Am I worthy to my leader? Role of leader-based self-esteem and social comparison in the LMX-performance relationship
Bibliographic record
Abstract
BACKGROUND: Most leadership theories, such as transformational, ethical, and servant leadership, emphasize the notion that leaders influence their followers’ in-role and extra-role work performance by treating them collectively and similarly. On the other hand, leader-member exchange (LMX) theory challenges this idea and argues that leaders treat followers differently and have high-quality exchange relationships with some followers and low-quality ones with others. However, few studies have examined LMX differentiated relationships in social contexts. OBJECTIVE: This study aims to investigate the role of employee leader-based self-esteem (LBSE) (i.e., employees’ self-evaluation of their worth derived from the quality of the relationship with their supervisor) in the relationship between LMX and two types of performance: task performance and organizational citizenship behaviour at individual level (OCB-I). Using an integrated theoretical framework of social comparison and self-consistency theories, we develop a moderated mediation model in which the mediating role of LBSE in the LMX-task performance and OCB-I relationships is conditional on the values of LMX social comparison (LMXSC). METHODS: Using a research sample of 298 manager-employee matching dyads working in 43 branches of a leading bank in Pakistan, results of hierarchical multiple regression analyses provided support for our developed model. RESULTS: We found that LMX positively led to LBSE which, in turn, served as a mediator between LMX and both performance types, with a stronger effect on OCB-I. We also found that by moderating the relationship between LMX and LBSE, LMXSC moderated the mediating role of LBSE, which had stronger effect on performance at high values of LMXSC than at low values. CONCLUSIONS: Following these findings, we discuss the contributions that this study offers to LMX and self-esteem literature and its managerial implications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".