2-1 Activity: Case Study:
Uber's Use of Technology-Mediated Control to Manage Drivers
Amanda Putzier
Southern New Hampshire University
IT 482: IT Operations and Systems Planning
Instructor Carla Paton
May 17th, 2026
, Uber Technologies represents one of the most discussed and extreme examples of TMC
in practice, operating a ride-hailing platform in over 65 countries through an almost entirely
algorithmic management system that has replaced traditional human supervision (Wiener et al.,
2021). As reported by PBS (PBS NewsHour, 2019), Uber has conducted approximately 10
billion trips since the start, which is roughly 15 million per day, generating a vast amount of
behavioral data that powers its automated management approach. The following responses
address the five discussion questions related to Uber's use of TMC, drawing on the case study
and supporting resources.
Question 1: Alignment Between Uber's Mission Statement, Business Model, and TMC
Uber's official mission is to "reimagine the way the world moves for the better", a
commitment to making transportation universally accessible, reliable, and affordable for riders
and a meaningful earning opportunity for drivers (Uber, 2025). Its business model is built on a
dual value proposition: offering riders on-demand, cashless transportation while offering drivers
the flexibility to work on their own schedule and access a large pool of ride requests. These two
groups are mutually dependent, and maintaining the balance between them at massive scale is
precisely what makes TMC necessary. As PBS (PBS NewsHour, 2019) reported, Uber operates
in 65 countries and completes approximately 15 million trips per day, a volume that makes
traditional human supervision of individual drivers operationally impossible and economically
unsustainable.
TMC aligns directly with Uber's mission because the company must ensure consistent,
predictable service quality across millions of daily rides without employing drivers as full-time
staff. Cram and Wiener (Cram & Wiener, 2020) define TMC as the use of digital technologies to
influence workers to behave according to organizational expectations, a definition that maps
precisely onto how Uber operates. The algorithm serves as both a virtual supervisor and a
behavioral guide, enabling Uber to pursue its mission of reliable transportation everywhere
without the legal or financial obligations of a traditional employer-employee relationship
(Wiener et al., 2021). In short, TMC is not merely incidental to Uber's business model, it is the
structural mechanism through which the company delivers on its stated mission.
Question 2: Effectiveness of Uber's "Automated Manager" as a Managerial Control
System
Uber's automated manager relies on what Cram and Wiener (Cram & Wiener, 2020)
describe as technology that fully automates the managerial role, removing the human controller
entirely and replacing them with algorithms that configure, enact, and deliver control to workers.
In Uber's case, the app monitors drivers' acceptance rates, star ratings, locations, and driving
behaviors in real time. PBS (PBS NewsHour, 2019) reported that economists studying Uber
describe its data collection practices as generating a "treasure trove" that enables the company to
understand and influence driver behavior with a precision no human manager could replicate.
The automated system operates through behavioral nudges, push notifications, earnings targets,
Uber's Use of Technology-Mediated Control to Manage Drivers
Amanda Putzier
Southern New Hampshire University
IT 482: IT Operations and Systems Planning
Instructor Carla Paton
May 17th, 2026
, Uber Technologies represents one of the most discussed and extreme examples of TMC
in practice, operating a ride-hailing platform in over 65 countries through an almost entirely
algorithmic management system that has replaced traditional human supervision (Wiener et al.,
2021). As reported by PBS (PBS NewsHour, 2019), Uber has conducted approximately 10
billion trips since the start, which is roughly 15 million per day, generating a vast amount of
behavioral data that powers its automated management approach. The following responses
address the five discussion questions related to Uber's use of TMC, drawing on the case study
and supporting resources.
Question 1: Alignment Between Uber's Mission Statement, Business Model, and TMC
Uber's official mission is to "reimagine the way the world moves for the better", a
commitment to making transportation universally accessible, reliable, and affordable for riders
and a meaningful earning opportunity for drivers (Uber, 2025). Its business model is built on a
dual value proposition: offering riders on-demand, cashless transportation while offering drivers
the flexibility to work on their own schedule and access a large pool of ride requests. These two
groups are mutually dependent, and maintaining the balance between them at massive scale is
precisely what makes TMC necessary. As PBS (PBS NewsHour, 2019) reported, Uber operates
in 65 countries and completes approximately 15 million trips per day, a volume that makes
traditional human supervision of individual drivers operationally impossible and economically
unsustainable.
TMC aligns directly with Uber's mission because the company must ensure consistent,
predictable service quality across millions of daily rides without employing drivers as full-time
staff. Cram and Wiener (Cram & Wiener, 2020) define TMC as the use of digital technologies to
influence workers to behave according to organizational expectations, a definition that maps
precisely onto how Uber operates. The algorithm serves as both a virtual supervisor and a
behavioral guide, enabling Uber to pursue its mission of reliable transportation everywhere
without the legal or financial obligations of a traditional employer-employee relationship
(Wiener et al., 2021). In short, TMC is not merely incidental to Uber's business model, it is the
structural mechanism through which the company delivers on its stated mission.
Question 2: Effectiveness of Uber's "Automated Manager" as a Managerial Control
System
Uber's automated manager relies on what Cram and Wiener (Cram & Wiener, 2020)
describe as technology that fully automates the managerial role, removing the human controller
entirely and replacing them with algorithms that configure, enact, and deliver control to workers.
In Uber's case, the app monitors drivers' acceptance rates, star ratings, locations, and driving
behaviors in real time. PBS (PBS NewsHour, 2019) reported that economists studying Uber
describe its data collection practices as generating a "treasure trove" that enables the company to
understand and influence driver behavior with a precision no human manager could replicate.
The automated system operates through behavioral nudges, push notifications, earnings targets,
