Developing sustainable management theory: goal-setting theory based in virtue
Bibliographic record
Abstract
Purpose – This paper responds to ongoing calls to develop alternative management theory to guide management practice. In particular, the purpose of the paper is to demonstrate the merit of developing sustainable management theory and organizational practices that parallel conventional management theory and practices. Sustainable theory is based on a variation of virtue theory that seeks to achieve multiple forms of well-being for multiple stakeholders in the immediate as well as distant future. To illustrate the approach, the authors develop a sustainable variation of goal setting theory. Design/methodology/approach – The paper includes three parts. First, the authors establish the need for developing sustainable management theory (based on virtue theory) that parallels conventional management theory. Second, the authors identify and briefly review the main tenets of goal setting theory and then describe a Sustainable variation of this theory. Finally, the authors discuss the implications of the paper for management and organization theory and practice. Findings – The conceptual arguments for a sustainable version of goal setting theory based in virtue are supported by research and practitioner examples. Originality/value – Although there is growing concern regarding the shortcomings of management theory and practice based on a materialist-individualist moral-point-of-view, few alternatives have been discussed in detail. This paper presents an alternative based in virtue theory and illustrates how it relates to goal setting theory and practice.
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 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 | 0.017 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".