MétaCan
Menu
Back to cohort

The Impact of Non-Territorial Office Space on Employee Performance

2025· article· en· W4416007152 on OpenAlexaff
Magdalena Dobrajska, Arnaud Banoun, Lucas Dufour, Massimo Maoret

Bibliographic record

VenueAcademy of Management Proceedings · 2025
Typearticle
Languageen
FieldPsychology
TopicFacilities and Workplace Management
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRelocationSpace (punctuation)Knowledge workerEmployee researchJob satisfactionEmployee engagementBoundary (topology)Employee morale

Abstract

fetched live from OpenAlex

In this paper, we analyze the relocation of the headquarters of a consulting company from a traditional to a non-territorial collaborative office environment. Using a quasi-experimental research design, we examine the impact of this relocation on both objective and subjective employee performance as well as employee satisfaction. We find that the shift to a flexible office enhances employee satisfaction and fosters an environment conducive to collaborative work. However, employee performance is adversely affected when relocated knowledge workers´ activity profile involves a low degree of collaboration or requires focused attention rather than switching attention from one project to another. This study contributes to the literature on flexible work, physical space and managing knowledge workers by highlighting the boundary conditions of adoption of innovative office design.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

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.

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

Opus teacher head0.013
GPT teacher head0.314
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAcademy of Management ProceedingsSame topicFacilities and Workplace ManagementFrench-language works237,207