HUMAN CAPITAL, SOCIAL CAPITAL, AND EXECUTIVE COMPENSATION: HOW DOES THE SLICE OF PIE EXECUTIVES APPROPRIATE COMPARE TO WHAT THEY BRING TO THE TABLE?
Bibliographic record
Abstract
Prior research has identified the manner in which human capital, social capital, and other intangible resources create value for organizations. Among such resources, those contributed by a firm's top managers have been singled out as particularly important for the generation and preservation of competitive advantage. However, the costs incurred to gain access to these resources, which reside at the individual and relational levels rather than at the firm level, are rarely considered. In this dissertation, I focus on individual executives as the level of analysis instead of the traditional view of firms as unitary actors in order to study intra-organizational value appropriation. I focus on the most direct and economically significant form of value appropriation by top managers: executive compensation. I introduce a theoretical framework linking executive compensation to executive-level intangible resources including human capital and social capital. I distinguish between generic and firm-specific forms of capital due to differences in the causal mechanisms linking each type of resource to compensation. Generic resources convey market power and are directly appropriable by executives. Firm-specific resources have no value outside the firm and therefore do not convey market power, yet they will convey a different sort of power derived from familiarity, visibility, and legitimacy. Drawing on a sample of 71 executives from 36 publicly-traded US firms in high-technology industries, I provide empirical results that are broadly supportive of three of four hypotheses. Executive compensation is found to be positively related to generic human capital (measured by the breadth of executives' experience across multiple industries), generic social capital (external network size, external network range) and firm-specific social capital (the strength of intra-TMT ties, internal network size, criticality of internal ties, criticality of external ties). I find no evidence linking executive compensation to firm-specific human capital. These results demonstrate the hazard of focusing on the value created by human capital and social capital without also considering the costs firms incur to access those resources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".