An exploratory investigation of the effects of supply chain complexity on delivery performance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As just-in-time delivery has become increasingly commonplace and customer demands continue to tighten, the importance of fast, reliable delivery cannot be overstated. This is particularly true for firms competing internationally, where the complexity of the supply chain must be managed within a global network. To explore the linkage between supply chain complexity and delivery, a two-dimensional framework is proposed that conceptualizes the degree of complexity embedded in a supply chain along two major dimensions: (1) form of technology and (2) nature of information processing. Technology is characterized using a conventional operations strategy framework of structural and infrastructural elements. In contrast, information processing captures both the level of complicatedness and of uncertainty that exists in the supply chain. Collectively, these two dimensions create a two-by-two framework that defines supply chain complexity and provides a strong theoretical basis for linking different aspects of complexity to delivery performance. An exploratory empirical investigation using an international database focused on immediate upstream and downstream echelons of a supply chain at the firm level. Results show strong support for the linkages between delivery performance and both complicatedness of the product/process and uncertainty of the management systems. In contrast, little evidence was found that greater product variety and more complicated supply networks adversely affected performance. Thus, management initiatives to improve delivery performance are best focused on improving informational flows within the supply chain and leveraging new process technologies that offer flexibility to respond to uncertainty.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it