Bibliographic record
Abstract
The purpose of this dissertation is twofold: (1) to examine the extent of integration and implementation of corporate sustainability (CS) into supply chain management (SCM) practices in corporations; and (2) to provide a basis for improved supplier selection with respect to sustainability criteria. Three interrelated research objectives were developed to achieve the purpose: (1) explore the extent to which CS principles are integrated into SCM in corporations; (2) investigate how sustainable supply chain management (SSCM) has evolved in corporations; and (3) develop a model to integrate the environmental and social criteria of CS into supplier assessment and selection. The dissertation is comprised of three main phases corresponding directly to the research objectives stated above. Canada is used as a case study to achieve this goal. Consequently, the first phase explores the extent to which CS principles are integrated into SCM in Canadian corporations. The study includes a primary content analysis of 100 Canadian corporate sustainable development reports (CSDRs) and in-depth interviews with thirty Canadian experts on SSCM. The second phase investigates how SSCM has evolved in Canadian corporations over a five-year period. The study is based on a sequential content analysis of 26 CSDRs to compare the findings with the results from the primary content analysis from Phase 1. The third phase aims to develop supplier assessment and selection models based exclusively on the environmental and social criteria of CS. This phase employs case studies of two major Canadian companies to develop a sustainable supplier selection model. The dissertation makes numerous contributions to the SSCM field. Taken together, Phase 1 and Phase 2 provide a holistic perspective for a range of interrelated criteria on SSCM; provide corporations and other supply chain partners with opportunities to learn from the best practices and shortcomings of the integration of CS practices into SCM; and encourage thinking and discussion into how the key gaps in the theory and practice of SSCM might be addressed. Phase 3 provides SCM professionals with a contingency-based, effective, and practical bespoke modeling approach to supplier assessment and selection within the context of SSCM.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".