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Download or read book Essays on Social Networks and Information Worker Productivity written by Lynn Wu and published by . This book was released on 2011 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, I examine how information, information technology, and social networks affect information worker productivity. The work is divided into three essays based on tracking detailed communication patterns of information workers in the high-tech industry. Essay 1: "Social Network Effects on Performance and Layoffs: Evidence from the Adoption of a Social Networking Tool." By studying the changes in employees' networks and performance before and after the introduction of a social networking tool, I find that a structurally diverse network (low in cohesion and rich in structural holes) has a positive effect on work performance. The size of the effect is smaller than traditional estimates, suggesting that omitted individual characteristics may bias the estimated network effect. I consider two intermediate mechanisms by which a structurally diverse network is theorized to improve work performance, information diversity (instrumental) and social communication (expressive), and quantify their effects on two types of work outcomes: billable revenue and layoffs. Analysis shows that the information diversity derived from a structurally diverse network is more correlated with generating billable revenue than is social communication. However, the opposite is true for layoffs. Friendship, as approximated by social communication, is more correlated with reduced layoff risks than is information diversity. Field interviews suggest that friends can serve as advocates in critical situations, ensuring that favorable information is distributed to decision makers. This, in turn, suggests that having a structurally diverse network can drive both work performance and job security, but that there is a tradeoff between either mobilizing friendship or gathering diverse information. Essay 2: "Identification of Influence: An Experimental Platform for Understanding the Relationship between Social Networks and Performance." This study creates an experimental platform for identifying the relationship between social networks and performance. While a large body of literature has examined the correlations between certain network topologies and performance, little research has shown a definitive causal linkage. I address this problem through conducting three sets of randomized field experiments using an on-line experimental platform at a large information technology firm. The platform enables randomly selected employees to achieve certain network characteristics. By examining work performance before and after the experiment, I plan to show the causal relationship between networks and productivity. Essay 3: "Water Cooler Networks: Performance Implications of Informal Face-to-Face Interaction Structures in Information-Intensive Work." This study examines the performance characteristics of face-to-face interaction networks and finds that their structural properties are important for effective knowledge transfer and productivity. We argue that network theory should incorporate the implications of media choice, and particularly differences between face-to- face and electronic communication, when assessing how networks affect individual performance. We introduce a new methodology, using Sociometric badges, to record precise data on face-to-face interaction networks for a group of workers in a large IT manufacturing firm over a one-month period. Linking these data to detailed performance metrics, we find that 1) network cohesion is associated with higher worker productivity, in contrast to previous findings in email data; 2) cohesion in face-to-face networks is associated with even higher performance during complex tasks, suggesting that cohesion complements information-rich media for transferring the complex knowledge needed to complete such tasks; 3) while information-seeking from many colleagues creates disruptions, more interactions with a few key strong-tie informants speeds up work. Face-to-face networks have more explanatory power than physical-proximity networks, suggesting that information flows in actual conversations (rather than individuals' correlated exposure to common environmental factors through physical proximity) are driving our results. These results augment our understanding of how media choice and network structure interact, shedding light on the organizational effects of face-to-face interaction. The methods and techniques we introduce are replicable, creating opportunities for new lines of research into the consequences of face-to-face interaction in organizations.