The DOI matches its Crossref record; 299 of the 299 references it cites were found in a registry or an index.
Algorithms at Work: The New Contested Terrain of Control
Abstract
The widespread implementation of algorithmic technologies in organizations prompts questions about how algorithms may reshape organizational control. We use Edwards’ (1979) perspective of “contested terrain,” wherein managers implement production technologies to maximize the value of labor and workers resist, to synthesize the interdisciplinary research on algorithms at work. We find that algorithmic control in the workplace operates through six main mechanisms, which we call the “6 Rs”—employers can use algorithms to direct workers by restricting and recommending, evaluate workers by recording and rating, and discipline workers by replacing and rewarding. We also discuss several key insights regarding algorithmic control. First, labor process theory helps to highlight potential problems with the largely positive view of algorithms at work. Second, the technical capabilities of algorithmic systems facilitate a form of rational control that is distinct from the technical and bureaucratic control used by employers for the past century. Third, employers’ use of algorithms is sparking the development of new algorithmic occupations. Finally, workers are individually and collectively resisting algorithmic control through a set of emerging tactics we call algoactivism. These insights sketch the contested terrain of algorithmic control and map critical areas for future research.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“For advertisers, algorithmic ad delivery creates uncertainty about the targets they reach and more generally reduces their control over the output of their actions (Kellogg et al., 2020).”
From How online advertising targets consumers: The uses of categories and algorithmic tools by audience planners (2024) · cites this paper as Kellogg et al., 2020
In the citing paper
“Understanding that algorithmic systems are socially constructed and embedded in existing power dynamics also means these systems are neither created nor function outside the biases rooted in the organizational cultures within which they are implemented (Kellogg et al., 2020).”
From Algorithmic management in a work context (2021) · cites this paper as Kellogg et al., 2020
In the citing paper
“However, the use of advanced algorithms cre-ates new opportunities for managers to exercise control over the workforce (Kellogg et al., 2020; Shapiro, 2018).”
From Algorithmic management in a work context (2021) · cites this paper as Kellogg et al., 2020
In the citing paper
“Different from traditional staffing agencies, digital labor platforms manage gig workers via algorithmic management (Kellogg et al., 2020;McDonnell et al., 2021).”
From Gig work and gig workers: An integrative review and agenda for future research (2024) · cites this paper as Kellogg et al., 2020
In the citing paper
“Indeed, gig workers' customer evaluations not only serve as surrogates for their performance ratings but also affect the likelihood of their future orders (Kellogg et al., 2020).”
From Gig work and gig workers: An integrative review and agenda for future research (2024) · cites this paper as Kellogg et al., 2020
In the citing paper
“Management scholars have therefore provided very little insight into AI during the last two decades (Kellogg, Valentine, & Christin, 2020;Lindebaum, Vesa, & den Hond, 2020).”
From Artificial Intelligence and Management: The Automation–Augmentation Paradox (2021) · cites this paper as Kellogg, Valentine, & Christin, 2020
In the citing paper
“Whenever the key actors of an organization negotiate who is authorized (4.1 & 4.3) to modify the AI system and to what extent modification is to be undertaken, dimensions of power and control are on the table (Kellogg et al. 2020;Ren 2019;Vallas and Hill 2012).”
From Keeping the organization in the loop: a socio-technical extension of human-centered artificial intelligence (2023) · cites this paper as Kellogg et al. 2020
In the citing paper
“First, we identify six management functions that algorithms are currently able to perform: monitoring, goal setting, performance management, scheduling, compensation, and job termination.”
From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Kellogg et al., 2019
In the citing paper
“However, recent reviews and conceptualizations (Kellogg et al., 2019;Mateescu & Nguyen, 2019a;Schafheitle et al., 2020) consider algorithmic management as a technological phenomenon that is not contingent on the type of organization and can be found in a large array of work contexts.”
From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Kellogg et al., 2019
In the citing paper
“Algorithmic control of platforms is used to control the behaviour of users on platforms to achieve the platform owners’ corporate objectives”
From Content Creators Between Platform Control and User Autonomy: The Role of Algorithms and Revenue Sharing (2023) · cites this paper as Kellogg et al. 2020
In the citing paper
“Other studies have found that content creators are ‘leveraging algorithms’ (Kellogg et al. 2020, p. 391) and ‘working around the algorithm’ (Curchod et al. 2020, p. 17) by constantly uploading (Arriagada and Ibáñez 2020), A/B testing (Cotter 2019), and diversifying their incomes (Cutolo and Kenney 2021).”
