Back to the future: The effect of returning family successions on firm performance
Bibliographic record
Abstract
Abstract Research Summary We study successions from a non‐family CEO back to a family CEO, which we label “Type‐R" successions. In our sample of 489 Italian family firms experiencing the departure of non‐family CEOs, these successions represent 42% of all cases. Our difference‐in‐differences results indicate that family firms undertaking Type‐R successions experience an 18% superiority in profitability. Exploring the heterogeneity underlying this result, we find that Type‐R successions produce weaker results in contexts that are highly volatile and that rely on innovative inputs before succession. Finally, in studying the drivers of the performance increase, we find that Type‐R successions reduce labor costs and spur efficiency. Collectively, our evidence suggests that Type‐R successions improve performance by leveraging family assets while avoiding dysfunctional nepotism and other parochial family priorities. Managerial Summary How does CEO succession affect family business performance? In this article, we study an unexplored yet common succession pattern in mature family firms—the appointment of a family member following the tenure of an outside CEO. Surprisingly, we find that when, after a period of professional leadership, a family CEO returns to lead the company; the firm exhibits an 18% advantage in profitability. This result is more prevalent in stable industries, where traditional family assets prove especially valuable. A key takeaway of our study is that family leadership can enhance performance in companies that have already professionalized their governance, and thus have learned to reconcile meritocratic principles with family‐based assets.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".