So Close, Yet So Far Away: Exploring the Role of Psychological Distance from Climate Change on Corporate Sustainability
Bibliographic record
Abstract
Despite some improvements and increasing social pressures, most organizations seem to be stagnating in a superficial implementation of sustainability practices despite the accumulation of climate change consequences. Research on corporate sustainability has shown that external pressures and psychological factors influence managers’ environmental decisions. However, these psychological factors have been undertheorized in the management research field. The concept of psychological distance has shown promising results in studying environmental behaviors. This concept is rooted in the construal level theory and is defined as the subjective experience of feeling that something is close or far away from the self, the here and the now. Therefore, it represents a relevant path for exploration in research on corporate sustainability. The main goals of this integrative review are to explore how the concept of psychological distance has been employed in research on corporate sustainability and to explore related concepts from this research field. Additionally, concepts that are related to the four dimensions of psychological distance (i.e., temporal, spatial, social, and hypothetical) are critically discussed. The links between these concepts and their impacts on sustainability endeavors within organizations are then visually presented through a conceptual map, which forms the main contribution of this review. Further theoretical contributions are presented, the implications for managers are discussed, and future research avenues are proposed.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".