From Content Creators Between Platform Control and User Autonomy: The Role of Algorithms and Revenue Sharing (2023) · cites this paper as Kellogg et al. 2020
In the citing paper
“Thus, they focus on content and topics that have delivered good key figures in the past, similar to algorithmic rewarding (Kellogg et al. 2020).”
From Content Creators Between Platform Control and User Autonomy: The Role of Algorithms and Revenue Sharing (2023) · cites this paper as Kellogg et al. 2020
In the citing paper
“Previous literature has already identified A/B testing (Cotter 2019), algorithmic gossip (Bishop 2019), and leveraging algorithms (Kellogg et al. 2020) as coping mechanisms.”
From Content Creators Between Platform Control and User Autonomy: The Role of Algorithms and Revenue Sharing (2023) · cites this paper as Kellogg et al. 2020
In the citing paper
“Empirical research shows that freelance platform workers respond to algorithmic control by gaming and at times, sabotaging algorithms to (re)gain control (Gandini, 2019;Kellogg et al., 2020;Newlands, 2020;Veen et al., 2020).”
From Algorithmic human resource management: Synthesizing developments and cross-disciplinary insights on digital HRM (2021) · cites this paper as Kellogg et al., 2020
In the citing paper
“This is the contested-terrain dynamic that the algorithmic management literature describes, deployed in a firm with no specialist function to contest it [21].”
From Borrowed Competence: When AI-Driven HR Builds Startups’ People Capability and When It Hollows It Out (2026) · cites this paper as [21]
In the citing paper
“The lack of transparency in algorithmic decision-making has been associated with dynamics of control, power, and surveillance (Kellogg et al., 2020).”
From Why do users trust algorithms? A review and conceptualization of initial trust and trust over time (2022) · cites this paper as Kellogg et al., 2020
In the citing paper
“Algorithmic management might perpetuate societal biases and reproduce discriminatory practices at work, whether the discrimination is built into the algorithms, or management's use of the algorithm, or as a result of customer's rating of workers (Noble 2018;Benjamin 2019;Kellogg et al. 2020;Akter et al. 2021;Zajko 2021;Heinrichs 2022).”
From Artificial intelligence and work: a critical review of recent research from the social sciences (2024) · cites this paper as Kellogg et al. 2020
Citations
Cites
(1994) · Journal of the American Dietetic Association · doi:10.1016/0002-8223(94)92216-0 · Cited by 46,726
ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-015-0816-y · Cited by 39,380
The Theory of Social and Economic Organization.
Salomon-Delatour, G., Weber, M., Henderson, A. M., & Parsons, T. (1948) · American Sociological Review · doi:10.2307/2086579 · Cited by 11,302
Burt, R. S. (1992) · doi:10.4159/9780674029095 · Cited by 9,093
The future of employment: How susceptible are jobs to computerisation?
Frey, C. B., & Osborne, M. A. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.08.019 · Cited by 8,727
Wing, J. M. (2006) · Communications of the ACM · doi:10.1145/1118178.1118215 · Cited by 8,102
Economy and Society: An Outline of Interpretive Sociology
Poggi, G. (1969) · Sociology · doi:10.1177/003803856900300342 · Cited by 6,851
Braverman, H. (1974) · Monthly Review · doi:10.14452/mr-026-03-1974-07_1 · Cited by 5,505
boyd, D., & Crawford, K. (2012) · Information, Communication & Society · doi:10.1080/1369118x.2012.678878 · Cited by 5,479
The Principles of Scientific Management.
