Understanding project champions’ ability to gain intra‐organizational commitment for environmental projects
Bibliographic record
Abstract
Abstract A key enabler of environmental projects is the ability of the project champion to gain commitment to the project from other stakeholders in his or her organization. This paper develops a model of commitment‐gaining success that is based on intra‐organizational influence theory. The model also includes project payback, customer pressure, government regulation, top management support and the project champion's position in the organizational hierarchy. The model was tested using survey data from 241 environmental professionals describing their attempts to gain the buy‐in of purchasing managers, operations managers, industrial engineers and others for environmental projects. The results (obtained from hierarchical regression analysis) show that intra‐organizational commitment is positively associated with the project champion's influence behavior—in particular, the champion's use of three influence tactics (inspirational appeals, consultation and rational persuasion) and avoidance of a fourth tactic (ingratiation). Commitment is also positively associated with project payback and with top management support for the environment and negatively associated with environmental regulation. The paper contributes to the OM knowledge base on environmental project implementation by bringing new theory to bear on the topic, by focusing on individual‐level, rather than organization‐level, variables and by taking a confirmatory, large sample approach which complements extant exploratory research. In addition, the paper contributes to the OM field by evaluating various antecedents to cross‐functional integration. The results also provide specific guidance to those who champion environmental projects within their companies.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".