Lindsey Cameron

Lindsey Cameron
  • Assistant Professor of Management

Contact Information

  • office Address:

    2027 SH-DH
    3620 Locust Walk
    Philadelphia, PA 19104

Research Interests: algorithms, gig economy/future of work, contemporary careers, financial well-being, labor issues, field research

Links: Personal Website, CV

Overview

Lindsey D. Cameron is an assistant professor of management at the Wharton School, University of Pennsylvania and holds an appointment in the sociology department. She is a fellow (member) at the Institute of Advanced Studies in Princeton and a Faculty Affiliate at the Berkman Klein Center for Internet and Society for the 2023- 2024 academic year. She is a current affiliate and former faculty fellow at the Data and Society Research Institute. Her research focuses on how algorithmic management is changing the modern workplace, with an emphasis on the gig economy. Professor Cameron has an on-going, seven-year ethnography of the largest sector of the gig economy, the ride-hailing industry, examining how algorithms management changes managerial control. She recently completed a study on how the COVID-19 pandemic affected workers on various gig platforms (TaskRabbit, Instacart, AmazonFlex, Uber, Lyft, DoorDash). She is currently working on a project on how the gig economy’s business model adapts in the Global South, with a focus on the implications for management and workers.

Professor Cameron’s work has been published in leading academic journals, including Administrative Science Quarterly, Organization Science, Journal of Applied Psychology, Organizational Behavior and Human Decision Process, Academy of Management Annals, Journal of Management Inquiry, Annual Review of Organizational Psychology and Organizational Behavior, and proceedings of the Association of Computing Machinery and the Academy of Management. She has won eleven best paper awards and several teaching awards, including the Wharton Teaching Excellence Award. She has published opinion pieces in Fast Company, Kiplinger’s, and the Society of Human Resource Management’s flagship magazine People & Strategy and her research has been mentioned in numerous media outlets including Bloomberg, NPR’s Marketplace, Fast Company, the World Economic Forum, CNBC, Forbes, The Skim, and Inc.

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Research

Pennsylvania Joint Taskforce on Worker Misclassification
PA Senate Democratic Policy Committee Hearing: Worker Misclassification and the Future of Work
Pennsylvania State Senate Democratic Policy Committee Hearing: Testimony on Ride-hailing Companies


  • Lindsey Cameron (2024), The Making of the “Good Bad” Job: How Algorithmic Management Manufactures Consent through Constant and Confined Choices, Administrative Science Quarterly, forthcoming.

    Abstract: This research explores how a new relation of production—specifically, the shift from human managers to algorithmic managers on digital platforms—manufactures workplace consent. While most research argues the task standardization and surveillance that accompanies algorithmic management will give rise to the quintessential “bad job” (Kalleberg, 2000), I find that, surprisingly, many workers report liking and finding choice while working under algorithmic management. Drawing on a seven-year qualitative study of the largest sector in the gig economy, the ridehailing industry, I describe how workers navigate being managed by an algorithm. I begin by showing how algorithms segment the work at multiple sites of human-algorithm interactions and that this configuration of the work process allows for more frequent and narrow choice. I find individuals use two sets of tactics. In engagement tactics, individuals generally follow the algorithmic nudges and do not try to get around the system, while in deviance tactics individuals manipulate their input into the algorithm. While the behaviors associated with these tactics are practical opposites, they both elicit consent, or active, enthusiastic participation to align one’s efforts with managerial interests, and workers seeing themselves as skillful agents. However, this choice-based consent can mask the more structurally problematic elements of the work, contributing to the growing popularity of what I call the “good bad” job.

  • Hatim A. Rahman, Arvind Karunakaran, Lindsey Cameron (2023), Taming Platform Power: Taking Accountability Into Account In the Management of Platforms, Academy of Management Annals.

    Abstract: Research on multi-sided platforms emphasizes how platform owners have accumulated significant power over other platform actors, such as producers and customers, arguing for the need to balance such power with accountability. We review two perspectives on platform accountability: a) a bottom-up, emergent perspective that focuses on the collective action taken by lower-powered platform actors such as producers (e.g., gig workers, app developers) to enhance rule adequacy and push back against platform owners’ power, and b) a top-down, institutional perspective that emphasizes the importance of preventing extractive opportunism and maintaining a level playing field among different platform actors by enabling legal, regulatory, and governance changes. The bottom-up perspective’s overarching focus is on procedural (rule-focused) fairness, while the top-down perspective’s focus is largely on distributive (outcome-focused) fairness. While both perspectives are important, they have limitations regarding platform accountability, especially given the power and informational asymmetries inherent among platform actors. Therefore, synthesizing across literatures, we provide a framework for platform accountability that accounts for both procedural and distributive fairness, and is based on a fundamental premise: multi-sided platforms require multi-sided accountability systems. Thus, our review proposes an approach for enforcing platform accountability that has the potential to rebalance the power between high-powered and low-powered platform actors.

