENZ E, Eds), pp 227–246, Edward Elgar, Cheltenham.
Marsden PV (1990) Network data and measurement. Annual Review of Sociology 16, 435–463.
Mayo M and Pastor JC (2005) Networks and effectiveness in work teams: the impact of diversity. Working Paper No. WP05-10, Instituto de Empresa Business School, Madrid, Spain, http://latienda.ie.edu/working_papers_economia/WP05-10.pdf (accessed 23 May 2007).
Mello AS and Ruckes ME (2006) Team composition. Journal of Business 79 (3), 1019–1039.
Mohammed S and Dumville BC (2001) Team mental models in a team knowledge framework: expanding theory and measurement across disciplinary boundaries. Journal of Organizational Behavior 22 (2), 89–106.
Monge PR and Contractor NS (2000) Emergence of communication networks. In The New Handbook of Organizational Communication (JABLIN FM and PUTNAM LL, Eds), pp 440–502, Sage, Thousand Oaks.
Moorman C and Miner AS (1997) The impact of organizational memory on new product performance and creativity. Journal of Marketing Research 34 (1), 91–106.
Moreno JL (1934) Who Shall Survive? Foundations of Sociometry, Group Psychotherapy, and Sociodrama Nervous and Mental Disease Monograph 58. Nervous and Mental Disease Publishing Company, Washington, DC.
Morrison A and Rabellotti R (2005) Knowledge dissemination and informal contacts in an Italian wine local system. In Proceedings of The Danish Research Unit for Industrial Dynamics (DRUID) Tenth Anniversary Summer Conference on Dynamics of Industry and Innovation: Organizations, Networks and Systems (MASKELL P, Ed), pp 1–24, June 27–29, Copenhagen, Denmark. http://www2.druid.dk/conferences/viewabstract.php?id=2638&cf=18 (accessed 01 December 2007).
Mulgan G (1998) Connexity: Responsibility, Freedom, Business and Power in the New Century. Vintage, London.
Müller-Prothmann T (2005) Leveraging knowledge communication for innovation – framework, methods and applications of social network analysis in research and development. PhD Thesis, Freien Universität Berlin, Germany.
Obstfeld D (2005) Social networks, the Tertius Lungens orientation, and involvement in innovation. Administrative Science Quarterly 50 (1), 100–130.
Parise S, Cross R and Davenport TH (2006) Strategies for preventing a knowledge-loss crisis. Sloan Management Review 47 (4), 31–38.
Postrel S (2002) Islands of shared knowledge: specialization and mutual understanding in problem-solving teams. Organization Science 13 (3), 303–320.
Prat A (1996) Shared knowledge vs diversified knowledge in teams. Journal of the Japanese and International Economies 10 (2), 181–195.
Radcliffe-Brown AR (1940) On social structure. Journal of the Royal Anthropological Society of Great Britain and Ireland 70, 1–12.
Reagans R (2005) Preferences, identity, and competition: predicting tie strength from demographic data. Management Science 51 (9), 1374–1383.
Reagans R and McEvily B (2003) Network structure and knowledge transfer: the effects of cohesion and range. Administrative Science Quarterly 48 (2), 240–267.
Reagans R and Zuckerman EW (2001) Networks, diversity, and productivity: the social capital of corporate R&D teams. Organization Science 12 (4), 502–517.
Rice RE and Aydin C (1991) Attitudes toward new organizational technology: network proximity as a mechanism for social information processing. Administrative Science Quarterly 36 (2), 219–244.
Rodan S and Galunic C (2004) More than network structure: how knowledge heterogeneity influences managerial performance and innovativeness. Strategic Management Journal 25 (6), 541–562.
Rulke DL and Galaskiewicz J (2000) Distribution of knowledge, group network structure, and group performance. Management Science 46 (5), 612–625.
Sandström A (2004) Innovative policy networks – the relation between structure and performance. PhD Thesis, Lulea University of Technology, Sweden.
Sarbaugh-Thompson M and Feldman MS (1998) Electronic mail and organizational communication: does saying “Hi” really matter? Organization Science 9 (6), 685–698.
Scholten VE (2006) The early growth of academic spin-offs: factors influencing the early growth of Dutch spin-offs in the Life Sciences, ICT and Consulting. PhD Thesis, Wageningen University and Researchcentrum, The Netherlands.
Shaw ME (1954) Group structure and the behavior of individuals in small groups. Journal of Psychology 38, 139–149.
Simmel G (1950) The Sociology of Georg Simmel. Translated by KH Wolff. Glencoe, Free Press, Illinois.
Sperling BK (2005) Information distribution in complex systems to improve team performance. PhD Thesis, Georgia Institute of Technology.
Stewart AM, Mullarkey GW and Craig JL (2003) Innovation or multiple copies of the same lottery ticket: the effect of widely shared knowledge on organizational adaptability. Journal of Marketing Theory and Practice 11 (3), 25–44.
Tortoriello M (2005) The social underpinnings of absorptive capacity: external knowledge, social networks, and individual innovativeness. PhD Thesis, Tepper School of Business, Carnegie Mellon University.
