Family-Controlled Business Groups: An In-Depth Review and a Microfoundations-Based Research Agenda
Bibliographic record
Abstract
It is now well-established that business groups (BGs)—an inimitable multifirm structure that enables legally distinct firms to take coordinated action—constitute a dominant organizational form in many economies around the world. The BG phenomenon has attracted sustained scholarly attention over the last three decades. Despite the shift in BG research toward BG heterogeneity and strategic performance outcomes, prior reviews and the last meta-analysis a decade ago focus narrowly on the question of whether BGs confer a financial performance advantage on affiliated firms. We provide a more extensive account of the BG effect and an in-depth review of the theoretical approaches used in prior work by focusing only on family-controlled business groups (FBGs)—the dominant type of BG. We make three contributions. First, we develop a parsimonious organizing framework to summarize extant FBG research in a nuanced way—specifying the relationships examined, theoretical explanations advanced, and empirical evidence adduced. This summary reveals that extant FBG theorizing is predominantly structurally focused. Second, we propose a reorientation of FBG research toward a microfoundations-based approach. We develop a scheme for theoretical “taking” and “giving” of relevant microfoundational frameworks from contiguous management subfields to systematically identify potential paths ahead for future FBG theorizing. Finally, we granularly discuss illustrative microfoundation-based frameworks, outlining how their application could both enrich and better integrate FBG research with contiguous management subfields such as entrepreneurship, family business, and strategy research. We thus consolidate our understanding of FBG research, identify gaps, and suggest promising pathways for future work.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".