  • M. Kulkarni, Lindsey Cameron, J. Gehman, V. Glaser, M. Greenwood, G. Islam, D. Lindebaum, S. Mantere, S. Pachidi, H. Rahman, E. Vaara, E. Van den Broek (2023), The Future of Research in an Artificial Intelligence Driven World, Journal of Management Inquiry, forthcoming.

    Abstract: Current and future developments in artificial intelligence (AI) systems have the capacity to revolutionize the research process for better or worse. On the one hand, AI systems can serve as collaborators as they help streamline and conduct our research. On the other hand, such systems can also become our adversaries when they impoverish our ability to learn as theorists, or when they lead us astray through inaccurate, biased, or fake information. No matter which angle is considered, and whether we like it or not, AI systems are here to stay. In this curated discussion, we raise questions about human centrality and agency in the research process, and about the multiple philosophical and practical challenges we are facing now and ones we will face in the future.

  • Lindsey Cameron, Laura Lamers, Ulrich Leicht-Deobald, Christoph Lutz, Jeroen Meijerink, Mareike Mohlmann (2023), Algorithmic Management: Its Implications for Information Systems Research, Communications of the Association for Information Systems.

    Abstract: In recent years, the topic of algorithmic management has received increasing attention in information systems (IS) research and beyond. As both emerging platform businesses and established companies rely on artificial intelligence and sophisticated software to automate tasks previously done by managers, important organizational, social, and ethical questions emerge. However, a cross -disciplinary approach to algorithmic management that brings together IS perspectives with other (sub-)disciplines such as macro - and micro -organizational behavior, business ethics, and digital sociology is missing, despite its usefulness for IS research. This article engages in cross-disciplinary agenda setting through an in-depth report of a professional development workshop (PDW) entitled “Algorithmic Management: Toward a Cross-Disciplinary Research Agenda” delivered at the 2021 Academy of Management Annual Meeting. Three leading experts (Mareike Möhlmann, Lindsey Cameron, and Laura Lamers) on the topic provide their insights on the current status of algorithmic management research, how their work contributes to this area, where the field is heading in the future, and what important questions should be answered going forward. These accounts are followed up by insights from the breakout group discussions at the PDW that provided further input. Overall, the experts and workshop participants highlighted that future research should examine both the desirable and undesirable outcomes of algorithmic management and should not shy away from posing ethical and normative questions.

  • Lindsey Cameron, Curtis Chan, Michel Anteby (2022), Heroes from Above But Not (Always) From Within?: Gig Workers Responses to the Public Moralization of their Work, Organizational Behavior and Human Decision Processes.

    Abstract: How do individuals react to the sudden public moralization of their work and with what consequences? Extant research has documented how public narratives can gradually moralize societal perceptions of select occupations. Yet, the implications of how workers individually respond and form self-narratives in light of—or in spite of—a sudden moralizing event remain less understood. Such an understanding is even more critical when workers are weakly socialized by their organization: a situation increasingly common today. During the COVID-19 pandemic, radically shifting public narratives suddenly transformed grocery delivery work, previously uncelebrated, into highly moralized “heroic” pursuits. Drawing on interviews (n=75), participant artifacts (n=85), and archival data (e.g., newspaper articles), we find that these workers (here, shoppers on the platform organization Instacart), left mainly to themselves, exhibited varying responses to this moralizing and that their perceived relations to the organization, customers, and tasks shaped these responses. Surprisingly, those who facilely adopted the hero label felt morally credentialled and were thus likely to minimize their extra-role helping of customers and show low commitment to the organization; in contrast, those who wrestled with the hero narrative, sought to earn those moral credentials, were more likely to embrace extra-role helping and remain committed to moralized aspects of the work. Our study contributes to literatures on the moralization of work and narratives by explaining why some workers accept a moralized narrative and others reject or wrestle with it, documenting consequences of workers’ reactions to such narratives, and suggesting how a moralized public narrative can backfire.

