Lindsey D. Cameron is an assistant professor of management at the Wharton School, University of Pennsylvania. Her research focuses on how changes in the modern workplace (e.g., algorithms/machine learning, short-term employment contracts, variable pay) affect work and workers. She recently completed a four-year ethnography of the largest employer in the gig economy, the ride-hailing industry, exploring how algorithms are fundamentally reshaping the nature of managerial control and how workers navigate this new workplace. Her research program is motivated by identifying and understanding how these changes affect how work is being organized and experienced by workers in a myriad of ways. She is currently studying how the COVID-19 pandemic is affecting gig workers as well as examining how ride-hailing workers on three continents navigate disputes.
In her prior career, Lindsey spent over a decade in the U.S. intelligence and diplomatic communities as a technical and political analyst and completed several overseas assignments in the Middle East, Africa, and Europe. She holds a PhD in Management from the University of Michigan, MS in Engineering Management from the George Washington University, and an SB from Harvard University in Electrical Engineering and Computer Science. She also studied Arabic intensively at the American University of Cairo.
Lindsey Cameron, “(Relative) Freedom in Algorithms: How Digital Platforms Repurpose Workplace Consent”. In Proceedings of the Eighty-first Annual Meeting of the Academy of Management. Online ISSN: 2151-6561, edited by Sonia Taneja, (2021)
Lindsey Cameron and H. Rahman, “(Not) Seeing Like an Algorithm: Managerial Control and Worker Resistance in The Platform Economy”. In Proceedings of the Eighty-first Annual Meeting of the Academy of Management. Online ISSN: 2151-6561, edited by Sonia Taneja, (2021)
Lindsey Cameron (2020), Allies or Adversaries?: Making Meaning of Work in the ‘New’ Gig Employment Relationship, In Guclu Atinc (Ed.), Proceedings of the Eightieth Annual Meeting of the Academy of Management. Online ISSN: 2151-6561.
Lindsey Cameron and M. Anteby (Under Review), Heroes from Above and Below: Workers’ Responses to the Moralization of their Work.
Lindsey Cameron, B. Thomason, V. Conzon (Under Review), Ideal Worker Image and Job Crafting During the COVID-19 Pandemic.
Description: Under review at Journal of Applied Psychology.
Lindsey Cameron (Under Revision), The Good Bad Job: Autonomy and Control in the Algorithmic Work Environment.
Description: Revise and Resubmit Requested at Administrative Science Quarterly.
Lindsey Cameron and Hatim Rahm (Under Revision), Resistance in the Age of Algorithms: Comparative Ethnography of Workers’ Resistance in Two Online Labor Markets.
Lindsey Cameron (Under Revision), Allies or Adversaries?: Making Meaning of ‘New’ Gig Employment Relationships.
Lindsey Cameron, A. Hafenbrack, G. M. Spreitzer, L. Noval, C. Zhang, S. Shaffakat (2019), Helping Others by Being in the Present Moment: Mindfulness and Prosocial Behavior at Work,.
Description: (Forthcoming) Organizational Behavior and Human Decision Processes.
Lindsey Cameron, L. E. Garrett, G. M. Spreitzer (2019), Contingent, Contract, and Alternative Work Arrangements, Oxford Bibliographies in Management.
This course is about managing during the early stages of an enterprise, when the firm faces the strategic challenge of being a new entrant in the market and the organizational challenge of needing to scale rapidly. The enterprises of interest in this course have moved past the purely entrepreneurial phase and need to systematically formalize strategies and organizational processes to reach maturity and stability, but they still lack the resources of a mature firm. The class is organized around three distinct but related topics that managers of emerging firms must consider: strategy, human and social capital, and global strategy.
This course is designed to provide students with an understanding of the methodological approaches we commonly think of as qualitative, with special emphasis on ethnography, semi- structured interviews, case studies, content analysis, and mixed-methods research. The course will cover the basic techniques for collecting, interpreting, and analyzing qualitative (i.e. non-numerical) data. In the spring quarter, the course will operate on two interrelated dimensions, one focused on the theoretical approaches to various types of qualitative research, the other focused on the practical techniques of data collection, such as identifying key informants, selecting respondents, collecting field notes and conducting interviews. In the fall semester, the course will operate on two interrelated dimensions, one focused on the theoretical approaches on building arguments and theory from qualitative data, the other focused on the practical techniques of data collection, such as analyzing data, writing, and presenting findings. Note: This class is part of a two-part sequence which focuses on qualitative data collection and analysis. The first of this course, offered in the Spring, focuses on data collection and the second half of the course, offered the following Fall, will focus on qualitative data analysis. Each course is seven weeks long. Students may take either class independently or consecutively.