Do family businesses “pay it forward”? seeking to understand the relationship between intergenerational behaviour and environmentally sustainable business practices
Bibliographic record
Abstract
Family business research has explored a number of important questions related to the complexity of intra-organizational family-based involvement (Sharma, 2004; Sharma, Hoy, Astrachen & Koiranen, 2007; Debicki, Matherne III, Kellermanns & Chrisman, 2009; Litz, Pearson & Litchfield, 2011), but the possibility of a potential link between the intentions and actions to facilitate or pursue the voluntary sacrifice by the current generation for generations still to come has largely gone unexplored. I seek to further explore how one’s intention and action, or succession strategy, to eventually pass an enterprise on to the next generation of family potentially influences how one manages that enterprise in the present. I conducted the research using a cross-sectional survey of 218 Manitoba family farms in 2011 to 2012. The data was collected in both an on-line and paper format. I have tested my hypotheses in the Manitoba family farm community to confirm a positive relationship between family farm succession strategy and environmental behaviour while controlling for industry specific measures. The proposed moderators of industry context (resource munificence) and familial context (intergenerational affinity) were not significant. The results provide further support to the notion that within the family business context, succession strategy and environmental behaviours are connected to intergenerational beneficence as “the extent to which members of the present generations are willing to sacrifice their own self-interest for the benefit of future others in the absence of economic or material incentives to present actors for doing so” (Wade-Benzoni & Tost, 2009:166).
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| 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".