  • Lindsey Cameron and Jirs Meuris, The Perils of Pay Variability: Determinants of Worker Aversion to Variable Compensation in Low and Middle Wage Jobs. In Proceedings of the Eighty-second Annual Meeting of the Academy of Management. Online ISSN: 2151-6561, edited by Sonia Taneja, (2022)

  • Lindsey Cameron (2022), “Making Out” While Driving: The Relational and Efficiency Game in the Gig Economy, Organization Science.

    Abstract: On-demand or “gig” workers show up to a workplace without walls, organizational routines, managers, or even coworkers. Without traditional organizational scaffolds, how do individuals make meaning of their work in a way that fosters engagement? Prior literature suggests that organizational practices, such as recruitment and socialization, foster group belonging and meaningfulness, which subsequently leads to engagement, and that without these practices alienation and attrition ensue. My four-year qualitative study of workers in the largest sector in the on-demand economy (ridehailing) suggests an alternative and more readily available mechanism of engagement—workplace games. Through interactions with touchpoints—in this context, the customer and the app—individuals turn their work into games they find meaningful, can control, and “win.” In the relational game, workers craft positive customer service encounters, offering gifts and extra services, in the pursuit of high customer ratings, which they track through the app’s rating system. In the efficiency game, workers set boundaries with customers, minimizing any “extra” behavior, in the pursuit of maximizing money per time spent driving and they create their own tracking tools outside the app. Whereas each game resulted in engagement—as workers were trying to “win”—games were associated with two divergent stances or relationships toward the work, with contrasting implications for retention. My findings embed meaning-making in what is fast-becoming the normal workplace, largely solitary and structured by emerging technologies, and holds insights for explaining why people remain engaged in a line of work typically deemed exploitative.

  • Lindsey Cameron and Hatim Rahman (2022), Expanding the Locus of Resistance: The Constitution of Control and Resistance in the Gig Economy, Organization Science.

    Abstract: Existing literature examines control and resistance in the context of service organizations that rely on both managers and customers to control workers during the execution of work. Digital platform companies, however, eschew managers in favor of algorithmically mediated customer control—that is, customers rate workers, and algorithms tally and track these ratings to control workers’ future platform-based opportunities. How has this shift in the distribution of control among platforms, customers, and workers affected the relationship between control and resistance? Drawing on workers’ experiences from a comparative ethnography of two of the largest platform companies, we find that platform use of algorithmically mediated customer control has expanded the service encounter such that organizational control and workers’ resistance extend well beyond the execution of work. We found that workers have the most latitude to deploy resistance early in the labor process, but must adjust their resistance tactics because their ability to resist decreases in each subsequent stage of the labor process. Our paper thus develops understanding of resistance by examining the relationship between control and resistance before, during, and after a task, providing insight into how control and resistance function in the gig economy. We also demonstrate the limitations of platforms’ reliance on algorithmically mediated customer control by illuminating how workers’ everyday interactions with customers can influence and manipulate algorithms in ways that platforms cannot always observe.

  • Lindsey Cameron, B. Thomason, V. Conzon (2021), Risky Business: Gig Workers and the Navigation of Ideal Worker Expectations During the COVID-19 Pandemic, Journal of Applied Psychology.

    Abstract: Managers and customers often expect individuals to be "ideal workers" devoted entirely to work, and this devotion is typically displayed through being available to work at any time, on any day (Reid, 2015). During the COVID-19 pandemic, many individuals in lower-paid, customer-facing jobs were expected to not only be available but also to take on physical risk. However, the ideal worker literature has paid relatively little attention to how risk relates to ideal worker expectations, reflecting in part the extant literature's focus on professionals who face relatively little physical and financial uncertainty. In this article, we draw upon the experiences of nonprofessional "gig" workers (TaskRabbit workers) to examine how they manage customers' ideal worker expectations-including risk-using data from interviews (n = 49), postings from online worker forums social media, and official company communications. We show how these workers engage in different tactics to manage risk in response to customers' expectations, including two tactics-covering and withdrawing-that have not been discussed in prior ideal worker literature. In doing so, we expand scholarly understanding by showing how concerns about risk shape workers' responses to ideal worker expectations, particularly in customer-facing service work outside of traditional organizations.

  • 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, Organizational Behavior and Human Decision Processes.

