Evidence map›Paper›PMID 42709758›Full record

ArticlePloS one2026

How to break free from the "tool" dilemma? A study on the impact of perceived algorithmic control on sustainable value co-creation behavior.

Xuan Liu, Yuqing Wang, Haowei Zheng, Yuci Chen

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xuan LiuSchool of Economics and Management, Nanjing Tech University, Nanjing, China.
Yuqing WangSchool of Economics and Management, Nanjing Tech University, Nanjing, China.ORCID https://orcid.org/0009-0009-9876-5485
Haowei ZhengSchool of Economics and Management, Nanjing Tech University, Nanjing, China.
Yuci ChenSchool of Economics and Management, Nanjing Tech University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the growing prevalence of algorithmic technologies, algorithmic management has become a dominant control mechanism in the gig economy, profoundly shaping platform workers' psychological states and behaviors. Grounded in objectification theory and trait activation theory, this study examines how perceived algorithmic control (PAC) affects platform workers' sustainable value co-creation behavior (SVCB), highlighting the mediating role of workplace objectification (WO) and the moderating role of algorithm aversion (AAV). Using a two-wave survey (n = 285) and a scenario-based experiment (PAC experimental vs. control group; n = 216), the study finds that: (1) PAC significantly negatively affects SVCB; (2) PAC increases WO, which in turn reduces SVCB; (3) AAV positively moderates the indirect effect of PAC on SVCB through WO. This study advances understanding of the psychological mechanisms linking PAC to SVCB in gig work settings. It provides actionable insights for enhancing algorithmic governance and fostering sustained engagement among platform workers.

Indexed as

AlgorithmsWorkplaceHumansSurveys and Questionnaires

Identifiers

PMID42709758
PMCPMC13552789

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.