Information, Technology and Information Worker Productivity
Massachusetts Institute of Technology (MIT) - Sloan School of Management
Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER)
Marshall W. Van Alstyne
Boston University - Department of Management Information Systems; Massachusetts Institute of Technology (MIT) - Sloan School
September 11, 2011
Information Systems Research, Forthcoming
We econometrically evaluate information worker productivity at a midsize executive recruiting firm and assess whether the knowledge that workers accessed through their electronic communication networks enabled them to multitask more productively. We estimate dynamic panel data models of multitasking, knowledge networks and productivity using several types of micro-level data: (a) direct observation of 125,000 e-mail messages over a period of 10 months, (b) detailed accounting data on individuals’ project output and team membership for 1300 projects spanning 5 years, and (c) survey and interview data about the same workers’ IT skills, IT use and information sharing. We find that (1) more multitasking is associated with more project output, but with diminishing marginal returns, and that (2) recruiters whose network contacts have heterogeneous knowledge – an even distribution of expertise over many project types – are less productive on average but more productive when juggling diverse multitasking portfolios. These results show how multitasking affects productivity and how knowledge networks, enabled by IT, can improve worker performance. The methods developed can be replicated in other settings, opening new frontiers for research on social networks and IT value.
Number of Pages in PDF File: 40
Keywords: Social Networks, Productivity, Information Worker, IT, Multitasking, Dynamic Panel Data, System GMM
Date posted: November 5, 2006 ; Last revised: August 31, 2014
© 2015 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo2 in 1.203 seconds