Turner VW (1957) Schism and Continuity in an African Society: A Study of Ndembu Village Life. Manchester University Press, Manchester.
Tushman ML and Katz R (1980) External communication and project performance: an investigation into the role of gatekeeper. Management Science 26 (11), 1071–1085.
Uzzi B (1997) Social structure and competition in interfirm networks: the paradox of embeddedness. Administrative Science Quarterly 42 (1), 35–67.
Van Wijk R (2003) Organizing knowledge in internal networks – a multilevel study. PhD Thesis, Erasmus University, Rotterdam.
von Hayek FA (1937) Economics and knowledge. Economica 4 (13), 33–54.
Walsh J (1995) Managerial and organizational cognition. Organization Science 6 (3), 280–321.
Wasserman S and Faust K (1994) Social Network Analysis: Methods and Applications. Cambridge University Press, New York.
Wegner DM (1986) Transactive memory: a contemporary analysis of the group mind. In Theories of Group Behavior (MULLEN B and GOETHALS GR, Eds), pp 185–208, Springer-Verlag, New York.
Wellman B (1983) Network analysis: some basic principles. In Social Structure and Network Analysis (MARSDEN PV and LIN N, Eds) Sage, Beverly Hills.
Wellman B, Koku E and Hunsinger J (2006) Chapter 57: networked scholarship. In The International Handbook of Virtual Learning Environments (WEISS J, NOLAN J and HUNSINGER J, Eds), Vol. 14, pp 1429–1447, Springer International Handbooks of Education, Holland.
Wenger E and Snyder W (2000) Communities of practice: the organizational frontier. Harvard Business Review 78 (1), 139–145.
Wexler MN (2002) Organizational memory and intellectual capital. Journal of Intellectual Capital 3 (4), 393–414.
Wholey DR, Wilson AR, Riley W and Knoke D (2007) Work and talk: information provision by informal consulting in medical clinics. Strategic Management Research Center, University of Minnesota http://www.csom.umn.edu/assets/83536.pdf (accessed 01 June 2006).
Xerox (2002) Sharing knowledge through documents. Digital Perspectives 1 (5), Xerox Corporation, Corporate Integrated Marketing, Stamford, http://www.xerox.com/downloads/kstreet/sharing_english_.pdf (accessed 29 July 2002).
Zack MH (2000) Researching organizational systems using social network analysis. In Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS) (SPRAGUE RH, Ed), p 7, 4–7 January, Maui, Hawaii. http://web.cba.neu.edu/~mzack/articles/socnet/socnet.htm (accessed 23 June 2007).
Zack MH and McKenney JL (1995) Social context and interaction in ongoing computer-supported management groups. Organization Science 6 (4), 394–422.
Zuboff S (1988) In the Age of the Smart Machine. Basic Books, New York.
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Appendix
Appendix
An illustrative example:
We derived the knowledge heterogeneity measure from the knowledge distance matrix (D) obtained from the knowledge similarity matrix (S, Table 2). Like Rodan & Galunic (2004), we started by calculating the uniqueness of knowledge for each member.
The uniqueness of knowledge of a member i is some function of the uniqueness of each of his or her contacts. This is obtained by calculating, for each network member, the value u i given by formula (1):
Eq. (2) is the characteristic equation for extracting eigenvectors and eigenvalues. The uniqueness values at the level of the entire network was obtained by solving for Eq. (2) in which U is the m × 1 eigenvector corresponding to the eigenvalue of the first principal component, λ, obtained on the basis of D (the largest eigenvalue of D) using the UCINET command, Network>Centrality>Eigenvector.
We solved this equation using the PopTools Excel addin (version 2.7) (Hood, 2005). We should point out that the derivation of U and λ was based on the assumption of a symmetric matrix in which all entries are comprised between 0 and 1.
The vector U is the eigenvector composed of the uniqueness measures for each member. Thus, at the member's level, heterogeneity hi is given by formula (3):
The 1/m factor compensates for network size since the eigenvalue, λ, increases linearly with m (Rodan & Galunic, 2004). At the network level, knowledge heterogeneity is obtained by summing the values given for each of its members. As an example, the network in Figure 2 and the similarity matrix of Table 2 where a number in row i and column j indicates the proportion of knowledge common to members i and j (obviously, the amount of knowledge common to a member and herself is 100%, or 1):
and
Since λ=3.71, it follows that:
Thus, for the first member (i=1), h1 is equal to: 0.79/6=0.13. Applying the same formula to each and every member of the network and computing the average of h1, h2, h3, h4, h5, and h6, yields a network knowledge heterogeneity index of 0.295.
Using Rulke & Galaskiewicz's (2000, p. 616) formula, the knowledge heterogeneity index is equal to 0.7373 and using UCINET's average of the cohesion densities, it is equal to 0.7373 as well.
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Louadi, M. Knowledge heterogeneity and social network analysis – Towards conceptual and measurement clarifications. Knowl Manage Res Pract 6, 199–213 (2008). https://doi.org/10.1057/kmrp.2008.9
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DOI: https://doi.org/10.1057/kmrp.2008.9