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Leader-Member Exchange in Flux: Exploring Longitudinal Profiles in the Era of Hybrid Work

2025· article· en· W4416007535 on OpenAlexaff
Marie‐Colombe Afota, Véronique Robert

Bibliographic record

VenueAcademy of Management Proceedings · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsContext (archaeology)Perspective (graphical)Longitudinal dataWork (physics)Longitudinal studyQuality (philosophy)Turnover

Abstract

fetched live from OpenAlex

Research on leader-member exchange (LMX) has been central to the leadership literature, emphasizing high-quality relationships between leaders and followers as desirable for a range of outcomes. While LMX literature traditionally views the quality of LMX relationships as stable over time, this perspective is increasingly being challenged. Accordingly, this study aims to (1) examine the evolution of LMX relationships over a 6-month period among established dyads and identify profiles of LMX trajectories; (2) assess the impact of the current hybrid work context on the LMX trajectories by focusing on teleworking intensity, frequency and amount of leader-member interactions, monitoring practices (observational or interactional), and leader response expectations (e.g., pressure to remain available and respond rapidly to solicitations outside work hours); and (3) analyze the implications of these trajectories for established LMX outcomes (i.e., emotional exhaustion, performance, and turnover intentions). Using three-wave longitudinal data from 769 workers across various industries, we identified five distinct profiles over a period of six months (i.e., High and Increasing; Moderate and Decreasing; Moderately Low and Decreasing; Moderate and Steady; Very Low and Increasing). These profiles had differing implications for the studied outcomes, further supporting their validity. The results demonstrated that teleworking intensity and frequency and amount of leader-member interactions did not impact profile membership. However, monitoring practices played a critical role: observational monitoring was linked to the least desirable profiles, while interactional monitoring was associated with the most desirable ones. Moreover, all three managerial practices examined in this study impacted LMX trajectories, regardless of profile membership. The implications for LMX theory and managerial practices in the hybrid work context are discussed.

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)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.057
GPT teacher head0.273
Teacher spread0.216 · 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 designObservational
Domainnot available
GenreEmpirical

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

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