Leadership behavior, satisfaction, and the balanced scorecard approach
Bibliographic record
Abstract
Purpose A literature review has revealed that a sales manager's transformational leadership has a positive impact on the job satisfaction of salespeople, while job satisfaction has significant influence on salespeople's work behaviors. The purpose of this paper is to examine the relationship between the transformational leadership of sales managers and the job satisfaction of salespeople. Design/methodology/approach The research was designed as a quantitative study, and the population was identified as salespeople in the consumer product industry in Taiwan, resulting in 123 individual surveys for analysis. Findings The findings supported the hypothesis that there is a positive and statistically significant relationship between sales managers' transformational leadership and sales associates' job satisfaction. The result identified the predictors of sales managers' transformational leadership on the sales associates' job satisfaction through regression analysis. Originality/value The balanced scorecard (BSC) was originally intended to solve problems related to the historical nature of financial measures in accounting approaches. The purpose of this paper is to make a contribution to this literature by focusing on a major issue that has been less investigated, namely, the linking of the BSC perspective to the empirical investigation of leadership behaviors using statistical and technical tools and to predict employee satisfaction. The paper suggests applying Kaplan and Norton's BSC, which includes the perspectives of financial, customer, internal business, and innovation and learning measures to consider the effects of leadership behaviors on employee job satisfaction.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".