Woolf, L. S., Taylor, F. W., Scott, W. D., & Goldmark, J. C. (1912) · The Economic Journal · doi:10.2307/2221959 · Cited by 5,254
Flagged first, then by citations
Research works printed but not linked: 94
- Ahmed S. I., 2016, Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems
- Aloisi A., 2015, Comparative Labor Law and Policy Journal, 37, 653
- Autor D. H., 2015, Performance and progress: Essays on capitalism, business and society
- Bailey D., 2019, Academy of Management
- Barocas S., 2016, California Law Review, 104, 671
- Berente N., 2014, Stakeholders, and Measurement (March 26, 2014)
- Beunza D., 2015, Systemic Risk Center
- Bodie M. T., 2017, University of Colorado Law Review, 88, 961
- Borch C., 2016, Socio-Economic Review, 15, 283
- Boyle E., 2018, Understanding latent style, Multithreaded
- Bradley A., 2019, Building our centralized experimental platform, Multithreaded, 2019
- Brayne S., Social Problems
- Brockman J., 2019, Possible minds: Twenty-five ways of looking at AI
- Burawoy M., 1985, The politics of production: Factory regimes under capitalism and socialism
- Calo R., 2017, Columbia Law Review, 117, 1623
- Cameron L., 2018, Academy of Management Annual Meeting
- Cameron L., 2019, 9th Biennial Positive Organizational Scholarship Conference
- Campbell H., 2018, The rideshare guy: A blog and podcast for rideshare drivers
- Chalmers M., 2003, Workshop at the Crossroads: The interaction of HCI and Systems Issues in UbiComp
- Cherry M. A., 2015, Comparative Labor Law and Policy Journal, 37, 577
- Christin A., 2017, Big Data & Society, Big Data & Society, 4, 1
- Christin A., 2019, International Journal of Communication
- Colner E., 2018, Three years of erch engineering, Multithreaded
- Common M., 2019, SSRN Electronic Journal
- Corporaal G. F., 2017, Platform sourcing–How fortune 500 firms are adopting online freelancing platforms
- Corporaal G. F., 2019, Reshaping Work Conference
- Crawford K., 2014, Boston College Law Review, 55, 93
- Curchod C., 2019, Administrative Science Quarterly, 1
- Davenport T. H., 2016, Only humans need apply: winners and losers in the age of smart machines
- Davidson A., 2016, The future Of work looks like a UPS truck
- De Stefano V., 2015, Comparative Labor Law and Policy Journal, 37, 471
- Deterding S., 2011, CHI 2011 gamification workshop proceedings
- Diakopoulos N., 2016, MIT Technology Review, 17, 2016
- Feller A., 2016, The Washington Post
- Felstiner A., 2011, Berkeley Journal of Employment and Labor Law, 32, 143
- Fourcade M., 2016, Socio-Economic Review, 15, 9
- Glynn P., 2018, Your client engagement program isn’t doing what you think it is, MultiThreaded
- Gomez-Uribe C. A., 2016, ACM Transactions on Management Information Systems (TMIS), 6, 13
- Gupta A., 2018, Crisis Text Line Blog, 2019
- Hall J. V., 2019, Pricing efficiently in designed markets: The case of ride-sharing
- Haraszti M., 1978, A worker in a worker’s state
- Howe J., 2006, Wired Magazine, 14, 1
- Jackson S. R., 2019, MIT Economic Sociology Working Group
- Karunakaran A., 2019, 35th European Group for Organizational Studies pre-colloquium
- Kaynak F. E., 2019, Bootcamps: A new path for occupational entry
- Kellogg K., 2018, Oxford Professional Services Conference
- Kellogg K., Organization Science
- Kessinger R., 2019, MIT Economic Sociology Working Group Seminar
- Kochan T. A., 2019, ILR Review, 72, 3
- Landay J., 2019, Smart interfaces for human-centered AI
- Lanier J., 2018, Harvard Business Review
- Lebovitz S., 2019, Doubting the diagnosis: How artificial intelligence increases ambiguity during professional decision making
- Leonardi P., 2018, Harvard Business Review, 96, 70
- Levy K., 2017, Berkeley Technology Law Journal, 32, 1183
- Levy K., 2018, International Journal of Communication, 12, 23
- Liu Y.-E., 2014, EDM
- Lix K., 2019, Expressly different: Interpretive diversity and team performance
- Lix K., 2019, Kharma scores and team learning in software development gigs
