Multiple temporal perspectives extend sustainable competitiveness
Bibliographic record
Abstract
Purpose In operations and supply chain management, time is largely one-dimensional – less is better – with much effort devoted to compressing, efficiently using, and competitively exploiting clock-time. However, by drawing on other literatures, the purpose of this paper is to understand implications for the field of operations management if we also emphasize how humans and organizations experience time, termed process-time, which is chronicled by events and stages of change. Design/methodology/approach After a brief review, the limitations of the recurrent time-oriented themes in operations management and the resulting short-termism are summarized. Next, sustainability is offered as an important starting point to explore the concept of temporality, including both clock- and process-time, as well as the implications of temporal orientation and temporal conflict in supply chains. Findings A framework that includes both management and stakeholder behavior is offered to illustrate how multiple temporal perspectives might be leveraged as a basis for an expanded and enriched understanding of more sustainable competitiveness in operations. Social implications Research by others emphasizes the importance of stakeholders to competitiveness. By recognizing that different stakeholder groups have varying temporal orientations and temporality, managers can establish objectives and systems that better reflect time-based diversity and diffuse temporal conflict. Originality/value This paper summarizes how time has been incorporated in operations management, as well as the challenges of short-termism. Sustainability forms the basis for exploring multiple perspectives of time and three key constructs: temporal orientation, temporality, and temporal conflict. A framework is proposed to better incorporate temporal perspectives as a basis for competitiveness in operations and supply chain management.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.027 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".