This thesis presents three arguments to support the inclusion of the analysis of communication patterns in organizational studies. Looking at an organization through the prism of social network analysis enables analytical assessment of interaction practices and broadens understanding of employees' performance. This research is based on two real-life cases for the application of Organizational Network Analysis within the realm of collaboration practices. This work has led to two important conclusions. The practical conclusion states that visualizing human resources through the network perspective provides a quantitative expression of collaboration practices, leadership positions, and organizational knowledge flows. Embracing this approach will allow companies to develop recognition mechanisms for acknowledging the role of teamwork and, at the same time, to fairly reward individual participation, decreasing undesired turnover. Conducted research reveals that central people in organizations are not necessarily the ones on the top of the hierarchy. Identifying informal leaders and ensuring their efficient physical allocation should improve knowledge flows and decrease coordination costs. Moreover, the identification of people who accumulate a high share of social capital gives an early indication of possible overload and consequent burnout and allows for building mechanisms to prevent the loss of human and information resources loss. A methodological conclusion reached in this work states that basing the analysis solely on the centrality statistics calculated in the static network significantly reduces the predictive power of the model. Communications are continuous by nature. As such, social networks must be periodically revisited or measured at least twice to ensure a good fit and higher predictive power of the model. Using longitudinal data extracted from digital communication tools can significantly enrich the interpretation of centrality statistics and provide an alternative view of individual performance. Both active and passive Organizational Network Analysis should be applied to ensure adequate human resource management.

Three essays on Organizations Networks and Knowledge

VELYKA, ANNA
2019

Abstract

This thesis presents three arguments to support the inclusion of the analysis of communication patterns in organizational studies. Looking at an organization through the prism of social network analysis enables analytical assessment of interaction practices and broadens understanding of employees' performance. This research is based on two real-life cases for the application of Organizational Network Analysis within the realm of collaboration practices. This work has led to two important conclusions. The practical conclusion states that visualizing human resources through the network perspective provides a quantitative expression of collaboration practices, leadership positions, and organizational knowledge flows. Embracing this approach will allow companies to develop recognition mechanisms for acknowledging the role of teamwork and, at the same time, to fairly reward individual participation, decreasing undesired turnover. Conducted research reveals that central people in organizations are not necessarily the ones on the top of the hierarchy. Identifying informal leaders and ensuring their efficient physical allocation should improve knowledge flows and decrease coordination costs. Moreover, the identification of people who accumulate a high share of social capital gives an early indication of possible overload and consequent burnout and allows for building mechanisms to prevent the loss of human and information resources loss. A methodological conclusion reached in this work states that basing the analysis solely on the centrality statistics calculated in the static network significantly reduces the predictive power of the model. Communications are continuous by nature. As such, social networks must be periodically revisited or measured at least twice to ensure a good fit and higher predictive power of the model. Using longitudinal data extracted from digital communication tools can significantly enrich the interpretation of centrality statistics and provide an alternative view of individual performance. Both active and passive Organizational Network Analysis should be applied to ensure adequate human resource management.
20-mag-2019
Inglese
GUERZONI, MARCO
Università degli Studi di Milano-Bicocca
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/76092
Il codice NBN di questa tesi è URN:NBN:IT:UNIMIB-76092