- McClelland M., 2012, Mother Jones
- Mindell D. A., 2015, Our robots, ourselves: Robotics and the myths of autonomy
- Mollick E. R., 2014, The Wharton School research paper series
- Myers J., 2019, An Expanded Role for State Actors: Coordinating Workforce Intermediation Across Multiple Geographies and Industries in Four U.S. States
- Nikolaidis S., 2012, Human-robot teaming using shared mental models
- O’Connor S., 2015, Financial Times, 8
- Pasquale F., 2015, The Hedgehog Review, 17, 30
- Pine K. H., 2016, Conference 2016 Proceedings
- Rahman H., 2017, Reputational ploys: Reputation and ratings in online labor markets
- Rahman H., 2019, From iron cages to invisible cages: Algorithmic evaluations in online labor markets
- Rahman H., 2019, How client managers restrain control to keep control: Evidence from technologically-mediated ‘Gigs’
- Ramsay R. A., 1966, Managers and men: Adventures in industry
- Ranganathan A., 2017, Academy of Management
- Raval N., 2016, Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing
- Rosenblat A., 2016, International Journal of Communication, 10, 3758
- Sachon M., 2017, KUKA: Planning for the future of automation
- Salehi N., 2015, Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
- Scheiber N., 2017, The New York Times, 2
- Scholz T., 2016, Challenging the corporate sharing economy
- Schwartz D., 2018, Work and Occupations, 45, 247, 10.1177/0730888418762263 · DOI
- Segal L., 2014, The decoded company: Know your talent better than you know your customers
- Stanculescu L. C., 2016, Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, 346
- Sundararajan A., 2016, The sharing economy: The end of employment and the rise of crowd-based capitalism
- Tabrizi B. N., 2019, Harvard Business Review, 13
- Thorp A. A., 2012, International Journal of Behavioral Nutrition and Physical Activity, 9, 1
- Truelove E., 2019, Integrating the crowd into the firm production process: The critical role of guided mobilization
- Valentine M., 2019, Algorithms and the org chart
- Vancil R. F., 1982, Implementing strategy: The role of top management
- Waardenburg L., 2018, 34th European Group for Organizational Studies (EGOS) Colloquium: Surprise in and around Organizations: Journeys to the Unexpected
- Walz S. P., 2014, The gameful world: Approaches, issues, applications
- Whyte W. H., 1956, The organization man
- Wilson H. J., 2017, Mit Sloan Management Review
- Winner L., 1980, Daedalus, 109, 121
- Wood A., 2019, SASE
- Zhou S., 2018, Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 1
- Zhou S., 2018, Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Cited by
Sorted by citations
Items 1,201–1,300 of 2,755
Trzebiatowski, T. M., Suh, E. Y., & Hollie, L. (2026) · Human Resource Management · doi:10.1002/hrm.70071 · Cited by 2
Rismawati, R., & Salju, S. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-4307-5.ch001 · Cited by 2
How platforms manufacture the ‘appropriate individual’
Jianu, B., Tussyadiah, I. P., & Miller, G. A. (2026) · Journal of Business Research · doi:10.1016/j.jbusres.2026.116168 · Cited by 2
Zhu, Y., Long, L., Huang, S., Zhang, Y. G., & Huang, Z. (2026) · Human Resource Management · doi:10.1002/hrm.70073 · Cited by 2
Ashraf, A., 闵庆飞, & Ashraf, A. (2026) · European Journal of Investigation in Health Psychology and Education · doi:10.3390/ejihpe16040052 · Cited by 2
Chung, H., & Muntaner, C. (2026) · Health Politics · doi:10.66534/hp.2026.0002 · Cited by 2
Prasetia, A. C. G., & Urciuoli, L. (2026) · Business Strategy and the Environment · doi:10.1002/bse.70846 · Cited by 3
Bayane, P. (2026) · Frontiers in Sociology · doi:10.3389/fsoc.2026.1804777 · Cited by 2
Surveillance, Spacing, Screaming and Scabbing: How Digital Technology Facilitates Union Busting
Reiber, F., Kim, N., McDonald, A., & Calacci, D. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791507 · Cited by 3
Against acceptance as legitimacy: Ethics and algorithmic management
