Bouncing forward or bouncing back? How family firms enact resilience in times of crisis
Bibliographic record
Abstract
Purpose The study aims to develop theoretical understanding about how family-run businesses navigate unexpected and highly disruptive events by examining how family-based resilience capacity is variously transformed into an organizational capability. Design/methodology/approach The study relies on a qualitative comparative case study design to explore how Croatian family-run businesses navigated market and operational disruptions brought on by the global coronavirus (COVID-19) pandemic. Drawing on semi-structured interviews and organizational data, this study compares how family-run businesses operating in different industries experienced and coped with disruptions. Using inductive qualitative coding methods, patterns across codes were identified and aggregated into dimensions that describe two broad approaches for leveraging family social capital in the enactment of organizational resilience. Findings The analysis shows that family-run businesses may employ family social capital in retrospective and prospective ways. A retrospective approach involves targeted and conservative uses of family social capital, wherein the aim is to maintain organizational functioning and return to “business as usual”. In contrast, a prospective approach employs these resources in a more strategic and flexible way to adapt to a “new” future. While both approaches can enable firms to successfully navigate crises, these approaches differ in terms of their temporal orientation and implications for marketing flexibility. Originality/value The study contributes to a better understanding of how family social capital can be differentially leveraged in times of crises, and how these differences may stem from having temporal orientations that focus on either preserving the past or adapting to new conditions. The study advances theorizing at the intersection of organizational resilience and family business by deepening understanding of the heterogeneity of ways in which family businesses manage change for long-term business continuity. For owners and managers of family-run business, the study provides insights into how unexpected disruptions can be managed and how businesses might respond to fast-changing market conditions.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".