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The Dark Side of Powerful Platform Owners: Aspiration Adaptations of Digital Firms

2024· article· en· 13 citations· W4399765187 on OpenAlex· 10.5465/amp.2022.0169

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

Candidate categories
none
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Theoretical or conceptualConsensus signal: Theoretical or conceptual
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.393
Threshold uncertainty score
0.409
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.005
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Opus teacher head0.025
GPT teacher head0.244
Teacher spread
0.219 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

This study provides a timely and critical perspective on the negative influences of powerful platform owners (PPOs) on the strategy aspiration adaptations of digital firms operating on these platforms. Contrary to the tenets of the behavioral theory of the firm, the aspiration adaptation of digital firms is largely influenced by PPOs rather than autonomously based on market- and competition-based referents. We call this Faustian bargain—the trade-off between the utility and advantages offered by PPOs’ technology affordance and the loss of aspiration adaptation control of independent digital firms—the “dark side” of powerful platforms. Drawing on resource-dependency logic and illustrative cases, we uncover how PPO characteristics, structural mechanisms, and the use of undesirable tactics manifest this phenomenon. In addition to uncovering the dynamics of an increasingly critical managerial and scholarly phenomenon, we provide much-needed implications for PPO governance practices and policies. Further, we advocate the formation of new institutions that can match the dynamic development of the digital platform economy with adaptive regulations and enforcement, superseding existing but ineffective antitrust laws mainly based on the pre-digital world.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

The record

Venue
Academy of Management Perspectives
Topic
Digital Platforms and Economics
Field
Business, Management and Accounting
Canadian institutions
Western University
Funders
not available
Keywords
Great RiftBusinessAdaptation (eye)Far side of the MoonPsychologyNeuroscienceAstronomyPhysics
Has abstract in OpenAlex
yes