Zientara, P. (2026) · Organization · doi:10.1177/13505084261443023 · Cited by 2
The Steered Self: Algorithmic Consumer Identity Theory in Platformized Markets
Camacho, L. J. (2026) · Businesses · doi:10.3390/businesses6020019 · Cited by 2
Bias in, symbolic compliance out? GPT 's reliance on gender and race in strategic evaluations
Botelho, T. L., & Wang, Q. (. (2026) · Strategic Management Journal · doi:10.1002/smj.70094 · Cited by 2
Automation, AI, and the Global Future of Work: Bridging North‐South Divides
Chigbu, B. I. (2026) · Sociology Compass · doi:10.1111/soc4.70198 · Cited by 2
Technology, Talents, and Control: How Artificial Intelligence Shapes Organization Capital
Chen, J., Bi, S., Zhou, Y., Wang, Y., & Lyu, X. (2026) · Emerging Markets Finance and Trade · doi:10.1080/1540496x.2026.2660310 · Cited by 2
Barbosa, I., & de Oliveira, E. R. (2026) · Journal of Modelling in Management · doi:10.1108/jm2-12-2025-0695 · Cited by 3
Karami, M. (2026) · Advances in Business and Management Research · doi:10.1016/j.abmr.2026.100005 · Cited by 2
Gratch, J. (2026) · Negotiation Journal · doi:10.1162/ngtn.a.65 · Cited by 3
Lin, W., Zhang, M., Zhang, W., & Zhang, C. (2026) · Systems · doi:10.3390/systems14050569 · Cited by 2
Wu, A., Zhang, S., Sun, L., Yuan, X., & Wang, X. (2026) · Behavioral Sciences · doi:10.3390/bs16050764 · Cited by 3
Provincializing Algorithmic Management: Platform Labour and Informal Economies in Accra, Ghana
Mensah, J. O., Ofoeda, J., Entee, E., Boye-Doe, Z., & Asamoah, G. K. (2026) · The Electronic Journal of Information Systems in Developing Countries · doi:10.1002/isd2.70068 · Cited by 2
AI and the production of truth in accounting practices: a Foucauldian analysis
Lehner, O. M. (2026) · Critical Perspectives on Accounting · doi:10.1016/j.cpa.2026.102862 · Cited by 7
Mansour, S. (2026) · International Journal of Manpower · doi:10.1108/ijm-08-2025-0635 · Cited by 4
The conditional turn: algorithmic transformation of organizational decision programmes
Liu, S. (2026) · Management Decision · doi:10.1108/md-01-2026-0301 · Cited by 2
Dong, H., Wang, L., & WangDu, F. (2026) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2026.103086 · Cited by 3
From Opacity to Transparency: User Behavior and Downstream Effects in Algorithmic Evaluation
Lakhiwal, A., Liu, C., Bala, H., & Suen, H.-Y. (2026) · Information Systems Research · doi:10.1287/isre.2023.0579 · Cited by 3
Fouda, B. M., & Medhat, M. (2026) · Frontiers in Sociology · doi:10.3389/fsoc.2026.1754294 · Cited by 2
Beyond recursive observation: relational viability in von Foerster’s cybernetics
Lavanderos, L. P. (2026) · Kybernetes · doi:10.1108/k-12-2025-3181 · Cited by 2
Patel, P. C., Rofcanın, Y., Kamaşak, R., & Belitski, M. (2026) · Human Resource Management Journal · doi:10.1111/1748-8583.70053 · Cited by 2
Continuous improvement in the age of AI: human and relational barriers in public higher education
Travasi, A., Bravi, L., Musso, F., & Murmura, F. (2026) · The TQM Journal · doi:10.1108/tqm-04-2026-0262 · Cited by 2
Wang, S., & Zhang, H. (2026) · Internet Research · doi:10.1108/intr-08-2025-1244 · Cited by 2
Kinana, O. B. B. (2026) · Horizons Intermediary Journal of Business Research · doi:10.67150/hijbr.v1i1.6 · Cited by 2
Adams, I. T., McLean, K. D., Vaughn, P. E., Fabila, A. R., & Alpert, G. P. (2026) · Evidence Base · doi:10.1080/30679125.2026.2696967 · Cited by 3
Nguyen, M., Trinh, N., & Malik, A. (2026) · German Journal of Human Resource Management Zeitschrift für Personalforschung · doi:10.1177/23970022261460618 · Cited by 3
Rathnayake, N., Ayentimi, D. T., & Amankwaa, A. (2026) · International Journal of Manpower · doi:10.1108/ijm-01-2026-0011 · Cited by 2
Objectification at work: The impact of algorithmic management on employee work engagement
Zhang, N., Zhang, Y., & Jin, C. (2026) · Acta Psychologica · doi:10.1016/j.actpsy.2026.107350 · Cited by 2
