seguendo la mia parte
bibliotecaria, ho visto che su questi temi Wiener ha scritto con
altri 1 articolo molto citato: Alexander Benlian et al., «Algorithmic Management», Business
& Information Systems Engineering 64, fasc. 6 (2022):
825–39, https://doi.org/10.1007/s12599-022-00764-w.
in accesso aperto.
così si fa flipped classroom e si arriva sapendo già un po' di cose
(se come per me l'argomento è nuovo, in questa forma di studio e non
di discorso pubblico)
Maurizio
Il 05/11/26 11:25, Daniele Quercia via
nexa ha scritto:
Algoactivism:
How Platform Workers Contest Algorithmic Management
Algorithmic
management (AM) has become a defining feature of online labor
platforms (OLPs), profoundly shaping platform workers’ control
over their working conditions. Prior research has documented
diverse forms of worker resistance to AM—or algoactivism—yet
existing studies rest on two problematic assumptions. First,
they often assume that algoactivistic practices are uniformly
accessible and arise directly from workers’ perceptions of
structural constraints. Second, they assume that such
practices are primarily reactive forms of resistance broadly
targeted at the OLP’s AM system. These assumptions obscure
heterogeneity in workers’ motivations and resources, as well
as variation in how algoactivistic practices unfold. This
study develops a more nuanced understanding of platform
workers’ algoactivism by tracing how corresponding practices
emerge through situated, reflective, and resource-dependent
processes. Drawing on the contested terrain lens from labor
process theory, we conceptualize the interplay between OLPs
and workers as an ongoing struggle over control of working
conditions. We examine this struggle in the context of Uber, a
widely recognized extreme case of AM. Using a
computer-assisted grounded theory approach that integrates
topic modeling with qualitative coding procedures across
multiple data sources, we develop a process-theoretical model
of how platform workers contest AM. Our model centers on three
recurring dynamics—reassessing terrain, exploring
opportunities for contestation, and contesting terrain through
algoactivistic practices—and yields two core theoretical
contributions. First, we show that worker algoactivism depends
on continual terrain reassessments and uneven capacities to
engage in three forms of resourcing: algorithm, market, and
voice resourcing. Second, we theorize algoactivism as a
heterogeneous and multi-arena phenomenon comprising
self-optimizing, distancing, and confronting practices that
vary in their logics, targets, and durability. Together, these
contributions advance a more dynamic and agentic understanding
of worker algoactivism and provide actionable insights for the
design and governance of platform-mediated work.
Martin holds the Chair of Business Information Systems,
esp. Business Engineering at TU Dresden, Germany. He is also an
Affiliated Researcher at FAU Erlangen-Nürnberg (Germany) and the
Stockholm School of Economics Institute for Research (Sweden).
Before joining TU Dresden, he was an Associate Professor at
Bentley University, USA. His research focuses on algorithmic
control and management, digital transformation processes,
human-AI collaboration, and value creation through open data.
His work has been published in leading Information Systems
journals, including MIS Quarterly (MISQ), Information Systems
Research (ISR), and the Journal of Management Information
Systems (JMIS). He currently serves as Senior Editor for the
Information Systems Journal(ISJ) and as Associate Editor for
Business & Information Systems Engineering (BISE) and ISR.
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daniele.quercia@polito.it
Si è stati invitati da Daniele
Quercia a [Responsible AI] Algoactivism, Martin Wiener
Algorithmic management (AM) has become a defining
feature of online labor platforms (OLPs), profoundly
shaping platform workers’ control over their working
conditions. Prior research has documented diverse
forms of worker resistance to AM—or algoactivism—yet
existing studies rest on two problematic assumptions.
First, they often assume that algoactivistic practices
are uniformly accessible and arise directly from
workers’ perceptions of structural constraints.
Second, they assume that such practices are primarily
reactive forms of resistance broadly targeted at the
OLP’s AM system. These assumptions obscure
heterogeneity in workers’ motivations and resources,
as well as variation in how algoactivistic practices
unfold. This study develops a more nuanced
understanding of platform workers’ algoactivism by
tracing how corresponding practices emerge through
situated, reflective, and resource-dependent
processes. Drawing on the contested terrain lens from
labor process theory, we conceptualize the interplay
between OLPs and workers as an ongoing struggle over
control of working conditions. We examine this
struggle in the context of Uber, a widely recognized
extreme case of AM. Using a computer-assisted grounded
theory approach that integrates topic modeling with
qualitative coding procedures across multiple data
sources, we develop a process-theoretical model of how
platform workers contest AM. Our model centers on
three recurring dynamics—reassessing terrain,
exploring opportunities for contestation, and
contesting terrain through algoactivistic
practices—and yields two core theoretical
contributions. First, we show that worker algoactivism
depends on continual terrain reassessments and uneven
capacities to engage in three forms of resourcing:
algorithm, market, and voice resourcing. Second, we
theorize algoactivism as a heterogeneous and
multi-arena phenomenon comprising self-optimizing,
distancing, and confronting practices that vary in
their logics, targets, and durability. Together, these
contributions advance a more dynamic and agentic
understanding of worker algoactivism and provide
actionable insights for the design and governance of
platform-mediated work.
Martin holds the Chair of Business Information
Systems, esp. Business Engineering at TU Dresden,
Germany. He is also an Affiliated Researcher at FAU
Erlangen-Nürnberg (Germany) and the Stockholm School
of Economics Institute for Research (Sweden). Before
joining TU Dresden, he was an Associate Professor at
Bentley University, USA. His research focuses on
algorithmic control and management, digital
transformation processes, human-AI collaboration, and
value creation through open data. His work has been
published in leading Information Systems journals,
including MIS Quarterly (MISQ), Information Systems
Research (ISR), and the Journal of Management
Information Systems (JMIS). He currently serves as
Senior Editor for the Information Systems Journal(ISJ)
and as Associate Editor for Business & Information
Systems Engineering (BISE) and ISR.
Subscribe to future talk announcements: Anyone outside
Bell Labs can receive talk announcements by
subscribing to the mailing list. To subscribe, send an
empty email with the subject line "Subscribe RAI" to daniele.quercia@polito.it