    Abstract: The present research tested whether mindfulness, a state characterized by focused, nonjudgmental awareness of the present moment, increases prosocial behavior in the workplace or work-related contexts. Study 1a was a longitudinal field experiment at a US insurance company. Compared to workers under waitlist control, employees who were assigned to a daily mindfulness training reported more helping behaviors over a five day period both in quantitative surveys and qualitative daily diaries. Study 1b, conducted in a large consulting company in India, extends these findings with a field experiment in which co-workers rated the prosocial behavior of teammates in a round robin design. Moving from devoting time to devoting money, in Studies 2a and 2b we find that individuals randomly assigned to engage in a focused breathing meditation were more financially generous. To understand the mechanisms of mindfulness’ effects on prosocial behavior, Study 3 found support for empathy and moderate support for perspective taking as mediators. This study also examined the effects of induced state mindfulness via two different mindfulness inductions, focused breathing and loving kindness meditation. Our results indicate that secular state mindfulness can make people more other-oriented and helpful. This benefit holds even in the workplace, where being helpful toward others might face constraints but is nevertheless of great importance.

Teaching

All Courses

  • MGMT6120 - Managing Emerg Entrprse

    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.

  • MGMT9320 - Prosem in Mgmt

    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.

  • MGMT9700 - Research Methods in Mgmt

    Students taking the course will be introduced to the seminal readings on a given method, have a hands-on discussion regarding their application often using a paper and dataset of the faculty member leading the discussion. The goal of the course is to make participants more informed users and reviewers of a wide variety of methodological approaches to Management research including Ordinary Least Squares, Discrete Choice, Count Models, Panel Data, Dealing with Endogeneity, Survival/failure/event history and event studies, experiments, factor analysis and structural equation modeling, hierarchical linear modeling, networks, comparative qualitative methods, coding of non-quantitative data, unstructured text and big data simulations.

Awards and Honors

  • Best 40-Under-40 MBA Professor, Poets & Quants, 2023
  • Faculty Associate, Berkman Klein Center for Internet and Society, Harvard University, 2023-2024
  • Wharton Teaching Excellence Award, 2023
  • CTO Best Published Paper Award, 2023
  • MOC Best Symposium Award, 2023
  • Member of the Institute of Advanced Studies, Princeton, 2023-2024
  • Aspen Ideas Fellow, 2022
  • AOM HR Division Best Overall Paper Award, 2022
  • AOM Showcase Symposium, 2021-2022
  • MOC Best Symposium Award, 2021
  • OMT Best Paper Award (top 10% of submissions), 2021
  • OCIS Best Paper Award (top 10% of submissions), 2021
  • Winner, Industry Studies Dissertation Award, 2021
  • Runner-Up, Louis Pondy Best Dissertation Paper, 2021
  • Finalist, Grigor McClelland Doctoral Dissertation Award, 2021
  • Industry Studies Association’s Giarratani Rising Star Award, 2020
  • MOC Division Best Paper Award Nominee, 2020
  • Wharton Dean’s Research Grant, 2020
  • Psychology of Technology Dissertation Award, 2020
  • Likert Dissertation Prize, 2020
  • Mack Institute Research Fellowship for Innovation Management, 2019
  • Center for Advanced Studies of the Behavioral Sciences Summer Institute, Stanford University, 2019
  • OMT Above and Beyond the Call of Duty Reviewer Award, 2019
  • Ruth and Gilbert Whitaker Doctoral Fellowship, 2018-2019
  • OB Doctoral Student Consortium, 2018
  • Pre-Doctoral Fellow, Wharton School, University of Pennsylvania, 2017-2018
  • Bouchet Honor Society, 2017
  • AOM Showcase Symposium, 2014
  • Rotary Ambassadorial Scholar, 2005
  • Coca Cola National Scholar, 2001
  • USA Today All-Academic Team, 2001
  • Siemens-Westinghouse (formerly Intel) Competition, Semi-finalist, 2001
  • Bill Gates Millenium Scholar, 2000

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Not Sure How Much to Tip Your DoorDash Driver? That’s by Design

If you’re wondering how much of your tip actually goes to your food delivery driver, you’re not alone. Wharton’s Lindsey Cameron explains why it’s so hard for customers to decipher the bills from DoorDash, Uber Eats, and Grubhub.Read More

Knowledge at Wharton - 6/30/2023
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Wharton Magazine

Data: Superstitious Investors, Mindfulness at Work, and More
Wharton Magazine - 04/17/2020

Wharton Stories

Research Spotlight: Prof. Lindsey Cameron on Drivers in the Gig Economy

In Wharton Social Impact’s “Research Spotlight” series, we highlight recent research by Wharton professors and doctoral students whose research focuses on the intersection of business and impact. This month, we spoke with Lindsey Cameron, assistant professor of management at Wharton, about her research on workers’ experiences in the gig economy…

Wharton Stories - 11/29/2021
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