Positive psychology 4.0: a science of consequence for a world that can no longer wait
van Zyl, L. E. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1726065 · Cited by 2
From tool to supervisor: Uncovering the impact of AI roles on employee performance
Chi, Y., Song, Y. (., & Bai, X. (2026) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2026.124817 · Cited by 2
Kapoor, M. A., Vikas, S., & Sharma, S. (2026) · Frontiers in Human Dynamics · doi:10.3389/fhumd.2026.1883258 · Cited by 2
Goswami, I., D’Silva, N., & Choudhury, R. R. (2026) · Global Business Review · doi:10.1177/09721509261474254 · Cited by 2
Responsible Leadership and Human-Centered Governance in Technology-Mediated Organizations
Meyer, L., Schmid, A., Braun, S., & Keller, L. (2026) · Journal of Applied Organizational Systems and Behavior · doi:10.51847/vjz12wp6rv · Cited by 2
Sorooshian, S., Ahadi, N., & Liravi, P. (2026) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2026.101631 · Cited by 3
Mask-Like Alignment: A Psychopathy-Informed Heuristic for Persona-Driven LLM Deployment
Danagher, L. (2026) · Philosophy & Technology · doi:10.1007/s13347-026-01188-0 · Cited by 2
Resilience, Reworking, and Resistance
Anwar, M. A., & Graham, M. (2022) · Oxford University Press eBooks · doi:10.1093/oso/9780198840800.003.0006 · Cited by 2
Lord, C., Bates, O., & Friday, A. (2022) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3491101.3519865 · Cited by 2
Sánchez, F. R. (2022) · Cuadernos de Relaciones Laborales · doi:10.5209/crla.77774 · Cited by 2
Facilitating timelier research with a novel classification of workplace technology
Wang, B., Zhang, Y., & Li, B. (2022) · Industrial and Organizational Psychology · doi:10.1017/iop.2022.52 · Cited by 2
Vianna, F. R. P. M., Meneghetti, F. K., & Peinado, J. (2022) · Cadernos EBAPE BR · doi:10.1590/1679-395120210159x · Cited by 2
How online collaboration software shapes control at work? Evidence from news organizations
Omidi, A., & Zotto, C. D. (2022) · International Journal of Sociology and Social Policy · doi:10.1108/ijssp-10-2022-0262 · Cited by 2
Ewen, J. (2023) · PROKLA Zeitschrift für kritische Sozialwissenschaft · doi:10.32387/prokla.v53i211.2051 · Cited by 2
Organizing the digital working-class in Portugal during the Covid-19 pandemic
Roque, I. M. B. (2023) · Sociedade e Estado · doi:10.1590/s0102-6992-202338010001 · Cited by 2
Seufert, S., & Meier, C. (2023) · Springer eBooks · doi:10.1007/978-3-658-40079-8_16 · Cited by 2
Alizadeh, A., Hirsch, F., Benlian, A., Wiener, M. J., & Cram, W. A. (2023) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2023.763 · Cited by 2
The complex relationship between automation and work intensity: evidence from selected EU countries
Christenko, A. (2024) · International Review of Applied Economics · doi:10.1080/02692171.2024.2345605 · Cited by 2
The Human–Technology Continuum
Shen, G. C., Mullen, D. M., DePuccio, M. J., & Kerrissey, M. J. (2024) · Quality Management in Health Care · doi:10.1097/qmh.0000000000000490 · Cited by 2
Silver, K. (2024) · Journal of Business Ethics · doi:10.1007/s10551-024-05804-x · Cited by 2
AI Orientation, Capabilities, and Business Value: Case Study
Lee, M. C. M., Scheepers, H., Lui, A. K. H., & Ngai, E. W. T. (2024) · Journal of Computer Information Systems · doi:10.1080/08874417.2024.2423190 · Cited by 4
Trottier, M., Oiry, E., Martin, D., Gambs, S., & Thibault-Bellerose, A. (2024) · Ad machina l avenir de l humain au travail · doi:10.1522/radm.no8.1844 · Cited by 3
A Human-Centered Algorithmic Management Framework: A Literature Review
Jiang, Y., Fan, S., Zhu, Y., Wang, L., Ye, K., Zhou, J., Zhang, L., Wang, Z., Liu, W., & Rau, P. P. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-76827-9_4 · Cited by 4
Things at Work: How Things Contribute to Performing Work
Sandberg, J., Dall’Alba, G., & Stephens, A. M. (2025) · Journal of Management Studies · doi:10.1111/joms.13182 · Cited by 3
Zhou, Z., Xiang, S., & Xie, Q. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1451944 · Cited by 3
