An Empirical Analysis of Strategies and Efficiencies in Social Networks

Bulkley, Nathaniel; Alstyne, Marshall W. Van

doi:10.2139/ssrn.887406

Cited by 26 publications

(16 citation statements)

References 32 publications

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“…Network density-calculated as the total number of ties divided by the total possible number of ties -impacts teams' performance by fostering creativity from less closely connected groups. As demonstrated by a recent study by Bulkley and Van Alstyne (2006) strong email ties to teammates are associated with network advantages, corroborating the search transfer paradigm (Hansen, 1999). Hansen (1999) found that when information is complex, transferring it from one context to another becomes difficult without strong ties to support mutual understanding.…”

Section: Hypothesessupporting

confidence: 60%

Measuring creative performance of teams through dynamic semantic social network analysis

Zhang

Gloor²,

Grippa

2013

IJODE

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In this project we compare communication structure and content exchanged by members of creative, interdisciplinary teams of medical researchers, physicians, patients and caretakers with their creative output. We find that longitudinal social networking patterns and word usage predict creative performance. We collected the e-mail archives of 60 members of a community of researchers working on 12 projects improving various aspects of the daily lives of patients of Crohn's disease. Our results indicate that more creative projects show a decrease in group density, while more actors are involved, and more emails are exchanged, suggesting that a more successful project attracts more attention from many different people. We also found that members of more creative projects use more outspoken language, which gets more focused over time.

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Section: Hypothesessupporting

confidence: 60%

Measuring creative performance of teams through dynamic semantic social network analysis

Zhang

Gloor²,

Grippa

2013

IJODE

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“…For a number of years, it has demonstrated its usefulness in a business context (Borgatti and Foster 2003;Cross and Parker 2004;Cross et al 2002;Müller and Gronau 2007). Work on this topic focused on the effect of network structures on the performance of the individual (e. g. Ahuja et al 2003;Bulkley and Van Alstyne 2006;Cross and Cummings 2004;Gloor et al 2008;Mehra et al 2001;Moran 2005;Sparrowe et al 2001), groups (Balkundi and Harrison 2006;Brass 1981;Mayo and Pastor 2005;Reagans and Zuckerman 2001;Sparrowe et al 2001) and organizations (Ahuja 2000;Podolny and Baron 1997;Powell et al 1996;Raz and Gloor 2007;Uzzi 1996).…”

Section: State Of the Art Of Research And The Approachmentioning

confidence: 99%

Analysis of Informal Communication Networks – A Case Study

Fischbach

Gloor

Schoder

2008

Bus. Inf. Syst. Eng.

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It is becoming more and more important for knowledge workers to increase their productivity. However, there is a general lack of (semi-)automated, IT-supported data collection and evaluation approaches that allow insights into the processes and structures of an enterprise's internal networks and the activities of its knowledge workers. The article presents a prototype of an IT-supported instrument ("Social Badges") that supports automatic collection of informal, personal interaction between (knowledge) workers within an enterprise. The authors' aim is to introduce a novel approach which improves data quality over legacy methods. The approach uses Social Network Analysis (SNA) to make it easier for executives to analyze and manage informal communications networks. Its practical applicability is demonstrated by a case study. IntroductionIf the formal organization is the skeleton of a company, the informal is the central nervous system driving the collective thought processes, actions, and reactions of its business units.( Krackhardt and Hanson 1993, p. 104) Both the volume and importance of knowledge workers are growing as industrialized countries go through structural changes towards service-oriented societies (Albach 1999;Drucker 1999;Davenport 2005). According to Apte and Nath (2007), knowledge workers already account for 70 % of the labor force in the USA and for more than 60 % of its added value. Despite the importance of knowledgeintensive work, little is known about how to improve it compared to manual work processes. This is because the work performed by knowledge workers is complex and hard to measure (Aral et al. 2006; Mangelsdorf 2008; Ramírez and Nembhard 2004). It can be assumed that the way information is exchanged and distributed will have an influence on the relative productivity of groups and actors (Aral et al. 2006;Cross et al. 2003). The modern enterprise's productivity, efficiency and the ability to innovate thus all require an efficient structure and culture with respect to the exchange of knowledge between employees ( Knowledge is mainly exchange via informal, social communication networks whose structures often differ greatly from the enterprise's organizational structure and workflows (Krackhardt and Hanson 1993). At the same time, these structures have a decisive influence on the ability of employees, workgroups and the whole enterprise to deliver superior performance as they determine how quickly information can be propagated across a network, or whether stake holding employees will be able to contact each other (Cross and Parker 2004). In this context Cross et al. (2003, p. 8) emphasize that "one of the most consistent findings in the social science literature is that whom you know often has a great deal to do with what you come to know".Within this context the management of informal communication networks between enterprise staff becomes strategically significant (Davenport and Prusak 1998;Cross et al. 2003;Berglind and Scales 1987). Knowledge management focuses on those parts o...

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“…Most of the studies in the context of network structure and performance report a positive relationship between degree centrality and performance at an individual (Bulkley et al, 2006) and a group level (Tsai, 2001). Gloor et al (2007) found that the success of an alliance was directly correlated with the degree centrality of its members.…”

Section: Degree Centrality and Firm Performancementioning

confidence: 99%