Family Ownership, Governance, Management, and the Power Consumption Efficiency in Private Firms
Bibliographic record
Abstract
Environmental sustainability is increasingly prominent in organizational research; however, mainstream discourse often narrows its focus to contexts where organizational activities produce on-site toxic emissions, overlooking the broader impact of remote pollution from inefficient resource use. This oversight creates a critical knowledge gap, as direct pollution is routinely monitored, whereas remote pollution is generally ignored. This study addresses this gap by examining power consumption and the factors influencing firms' (in)efficient energy use. Specifically, we investigate how corporate governance structures in family and non-family firms shape environmental performance in this unregulated area. We focus on the role of employee agency and explore whether family ownership, governance, and management enhance the impact of workforce size on firms' power consumption efficiency. Analyzing 14,959 firm-year observations from 2,908 privately owned firms in Atlantic Canada, we find that family ownership does not significantly affect power consumption efficiency, while family governance and executive involvement improve it, though this advantage quickly diminishes and inverts as firm size increases. We discuss the theoretical and practical implications of these findings.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".