Liang, W., Jiang, X., & Ma, L. (2024) · IEEE International Conference on Cognitive Computing and Complex Data (ICCD) · doi:10.1109/iccd62811.2024.10843614 · Cited by 2
Jose, S. P. (2025) · New Technology Work and Employment · doi:10.1111/ntwe.12339 · Cited by 2
Serf‐ing the Net: Contrasting Uber Workers in the United Kingdom With Uber Neo‐Villeins in Ontario
Harvey, G., Prakasam, N., & Shakirzhanov, R. (2025) · Industrial Relations Journal · doi:10.1111/irj.12471 · Cited by 2
The paradox of AI assistance: enhancing quality while hindering efficiency in local hospitals
Dai, S., Xie, Z., Yang, Z., & Miao, W. (2025) · Journal of Digital Management · doi:10.1007/s44362-025-00009-2 · Cited by 4
Bernstein, E. S., & Li, S. X. (2025) · Management Science · doi:10.1287/mnsc.2022.02395 · Cited by 2
Algorithmic human resource management: A brief introduction and managerial toolkit
Grasiaswaty, N. (2025) · EWOP in Practice · doi:10.21825/ewopinpractice.94698 · Cited by 2
Li, J., Wang, Y., Xiong, W., Jiang, Y., Chen, Y., & Yang, Q. (2025) · Work · doi:10.1177/10519815251337922 · Cited by 2
Petroff, A. (2025) · Springer eBooks · doi:10.1007/978-3-031-86540-4_4 · Cited by 2
Doan, H. T. D., & Diehl, M. (2025) · European Journal of Work and Organizational Psychology · doi:10.1080/1359432x.2025.2517587 · Cited by 2
Management Controls and the Reproduction of Gender Inequality: A Review and Research Agenda
AleAhmad, Y., & Lupu, I. (2025) · European Accounting Review · doi:10.1080/09638180.2025.2522098 · Cited by 4
Digital ethnography and the labor process in food delivery gig work: a methodological reflection
Manriquez, M. (2025) · Journal of Organizational Ethnography · doi:10.1108/joe-11-2024-0090 · Cited by 3
AI at work, algorithmic bosses, and the ambivalence of automation
Aloisi, A., & Stefano, V. D. (2026) · Routledge eBooks · doi:10.4324/9781042003266-3 · Cited by 2
Grenzauflösungen: Arbeit, Aktivität und Freiwilligkeit im digitalisierten Kapitalismus
van Dyk, S., Graefe, S., & Lorig, P. (2025) · Berliner Journal für Soziologie · doi:10.1007/s11609-025-00570-7 · Cited by 2
Chang, Q., Zhang, J., & Xiao, X. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2543991 · Cited by 4
Digital Responsibility: Building Bridges Between Organization Theory and Information Systems
Trittin‐Ulbrich, H., Zimmer, M. P., Habersang, S., Dobusch, L., Gierlich-Joas, M., Schüßler, E., Mueller, B., Mihale-Wilson, C., Lanzl, J., Bohn, S., et al. (2025) · Schmalenbach Journal of Business Research · doi:10.1007/s41471-025-00234-5 · Cited by 3
The Growth of Process Expertise and the Absence of Process Experts in the Digital Age
Treem, J. W., & Barley, W. C. (2025) · Emerald Group Publishing Limited eBooks · doi:10.1108/s0733-558x20250000097004 · Cited by 2
Human Judgment and Responsibility after Artificial Intelligence Recommendations
Zhao, Y., Chen, L., Fauzi, A., & Hayati, N. (2024) · Journal of Applied Organizational Systems and Behavior · doi:10.51847/5ubpujo0hh · Cited by 2
Heiland, H., & Schaupp, S. (2022) · Arbeit und Organisation · doi:10.1515/9783839465240 · Cited by 7
Towards an Ethics of Hybrid Agency in Performance
Jamieson, D. (2020) · Performance Research · doi:10.1080/13528165.2020.1842023 · Cited by 2
Aloisi, A., & STEFANO, V. D. (2022) · Revista Internacional del Trabajo · doi:10.1111/ilrs.12245 · Cited by 2
Schwab, A., Shuumarjav, Y., Telkamp, J. B., & Beltran, J. R. (2022) · Research methodology in strategy and management · doi:10.1108/s1479-838720220000014007 · Cited by 2
The illusion of validity: how effort inflates the perceived validity of interview questions
Zhang, D. C., & Kausel, E. E. (2022) · European Journal of Work and Organizational Psychology · doi:10.1080/1359432x.2022.2144240 · Cited by 2
Kraak, J. M., Griep, Y., & Altman, Y. H. (2023) · Economic and Industrial Democracy · doi:10.1177/0143831x231161388 · Cited by 2
