The Influence of Executives’ Values on Corporate Responsibility Adoption
Bibliographic record
Abstract
The research aim of this inquiry is to understand how executives’ values influence the adoption of Corporate Responsibility practice. Corporate Responsibility (CR) is recognised as a values-laden concept which encompasses both normative and instrumental value orientations. Strategic Leadership Theory posits that senior executives are responsible for shaping their organisations’ strategic direction. Since humans are at the nexus of all decisions – and, according to Values Theory, human values are the underlying construct for motivations, goals and social ideals – executives’ values play an important role in influencing organisational approaches to CR adoption. While there is general agreement that values do influence Corporate Responsibility adoption, empirical evidence provides only partial support and some contradictory results. The paucity of qualitative research providing insights into the complexity of leaders’ values-to-action in business highlights a significant research gap in understanding the role of Strategic Leadership on CR adoption beyond normative studies. Adopting a constructionist interpretive research paradigm, this research inquiry explores the influence of executives’ values via in-depth semi-structured interviews as a data collection method. Twenty senior Canadian executive interviews were conducted. Using thematic analysis, this inquiry collects from the interview data common themes as well as divergences, providing a rich description of the executives’ values-to-CR adoption process. The data findings point to a number of factors that mediate the influence of values on CR adoption, and the types of CR practices. A tentative model is proposed that highlights the common patterns that emerged from the data analysis. This research inquiry contributes to a deepening of the Strategic Leadership knowledge, in particular the influence of values on organisational CR decisions; expands interpretivist qualitative studies in management studies; and contributes to practice by highlighting the importance of values in executive recruitment, business education and management development.
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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 | 0.015 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".