M. Lynne Markus

M. Lynne Markus (born c. 1950) is an American Information systems researcher, and John W. Poduska, Sr. Chair of Information Management, Bentley University, who has made fundamental contributions to the study of enterprise systems and inter-enterprise systems, IT and organizational change, and knowledge management.

M. Lynne Markus
Bornc. 1950 (age 6970)
Alma materCase Western Reserve University
OccupationProfessor
Consultant
EmployerBentley University

Education

Markus received her B.S. in 1972 from the University of Pittsburgh, and her PhD in Organizational Behavior in 1979 from the Case Western Reserve University.

Career and research

She was formerly a member of the Faculty of Business at the City University of Hong Kong (as Chair Professor of Electronic Business), the Peter F. Drucker Graduate School of Management at Claremont Graduate University, the Anderson Graduate School of Management (UCLA), and the MIT Sloan School of Management.

Markus' research interests are in the fields of "effective design, implementation and use of information systems within and across organizations; the risks and unintended consequences of information technology use; and innovations in the governance and management of information technology."[1]

Her work in these areas has been published in several high-impact peer-reviewed journals, and set the stage for much of the future work in these areas. She is one of the most widely cited researchers in the field of information systems.[2]

Her article The Technology Shaping Effects of E-Collaboration Technologies – Bugs and Features was selected as the best article published in 2005 in the International Journal of e-Collaboration. The article Industry-Wide Information Systems Standardization as Collective Action: The Case of the U.S. Residential Mortgage Industry, which she co-authored, was selected as the paper of the year for 2006 in the journal MIS Quarterly.[3]

Awards and honours

Selected publications

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gollark: Technically yes but I can't be bothered.
gollark: There are probably statistical tests we could apply. Also we would need to obtain MANY dataeoforms.
gollark: I hope not! This would undermine public trust in quantitative gay analysis!
gollark: What? The bots' reports aren't even stable.

References

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