Situating the debates on technologies and work in the Asia Pacific
Liu, M., Zhang, H., & Lansbury, R. D. (2023) · Asia Pacific Journal of Human Resources · doi:10.1111/1744-7941.12386 · Cited by 2
Chy, M. T. I. (2024) · American Journal of Advanced Technology and Engineering Solutions · doi:10.63125/kwfvzw68 · Cited by 15
Drones in Military Warfare: The moral and emotional implications of an emerging technology
Rauch, M. S. (2021) · Academy of Management Proceedings · doi:10.5465/ambpp.2021.235 · Cited by 2
Saxena, D., & Guha, S. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4077245 · Cited by 2
Generating Knowledge Around the Unknowable Algorithm
Kim, B., & Mehrizi, M. H. R. (2022) · Academy of Management Proceedings · doi:10.5465/ambpp.2022.31 · Cited by 2
Gig platforms and technology-driven management – An overview of algorithms driving platform laborPreprint
Aliemuddin, W. (2022) · doi:10.14293/s2199-1006.1.sor-.pp4vwlu.v1 · Cited by 2
Opaque Overwatch: How Food-Delivery Workers Make Sense of Algorithmic Management in the Gig Economy
Weber, M., de Jong, A., & Remus, U. (2023) · Academy of Management Proceedings · doi:10.5465/amproc.2023.13983abstract · Cited by 2
Inteligência Artificial, ChatGPT e Estudos Organizacionais
de Oliveira, J. S., & Neves, I. B. S. (2023) · Organizações & Sociedade · doi:10.1590/1984-92302023v30n0013pt · Cited by 2
Cervi, L., Appleyard, L., Syed, T. A., Briggs, J., Padmanabhan, D., & Sinha, G. (2023) · SocArXiv (OSF Preprints) · doi:10.31235/osf.io/fgcus · Cited by 4
Labor control and the experience of work in the platform economy
Tirrell, C. (2023) · doi:10.17760/d20487636 · Cited by 3
Ethical Integration of AI into Organizational Behavior: Introducing the AI-IOB ModelPreprint
Ofem, O. E. (2024) · Research Square · doi:10.21203/rs.3.rs-5272515/v1 · Cited by 6
Chebeň, J. (2026) · Management Research Quarterly · doi:10.63029/h4amsv88 · Cited by 2
Ali, M., Asghar, T., Kadirova, Z., Vokhidova, M. K., & Akram, M. F. (2026) · Research Square · doi:10.21203/rs.3.rs-11412497/v1 · Cited by 4
Manky, O. (2026) · New Technology, Work and Employment · doi:10.1111/ntwe.70005 · Cited by 1
Panchanadikar, R., Hu, Y., & Freeman, G. (2026) · Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3805689.3812248 · Cited by 1
“Previous works have argued that such infrastructural shifts can obscure accountability, normalize dependency, and flatten distinctions between novice and expert performance, making it more difficult for workers to assess their own readiness or identify areas for growth [4, 39, 44, 63].”
Bureaucratic routines and error management in algorithmic systems
Pääkkönen, J. (2021) · Hallinnon Tutkimus · doi:10.37450/ht.107880 · Cited by 1
Mapping Exit, Voice, and Solidarity in the Case Studies
Doellgast, V. (2022) · Oxford University Press eBooks · doi:10.1093/oso/9780197659779.003.0003 · Cited by 1
Metadata
- Authors
- Kellogg, K. C., Valentine, M. A., & Christin, A.
- Affiliations
- Massachusetts Institute of Technology (US)
- Stanford University (US)
- Department of Communication Stanford School of Humanities and Sciences
- Venue
- Academy of Management Annals
- Publisher
- Academy of Management
- Published
- 2020-01
- Volume
- 14
- Issue
- 1
- Pages
- 366-410
- ISSN
- 1941-6067 (ISSN-L)
- 1941-6520
- OpenAlex
- W2990520658
- Cited by
- 2,732
- References
- 284
- Citations by year
- 2026: 1145 · 2025: 477 · 2024: 350 · 2023: 288 · 2022: 247 · 2021: 175 · 2020: 48
- FWCI
- 237.04
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Academy of Management Annals (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
- Social Sciences › Business, Management and Accounting › Industrial relations › Legal and Labor Studies
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Keywords
- algorithmic control, contested terrain, labour process theory, rational control, employee resistance, worker evaluation, worker discipline
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
