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Record W3022140202 · doi:10.1108/jibr-05-2018-0144

Relational age and leader–member exchange: mediating role of perceived trust

2020· article· en· W3022140202 on OpenAlexaff
Megha Gupta, Kanika T. Bhal, Mahfooz A. Ansari

Bibliographic record

VenueJournal of Indian Business Research · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsDyadPsychologySocial psychologyOriginalityPerceptionLoyaltyPerspective (graphical)Value (mathematics)CreativityPolitical science

Abstract

fetched live from OpenAlex

Purpose Drawing on similarity-attraction hypothesis and generational gap literatures, this study aims to examine the impact of age difference in a leader–member dyad on leader–member exchange (LMX). The study hypothesized that relational age would impact the subordinates-reported LMX. However, given that leaders have structural power over subordinates and hence have mechanisms of interaction available to them, the age difference might not determine their perception of quality of LMX. The study also hypothesized that generation gap in values and beliefs leads to lack of trust, on the part of subordinates, which in turn might be the reason for poor quality of LMX. Design/methodology/approach A total of 200 leader–member dyads from five organizations in the National Capital Region of India were used in this study. Data were collected via separate structured questionnaires for leaders and members, which comprised of standard scales of LMX and perceived trust, and demographics. Findings Hypotheses received substantial support from the data with a few exceptions. Only the loyalty dimension of perceived trust mediates the relationship between relational age and member perception of LMX. Research limitations/implications Results have implications for relational age and LMX interventions. However, the results are to be viewed in the light of members’ perspective. While this is a common practice in LMX research, it would be interesting to explore leaders’ trust and psychological reactions as well, for additional insights into leadership practice. Originality/value Limited work has been done to explore the impact of relational age on LMX, that too mediated by trust. An attempt has been made in this study to do so via leader–member dyads.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.095
GPT teacher head0.314
Teacher spread0.219 · 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 teacher head, not a consensus.

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

Citations7
Published2020
Admission routes1
Has abstractyes

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